Copyright: Copyright 2004, Tom Hall


BioEdit Help Contents

This is the current help file for BioEdit version 7.0.0.

Copyright ©1997-2004

Tom Hall

Ibis Therapeutics, a division of Isis Pharmaceuticals, Inc.

BioEdit is a free program and comes with a disclaimer:

 DISCLAIMER:  This software is provided as is.  There are no warranties, express or implied.  The author will not be held responsible for any problems.  This software may be

freely distributed, provided that the original full installation is distributed along with this documentation and the license agreement.

That aside, if you have any questions or problems, you may email Tom Hall at:  thall@isisph.com.

This file was last updated on 6/1/2004.

I would like to thank Isis Pharmaceuticals, Inc for generous support to the Brown lab (James W. Brown, NCSU) for additions to BioEdit version 5.0.0 and for employment thereafter.

About BioEdit

Introduction

BioEdit v7.0.0  features

General overview of program and program organization

Known problems / Limitations

Contacting the Author

General use of BioEdit

Sequence Editing / manipulation

Basic editing – selecting, sliding, edit box, on-screen editing

Basic manipulations / Sequence Menu

Customizing the view

Customizing menu shortcuts

Splitting the window view

Sorting sequences

Feature annotations

Sequence groups or families

Verbal confirmation of sequences

Valid residue characters vs. non-residue characters

Locking a sequence to prevent accidental edits

Anchoring a column

Comments

Phylogenetic Tree Viewer

Importing Phylogenetic Trees into an alignment

File formats

File formats that BioEdit currently reads and writes

Saving sequence annotation information

ABI autosequencer files

Reading files in a Macintosh program

Toggling between nucleotide and protein views

Printing

Exporting as raw text

Exporting as rich text

Shaded graphic view of alignment

Restriction Maps

Restriction Enzyme Browser

Codon tables

Six-frame translation

Plasmid drawing

Minimizing an alignment

Searching functions

Conservation plot view

Basic Analysis Tools:

External Accessories

    Installing TreeView

    Configuring and Using External Applications

        Adding and configuring a new application

        Modifying an existing application configuration

        Removing an accessory application

        Storage of the configuration information

        An example: Configuring ClustalW to run through a custom BioEdit interface

BLAST

    Local BLAST

    Creating a database

    Local BLAST searching

    BLAST Internet Client

   ClustalW

    Using World Wide Web tools

Automated links

    Restriction mapping

    BLAST

    PSI-BLAST

    PHI-BLAST

    Prosite pattern and profile scans

    nnPredict protein secondary structure prediction

 	Other links

    ENTREZ and PubMed

    Pedro’s BioMolecular Research Tools

    Constructing World Wide Web bookmarks for BioEdit

Incorporated into BioEdit

    Amino Acid and Nucleotide Composition

    Entropy Plot

    Hydrophobicity Profiles

    Identity Matrix

    Nucleotide translation with codon usage

    Positional nucleotide numerical summary

    Search for conserved regions of an alignment

    Dot Plot of two sequences

    Pairwise sequence alignment

    RNA comparative analysis

    The basis of phylogenetic comparison

    Covariation

Using Covariation in BioEdit

   List output

   Table output

Covariation analysis preferences

The covariation algorithm

    Potential Pairings

Using Potential Pairings in BioEdit

   List Output

   Table output

Potential pairings analysis preferences

The potential pairings algorithm

    Mutual Information

        General Overview of mutual Information

        Mathematical Overview of Mutual Information

        Using Mutual Information in BioEdit

        Mutual Information Example

        Setting Mutual Information Preferences

        Using the Matrix Plotter for Mutual Information Data

       1-D plots of matrix data rows and columns

The Mutual Information Examiner

    Using Masks

    Setting preferences for BioEdit analysis tools


Introduction

BioEdit version 7.0.0

Copyright ©1997-2004

Tom Hall

Current version built 6/1//2004

BioEdit is a biological sequence editor that runs in Windows 95/98/NT/2000/XP and is intended to provide basic functions for protein and nucleic sequence editing, alignment, manipulation and analysis.  BioEdit is not a powerful sequence analysis program, but offers many quick and easy functions for sequence editing, annotation and manipulation, as well as a few links to external sequence analysis programs.  Sequence lengths and numbers are limited only by available system memory.  Alignments >100 Mb have been edited on an average desktop with reasonable efficiency.  The document interface was originally modeled after the very nice programs SeqApp and SeqPup by Don Gilbert.   SeqApp (Macintosh) and SeqPup (cross-platform) are offered free of charge from Indiana University at:

ftp://iubio.bio.indiana.edu/molbio/seqpup/

An exceptional alignment program that is freely available for Windows 95/98/2000 is called GeneDoc.  GeneDoc is very professional and has nice protein alignment annotation and analysis, shading and structural definition features not offered in BioEdit, as well as an internal phylogenetic tree view of alignments.  GeneDoc can also be found on the World Wide Web:

http://www.psc.edu/biomed/genedoc/


BioEdit Features

The main goal of BioEdit is to provide a useful tool for biologists who do not want to have to know much about a program to utilize it.  BioEdit is intuitive, menu-driven, and highly graphical and offers a graphical interface for users to run external analysis programs.  The main functions are intended to be visible by simply playing with the menu options.

Version 7.0.0 offers the following features:

•	An easy, graphical interface for sequence manipulation and editing.

•	Variable editing options, including ‘select and drag’ sliding and 'grab and drag' sliding of residues, variable selection options, mouse-click insert and delete of gaps, full column selecting, on-screen editing with cut, copy and paste, and auto-scrolling of edit window.

•	Split the window vertically or horizontally to manipulate two regions of an alignment at the same time.

•	Collapse multiple columns of an alignment to hide them on the screen.

•	Anchor alignment columns to protect fixed regions in an alignment.

•	Automatically and manually annotate sequences with features such as introns, exons, promoters, CDS, and all standard GenBank feature types.  Automatically annotate other sequences in an alignment using one sequence as a template.

•	Download sequences into an alignment document directly from GenBank.

•	Group sequences into color-coded families and lock group members for synchronized hand-alignment.

•	User-defined character-relevance (any characters can be set to be considered as relevant bases in nucleic acid or amino acid sequences for the purposes of similarity shading, sequence identity matrices, and conservation plot views.

•	User-defined motif searching using standard Prosite nomenclature and utilizing IUPAC characters to allow searching in nucleic acid or amino acid sequences, as well as exact text searches including or ignoring gaps.

•	Lines may be defined as DNA, RNA, nucleic acid, protein, undefined, comments, sequence mask (basically the same as comments) or RNA structure mask.  Comments may be used to hold general notes or things such as secondary structure mask definitions, but do not contribute to conservation calculations.

•	Configure accessory application interfaces to run external analysis programs through a graphical interface created by BioEdit.  Automatically feed information to and retrieve files from external apps.  External apps run in a separate thread to allow simultaneous use of BioEdit while running time-consuming processes.  Output from an external program may be automatically opened by another program.

•	Merge alignments through a common reference sequence.

•	Append one alignment to the end of another

•	Rudimentary phylogenetic tree viewer that supports node flipping and printing.

•	Display, print and edit ABI trace files from ABI autosequencer model 377, 373, and 3700, as well as SCF files of version 2 and 3, such as the files output by Licor sequencers.

•	RNA comparative analysis tools, including covariation, potential pairings, and mutual information analyses.

•	2-D matrix plotter for mutual information output with dynamic data viewing with the mouse pointer. (Also allows image copy/paste and bitmap save).

•	Interactive 1-D plots of mutual information matrix rows and columns.

•	Color RNA secondary structure by base-pairs based upon a structure definition mask.

•	Save sequence annotation information in BioEdit or GenBank format

•	Align protein-encoding nucleic acid sequences through amino acid translation.  Slide residues in toggled hybrid protein-DNA translations by toggling translation of annotated CDS features.

•	Search for conserved regions in an alignment (find good PCR targets or help define motifs)

•	Search for user-defined motifs in nucleic acid or protein sequences or search exact text with wildcards and choice of including or ignoring gaps.

•	Dynamic memory allocation.  Alignment size, number and length of sequences are limited only by avalailable memory.

•	BioEdit currently reads and writes GenBank, Fasta, NBRF/PIR, Phylip 3.2 and Phylip 4 formats and reads ClustalW and GCG formats.

•	Import/Export filter for 10 additional formats (Using Don Gilbert’s ReadSeq).

•	Import/Append one file on to the end of another (regardless of file format).

•	Read and write large alignment files quickly with the BioEdit Project file format.

•	ClustalW multiple sequence alignment (interface internal, external program by Des Higgins et. al.) with auto-update of aligned protein full titles and GenBank field information, as well as nucleotide coding sequence when aligned from a protein view of nucleotide sequences.

•	Block copying of residues or sequence titles to clipboard allowing for pasting of full alignments or parts of alignments into a word processor or spreadsheet.

•	Paste over blocks of sequence or sequence titles.

•	Basic sequence manipulations (copy/paste of sequences between documents, translation and degenerate encoding, RNA->DNA->RNA, reverse/complement, upper/lowercase).

•	Multiple document interface  (Maximum of 50 open alignment documents at a time, but no set limit on other open windows).

•	Six-Frame translation of nucleic acid sequences into Fasta-format ORF lists.  Tested by translating the E. coli genome (4.6 Mbases) into 10,125 sorted raw codon stretches of 100 or more amino acids and 39,880 unsorted raw codon stretches of 50 or more amino acids.

•	Semi-automated plasmid/vector drawing and annotation with vectored graphics, automatic restriction site and positional marking, automated polylinker view, and user-controlled drawing objects

•	Save plasmid files as editable vectored graphic files or as bitmaps, copy to other graphics applications, and print plasmids at printer’s full resolution.

•	Amino acid and nucleotide composition summaries and plots

•	'Revert to Saved' and 'undo'/’redo’ functions (up to 30 undo levels allowed).

•	Edit both amino acid and nucleic acid sequences.

•	Easy point-and-click color table editing, with different tables for protein and nucleic acid sequences.

•	Alignment-responsive shading based on information content of alignment positions.

•	Basic rich-text editor.

•	Internal restriction mapping utility with any or all-frames translation, multiple enzyme and output options, including enzyme suppliers, and circular DNA option.  Annotate sequences with restriction sites, fragment sequences with exact monoisotopic mass calculation of all resulting fragment strands.

•	Browse restriction enzymes by manufacturer, or choose enzymes by properties or from a list.

•	Auto-linking to your favorite Web Browser (e.g., Netscape or Internet Explorer).

•	World Wide Web Bookmarks.

•	NCBI BLAST tools, including BLAST 3.0 Internet client and local BLAST with the ability to compile local databases from Fasta files

•	Configurable formatted text print with dynamic print preview,

•	Configurable formatted shaded graphical output with dynamic preview, identity and similarity shading, and ability to cut and paste directly to graphics/presentation program for generation of figures.

•	Entropy (lack of information) plotting of alignments

•	Hydrophobicity profiles of multiple proteins using several hydrophobicity scales, with variable window width and option to analyze degapped sequences or alignments.

•	Retain data from GenBank files, including LOCUS, DEFINITION, ACCESSION, VERSION, PID/SID, SOURCE, DBSOURCE, FEATURES, KEYWORDS, REFERENCE, FEATURES and COMMENT.

•	Add table-based taxonomy data, as well as the NCBI-defined semicolon-delimited phylogeny string.  Automatically map Bacterial phylogenies to a columnized phylogeny table.  Map other phylogenies to your own curated phylogeny table.

•	A variety of search functions, including all GenBank fields and phylogeny table.

•	A variety of title search functions including a flexible search and replace using wilcards.

•	Several sort functions, including phylogeny-based sorting.

•	Calculate exact monoisotopic masses for DNA and RNA molecules.

•	Rudimentary FTICR mass-spec data viewer foir BRUKER FTICR acqus+fid data files.

•	Calculate oligo Tms with oligo/target mismatches based on mismatch parameters from John SantaLucia’s lab.

•	Automatically grab Pubmed references associated with sequences directly from the web (requires Internet Explorer as an ActiveX component).

•	Multiple levels of undo (up to 30), with more complete coverage of undoable operations (all should theoretically be undoable, but there have been some oversights in previous versions).


Contacting the Author

The author can be reached at:

Tom Hall

Ibis Therapeutics, a division of Isis Pharmaceuticals

1891 Rutherford Road

Carlsbad, CA  92008

760-603-2375

thall@isisph.com


Program Limitations
Known problems / Limitations

BioEdit is intended to be a general-purpose interface for several simple sequence manipulations, general alignment of sequences with an option for automated multiple alignment, optimal pairwise alignment, and an emphasis on making hand alignment easy.  Several accessory functions have been added over time (plasmid drawing, restriction mapping, ABI and SCF viewing, RNA comparative analysis and graphical annotation among other features).  However, sophisticated search functions, specialized analyses such as protein secondary or tertiary structure predictions, thermodynamic predictions of RNA structure, statistical analyses of alignment quality, and probabilistic or neural network modeling of sequence patterns, alignment and structure prediction are outside the scope of this program.

Although command-line accessory applications may be configured by the user, there are programmed links to ClustalW and local BLAST and BLAST client 3.  These links are not guaranteed to work correctly if the Clustal program or BLAST programs are replaced with an upgrade.  Although the local BLAST and Clustal programs provided in the BioEdit installations will continue to work, BLAST client 3 may not work correctly after the next time the NCBI decides to change its client and I am no longer supporting this program directly.  The source code may be offered for download at a later date, but is somewhat disorganized, not well commented, and really constrained to Borland C++ Builder (which is the main reason I don't bother to post the source code).

Also, automated web links which feed a selected sequence to the web page (e.g. for BLAST, PSI-BLAST, PROSITE profile scan) work by keeping a local HTML template for the web page, the source for which BioEdit edits to include the selected sequence within the query text area.  Because of the highly mutable nature of the World Wide Web, these may not function correctly for very long.  If the server addresses change, or the HTML interface changes substantially, these will no longer work correctly.  They can possibly be updated by placing the newer web page locally into the BioEdit/apps folder under the same name as the current ones, but whether they work correctly will depend upon whether necessary URL references in the web page are specified as absolute or relative paths, and whether they depend on calling local CGI or Java programs, and other such potential problems.

The interface to configure command-line analysis programs does its best to be as complete as possible without requiring a complicated general-purpose scripting language.  Because of the static nature of this interface and its options, however, there will be programs that just cannot be run correctly through BioEdit, though most programs that accept a command line should be able to be configured.  Many people may prefer to run a program from the command line for better control of the options, anyway.  The accessory application configuration is mainly intended for labs that want to be able to set up an easy method for several people who grew up on easy GUI interfaces to be able to run routine analyses without having to navigate the files and command-line options manually.

Every alignment is loaded completely into memory for editing.  Very large alignments will use a large amount of memory.


Basic Editing
Basic editing – selecting, sliding, edit box, on-screen editing

Manual alignment: Selecting and sliding residues / speed buttons

Editing in an edit box

Windowshading

Adding a new sequence

Editing on screen

Selecting sequences

Moving sequences

Deleting sequences

Cut/Copy/Paste

Minimizing an alignment

Searching functions


Manual alignment of sequences
Manual alignment of sequences (and button summaries)

Below is an image of the basic BioEdit alignment document window.

Don’t worry if you don’t like the current view.  The font, size, background color, residues colors, and title window width may all be changed.  The yellow box to the lower right of the mouse arrow shows the absolute position in the current sequence.  This also appears in the “Position” caption on the control bar, and the option to shut off the yellow boxes is found under

View->show sequence position by mouse arrow.

The general manual alignment functions are:

0	There are three basic modes available in the edit window:

1	These options may also be found under Sequence->Edit Mode

2	Select / Slide mode:  Select residues by boxing them with the mouse (left mouse button).  Drag the selection back and forth with the mouse.  The default is to “crunch” unlocked gaps in the direction you are sliding and open new unlocked gaps on the other side of the selection.  To move the entire sequence downstream of the selection, regardless of gaps, hold down the shift key while dragging.  You may also toggle the appropriate button on the buttons panel (see below) to change the default to moving the entire sequence downstream of the selection.  With this option selected, use the shift key to “crunch” unlocked gaps when sliding.

3	Using the shift key while selecting will select all residues between the current selection and new selection.  The CTRL key allows you to add only the new selection to the current selection (for instance, you may want to select residues in three sequences which are not right next to each other).

4	Edit mode:  When in edit residues mode you may place the cursor anywhere in the document (except the titles) and type.  You may move around between sequences with the arrow keys.  There are two basic modes of editing, as in a word processor: insert and overwrite.  When the editor is in "Edit" mode, a choice will be visible to the right of the edit mode drop-down:

5

6	When in the other two alignment modes, this choice will not be visible.

7	Grab & Drag mode:  Choosing “Grab & Drag” from the “mode” list or toggling the “G/D” button (see below) allows you to grab and drag a single residue dynamically on the screen.  Use the shift key to move the entire sequence downstream of the residue (or toggle the appropriate button on the buttons panel  -- see below).

8	Grouping of sequences:  Sequences may be grouped into groups (or "families").  The alignment for a group of sequences may be locked together, meaning that hand adjustments (insertion and/or deletion of gaps by sliding residues) will be automatically synchronized for a locked group.  This only applies to sliding resides (Select / slide mode or Grab & Drag mode), not to single insertions and deletions of gaps with right mouse clicks.  For information on grouping sequences and locking the alignment of groups of sequences, see grouping sequences.

9	  Tool Bar/Speed buttons:

10	  Lock and unlock all gaps in the entire alignment (shows all unlocked position).  When an alignment is opened, this button is in the unlocked state, but gaps are present however they were saved.  Changes are only made each time this button is pressed.  To unlock all gaps in a current alignment, you must press this button twice to toggle it back to this state ( the first press will lock all gaps).

11	  Locked state of above button.

12	  When down, allows you to insert single gaps by right-clicking the mouse.

13	  Delete gaps by right-clicking the mouse.

14	  Insert gaps in all sequences except the one clicked on with the right mouse button.

15	 Delete gaps in all sequences except the one clicked on with the right mouse button.  Sequences that do not have a gap at the selected position will be unchanged, but the gap will still be removed from any sequences that have one there.

16	  Reverses the default functions of the left and right mouse buttons

17	  Toggle “Grab & Drag” mode.

18	 When this button is down, the default when sliding residues is to crunch or expand downstream gaps.  Use the shift key while sliding to reverse this.

19	  When this button is down, the default when sliding residues is to move the entire sequence downstream of the selection, rather than crunching or expanding gaps. Use the shift key while sliding to reverse this.

20	  Normal view mode.  When sequences are viewed in color, residues are colored according to the current color table.  This option must be chosen to view sequences in monochrome.  All other views override monochrome viewing.

21	  Inverse color view mode.  Background boxes are shaded according to the color table for each residue.  Residue colors are the inverse of their normal colors.

22	  “Strength of Alignment” -- Residues are shaded in grayscale according to the information content at each column position.

23	  Residue backgrounds are shaded according to the information content at each column position.

24	  Shade residues by identity and similarity in the document window.  When this button is down, a drop-down list will appear on the control bar which controls the percent threshold for shading. The matrix file used for similarity shading of protein alignments can be specified from the Alignment->Similarity Matrix menu.

25	  Draw features with sequences superimposed over them.

26	  Draw features only.  Do not show sequences.

27	  View sequences in color, according to the current color table.

28	  View sequences in monochrome, according to the currently selected sequence color.  This mode only applies if the “normal view” button is also down.

29	  Show identities to a reference sequence (default = top) with a character (default = '.').

30	  This drop-down allows for selection of the character to plot identities with, provided that the previous button is active (depressed).

31	  Show or hide the mutual information examiner (for RNA analysis only).

32	  Brings up the color table edit dialog.

33	  Toggles “ignore anchor points” mode.  When this is off (the button is not down), column anchors restrict the range of alignment.  When this button is down, column anchors are ignored.

34	 Scroll speed controller:  controls the speed of the horizontal scroll bar (scrolling is in increments of residues).

  Add or remove a positional marker flag.

0	  Add or remove a column anchoring point.


Editing in an Edit Box

To make major edits to a sequence, it may be convenient to edit it in a text window.  To open an edit window for a sequence, either double-click on the sequence title, or select the sequence and choose “Edit Sequence” from the “Sequence” menu.  For changes to take effect, the “Apply” or “Apply and Close” button must be pressed.  Canceling will cause no change in the sequence.  The following window will appear when a sequence is first opened for editing.

In the "Sequence Type" drop-down, the following options are available.  If a sequence is "unknown", the protein color table is used for coloring, and it is treated like a protein sequence for the purposes of similarity shading.

A "comment" may be reserved to hold information on the screen at any line in the alignment, but does not contribute to calculations of similarity and identity, and is not subject to the standard manipulations such as translation, complementing, automatic alignment, etc.

You may choose to lock any sequence with the "lock sequence" option within the single sequence editor.

When this option is applied, editing on screen and hand alignment by selecting/dragging or grab and drag will be disabled.  Adding and deleting of gaps by right mouse clicks will still be enabled, however.

To expand the window to see associated GenBank information, press the [image] button

The window will expanded as follows:

The [image] button may be used to bring up the associated field in a larger edit window.

**  Note: GenBank information will only be saved in GenBank or BioEdit format

***Note:  GenBank information, including the "features" field, is internally independent of user-defined graphical annotations.


Windowshading

A document may be “Window shaded”, that is, reduced to its title bar, by double-clicking on the title bar of the window.  Double-clicking again will bring it back to its original size.  It can also be  minimized and maximized in the normal manner.  This is not a useful feature, and in fact acts more like a bug, but is simply a hold-over from the original pre-distribution of BioEdit (called AlignSeq) that had independent windows on the desktop for each document window rather than a multiple-document interface.


Adding a new sequence

A new sequence may be added by:

1. Selecting the “New Sequence” option under the “Sequence” menu.  The sequence may be typed, or copied as raw text, into the sequence window.  Press “Apply” to add the sequence to the document.

2.  Sequences may be copied and pasted from other BioEdit documents with the “Copy Sequence(s)” and “Paste Sequence(s) commands from the “Edit” menu.  Also, current menu shortcuts may be used (defaults: Ctrl+F8 for copy and Ctrl+F9 for paste).


Editing on screen

Sequences may be edited on screen much like working in  a word-processor.  The “Mode” option of “Edit Residues” must be set first (BioEdit is installed with the “Slide Residues” mode as the default).

1	When in edit mode, you may use the arrow keys to move around on the screen and type as in a text editor.  There are two options for editing:  Insert mode or overwrite mode, that each behave as the analogous functions in a common word-processor.


Selecting Sequences

Sequences are selected by clicking on their titles.  Multiple sequences may be selected by drawing a box around them, or by shift-clicking to select everything between two selections.  Use the Ctrl key with the mouse to de-select selected titles, or to add specific titles to the selection.  Double-clicking on a title will open the single sequence editor.  Clicking again on a previously selected title will put it into on-screen editing mode.  You may then edit the title and either press <return> or click the sequence title panel anywhere off of the current title for the change to take effect.


Moving Sequences

To move a sequence (or sequences), select it (highlight its title by clicking it with the left mouse button) and drag it to where you would like it in the alignment.


Deleting sequences

To a delete a sequence or sequences, select their titles on the left panel by drawing a box around them with the mouse or Shift-clicking or Ctrl-clicking on the titles, then choose “Delete sequences” from the Edit menu.  Note that this is a different operation from “Delete”, which is reserved for sequence residues.


Cut, Copy and Paste
Cut/Copy/Paste

Copy:

Text in edit window (sequence residues): Select the text with the mouse and choose “Copy” from the “Edit” menu.  Unlike a word processor, you may copy discreet blocks of text without copying entire lines of text.  A block of text copied this way may be pasted into any text edit-capable program.

Entire sequences: Select the sequence title(s) with the mouse and choose “Copy Sequence(s)” from the “Edit” menu.  Sequences whose titles are selected will also be copied to the Windows Clipboard in Fasta format.  More than one selected sequence will be copied to the clipboard as a Fasta sequence list, and copied internally within BioEdit as a group of full BioEdit sequence structures that can be pasted into any BioEdit document.

Note:  The BioEdit "clipboard" which contains all sequence-related data (GenBank information, graphical annotations) is internal to a single instance of BioEdit (they cannot be transferred between independent processes).  To copy sequences between BioEdit alignment documents, make sure to have both documents open within the same instance of the program, as only Fasta-formatted sequences are copied to the general Windows clipboard.

Copy sequence titles:

Copies selected sequence titles to the Windows clipboard as plain text.

Paste:

Text in edit window: To paste into a sequence within the main edit window, the interface must be in “Edit Residues” mode (see Editing On Screen).  If a block of text is pasted into a sequence, only the first line (defined by a carriage return) will be pasted in.  This is to avoid possible problems with pasting text into one sequence and inadvertently corrupting sequences below it.  To paste segments of text into a block of an alignment, segments must be pasted into sequences one at a time.  If the document is in “Slide Residues” or “Grab and Drag” mode, then Paste will behave the same as Paste Sequence(s) (see below).

Entire sequences: From the menu of the document to paste sequences into, choose “Paste Sequence(s)” from the “Edit” menu.  The sequence(s) will be added to the end of the document.  They may be then be moved to somewhere else within the alignment.

“Cut” and “Cut Sequence(s)”: Same as “Copy” and “Copy Sequences”, but deletes copied information from document.  Residues are only deleted from the document if “Edit Residues” mode is active, however.  Also, when Cut is used when no residues are selected in the document, sequences whose titles are selected are copied to the BioEdit Clipboard as sequence structures and to the Windows Clipboard in Fasta format, but they are not deleted from the document.  To properly cut sequences from a document, choose “Cut Sequence(s)”.

0aste over:  Pastes a block of text from the windows clipboard over an existing region of an alignment document, replacing any text that is currently there.  If there are more lines on the clipboard than existing sequences, new untitled sequences will be created with gaps placed at all positions preceding the paste point.


Minimizing an Alignment

When an alignment is manipulated and tweaked extensively by hand, and when sequences are periodically added to an existing alignment and aligned manually, gaps often result which are present  throughout a column in every sequence.  To remove gaps that don’t change the actual alignment, simply choose “Minimize Alignment” from the “Alignment” menu.

 The menu item “Minimize alignment to mask” minimizes the alignment to only non-gap positions present in a mask sequence.


Sequence Menu
Basic Manipulations / Sequence Menu

There are a few simple sequence manipulations which can be done automatically with BioEdit with a single menu option.  These options are found in the “Sequence” menu.

Masking in BioEdit is at this point a little weak, and is provided mainly for use with the RNA comparative analysis functions.  For an explanation of how BioEdit uses masks, see Masks.

Gaps:

Lock and unlock gaps: A locked gap will not be compressed when residues within a sequence are slid.  To lock gaps, select the gaps to be locked and choose “Lock Gaps”.  To lock all gaps in a sequence, select the sequence title, then choose “Lock Gaps”.  To lock all of the gaps for an alignment, toggle lock/unlock button to the locked state:

0

1	Unlocking gaps is just the reverse of locking them.  To unlock all gaps in an alignment, toggle the locked/unlocked button to the unlocked state:

2	The “Degap” option will remove all selected unlocked gaps.  It will also remove and all unlocked gaps from sequences whose titles are selected.

3	Note:  '~' and '.' (tilde and period) represent unlocked gaps, and '-' (dash) represents a locked gap.  These conventions are used throughout every window and function in BioEdit.  A period is never produced by BioEdit to represent a gap character, but is treated as a type of gap for computability with programs that prefer this character.  Also, some programs may use a period to represent alignment positions that are neither residues nor gaps, but simply fill alignment slots before the beginning or after the end of a sequence.  BioEdit does not directly pay attention to this distinction.  Positions before or after a sequence's range are treated as gaps and BioEdit assumes each alignment consists of truly homologous sequences (although BioEdit is also designed to allow the user to ignore the alignment focus of the program and use it simply to manipulate lists of sequences).

0	Sequence Menu  (excluding the “mask” functions)

1	New Sequence:  Create a new sequence.  This opens up the single sequence editor

2	Edit Sequence:  Opens the first selected sequence in the single sequence editor

3	Edit all selected:  Allows a few things to be changed for a set of sequences simultaneously.

4	Select Positions:  Opens a dialog that allows selecting of specified positions in all selected sequences.

5	Open at  cursor position:  If the document is in edit mode, and the cursor is showing, this option will open the sequence with the cursor at the cursor’s current position in the single sequence editor.

6	Extract positions:  Extracts indicated positions from selected sequence and creates new sequences from the extracted residues.  If the sequence(s) is/are nucleotide, and the coordinates are imput backwards, then the extracted sequence(s) is/are reverse complemented.  To extract positions from a sequence, enter two coordinates per line separated by a tab (or any non-digit character) in the dialog box that comes up when the Extract positions menu is activated.  Checking the “True positions” box allows you to extract out absolute sequence positions without counting alignment gaps.

7

8	Go to Pubmed references:  Attempts to retrieve pubmed references associated with a GenBank sequence according to the gi number.  If a proxy server is required, this can be set in the preferences dialog.  The gi number is first searched for in the title according to the default GenBank fasta defline format (e.g. gi|16082679|ref|NC_003132.1|), with the gi number being located between two pipe (‘|’) characters.  If no gi number is found in the title, the VERSION field of the genBank records is queried.  Note that the sequence type in BioEdit must match the sequence entry for the pubmed query to work.

9	Overwrite/Retrieve sequences by gi number in title by HTTP to GenBank: Retrieve a sequence from GenBank with GenBank field information directly for all selected titles.  Note that all selected titles must have a valid gi number between two pipe (‘|’) characters immediately preceded by “gi” (no quotes).  If the title does not start with “gi”, there must be a pipe immediately before “gi”.  For example: “gi|16082679|ref|NC_003132.1|”.  If a proxy server is required, this can be set in the preferences dialog.  Note this function will overwrite a sequence, even if it’s the same as the existing sequence, and the new sequence will be ungapped, even if it is aligned prior to using the function.  To only retrieve GenBank information without modifying the sequence, use the next function.

10	Overwrite/Retrieve Genbank data by gi number in title by HTTP to GenBank (ignore sequence):  The same as the previous function, but only returns associated GenBank information (does not overwrite the sequence).

11	True positions from alignment positions:  Convert a list of alignment position pairs into a list of true position pairs for a list of selected sequences.  Pairs of coordinates should be separated by any non-digit character (e.g., a tab) in the following dialog.  The returned list comes up in a text editor with coordinates formatted as two numbers separated by an underscore.

12	Phylogeny / Taxonomy:

13	Extract taxonomy:

By organism name on defline as gi|<gi#>|<organism>| ...:  Extract a (Bacterial only) taxonomy based upon a mapping of the genus species name to a 16-field phylogeny tab-delimited phylogeny file (“<BioEdit>\tables\Bacterial_phylogeny.tab”).  This table can be updated to include any

0	From title, semicolons -delimited:  Titles may be formatted with taxonomy information delimited by semicolons, with the organism name being first, followed by a series of taxonomic groupings separated by semicolons.  For example: Bacillus subtilis;Bacteria;Firmicutes;Bacilli;Bacillales;Bacillaceae;Bacillus;Bacillus subtilis.  Taxonomic headings (phylum, class, order, family, etc.) will need to be added manually. In this case.  In the current example, the headings would be edited in the sequence editor by double-clicking ono the title, expanding the window with the [image] button, then typing the proper headings in the phylogeny table.  If there is a large collection of sequences, and care is taken to ensure a tabular taxonomy level organization, the menu option “SequencePhylogeny / TaxonomyExtract taxonomy  Apply taxonomy headings from first sequence to selected sequences” can be used to replicate the headings down an entire list of sequences.

1	Apply taxonomy headings from first sequence to selected sequences:  Replicates the taxonomy headings from the top sequence in an alignment (or list) to all sequences that are selected.

2	Map from custom master taxonomy file:  Map taxonomy information from selected sequences from a custom phylogeny table.  The full title needs to be the full genus species name (correctly spelled) and nothing more.  The phylogeny table needs to be formatted as tab-delimted text in the same format as “<BioEdit>\tables\Bacterial_phylogeny.tab” or “<BioEdit>\tables\Viral_phylogeny.tab”.

3	Map from master Bacterial taxonomy file:  Map tabular-formatted phylogeny information for Bacteria assuming the sequence title is the genus-species name of the organism.  Mapping information is taken from “<BioEdit>\tables\Bacterial_phylogeny.tab”

4	Map from master viral taxonomy file: Map tabular-formatted phylogeny information for virus assuming the sequence title is the proper name of the organism (according to the NCBI taxonomy web site: http://www.ncbi.nlm.nih.gov/Taxonomy/taxonomyhome.html/.  Mapping information is taken from “<BioEdit>\tables\Viral_phylogeny.tab”.

0	Phylogenetic tree (derived from sequences):

1	Rename:  Rename sequence titles according to a submenu option:

0	Edit title:  Change the title of a sequence on-screen.

1	with LOCUS:  Change all selected titles to the LOCUS field.

2	with DEFINITION:  Change all selected titles to the DEFINITION field.

3	with ACCESSION:  Change all selected titles to the ACCESSION field.

4	with PID/NID:  Change all selected titles to the PID or NID field.

0	Sort:  Sort sequences according to the following criteria:

1

By Title

0	By Locus

1	By Definition

2	By Accession

3	By PID or NID

4	By Reference

5	By Comment

6	By residue frequency in selected columns

0	Pairwise alignment:  Optimal alignment of two sequences

0	Align two sequences (optimal GLOBAL alignment):  Align two sequences optimally with a global alignment algorithm based upon the Needleman and Wunsch optimal alignment method.

1	Align two sequence (allow ends to slide): Align two sequences optimally with a local alignment algorithm based upon a version of  the Smith and Waterman optimal alignment method which does not constrain the ends of either sequence (either sequence end is allowed to slide freely over the other sequence).  This alignment tends to be very useful for quickly identifying overlapping regions of sequence reads in small sequences where an auto-contig assembly program is not required.

2	Calculate identity/similarity for two sequences:  Calculates the identity and similarity (according to the current similarity matrix) for two sequences as they are currently aligned in the document (does not align them).

0	Similarity Matrix (for pairwise alignments and shading):  These matrices apply to amino acid

1	sequences only.  BioEdit does not use any matrix scoring schemes for nucleic acids (only simple identity).

BLOSUM62:  The default matrix used by BLAST.  The BLOSUM matrices are generally good for database searches and assume moderately large evolutionary distances (smaller BLOSUM number = greater evolutionary distance -- only the BLOSUM62 matrix [intermediate] is supplied in BioEdit).

PAM40:  Intended for very closely related sequences (40 PAM units = relatively small evolutionary distance -- in the PAM matrices, large PAM number = greater evolutionary distance).

0	PAM80

PAM120

PAM250:  Intended for more distantly related sequences (larger PAM distance).

IDENTIFY:  Simple match or mismatch matrix with a very large (-10000) penalty for mismatches

DAYHOFF:  Actually a PAM250 matrix -- M.O. Dayhoff's original PAM250 matrix (each value rounded to the nearest integer).

MATCH:  Simple match or mismatch matrix with a -1 penalty for mismatches and a +1 score for matches.

GONNET:  A modified PAM250 matrix recommended by Gonnet (1992).

0	Features (Feature annotation functions):

Automatically annotate from GenBank Feature Fields:  This option allows you to add features according to the pre-existing GenBank data already deposited for the sequence.

Edit Features:  Add, modify or delete features in a sequence.

Annotate Selection:  Add a feature that will span the currently selected positions in all sequences with a selection in them.

0	Annotate selected sequences using the first sequence as a template

0	Sequence groups (or families):  Group and ungroup sequences and edit current groups.

1	Edit Mode:  Sets the current editing mode.  See Manual alignment of sequences.

2	Mask (covered above).

3	Toggle color:  toggles coloring of single sequences.  This is a left-over of an early version and is pretty useless.

4	Gaps:

Lock gaps, Unlock gaps and Degap:  explained above.

0	Insert multiple gaps:  insert a variable number of gaps at the currently selected position in the alignment window.

Manipulations:  Simple manipulations that are independent of sequence type.

lowercase and UPPERCASE: As indicated -- sequences only, not titles.

0	Reverse:  Reverses any sequence

1	Remove numbers:  As indicated.  This was added by request to ease the process of pasting partial sequences from GenBank formatted text files and web pages.

0	World Wide Web:

Automated links are provided to the following selected WWW search functions:

0	      BLAST, PSI-BLAST and PHI-BLAST.

1	Prosite profile and pattern scans

2	nnPredict protein secondary structure prediction

0	Nucleic Acid:

Nucleotide Composition:  Plots nucleotide composition and gives a summary including G+C and A+T percentages and molecular weight

0	Complement:  The complement of a DNA or an RNA sequence.  This option has no effect upon protein sequences, and characters other than the standard five bases (A, G, C, T and U) and  purines/pyrimidines are not affected (the complement of a purine (“R”)  is a pyrimidine (“Y”)).

Reverse complement: Behaves the same as complement, but also reverses the sequence.

DNA->RNA and RNA->DNA: These really do nothing but toggle “T”’s and “U”’s and change the sequence type.

0	Translate:  Translate sequence in frame 1, 2 or 3, or translate the currently selected region of a sequence.  Codons are separated by spaces.  The nucleotide sequence is shown on top of the protein sequence.  The translated sequence is specified by three-letter or one-letter amino acid codes, depending on the preferences.  If a selected part of a sequence is translated sequence is translated, either the entire nucleic acid sequence or only the translated region may be displayed, depending on the current preferences.  A summary table may be displayed below the translation which shows the number of times each codon appears in the sequence, as well as the frequency with which each codon codes for a particular amino acid according to the codon table provided.

1	Find Next ORF:  Searches the currently selected sequences from the point of the last current selection for ORFs according to the parameters defined in the preferences.

2	Create plasmid from sequence:  A DNA sequence may be converted directly into a plasmid/vector.  A restriction map is automatically run on the sequence.  For help on annotating a plasmid, see Plasmid drawing with BioEdit

3	Restriction Map:  Run a restriction map on a DNA or RNA sequence.

Sorted and Unsorted six frame translations:  Translate nucleic acid sequences in all six frames by specifying a start codon (ATG, “any”, or user-defined), and a minimum and maximum ORF size.  Sorted translations are limited to a few thousand output ORFs.  To get a raw translation of entire genome (or larger), use an unsorted translation (in an unsorted translation, the output data is printed directly to a file, and very little memory is required).

0	Protein:

Amino Acid composition:  Gives a plot and summary of the amino acid composition of a protein, including the molecular weight.

0	Hydrophobicity profiles:

Mean hydrophobicity is calculated by the method of Kyte and Doolittle (1982)  using a choice of hydrophobicity scales.

0	Hydrophobic moment is calculated according to the method of Eisenberg et. al., 1984).  The algorithm of Eisenberg et. al. for finding transmembrane alpha helices is not applied here, rather the hydrophobic moment of a user defined segment of sequence is plotted for each residue (each residue represents the beginning of a user-defined segment);

1	Mean hydrophobic moment:  For each residue, the mean hydrophobic moment for a window the same size as that used to calculate each hydrophobic moment is applied.

2	Note:  I do not have the expertise to make any claims about the predictive power of these profile plots.  BioEdit makes no conclusions about hydrophobic and/or transmembrane segments of proteins, and interpretation of these plots is up to the judgment of the user.

3	For a description of the method and meaning of these plots, and references to the hydrophobicity scales and to hydrophobicity analysis algorithms, see Hydrophobicity Profiles.

0	Translate or Reverse-Translate: Translation from DNA or RNA to protein is done according to the codon table specified in the BioEdit.ini file.  The default is “codon.tab” found in the /tables directory.  The default is the  E. coli codon usage table produced by J. Michael Cherry (cherry@frodo.mgh.harvard.edu) with the GCG program CodonFrequency.  Any codon table with this format may be used, but the codon table must be in this format to be recognized by BioEdit.  To choose a different table, see Codon Tables.  A protein sequence will be degenerately encoded (to DNA) based upon codon preference for each particular amino acid.  Obviously, if a nucleic acid sequence is translated to protein and back, information will be lost.

1	Translate in Selected Frame (Permanent):  This allows you to translate a nucleotide sequence as if the currently selected column (defined as the start of a selection if more than one column is selected) is frame +1.  When applied to a protein sequence, it simply results in the same degenerate reverse translation as the above option.

2	Toggle Translation:  Toggles nucleotide sequences between the nucleic acid and encoded protein sequences, allowing for alignment of the sequences in either view.  See Toggling between nucleotide and protein views

3	Toggle Translation in selected frame:  This option allows you to toggle the translated view (without losing any nucleotide information) as if the currently selected column (defined as the start of the selection if more than one column is selected)  was in frame +1.

4	Dot Plot (pairwise comparison):   Create a dot plot of two sequences compared to each other in a matrix.


General overview of program
General overview of program and program organization

BioEdit was written in Borland C++ Builder 3.0 (started in C++ Builder 1.0).  This (was) Borland’s newest C++ product which combines Borland C++ 5 with the Visual Component Library (VCL) of Delphi, allowing for visual development of the user interface.  The benefit of using a Rapid Application Development (RAD) environment such as this is that it allows for the easy creation of a very rich graphical interface.  The drawback is that the code is not portable.  BioEdit runs only in Windows 95, 98, NT and 2000.  I originally planned to port BioEdit to Win16, but I no longer plan to do this, since Windows 3.x is obsolete.

Organization: BioEdit currently supports the simultaneous editing of up to 50 documents.  A main  control form contains menus to open documents, create new documents, set global options such as color tables, codon table, and analysis preferences, and a window manager.  Originally, each document had its own complete set of menus for all manipulations confined to that document, however, this has been abandoned for a more traditional multiple document interface.  BioEdit does not use excessive physical memory (unless big alignments are being edited), but it does appear to be a bit of a resource hog.  BioEdit has a limit of 20,000 sequences per document with no defined limit on sequence size.  On a 233 MHz PC with 80 Mb of RAM, manipulating the entire prokaryotic 16S rRNA alignment from the Ribosomal Database (6205 seqs, 3319 characters each) works fine.  Once saved in BioEdit format, this file opens in only a few seconds (takes a couple of minutes from GenBank format).

The program file (BioEdit.exe) is found in the main installation directory.  There should also be the following subdirectories:

•	apps (accessory applications, Web pages and WWW bookmarks)

Currently, the following files should be in the apps folder (as shown in the file manager sorted by name):

accApp.ini (accApp.def when first installed)

0	Bblast.html

1	BioEdit.html

2	blast_adv.gif

3	blast_form_0.gif

4	blastall.exe (not in the version without BLAST)

5	blastcl3.exe (not in the version without BLAST)

6	blast.txt

7	bookmark.txt

8	cap.doc

9	cap.exe

10	clear_inp.gif

11	clustalw.exe

12	clustalw.txt

13	cutter.html

14	Dnadist.doc

15	Dnadist.exe

16	Dnamlk.doc

17	Dnamlk.exe

18	Dos4gw.exe (needed for PHYLIP programs)

19	Expasy.gif

20	fastDNAml.doc

21	fastdnaml.exe

22	Fitch.doc

23	Fitch.exe

24	formatdb.exe (not in the version without BLAST)

25	IdPlot.exe

26	isrecsmall.gif

27	Kitsch.doc

28	Kitsch.exe

29	mod_ad.gif

30	mod_submit.gif

31	nnpredict.html

32	Note.gif

33	PFSCAN_form.html

34	phi_blast.gif

35	PHIBlast.html

36	Phylip.map

37	Protdist.doc

38	Protdist.exe

39	Protpars.doc

40	Protpars.exe

41	psi_blast.gif

42	PSIBlast.html

43	Readseq.exe

44	ReadSeq.txt

45	scnpsit1.html

46	Siblogo.gif

smweb.gif

•	database (for local BLAST databases, unless the version was installed without BLAST tools).  BioEdit (full version) comes with the following files in the database folder:

Ecoli.phr

0	Ecoli.pin

1	Ecoli.psq

2	Ecoli_ORFs.txt (text file with E. coli open reading frames).

•	help

BioEdit.cnt

0	BioEdit.GID (not installed -- will appear after the first time help is accessed)

1	Bioedit.hlp

•	tables

Blosum62

0	codon.tab

1	color.tab

2	dayhoff

3	defcolor.tab

4	enzyme.tab

5	Gc.val

6	gonnet

7	Identify

8	match

9	Pam120

10	Pam250

11	Pam40

12	Pam80

13	Seqcode.val

The installation folder will also contain the following files:

_deisreg.isr (installation related file)

0	_isreg32.dll (installation related file)

1	BioEdit.exe (BioEdit executable)

      DeIsL1.isu (installation related file)

0	      RNaseP_prot.gb (sample protein alignment

1	      RNaseP_prot_genes.gb (sample DNA alignment)

2	      RNaseP_RNA.gb (sample RNA alignment)

3	      PBSSK_plus.pmd (Sample plasmid drawing)

4	      bacterio.gb (sample protein alignment with GenBank information)

5	      bacterio.bio (sample BioEdit file with GenBank information, graphical annotations, marker

6	                            flags, and sequence groups)

7	      YopD.gb (another sample file with GenBank info)

8	      TreeView.zip (Excellent Phylogenetic tree viewer by Roderic D.M. Page, full installation)

9	      TreeView.txt (Information on installing TreeView and configuring BioEdit to link tree-

10	                              generating accessories directly to it).

11	      license.txt (BioEdit license agreement)

12	      ReadMe.txt (General information)

0	It is important that none of the folder names nor file names are changed, as parts of BioEdit will not run correctly if these names are changed.

1	There will be a file called “BioEdit.ini” found in your main Windows directory which contains the initialization defaults and preferences for BioEdit.  Although this file can be edited manually, there should be no need and manual editing of this file is not recommended.

2	For a list of currently supported features and known problems, see BioEdit Features and Known Problems / Limitations.


Customizing the View

BioEdit currently supports the following view options:

•	Background colors for sequence and title windows

•	Default monochrome sequence and title colors

•	Character fonts.

•	Font size

•	View sequences in bold-face type.

•	View sequences in monochrome or color (editing is faster in monochrome).

•	Normal color view (residues colored)

•	Inverse (background colored)

•	Strength of alignment:  shading is based upon the information contained at each position -- information is calculated as follows:

•	DNA/RNA: information = ln5+Σ(fbx[ln(fbx)])

•	Protein: information = ln21+Σ(fbx[ln(fbx)]),

where fbx represents the frequency of each residue b occurring at position x.  5 represents the number of possible residues for nucleic acid (4 nucleotides plus gaps).  This is not quite right, and the usefulness decreases if a lot of alternative characters are used.  21 represents the number of possibilities for amino acids (including the gap).  ln5 and ln21 are the maximum information for a nucleic acid position or a protein position, respectively and the term

0	-Σ(fbx[ln(fbx)]) represents the entropy (a measure of variability) at the position.

1	The above description was true of BioEdit versions before 5.0.0.  In BioEdit version 5.0.0, only the user-defined valid residues contribute to the entropy calculation.  In this case, gaps only contribute to the calculation of entropy if they are defined as valid residues (or place-holding characters, if you'd rather think of it that way, as it is obvious that a gap cannot be a residue).

•	Strength of Alignment - Inverse:  Same as Strength of alignment, but the background instead of the residue is shaded.

•	Identity/Similarity shading:  Residues are background-shaded with there color-table defined colors if their frequency in a column equals or exceeds a user-defined cutoff (the option to choose the cutoff goes in increments of 10% and is visible when this mode is active).  Nucleotide alignments are shaded according to identity only, while protein alignments are shaded according to identity and similarity according to the currently selected amino acid similarity scoring matrix.  Only characters defined as valid residues and only non-comment sequences contribute to the similarity and identity calculations.

•	Sequences and Graphical Features:  Draw graphical sequence annotations on the document screen with the sequences superimposed on top of them.

•	Graphical Features:  Draw graphical sequence annotations in cartoon mode and do not draw the residue characters.  When this mode is active, there is a scale-factor slide bar toward the top of the window that enables a scaling factor between 1:1 and 1:32768, by orders of 2.

•	Conservation plot:  Residues are plotted as a user-defined character (default = a period) if they are identical to the residue in the same column as a user-defined standard (default = the top sequence).  To change the standard (reference) sequence, right-click the sequence title with the mouse that you want to be the new standard for the conservation plot.  Only characters set as valid residues are recognized for the identity plot.

•	Show or hide the mutual information examiner (this is only useful for RNA comparative  analysis).

•	Show or Hide the translation toggling control.  This is mutually exclusive with the mutual information examiner control, because of space limitations.

•	Show sequence position by mouse arrow:  when moving the mouse over sequences in a document window, the absolute position of the mouse (ignoring gaps) is reported on the control bar above the sequence view window.  The position may also e reported (including the full length of the title) at the mouse arrow.  This option turns this feature on or off.

•	Split window vertically:  A duplicate window is created which sits inside the document window and is synchronized with the current document.  The window is placed such that the document appears to be split by a vertical window splitter (it’s really just two synchronized documents, one with most of it’s interface removed).  The vertical scroll position of the two windows stays in register, but horizontal scrolling in each is independent of the other.  The window may be resized by grabbing the window splitter within the main document.  The window may be returned to normal by choosing this menu option again.

•	Split window horizontally:  A synchronized window is created which is placed directly below the original window such that the border between the bottom of the original window and the top of the new window behaves like a window splitter.  Remove this window by choosing the option again.

•	Save options as default:  When “Auto-update view options” is off, choosing this item will save the view options of the current document as the default for all newly created or newly opened documents.

•	Auto-update view options:  when this item is checked, all changes made to the document views and preferences are automatically saved as the default for new documents.

•	Customize menu shortcuts:  brings up a dialog that allows changing of menu shortcuts to any key combination.

•	Hide control bar or Show control bar:  The main control bar may be removed in order to fit more sequences on the screen in a simple frame window.  If the control bar is hidden, then the “Show control bar” option is offered.   If the control bar is hidden, sequence editing modes may be changed through the Sequence->Edit Mode submenus.  View defaults may be changed via menus as well.

0	To change these settings, choose the appropriate option from the “View” menu of an open document.  To make the current view from any particular document into the default view for all subsequently opened documents, choose “Save Options as Default”.

1	These views may be selected either through the “View” menu or by pressing the appropriate speed button on in alignment window.

2	Color Table: One color table is used for all documents.  This table is called “color.tab” and is found in the \tables directory of the BioEdit install directory (see Program Organization).  Although the table may be edited by hand, it is much easier to use the “Color Table” option under the “Options” menu of the main application control form.

3	Editing the color table: To edit the color table, choose “Color Table” from the “options” menu of the  main application control bar.  There is a different color table for nucleotide and protein sequences.  To change the color of a residue, double-click on the colored box above the residue to get a color dialog.  To add or delete a residue, click the “+” or “-” button.  In the window that appears, push the button for the residue to be added or deleted.  When adding a residue, it comes in with black as the default color.  The color must then be changed to the desired color.

4	To edit the color table by hand, the following format must be observed:

•	Each color table is denoted by a line containing the exact text “/amino acids/” or “/nucleotides/” (without the double quotes).

•	The end of each table is denoted by (exactly) “/////” (without the double quotes);

•	Each residue color is specified by two lines in the file:

•	Line 1: A 3-byte hexadecimal number (or its integer value). The three bytes represent the values for blue, green and red, respectively (backwards RGB).

•	Line 2:  An unbroken list of all characters representing all characters which should have this color.  If a character color is redefined elsewhere in the file, the last occurrence will be the valid one.

0	Note: Manual editing of the color table should not be necessary and is not recommended.

1	If the color table becomes corrupted, it may lead to program failure on startup or when the color table is edited.  If this happens, you may delete the color table and create a new one, one residue at a time  (you will get an error on startup and on choosing “Color Table”, but the program will create a new table when the “Save Table” button is pressed).  This is tedious, so the /tables folder of BioEdit also comes with a file called “defcolor.tab”.  If the color table becomes corrupted, you can make a copy of defcolor.tab and change the name of the copy to “color.tab”.

2


Sequence editing and manipulation
Sequence Editing / manipulation

Basic editing – selecting, sliding, edit box, on-screen editing

Basic manipulations

Customizing the view

0	Customizing menu shortcuts

1	Splitting the window view


File formats read and written by BioEdit

BioEdit v5.0.6 reads and writes the following formats:

•	BioEdit

•	Genbank

•	Fasta

•	NBRF/PIR

•	Phylip 3.2 / 2

•	Phylip 4

•	In addition, BioEdit version 4.7.0 and above will read ABI model 377 autosequencer files.  The sequence is extracted and the trace is displayed on the screen and may also be printed in color.  BioEdit version 4.7.7 and above allows editing the editable sequence.  The current version also reads SCF trace files (versions 2 and 3), and ABI 373 and 3700 files.

•	BioEdit 4.7.7 and above also read both ClustalW and GCG-formatted files, but it does not write them.

0	In addition to these formats, an external input/output filter (Don Gilbert’s ReadSeq) is provided, allowing for the import and export of the following formats:

•	IG/Stanford

•	EMBL

•	GCG (single sequence only)

•	DNAStrider

•	Fitch

•	Zuker (import only)

•	Olsen (import only)

•	Plain or raw (single sequence only)

•	PIR/CODATA

•	MSF (multiple sequence format)

•	ASN.1 (NCBI)

•	PAUP/NEXUS

0	Documentation for the ReadSeq utility can be found in the file ReadSeq.txt in the /apps folder of the BioEdit installation directory.  Use of this utility within BioEdit is automatic when opening sequences.  If a file is opened which is not one of the formats read by BioEdit, you be prompted to try to open it with ReadSeq. If ReadSeq can open it, it will be imported into BioEdit as a GenBank file, otherwise it will be opened as text.  To save a file in one of these formats, choose File->Export->Sequence alignment from an open document.


BioEdit format
BioEdit Project File Format

BioEdit provides a specialized binary alignment format for very fast opening and saving of large alignment files (20 Mb+ file sizes -- even up to 100 Mb or larger).  Reading and figuring out raw text becomes very slow in large alignments of formats such as GenBank, where there is no header telling the program how may sequences there are or how big they are.

The structure of a BioEdit Project file is as follows:

•	Header

1.	offset 0x00000000:  the string “**BioEdit Project File**” identifies the file as a BioEdit Project file (first version).

1.	The string “**BioEdit Project File02” at offset 0x00000000 identifies the file as version 2 of the BioEdit format (the current version).  Previous versions of BioEdit will not read the current BioEdit format, but BioEdit v5.0.0 or above will read the old BioEdit format.

1.	offset 0x00000018:  the number of sequences in the file.

1.	offset 0x0000001C: the index of the mask sequence (if there is one).

1.	offset 0x00000020:  the index of the numbering mask (if there is one).

•	Offset 0x000000C8:  The offsets for each sequence data structure.

0	Each sequence structure consists of a title, a sequence, the sequence type, and all of the same GenBank fields included with a GenBank file in BioEdit.  In addition, in BioEdit v5.0.0 or above, graphical sequence annotations, sequence grouping information, consensus sequence information, sequence locking status, and positional flags are saved.   In BioEdit version 5.0.4 and above, column anchor information is saved.  In BioEdit version 5.0.6 or above, phylogenetic tree information is also saved.  None of these latter additions are saved in any of the other, standard, formats  Each field is preceded by a long integer specifying the length of the data, so each piece of data may be read from the file as a single chunk, which allows a file to be read very quickly.


GenBank Format

GenBank files written by BioEdit have the following minimal format:

LOCUS       Escherichi       119 amino acids

0	DEFINITION  Escherichi     119 amino acids

1	ORIGIN

2	     1	 MVKLA FPREL RLLTP SQFTF VFQQP QRAGT PQITI LGRLN SLGHP RIGLT

3	     51	 VAKKN VRRAH ERNRI KRLTR ESFRL RQHEL PAMDF VVVAK KGVAD LDNRA

4	     101  LSEAL EKLWR RHCRL ARGS

5	//

6	LOCUS       Proteus_mi       119 amino acids

7	DEFINITION  Proteus_mi     119 amino acids

8	ORIGIN

9	  1	 MVKLA FPREL RLLTP KHFNF VFQQP QRASS PEVTI LGRQN ELGHP RIGLT

10	  51	 IAKKN VKRAH ERNRI KRLAR EYFRL HQHQL PAMDF VVLVR KGVAE LDNHQ

11	  101  LTEVL GKLWR RHCRL AQKS

12	//

etc...

0	The LOCUS, DEFINITION and ORIGIN keywords are looked for in detecting GenBank files.

1	GenBank files may also contain additional information.  The following fields may be included in any GenBank sequence entry, and are looked for when opening a GenBank file:

2	LOCUS:  The locus of the sequence (often the position in the genome).  This field is generally a single line and contains the Locus name, length of the sequence, and often the date of submission.  Previous versions of BioEdit used the LOCUS as the sequence title.

3	DEFINITION:  A description the sequence, usually one-line.  The definition field is used as the default title in the absence of a BioEdit-specific “TITLE” field.

4	TITLE:  This is a BioEdit-specific field and should be ignored by other programs that read GenBank format.  The title field allows you to save sequence titles that are different from either the LOCUS or DEFINITION field entries.  This is included so that user-defined titles may be given to sequences downloaded via Entrez without changing the original data in the sequence file.  The TITLE field is not a part of a standard GenBank file and is used only by BioEdit.  If this field is a problem with a sequence when trying to open it with another program, open the sequence as text and delete this field before using the file with the other program.

5	ACCESSION:  the GenBank accession number for the sequence.

6	PID or NID:  Protein or Nucleic Acid  ID.

7	DBSOURCE:  The database from which the sequence was obtained.

8	KEYWORDS

9	SOURCE:  The source of the sequence (usually the organism from which it was obtained).  This field often contains the subfield ORGANISM, which gives a description of the organism (often the taxonomic classification).

10	REFERENCES:  references associated with the sequence submission.

11	COMMENT:  miscellaneous information.  A convenient place for user-defined information associated with a given sequence.

12	FEATURES:  Sequence features including translations, promoters, more source information, etc.

13	ORIGIN:  Marks the beginning of the actual sequence data.  Two forward slashes (//) designate the end of the sequence.

14	The LOCUS,  DEFINITION and ORIGIN fields are required for a GenBank file to be recognized by BioEdit.  The other fields are optional.  When GenBank files are saved, if LOCUS or DEFINITION fields are empty, they will be created with the sequence title and length.  In this case, the LOCUS and DEFINITION will be identical.  Other empty fields are not written into the sequence entry.

15	When opening a file, each field is read in as a single text block.  subfields are not formally recognized, so any “unusual” formatting that may exist in the original file (non-standard spacing, for example) will be appear as is when a file is opened in BioEdit.  When saving a GenBank file, however,  specific subfield names are looked for and spaced as in a NCBI Entrez GenBank or GenPep report.  The following subfields are looked for:

16	REFERENCES field(s):

17	reference number (format = REFERENCE   <num>  <description>)

18	AUTHORS

19	TITLE

20	JOURNAL

21	MEDLINE

22	REMARK

23	STRAIN

24	FEATURES field:

25	Previous versions of BioEdit only looked for a small selection of GenBank FEATURES tags.  Version 5.0.0 or above looks for all of the following 67 tags:

3'clip

0	3'UTR

1	5'clip

2	5'UTR

3	-10_signal

4	-35_signal

5	-

6	allele

7	attenuator

8	CDS

9	C_region

10	CAAT_signal

11	conflict

12	D-loop

13	D_segment

14	enhancer

15	exon

16	Gene

17	iDNA

18	intron

19	J_segment

20	LTR

21	mat_peptide

22	misc_binding

23	misc_difference

24	misc_feature

25	misc_recomb

26	misc_RNA

27	misc_signal

28	misc_structure

29	modified_base

30	mRNA

31	mutation

32	N_region

33	old_sequence

34	polyA_signal

35	polyA_site

36	precursor_RNA

37	prim_transcript

38	primer_bind

39	promoter

40	Protein

41	protein_bind

42	RBS

43	Region

44	repeat_region

45	repeat_unit

46	rep_origin

47	 rRNA

48	S_region

49	satellite

50	 scRNA

51	SecStr

52	sig_peptide

53	Site

54	snRNA

55	source

56	stem_loop

57	STS

58	TATA_signal

59	terminator

60	transit_peptide

61	tRNA

62	unsure

63	V_region

64	V_segment

65	 variation

0	Any data included within a field will be saved, however, in REFERENCE and FEATURES fields, data saved under a subheading not shown above may not be spaced as expected.

1	To edit specific fields, see Editing in an Edit Box


Fasta Format

Fasta/Pearson files written by BioEdit have the following format:

>Escherichi  119 amino acids

0	MVKLAFPRELRLLTPSQFTFVFQQPQRAGTPQITILGRLNSLGHPRIGLT

1	VAKKNVRRAHERNRIKRLTRESFRLRQHELPAMDFVVVAKKGVADLDNRA

2	LSEALEKLWRRHCRLARGS

3	>Proteus_mi  119 amino acids

4	MVKLAFPRELRLLTPKHFNFVFQQPQRASSPEVTILGRQNELGHPRIGLT

5	IAKKNVKRAHERNRIKRLAREYFRLHQHQLPAMDFVVLVRKGVAELDNHQ

6	LTEVLGKLWRRHCRLAQKS

7	etc ...

0	The “>” character followed by a string consistent with a title, followed by an unbroken string of characters is looked for in detecting Fasta files.


NBRF/PIR format

NBRF/PIR files written by BioEdit have the following format:

>P1;Escherichi

0	Escherichi  119 amino acids

1	 MVKLAFPREL RLLTPSQFTF VFQQPQRAGT PQITILGRLN SLGHPRIGLT

2	 VAKKNVRRAH ERNRIKRLTR ESFRLRQHEL PAMDFVVVAK KGVADLDNRA

3	 LSEALEKLWR RHCRLARGS*

4	>P1;Proteus_mi

5	Proteus_mi  119 amino acids

6	 MVKLAFPREL RLLTPKHFNF VFQQPQRASS PEVTILGRQN ELGHPRIGLT

7	 IAKKNVKRAH ERNRIKRLAR EYFRLHQHQL PAMDFVVLVR KGVAELDNHQ

8	 LTEVLGKLWR RHCRLAQKS*

9	etc ...

0	>P1; signifies a protein sequence, >DL; would signify a nucleic acid sequence.

1	The sequence is written in blocks of 10.  The end of a sequence is denoted with an asterisk.  NBRF files are detected by the presence of “>P1;” or “>DL;” immediately followed by a title


Phylip 3.2/2 format

Phylip 3.2 / Phylip 2 files written by BioEdit have the following format:

 3 136 I

Escherichi   MVKLAFPREL RLLTPSQFTF VFQQPQRAGT PQITILGRLN SLGHPRIGLT

0	             VAKKNVRRAH ERNRIKRLTR ESFRLRQHEL PAMDFVVVAK KGVADLDNRA

1	             LSEALEKLWR RHCRLARGS- ---------- ------

2	Proteus_mi   MVKLAFPREL RLLTPKHFNF VFQQPQRASS PEVTILGRQN ELGHPRIGLT

3	             IAKKNVKRAH ERNRIKRLAR EYFRLHQHQL PAMDFVVLVR KGVAELDNHQ

4	             LTEVLGKLWR RHCRLAQKS- ---------- ------

5	Haemophilu   MLKVVKVYLH NHNSQFLVVK LNFSRELRLL TPIQFKNVFE QPFRASTPEI

6	             TILARKNNLE HPRLGLTVAK KHLKRAHERN RIKRLVRESF RLSQHRLPAY

7	             DFVFVAKNGI GKLDNNTFAQ ILEKLWQRHI RLAQKS

0	All sequences in Phylip format have the same length.  The first line of the file specifies the number of sequences and the length of each sequence.  The “I” here specifies that it is Phylip 3.2 format rather than Phylip 4.  Each sequence is written after its title in blocks of 10.  The titles are 10 characters long and the sequences are spaced three spaces after the titles.


Phylip 4 format

Phylip 4 files written by BioEdit have the following format

 3 136

0	Escherichi   MVKLAFPREL RLLTPSQFTF VFQQPQRAGT PQITILGRLN SLGHPRIGLT

1	Proteus_mi   MVKLAFPREL RLLTPKHFNF VFQQPQRASS PEVTILGRQN ELGHPRIGLT

2	Haemophilu   MLKVVKVYLH NHNSQFLVVK LNFSRELRLL TPIQFKNVFE QPFRASTPEI

3	             VAKKNVRRAH ERNRIKRLTR ESFRLRQHEL PAMDFVVVAK KGVADLDNRA

4	             IAKKNVKRAH ERNRIKRLAR EYFRLHQHQL PAMDFVVLVR KGVAELDNHQ

5	             TILARKNNLE HPRLGLTVAK KHLKRAHERN RIKRLVRESF RLSQHRLPAY

6	             LSEALEKLWR RHCRLARGS- ---------- ------

7	             LTEVLGKLWR RHCRLAQKS- ---------- ------

8	             DFVFVAKNGI GKLDNNTFAQ ILEKLWQRHI RLAQKS

0	The sequences are all the same length and are interleaved.  The first line specifies the number of sequences and the length of the sequences.  The sequences are written in blocks of 10 and interleaved with 50 residues of each sequence written per block.  The titles are written before the first block.  Titles are 10 characters long and sequences are spaced 3 spaces after the titles.  All blocks are spaced over to the right 13 spaces.


Reading PC files on a Macintosh
Reading Files saved with BioEdit with a Macintosh program

Macintosh computers use a different carriage return character than PC-compatibles.  If you need to use a file created in BioEdit with a Macintosh program such as SeqApp or DNA Strider, you may need to first open the file with a word processor such as Microsoft Word or WordPerfect, then save it again to produce the correct carriage returns.  BioEdit will correctly read a file that was created  on a Macintosh or a UNIX machine.


Printing

To print an alignment, choose “Print Alignment as Text” from the “File” menu.  A preview window will appear.  This preview is incorporated into a rich text editor, and you may edit the alignment on-screen if you wish.  If a title is specified, it is printed at the beginning of the alignment.  Pressing the preview button causes the alignment to be re-drawn in the preview window with the selected specifications.  If any on-screen editing will be done, make sure that the basic format (residues per line, characters per title, etc) is set, because pressing preview again will overwrite any typing in the preview window.

The preview interface is fairly straightforward:

1	Note:  The preview window will do its best to show a preview that will let you know if you’ve overshot on residues per row with the currently chosen right margin and font size.  If this happens, the individual lines of sequence will wrap.  This is what will happen on the printer if you try to print with the residues per row set beyond the end of the specified right margin.  If this happens, decrease the residues per row, font size, or the right margin, or print in landscape orientation.


Exporting raw text
Exporting as raw text

BioEdit provides an easy function for converting alignments into properly spaced raw text files.  To export the alignment as a raw text file (no formatting), select the “Save As ...” option from the “File” menu and choose “Text Files” from the “Save as type” options in the save dialog.  You will get a dialog that asks for the number of residues per line (by tens) and the number of characters per title to save:


About BioEdit

Introduction

BioEdit v5.0.6 features

0	known problems / Limitations

General overview of program and program organization

Contacting the Author


General use of BioEdit

Sequence Editing / manipulation

Basic editing – selecting, sliding, edit box, on-screen editing

Basic manipulations

Customizing the view

File formats

File formats that BioEdit currently reads and writes

Saving sequence annotation information

Reading files in a Macintosh program

Toggling between nucleotide and protein views

Printing

Exporting as raw text

Exporting as rich text

Shaded graphic view of alignment

Restriction Maps

Restriction Enzyme Browser

Codon tables

Six-frame translation

Plasmid Drawing


Shaded graphic view of alignment

For a presentation of the alignment showing identities and similarities shaded, select the titles for the sequences you want to include, then choose “Graphic View” from the “File” menu of an open document.  This is similar to the print preview, but allows for the shading of identical and similar residues in the alignment, and allows you to show any subset of the alignment.

The following options are currently offered:

•	Variable threshold percentage for shading residues (one threshold for both identities and similarities)

•	Show or hide ruler

•	Show or hide titles on the left and right of sequence data

•	Show or hide position numbers on the left and right

•	Variable number of residues per line (by tens -- 20 to 2000)

•	Variable number of characters per title (5 to 30)

•	Titles may be bolded, italicized and/or underlined

•	Sequences may be italicized and/or bolded

•	A choice of scoring matrices is available

•	Fonts:  Any font can be used and will spaced approximately correctly.  However, some fonts look odd in this view (most, actually, are spaced too wide because the widest character must be accommodated), and typeset fonts work best.  For greater control over the font, choose “Character Font” from the “Font” menu.

•	Colors for background of page, identities and similarities and colors for non-identical, identical and similar residue characters.

•	A title may be added which will be placed at the beginning of each page.   In this release, this creates a problem if the alignment requires more than one page, so it is best to leave the title field blank.

•	Alignment may be drawn in the standard color table colors (to allow printing of the alignment in color).

•	Shading according to identity and similarity (threshold defined by “Threshold (%) for shading” on control panel) may be done with the user defined colors on the control panel, or with current alignment color table colors.

•	Lines of sequence may be blocked into groups of 10 (like a Phylip file) or printed as continuous, unbroken lines.

•	Translations may be shown below nucleic acid sequences in either 3-letter or one-letter codes

•	Shaded alignments may be exported as rich text documents which preserve colored highlighting (Word 97 or above, or equivalent, is required to display highlighting in rich text).

0	When certain changes are made to the current view, the “Redraw” button must be pressed for the changes to take place on the screen.  Many changes are automatically updated.

1	To change colors, either double-click on the labeled, colored box, or press the small button to the left of it.

2	To copy a page to the clipboard for pasting into another application, choose “Copy” form the “Edit” menu.  A page may be copied as a bitmap or an Enhanced Windows Metafile (EMF).  Copying as a metafile allows for pasting directly into an application such as PowerPoint for inclusion of a shaded alignment in a slide presentation, or into a page layout program for creation of a publication figure. A metafile offers the advantage of being a vectored graphic (the graphics are defined by formula/code rather than pixels such as in a bitmap) which can take advantage of the full resolution of the output device.  At this time, only an entire page can be copied.  A later version may offer annotation and selection capabilities, if there is demand for this.

3	Multiple pages are supported for long alignments, however, this is a serious problem with this version of BioEdit.  Currently, a page is defined vertically by the page height in inches specified by the user in the graphic view window.  When vertically scrolling through the graphic view, the current page is shown in the upper right of the form.  When the end of one page is reached, the next page is drawn in its place.  There is no continuing view from page to page, which can make viewing page transitions on-screen very tedious.  Also, some image-editing is required to produce an image figure of an alignment that takes more than one page.  Currently, it is easiest if the alignment can be made to fit on one page.  The height of a page can be set to up to 100 inches, but this will take an enormous amount of memory and is not recommended (each page is a bitmapped image).  To create an image longer than a piece of paper, you can increase the page height and copy the image to the clipboard.  On a slow computer, there is a delay as each new page is drawn.

4	Previous versions of BioEdit determined the page size only vertically.  The current version calculates the specified page settings (from the print setup and the margin and page size settings) and will clip the graphical image if it runs over the right side of the page.  This should correspond rather closely (may not always be perfect) with what will print on the currently chosen printer with the current settings.  Also, margins are now shown in the graphic view to reflect a fairly accurate print preview for each page.

5	The following are two shaded views of a ClustalW alignment of bacteriorhodopsin protein sequences from representative halophilic Archaea:


Codon Tables

BioEdit uses only codon tables with the format produced by the GCG program CodonFrequency.  The default codon table that comes with BioEdit is the E. coli codon usage table produced by J. Michael Cherry (cherry@frodo.mgh.harvard.edu).  The default codon table is shown below as an example of the format:

Escherichia coli

681 genes found in GenBank 63.

 Produced by J. Michael Cherry (cherry@frodo.mgh.harvard.edu) with the

 GCG program CodonFrequency.

 Duplicates, pseudogenes, mutant and synthetic genes were not included.

 Coding regions were specified using the Feature Table of each entry, then

 checked for accuracy. If more than one stop codon was found the sequence

 was not included.

This table was taken directly from the SeqPup distribution (Don Gilbert).

The following note is left in:

_________________________________________________________________________

    Note for SeqPup usage ----

        The start codon needs to be in >>lower case<< to

  	be recognized by SeqPup as the start codon.  Otherwise,

  	Met/atg will be used as the start codon for ORF searching.

_________________________________________________________________________

BioEdit v1.0 alpha has no ORF-searching, but later versions will, and the

same convention will be followed.

AmAcid  Codon     Number    /1000     Fraction   ..

Gly     GGG     1743.00      9.38      0.13

Gly     GGA     1290.00      6.94      0.09

Gly     GGT     5243.00     28.22      0.38

Gly     GGC     5588.00     30.08      0.40

Glu     GAG     3527.00     18.98      0.30

Glu     GAA     8101.00     43.61      0.70

Asp     GAT     6103.00     32.85      0.59

Asp     GAC     4244.00     22.84      0.41

Val     GTG     4429.00     23.84      0.34

Val     GTA     2231.00     12.01      0.17

Val     GTT     3744.00     20.15      0.29

Val     GTC     2601.00     14.00      0.20

Ala     GCG     5946.00     32.01      0.34

Ala     GCA     3899.00     20.99      0.22

Ala     GCT     3266.00     17.58      0.19

Ala     GCC     4274.00     23.01      0.25

Arg     AGG      286.00      1.54      0.03

Arg     AGA      464.00      2.50      0.04

Ser     AGT     1366.00      7.35      0.13

Ser     AGC     2871.00     15.45      0.27

Lys     AAG     2238.00     12.05      0.24

Lys     AAA     7102.00     38.23      0.76

Asn     AAT     3047.00     16.40      0.39

Asn     AAC     4755.00     25.59      0.61

Met     atg     4756.00     25.60      1.00

Ile     ATA      738.00      3.97      0.07

Ile     ATT     4970.00     26.75      0.47

Ile     ATC     4955.00     26.67      0.46

Thr     ACG     2375.00     12.78      0.23

Thr     ACA     1263.00      6.80      0.12

Thr     ACT     2160.00     11.63      0.21

Thr     ACC     4437.00     23.88      0.43

Trp     TGG     2504.00     13.48      1.00

End     TGA      180.00      0.97      0.30

Cys     TGT      887.00      4.77      0.43

Cys     TGC     1173.00      6.31      0.57

End     TAG       52.00      0.28      0.09

End     TAA      371.00      2.00      0.62

Tyr     TAT     3017.00     16.24      0.53

Tyr     TAC     2629.00     14.15      0.47

Leu     TTG     2046.00     11.01      0.11

Leu     TTA     1879.00     10.11      0.11

Phe     TTT     3443.00     18.53      0.51

Phe     TTC     3328.00     17.91      0.49

Ser     TCG     1434.00      7.72      0.13

Ser     TCA     1274.00      6.86      0.12

Ser     TCT     1992.00     10.72      0.19

Ser     TCC     1794.00      9.66      0.17

Arg     CGG      851.00      4.58      0.08

Arg     CGA      580.00      3.12      0.05

Arg     CGT     4534.00     24.41      0.42

Arg     CGC     4006.00     21.56      0.37

Gln     CAG     5389.00     29.01      0.69

Gln     CAA     2375.00     12.78      0.31

His     CAT     2145.00     11.55      0.52

His     CAC     1987.00     10.70      0.48

Leu     CTG     9749.00     52.48      0.55

Leu     CTA      565.00      3.04      0.03

Leu     CTT     1857.00     10.00      0.10

Leu     CTC     1764.00      9.50      0.10

Pro     CCG     4371.00     23.53      0.55

Pro     CCA     1559.00      8.39      0.20

Pro     CCT     1248.00      6.72      0.16

Pro     CCC      785.00      4.23      0.10


BLAST

A BLAST (Basic Local Alignment Search Tool) search is often the most convenient method for detecting homology of a biological sequence to existing characterized sequences.  BLAST looks for homology by searching for locally aligned regions of identity and/or similarity between a query sequence and sequences in a database.  The algorithm works by the following general method:

1.  A query sequence is divided into short sequences (called words, ca. 3 to 8 residues, depending on whether it’s protein or nucleic acid).

2.  A table of all sequences of the same word size which can pair with each of the words from the query sequence with a score above a defined threshold is constructed (the lookup table).

3.  The database sequences are scanned for occurrence of sequences in the lookup table.

4.  When a word is found in the database which can align to a word in the query over the critical threshold, the alignment is extended in both directions.  This extension continues in both directions as long as the length of the extension does not exceed a defined limit without further increasing the score of the alignment.

5.  If, when an extension is terminated, the total sub-alignment score is above another defined threshold, the alignment is reported.

6.  When a threshold alignment is produced, that particular database sequence is re-scanned for other  non-redundant high-scoring segment pairs (HSPs) which score above yet another defined cut-off (the sum of several non-significant sub-alignments within the same two sequences can, when taken together, indicate significant similarity indicative of homology).

7.  A statistical measure is reported which indicates the probability that a similar-scoring HSP or set of HSPs found for a given query would result from searching the same database with a randomly-generated sequence of the same length as the query.

For a reference on BLAST, see:

Altschul, Stephen F., Warren Gish, Webb Miller, Eugene W. Myers, and David J. Lipman (1990).  Basic local alignment search tool.  J. Mol. Biol. 215:403-10.

and, for the newer gapped BLAST and PSI-BLAST versions,

Altschul, Stephen F., Thomas L. Madden, Alejandro A. Schäffer, Jinghui Zhang, Zheng Zhang, Webb Miller, and David J. Lipman (1997), "Gapped BLAST and PSI-BLAST: a new generation of protein database search programs", Nucleic Acids Res. 25:3389-3402.

for a description of the newer PHI-BLAST method, see:

Zhang, Zheng, Alejandro A. Schäffer, Webb Miller, Thomas L. Madden, David J. Lipman, Eugene V. Koonin and Stephen F. Altschul (1998), "Protein sequence similarity searches using patterns as seeds", Nucleic Acids Res. 26:3986-3990.

Sub-topics:

 Local BLAST

 Creating a database

 Local BLAST searching

 BLAST Internet client


Local BLAST

 	The NCBI BLAST version 2.0.3 ( [Nov-14-1997], Altschul, Stephen F., Thomas L. Madden, Alejandro A. Schaffer, Jinghui Zhang, Zheng Zhang, Webb Miller, and David J. Lipman (1997), "Gapped BLAST and PSI-BLAST: a new generation of protein database search programs", Nucleic Acids Res. 25:3389-3402.) is included in the BioEdit distribution and is found in the \apps folder of the install directory.  This is particular useful if you are interested in fishing out a specific gene from a partially sequenced genome whose sequences have not yet been assigned and deposited.

To use this program, you must first create a local database.  You can create as many local databases as you want, just keep in mind the following requirements:

1.  Nucleotide and protein databases are separate entities.

2.  Databases must be present within the \database directory of the BioEdit folder to be recognized by the BioEdit local BLAST interface (the NCBI blastall.exe program, however, is a stand-alone app that can be used entirely separately from BioEdit).  When a database is created using BioEdit, it is automatically placed into the \database directory.

Creating a database

Local BLAST searching


Local BLAST Searching

To use local BLAST from within BioEdit, highlight the title of the query sequence from within a BioEdit document.  Next, choose “Local Blast” from the “Blast” menu under the “Accessory apps” menu.  Don’t worry about gaps, these will be removed automatically.  You may also choose several sequences at once if you want to for a batch job.  Choose the program  you would like to use, then the database to search.  In the upper right of the form, there will be a drop-down list for both nucleotide and protein databases.  Choose the one you want for the appropriate type, and don’t worry about the other type (a selected choice of nucleotide database will be ignored  when doing a protein search).  You may choose whether to save the output to a user-named file, or simply have BioEdit create a temp file which is automatically opened when the search is done.


Creating a local BLAST database
Creating a local database

To create a local protein or nucleotide database for BLAST searching, you need only have a Fasta-format file containing all of the sequences you want in the database.  Nucleotide and protein sequences cannot be mixed within the same database.  From the “Accessory Application” menu, choose “BLAST”, then “Create a local ... database file”.  You will be prompted for the input Fasta file.  The rest is automatic.  The database will be placed in to the \database folder of the BioEdit install directory.  The new database should appear in the appropriate database list box of the local BLAST interface form.

Note: If you create a database or copy one into the \database folder, and it does not appear in the choices on the BLAST search form, try quitting BioEdit and restarting.  If this does not work, you may have to rename the *.pin (protein) or *.nin  (nucleotide) file.  You can give it the same name.  I am not sure exactly why this (rarely) happens, but renaming the file to the same name seems to solve  the problem.


BLAST 2.0 Client
BLAST Internet Client

Originally, the BioEdit installation packaged the NCBI BLAST client 2.0 program blatstcli.exe, which I had modified to accept an input sequence file at the command line.

The NCBI BLAST 2.0 client has since been discontinued.

BioEdit now includes the NCBI's BLAST client 3 (blastcl3.exe in the "/apps" folder).  If you select a sequence, or multiple sequences, from the alignment window, and choose "Accessory Applications->BLAST->NCBI BLAST over the Internet", the following interface will come up:

You may BLAST one or more sequences at a time.  Also, you may have the output come back as HTML if you want, otherwise you may have plain text output produced.  If HTML output is selected, the output will automatically be opened in the your WWW browser.  Otherwise, the text output will be opened in BioEdit.

You may choose any of the standard BLAST formatting options (Pairwise is always the default):

Altschul, Stephen F., Thomas L. Madden, Alejandro A. Schaffer, Jinghui Zhang, Zheng Zhang, Webb Miller, and David J. Lipman (1997), "Gapped BLAST and PSI-BLAST: a new generation of protein database search programs", Nucleic Acids Res. 25:3389-3402.


ClustalW

ClustalW is a program by Thompson, J.D., Higgins, D.G. and Gibson, T.J. (1994)

designed to construct multiple alignments of biological sequences.  Clustal will automatically align many sequences with a profile-based progressive alignment procedure.  This program is utilized unaltered by BioEdit and basic on-line help for this program is provided as a linked version of the original documentation distributed with the program.  The original document can be found in the \apps directory and has been named “clustalw.txt”.  The BioEdit interface for ClustalW is straightforward and options are described in the ClustalW documentation.

clustalw_help   for version 1.4 (September 1994).


Clustal Help for version 1.4
clustalw_help   for version 1.4 (September 1994).

Note:  The information linked to in the contents below was copied directly from the ClustalW 1.4 documentation (Higgins et al., 1994) which can be found in "\apps\clustalw.txt".

Contents:

General Info

General help for CLUSTAL W

Help for multiple alignments

Help for pairwise alignment parameters

Help for multiple alignment parameters

Help for protein gap parameters

Help for output format options

Help for profile alignments

Help for phylogenetic trees

Help for choosing protein weight matrix

Help for command line parameters

Help for tree output format options


General info for ClustalW
General Info

Note:  The text below was copied directly from the ClustalW 1.4 documentation  (Higgins et al., 1994)  which can be found in "\apps\clustalw.txt".

clustalw_help   for version 1.4 (September 1994).

This is the on-line help file for CLUSTAL W.

It should be named or defined as: clustalw_help

except with MSDOS in which case it should be named CLUSTALW.HLP

For full details of usage and algorithms, please see the files:

cluustalv.doc    The documentation for Clustal V (most of the program usage and the basic algorithms are the same).

clustalw.ms      A manuscript describing the main algorithmic changes over Clustal V.

readme.txt       A brief summary of the main changes over Clustal V.

Toby  Gibson

Des   Higgins    (now at the EBI, Hinxton, Great Britain)

Julie Thompson

EMBL, Heidelberg, Germany.

The paper describing Clustal W is:

Thompson, J.D., Higgins, D.G. and Gibson, T.J. (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position specific gap penalties and weight matrix choice. Nucleic Acids Research, submitted, June 1994.


General help for CLUSTAL W

Note:  The text below was copied directly from the ClustalW 1.4 documentation  (Higgins et al., 1994)  which can be found in "\apps\clustalw.txt".

Clustal W is a general purpose multiple alignment program for DNA or proteins.

SEQUENCE INPUT:  all sequences must be in 1 file, one after another.

6 formats are automatically recognized: NBRF/PIR, EMBL/SWISSPROT,

Pearson (Fasta), Clustal (*.aln), GCG/MSF (Pileup) and GDE.

All non-alphabetic characters (spaces, digits, punctuation marks) are ignored

except "-" which is used to indicate a GAP ("." in GCG/MSF).

To do a MULTIPLE ALIGNMENT on a set of sequences, use item 1 from this menu to

INPUT them; go to menu item 2 to do the multiple alignment.

PROFILE ALIGNMENTS (menu item 3) are used to align 2 alignments or to add a set

of new sequences to an old alignment.  Use this to add new sequences to an old

alignment.  GAPS in the old alignments are

indicated using the "-" character.   PROFILES can be input in ANY of the

allowed formats; just use "-" (or "." for MSF) for each gap position.

PHYLOGENETIC TREES (menu item 4) can be calculated from old alignments (read in

with "-" characters to indicate gaps) OR after a multiple alignment while the

alignment is still in memory.

The program tries to automatically recognize the different file formats used

and to guess whether the sequences are amino acid or nucleotide.  This is not

always foolproof.

FASTA and NBRF/PIR formats are recognized by having a ">" as the first

character in the file.

EMBL/Swiss Prot formats are recognised by the letters

ID at the start of the file (the token for the entry name field).

CLUSTAL format is recognised by the word CLUSTAL at the beginning of the file.

GCG/MSF format is recognised by the word PileUp at the start of the file.  If

your msf files do not contain this word first, edit it in at the start

of the first line.

If 85% or more of the characters in the sequence are from A,C,G,T,U or N, the

sequence will be assumed to be nucleotide.  This works in 97.3% of cases

but watch out!

The paper describing Clustal W is:

Thompson, J.D., Higgins, D.G. and Gibson, T.J. (1994)

CLUSTAL W: improving the sensitivity of progressive multiple

sequence alignment through sequence weighting, position specific

gap penalties and weight matrix choice.

Nucleic Acids Research, submitted, June 1994.


Clustal help for multiple alignments
Help for multiple alignments

Note:  The text below was copied directly from the ClustalW 1.4 documentation  (Higgins et al., 1994)  which can be found in "\apps\clustalw.txt".

If you have already loaded sequences, use menu item 1 to do the complete

multiple alignment.  You will be prompted for 2 output files: 1 for the

alignment itself; another to store a dendrogram that describes the similarity

of the sequences to each other.

Multiple alignments are carried out in 3 stages (automatically done from menu

item 1 ...Do complete multiple alignments now):

1) all sequences are compared to each other (pairwise alignments);

2) a dendrogram (like a phylogenetic tree) is constructed, describing the

approximate groupings of the sequences by similarity (stored in a file).

3) the final multiple alignment is carried out, using the dendrogram as a guide.

PAIRWISE ALIGNMENT parameters control the speed/sensitivity of the initial

alignments.

MULTIPLE ALIGNMENT parameters control the gaps in the final multiple alignments.

RESET GAPS (menu item 7) will remove any new gaps introduced into the sequences

during multiple alignment if you wish to change the parameters and try again.

This only takes effect just before you do a second multiple alignment.  You

can make phylogenetic trees after alignment whether or not this is ON.

If you turn this OFF, the new gaps are kept even if you do a second multiple

alignment. This allows you to iterate the alignment gradually.  Sometimes, the

alignment is improved by a second or third pass.

SCREEN DISPLAY can be used to send the output alignments to the screen

as well as to the output file.

You can skip the first stages (pairwise alignments; dendrogram) by using an

old dendrogram file (menu item 3); or you can just produce the dendrogram

with no final multiple alignment (menu item 2).

OUTPUT FORMAT: Menu item 9 (format options) allows you to choose from 5

different alignment formats (CLUSTAL, GCG, NBRF/PIR, PHYLIP and GDE).

You can toggle between FAST/APPROXIMATE or SLOW/ACCURATE alignments for

the initial alignments used to make the guide tree.  The fast ones are

extremely fast but are less reliable than the slow ones.


Clustal help for pairwise alignment parameters
Help for pairwise alignment parameters

Note:  The text below was copied directly from the ClustalW 1.4 documentation  (Higgins et al., 1994)  which can be found in "\apps\clustalw.txt".

A distance is calculated between every pair of sequences and these are

used to construct the dendrogram which guides the final multiple alignment.

The scores are calculated from separate pairwise alignments.  These can be

calculated using 2 methods: dynamic programming (slow but accurate) or by the

method of Wilbur and Lipman (extremely fast but approximate).

You can choose between the 2 alignment methods using menu option 8.  The

slow/accurate method is fine for short sequences but will be VERY SLOW

for many (e.g. >20) long (e.g. >1000 residue) sequences.

SLOW/ACCURATE alignment parameters:

These parameters do not have any affect on the speed of the alignments.  They

are used to give initial alignments which are then rescored to give percent

identity scores.  These % scores are the ones which are displayed on the

screen.  The scores are converted to distances for the trees.

1) Gap Open Penalty:      the penalty for opening a gap in the alignment.

2) Gap extension penalty: the penalty for extending a gap by 1 residue.

3) Protein weight matrix: the scoring table which describes the similarity of

each amino acid to each other.  For DNA, an identity matrix is used.

FAST/APPROXIMATE alignment parameters:

These similarity scores are calculated from fast, approximate, global align-

ments, which are controlled by 4 parameters.   2 techniques are used to make

these alignments very fast: 1) only exactly matching fragments (k-tuples) are

considered; 2) only the 'best' diagonals (the ones with most k-tuple matches)

are used.

K-TUPLE SIZE:  This is the size of exactly matching fragment that is used.

INCREASE for speed (max= 2 for proteins; 4 for DNA), DECREASE for sensitivity.

For longer sequences (e.g. >1000 residues) you may need to increase the default.

GAP PENALTY:   This is a penalty for each gap in the fast alignments.  It has

little affect on the speed or sensitivity except for extreme values.

TOP DIAGONALS: The number of k-tuple matches on each diagonal (in an imaginary

dot-matrix plot) is calculated.  Only the best ones (with most matches) are

used in the alignment.  This parameter specifies how many.  Decrease for speed;

increase for sensitivity.

WINDOW SIZE:  This is the number of diagonals around each of the 'best'

diagonals that will be used.  Decrease for speed; increase for sensitivity.


Clustal help for multiple alignment parameters
Help for multiple alignment parameters

Note:  The text below was copied directly from the ClustalW 1.4 documentation  (Higgins et al., 1994)  which can be found in "\apps\clustalw.txt".

These parameters control the final multiple alignment.  This is the core of

the program and the details are complicated.  To fully understand the use

of the parameters and the scoring system, you will have to refer to the

documentation.

Each step in the final multiple alignment consists of aligning two alignments

or sequences.  This is done progressively, following the branching order in

the GUIDE TREE.  The basic parameters to control this are two gap penalties and

the scores for various identical/non-indentical residues.

1) and 2) The GAP PENALTIES are set by menu items 1 and 2.  These control the

cost of opening up every new gap and the cost of every item in a gap.

Increasing the gap opening penalty will make gaps less frequent.  Increasing

the gap extension penalty will make gaps shorter.   Terminal gaps are not

penalised.

3) The DELAY DIVERGENT SEQUENCES switch delays the alignment of the most

distantly related sequences until after the most closely related sequences have

been aligned.   The setting shows the percent identity level required to delay

the addition of a sequence; sequences that are less identical than this level

to any other sequences will be aligned later.

4) For DNA, the scoring system assigns a score of 3 for two identical bases

and zero otherwise.   The TOGGLE TRANSITIONS switch (menu item 3) gives

transitions (A <--> G or C <--> T i.e. purine-purine or pyrimidine-pyrimidine

substitutions) a score of 1; otherwise, these are scored as mismatches and

get a score of zero.  For distantly related DNA sequences, this switch

might be better turned off; for closely related sequences it can be useful.

5) PROTEIN WEIGHT MATRIX leads to a new menu where you are offered a

choice of weight matrices.   The default is the BLOSUM series of

matrices by Jorja and Steven Henikoff.  Note, a series is used!  The actual

matrix that is used depends on how similar the sequences to be aligned at this

alignment step are.   Different matrices work differently at each

evolutionary distance.  Further help is offered in the weight matrix menu.


Clustal help for gap parameters
Help for protein gap parameters

Note:  The text below was copied directly from the ClustalW 1.4 documentation  (Higgins et al., 1994)  which can be found in "\apps\clustalw.txt".

1) RESIDUE SPECIFIC PENALTIES are amino acid specific gap penalties that reduce

or increase the gap opening penalties at each position in the alignment or

sequence.  See the documentation for details.  As an example, positions that

are rich in glycine are more likely to have an adjacent gap than positions that

are rich in valine.

2) 3) HYDROPHILIC GAP PENALTIES are used to increase the chances of a gap within

a run (5 or more residues) of hydrophilic amino acids; these are likely to

be loop or random coil regions where gaps are more common.  The residues that

are "considered" to be hydrophilic are set by menu item 3.

4) GAP SEPARATION DISTANCE tries to decrease the chances of gaps being

too close to each other.  Gaps that are less than this distance apart

are penalised more than other gaps.  This does not prevent close gaps;

it makes them less frequent, promoting a block-like appearance of the alignment.

5) END GAP SEPARATION treats end gaps just like internal gaps for the purposes

of avoiding gaps that are too close (set by GAP SEPARATION DISTANCE above).

If this is off (default), end gaps will be ignored for this purpose.  This is

useful when you wish to align fragments where the end gaps are not biologically

meaningful.


Clustal help for output format options
Help for output format options.

Note:  The text below was copied directly from the ClustalW 1.4 documentation  (Higgins et al., 1994)  which can be found in "\apps\clustalw.txt".

Five output formats are offered.  You can choose more than one (or all 5 if

you wish).

CLUSTAL format output is a self explanatory alignment format.  It shows the

sequences aligned in blocks.  It can be read in again at a later date to

(for example) calculate a phylogenetic tree or add a new sequence with a

profile alignment.

GCG output can be used by any of the GCG programs that can work on multiple

alignments (e.g. PRETTY, PROFILEMAKE, PLOTALIGN).  It is the same as the GCG

.msf format files (multiple sequence file); new in version 7 of GCG.

PHYLIP format output can be used for input to the PHYLIP package of Joe

Felsenstein.  This is an extremely widely used package for doing every

imaginable form of phylogenetic analysis (MUCH more than the modest intro-

duction offered by this program).

NBRF/PIR:  this is the same as the standard PIR format with ONE ADDITION.  Gap

characters "-" are used to indicate the positions of gaps in the multiple

alignment.   These files can be re-used as input in any part of clustal that

allows sequences (or alignments or profiles) to be read in.

GDE:  this format is used by the GDE package of Steven Smith.

OUTPUT ORDER is used to control the order of the sequences in the output

alignments.  By default, it is the same as the input order.  This switch can

be used to make the order correspond to the order in which the sequences

were aligned (from the guide tree/dendrogram), thus automatically grouping

closely related sequences.


Clustal help for profile alignments
Help for profile alignments

Note:  The text below was copied directly from the ClustalW 1.4 documentation  (Higgins et al., 1994)  which can be found in "\apps\clustalw.txt".

By PROFILE ALIGNMENT, we mean alignment to an existing alignment.  Either of the

alignments can be a single sequence.  A profile is simply an alignment of

one or more sequences (e.g. an alignment output file from Clustal W) or a set

of unaligned sequences.

The profiles can be in any of the allowed input formats with "-" characters

used to specify gaps (except for GCG/MSF where "." is used).

You have to specify the 2 profiles by choosing menu items 1 and 2 and giving

2 file names.  Then Menu item 3 will align the 2 profiles to each other.

Menu item 4 will take the sequences in the second profile and align them to

the first profile, 1 at a time.  This is useful to add some new sequences to

an existing alignment.  In this case, the second profile need not be pre-

aligned.

The alignment parameters can be set using menu items 6 and 7 ("Alignment

parameters"). These are EXACTLY the same parameters as used by the general,

automatic multiple alignment procedure.  The general multiple alignment proc-

edure is simply a series of profile alignments.   Carrying out a series of

profile alignments on larger and larger groups of sequences, allows you to

manually build up a complete alignment.

Profile alignments allow you to store alignments of your favorite sequences

and add new sequences to them in small bunches at a time.


Clustal help for phylogenetic trees
Help for phylogenetic trees

Note:  The text below was copied directly from the ClustalW 1.4 documentation  (Higgins et al., 1994)  which can be found in "\apps\clustalw.txt".

1) Before calculating a tree, you must have an ALIGNMENT in memory.  This can be input in any format or you should have just carried out a full multiple alignment and the alignment is still in memory.  Remember YOU MUST ALIGN THE SEQUENCES FIRST!!!!

The method used is the NJ (Neighbour Joining) method of Saitou and Nei.  First you calculate distances (percent divergence) between all pairs of sequence from a multiple alignment; second you apply the NJ method to the distance matrix.

2) EXCLUDE POSITIONS WITH GAPS?  With this option, any alignment positions where ANY of the sequences have a gap will be ignored.  This means that 'like'  will be compared to 'like' in all distances.  It also, automatically throws away the most ambiguous parts of the alignment, which are concentrated around gaps (usually).  The disadvantage is that you may throw away much of the data if there are many gaps.

3) CORRECT FOR MULTIPLE SUBSTITUTIONS?  For small divergence (say <10%) this option makes no difference.  For greater divergence, this option corrects for the fact that observed distances underestimate actual evolutionary distances.  This is because, as sequences diverge, more than one substitution will happen at many sites.  However, you only see one difference when you look at the present day sequences.  Therefore, this option has the effect of stretching branch lengths in trees  (especially long branches).  The corrections used here (for DNA or proteins) are both due to Motoo Kimura.  See the documentation for details.  README.TXT describes a new modification for proteins distances.

For VERY divergent sequences, the distances cannot be reliably corrected.  You will be warned if this happens.  Even if none of the distances in a data set exceed the reliable threshold, if you bootstrap the data,  some of the bootstrap distances may randomly exceed the safe limit.

4) To calculate a tree, use option 4 (DRAW TREE NOW).  This gives an UNROOTED tree and all branch lengths.  The root of the tree can only be inferred by using an outgroup (a sequence that you are certain branches at the outside of the tree .... certain on biological grounds) OR if you assume a degree of constancy in the 'molecular clock', you can place the root in the 'middle' of the tree (roughly equidistant from all tips).

5) BOOTSTRAPPING is a method for deriving confidence values for the groupings in a tree (first adapted for trees by Joe Felsenstein).   It involves making N random samples of sites from the alignment (N should be LARGE, e.g. 500 - 1000); drawing N trees (1 from each sample) and counting how many times each grouping from the original tree occurs in the sample trees.   You must supply a seed  number for the random number generator.  Different runs with the same seed will give the same answer.  See the documentation for details.

6) OUTPUT FORMATS:  three different formats are allowed.  None of these displays the tree visually.  You must make the tree yourself (on paper) using the results OR get the PHYLIP package and use the tree drawing facilities there.  (Get the PHYLIP package anyway if you are interested in trees).


Clustal help for choosing protein weight matrix
Help for choosing protein weight matrix

Note:  The text below was copied directly from the ClustalW 1.4 documentation  (Higgins et al., 1994)  which can be found in "\apps\clustalw.txt".

For protein alignments, you use a weight matrix to determine the similarity of

non-identical amino acids.  For example, Tyr aligned with Phe is usually judged

to be 'better' than Tyr aligned with Pro.   These are not used with DNA.

There are two 'in-built' series of weight matrices offered.  Each consists

of several matrices which work differently at different evolutionary distances.

To see the exact details, read the documentation.  Crudely, we store several

matrices in memory, spanning the full range of amino acid distance (from

almost identical sequences to highly divergent ones).   For very similar

sequences, it is best to use a strict weight matrix which only gives a high

score to identities and the most favoured conservative substitutions.  For

more divergent sequences, it is appropriate to use "softer" matrices which

give a high score to many other frequent substitutions.

1) BLOSUM (Henikoff).   These matrices appear to be the best available for

carrying out data base similarity (homology searches).  The matrices used are:

Blosum80, 62, 40 and 30.

2) PAM (Dayhoff).  These have been extremely widely used since the late '70s.

We use the PAM 120, 160, 250 and 350 matrices.

We also supply an identity matrix which gives a score of 10 to two identical

amino acids and a score of zero otherwise.  This matrix is not very useful.

Alternatively, you can read in your own (just one matrix, not a series).

A new matrix can be read from a file on disk, if the filename consists only

of lower case characters. The values in the new weight matrix must be integers

and the scores should be similarities.  You can use negative as well as positive

values if you wish, although the matrix will be automatically adjusted to all

positive scores.

INPUT FORMAT  The format used for a new matrix is the same as the BLAST program.

Any lines beginning with a # character are assumed to be comments. The first

non-comment line should contain a list of amino acids in any order, using the

1 letter code, followed by a * character. This should be followed by a square

matrix of integer scores, with one row and one column for each amino acid. The

last row and column of the matrix (corresponding to the * character) contain

the minimum score over the whole matrix.


Clustal help for command line parameters
Help for command line parameters

Note:  The text below was copied directly from the ClustalW 1.4 documentation  (Higgins et al., 1994)  which can be found in "\apps\clustalw.txt".

                DATA (sequences)

/INFILE=file.ext                             :input sequences.

/PROFILE1=file.ext  and  /PROFILE2=file.ext  :profiles (old alignment).

                VERBS (do things)

/OPTIONS	    :list the command line parameters

/HELP  or /CHECK    :outline the command line params.

/ALIGN              :do full multiple alignment

/TREE               :calculate NJ tree.

/BOOTSTRAP(=n)      :bootstrap a NJ tree (n= number of bootstraps; def. = 1000).

                PARAMETERS (set things)

***General settings:****

/INTERACTIVE :read command line, then enter normal interactive menus

/QUICKTREE   :use FAST algorithm for the alignment guide tree

/NEWTREE=    :file for new guide tree

/USETREE=    :file for old guide tree

/NEGATIVE    :protein alignment with negative values in matrix

/OUTFILE=    :sequence alignment file name

/OUTPUT=     :GCG, GDE, PHYLIP or PIR

/OUTORDER=   :INPUT or ALIGNED

/CASE        :LOWER or UPPER (for GDE output only)

***Fast Pairwise Alignments:***

/KTUP=n      :word size                  /TOPDIAGS=n  :number of best diags.

/WINDOW=n    :window around best diags.  /PAIRGAP=n   :gap penalty

/SCORE       :PERCENT or ABSOLUTE

***Slow Pairwise Alignments:***

/PWMATRIX=   :BLOSUM, PAM, ID or filename

/PWGAPOPEN=f :gap opening penalty        /PWGAPEXT=f  :gap opening penalty

***Multiple Alignments:***

/MATRIX=     :BLOSUM, PAM, ID or filename

/GAPOPEN=f   :gap opening penalty        /GAPEXT=f    :gap extension penalty

/ENDGAPS     :no end gap separation pen. /GAPDIST=n   :gap separation pen. range

/NORGAP      :Residue specific gaps off  /NOHGAP      :hydrophilic gaps off

/HGAPRESIDUES= :list hydrophilic res.    /MAXDIV=n    :% ident. for delay

/TYPE=       :PROTEIN or DNA             /TRANSITIONS :transitions NOT weighted.

***Trees:***                             /SEED=n    :seed number for bootstraps.

/KIMURA      :use Kimura's correction.   /TOSSGAPS  :ignore positions with gaps.


Clustal help for tree output format options
Help for tree output format options

Note:  The text below was copied directly from the ClustalW 1.4 documentation  (Higgins et al., 1994)  which can be found in "\apps\clustalw.txt".

Three output formats are offered: 1) Clustal, 2) Phylip/TreeTool,

3) Just the distances.

None of these formats displays the results graphically.  To see a graphic

representation of a tree (not a bootstrapped tree), get the PHYLIP package and

use format 2) below.  It can be imported into the PHYLIP programs RETREE,

DRAWTREE and DRAWGRAM and displayed graphically.  TreeTool can also do this

but is only available for SUN (by ftp from rdp.life.uiuc.edu).  TreeTool,

however has a neat facility for labels on internal nodes which we use to

display bootstrap figures on the bootstrap trees.  If you do not have TreeTool,

please request the trees in Clustal format 1) below.

1) Clustal format output.

This format is verbose and lists all of the distances between the sequences

and the number of alignment positions used for each.   The tree is described

at the end of the file.  It lists the sequences that are joined at each

alignment step and the branch lengths.  After two sequences are joined, it is

referred to later as a NODE.  The number of a NODE is the number of the

lowest sequence in that NODE.

2) Phylip or TreeTool format output.

This format is the New Hampshire format, used by many phylogenetic analysis

packages.  It consists of a series of nested parentheses, describing the

branching order, with the sequence names and branch lengths.  With a simple

tree, it can be used by the RETREE, DRAWGRAM and DRAWTREE programs of the PHYLIP

package to see the trees graphically.  This is the same format used during

multiple alignment for the guide trees.

With a bootstrap tree, you need to use TreeTool or request format 1) above.

3) The distances only.

This format just outputs a matrix of all the pairwise distances in a format

that can be used by the Phylip package.  It used to be useful when one

could not produce distances from protein sequences in the Phylip package but

is now redundant (Protdist of Phylip 3.5 now does this).


Basic analysis tools
Basic Analysis Tools:

External Accessories

0	    Installing TreeView

1	    Configuring and Using External Applications

2	        Adding and configuring a new application

3	        Modifying an existing application configuration

4	        Removing an accessory application

5	        Storage of the configuration information

6	        An example: Configuring ClustalW to run through a custom BioEdit interface

7	BLAST

8	    Local BLAST

9	    Creating a database

10	    Local BLAST searching

11	    BLAST Internet Client

12	   ClustalW

13	    Using World Wide Web tools

14	Automated links

15	    Restriction mapping

16	    BLAST

17	    PSI-BLAST

18	    PHI-BLAST

19	    Prosite pattern and profile scans

20	    nnPredict protein secondary structure prediction

21	 	Other links

22	    ENTREZ and PubMed

23	    Pedro’s BioMolecular Research Tools

24	    Constructing World Wide Web bookmarks for BioEdit

25	Incorporated into BioEdit

26

27	    Amino Acid and Nucleotide Composition

28	    Entropy Plot

29	    Hydrophobicity Profiles

30	    Identity Matrix

31	    Nucleotide translation with codon usage

32	    Positional nucleotide numerical summary

33	    Search for conserved regions of an alignment

34	    Dot Plot of two sequence

35	    Pairwise sequence alignment

36	    RNA comparative analysis

37	    The basis of phylogenetic comparison

38	    Covariation

39	Using Covariation in BioEdit

40	   List output

41	   Table output

42	Covariation analysis preferences

43	The covariation algorithm

44	    Potential Pairings

45	Using Potential Pairings in BioEdit

46	   List Output

47	   Table output

48	Potential pairings analysis preferences

49	The potential pairings algorithm

50	    Mutual Information

51	        General Overview of mutual Information

52	        Mathematical Overview of Mutual Information

53	        Using Mutual Information in BioEdit

54	        Mutual Information Example

55	        Setting Mutual Information Preferences

56	        Using the Matrix Plotter for Mutual Information Data

57	       1-D plots of matrix data rows and columns

58	The Mutual Information Examiner

59	    Using Masks

60	    Setting preferences for BioEdit analysis tools


External Accessories

 Installing TreeView

0	    Configuring and Using External Applications

1	        Adding and configuring a new application

2	        Modifying an existing application configuration

3	        Removing an accessory application

4	        Storage of the configuration information

5	        An example: Configuring ClustalW to run through a custom BioEdit interface

6	BLAST

7	    Local BLAST

8	    Creating a database

9	    Local BLAST searching

10	    BLAST Internet Client

11	   ClustalW

12	    Using World Wide Web tools

13	Automated links

14	    Restriction mapping

15	    BLAST

16	    PSI-BLAST

17	    PHI-BLAST

18	    Prosite pattern and profile scans

19	    nnPredict protein secondary structure prediction

20	 	Other links

21	    ENTREZ and PubMed

22	    Pedro’s BioMolecular Research Tools

    Constructing World Wide Web bookmarks for BioEdit


File formats

File formats that BioEdit currently reads and writes

Reading files in a Macintosh program


Restriction Mapping

If you have access to the World Wide Web, there is an automatic link to WebCutter, a web tool for generating restriction maps.  Simply highlight your sequence title in the edit window and Choose “Auto-fed Restriction Mapping” from the “World Wide Web” menu.  There are some options to choose from, then press the “Analyze Sequence” button.  In a short time your map will be returned and reformatted.  You may also use this feature with your external browser (which may be necessary to fully view large maps).

BioEdit now also has an internal restriction map utility which has several nice options.


BLAST with the Web browser
HTML BLAST with a Web Browser

This is general BLAST at NCBI.  The only difference between using this feature and using Netscape or Internet Explorer is that a selected sequence is automatically degapped and entered into the query window of the BLAST form.  If this feature is used with an external browser from within BioEdit, however, the sequence is degapped and fed directly to the form.  The most obvious benefit of World Wide Web BLAST over the BLAST client program is that the resulting hits have easy links directly to ENTREZ entries and to Medline abstracts.  Since the BLAST client program is just over 1 megabyte on disk, I may not include it in the next version of BioEdit to make a smaller installation.

To use WWW BLAST from a BioEdit document, select the sequence title of interest and choose “Auto-fed NCBI Standard BLAST” from the “World Wide Web” menu.


PSI-BLAST

PSI-BLAST is the newest search algorithm offered by NCBI.  It is a variation on the original BLAST algorithm and is embellished to provide a search method analogous to searching with a consensus matrix defined by a set of homologous sequences in order to get a more sensitive measure of distant homology.

PSI-BLAST (Position-Specific Iterated BLAST) is an extension to standard BLAST which creates a position-specific weighted consensus matrix based upon an alignment of all high scoring segment pairs (HSPs) scoring above a defined threshold resulting from a standard BLAST search with the original query.  During iterations of PSI-BLAST, the matrix is used in place of the original query.  The matrix is refined at each iteration.  In most cases, the matrix eventually converges to a point at which further iterations do not change the matrix.  The resulting position-weighted alignments may give a strong indication of distant homologies that would be entirely missed with a single standard BLAST search.

For further reading on PSI-BLAST, see:

Altschul, Stephen F., Thomas L. Madden, Alejandro A. Schäffer, Jinghui Zhang, Zheng Zhang, Webb Miller, and David J. Lipman (1997), "Gapped BLAST and PSI-BLAST: a new generation of protein database search programs", Nucleic Acids Res. 25:3389-3402.


Entrez and PubMed

These sites are maintained by the NCBI (National Center for Biotechnology Information:

http://www.ncbi.nlm.nih.gov).  PubMed contains the full Medline indexes freely available to the public.


Pedro's BioMolecular Research Tools
Pedro’s BioMolecular Research Tools

This site contains a plethora of biotechnology and molecular biology links, especially to services available through server programs over the World Wide Web.


 Using World Wide Web tools

 Automated links

0	    Restriction mapping

1	    BLAST

2	    PSI-BLAST

3	    PHI-BLAST

4	    Prosite pattern and profile scans

5	    nnPredict protein secondary structure prediction

6	 Other links

7	    ENTREZ and PubMed

8	    Pedro’s BioMolecular Research Tools

 Constructing World Wide Web bookmarks for BioEdit


Analysis tools incorporated into BioEdit
Incorporated into BioEdit

Amino Acid and Nucleotide Composition

0	    Entropy Plot

1	    Hydrophobicity Profiles

2	    Identity Matrix

3	    Nucleotide translation with codon usage

4	    Positional nucleotide numerical summary

5	    Search for conserved regions of an alignment

6	    Dot Plot of two sequence

7	    Pairwise sequence alignment

8	    RNA comparative analysis

9	    The basis of phylogenetic comparison

10	    Covariation

11	Using Covariation in BioEdit

12	   List output

13	   Table output

14	Covariation analysis preferences

15	The covariation algorithm

16	    Potential Pairings

17	Using Potential Pairings in BioEdit

18	   List Output

19	   Table output

20	Potential pairings analysis preferences

21	The potential pairings algorithm

22	    Mutual Information

23	        General Overview of mutual Information

24	        Mathematical Overview of Mutual Information

25	        Using Mutual Information in BioEdit

26	        Mutual Information Example

27	        Setting Mutual Information Preferences

28	        Using the Matrix Plotter for Mutual Information Data

29	       1-D plots of matrix data rows and columns

30	The Mutual Information Examiner

31	    Using Masks

32	    Setting preferences for BioEdit analysis tools


Masks

Masks are used to indicate a subsection of an alignment to be included in an analysis, at the exclusion of everything else.  For example, if you have an alignment of long RNA sequences and you want to do a comparative analysis on only a small region to decipher a localized secondary structure, you might want to exclude from the analysis the parts of the sequences that you do not want data for.  By specifying a mask prior to running covariation, potential pairings or mutual information analyses, you tell the program to report data only for specified positions.  Sometimes one wishes to analyze an RNA secondary structure element in a structure for which a standardized numbering system based on the structure from one organism exists (for example the RNase P RNA from E. coli is often used to number nearly universal positions for all bacterial RNase P RNAs).  For this purpose, a sequence may be set as a numbering mask, and positions of bases in a comparative analysis will be numbered to correspond to the numbering mask.  Often the numbering mask and sequence mask are the same.

Conventions used in BioEdit for masks:

For any mask, the three characters ‘-’, ‘~’ and ‘.’ (all gap indicators) designate that a position is not to be included in an analysis.

Any other character specifies that the position be included.

For masks created in BioEdit, a ‘*’ generally indicates inclusion, a ‘-’ indicates exclusion.

A mask might look like this:

-----**********-----**********-----

This specifies that the first 5 are excluded, the next 10 included, etc.

A sequence and numbering mask may be used simultaneously in an analysis, but neither one is a requirement.  If the numbering is set to mask numbering in an analysis preferences set, then there must be a numbering mask specified.

 To set a sequence as a mask or numbering mask, choose the “Set as Sequence Mask” or “Set as Numbering Mask” option under the “Sequence” menu.

To create a new mask, select the “Create New Mask” option under the “Sequence” menu.  The new mask will be created as a series of asterisks (e.g. “***********************************************”)

To toggle mask positions on or off, select the region to be toggled with the mouse, then choose “Toggle Mask” under the ”Sequence” menu.


BLAST Programs

BLAST offers the following programs:

blastn: Search a nucleotide database with a nucleotide query

blastp: Search protein database with a protein query

tblastn: Search a six-frame dynamic translation of a nucleotide database with a protein query

blastx: Search a protein database with a six-frame translation of a nucleotide query sequence.

tblastx: Search a six-frame translation of a nucleotide database with a six-frame translation of a nucleotide query sequence (very slow).


Setting preferences for analysis tools
Setting Preferences for BioEdit analysis tools

The dialog for preferences can be found under the “Options” menu under “Preferences”.  For preferences for each of the individual analyses see:

Covariation Preferences

Potential Pairings Preferences

Mutual Information Preferences

ORFs

Consensus Sequence

Pairwise Alignment

General (valid residue characters)

Preferences are automatically saved when the dialog is closed, unless the cancel button is pressed.


The basis of phylogenetic comparative analysis

Reproduced with permission from “Covariation”, the Macintosh Hypercard program by Dr. James W. Brown

Copyright © 1994, James W. Brown

This program can be found from the RNase P database:

http://jwbrown.mbio.ncsu.edu/RNaseP

The structures of RNAs are primarily defined by the interactions between nucleotide bases - in the simplest case, by Watson-Crick base-pairing between base pairs in a helix. The phylogenetic comparative method for analyzing RNA structure is based on the premise that the important secondary and tertiary structure in an RNA molecule remains the same despite changes in the nucleotide sequence of the RNA during evolution; any change in the sequence that might disrupt the structure is compensated for by change elsewhere in the sequence that allows the maintenance of the active structure. The homologous RNAs of different organisms will therefore contain "compensating base changes", or covariations. The structure of an RNA can therefore be elucidated by examination of homologous RNA sequences from a variety of organisms in order to identify such compensating base changes. For example, a given sequence, e.g. GAAGA, will have the potential to base pair with any UCUUC sequence within the RNA - such a sequence will most likely occur several times in that RNA. In order to identify which UCUUC sequence the GAAGA actually base pairs with (if any), the homologous nucleotides in the RNA from different organisms are examined in an attempt to identify compensating base changes:

                   *           x               x            *

0	organism #1 -----GAAGA---------UCUUC--------UCUUC---------UCUUC-------

1	organism #2 -----GAUGA---------UCUUC--------UCUGC---------UCAUC-------

2	organism #2 -----GAUGA---------GCUUC--------UCUAC---------UCAUC-------

3	organism #2 -----GACGA---------UCUUC--------UCUGC---------UCGUC-------

In the above example, only the last UCUUC (UCUUC in organism #1, that is) sequence changes to maintain the ability to base pair with the GAAGA sequence. Such compensating base changes at two positions in a potential helix are considered "proof" of the presence of that helix. Failure of two sequence to maintain complementarity suggests that the pairing do not occur.

0	The key to a phylogenetic comparative analysis of RNA structure is the alignment of the sequences - homologous nucleotides must be properly aligned. Homology is used here in its strictest sense - "homologous" nucleotides are defined as those which share a common ancestor. It is best therefore to begin by aligning closely related sequences, which can be aligned reliably on the basis of sequence similarity without the need for numerous alignment gaps. A handful of covariations between complementary sequences can usually be readily identified from these alignments, which starts the process of building of the secondary structure model. Starting with the beginning secondary structure model, more divergent sequences can be added to the alignment. This process is repeated by the sequential addition of new sequences & covariation analysis until both the alignment and secondary structure model emerge. A complete description of this process can be found in the references (see "More Information").

1	Once a complete secondary structure model is available, covariation analysis can be used to identify interactions between nucleotides that are not in helices (higher-order structure), non-canonical interactions, etc. Such interactions are identified because the associated nucleotides will vary in concert (i.e. covary), even if the do not form a canonical base pair or are part of a longer helix.


Entropy plots

An entropy plot can give an idea of the amount of variability through a column in an alignment.  It is a measure of the lack of “information content” at each position in the alignment.  More accurately, it is a measure of the lack of predictability for an alignment position.  If there are x sequences in an alignment (say x = 40 sequences) of DNA sequences, and at position y (say y = position 5) there is an ‘A’ in all sequences, we can assume we have a lot of information for position 5 and chances are if we had to guess at the base at position 5 of another homologous sequence, we would be correct to guess ‘A’.  We have maximum “information” for position 5, and the entropy is 0.  Now, if there are four possibilities for each position (A, G, C or T) and each occurs at position 5 with a frequency of 0.25 (equally probable), then our information content (how well we could predict the position for a new incoming sequence) has been reduced to 0, and the entropy is at maximum variability.

Information is often measured in bits, which are basically either/or (yes/no, on/off) units, or a base-2 number system.  If there are 4 possible residues at a given position, then two bits of information are required to determine the base at that position (e.g.., purine or pyrimidine? = 1 bit, if purine, ‘A’ or ‘G’? = 1 more bit -- 2 bits total).  For proteins (with 20 amino acids) at most 5 bits are required (e.g.. 1st 10? -- 1 bit, 1st 5 of block of 10? -- 1 more bit, 1st 3 of block of 5?, 1st 2 of 3?, 1st 1 or 2?: = 5 yes/no answers).  If a position in an alignment can take any of four positions, but always turns up ‘A’, we have no uncertainty at that position and therefore can say we have maximum (two bits) of information.

Mathematically, the basis of information theory was defined by Claude Shannon:

H(l) = -Σf(b,l)log(base 2)f(b,l)     (measured in bits)

where H(l) = the uncertainty, also called entropy at position l, b represents a residue (out of the allowed choices for the sequence in question), and f(b,l) is the frequency at which residue b is found at position l.  The information content of a position l, then, is defined as a decrease in uncertainty or entropy at that position.  As an alignment improves in quality, therefore, the entropy at each position (especially conserved regions) should decrease.

BioEdit plots the entropy at each position, rather than the information content, because, in order to determine information at a position, the total number of possible residues must be known.  This will vary depending on whether one wishes to include gaps or degenerate nucleotide bases such as S, M, K, W, etc. in the analysis.  For entropy plotting, the sequences are treated as a matrix of characters.  Entropy at a column position is independent of the total information possible at a given position, and depends only upon the frequencies of characters that appear in that column.  BioEdit uses the natural logarithm rather than log(base 2) for convenience, so the values are actually in nits rather than bits, but the data are the same relative to each other.  Entropy is then calculated as  H(l) = -Σf(b,l)ln(f(b,l)), which gives a measure of uncertainty at each position relative to other positions.  Maximum total uncertainty will be defined by the maximum number of different characters found in a column.  For example, if 20 amino acids and gaps are represented, but no user-defined characters are present, then the maximum uncertainty possible would be (21*(1/21)ln(1/21))=3.04 (if, say, there were 42 sequences in the alignment and each character was represented exactly twice at a given column position).  This measure is not given in bits.  Conversion to bits simply requires conversion to log base 2, however, and the entropy calculation could be made as:  H(l) = -Σf(b,l)*(ln(f(b,l)/ln2).  This is not really necessary, however, since the entropy differences across the alignment still compare the same relative to each other.

To perform an entropy plot, highlight the titles of the sequences you want included in the analysis, then choose “Entropy (Hx) Plot” from the “Alignment” menu of an open alignment document.  A graphical plot will be presented on one form and a numerical list of entropies by position will be displayed in a text editor.  If a mask is used, only the mask positions will be analyzed, and if a numbering mask is used, the numbers will reflect the corresponding true positions in the numbering mask.

Below is an example of an entropy plot:

1	Pierce, J.R. (1980).  An Introduction to Information Theory: Symbols, Signals and Noise, Dover Publications, Inc., New York. second edition.

2	Schneider, T.D. and R.M. Stephens. (1990) Sequence Logos: A new Way to Display Consensus Sequences. Nucleic Acids Res. 18: 6097-6100.


Identity Matrix

An identity matrix shows the proportion of identical residues between all of the sequences in the alignment as they are currently aligned.  The output is a 2-D matrix table which can either be tab-delimited or comma-delimited (*.csv).  The output depends completely upon the quality of the alignment.  The sequences are not automatically aligned before the procedure is run.  BioEdit offers ClustalW as a means of computer-aided alignment.

To produce an identity matrix, first select the sequences you would like included in the matrix (any 2 or more sequences may be included, and you don’t necessarily have to include the entire alignment).  If no sequences are selected, the entire alignment will be selected automatically.  After selecting the sequences to include, choose “Sequence Identity Matrix” from the “Alignment” menu.

Note: Sequence titles will be truncated to the first five characters.

Output: Following is an identity matrix generated for the sample file “sample1.gb” included with the BioEdit install:

This is an alignment of bacterial RNase P proteins.

Sequence Identity Matrix

Input Alignment File: I:\BioEdit\Bacterial_RNaseP_proteins.gb

Seq->	E.col	P.mir	H.inf	P.put	B.aph	C.bur	S.bik	S.coe	M.lut	M.tub	M.lep	B.sub	M.cap	M.pne	M.gen	B.bur	T.mar	T.pal	H.pyl	S.PCC

0	E.col	1.000	0.781	0.602	0.388	0.445	0.327	0.248	0.248	0.204	0.231	0.224	0.254	0.173	0.173	0.203	0.241	0.241	0.216	0.166	0.228

1	P.mir	 --- 	1.000	0.573	0.410	0.420	0.303	0.217	0.217	0.197	0.214	0.216	0.270	0.190	0.214	0.226	0.233	0.233	0.232	0.154	0.228

2	H.inf	 --- 	 --- 	1.000	0.370	0.375	0.251	0.191	0.184	0.142	0.166	0.183	0.215	0.123	0.173	0.177	0.212	0.204	0.176	0.143	0.194

3	P.put	 --- 	 --- 	 --- 	1.000	0.298	0.293	0.181	0.209	0.171	0.164	0.188	0.233	0.162	0.187	0.224	0.205	0.268	0.179	0.172	0.185

4	B.aph	 --- 	 --- 	 --- 	 --- 	1.000	0.213	0.132	0.156	0.094	0.132	0.128	0.278	0.206	0.198	0.210	0.177	0.243	0.168	0.135	0.204

5	C.bur	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.206	0.221	0.227	0.188	0.174	0.213	0.178	0.223	0.187	0.240	0.270	0.241	0.141	0.190

6	S.bik	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.878	0.424	0.344	0.320	0.217	0.144	0.195	0.152	0.156	0.204	0.165	0.154	0.218

7	S.coe	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.431	0.352	0.320	0.217	0.152	0.210	0.159	0.156	0.228	0.157	0.166	0.218

8	M.lut	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.272	0.272	0.207	0.159	0.171	0.120	0.119	0.177	0.140	0.151	0.214

9	M.tub	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.633	0.233	0.152	0.134	0.162	0.117	0.158	0.177	0.117	0.200

10	M.lep	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.201	0.155	0.146	0.112	0.121	0.145	0.187	0.129	0.171

11	B.sub	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.280	0.200	0.224	0.237	0.214	0.177	0.204	0.269

12	M.cap	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.158	0.223	0.198	0.237	0.137	0.147	0.176

13	M.pne	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.507	0.204	0.157	0.193	0.123	0.161

14	M.gen	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.196	0.193	0.170	0.172	0.190

15	B.bur	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.195	0.259	0.134	0.164

16	T.mar	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.227	0.123	0.214

17	T.pal	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.080	0.230

18	H.pyl	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000	0.128

19	S.PCC	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	 --- 	1.000

0	The score for each pair of sequences is generated as follows:

1	1.  All positions are compared directly for each pair of sequences, one at a time.

2	2.  All ‘gap’ or place-holding characters ( ‘-’, ‘~’, ‘.’, and ‘*’) are treated as a gap.

3	3.  Positions where both sequences have a gap do not contribute (they are not an identity, they simply don’t exist).

4	4.  Positions where there is a residue in one sequence and a gap in the other do count as a mismatch.

5	5.  The reported number represent the ratio of identities to the length of the longer of the two sequences  after positions where both sequences contain a gap are removed.

6	The above methodology should produce valid comparisons as long as the alignment is accurate.  When the sequences in an alignment are properly aligned, gaps are simply added to the ends of each sequence until all lengths match the longest sequence.


Restriction Maps

BioEdit offers two ways to generate restriction maps of nucleic acid sequences.  An internal restriction map utility allows generation of maps for sequences up to 65,536 nucleotides.  It has only really been tested up to about 35 Kb, and it takes a while on a slower computer for a large sequence.  You can also link directly to WebCutter restriction mapping via the World Wide Web.

WebCutter:   Highlight the title of the sequence you wish to map and choose “Auto-fed WebCutter Restriction Mapping” from the “World Wide Web” menu.

0	BioEdit:  Highlight the title of the sequence you wish to map and choose “Restriction Map” from the “Sequence” menu.  An interface window will appear with the following options:

1	-- Display Map: Display or omit a full map of the sequence and the complementary strand showing the cut positions of each enzyme.  Default: yes

2	-- Alphabetical by name: Display a list of all enzymes that cut, their recognition sequences, frequency of cutting, and all positions (5' end starting at 1).  Default: yes

3	-- Numeric by position: A list of all positions that are cut, in increasing order, and the enzymes that cut there.  Enzyme cut positions are defined at the cut site, rather than the start of the recognition sequence (e.g.. if a BamHI site  (G'GATC_C) started at position 1476, the cut position would be reported as 1477 -- where it actually cuts).  Default: no

4	-- List of unique sites: List of enzymes that cut only once in the entire sequence.  Default: no

5	-- Enzymes that cut five or fewer times.  Default: yes

6	-- Summary table of frequencies: A table of all enzymes currently selected and the number of times they cut in the sequence.  Default: no

7	-- Enzymes that do not cut.  Default: yes

8	-- 4-base cutters: You may choose to omit enzymes that cut at a 4-base recognition sequence.  To include these enzymes, the box must be checked.  Default: no (don’t include 4-base cutters).

9	-- 5-base cutters: Same as 4-base cutters.

10	-- Enzymes with degenerate recognition sequences: Many restriction enzymes recognize sequences loosely.  For example, AccI recognizes the sequence “GT'mk_AC”, where ‘m’ can be A or C and ‘k’ can be G or T.  You may wish to exclude these on occasion.  Default: include these.

11	-- Large recognition sites: Often for cloning, only the common 6-base recognizing enzymes are used.  If you do not want a map cluttered with extra information, uncheck this box (as well as 4-base and 5-base cutters).

12	-- All Isoschizomers: The enzyme list file used is the GCG-format file available from ReBase.  Several enzymes are in this file which cut the same recognition sequence of other enzymes in the file.  To show only one enzyme for a particular recognition site, uncheck this box (Default=unchecked).  If this option is chosen, the map will be very large.  Isoschizomers for all enzymes which you choose to include may be examined by viewing the enzyme table from the mapping interface (press the “View Current Enzyme Table” button).

13	-- Three frame translation: Shows a translation along the sequence as shown in the alignment (assumed to be in the 5' to 3' orientation left to right).

14	-- Translation of complement: A three-frame translation of the complementary strand running the opposite direction.

15	Considerations for BioEdit restriction mapper.

16	-- Numbering is at the nucleotide where the enzyme cuts, not the start of the recognition sequence.  This is important to keep in mind for enzymes such as AceIII, which recognizes the sequence “CAGCTCnnnnnnn'nnnn_”.  AceIII actually cuts 12 bps. downstream of its recognition sequence start.

17	-- The interface window is not an MDI child and is designed to stay on top of the application.  When a restriction map is generated, the window disappears, but the selected options remain as the default until the application is closed and reopened.  To view the enzyme list, the interface window must either be closed or minimized to see the table list behind it.

18	-- A different enzyme file may be supplied to BioEdit, but it must be in the GCG format, must be named “enzyme.tab” (case sensitive), and must be located in the \tables\ folder.

19	An example of the GCG format for restriction enzyme tables is:

REBASE version 811                                                gcgenz.811

0

1	    =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

2	    REBASE, The Restriction Enzyme Database   http://www.neb.com/rebase

3	    Copyright (c)  Dr. Richard J. Roberts, 1998.   All rights reserved.

4	    =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

5

6	Rich Roberts                                                      Oct 28 98

7

8	REBASE codes for commercial sources of restriction enzymes & methylases

9	                A        Amersham Life Sciences-USB (4/97)

10	                B        Life Technologies Inc. (1/98)

11	                C        Minotech Molecular Biology Products (1/98)

12	                D        Angewandte Gentechnologie Systeme (10/97)

13	                E        Stratagene (1/98)

14	                F        Fermentas AB (5/98)

15	                G        Appligene Oncor (10/97)

16	                H        American Allied Biochemical, Inc. (10/98)

17	                I        SibEnzyme Ltd. (10/98)

18	                J        Nippon Gene Co., Ltd. (10/97)

19	                K        Takara Shuzo Co. Ltd. (1/98)

20	                L        Kramel Biotech (7/98)

21	                M        Boehringer-Mannheim (10/97)

22	                N        New England BioLabs (8/98)

23	                O        Toyobo Biochemicals (1/98)

24	                P        Pharmacia Biotech Inc. (8/97)

25	                Q        CHIMERx (10/97)

26	                R        Promega Corporation (10/98)

27	                S        Sigma (7/98)

28	                T        Advanced Biotechnologies Ltd. (3/98)

29	..

30	AarI       3 CACCTGC        0 ? !                                    >	1667

31	;AatI      3 AGG'CCT        0 !  Eco147I,Pme55I,StuI,SseBI         >O	6643

32	AatII      5 G_ACGT'C      -4 !                                    >ADEFKLMNOPR	6643

33	;AauI      1 T'GTAC_A       4 !  Bsp1407I,BsrGI,SspBI              >I	6251

34	AccI       2 GT'mk_AC       2 !  FblI                              >ABDEGJKLMNOPQRS

35	;AccII     2 CG'CG          0 !  BstUI,MvnI,ThaI,Bsh1236I          >AJKQ	3992,7430

36	;AccIII    1 T'CCGG_A       4 !  BseAI,BsiMI,Bsp13I,BspEI,Kpn2I,MroI  >EJKQR	3994,5140

0	... and on like this -- the file simply ends after the last enzyme.


Covariation

Using Covariation from BioEdit.

Setting Covariation analysis preferences.

The covariation algorithm

Covariation refers to the situation where two residues in a sequence vary in concert.  Strictly speaking, this means that whenever position ‘x’ varies from the norm in an alignment, position ‘y’ also varies, and that the variation is consistent (for example, if ‘x’ changes to ‘A’ and ‘y’ to ‘T’, then every time ‘x’ is an ‘A’ ‘y’ must be a ‘T’).  Covariation between residues suggests that there might be an essential interaction between them and that nature has selected for compensatory mutations when mutations in important structural residues have occurred (see The basis of phylogenetic comparative analysis ).

Covariation example:

Let’s say we have an alignment of sequences that represent a particular RNA with a conserved secondary structure from several different organisms.  We want to use information contained in the alignment to deduce something about the secondary structure of this RNA.  As an example, take this short segment of an alignment:

             ....|....| ....|....| ....|....

0	                      10         20

sample 1     CCGGAUACGA UCGUCGGGUA CGUAUCCGG

0	sample 2     CCGGAUACUA UCUUGGCGAA AGUAUCUGG

1	sample 3     CGGGAUACGA UCGACGCGUA CGUAUCCCG

2	sample 4     CGCGGUACCA UCCACCCCUA GGUACCGCG

3	sample 5     CCGGAUACGA UCGUCCCGUU CGUAUCCGG

4	sample 6     CCGGAUACGA UCGUCGGGUA CGUAUCCGG

5	sample 7     CCGGACACGA UCGUCGGGUA CGUAUCCGG

6	sample 8     CCAGAUACGA UCGAAACUUU CGUAUCUGG

7	sample 9     CCGGUUACCA UCGUCGGGUA GGUAACCGG

8	sample 9     CCGGAUACGA UCGACAGGAA CGUAUCCGG

9	sample 10    CCGGAUACGA UCGUCCCGUA CGUAUCCGG

10	sample 11    CCGGAUACGA UCGUCGGGUA CGUAUCCGG

11	sample 12    CCUGAUACUA UCGUCGCCUA AGUAUCGGG

12	sample 13    CGGGGUACGA UCGAGGCCUA CGUACCCCG

13	sample 14    CCCGCUACGA UCGAGGCCUU CGUAGCGGG

14	sample 15    CCGGAUACGA UCGAGGCCUU CGUAUCCGG

0	Covariation analysis

1	Input file: I:\BioEdit\help\samples.gb

2	Position numbering is relative to the alignment numbering.

3	No mask was used.

4	1     CCCCCCCCCCCCCCCC

5	------------------------

6	Position 2:

7	------------------------

8	2     CCGGCCCCCCCCCGCC

9	28    GGCCGGGGGGGGGCGG    All potential Watson Crick or G-U pairs

10	------------------------

11	3     GGGCGGGAGGGGUGCG

12	------------------------

13	4     GGGGGGGGGGGGGGGG

14	------------------------

15	Position 5:

16	------------------------

17	5     AAAGAAAAUAAAAGCA

18	25    UUUCUUUUAUUUUCGU    All potential Watson Crick or G-U pairs

19	------------------------

20	6     UUUUUUCUUUUUUUUU

21	------------------------

22	7     AAAAAAAAAAAAAAAA

23	------------------------

24	8     CCCCCCCCCCCCCCCC

25	------------------------

26	Position 9:

27	------------------------

28	9     GUGCGGGGCGGGUGGG

29	21    CACGCCCCGCCCACCC    All potential Watson Crick or G-U pairs

30	------------------------

31	10    AAAAAAAAAAAAAAAA

32	------------------------

33	11    UUUUUUUUUUUUUUUU

34	------------------------

35	12    CCCCCCCCCCCCCCCC

36	------------------------

37	13    GUGCGGGGGGGGGGGG

38	------------------------

39	14    UUAAUUUAUAUUUAAA

40	------------------------

41	15    CGCCCCCACCCCCGGG

42	------------------------

43	16    GGGCCGGAGACGGGGG

44	------------------------

45	17    GCCCCGGCGGCGCCCC

46	------------------------

47	18    GGGCGGGUGGGGCCCC

48	------------------------

49	19    UAUUUUUUUAUUUUUU

50	------------------------

51	20    AAAAUAAUAAAAAAUU

52	------------------------

53	Position 21:

54	------------------------

55	21    CACGCCCCGCCCACCC

56	9     GUGCGGGGCGGGUGGG    All potential Watson Crick or G-U pairs

57	------------------------

58	22    GGGGGGGGGGGGGGGG

59	------------------------

60	23    UUUUUUUUUUUUUUUU

61	------------------------

62	24    AAAAAAAAAAAAAAAA

63	------------------------

64	Position 25:

65	------------------------

66	25    UUUCUUUUAUUUUCGU

67	5     AAAGAAAAUAAAAGCA    All potential Watson Crick or G-U pairs

68	------------------------

69	26    CCCCCCCCCCCCCCCC

70	------------------------

71	27    CUCGCCCUCCCCGCGC

72	------------------------

73	Position 28:

74	------------------------

75	28    GGCCGGGGGGGGGCGG

76	2     CCGGCCCCCCCCCGCC    All potential Watson Crick or G-U pairs

77	------------------------

78	29    GGGGGGGGGGGGGGGG

------------------------

0	There are 3 pairs of  positions that “covary” in this alignment section: 2/28, 5/25 and 9/21.  When two bases covary, there is a strong possibility that they interact.  When a mutation occurs in a base that makes an important contact with another nucleotide (usually a base pair), selection pressure may dictate that only instances where the other base shows a compensatory change survive.  The covariations in the three pairs of bases above suggest that theses bases may interact.  The fact that they all involve bases that can form canonical base pairings (Watson-Crick, or G-U for RNA),  suggests that they may base-pair.  Residues 2 and 5 are the same distance apart as 5 and 25, and 5 and 25 are the same distance apart as 9 and 21.  By looking at the alignment, we can see that these intervening bases can also form base-pairs, suggesting that the two ends of this alignment may be joined in a helix, as shown below for the sequence “sample 1":

1

                      U C

0	                    A     G

1	-- C C G G A T A C G       U

2	-- G G C C T A T G C       C

3	                    A     G

4	                     U G G

The other bases along the helix are invariant.  Comparative analysis at these positions does not provide direct evidence of interaction.  However, combined with analysis of potential pairings, the positions of these residues suggests that they may be involved in helix base-pairing.

0	Using Covariation from BioEdit.

1	Setting Covariation analysis preferences.

2	The covariation algorithm

3	Brown, J.W.  1991.  Phylogenetic comparative analysis on Macintosh computers.   Comput. Appl. Biosci.  7(3):391-393.

4	Gutell, R.R. 1985.  Comparative anatomy of 16-S-like ribosomal RNA.  Prog. Nucl. Acids Res. Mol. Biol.  32:155-216.


Using Covariation in BioEdit

BioEdit provides two basic output formats for covariation data: list format or table format.

Click on either of the above for a description and example of each format.

The output is raw text for both.  Table formats may be tab delimited or comma delimited.  Tab delimited files are best if the table will be viewed in a text editor.  Comma delimited files (*.csv) allow easy importing into a spreadsheet such as Microsoft Excel (most also read tab delimited files).  Files may be written in PC or Macintosh format.

To perform a covariation analysis from a BioEdit alignment document:

1.  Set the preferences you want (file format, output type -- you may choose to output both a list and table if you want).

2.  If you want to analyze only a portion of the alignment, create a mask (or set an existing sequence to be a mask).  If you would like to analyze only a portion of the alignment, but would like the numbering of alignment positions to match the number of a standard sequence (must be included in the alignment), set that sequence as the numbering mask).

3.  Select all the sequences you want included in the analysis.  Only selected sequences will be analyzed.  If there is a mask specified that is not an actual sequence, you will want to exclude it from the analysis.  If no sequences are selected, all sequences in the document will be automatically selected.

4.  Run Covariation from the “RNA” menu. You will be prompted for the name(s) of the output file(s).  If you choose to generate a list, it will be opened for you in the BioEdit text editor.

Considerations for each format:

List files can be quite long.  each column is printed out as a string and for each two columns which covary, the two columns are printed one on top of the other.  If only the positions are desired, this may be specified in the preferences.  Also, the option to show or exclude output of columns for invariant positions is offered.

Table format: A table is often nice to look at in a spreadsheet on-screen, but is often not very convenient for printing out, especially when the analysis is fairly large.


Covariation Tables

Covariation tables are formatted as a 2-dimensional matrix of alignment positions (each position compared to every other position).  When two positions covary, a ‘5' is placed at the matrix intersection of the two positions.  If both of the positions are invariant, a ‘1' is placed in that position.  When they are not both invariant and do not covary, a 0 is placed at their intersection.

0	As an example, take the following short alignment:

             ....|....| ....|....| ....|....

                      10         20

0	sample 1     CCGGAUACGA UCGUCGGGUA CGUAUCCGG

1	sample 2     CCGGAUACUA UCUUGGCGAA AGUAUCCGG

2	sample 3     CGGGAUACGA UCGACGCGUA CGUAUCCCG

3	sample 4     CGGGGUACCA UCCACCCCUA GGUACCCCG

4	sample 5     CCGGAUACGA UCGUCCCGUU CGUAUCCGG

5	sample 6     CCGGAUACGA UCGUCGGGUA CGUAUCCGG

6	sample 7     CCGGAUACGA UCGUCGGGUA CGUAUCCGG

7	sample 8     CCGGAUACGA UCGAAACUUU CGUAUCCGG

8	sample 9     CCGGUUACCA UCGUCGGGUA GGUAACCGG

9	sample 9     CCGGAUACGA UCGACAGGAA CGUAUCCGG

10	sample 10    CCGGAUACGA UCGUCCCGUA CGUAUCCGG

11	sample 11    CCGGAUACGA UCGUCGGGUA CGUAUCCGG

12	sample 12    CCGGAUACUA UCGUCGCCUA AGUAUCCGG

13	sample 13    CGGGGUACGA UCGAGGCCUA CGUACCCCG

14	sample 14    CCGGCUACGA UCGAGGCCUU CGUAGCCGG

15	sample 15    CCGGAUACGA UCGAGGCCUU CGUAUCCGG

0	Table output of covariation data would look like this (larger tables will appear wrapped in a word processor, but may be viewed unwrapped in an editor such as WordPad):

Covariation analysis

0	Input file: D:\BioEdit\help\samples.gb

1	Matrix Output

2	5 = Covariation, 1 = Invariant

3	Position numbering is relative to the alignment numbering.

4	No mask was used.

5	   1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

6	1  0  0  1  1  0  1  1  1  0  1  1  1  0  0  0  0  0  0  0  0  0  1  1  1  0  1  1  0  1

7	2  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  5  0

8	3  1  0  0  1  0  1  1  1  0  1  1  1  0  0  0  0  0  0  0  0  0  1  1  1  0  1  1  0  1

9	4  1  0  1  0  0  1  1  1  0  1  1  1  0  0  0  0  0  0  0  0  0  1  1  1  0  1  1  0  1

10	5  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  5  0  0  0  0

11	6  1  0  1  1  0  0  1  1  0  1  1  1  0  0  0  0  0  0  0  0  0  1  1  1  0  1  1  0  1

12	7  1  0  1  1  0  1  0  1  0  1  1  1  0  0  0  0  0  0  0  0  0  1  1  1  0  1  1  0  1

13	8  1  0  1  1  0  1  1  0  0  1  1  1  0  0  0  0  0  0  0  0  0  1  1  1  0  1  1  0  1

14	9  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  5  0  0  0  0  0  0  0  0

15	10 1  0  1  1  0  1  1  1  0  0  1  1  0  0  0  0  0  0  0  0  0  1  1  1  0  1  1  0  1

16	11 1  0  1  1  0  1  1  1  0  1  0  1  0  0  0  0  0  0  0  0  0  1  1  1  0  1  1  0  1

17	12 1  0  1  1  0  1  1  1  0  1  1  0  0  0  0  0  0  0  0  0  0  1  1  1  0  1  1  0  1

18	13 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0

19	14 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0

20	15 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0

21	16 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0

22	17 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0

23	18 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0

24	19 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0

25	20 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0

26	21 0  0  0  0  0  0  0  0  5  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0

27	22 1  0  1  1  0  1  1  1  0  1  1  1  0  0  0  0  0  0  0  0  0  0  1  1  0  1  1  0  1

28	23 1  0  1  1  0  1  1  1  0  1  1  1  0  0  0  0  0  0  0  0  0  1  0  1  0  1  1  0  1

29	24 1  0  1  1  0  1  1  1  0  1  1  1  0  0  0  0  0  0  0  0  0  1  1  0  0  1  1  0  1

30	25 0  0  0  0  5  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0

31	26 1  0  1  1  0  1  1  1  0  1  1  1  0  0  0  0  0  0  0  0  0  1  1  1  0  0  1  0  1

32	27 1  0  1  1  0  1  1  1  0  1  1  1  0  0  0  0  0  0  0  0  0  1  1  1  0  1  0  0  1

33	28 0  5  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0

34	29 1  0  1  1  0  1  1  1  0  1  1  1  0  0  0  0  0  0  0  0  0  1  1  1  0  1  1  0  0

0	Where two positions covary, a 5 is placed at their intersection.  When there is no covariation, there is a 0.  A  1' indicated a pair of columns where both are invariant.  Sometimes it is useful to look at these positions along with the covariation data to see if invariant positions that fall in line with covarying pairs are able to form base pairs.  This type of information can also be gathered in an analysis of potential pairings.  A comma-delimited file may also be produced which allows easy opening in a spreadsheet program such as Microsoft Excel or Quattro Pro.


Covariation List

     An example of covariation list output is shown in the main section of covariation.  Covariation lists may be written with the following options:

-- Show nucleotides or show positions only:

Show nucleotides: Reports the each column of the alignment (position) as a string of nucleotide bases.

Show positions only: Only shows the positions of pairs of positions that covary.  This is useful if you want a small file and will be looking at a printout of the alignment or viewing it on-screen.

Position-only output of the same analysis shown in the example would be:

0	2, 28    All potential Watson Crick or G-U pairs

1	5, 25    All potential Watson Crick or G-U pairs

2	9, 21    All potential Watson Crick or G-U pairs

3	21, 9    All potential Watson Crick or G-U pairs

4	25, 5    All potential Watson Crick or G-U pairs

5	28, 2    All potential Watson Crick or G-U pairs

0	Often this is much easier to look at.


Setting Covariation Preferences

The covariation preferences dialog may be brought up by choosing “Preferences” from the “Options” menu:

Both list and table formats may be chosen at the same time.  Mask numbering will cause the reported position numbers to match the true position numbers of the selected numbering mask.

Reporting nucleotides compared to positions only is explained in covariation lists.


The Covariation Algorithm

The covariation algorithm is quite simple.  Two positions are said to covary if they both show at least some variation through the alignment (are not invariant) and follow an identical pattern (vary in perfect concert).  The algorithm works like this:

1. The alignment is divided up into vertical columns (an alignment is really a 2-D matrix of characters with rows and columns of characters).

2.  Each column is converted to a string of numbers in the following manner:

a.  The first residue in each column is assigned the number 1.

b.  If the next residue is the same as the first, it is assigned number 1, otherwise it is assigned 2.

c.  As each characters in each column is examined one at a time, if it is unique (the first occurrence of that character in that column), it is assigned the next untaken integer, otherwise it is given the same number as the previous occurrence of that character.

d.  When this is done, columns that represent invariant positions will be strings of all 1's.  Two positions that covary (vary in exact concert) will have an identical pattern of numbers.

Example: Take the following four columns:

A C G G

A C G G

A C G G

A A U G

A G C C

A C G C

A C G C

A U A C

A C G G

A A U G

The number string representations for these would be:

1.  1111111111

2.  1112311412

3.  1112311412

4.  1111222211

Position 1 is invariant and is represented by all 1's.  Positions 2 and 3 covary and result in the same string of numbers.  Position 4 does not covary with 1, 2 or 3.  This algorithm is easily implemented by comparing strings for an exact match.  It is the simple and quick, but it does not allow for any exceptions in the pattern (for example, an A-T pair might change to a G-C in one sequence and a G-U in another -- this would be missed by covariation).  On the other hand, it does not depend on guessing at which interactions are likely and may pick out necessary tertiary interactions in large sequence sets.

Brown, J.W.  1991.  Phylogenetic comparative analysis on Macintosh computers.   Comput. Appl. Biosci.  7(3):391-393.

Gutell, R.R. 1985.  Comparative anatomy of 16-S-like ribosomal RNA.  Prog. Nucl. Acids Res. Mol. Biol.  32:155-216.


Potential Pairings

Using potential pairings in BioEdit

Setting potential pairings preferences

The potential pairings algorithm

When two nucleotides in an RNA molecule have a necessary base-pairing interaction, sometimes a compensatory base change to more than one particular nucleotide is sufficient to complement a mutation (for example, an A-U pair may mutate to a G-C in one sequence and to a G-U in another).  This type of interaction will be missed by a covariation analysis because the variation will not follow an identical pattern at each position.  An analysis of positions that have the ability to form pairs conforming to a set of allowed choices (set in the preferences dialog) will allow the identification of these positions.

Potential pairings, as implemented in BioEdit, does not require that the positions show any variation, and so invariant positions which can form base pairs will also be reported.  The option to filter out invariant-invariant pairings is offered in the preferences setup screen.

Using the same sample alignment as used in the covariation example:

             ....|....| ....|....| ....|....

                      10         20

sample 1     CCGGAUACGA UCGUCGGGUA CGUAUCCGG

sample 2     CCGGAUACUA UCUUGGCGAA AGUAUCUGG

sample 3     CGGGAUACGA UCGACGCGUA CGUAUCCCG

sample 4     CGCGGUACCA UCCACCCCUA GGUACCGCG

sample 5     CCGGAUACGA UCGUCCCGUU CGUAUCCGG

sample 6     CCGGAUACGA UCGUCGGGUA CGUAUCCGG

sample 7     CCGGACACGA UCGUCGGGUA CGUAUCCGG

sample 8     CCAGAUACGA UCGAAACUUU CGUAUCUGG

sample 9     CCGGUUACCA UCGUCGGGUA GGUAACCGG

sample 9     CCGGAUACGA UCGACAGGAA CGUAUCCGG

sample 10    CCGGAUACGA UCGUCCCGUA CGUAUCCGG

sample 11    CCGGAUACGA UCGUCGGGUA CGUAUCCGG

sample 12    CCUGAUACUA UCGUCGCCUA AGUAUCGGG

sample 13    CGGGGUACGA UCGAGGCCUA CGUACCCCG

sample 14    CCCGCUACGA UCGAGGCCUU CGUAGCGGG

sample 15    CCGGAUACGA UCGAGGCCUU CGUAUCCGG

An analysis of potential pairings allowing for A-U, G-C and G-U base pairs with 1 mismatch would yield the following (list format, filtered to ignore potential pairings between two invariant positions).  Examination of this data compared to the sample output for covariation reveals a possible base-pair between positions 3 and 27 which is not picked up by the covariation algorithm.  Potential pairing data may also be written as a numerical table (2-D matrix) of either frequency of allowed pairings or raw number of allowed pairings between each pair of positions.

Potential Pairings List

Input File: I:\BioEdit\help\samples.gb

Allowed Mispairings = 1

16 total sequences, 29 nucleotides per sequence.

Axes reflect numbering of the entire alignment.

No Mask was used.

Hits on invariant pairs have been filtered out.

------------------------

1    CCCCCCCCCCCCCCCC

------------------------

Position: 2

------------------------

2    CCGGCCCCCCCCCGCC

28   GGCCGGGGGGGGGCGG   0 mis-matches

------------------------

Position: 3

------------------------

3    GGGCGGGAGGGGUGCG

27   CUCGCCCUCCCCGCGC   0 mis-matches

------------------------

Position: 4

------------------------

4    GGGGGGGGGGGGGGGG

6    UUUUUUCUUUUUUUUU   0 mis-matches

------------------------

Position: 5

------------------------

5    AAAGAAAAUAAAAGCA

25   UUUCUUUUAUUUUCGU   0 mis-matches

------------------------

Position: 6

------------------------

6    UUUUUUCUUUUUUUUU

4    GGGGGGGGGGGGGGGG   0 mis-matches

------------------------

6    UUUUUUCUUUUUUUUU

7    AAAAAAAAAAAAAAAA   1 mis-matches

------------------------

6    UUUUUUCUUUUUUUUU

10   AAAAAAAAAAAAAAAA   1 mis-matches

------------------------

6    UUUUUUCUUUUUUUUU

22   GGGGGGGGGGGGGGGG   0 mis-matches

------------------------

6    UUUUUUCUUUUUUUUU

24   AAAAAAAAAAAAAAAA   1 mis-matches

------------------------

6    UUUUUUCUUUUUUUUU

29   GGGGGGGGGGGGGGGG   0 mis-matches

------------------------

Position: 7

------------------------

7    AAAAAAAAAAAAAAAA

6    UUUUUUCUUUUUUUUU   1 mis-matches

------------------------

8    CCCCCCCCCCCCCCCC

------------------------

Position: 9

------------------------

9    GUGCGGGGCGGGUGGG

21   CACGCCCCGCCCACCC   0 mis-matches

------------------------

Position: 10

------------------------

10   AAAAAAAAAAAAAAAA

6    UUUUUUCUUUUUUUUU   1 mis-matches

------------------------

11   UUUUUUUUUUUUUUUU

------------------------

12   CCCCCCCCCCCCCCCC

------------------------

13   GUGCGGGGGGGGGGGG

------------------------

14   UUAAUUUAUAUUUAAA

------------------------

15   CGCCCCCACCCCCGGG

------------------------

16   GGGCCGGAGACGGGGG

------------------------

17   GCCCCGGCGGCGCCCC

------------------------

18   GGGCGGGUGGGGCCCC

------------------------

19   UAUUUUUUUAUUUUUU

------------------------

20   AAAAUAAUAAAAAAUU

------------------------

Position: 21

------------------------

21   CACGCCCCGCCCACCC

9    GUGCGGGGCGGGUGGG   0 mis-matches

------------------------

Position: 22

------------------------

22   GGGGGGGGGGGGGGGG

6    UUUUUUCUUUUUUUUU   0 mis-matches

------------------------

23   UUUUUUUUUUUUUUUU

------------------------

Position: 24

------------------------

24   AAAAAAAAAAAAAAAA

6    UUUUUUCUUUUUUUUU   1 mis-matches

------------------------

Position: 25

------------------------

25   UUUCUUUUAUUUUCGU

5    AAAGAAAAUAAAAGCA   0 mis-matches

------------------------

26   CCCCCCCCCCCCCCCC

------------------------

Position: 27

------------------------

27   CUCGCCCUCCCCGCGC

3    GGGCGGGAGGGGUGCG   0 mis-matches

------------------------

Position: 28

------------------------

28   GGCCGGGGGGGGGCGG

2    CCGGCCCCCCCCCGCC   0 mis-matches

------------------------

Position: 29

------------------------

29   GGGGGGGGGGGGGGGG

6    UUUUUUCUUUUUUUUU   0 mis-matches

------------------------

Using potential pairings in BioEdit

Setting potential pairings preferences

The potential pairings algorithm

Brown, J.W.  1991.  Phylogenetic comparative analysis on Macintosh computers.   Comput. Appl. Biosci.  7(3):391-393.


Using Potential Pairings in BioEdit

BioEdit provides two basic output formats for potential pairings data: lists or table format.

Click on either of the above for a description and example of each format.

The output is raw text for both.  Table formats may be tab delimited or comma delimited.  Tab delimited files are best if the table will be viewed in a text editor.  Comma delimited files (*.csv) allow easy importing into a spreadsheet such as Microsoft Excel (most also read tab delimited files).  Files may be written in PC or Macintosh format.

To perform a potential pairings analysis from a BioEdit alignment document:

1.  Set the preferences you want (file format, output type -- you may choose to output both a list and table if you want).

2.  Before staring, you will also want to decide which pairings are to be allowed.  By default, allowed pairings are initially set to A-T, C-G and G-U, but whenever preferences are saved from the preferences dialog, these become the new defaults.

3.  If you want to analyze only a portion of the alignment, create a mask (or set an existing sequence to be a mask).  If you would like to analyze only a portion of the alignment, but would like the numbering of alignment positions to match the number of a standard sequence (must be included in the alignment), set that sequence as the numbering mask).

4.  Select all the sequences you want included in the analysis.  Only selected sequences will be analyzed.  If there is a mask specified that is not an actual sequence, you will want to exclude it from the analysis.  If no sequences are selected, all sequences in the document will be automatically selected.

5.  Run “Potential Pairings” from the “RNA” menu of an open alignment document. You will be prompted for the name(s) of the output file(s).  If you choose to generate a list, it will be opened for you in the BioEdit text editor.

Considerations for each format:

List files can be quite long.  Invariant positions are shown and can often produce many redundant matches that most likely don’t mean anything.  For this reason, pairings between two invariant positions may be filtered out.

Table format: A table is often nice to look at in a spreadsheet on-screen, but is often not very convenient for printing out, especially when the analysis is fairly large.


Setting Preferences for Potential Pairings

To bring up the potential pairings preferences, choose “Preferences” from the “Options” menu and click on the tab for potential pairings:

For a particular type of base pair to be allowed, it must be checked in the preferences dialog prior to running the analysis.  The general default allowed pairings are the canonical A-T, G-C and G-U base pairs commonly seen in RNA helices.  It is also recommended to allow gap-gap pairings, since gaps represent the absence of a position in a sequence that is homologous to the other sequences in the alignment.  Just because this position does not exist in some sequences does not mean that it does not form a defined structure in those sequences that have it.  If gap-gap matches are not allowed, these positions will be seen as mismatches rather than the absence of residues.  Like covariation, position numbering may be according to the numbering of the entire alignment, or to a specified numbering mask.  When setting any preferences, pressing Save Preferences will cause all preferences in the preferences dialog (all four sheets) to be saved as the default.

     If the Numerical table option is checked, a 2-D matrix will be saved with either the raw number of potential pairings for each pair of positions (Integer choice) or the frequency (matches/total sequences) of potential pairings for each position.


Potential pairings list
Potential pairings Lists

An example of list output for a potential pairings is shown in the main section of potential pairings.  If you do not wish to show all the nucleotides, and do not want positions displayed that have no potential pairings matches to other positions, choose the “positions only” option in the preferences dialog.  An example of list output with the positions only option chosen for the sample alignment shown in the main section of potential pairings is shown below.  The option is also offered to filter out matches between two invariant positions.

------------------------

Position: 1

------------------------

4     0 mis-matches

22    0 mis-matches

29    0 mis-matches

Position: 2

------------------------

28    0 mis-matches

Position: 3

------------------------

27    0 mis-matches

Position: 4

------------------------

1     0 mis-matches

6     0 mis-matches

8     0 mis-matches

11    0 mis-matches

12    0 mis-matches

23    0 mis-matches

26    0 mis-matches

Position: 5

------------------------

25    0 mis-matches

Position: 6

------------------------

4     0 mis-matches

7     1 mis-matches

10    1 mis-matches

22    0 mis-matches

24    1 mis-matches

29    0 mis-matches

Position: 7

------------------------

6     1 mis-matches

11    0 mis-matches

23    0 mis-matches

Position: 8

------------------------

4     0 mis-matches

22    0 mis-matches

29    0 mis-matches

Position: 9

------------------------

21    0 mis-matches

Position: 10

------------------------

6     1 mis-matches

11    0 mis-matches

23    0 mis-matches

Position: 11

------------------------

4     0 mis-matches

7     0 mis-matches

10    0 mis-matches

22    0 mis-matches

24    0 mis-matches

29    0 mis-matches

Position: 12

------------------------

4     0 mis-matches

22    0 mis-matches

29    0 mis-matches

Position: 21

------------------------

9     0 mis-matches

Position: 22

------------------------

1     0 mis-matches

6     0 mis-matches

8     0 mis-matches

11    0 mis-matches

12    0 mis-matches

23    0 mis-matches

26    0 mis-matches

Position: 23

------------------------

4     0 mis-matches

7     0 mis-matches

10    0 mis-matches

22    0 mis-matches

24    0 mis-matches

29    0 mis-matches

Position: 24

------------------------

6     1 mis-matches

11    0 mis-matches

23    0 mis-matches

Position: 25

------------------------

5     0 mis-matches

Position: 26

------------------------

4     0 mis-matches

22    0 mis-matches

29    0 mis-matches

Position: 27

------------------------

3     0 mis-matches

Position: 28

------------------------

2     0 mis-matches

Position: 29

------------------------

1     0 mis-matches

6     0 mis-matches

8     0 mis-matches

11    0 mis-matches

12    0 mis-matches

23    0 mis-matches

26    0 mis-matches


Potential pairings Table

Potential pairings data can also be output as a numerical 2-D matrix, with the intersection of each two positions containing either the number of sequences in which they can form an allowed pair, or the frequency with which they form an allowed pair.  A table of potential pairings data will be formatted in the same manner as a covariation table.


The Potential Pairings Algorithm

The basic algorithm for potential pairings analysis is very straightforward and is essentially a brute-force examination of every position compared to every other position in an alignment against a set of allowed pairings.

Computationally, BioEdit approaches this numerically by assigning each nucleotide in each sequence an integer value as follows:

A   = 2

G   = 3

C   = 5

U   = 9

GAP = 14

The sum of any two pairs of these numbers is unique (including each one paired to itself):

A+A = 4

A+C = 7

A+G = 5

A+U = 11

A+GAP =16

C+C = 10

C+G = 8

C+U = 14

C+GAP = 19

G+G = 6

G+U = 12

G+GAP = 17

U+U = 18

U+GAP = 23

GAP+GAP = 28

An array of 28 values which can take the value 1 or 0  is thus set up such that each of the above sums represents the index to an array position holding a value which states that the pair is allowed (1) or not allowed (0).  As the residues are scanned for each pair of column positions in the alignment, the value present at the array index of the sum of the two position residues for each sequence is added to a total sum for that pair of positions (1 is added if the pair is a match, otherwise 0 is added).  If the total for a pair of positions is greater than or equal to the required number (depends upon mismatches allowed), the potential pairing is reported in the output (for table output, the total or total/number of sequences is reported for all positions).


Mutual Information Analysis

Before using mutual information as a structure probe, you probably want to read:

Gutell, R.R., A. Power, G.Z. Hertz, E.J. Putz and G.D. Stormo. 1992. Identifying constraints on the higher-order structure of RNA: continued development and application of comparative sequence analysis methods.  Nucleic Acids Res. 20(21):5785-5795.

General Overview of mutual Information

Mathematical Overview of Mutual Information

Using Mutual Information in BioEdit

Mutual Information Example

Setting Mutual Information Preferences

Using the Matrix Plotter for Mutual Information Data

1-D plots of matrix data rows and columns

The Mutual Information Examiner


General Overview of Mutual Information

     Mutual information, as applied to phylogenetic comparative analysis,  is a measure of the amount of information shared by two positions in a set of properly aligned sequences.  This measurement, symbolized as M(x,y) (the mutual information shared by positions x and y), gives an idea of how strongly the identities of two positions are correlated, which is often a sign of direct interaction such as base-pairing.  Two other measurements that BioEdit will calculate, R1 and R2, give a measure of the contribution made by positions x and y to M(x,y).  These measurements are described at the end of mathematical overview of mutual information.

General Overview -- What is mutual information?

     Mutual information analysis is an extension of the idea that  information content may be assessed as a general decrease in uncertainty about a particular situation.  Given no prior knowledge about a particular situation (such as the identity of a nucleotide in an RNA sequence), uncertainty is at a maximum and one possesses no information about that situation.  If the identity of the nucleotide is discovered, uncertainty is removed and information about that nucleotide is at a maximum.  Now consider a large set of sequences, all of which contain a homologous nucleotide at this position.  Knowing the nucleotide’s identity in the first sequence does not necessary offer much information about the same position in the next sequence or a randomly chosen sequence.  However, if the identity of this residue is known in many sequences, and in nearly all of these sequences it is a particular base (say ‘C’), and is never a particular other residue (say ‘G’), uncertainty drops way down about the possible identity of this base in an as yet unexamined sequence.  There is now considerable “information” accumulated about this base which can be used to predict the probability of its identity being a particular base if a new sequence is examined.  This is the basis of the sequence logo (1) or the BioEdit implementation of an entropy plot.

     Mutual information extends this basic principal to examine the information content shared between a pair of positions in an alignment.  This is related to, and depends upon, the information content of two individual positions, but refers specifically to the information that the two positions possess together.  More generally, it is a measure of the decrease in uncertainty about the extent to which two things influence each other, or interact with each other.  The use of mutual information to probe RNA structure was developed by Robin Gutell (2).  This measure is ideally suited to phylogenetic comparative analysis because a high degree of mutual influence between two positions may be a strong indication that these two residues directly interact.

     As an example, examine the following small piece of an alignment:

     1 2 3 4

  A C G U

  A C G U

  A G C U

  A U A U

  A U A U

  A A U U

  A A U U

  A G C U

There are 8 total sequences.  Positions 1 and 4 are invariant.  The information content at each of these two bases is maximum (we could feel pretty certain about the identity of the next sequence if we had to guess).  Bases 2 and 3 are both evenly divided between A, G, C and U.  The information content of each of these positions would be zero, since we would have no idea which of four bases to choose if we had to guess them for a new sequence.  The shared information between any of these bases, however, is different.  The shared information (mutual information) refers to our decrease in uncertainty about how much the identity of one base influences the identity of another.  Although we have a lot of information about the identities of bases 1 and 4, we have no way of determining if and how much they influence each other (because they never change, and so there is no chance to test this).  The mutual information shared between them is thus zero.  On the other hand, although bases 2 and 3 each individually carry essentially no information, together they share a certain amount of information about how they influence each other.  If asked to guess the identity of position 2 in a new sequence, I couldn’t.  But, if I was told that position 3 was a ‘C’, I would have a strong feeling now that position 2 would be a ‘G’.  This guess can be made based upon the mutual information that these two positions share (they are seen to follow the same pattern of pairs).  This mutual information suggests that these bases may interact (their particular identities further suggest that they probably base-pair together).

     Mutual information analysis of a sequence alignment gives a mathematical measure of covariation between pairs of positions in the alignment.  It differs from covariation analysis in that it gives a quantitative measure of the extent of covariation between two positions.  For a more in-depth explanation of mutual information, see Mathematical overview of mutual information.

Brown, J.W.  1991.  Phylogenetic comparative analysis on Macintosh computers.   Comput. Appl. Biosci.  7(3):391-393.

Gutell, R.R., A. Power, G.Z. Hertz, E.J. Putz and G.D. Stormo. 1992. Identifying constraints on the higher-order structure of RNA: continued development and application of comparative sequence analysis methods.  Nucleic Acids Res. 20(21):5785-5795.


Mathematical Overview of Mutual Information

Mutual information refers to the amount of information shared by the interaction of two things, or the decease in uncertainty in one thing based upon knowledge about another.  In phylogenetic comparative analysis, this refers to the degree to which two positions in an alignment are not independent of each other.  The concept of mutual information was applied to RNA structure analysis in 1992 by Robin Gutell.

If two positions, x and y, show a strong interdependence, then mutual information, or M(x,y), will be relatively high. If the identities of x and y appear to be uncorrelated, M(x,y) will be low or zero.  Mutual information may be defined (in nits) as:

M(x,y) = Σ(fbxby)ln(fbxby/fbxfby) for all bases bx and by (or in bits if the log base 2 is used)

where bx and by refer to the identities of each possible base at positions x and y (A, G, C, U or GAP in BioEdit -- ambiguous bases are ignored), fbx and fby are the frequencies of each base at each position, and fbxby is the frequency of each possible pair of bases at x and y.  When there is no variation in one or both positions, mutual information is zero, and no interdependence can be shown (although this does not prove that there is none, it just can’t be shown if the bases never vary).  For example, if x is always ‘A’,  fbxfby is 0 for all combinations except when bx is ‘A’. When bx = ‘A’,  fbxfby =  fby, and fbxby=fby, so ln(fbxby/fbxfby )=0..  For these two bases, fbxby/fbxfby = 1 and ln(fbxby/fbxfby )=0.  M(x,y) therefore will be zero when either base is invariant.  When both positions show maximum variation,  fbx =  fby = 1/n for all b, where n is the number of possible bases to choose from (5 in BioEdit, treating gaps as a base).   Now, for all bx and by, 0<=fbxby<=1/n (because the frequency of a combination can’t possibly exceed the frequency of either of its contributing bases).  When all bases are completely independent of each other, fbxby = 1/n^2 for all combinations bxby.   For all bxby, then, (fbxby)log2(fbxby/fbxfby) =  1/n^2(ln((1/n^2)/1/n^2)) = 1/n^2(ln(1)) = 0.  M(x,y) = 0 when the bases at x and y vary independently of each other.  When the two bases are completely correlated,  fbxby = 1/n for each of the possible pairs, and 0 for all others.   Therefore, (fbxby)ln(fbxby/fbxfby)=0 for all combinations of bx and by  except for exactly n times, for which (fbxby)ln(fbxby/fbxfby) = 1/n(ln((1/n)/1/n^2)) = 1/n(ln(n)) = (ln(n))/n.  Therefore, the maximum value of M(x,y) occurs when the two positions are completely correlated and is equal to M(x,y)(max) = n(ln(n))/n = ln(n).  If n = 5 (A, G, C, U or GAP, as implemented in BioEdit), then M(x,y)(max ) = 1n(5) = ca. 1.609.

     The way BioEdit actually calculates M(x,y) is based upon the method used by Gutell et al.  M(x,y)=Σ(fbxby)ln(fbxby/fbxfby) is equivalent to:

 M(x,y) = H(x) + H(y) - H(x,y),

where H(x) and H(y) are the entropy at positions x and y, respectively (see Entropy plots).  The entropy terms H(x) and H(y) are calculated as:

H(x) = -Σfbxln(fbx),

and

H(x,y) = -Σfbxbyln(fbxby).

Examination of these formulas will reveal that they will yield the same result as those shown above.  BioEdit uses the natural logarithm (ln) for convenience.  If log base 2 is used instead, information will be in bits, but the data are the same relative to each other.

     because M(x,y) measures the mutual interdependence of two positions, and depends equally on frequencies of bases at each positions, it is a symmetric calculation (M(x,y) = M(y, x)).  In some cases where there is an interdependence between two bases, but some other factor constrains one of those positions, the small amount of variation in one position causes M(x,y) to be so small that the covariation between the two positions is missed.  In these cases, two other terms, R1(x), and R2(x) can sometimes bring this to light.  R1 and R2 are ratios of mutual information to entropy at the x and y positions, respectively.

R1(x) = M(x,y)/H(x)

R2(x) = M(x,y)/H(y)    (and, incidentally, R2(x) =  R1(y))

If position x shows little variation, but the variation it does show correlates with the variation seen in position y, R1(x) will be relatively large. R1(x) and R2(x) will often not be equal.

Gutell, R.R., A. Power, G.Z. Hertz, E.J. Putz and G.D. Stormo. 1992. Identifying constraints on the higher-order structure of RNA: continued development and application of comparative sequence analysis methods.  Nucleic Acids Res. 20(21):5785-5795.


Using Mutual Information in BioEdit

BioEdit calculates Mutual Information as M(x,y) = H(x) + H(y) - H(x,y) (see General Overview of Mutual Information and Mathematical Overview of Mutual Information).  This information can give a good indication of mutual interdependence of two bases in an evolutionarily conserved molecular structure which can be used to help build and refine secondary and tertiary structures of RNA molecules through phylogenetic comparative analysis.

If you’re not familiar with mutual information analysis, you probably want to read:

Gutell, R.R., A. Power, G.Z. Hertz, E.J. Putz and G.D. Stormo. 1992. Identifying constraints on the higher-order structure of RNA: continued development and application of comparative sequence analysis methods.  Nucleic Acids Res. 20(21):5785-5795.

Before doing a mutual information analysis, like any comparative sequence analysis, a high quality alignment is absolutely necessary.  If bases are not lined up in their homologous positions, the resulting data and structures they lead to will necessarily be incorrect.

Also, be sure to choose the output type(s) you would like before running the analysis (see Setting Mutual Information Preferences).

BioEdit allows the following options for mutual information output:

1.  Tabular output (matrix):

     a.  M(x,y) -- full table or only above the diagonal (M(x,y) is symmetric).

     b.  R1(x) -- full table only

     c.  R2(x) -- full table only

Any or all of the above may be chosen at the same time.  If more than one are chosen together, a single table will be generated with the second value right below the first in each column.  For example, if M(x,y) and R1(x) are chosen together, R1(x) values will be printed directly below M(x,y) values.

The option to set M(x,y) to 0 when x=y is offered (the real value is M(x,y) = H(x) when x=y).  Setting M(x,y) to 0 when x=y will suppress the diagonal on a plot of the M(x,y) matrix.

Output may be comma delimited or tab delimited.  For text editor viewing, tab delimited is recommended.  For small tables, the BioEdit Rich Text Editor works well on “no word wrap” mode.

An external application such as Excel may be linked to if you wish.  As long as it can read the file format and will accept a file as a command-line parameter, it will open your table after it is generated.

2.  List outputs:

     a.  Pbest:  A Pbest list reports all scores within a user-specified percentage of the highest M(x,y), R1(x) or R2(x) value.  All three values are reported, but the cut-off for reporting and sorting are according to the measure specified by the preferences.  The Pbest output may be a percentage of the highest score for each individual position taken separately, or for the highest score in the entire analysis.  P may be specified as 0 to 50% (whole numbers only).

     b.  Nbest: An Nbest list reports the N highest scores either for each position separately, or for the entire analysis (chosen by the user).  Like Pbest, M(x,y), R1(x) and R2(x) are reported, but the score threshold and sorting are according to the value specified in the preferences.

     For all types of analysis, the numbering of positions may be according to the numbering as seen in the alignment window (alignment numbering), or to the true positions of the mask (only included residues are incremented).

     File output is in raw text which may be in PC or Macintosh format (only carriage returns are different.  For example, if one has access to a Macintosh and would like to use a program such as SpyGlass Transform to view data, then M(x,y) matrix files should be output in Macintosh format (otherwise the files need to be converted by a word processor).

To do a mutual information analysis from a BioEdit alignment document:

1.  Have the alignment open in an alignment document window.

2.  If you would like to use a mask, create one or specify an existing sequence to be the mask.

3.  Select the preferences you would like for output (choose Analysis preferences” under the “Options” menu, then click the “Mutual Information” tab).

4. Select all of the sequences you would like to be included in the analysis (sequences are selected by selecting their titles).  Only sequences whose titles are selected will be included in the analysis.  If no sequences at all are selected, all sequences will be automatically selected for you.  If you are using a mask that is not a sequence and specifies positions only, make sure to exclude that from the analysis.  An easy way to select all but one sequence is to use “Select all Sequences” from the “Edit” menu, then deselect one sequence by Ctrl+left-mouse-click.

5.  To run the analysis, choose “Mutual Information” from the “RNA” menu.  You will be prompted for a file name for each output chosen.  List outputs will be opened in the text editor, but matrix outputs will not.  If you would like to link matrix outputs to a spreadsheet or other external program, this may be done by setting this option in the preferences.

If you have output data as a matrix, you might want to view the data with the BioEdit matrix plotter.


Mutual Information Example

In this example, mutual information analysis is performed on a segment of a sequence alignment  of bacterial RNase P RNA sequences.  (click on alignment to view the alignment).  The chosen output is a full table of M(x,y) values and an Nbest list of the 5 highest scores for each position.  (see Setting mutual information preferences).  Both the sequence and numbering masks are set as E. coli.  The numbering is according to the E. coli mask sequence.  This part of the alignment contains a highly structured region referred to as the “cruciform region” of RNase P RNA (see E. coli sample RNase P RNA structure).  The matrix text is too large to view within this help, but a graphical plot of the table is a convenient way to look at it.  With the BioEdit matrix plotter, the data may be dynamically examined numerically as well as graphically.

View Nbest list

View matrix plot of data table


Sample Alignment for Mutual Information

Below is a subsection of an alignment of RNase P RNAs from bacteria.  There are 138 sequences, which is more than plenty for a meaningful analysis.  This alignment contains what is referred to as the “cruciform region” (see the sample RNA structure).  The region of the alignment where “~~~” appears in every sequence denotes a section RNase P RNA of poorly conserved sequence and length that has been removed from the alignment.

Brown, J.W.  1998.  The Ribonuclease P Database.  Nucleic Acids Res. 26:351-352.

http://jwbrown.mbio.ncsu.edu/RNaseP

Alignment: I:\BioEdit\bacterial_analysis\minimized_cruciform.gb

0	                  ....|....| ....|....| ....|....| ....|....| ....|....| ....|....| ....|....| ....

1	                           10         20         30         40         50         60         70

2	Escherichia-col   CUCCAUAGGG CAGGGUGCCA GGUAACGCCU GGGGGGGAAA CCCACGACCA GU~~~GCGUA AACUCCACCC GGAG

3	Rhodospirillum-   CUCCACGGAA CACGGUGCCG GGUAACGCCC GGCGGGGCGA CCUAGGGAAA GU~~~GCGUA AACCCCACCG GGAG

4	Agrobacterium-t   CUCCACGAAA UACGGUGCCG GAUAACGUCC GGCGGGGCGA CCCAGGGAAA GU~~~GCGUA AACCCCACCG GGAG

5	Alcaligenes-eut   CUCCACAGGG CAGGGUGUUG GCUAACAGCC AUCCACGCAA GUGCGGAAUA GG~~~GCGUA ACCUCCACCU GGAG

6	Pseudomonas-tes   cUGCAUAGGG CGGCGUAGCA GCUAACAGCU GUCCACGUGA GUGAGGAUCA GA~~~GCGCA AUCUCUACGC GCAG

7	Thiobacillus.th   cUCCACAGAG CAGGAUGCCG GCUAACGGCC GGACGCGCGA GCGAGGAAUA GG~~~GCGUA ACCUCCAUCC GGAG

8	N-meningitidis    CUCCGCAgGG UAGAAUGCCG GUUAACGGCC GGGCGCGUAA GCGACGGAAA GU~~~GGCCA AACCCCAUUC GGAG

9	N-gonnorhoeae     CUCCGCAGGG UAGAAUGCCG GUUAACGGCC GGGCGCGUAA GCGACGGAAA GU~~~GGCCA AACCCCAUUC GGAG

10	Thiobacillus-fe   CUCCAUAGGG CAAGGCGCCG GUUAACGGCC GGGGGGGUGA CCUACGGAAA GU~~~GCGAA AACCCCGCCU GGAG

11	Salmonella-typh   CUCCAUAGGG CAGGGUGCCA GGUAACGCCU GGGGGGGAAA CCCACGACCA GU~~~GCGUA AACUCCACCC GGAG

12	Klebsiella-pneu   CUCCAUAGGG CAAGGUGCCA GGUAACGCCU GGGGGGUCAC CCCACGACCA GU~~~GCGUA AACUCCACCC GGAG

13	Erwinia-agglome   CUCCAUAGGG CAAGGUGCCA GGUAACGCCU GGGGGGUCAC CCCACGACCA GU~~~GCGUA AACUCCACCC GGAG

14	Serratia-marces   CUCCAUAGGG CAGGGUGCCA GGUAACGCCU GGGAGGGCAA CCUACGACUA GU~~~GCGUA AACUCCACCC GGAG

15	H.influenza       CUACACAGGG CAGAGUGCCG GAUAACGUCC GGGCGGGUGA CCGACGACCA GU~~~GCGUA AACUCCACUC GUAG

16	Vibrio-cholera    CUCCAUAGAG CAGGGUGCCA GGUAACGCCU GGGGGGGCAA CCUACGACAA GU~~~GCGUA AACUCCACCC GGAG

17	Pseudomonas-flu   CUCCAUAGGG CGAAGUGCCA GGUAAUGCCU GGGGGGGUGA CCUACGGAAA GU~~~GCGUA AACCCCACUU GGAG

18	Chromatium-vino   CUCCAUAGGG CAGGGUGCCA GGUAACGCCU GGGGGGGAGA UCCACGGAAA GU~~~GCGUA AACCCCACCC GGAG

19	Desulfovibrio-d   CUCCAAAGGG CAGAACGCUG GAUAACAUCC AGGGAGGCAA CUC-CGGACA GC~~~GCGCA UACCCCGUUC GGAG

20	Myxococcus-xant   cUCCAGAGGG CAGGGUGCUG GCUAACGGCC AGUCGAGCGA UCGCAGGAAA GU~~~GCGUA AACCCCGCCU GGAG

21	H-pylori          CUACAUUAGA CAAAAUUCCA UCUAACGGAU GGCUAGGCAA CUAAGGGAAA GU~~~GCGCA AACCCAAUUU GAAG

22	Streptomyces-bi   CUCCACAGAG CAGGGUGGUG GCUAACGGCC ACCCGGGUGA CCGCGGGACA GU~~~GCGUA AACCCCACUC GGAG

23	Streptomyces-li   CUCCACAGGG CAGGGUGAUG GCUAaCGgCC ACCCGGGUGA CCGCGGGACA GU~~~GCGUA AACCCCACCC GGAG

24	Micrococcus-lut   cACCGCAGAG CAGGAUGGUG GACAACAUCC ACCCGGGCGA CCGCGGGCCA GU~~~GCGUA AACCCCAUCC GGUG

25	Eubacterium-the   cUCCGCAGGG CAGGAUGCUG GGUAAUACCC AGUGGGGCGA CCUAAGGAUA GU~~~GCGUA AACCCCAUCU GGAG

26	Clostridium-ace   CUCCAUAGGG CAGGGUGCCG GGUAACUCCC GGUCAAGCGA UUGAAGGAAA GU~~~GCGUA AACCCCAUCU GGAG

27	Clostridium-spo   cUCCAUAGGG CAGGGUGCUG GGUAAUACCC AGUGGAGCGA UUUAAGGAAA GU~~~GCGUG AACCCCAUCU GGAG

28	Mycobacterium_l   CUUCACAGAG CAGGGUGAUU GCUAACAGCA AUCCGAGUGA UCGCGGGAUA GU~~~GCGUA AACCCCACCC GAAG

29	Mycobacterium_t   CUUCACAGAG CAGGGUGAUU GCUAACGGCA AUCCGAGUGA UCGCGGGAAA GU~~~GCGCA AACCCCACCC GAAG

30	Bacillus-subtil   CUCCAG---- -UUCGUGCCA GCAGUCAGCU GGGCAGUUAG CUGACGGCAA GU~~~GCGUA AACCCCUCGA GGAG

31	Bacillus-brevis   CUCCAG---- -UUCGUACCG GC-GCAAGCC GGGCAGGCAA CUGACGGCAA GU~~~GCGUA AACCCUGCGA GGAG

32	Bacillus-stearo   CUCCAG---- -UUCGUGCCA GCAUCCAGCU GGGCAGUUCG CUGACGGCAA GU~~~GCGUA AACCCCACGA GGAG

33	Bacillus-megate   CUCCAG---- -UUCGUGCCA GUAAAAAGCU GGGCAG-UAU CUGACGGCAA GU~~~GCGUA AACCCCACGA GGAG

34	Staphylococcus-   cUCCAG---- -UUCGUGCUG AUAACAAAUC AGGCA-UAAU -UGACGGCAA GU~~~GCGUA AACCCCUCGA GGAG

35	Streptococcus-f   cUCCAG---- -UUCGUGCUA GCAAUCAGCU AGGUAC-UUU GUAACGGCAA GU~~~GCGUA AACCCCUCGA GGAG

36	Streptococcus-p   CUACAG---- -AUUGUGCUG GCACACAGCC AGGGAUCAUA AUUACGGCAA GU~~~GCGUA AACCCCUCAA GUAG

37	Streptococcus-f   cUCCAG---- -UUCGUGCUA GCAACAAGCU AGGUGC-AUU GUAACGGCAA GU~~~GCGUA AACCCCUCGA GGAG

38	Lactobacillus-a   cCCCAG---- -UUCGUGCUA GCCAAUAGCU AGGGGCGUAA GCUACGGCAA GU~~~GCGUA AACCCCGCGA GGAG

39	Acholeplasma_la   cUACAG---- -UUUGUGCUA GGAAUCACCU AGGUAUUAUA AUAACGGCAA GU~~~GCGUA AACCCCUCAA GUAG

40	Mycoplasma-ferm   CUACAG---- -AUCAUGCUG GCCAAUAGCC AGGC---UUA --GACGACUA GU~~~GCGUA AACUCCAUGA GUAG

41	Mycoplasma-floc   CUACAG---- -UUCAUGUUG GUUAAUAACC AAGC---UUA --GACGACAA GU~~~GCGUA AACUCCAUGA GUAG

42	Mycoplasma-hyop   CUACAG---- -UUCAUGUUG AUUAAUAAUC AAGC--UUUA --GACGACCA GU~~~GCGUA AACUCCAUGA GUAG

43	Mycoplasma.geni   CUUCAG---- -UUUGUG-UA AUAGCGAGAU UAGGAUGAUA AUAACGACAA GU~~~GCGUA AACUCCACAA GAAG

44	Mycoplasma-capr   CUUC-G---- -UUUAUGCUA AUAAAUAUUU AGGCAGUUAA AUAACAACAA GU~~~GCGUA AACCCCAUAA GAA-

45	Mycoplasma-pneu   CUUCAG---- -UUUGUG-UA AUAACAAGAU UAGGACUAAU --GACGUCAA GU~~~ACGUA AACUCCACAA GAAG

46	Clostridium-inn   cUCCAG---- -UUUGUGCUG AUAACGAAUC AGGCAGGUAA CUGACGGCAA GU~~~GCGUA AACCCCGCAA GGAG

47	Heliobacillus.m   cuCCAG---- -UUCGUGCCG UUCGUAAGGC GGGCAGUUUU CUGACGGCAA GU~~~GGCUA AACCCCACGA GGAG

48	Cyanophora.para   CUCUUAAGGU UAGAAUGCUG GGUAAUUCCC AGUACGGAUA CGUGAGGAUA GU~~~GCGUA AACCCCGUUC AGAG

49	Anacystis-nidul   CUCCAAAGAC CAGACUGCUG GGUAACGCCC AGUGCGGUGA CGUGAGGAGA GU~~~GCGUA AACCCCGGUU GGAG

50	Anabaena-PCC712   CUCCGAAGAC CAGACUGCUG GAUAACGUCC AGUGCGGCGA CGUGAGGAUA GU~~~GCGUA AACCCCGGUU GGAG

51	Calothrix-PCC76   CUCCGAAGAC CAAACUGCUG GAUAACGUCC AGUGCGGCGA CGUGAGGAUA GU~~~GCGUA AACCCCGGUU GGAG

52	Synechocystis-P   CUUCCAAGGC CAAACUGCUG GGUAACGCCC AGUGCGGCGA CGUGAGGACA GU~~~GCGUA AACCCCGGUU GAAG

53	Pseudoanabaena-   CUUCAAAGAU CAGGCUGCUG GAUAACGCCC AGUGCGGCAA CGUGAGGAUA GU~~~GCGUA AACCCCAGUC GAAG

54	Synechocystis.P   cuCCAAAGAU CAAACUGCUG GGUAACGCCC AGUGCGGUGA CGUGAGGAUA GU~~~GCGUA AACCCCGGUG GGAG

55	Anabaena.ATCC29   cuCCGAAGAC CAGACUGCUG GAUAACUUCC AGUGCGGCGA CGUGAGGAUA GU~~~GCGUA AACCCCGGUU GGAG

56	Nostoc.PCC6705    cuCCGAAGAC CAGACUGCUG GAUAACGUCC AGUGCGGCGA CGUGAGGAUA GU~~~GCGUA AACCCCGGUU GGAG

57	Nostoc.PCC7107    cuCCGAAGAC CAAACUGCUG GAUAACGUCC AGUGCGGCGA CGUGAGGAUA GU~~~GCGUA AACCCCGGUU GGAG

58	Fischerella.UTE   cuUCGAAGAC CAAACUGCUG GGUAACGCCC AGUGCGGCGA CGCGAGGAUA GU~~~GCGUA AACCCCGGUU GAAG

59	Dermocarpa.PCC7   cUCCGAAGAC CAAACUGCUG GGUAACGCCC AGUACAGCGA UGUGAGGAUA GU~~~GCGUA AACCCCGGUU GGAG

60	Nostoc.PCC7413    cuCCGAAGAC CAGACUGCUG GAUAACGUCC AGUGCGGCGA CGUGAGGAUA GU~~~GCGUA AACCCCGGUU GGAG

61	Oscillatoria.PC   cuCCAAAGGC CAAGCUGCUG GGUAACGCCC AGUGCGGCGA CGCGAGGAUA GU~~~GCGUA AACCCCGGCU GGAG

62	Syenchococcus.P   cUUCGAAGAC CAAGCUGCUG GGUAACGCCC AGUGCGGUGA CGUGAGGAAA GU~~~GCGUA AACCCCGGCU GAAG

63	Synechococcus.P   cUCCCAUGGC CAGGCUGCUG GGUAACGCCC AGUGCGGUGA CGUGAGGAGA GU~~~GCGUA AACCCCGGCC GGAG

64	Synechococcus.P   cACACAGGCU GGUUGUGGGU AAUUCCCAGU GCGCGCAGCG GAGGAUAGUG CC~~~ACGGU AAACCCCGCU GAGG

65	Synechococcus.P   CCAAAGCCAG ACUUGUGGGU AACGCCCAGU GCGGGUACCG GAGGAGAGUG CC~~~AC-GU AAACCCCGGU UGGA

66	Chlorobium-limi   CUUCACAGGG CAGGG-GCCG UCACCUGGGC GGGGGCGCAA GUCACAGAGA GU~~~GCUGA AACCUC-CCC GAAG

67	Chlorobium-tepi   CUUCACAGGG CAGGG-GCCG UCACGUUGAC GGGGGCGCAA GUCACAGAGA GU~~~GCUGA AACCUC-CCC GAAG

68	Bacteroides-the   CAACACAGAG CAUCCUACUU CCUAACAGAA AGCUGUGCGA GUA-GAG-UA AC~~~GUGUA CGUCUUAGGA GUUG

69	Flavobacterium-   cAACACAGAG CAACUCACUU CCUAACGGGA AGGCUCUCAG GAGACAGCAA GU~~~GCGUA AACCUUGAGU GUUG

70	Planctomyces-ma   cUCCACAGGG CACGGUGGUG GGUAACGCCC ACCGUCGCGA GACAGGGAAA GU~~~GCGUA AACCCCACCG GGUG

71	Pirellula-stayl   cUCCACAGGA CAGGGUGGUC GAUAACGUCG ACCGGUGUGA AUCAGGGACA GU~~~GCGUA AACCCCGCCC GGAG

72	Chlamydia-trach   cUUUAUAAGA AAAGAUGCUG GAGAAAUUCC AGGGGCGUAA GCUACGGAAA GU~~~GCGUA AACCCCAUCU GAAG

73	Chlamydia-psitt   cUUCAUAAGA AAAGAUACUG GAGAAACUCC AGGGGCGUAA GCUACGGAAA GU~~~GCGCA AACCCUAUCU GAAG

74	Borrelia-hermsi   cUCCAA-AGA GAUAAUGCUA GGUAAUGCCU AGGAGU-UAA ACU-UAGAGA GU~~~GUGUA AACCUCAUUA GGAG

75	Borrelia-burgdo   CUCCAA-AGA AAUAAUGCUA GGUAAUGCCU AGGGGU-UUA ACC-UAGAAA GU~~~GUGUA AACCUCAUUA GGAG

76	Leptospira-borg   cACCAG-AAA CACGGGACCG GGUAAUCCCC GGAGUUGAAA AAUAUGGAAA GU~~~GCGUA AACCCUCCCG GGUG

77	Leptospira-weil   cACCAG-AAA CACGGGACCG GGUAAUUCCC GGAAUUGAAA AAUAUGGAAA GU~~~GCGUA AACCCUCCCG GGUG

78	Deincoccus-radi   CACCGCAGGG CAGGAUGCCA GCUAACGGCU GGUCGGGCCG CCGAAGGACA GU~~~GCGUC AACCCCAUCC GGUG

79	Thermus-aquatic   CACCAUAGGG CAGGGUGCCA GCUAACGGCU GGGCGGGCAA CCGACGGAAA GU~~~GCGCA AACCCCACCC GGUG

80	Thermus-thermop   CACCAUAGGG CAGGGUGCCA GGUAACGCCU GGGCGGGUAA CCGACGGAAA GU~~~GCGCA AACCCCACCC GGUG

81	Thermomicrobium   CUGCACAGAG CGGGG-GCCU GGGUCAACCA GGGCAGACCG CUGACAGUGA GC~~~AAGCA AUCCUC-CCU GCAG

82	Chloroflexus-au   cUCCAUAGAG CAGGGUGGUG GGUAACGCCC ACCCGGGUGA CCGCGGGAAA GU~~~GCGCA AACCCCACCU GGAG

83	Herpetosiphon-a   cUCCAUAGGG CGAAGUGCCA GGUAAUGCCU GGGAGGGUGA CCUACGGAAA GU~~~GCGCA AACCCCACCU GGAG

84	Thermoleophilum   cACCGCAGGG CAGGGUGGUC GGGAAA-CCG ACCCGGGAAA CCGCGGGAAA GU~~~GCGCA AACCCCACCC GGUG

85	Thermotoga-mari   CUCU--GGAG CGGGGUGCCG GGUAACGCCC GGGAGGGUGA CCU-CGGACA GG~~~GCGCA ACCCCCACCU GGAG

86	Thermotoga-neap   CUCU--GGAG CGGGGUGCCG GGUAACGCCC GGGAGGGUGA CCU-CGGACA GG~~~GCGCA ACCCCCACCU GGAG

87	vB11              cUCCACAGAG CAGGAUGCCG GCUAACGGCC GGACGCGCGA GCGAGGAAUA GG~~~GCGUA ACCUCCAUCC GGAG

88	vHge8-3           cUCCGCAGGG CAGGGUGCCG GGUAACUCCC GGUGAAGUGA UUCAAGGAAA GU~~~GCGUA AACCCCACUC GGAG

89	Mxa1              cUGCACAGAG CGGGAUGACG GCUAACGGCC GUACGCGUAA GCGAGGAAUA GG~~~GCGUA ACCUCCAUCU GCAG

90	ESH7-4            cUCCACAGGG CAGGAUGCUG GCUAACGGCC AGGCGUGCGA GCGACGGAAA GU~~~GGCUA AACCCCAUCC GGAG

91	ESH7-9            cUUCAACGGG CAAGGUGCCA GGUAACGCCU GGGCGGGUGA CCGACGGAAA GU~~~GCGUA AACCCCACCG GAAG

92	ESH7-16           cUACAUAGGG CAGCGUGCCA GCUAACGGCU GGGCAGGUAA UUGACGACCA GU~~~GCGUA AACUCCACGC GUAG

93	ESH17b-7          cUCCAUAGGG CGGAGUGCCA GGUAAUGCCU GGGGGGGUGA CCUACGGAAA GU~~~GCGUA AACCCCACUC GGAG

94	ESH20b-4          cUCCAUAGGG CAGAGCGCCA GGUAACACCU GGGAGGGUGA CCUACGGAAA GU~~~GCGUA AACCCCACUU GGAG

95	ESH20b-1          cUUCACAGGG CAGGAUGCCA GAUAACGUCU GGCGGAGCGA UCCAGGGAAA GU~~~GCGUA AACCCCAUCC GAAG

96	ESH21b-4          cUCCAUAGGG CGAAGUGCCA GGUAAUGCCU GGGAGGGUGA CCUACGGAAA GU~~~GCGUA AACCCCACUU GGAG

97	ESH26-4           cUGCACAGAG CGGGAUGACG GCUAACGGCC GUACGCGCAA GCGAGGAAUA GG~~~GCGUA ACCUCCAUCA GCAG

98	ESH30-3           cAACACAGAG CAUCCUACUU CUUAACGGGA AGCUAUGCGA GUA-GAGU-A AU~~~GUGUA CGUCUUAGGA GUUG

99	ESH46a-1          cUCCACAGAG CAGAAUGCCG GCUAACGGCC GGGCGCGCAA GCGACGGAAA GU~~~GGGUA AACCCCAUUC GGAG

100	ESH167E           cAGUACAGAG CAACCCACCG GUGAACAGCC GGCCACAAUU GUGAGAGAAA GU~~~GCGUA AACCUUGGGU GCUG

101	ESH167F           cUCCAUAGAG CAGGGUGAUG GCUAACGACC AUCCACGUGA GUGCGGAAUA GG~~~GCGUA ACCGCCACCC GGAG

102	ESH183A           cACCACAGGG CUGGU-GCUG GGUAAUGCCC AGUGCGGUGA CGUGAGGAUA GU~~~GCGUA AACCCC-ACU GGUG

103	ESH183D           cUCCAUAGGG CAGGGUGUUG GCUAAUAGCC AUCCACGCAA GUGCGGAAUA GG~~~GCGUA ACCUCCACCU GGAG

104	ESH210B           cUCUACAGAG CAAAGUGGUG GAUAACUUCC ACCCGGGCGA CCGCGGGAUA GU~~~GCGCA AACCCCACUU UGAG

105	ESH212C           cuCCAUCGAC AACGGUGCCG GAUAACACCC GGCGGGGCGA CCCAGGGAAA GU~~~GCGCA AACCCCACCG GGAG

106	PS#1              cUCCACGAAA CACGGUGCCG GAUAAUGCCC GGCGGGGUGA CCCAGGGAAA GU~~~GCGCA AACCCCACCG GGAG

107	PS#2              cUCCACGGAA GAUGGUGCCG GGUAACGCCC GGCGGGGCGA CCCAGGGACA GC~~~GCGCA AGCCCCGCCA GGAG

108	PS#4              cACCAAAGGG CUGGU-GCUG GGUAACGCCC AGUGCGGUGA CGUGAGGAUA GU~~~GCGUA AACCCC-GCU GGUG

109	PS#6              cUCCACGGAA CGCGGUGCCG GGUAACGCCC GGCGGGGCGA CCCAGGGAAA GU~~~GCGCA AACCCCACCG GGAG

110	PS#8              cAACACAGAG CAGGAUACUU CUUAACGAGA AGCAGUGCGA GCU-GAG-UA GU~~~GUGUA CGCCUUAUGG GUUG

111	PS#22             cCCCACAGAG CAGGAUGCCG GCUAACGGCC GGGCGCGCGA GCGACAGACA GU~~~GCGCA AACCUCAUCC GGGG

112	PS#24             cUCCACAUAA CACGGUGCCG GGUAACGCCC GGCGGUCGUG GCAAGGGACA GU~~~GCGCA AACCCCACCG GGAG

113	PS#26             cUCCACGAAA CACGGUGCCG GAUAAUGUCC GGCGAGGUGA CUUAGGGAAA GU~~~GCGCA AACCCCACCC GGAG

114	PS#27             cUCCACGGAA CGCGGUGCCG GGUAACACCC GGCGGGGCGA CCCAGGGACA GU~~~GCGCA AACCCCACCG GGAG

115	PS#31             cUCCACGAAA CAGGGUGGCG GGUAACGCCC GCCGGCUUCG GCAAGGGAAA GU~~~GCGCA AACCCCACCC GGAG

116	PS#33             cACCACAGGG CAGGAUGC-G GCUAACGGCC -GGCGCGUGA GCGACGGAAA GU~~~GCGCA AACCCCAUCC GGUG

117	LGA#1             cAGCACAGAG CAAUGCACCG GUGAAUAGCC GGGUUC-UUU GAAACAGACA GU~~~GCGUA AACCUUGCAU GCUG

118	LGA#2             cCCCACAGAG CAGGAUGCCG GCUAACGGCC GGGCGCGCAA GCGACAGACA GU~~~GCGC- AACCUCAUCC GGGG

119	LGA#6             cUCCACAGGA CAGAGUGGUC GGUAACGCCG ACCGGCGAAA GCUCGGGACA GG~~~GCGCA ACCCCCACUC GGAG

120	LGA#8             cUCCACAGGA CAGAGUGGUC GCUAACGGCG ACCGGCGCAA GCUCGGGAAA GU~~~GCGCA AACCCCACUC GGAG

121	LGB#5             cUCCACAGGG cAAGAUGGUU GCUAGCGGCA ACUGUCUAGU GAUAAGGAAA GU~~~GCGUA AACCCCAUCU GGAG

122	LGA#10            cUCCU-UGGA CAAACUGCCA GGUAGCACCU GGGCACAUGA GUGACGGAAA GU~~~GCGUA AACCCCAGUU GGAG

123	LGB#21            cAUCGACGGG CAGGAUGGUC UCUAACGGAG ACUGGGGUAA CCUAAGGAAA GU~~~GCGCA AACCCCAUCC GAUG

124	LGB#23            cUCCAUGAAG CAGGGUGCCG GGUAAUGCCC GGCCGGGAAA CCGAGGGAAA GC~~~GCGCA AGCCCCACCC GGAG

125	LGB#27            cAACACAGGG CAGCGUACUU CCUAACGGGA AGGCCCUUAG GGGACAGAAA GU~~~ACGCA AACCUUACGC GUUG

126	LGB#32            cUCCU-UGGA CAAACUGCCA GGUAACACCU GGGCACAUGA GUGACGGAAA GU~~~GCGUA AACCCCAGUU GGAG

127	LGB#41            cUCCACGGAA CACGGUGCCG GGUAACGCCC GGCGGCCUCG GUUAGGGAAA GU~~~GCGUA AACCCCACCG GGUG

128	LGW#17            cUCCAUAGGG CAGGAUGCCA GUUAACGGCU GGGUGCGCAA GCAACGGACA GU~~~GCGUG AACCCCAUCC GGAG

129	LGW#18            cUCCGCAGGG CAGUGUGGUU CCUAACGGGA ACCGGGGUAA CCCAGGGAAA GU~~~GCGUA AACCCCACAC GGAG

130	LGW#23            cUCCAUAGGG CAAGGUGCCA GGUAACGCCU GGGGGGGCGA CCCACGGACA GU~~~GCGCA AACCCCACCU GGAG

131	LGW#46            cACCAUAGGA CAGGGUGGUG GGUAACGCCC ACCGGCGUAA GUUAGGGAAA GU~~~GCGUA AACCCCGCCC GGUG

132	LGW#113           cUCCACGGAA CACGGUGCCG GGUAACGCCC GGCGGCCUCG GUUAGGGAAA GU~~~GCGUA AACCCCACCG GGUG

133	LGW#116           cUCCGCAGGA CAGGGUGGUC GGUAACGCCG ACCGGCGCAA GCUCGGGAAA GU~~~GCGCA AACCCCACCC GGAG

134	EM14b-9           cUCAGAGGUG CGCGUAUCCG UUGAUGAAGC GGGGCGGAGA CGC-CGGAAA GU~~~GCGUA AACCCAUACG CGAG

135	EM14b-11          cUCCAAAGGG CAGGGCGCCG GGUAAUACCC GGGGUG-AAA CACACGGUAA GG~~~GCGUA ACUCCCGCCC GGAG

136	PF#101            cUCCAUAGGG CAGGGCGCUG UCGGAA-GGC GGGAGUAGA- ACUUCGGAAA GU~~~GCGCA AACCCCGCCC GGAG

137	BH#145            cUCCAUAGGG CGAAGUGCCA GGUAAUGCCU GGGAGGGUGA CCUACGGAAA GU~~~GCGUA AACCCCACUU GGAG

138	P#126             cUCCAUAGGG CGAAGUGCCA GGUAAUGCCU GGGAGGGUGA CCUACGGAAA GU~~~GCGUA AACCCCACUU GGAG

139	P#131             cUCCAUAGGG CAGGGUGCCA GGUAACGCCU GGGAAGGCGA CUUACGACAA GU~~~GCGUA AACUCCACCC GGAG


N-best output
N-best sample output

Below is the N-best list generated from our sample alignment using E. coli as the mask.  Positions for which mutual information is 0 for all pairs (such as invariant positions) are not reported, because the highest score would be zero (for example, position 1 is invariant).

Brown, J.W.  1991.  Phylogenetic comparative analysis on Macintosh computers.   Comput. Appl. Biosci.  7(3):391-393.

Mutual information analysis, BioEdit v1.0 M(xy) values

7/20/98 5:39:51 PM

Input from I:\BioEdit\samples\bac_cruciform.gb

N-best:  N = 5

Data are reported as the 5 best scores for each position.

Position numbering is relative to the numbering of the mask.

Mask Sequence: Escherichia-coli.

X	Y	M(xy)	R1(xy)	R2(xy)

0	2	64	0.41919	0.74220	0.77571

1	2	57	0.09703	0.26234	0.17955

2	2	17	0.09703	0.26234	0.17955

3	2	46	0.07606	0.19712	0.14075

4	2	58	0.07188	0.07427	0.13302

5	3	63	0.74543	0.88974	0.88562

6	3	64	0.41919	0.74220	0.77571

7	3	60	0.19326	0.17130	0.22960

8	3	14	0.15305	0.13573	0.18184

9	3	48	0.14794	0.18927	0.17576

10	4	63	0.74543	0.88974	0.88562

11	4	62	0.09973	0.61816	0.35290

12	4	27	0.08872	0.09120	0.31397

13	4	9	0.08024	0.07587	0.28395

14	4	48	0.07747	0.09912	0.27415

15	5	63	0.74543	0.88974	0.88562

16	5	6	0.29015	0.20469	0.40527

17	5	10	0.20639	0.16705	0.28828

18	5	45	0.16331	0.14267	0.22810

19	5	42	0.15679	0.12421	0.21899

20	6	63	0.74543	0.88974	0.88562

21	6	10	0.55651	0.45044	0.39259

22	6	7	0.46708	0.46467	0.32950

23	6	42	0.41007	0.32486	0.28929

24	6	45	0.40599	0.35468	0.28641

25	7	63	0.74543	0.88974	0.88562

26	7	10	0.50095	0.40546	0.49836

27	7	13	0.48571	0.40235	0.48321

28	7	6	0.46708	0.32950	0.46467

29	7	8	0.46486	0.61807	0.46246

30	8	63	0.74543	0.88974	0.88562

31	8	10	0.52448	0.42451	0.69735

32	8	7	0.46486	0.46246	0.61807

33	8	11	0.45904	0.60117	0.61035

34	8	9	0.40559	0.38349	0.53928

35	9	63	0.74543	0.88974	0.88562

36	9	10	0.45687	0.36979	0.43198

37	9	7	0.44283	0.44054	0.41870

38	9	11	0.41858	0.54817	0.39577

39	9	8	0.40559	0.53928	0.38349

40	10	63	0.74543	0.88974	0.88562

41	10	6	0.55651	0.39259	0.45044

42	10	8	0.52448	0.69735	0.42451

43	10	7	0.50095	0.49836	0.40546

44	10	11	0.45784	0.59959	0.37058

45	11	63	0.74543	0.88974	0.88562

46	11	8	0.45904	0.61035	0.60117

47	11	10	0.45784	0.37058	0.59959

48	11	9	0.41858	0.39577	0.54817

49	11	13	0.40752	0.33758	0.53369

50	12	63	0.74543	0.88974	0.88562

51	12	8	0.32859	0.43689	0.42700

52	12	9	0.31537	0.29819	0.40983

53	12	11	0.30674	0.40170	0.39860

54	12	10	0.30231	0.24469	0.39285

55	13	63	0.74543	0.88974	0.88562

56	13	61	0.73672	0.57245	0.61029

57	13	7	0.48571	0.48321	0.40235

58	13	10	0.42854	0.34686	0.35499

59	13	11	0.40752	0.53369	0.33758

60	14	60	0.91933	0.81491	0.81527

61	14	63	0.74543	0.88974	0.88562

62	14	13	0.35197	0.29157	0.31213

63	14	10	0.34776	0.28148	0.30840

64	14	6	0.30004	0.21166	0.26608

65	15	60	0.91933	0.81491	0.81527

66	15	59	0.88391	0.85251	0.86956

67	15	42	0.35116	0.27819	0.34546

68	15	35	0.33429	0.28780	0.32887

69	15	44	0.27533	0.27510	0.27086

70	16	60	0.91933	0.81491	0.81527

71	16	58	0.29422	0.30400	0.59885

72	16	42	0.12736	0.10089	0.25923

73	16	35	0.11830	0.10185	0.24079

74	16	15	0.10383	0.10215	0.21134

75	17	60	0.91933	0.81491	0.81527

76	17	57	0.36986	1.00000	1.00000

77	17	21	0.12789	0.21581	0.34579

78	18	60	0.91933	0.81491	0.81527

79	18	32	0.65757	0.90669	0.86769

80	18	45	0.19840	0.17332	0.26180

81	18	44	0.18460	0.18444	0.24359

82	18	20	0.18288	0.17954	0.24132

83	19	60	0.91933	0.81491	0.81527

84	19	31	0.69220	0.87127	0.86915

85	19	44	0.27079	0.27056	0.34002

86	19	42	0.16344	0.12948	0.20523

87	19	6	0.14507	0.10234	0.18216

88	20	30	0.96065	0.96081	0.94314

89	20	60	0.91933	0.81491	0.81527

90	20	6	0.22387	0.15792	0.21978

91	20	9	0.21436	0.20268	0.21045

92	20	33	0.19540	0.16923	0.19184

93	21	30	0.96065	0.96081	0.94314

94	21	29	0.46603	0.80276	0.78641

95	21	28	0.18711	0.16084	0.31574

96	21	22	0.18693	0.14668	0.31545

97	21	14	0.18391	0.16309	0.31035

98	22	30	0.96065	0.96081	0.94314

99	22	28	0.91355	0.78530	0.71684

100	22	10	0.26520	0.21465	0.20809

101	22	60	0.22712	0.20132	0.17821

102	22	34	0.22136	0.19611	0.17369

103	23	30	0.96065	0.96081	0.94314

104	23	9	0.28987	0.27407	0.39497

105	23	8	0.28917	0.38447	0.39401

106	23	11	0.28885	0.37828	0.39358

107	23	10	0.27208	0.22022	0.37074

108	24	30	0.96065	0.96081	0.94314

109	24	23	0.16429	0.22385	0.42579

110	24	25	0.16080	0.30181	0.41675

111	24	39	0.12221	0.10977	0.31673

112	24	58	0.11448	0.11829	0.29671

113	25	30	0.96065	0.96081	0.94314

114	25	23	0.22088	0.30096	0.41457

115	25	9	0.20630	0.19506	0.38721

116	25	12	0.18472	0.24004	0.34670

117	25	58	0.16808	0.17366	0.31546

118	26	30	0.96065	0.96081	0.94314

119	26	23	0.22745	0.30992	0.26702

120	26	27	0.16967	0.17440	0.19918

121	26	8	0.14760	0.19625	0.17327

122	26	9	0.14384	0.13600	0.16886

123	27	30	0.96065	0.96081	0.94314

124	27	11	0.27449	0.35947	0.28214

125	27	23	0.27131	0.36968	0.27888

126	27	8	0.27119	0.36058	0.27876

127	27	42	0.25483	0.20188	0.26194

128	28	30	0.96065	0.96081	0.94314

129	28	22	0.91355	0.71684	0.78530

130	28	10	0.23248	0.18817	0.19984

131	28	14	0.21711	0.19254	0.18663

132	28	34	0.21609	0.19144	0.18576

133	29	30	0.96065	0.96081	0.94314

134	29	21	0.46603	0.78641	0.80276

135	29	28	0.21114	0.18150	0.36370

136	29	22	0.16729	0.13126	0.28816

137	29	60	0.13282	0.11773	0.22879

138	30	30	0.96065	0.96081	0.94314

139	30	20	0.96065	0.94314	0.96081

140	30	6	0.24572	0.17334	0.24576

141	30	33	0.20867	0.18072	0.20870

142	30	9	0.18383	0.17382	0.18386

143	31	30	0.96065	0.96081	0.94314

144	31	19	0.69220	0.86915	0.87127

145	31	44	0.21776	0.21758	0.27410

146	31	42	0.15027	0.11904	0.18914

147	31	33	0.15023	0.13010	0.18909

148	32	30	0.96065	0.96081	0.94314

149	32	18	0.65757	0.86769	0.90669

150	32	45	0.21849	0.19088	0.30127

151	32	44	0.19492	0.19476	0.26877

152	32	33	0.19272	0.16691	0.26574

153	33	45	0.98665	0.86196	0.85449

154	33	30	0.96065	0.96081	0.94314

155	33	44	0.36804	0.36773	0.31874

156	33	6	0.36519	0.25763	0.31627

157	33	10	0.35555	0.28778	0.30793

158	34	45	0.98665	0.86196	0.85449

159	34	43	0.77463	0.61597	0.68627

160	34	22	0.22136	0.17369	0.19611

161	34	28	0.21609	0.18576	0.19144

162	34	44	0.17964	0.17949	0.15915

163	35	45	0.98665	0.86196	0.85449

164	35	42	0.96193	0.76205	0.82816

165	35	10	0.41450	0.33549	0.35685

166	35	6	0.39793	0.28072	0.34259

167	35	15	0.33429	0.32887	0.28780

168	36	41	1.00056	0.82580	0.82999

169	36	45	0.98665	0.86196	0.85449

170	36	42	0.19910	0.15773	0.16515

171	36	6	0.18587	0.13112	0.15418

172	36	45	0.18023	0.15745	0.14951

173	37	41	1.00056	0.82580	0.82999

174	37	40	0.34326	0.53193	0.39131

175	37	39	0.28461	0.25564	0.32444

176	37	13	0.22223	0.18409	0.25333

177	37	61	0.21648	0.16820	0.24678

178	38	41	1.00056	0.82580	0.82999

179	38	40	0.14161	0.21945	0.13060

180	38	37	0.12777	0.14565	0.11783

181	38	39	0.12475	0.11205	0.11505

182	38	9	0.11968	0.11316	0.11037

183	39	41	1.00056	0.82580	0.82999

184	39	37	0.28461	0.32444	0.25564

185	39	40	0.26534	0.41117	0.23833

186	39	10	0.23425	0.18960	0.21041

187	39	7	0.23404	0.23283	0.21022

188	40	41	1.00056	0.82580	0.82999

189	40	37	0.34326	0.39131	0.53193

190	40	39	0.26534	0.23833	0.41117

191	40	60	0.14354	0.12723	0.22243

192	40	38	0.14161	0.13060	0.21945

193	41	41	1.00056	0.82580	0.82999

194	41	36	1.00056	0.82999	0.82580

195	41	42	0.24373	0.19308	0.20116

196	41	6	0.23787	0.16781	0.19633

197	41	10	0.23534	0.19048	0.19423

198	42	41	1.00056	0.82580	0.82999

199	42	35	0.96193	0.82816	0.76205

200	42	10	0.43539	0.35240	0.34492

201	42	6	0.41007	0.28929	0.32486

202	42	44	0.37279	0.37247	0.29533

203	43	41	1.00056	0.82580	0.82999

204	43	34	0.77463	0.68627	0.61597

205	43	10	0.20444	0.16548	0.16257

206	43	28	0.19881	0.17090	0.15809

207	43	22	0.19501	0.15302	0.15506

208	44	41	1.00056	0.82580	0.82999

209	44	45	0.42945	0.37517	0.42908

210	44	42	0.37279	0.29533	0.37247

211	44	33	0.36804	0.31874	0.36773

212	44	6	0.36641	0.25848	0.36609

213	45	41	1.00056	0.82580	0.82999

214	45	33	0.98665	0.85449	0.86196

215	45	44	0.42945	0.42908	0.37517

216	45	10	0.42248	0.34196	0.36909

217	45	6	0.40599	0.28641	0.35468

218	46	41	1.00056	0.82580	0.82999

219	46	56	0.30163	0.91889	0.78170

220	46	21	0.10125	0.17086	0.26241

221	46	41	0.09195	0.07589	0.23831

222	46	63	0.08899	0.10622	0.23063

223	47	41	1.00056	0.82580	0.82999

224	47	55	0.37352	0.79781	0.74175

225	47	48	0.13079	0.16733	0.25973

226	47	32	0.12143	0.16744	0.24115

227	47	18	0.11688	0.15423	0.23211

228	48	41	1.00056	0.82580	0.82999

229	48	10	0.32626	0.26408	0.41742

230	48	9	0.30360	0.28705	0.38842

231	48	11	0.30129	0.39458	0.38547

232	48	8	0.29604	0.39361	0.37875

233	49	41	1.00056	0.82580	0.82999

234	49	44	0.24093	0.24072	0.20956

235	49	10	0.19901	0.16108	0.17311

236	49	45	0.19132	0.16714	0.16642

237	49	6	0.16181	0.11415	0.14074

238	50	41	1.00056	0.82580	0.82999

239	50	19	0.07575	0.09511	1.00000

240	50	48	0.07575	0.09691	1.00000

241	50	51	0.07575	0.50070	1.00000

242	50	54	0.07575	0.42045	1.00000

243	51	41	1.00056	0.82580	0.82999

244	51	54	0.13745	0.76293	0.90853

245	51	48	0.12494	0.15985	0.82586

246	51	21	0.09101	0.15358	0.60159

247	51	19	0.08634	0.10841	0.57072

248	52	41	1.00056	0.82580	0.82999

249	52	53	0.38019	0.75327	0.73640

250	52	48	0.13417	0.17165	0.25988

251	52	32	0.09982	0.13764	0.19336

252	52	20	0.09820	0.09641	0.19022

253	53	41	1.00056	0.82580	0.82999

254	53	52	0.38019	0.73640	0.75327

255	53	48	0.16859	0.21570	0.33403

256	53	33	0.12345	0.10691	0.24459

257	53	63	0.11749	0.14024	0.23279

258	54	41	1.00056	0.82580	0.82999

259	54	48	0.15002	0.19194	0.83272

260	54	51	0.13745	0.90853	0.76293

261	54	21	0.07816	0.13190	0.43385

262	54	19	0.07734	0.09711	0.42929

263	55	41	1.00056	0.82580	0.82999

264	55	47	0.37352	0.74175	0.79781

265	55	32	0.14299	0.19717	0.30542

266	55	18	0.12322	0.16260	0.26319

267	55	48	0.10122	0.12950	0.21621

268	56	41	1.00056	0.82580	0.82999

269	56	46	0.30163	0.78170	0.91889

270	56	21	0.08628	0.14561	0.26287

271	56	36	0.07747	0.06427	0.23603

272	56	41	0.07482	0.06175	0.22794

273	57	41	1.00056	0.82580	0.82999

274	57	17	0.36986	1.00000	1.00000

275	57	21	0.12789	0.21581	0.34579

276	58	41	1.00056	0.82580	0.82999

277	58	42	0.35383	0.28031	0.36558

278	58	16	0.29422	0.59885	0.30400

279	58	6	0.29124	0.20546	0.30091

280	58	10	0.27401	0.22178	0.28311

281	59	41	1.00056	0.82580	0.82999

282	59	15	0.88391	0.86956	0.85251

283	59	44	0.34460	0.34431	0.33236

284	59	42	0.32606	0.25831	0.31448

285	59	35	0.29976	0.25807	0.28911

286	60	41	1.00056	0.82580	0.82999

287	60	14	0.91933	0.81527	0.81491

288	60	10	0.34692	0.28080	0.30752

289	60	6	0.30462	0.21490	0.27002

290	60	13	0.30073	0.24912	0.26658

291	61	41	1.00056	0.82580	0.82999

292	61	13	0.73672	0.61029	0.57245

293	61	10	0.42695	0.34557	0.33175

294	61	7	0.42356	0.42138	0.32912

295	61	9	0.37911	0.35846	0.29458

296	62	41	1.00056	0.82580	0.82999

297	62	4	0.09973	0.35290	0.61816

298	62	27	0.06907	0.07100	0.42815

299	62	9	0.06235	0.05895	0.38649

300	62	44	0.05480	0.05475	0.33968

301	63	41	1.00056	0.82580	0.82999

302	63	3	0.74543	0.88562	0.88974

303	63	60	0.18280	0.16204	0.21819

304	63	48	0.16010	0.20483	0.19110

305	63	14	0.15541	0.13782	0.18550

306	64	41	1.00056	0.82580	0.82999

307	65	41	1.00056	0.82580	0.82999

308	65	12	0.05781	0.07512	0.67381

309	65	8	0.05781	0.07686	0.67381

310	65	29	0.04521	0.07788	0.52699

311	65	48	0.04423	0.05658	0.51552


Mutual Information Plot Example

Below is shown a matrix plot of mutual information data from the sample alignment.  High-information pairs are diagrammed.  Currently, BioEdit will produce this matrix plot with the axes, but will not add the additional annotation.  Later releases may include automatic annotation of high-scores.  The representative structure of this region from E. coli is shown in the lower left of the plot.  This region represents a portion of the RNase P RNA from E. coli.  As seen on the plot, regions of high information running perpendicular to the diagonal represent pairs of positions with highly correlated identities (they appear to influence each other), suggesting that they base-pair.  Diagonal runs of high information strongly suggest the presence of base-paired helices.  If you look at the partial E. coli RNase P structure below, you will notice localized diagonal regions of high information that correspond directly to positions along the helices (labeled H1-H5 in both the structure and the data).  Click for an example of using the data examiner with the matrix plotter to dynamically view these data.

Brown, J.W.  1998.  The Ribonuclease P Database.  Nucleic Acids Res. 26:351-352

http://jwbrown.mbio.ncsu.edu/RNaseP


Setting Mutual Information Preferences

The mutual information preferences dialog may be brought up by choosing “Preferences” from the “Options” menu and clicking the “mutual information” tab.

The options available are:

1.  Save table: check this if you want a matrix of any or all of M(x,y), R1(x), or R2(x) values.

If this option is checked, the following options are available:

a.  Link to external program: A spreadsheet such as Excel or Quattro Pro may be specified on your computer to automatically open your saved table file after the analysis is run.  This option is only available for the table.  Lists will be opened in the BioEdit text editor.

b.  M(x,y), R1(x) and R2(x) checkboxes: Choose any or all of these, depending on what you want.  The data are not stored as separate tables if you choose more than one, so if you plan to use the matrix plotter or an external program such as SpyGlass Transform to view the table, you must make a separate table for each value.  If you choose to put more than one value into the same table, the data for each position will be grouped vertically in the same order as shown on the preferences dialog.  If you only want one half of the matrix (since M(x,y) is symmetrical), you may choose to calculate above the diagonal only.  If you want to use the matrix plotter, you must have a full table.  The R1 and R2 options will cause a full table to automatically be generated.

c.  When x = y:  When x = y, M(x,y) =H(x).  If you are going to view this data in a plotting program and want the diagonal out of the picture, values along the diagonal may be set to zero.

2.  File format may be PC or Macintosh.  This will affect the output of all mutual information analyses.

3.  Alignment Numbering vs. mask numbering: You may want the numbering of positions in the output to reflect the numbers as seen in the alignment window, or to the sequential positions of the mask.  For example, if you are basing a structural analysis on the positions of a standard sequence which was used as the mask, you may want the numbering to reflect positions in that sequence rather than the gapped-out positions in the whole alignment.  This is simply offered for convenience in analyzing the data.

4.    Pbest and Nbest options: see using mutual information in BioEdit.

Once the options you would like are chosen, you may either save them, then close the dialog, or simply close the dialog.  If you close without saving, the chosen options will remain until the program is closed.  If the options are saved, they will become the new defaults.

The options on the right are specifically for the Mutual Information Examiner, which is accessible directly from an alignment window.


Using the Matrix Plotter

To plot a 2-D matrix file, choose “matrix plotter” from the “RNA” menu of an open alignment or from the main application window.  Once the plotter window is open, choose “plot a matrix” from the “plot” menu.

BioEdit will first look at the file to determine if it’s a file that it can figure out and plot (any fully tab-delimited, symmetric matrix should work).  Then, the rows and columns are counted and a dialog is presented which asks what part of the matrix to plot (defaults to all rows and columns).  For example, for a matrix representing an M(xy) analysis of 146 bacterial RNase P RNA sequences using E. coli as the sequence and numbering masks, the following dialog comes up:

Note: the limit for a single graphical plot appears to be less than about 2000 x 2000, so very large matrices must be analyzed in sections.

A plot of Mxy values for all positions of bacterial RNase P RNA present in E. coli is shown below:

After the data has been plotted, you may open the data examiner from the “view” menu.  To look at the data, simply move the mouse over the image.  The x, y coordinates and the data values will show up in the data examiner.  You may also click on a data point with the mouse and the data is reported on the top bar of the matrix plotter.  Currently, printing is not supported from this window, but may be added later.  However, the image may be copied directly to the clipboard and pasted into any application, or it can be saved as a bitmap (*.bmp).

0	The zoom control may be used to zoom in on the image from 25% to 800%.

The currently selected point may be used as a launch point for a 1-D plot of a rows or columns of matrix data (see 1-D Plots of Matrix Data Rows and Columns)

0	The threshold controls set the data thresholds for shading in the matrix plotter.  This may be useful for bringing out only high scoring data, as in the following example showing the same plot as shown above, with the low threshold set at 0.3881.  The high threshold causes anything over the set value to be shaded light blue.  This is currently set to max here.


Mutual information examiner
The mutual information examiner

If you would like to view the mutual information between any two positions from within the alignment window, make the “mutual information examiner” visible by choosing this option under the “View” menu.  This is an idea stolen directly from Dr. J. Brown’s Macintosh Hypercard program “Covariation”.

To use the mutual information examiner, first make the control visible by choosing View->Mutual Information Examiner.  The control comes up at the top of the form:

1	Enter the numbers of the positions (x and y) you would like to analyze.  If you want these to reflect the positions of a particular sequence (not gapped), set this sequence as the numbering mask and enter the positions accordingly.  The above positions correspond to the position selected on the matrix plot example.  Make sure to select all the sequences you would like to include in the analysis.  If for some reason you would like to exclude sequences from the analysis, either do not select them or deselect them by Ctrl-mouse-clicking them.  After the positions are entered, press calculate.  A window with the following information will appear:

2	To get a text summary which can be copied and pasted easily, press the Text-> button.  The following will appear in a text editor window:

If you would like to analyze several positions at once, you may specify the positions with commas and dashes.  For example, you could enter the following:

0

1	You will get a list such as the following:

2	When regions are specified as X = a-b and Y = c-d, it is assumed that what you are interested in is helices, and the positions are analyzed in antiparallel order. regardless of whether they are written as c-d or d-c.  To force the comparison of positions in a particular order, specify them such as X = a, b, c, d      Y = e, f, g, h.

3	For the list output, you may not want to weed through all of the reporting options.  Therefore, under Options->Preferences->Mutual Information, you have the following list formatting options:

4	Brown, J.W.  1991.  Phylogenetic comparative analysis of RNA structure on Macintosh computers.  Comput. Appl. Biosci.  7(3):391-393


Sample RNA structure

     Below is the current model of the secondary structure of the RNase P RNA from E. coli.  The “cruciform” region analyzed in the mutual information example  and shown in the sample matrix plot output is circled.  This image, as well as the full collection of currently known bacterial and archaeal RNase P structures and sequences can be found at the RNase P database:

Brown, J.W.  1998.  The Ribonuclease P Database.  Nucleic Acids Res. 26:351-352.

http://jwbrown.mbio.ncsu.edu/RNaseP


Configuring and Using External Applications

BioEdit provides an interface to add and configure external applications which will be added to the “Accessory Application” menu of alignment documents.  Once an application is properly configured, it can be run via a graphical interface created by BioEdit when its menu option is selected.  Although any application may be configured to be launched through BioEdit,  DOS and Win32 programs which can accept command line parameters to fully perform an analysis are most convenient.  BioEdit may be configured to automatically feed sequences to the application, then automatically load the output when the application is finished.  Multiple output files may be opened, and the output of one program may be configured to be automatically opened by another program.

Click the following headings to continue:

Adding and configuring a new application

Modifying an existing application configuration

Removing an accessory application

Storage of the configuration information

An example: Configuring ClustalW to run through a custom BioEdit interface


Adding and configuring a new application

BioEdit v2.0 and later offers a graphical interface for configuring external applications to be run from a BioEdit alignment document.  Unfortunately, there is no way to do this without knowing how to run the application independently of BioEdit.  A few programs come with the BioEdit installation and are configured already.  Permission has been granted by Joe Felsenstein to use PHYLIP programs with BioEdit (as long as no money changes hands).  Permission has also been obtained from Roderic D.M. Page to distribute TreeView.  TreeView is no longer pre-configured, however.  At the request of the author, BioEdit now comes with the TreeView install package, which is extracted into the main installation folder upon installing BioEdit.  For more information, see Installing TreeView.

To add a new application to be included in the “Accessory Applications” menu, choose “Add / Modify / Remove an  Accessory Application” from the “Accessory Applications” menu.

There are several settings which must be specified for an accessory to be run successfully through BioEdit.  Many settings will not be required for many applications and each configuration will be different, as programs are written differently by different people.  One must know how to run the program via a command line in order to configure BioEdit to run the program.  Refer to the documentation of your accessory application to learn how to run it before trying to configure it as an accessory.  The following options are present in the configuration interface.  Only the first two are universally required for all applications.

•	Name of Accessory:  This is the name that will appear in the “Accessory Applications” menu.  This can be any name you want.  It is recommended to keep it relatively short, however, as it will be a menu option in all  alignment documents.

•	Program:  The absolute or relative path to the program, including the program name (usually an .exe file, but could be a .com or a .bat  file).  To specify the path relative to the BioEdit installation directory, specify the main installation directory as “<BioEdit>“ (not case sensitive).  For example, an application named “MyApp.exe” might be placed in the “apps” directory.  To allow the whole BioEdit directory to be moved without causing a problem with finding the application, specify the path as “<BioEdit>\apps\MyApp.exe”.  (Note:  do not include the quote marks).  Alternatively, if the absolute path will be specified, you may browse the disk to find the application by pressing “Specify”.

•	Automatically feed sequences to App:  If the program analyzes sequence or alignment data (such as ClustalW or certain PHYLIP programs), you may choose to have the sequences automatically fed to the application.  This is one of the most useful benefits of running the program directly from an alignment editor.  An application that takes only one or several sequences may be done this way also, as BioEdit will only feed selected sequences at runtime (if no sequences are selected, they will all be selected automatically).

•	Specific File name required (for auto-fed sequence data):  Some applications expect a specific input file name.  For example, the PHYLIP programs all expect to process a file called “infile”.  If this is the case, check this box and enter the expected name in the “File name” input box.  Don’t include a path, since the file will be automatically saved to the directory containing the application.

•	Degap sequences:  Some applications require alignment data (such as DNAml, Protdist, DNAdist, etc.) and gaps will be included in the input.  Other programs (e.g. search programs such as BLAST) may take simple sequence data rather than alignment data.  In these cases, gaps must be removed or they will be viewed as residues.

•	Format (for auto-fed sequences):  Eight file formats are available for auto-feeding alignment / sequence data to programs: (if you have an application that requires a different format, you may have to configure the application to take a certain file name, choose not to auto-feed the sequences, and convert the file to the correct format before running the program -- or simply run the program separately.  If it would very convenient to have it run through BioEdit, simply email me at  tahall2@unity.ncsu.edu  with file format name and specifications and it would be a minor thing to write an export filter and add it to the accessory applications method of BioEdit.  If you need this, feel free to email me and I will mail back with an address where the new copy of the program may be picked up and when (or if I can’t for some reason, I will mail back and tell you that).  Currently available formats are:

•	Fasta

•	GenBank

•	PHYLIP 2 / 3.2 (PHYLIP 3)

•	PHYLIP 4

•	NBRF/PIR

•	MSF (via ReadSeq.exe:  Don Gilbert’s sequence conversion filter).

•	GCG (via ReadSeq.exe)

•	EMBL (via ReadSeq)

•	Prompt for input file:  you may want to be prompted at runtime for an input file.  BioEdit will produce an open file dialog.  The file name will be fed to the external program.

•	You may want BioEdit to prompt you at runtime to specify an output file name to feed to the program.

•	Open as alignment:  The main output of the program may be opened as a new alignment document.  (By default, there is expected to be one main output file, however, this is often not the case, and additional output files may be specified in the box titled “Additional output files:” -- this entry could be left blank and a single output could be specified as an additional output.  Functionally, this would make no difference).

•	Open as text.  If the output is a text data file, it may be opened as text in the BioEdit rich text editor.

•	Open with external program:  Perhaps the program exports tabular or matrix data that you would like to view in a spreadsheet program such as Microsoft Excel.  You may specify any external program to be launched and open the output automatically.  You may browse the disk by pressing “Specify”.  You may  also specify a path relative to the BioEdit installation directory with “<BioEdit>“.

Note:  An output file may be opened as a new alignment, as text and by an external program all   at the same time if you want.

•	Use input prefix:  Some programs expect a specific prefix at the command line to specify the input file, output file, the input of specific parameters, or all of these things.  Other programs may expect the input, output and parameters simply typed in a specific order.  If you program requires a prefix to specify the input file, check this box and enter the prefix exactly in the associated edit box.  Note:  If the prefix and the file name will be separated by a space, type that space after the prefix when configuring the application.  For example, one application may expect to see  “-i inputFile” while another may expect “input=inputFile”.  Depending on how the applications are written, the first one may not work if the space is not included, and the second one may not work if a space is included.

•	Use output prefix:  Same as input prefix.

•	Input name required:  Some applications require that an input file name be specified in the command line (e.g. ClustalW).  Others may expect a specific file name which therefore is not specified at the command line (e.g. PHYLIP programs).  If the application expects to be given the name of the input file at the command line, check this option.

•	Output name required:  Same as “Input name required”

•	Input or Output name arbitrary (check boxes labeled “Arbitrary”):  Sometimes a file name is required at the command line, but can be any file name, as long as it is specified correctly.  If this is the case, you may simply check the “Arbitrary” option(s) and BioEdit will assign input and/or output files arbitrary names.  For example, ClustalW is configured to automatically feed sequences to the application, then automatically open the output as an alignment.  The “Input name required” option is checked, and so is the “Arbitrary” option.  When ClustalW is run through this interface, input and output files are given the names “~inTemp.tmp” and “~outTemp.tmp”, respectively.

•	From stdin and To stdout:  Some programs (such as FastDNAml”) expect to get input from stdin and/or send output to stdout.  Stdin and stdout are the standard system input and output streams and the defaults are from the keyboard and to the screen, respectively.  To redirect the input or output from stdin or stdout to a file, which is necessary to run the program automatically, choose the appropriate checkbox(es).  Most programs that expect data from stdin expect it to be redirected from a file anyway.  Stdout must be redirected to a file in order to be able to save the data and/or open it up in BioEdit or another program.

•	Checkboxes:  The Interface created by BioEdit to run external applications may include yes/no choices in the form of checkboxes so that certain program options may be set easily at runtime.  These checkboxes will be drawn on the interface created by BioEdit to run the program.  Theoretically, up to 50 checkbox options may be included per application.  This limit was set because I had a hard time imagining an application that would allow anywhere close to that many options and not already have its own graphical interface.  Most programs will probably have none, and those that do will usually have fewer than 5.  To add a checkbox,  type the Caption you want to appear on the interface in the Checkboxes” drop-down list box, then press the “Add / Modify” button.  A dialog will appear in which you may specify the default state of the check box (checked or unchecked), and also the command line action to specify for each choice.  If no command line parameters will be added for a particular choice, leave it blank.  Press OK for the changes to be entered.  To modify an existing checkbox, choose it in the drop-down list and press “Add / Modify”.  To delete a checkbox, choose it from the list and press “Delete”.

•	Inputs:  Some programs may allow or expect  specific data to be entered which affects program execution (for example, CAP assembly asks the user for the minimum base overlap and the minimum percent match).  For this purpose, input boxes may be included on the accessory application interface.  Add, modify or delete  an input the same way you would  a checkbox.  Each input may also have associated with it a checkbox, which allows the option to choose whether or not to use the input at runtime.  In the configuration dialog, you  may specify a command prefix for the parameter in the command line (may or may not be required -- if not, leave it blank), and a default value that will appear as the input text in the interface.  If you want an associated checkbox, you must check this option and enter the caption for the checkbox, as well as the default state of the checkbox.  Up to 50 inputs are theoretically allowed, all with the option for associated checkboxes.

•	Additional output files:  Up to 10 different output files may be specified and specifically dealt with, in addition to the “main” default output file.  *** Note:  It is assumed here that the additional outputs are automatically generated by the program and the file names are not specified at the command line ***.  If this is not the case, this is not really a problem.  Simply either add the appropriate parameters to the default command line or include an edit control on the program interface to enter them at runtime (see below).  Add, modify or delete additional output configurations the same as checkboxes and inputs.  Each additional output configuration expects a specific file name.  In most cases, do not enter a path (just the file name), as most programs will simply save the output in the directory they are in.  If a specific path is required, it may be included.  Some programs (such as ClustalW) may produce an output file which is given the same name as the input file, only with a different extension.  In this case, specify the filename as “<infile>.ext” (for example, if the input file name is “temp.tmp” and the output is specified as “<infile>.out”, then the file should be named “temp.out”).  The output may be opened as an alignment, as text, by an external application, or any combination of these three options.  If the output is not opened by an external application, the temporary file which contains it will automatically be deleted (you must save any information you wish to keep).

•	 Default command line:  Certain parameters may be desired for all runs of the program.  In this case, specify these in the default command-line box.  For example, ClustalW allows output in GCG, GDE, PHYLIP or PIR (NBRF) formats.  Since BioEdit read NBRF/PIR files internally, “/output=PIR” may be specified as the default command line to provide an output that BioEdit quickly recognizes as an alignment file.

•	Add input file to command line: If this box is checked, BioEdit will automatically construct a command line that includes the input file and command prefix (if there is one), depending on the configuration for the input file.  It may be necessary to leave this box unchecked and write the input file specs right into a default command line if the absolute position in the command line is important and it is not at the beginning or end.  Otherwise, select either the “at beginning” or “at end” option to specify where to place the input file name in the command line.

•	Add output file to command line:  same as for input file

•	View documentation option:  If documentation comes with the program, or you are configuring the program for other people who are less familiar with it, you may want to include an automatic link to the documentation.  This will work if the documentation is in a single text or rich text file.  If this option I chosen, you may specify the doc file by pressing “Specify” or by entering the path in the “Documentation file:” box.  The designation “<BioEdit>” may be used to specify a path relative to the BioEdit installation directory.  If this option is chosen, a button will appear on the interface with the label “View Documentation”.

•	Include an options box (to type in command-line parameters).  If you would like an input box to appear on the interface which allows you to enter additional command-line parameters at runtime, check this option.  If you have an application which requires a very unique arrangement of command line options, but is still convenient to run through BioEdit, you may create an interface that has only this input box and simply enter the command-line at runtime.

•	Redirect stdout.  Some programs may print data or progress information to the screen when running.  If you would rather have this information saved to a file and opened by BioEdit for viewing later, choose redirect stdout, specify a file name, and configure that file to be opened as an additional output file (see above).

•	Redirect stdin:  Some programs, such as programs in the PHYLIP package, provide a menu when launched that allows settings to be specified.  If a specific set of settings will be used all of the time, a file may be created with the exact series of keystrokes that would specify these settings from the menu(s), then stdin may be redirected to this file rather than the keyboard.  So far, this does not seem to work when programs are launched from within BioEdit.  There does not seem to be any good reason that it should not work however, and this option has not been completely removed because I plan to fix it in the future.  For now, I’m not sure if the option will work in some cases and not in others, but it is probably best to not use this option until it is figured out.

•	General description:  In this box, type a description of the program that will be printed on the interface at runtime.  The description may be as long as you want, but it must be entered as a single line of text.  If any carriage returns are entered, the description will be truncated at the first return character.  This is because of the way the configuration data is stored.  This description will often contain a short description of the program and a reference to the author(s).

•	“Add / Modify”:  Pressing this button will save the entered information and list the current configuration in the “Current configuration” box.

0	Pressing Close will close the dialog without updating the information.

1	To print the current configuration, press the “Print Configuration” button.

2


Modifying an existing configuration

To modify an existing application configuration, first bring up the configuration dialog by choosing the  “Add / Remove / Modify an Accessory Application” from the “Accessory Application” menu.  Press the arrow on the “Name of Accessory” drop-down box to drop down a list of currently configured applications.  Choose the application you would like to modify and press “Open”.  Reconfigure the application the way you want.

You may modify the information associated with checkboxes and inputs at any time by choosing the title of the checkbox or input you would like to modify from the drop down lists associated with them, then pressing the appropriate “Add / Modify” button.  You may delete any checkbox or input by highlighting its name (or typing it) in the appropriate drop-down box and pressing the associated “Delete” button.  Likewise, additional output file handling may be configured in the same manner.


Removing an accessory application

To remove an accessory application from the configuration, simply bring the accessory applications dialog up, then choose the name of the application you would like to remove from the drop down list labeled “Name of Accessory”.  Press the “Delete” button to remove the accessory.


Storage of Accessory Application Configuration Information

BioEdit accessory application information is stored in a file called “accApp.ini” which is found in the “apps” folder of the BioEdit installation.  This file is organized in the same manner as the BioEdit.ini file found in your Windows directory.  The configuration information for the ClustalW Sample configuration is shown below.  As you can probably see, the information is a little cryptic as is, though it can be deciphered with a minimal effort.  It is much easier to configure applications using the graphical interface than directly editing this configuration file, and a more meaningful summary of each configuration showing the same information as below  is displayed on the interface and may be printed from the dialog as well.  This file can be directly edited, however, following the general format laid out below.  Checkboxes are designated as c<checkbox #>, starting at 0, and inputs are i<input #>, starting at 0.  All of the categories of data are written as shown below.  Parameters which are not used or have no value are written into the configuration as blanks.  Values which may be either true or false are written as 1 or 0, respectively.

[ClustalW multiple alignment program]

Program=<BioEdit>\apps\clustalw.exe

Auto-Feed=1

Degap Sequences=0

Auto-Feed File Format=1

Auto-Feed File Name Required=0

Specific File Name=

Prompt for Input File=0

Prompt for Output File=0

Open Output as Alignment=1

Open Output as Text=0

Open Output with External Program=0

External Program Name=

Input File Prefix=/INFILE=

Output File Prefix=/OUTFILE=

Specify Input File Name=1

Specify Output File Name=1

Input File Name=

Output File Name=

Input File Prefix Required=1

Output File Prefix Required=1

Input File Name Arbitrary=1

Output File Name Arbitrary=1

Redirect input from stdin=0

Redirect output from stdout=0

Default Command Line=/output=PIR

View Documentation Option=1

Documentation File=<BioEdit>\apps\clustalw.txt

Description=ClustalW:  Thompson, J.D., Higgins, D.G. and Gibson, T.J. (1994).  CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position specific gap penalties and weight matrix choice. Nucleic Acids Research, submitted, June 1994.

Include Additional Options Box=1

Redirect General stdout=1

Stdout Redirected Filename=clustal.sto

Redirect General stdin=0

Stdin Redirected Filename=

c0 Title=Full Multiple Alignment

c0YES=/ALIGN

c0NO=

c0 Default=1

c1 Title=Calculate NJ Tree

c1YES=/TREE

c1NO=

c1 Default=0

c2 Title=FAST Algorithm for Guide Tree

c2YES=/QUICKTREE

c2NO=

c2 Default=0

i0 Title=Number of Bootstraps

i0 Prefix=/BOOTSTRAP=

i0 Default=1000

i0 CheckBox=1

i0 CheckBox Title=Bootstrap NJ Tree

i0 CheckBox Default=1

Additional Output 0 Name=<infile>.dnd

Additional Output 0 Open as Text=0

Additional Output 0 Open as Alignment=0

Additional Output 0 Open with External Program=1

Additional Output 0 External Program Name=<BioEdit>\apps\treev32.exe

Additional Output 1 Name=clustal.sto

Additional Output 1 Open as Text=1

Additional Output 1 Open as Alignment=0

Additional Output 1 Open with External Program=0

Additional Output 1 External Program Name=


Accessory application configuration example

Accessory Application Example: Configuring ClustalW to run through a custom BioEdit interface

Below is a step-by-step example of configuring an external application to run from and work with BioEdit.  This example configures ClustalW, for which an interface was already directly programmed into BioEdit before addition of the configuration interface.  You will see that, after configuring ClustalW correctly, calling the new menu option will bring up an interface that looks slightly different than the one included in BioEdit, but is functionally identical.  Also, if you run ClustalW from the new interface, compared to the old one, it will run in a “thread” separate from the main BioEdit application, which means that you can continue to work on other stuff while the accessory application runs simultaneously in the background.

*** Step 0: Before step 1 of any application configuration, you must know what command line options are required and what their specific designations are.  If you are dealing with a new program you have not used before, you probably need to read the documentation.

To configure ClustalW:

•	Bring up the configuration dialog by choosing “Add / Remove / Modify an Accessory Application” from the “Accessory Application” menu.

•	Type “ClustalW Example Application” in the input labeled “Name of Accessory”.

•	To specify the program executable, press the “Specify” button and choose “clustalw.exe” (the directory browser should start you off in the “apps” directory which contains clustalw.exe.  Replace the path up through “BioEdit” with “<BioEdit> to specify a relative path.  For example, if, after clicking on clustalw.exe, the Program box contains the text “C:\BioEdit\apps\clustalw.exe”, change it to “<BioEdit>\apps\clustalw.exe”.

•	check the “Automatically feed sequences to App” box.

•	Check “Fasta” as the output format.

•	If you want the sequences degapped before running ClustalW, check the  “Degap Sequences” box.  Otherwise leave this box unchecked (it shouldn’t really matter in this case)

•	Check the box titled “Open output as new alignment” to have BioEdit automatically open the new alignment as a new document when ClustalW is finished running.  Leave other boxes in this area unchecked and ignore the “open with external program” option.

•	Check both “Use input prefix” and “Use output prefix”.  These options tell BioEdit that the command line must use specific prefixes to indicate which parameter specifies the input file name and which specifies the output file name to ClustalW.

•	For the “Input file command prefix”, type “/INFILE=“

•	For the “Output file command prefix”, type “/OUTFILE=“

•	Check the boxes labeled “Input name required” and “Output name required”.  These tell BioEdit that ClustalW that the names of the input and output files are needed (they are not some set file name that the program always looks for).

•	For both, check the “Arbitrary” box to indicate that any arbitrary file name may be used for the input and output names, as long as ClustalW is told those names.

•	Leave the boxes called “Space between input prefix and command” and Space between output prefix and command” unchecked.

•	Make sure that the box for “Add input file to command line” is checked and check the “at beginning” box.

•	Check the “Add output file to command line” and again check the “at beginning” box.

•	Next, we will add the same checkbox options as seen on the internal ClustalW interface:

•	In the “CheckBoxes input, type “Full Multiple Alignment” and press “Add / Modify”.  The same name will appear as the “Title” parameter in the dialog that pops up.  For the “Command if checked” parameter, type “/ALIGN”.  Leave the “Command if not checked” input blank.  Check the “Default checked” box.

•	In the “CheckBoxes input, type “Calculate NJ Tree” and press “Add / Modify”.  For the “Command if checked” parameter, type “/TREE”.  Leave the “Command if not checked” input blank.  Do not check the “Default checked” box.

•	Create a checkbox called  “FAST Algorithm for Guide Tree”.   For the “Command if checked” parameter, type “/QUICKTREE”.  Leave the “Command if not checked” input blank.  Do not check the “Default checked” box.

•	Create an input called  “Number of Bootstraps”.   For the “Command prefix” parameter, type “/BOOTSTRAP=”.  In the “Default value input, type 1000.  Check the box labeled “Associate a checkbox”.  Name the checkbox “Bootstrap NJ Tree” and choose the default state as checked.  This will allow you to choose whether or not to bootstrap, and, if done, the number of bootstraps.

•	In the “Default command line” box, type “ /output=PIR”.  This specifies that the program save the output as an NBRF/PIR file.

•	Check the “View documentation option” box, then press the “Specify doc file” button.  Choose “clustalw.txt” as the documentation file.  Modify the beginning of the path to the doc file as <BioEdit>.

•	Check the box labeled “Include an options box (to type in command-line parameters)”.

•	In the “General description” box, type “ClustalW:  Thompson, J.D., Higgins, D.G. and Gibson, T.J. (1994).  CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position specific gap penalties and weight matrix choice. Nucleic Acids Research, submitted, June 1994.”, without using any return characters (type as a single continuous line of text).

•	If TreeView has already been installed, in the “Additional output files” box type “<infile>.dnd” and press the “Add / Modify” button next to this box.  In the dialog that appears check “Open with external program”, then Choose “specify” and browse to the file treev32.exe (the executable for TreeView -- this will likely be in C:\Program Files\Rod Page\Tree View if you chose the defaults when installing).  This specifies that a file will be created by ClustalW with the same base file name as the input, but with an extension of .dnd.  This file is a phylogenetic tree, and may be opened by treev32.exe, which is the executable for TreeView version 1.5.2, Copyright Roderic D.M. Page, 1998.  This will cause this output file to be opened automatically with TreeView.

•	In the “Additional output files” box type “clustal.sto” and press the “Add / Modify” button next to this box. In the dialog that appears check “Open as new text document”.  Then press OK.

•	Check the “Redirect general stdout to file” and enter “clustal.sto” in the input box.  This will cause the general screen output to be directed to a file called “clustal.sto” which will be brought up as a text document in BioEdit after ClustalW is finished executing.

•	Press the “Add / Modify” button at the bottom of the dialog.  A configuration summary should come up in the “Current Configuration” box which looks something like this:

BioEdit version 4.7.1 accessory application configuration

0	7/31/99 10:40:51 PM

1	Accessory: ClustalW example application

2	Program: <BioEdit>\APPS\Clustalw.exe

3	Auto-Feed Sequences: Yes

4	Auto-Feed File Format: Fasta

5	Degap sequences: No

6	Prompt for name of input file: No

7	Open output as new alignment: Yes

8	Open output as text document: No

9	Open output with external program: No

10	Prompt for name of output file: No

11	Prefix required for input file: Yes

12	Space after input prefix: No

13	Prefix for input file: /INFILE=

14	Use arbitrary default input file name: Yes

15	Prefix required for output file: Yes

16	Space after output prefix: No

17	Prefix for output file: /OUTFILE=

18	Specify input file name: Yes

19	Use arbitrary default output file name: Yes

20	Input file name:

21	Specify output file name: Yes

22	Output file name:

23	Add input file to command line: Yes

24	   Add input file at beginning of command line.

25	Add output file to command line: Yes

26	   Add output file at beginning of command line.

27	Redirect input from stdin: No

28	Redirect output from stdout: No

29	Additional output file 1:

30	   File Name: <infile>.dnd

31	   Open as new text document: No

32	   Open as new alignment document: No

33	   Open with external program: Yes

34	   External program name: C:\Program Files\Rod Page\TreeView\treev32.exe

35	Additional output file 2:

36	   File Name: clustal.sto

37	   Open as new text document: Yes

38	   Open as new alignment document: No

39	   Open with external program: No

40	Default command line: /output=PIR

41	Redirect general stdout: Yes

42	Redirect general stdout to file: clustal.sto

43	Redirect general stdin: No

44	Add option to view documentation: Yes

45	Documentation file: C:\BioEdit\APPS\Clustalw.txt

46	Include a box for additional command-line options: Yes

47	Description ClustalW:  Thompson, J.D., Higgins, D.G. and Gibson, T.J. (1994).  CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position specific gap penalties and weight matrix choice. Nucleic Acids Research, submitted, June 1994.

48	CheckBox 1:

49	   Title: Full Multiple Alignment

50	   Command when checked: /ALIGN

51	   Command when not checked:

52	   Default state: Yes

53	CheckBox 2:

54	   Title: Calculate NJ Tree

55	   Command when checked: /TREE

56	   Command when not checked:

57	   Default state: No

58	CheckBox 3:

59	   Title: FAST Algorithm for Guide Tree

60	   Command when checked: /QUICKTREE

61	   Command when not checked:

62	   Default state: No

63	Input 1:

64	   Title: Number of Bootstraps

65	   Command Prefix: /BOOTSTRAP=

66	   Default value: 1000

67	   Include associated CheckBox: Yes

68	        Associated CheckBox name: Bootstrap NJ Tree

69	        Associated CheckBox default state: Yes

•	Press “Close” to close the dialog.  You will get a message asking if you want to restart BioEdit for the new changes to take effect.  Press “Yes” and wait for BioEdit to close down and restart.  Now the menu option “ClustalW Example Application” should appear in the “Accessory Applications” menu.

•	Open a file containing some homologous sequences to be aligned.  Choose “ClustalW Example Application” from  the “Accessory Applications” menu.  You should see the following interface, which is functionally identical to the one incorporated directly into BioEdit.


World Wide Web bookmarks
Constructing World Wide Web Bookmarks for BioEdit

BioEdit may store up to 500 World Wide Web bookmarks for which appear in the World Wide Web menu at startup.  These bookmarks may be used with your favorite external Web browser as a convenient link to sequence analysis-related web sites from within a sequence editor.

The BioEdit web bookmarks are stored in a raw text file called “bookmark.txt”.  This file is found in the “apps” folder of the install directory.  If the name of this file is changed, BioEdit will not recognize it.  If this file is corrupted, BioEdit will allow you to automatically write a default file with some canned bookmarks.

The required format for the bookmarks file is very simple.  Each entry consists of two lines of text, one for the description and one for the URL.  The format is as follows:

name=<description>

address=<exact URL>

The following example shows the default bookmarks file that comes with BioEdit (or did at one time):

name=WebCutter Restriction Map Generator

address=http://www.firstmarket.com/cutter/cut2.html

name=BLAST at NCBI

address=http://www.ncbi.nlm.nih.gov/cgi-bin/BLAST/nph-blast?Jform=1

name=PSI-BLAST at NCBI

address=http://www.ncbi.nlm.nih.gov/cgi-bin/BLAST/nph-psi_blast

name=Pub Med Literature Search

address=http://www.ncbi.nlm.nih.gov/PubMed/medline.html

name=National Center for Biotechnology information

address=http://www.ncbi.nlm.nih.gov/

name=Pedro's BioMolecular Research Tools

address=http://www.fmi.ch/biology/research_tools.html

name=information about sequence logos (Tom Schneider)

address=http://www.bio.cam.ac.uk/seqlogo/

name=Sequence logo submission form

address=http://www.bio.cam.ac.uk/cgi-bin/seqlogo/logo.cgi

name=The Institute for Genomic Research (TIGR)

address=http://www.tigr.org/tigr_home/index.html

name=The RNase P Database

address=http://www.mbio.ncsu.edu/RNaseP/home.html

name=NCSU Microbiology Web Server

address=http://www.mbio.ncsu.edu/

That’s all there is to it.  If  a bookmark entry is not formatted correctly, it will be ignored.

If you have made an entry and it does not appear in the World Wide Web menu after restarting BioEdit, check the entry to make sure the format matches exactly.

You may edit the bookmarks in any text editor.  You may also edit them by choosing “View bookmarks” from the World Wide Web menu.  The bookmarks will appear in a text window with the option to edit and save.  At this time there is no graphical interface for bookmark manipulation.


Saving sequence annotation information

BioEdit will save much of the information contained within a standard GenBank formatted file.

The following fields may be included in any GenBank or BioEdit file:

LOCUS

0	DEFINITION

1	TITLE (BioEdit specific -- not standard in GenBank format)

2	ACCESSION

3	PID or NID

4	DBSOURCE

5	KEYWORDS

6	SOURCE

7	REFERENCES

8	COMMENT

9	FEATURES

0	For a description of these fields, see GenBank file format.

1	Note that information other than sequence, title and length will only be saved in GenBank format.  It may be easiest to keep most sequence files in GenBank format and only use other formats when a specific conversion is needed.

2


Six-frame translation

A DNA sequence may be translated in all six reading frames into all possible open reading frames (simple codon stretches, actually) by highlighting the sequence title in the document window and choosing either “Sorted Six-Frame Translation” or “Unsorted Six-Frame Translation” from the “Sequence” menu.  You will get a dialog asking you to specify the minimum ORF size, maximum ORF size, and start codon.

Minimum ORF size:  Only codon stretches equal to or greater in length than the minimum will be reported.

Maximum ORF size:  Only codon stretches equal to or lesser in length than the maximum will be reported.  Leave this entry blank to allow unlimited ORF size.

Start codon:  Choose ATG or Any from the drop-down box, or type in any three-base codon you wish.  Only codon stretches beginning with this start codon will be reported.  If “Any” is chosen, codon stretches will basically go from stop to stop.

Differences between sorted and unsorted translations:

Sorted:  ORFs will be reported in order of start position.  Negative-frame sequences are sorted according to their end positions (first position along the positive sequence).  The number of sequences which can be translated and sorted is limited to something above 10,500 sequences.  The exact number, I am not sure of.  If a sorted translation becomes too large, resources for storing the sequences to be sorted runs out.  If this happens, BioEdit will tell you, then present the sequences it was able to translate.  Multiple sequences may be translated into a single ORF list suitable for BLAST database creation.

Unsorted:  Sequences are reported in the order that their stop codons are encountered in a once-through, 6-frame simultaneous pass through the entire sequence.  The codon stretches are written into a file as they are encountered and therefore do not need to be stored in memory.  Very long lists can thus be generated.  Currently, only one sequence at a time may be translated this way.

No sophisticated ORF identification is currently implemented.  sequences are simply translated into raw codon stretches.  A future addition may allow the user to require threshold matches to consensus promoters and/or ribosome-binding sites for ORF reporting.

Possible open reading frames are reported as shown in the following example:

>ecoli.m52: 620 to 111: Frame -2       170 aa

0	STKVFNCASGNPGWAAASPVKSSAKIRSASLILGKASWPLMVFSIIATRWLVIL

1	AGAERTVATCPCLALLSRISATRRKRSAFATDVPPNFNTRMVVTSLPLVEKKSP

2	HCQVRAFFCVSCTRQPAPLPVVMVMVVVMVVLMRFMDVVYSVIFICLCAMPILV

3	KVFSDLSQ

4	>ecoli.m52: 292 to 2796: Frame 1       835 aa

5	QCGLFFSTKGNEVTTMRVLKFGGTSVANAERFLRVADILESNARQGQVATVLSA

6	PAKITNHLVAMIEKTISGQDALPNISDAERIFAELLTGLAAAQPGFPLAQLKTF

7	VDQEFAQIKHVLHGISLLGQCPDSINAALICRGEKMSIAIMAGVLEARGHNVTV

8	IDPVEKLLAVGHYLESTVDIAESTRRIAASRIPADHMVLMAGFTAGNEKGELVV

9	LGRNGSDYSAAVLAACLRADCCEIWTDVDGVYTCDPRQVPDARLLKSMSYQEAM

10	ELSYFGAKVLHPRTITPIAQFQIPCLIKNTGNPQAPGTLIGASRDEDELPVKGI

11	SNLNNMAMFSVSGPGMKGMVGMAARVFAAMSRARISVVLITQSSSEYSISFCVP

12	QSDCVRAERAMQEEFYLELKEGLLEPLAVTERLAIISVVGDGMRTLRGISAKFF

13	AALARANINIVAIAQGSSERSISVVVNNDDATTGVRVTHQMLFNTDQVIEVFVI

14	GVGGVGGALLEQLKRQQSWLKNKHIDLRVCGVANSKALLTNVHGLNLENWQEEL

15	AQAKEPFNLGRLIRLVKEYHLLNPVIVDCTSSQAVADQYADFLREGFHVVTPNK

16	KANTSSMDYYHQLRYAAEKSRRKFLYDTNVGAGLPVIENLQNLLNAGDELMKFS

17	GILSGSLSYIFGKLDEGMSFSEATTLAREMGYTEPDPRDDLSGMDVARKLLILA

18	RETGRELELADIEIEPVLPAEFNAEGDVAAFMANLSQLDDLFAARVAKARDEGK

19	VLRYVGNIDEDGVCRVKIAEVDGNDPLFKVKNGENALAFYSHYYQPLPLVLRGY

20	GAGNDVTAAGVFADLLRTLSWKLGV

21	>ecoli.m52: 2792 to 3730: Frame 2       313 aa

ESDMVKVYAPASSANMSVGFDVLGAAVTPVDGALLGDVVTVEAAETFSLNNLGR

0	FADKLPSEPRENIVYQCWERFCQELGKQIPVAMTLEKNMPIGSGLGSSACSVVA

1	ALMAMNEHCGKPLNDTRLLALMGELEGRISGSIHYDNVAPCFLGGMQLMIEEND

2	IISQQVPGFDEWLWVLAYPGIKVSTAEARAILPAQYRRQDCIAHGRHLAGFIHA

3	CYSRQPELAAKLMKDVIAEPYRERLLPGFRQARQAVAEIGAVASGISGSGPTLF

4	ALCDKPETAQRVADWLGKNYLQNQEGFVHICRLDTAGARVLEN

5	... etc.

6	The ORF titles are constructed as follows:

7	<sequence title>: <start base> to <end base>: Frame <frame number>     <sequence length>


Amino Acid and Nucleotide Composition

Amino acid or nucleotide composition summaries and plots may be obtained by choosing “Amino Acid Composition” from the “Protein” submenu of the “Sequence” menu, or “Nucleotide Composition” form the “Nucleic Acid” submenu of the “Sequence” menu, respectively.  Bar plots show the Molar percent of each residue in the sequence.  For nucleic acids, degenerate nucleotide designations are added to the plot if and as they are encountered.  For example, a sequence that has only A, G, C and T will have four bars on the graph, but if there are R’s, Y’s , M’s, etc in the sequence, they will be added to the summary.   For example, a nucleotide composition plot of the following sequence would look as follows

ATGAGCCAGGATTTTAGCCGTGAAAAACGTCTGCTGACCCCGCGTCATTTTAAAGCGGTGTTTGATAGCCCGACCGGC

AAAGTGCCGGGCAAAAACCTGCTGATTCTGGCGCGrTGAAAACGGCCTGGATCATCCGCGTCTGGGCCTGGTGyATTG

GCAAkAAAAAGCGTGAAACTGGCGGTGCrAGCGTAACCGTCTGAAACGTCTGATGCGTGATArGCTTTCGTCTrGAAC

CAGCAyGCTGCTGGyCGGGCCTGGATATTyGTGATTGTGGCGCGTAAAGGCCTGGGCGAAATTGAAAACCCGGAACTG

CArTCAGCATTTTGGCAAACTGTGGAAACGTCTGGCGCGTAGCCGTCCGyACCCCGGCGGTrGACCGCGAArCAGCGC

GGkGCGTGGATAGCCAGGATGCG

Bar colors correspond to the residue colors specified in the color table.

A corresponding summary is generated and displayed in the text editor:

DNA molecule: Pseudomona

0	Length = 413 base pairs

1	Molecular Weight = 133038 Daltons, single stranded

2	Molecular Weight = 267066 Daltons, double stranded

3	G+C content = 54.96%

4	A+T content = 41.65%

5	Nucleotide  Number   Mol%

6	    A        91      22.03

7	    C        99      23.97

8	    G        128     30.99

9	    T        81      19.61

10	    R        7       1.69

11	    Y        5       1.21

    K        2       0.48

0	Amino Acid plots and summaries are similar, though residues other than the standard 20 amino acids are ignored.

1	Molecular weights:

2	The molecular weights of proteins are calculated as the sum of the internal molecular weights of each amino acid, or

3	   where R = the side group, plus 2 hydrogens and an oxygen at the amino and carboxy termini, respectively.

5	Nucleotide weights are calculated as the sum of the monophosphate forms of each ribonucleotide or deoxyribonucleotide minus one water each.  One water (18 Da) is added at the end to represent the 3’ hydroxyl at the end of the chain  and one more hydrogen at the 5’ phosphate end.  Nucleotide weights used are:

RNA               M.W.

0	   Adenosine      328.2

1	   Guanosine      344.2

2	   Cytidine       304.2

3	   Uridine        305.2

4	   Average AUGC   320.5

5	DNA

6	   dAdenosine     312.2

7	   dGuanosine     328.2

8	   dCytidine      288.2

9	   dThymidine     287.2

10	   Average dATGC  304.0

0	These values were derived by adding all atoms in each nucleotide monophosphate minus one oxygen and two hydrogens using:

1	C = 12.011

2	O = 15.9994

3	N = 14.00674

4	P = 30.973762

5	H = 1.00794


Hydrophobicity Profiles

Mean Hydrophobicity profiles are generated using the general method of Kyte and Doolittle (1982).  Kyte and Doolittle compiled a set of “hydropathy scores” for the 20 amino acids based upon a compilation of experimental data from the literature.  A window of defined size is moved along a sequence, the hydropathy scores are summed along the window, and the average (the sum divided by the window size) is taken for each position in the sequence.   The mean hydrophobicity value is plotted for the middle residue of the window.

Hydrophobic moment profiles plot the hydrophobic moment of segments of defined length along the sequence.  For example, if the window size is 21 residues, the plotted value at a residue is the hydrophobic moment of the window of ten residues on either side of the current residue.  Hydrophobic moment is calculated according to Eisenberg et. al. (1984):

μΗ = {[ΣHnsin(δn)]^2 + [ΣHncos(δn)]}^(1/2),

Where μH is the hydrophobic moment, Hn is the hydrophobicity score of residue H at position n, δ=100 degrees, n is position within the segment, and each hydrophobic moment is summed over a segment of the same defined window length.

Mean hydrophobic moment profiles plot the average hydrophobic moment for a segment of defined window length, using the same window width to calculate the hydrophobic moments.  For example, for a window size of 21, the hydrophobic moments of 21 segments, each 21 residues long and each value representing the start residue of the corresponding segment, are summed and their average is taken and plotted for the center residue of the segment.

Previous versions of BioEdit simply plotted the mean hydrophobicity of a sequence segment at the first position of the segment.  The result was that the mean hydrophobicity at the end of the plot, after the point L-W, where L is the sequence length and W is the window size, the mean value would become deceptively closer to 0.  The current method is more akin to the method of Kyte and Doolittle, and may be more familiar.

Note:  I do not have the expertise to make any claims about the predictive power of these profile plots.  BioEdit makes no conclusions about hydrophobic and/or transmembrane segments of proteins, and interpretation of these plots is up to the judgment of the user.

For information and references about hydrophobicity analysis of proteins, see:

Cornette, J.L., K.B. Cease, H. Margalit, J.L. Spouge, J.A. Berzofsky and C. DeList.  1987.  Hydrophobicity Scales and Computational Techniques for Detecting Amphipathic Structures in Proteins.  J. Mol. Biol. 195: 659-685.

Eisenberg D. E. Schwarz, M. Komaromy and R.Wall. 1984.  Analysis of membrane and surface protein sequences with the hydrophobic moment plot.   J. Mol. Biol. 179(1):125-42.

Hopp, T.P. and K.R. Woods.  1981.  Prediction of protein antigenic determinants from amino acid sequences.  Proc. Natl. Acad. Sci. USA.  78(6): 3824-3828.

Kyte, J. and R.F. Doolittle.  1982.  A Simple Method for Displaying the Hydrophobic Character of a Protein.  J. Mol. Biol.  157: 105-142.

Parker, J.M.R., D. Guo and R.S. Hodges.  1986.  New Hydrophilicity Scale Derived from High-Performance Liquid Chromatography Peptide Retention Data: Correlation of Predicted Surface Residues with Antigenicity and X-ray-Derived Accessible Sites.  Biochemistry 25: 5425-5432.

The following plots were generated from the sample file called “bacterio.gb”, included in the main BioEdit folder.  This is an alignment of Archaeal bacteriorhodopsin proteins.  Bacteriorhodopsin is a membrane-bound, light energy-transducing proton pump with similarity to the rhodopsin.  Bacteriorhodopsin is a membrane bound protein with several membrane-spanning regions.  The following plots show:

1.  Kyte and Doolittle mean hydrophobicity profile of  Halobacterium holbium bacteriorhodopsin, window size = 9

2.  Kyte and Doolittle mean hydrophobicity profile of eight unaligned bacteriorhodopsins, window size = 9

3.  Kyte and Doolittle mean hydrophobicity profile of  eight aligned bacteriorhodopsins, window size = 9.  This demonstrates that superimposed hydrophobicity profiles may be used to help examine the quality of an alignment.

4.  Hydrophobic moment profile for the 8 aligned sequences, window size =9

5.  Mean hydrophobic moment profile for the 8 aligned sequences, window size = 9

1.

2.

3.

4.

5.


Nucleic Acid Translation with Codon Usage

Nucleic acid sequences may be translated into predicted protein sequences with codon triplets separated by spaces.

Choose “Translate” from the “Protein” submenu of the “Sequence” menu, then choose the frame in which to translate.

Example:  The coding region for a hypothetical open reading frame from Methanobacterium is shown below:

>MTH671 coding region

ATGGTTGCAGTACCCGGCAGTGAGATACTGAGCGGTGCACTACACGTTGTCTCCCAGAGCCTCCTCATACCGGTTATA

GCAGGTCTACTGTTATTCATGGTATACGCCATAGTGACCCTCGGAGGGCTCATATCAGAGTACTCTGGAAGGATAAGG

ACTGATGTTAAGGAACTTGAATCGGCAATAAAATCAATTTCAAACCCAGGAACCCCTGAAAAGATAATTGAGGTCGTC

GATTCGATGGACATACCACAGAGCCAGAAGGCCGTGCTCACTGATATCGCAGGGACAGCTGAACTCGGACCAAAATCA

AGGGAGGCCCTCGCAAGGAAGTTGATAGAGAATGAGGAACTCAGGGCTGCCAAGAGCCTTGAGAAGACAGACATTGTA

ACCAGACTCGGCCCAACCCTTGGACTGATGGGGACACTCATACCCATGGGTCCAGGACTCGCAGCCCTCGGGGCAGGT

GACATCAATACACTGGCCCAGGCCATCATCATAGCCTTCGATACAACAGTTGTGGGACTTGCATCAGGGGGTATAGCA

TACATCATCTCCAAGGTCAGGAGAAGATGGTATGAGGAGTACCTCTCAAATCTTGAGACAATGGCCGAGGCAGTGCTG

GAGGTGATGGATAATGCCACTCAGACGCCGGCGAAGGCTCCTCTCGGATCAAAA

A frame 1 of this sequence is displayed as follows in the BioEdit text editor:

>MTH671 coding region

0	1     ATG GTT GCA GTA CCC GGC AGT GAG ATA CTG AGC GGT GCA CTA CAC   45

1	1     Met Val Ala Val Pro Gly Ser Glu Ile Leu Ser Gly Ala Leu His   15

2	46    GTT GTC TCC CAG AGC CTC CTC ATA CCG GTT ATA GCA GGT CTA CTG   90

3	16    Val Val Ser Gln Ser Leu Leu Ile Pro Val Ile Ala Gly Leu Leu   30

4	91    TTA TTC ATG GTA TAC GCC ATA GTG ACC CTC GGA GGG CTC ATA TCA   135

5	31    Leu Phe Met Val Tyr Ala Ile Val Thr Leu Gly Gly Leu Ile Ser   45

6	136   GAG TAC TCT GGA AGG ATA AGG ACT GAT GTT AAG GAA CTT GAA TCG   180

7	46    Glu Tyr Ser Gly Arg Ile Arg Thr Asp Val Lys Glu Leu Glu Ser   60

8	181   GCA ATA AAA TCA ATT TCA AAC CCA GGA ACC CCT GAA AAG ATA ATT   225

9	61    Ala Ile Lys Ser Ile Ser Asn Pro Gly Thr Pro Glu Lys Ile Ile   75

10	226   GAG GTC GTC GAT TCG ATG GAC ATA CCA CAG AGC CAG AAG GCC GTG   270

11	76    Glu Val Val Asp Ser Met Asp Ile Pro Gln Ser Gln Lys Ala Val   90

12	271   CTC ACT GAT ATC GCA GGG ACA GCT GAA CTC GGA CCA AAA TCA AGG   315

13	91    Leu Thr Asp Ile Ala Gly Thr Ala Glu Leu Gly Pro Lys Ser Arg   105

14	316   GAG GCC CTC GCA AGG AAG TTG ATA GAG AAT GAG GAA CTC AGG GCT   360

15	106   Glu Ala Leu Ala Arg Lys Leu Ile Glu Asn Glu Glu Leu Arg Ala   120

16	361   GCC AAG AGC CTT GAG AAG ACA GAC ATT GTA ACC AGA CTC GGC CCA   405

17	121   Ala Lys Ser Leu Glu Lys Thr Asp Ile Val Thr Arg Leu Gly Pro   135

18	406   ACC CTT GGA CTG ATG GGG ACA CTC ATA CCC ATG GGT CCA GGA CTC   450

19	136   Thr Leu Gly Leu Met Gly Thr Leu Ile Pro Met Gly Pro Gly Leu   150

20	451   GCA GCC CTC GGG GCA GGT GAC ATC AAT ACA CTG GCC CAG GCC ATC   495

21	151   Ala Ala Leu Gly Ala Gly Asp Ile Asn Thr Leu Ala Gln Ala Ile   165

22	496   ATC ATA GCC TTC GAT ACA ACA GTT GTG GGA CTT GCA TCA GGG GGT   540

23	166   Ile Ile Ala Phe Asp Thr Thr Val Val Gly Leu Ala Ser Gly Gly   180

24	541   ATA GCA TAC ATC ATC TCC AAG GTC AGG AGA AGA TGG TAT GAG GAG   585

25	181   Ile Ala Tyr Ile Ile Ser Lys Val Arg Arg Arg Trp Tyr Glu Glu   195

26	586   TAC CTC TCA AAT CTT GAG ACA ATG GCC GAG GCA GTG CTG GAG GTG   630

27	196   Tyr Leu Ser Asn Leu Glu Thr Met Ala Glu Ala Val Leu Glu Val   210

28	631   ATG GAT AAT GCC ACT CAG ACG CCG GCG AAG GCT CCT CTC GGA TCA   675

29	211   Met Asp Asn Ala Thr Gln Thr Pro Ala Lys Ala Pro Leu Gly Ser   225

30	676   AAA   678

31	226   Lys   226

32	Each codon is read as left nucleotide, top nucleotide, right nucleotide

33	Each entry is organized as follows:

34	   The number of occurrences of the codon in the sequence

35	   Preference of that codon in organism represented by the codon table

36	     (as a fraction of all codons coding for the same amino acid)

37	   Three-letter code for the amino acid coded for according to the codon table

38	   |A     C     G     T     |

39	-----------------------------

40	 A |3     7     3     13    |A

41	   |0.76  0.12  0.04  0.07  |

42	   |Lys   Thr   Arg   Ile   |

43	-----------------------------

44	 A |1     4     4     6     |C

45	   |0.61  0.43  0.27  0.46  |

46	   |Asn   Thr   Ser   Ile   |

47	-----------------------------

48	 A |8     1     6     7     |G

49	   |0.24  0.23  0.03  1     |

50	   |Lys   Thr   Arg   Met   |

51	-----------------------------

52	 A |4     3     1     3     |T

53	   |0.39  0.21  0.13  0.47  |

54	   |Asn   Thr   Ser   Ile   |

55	-----------------------------

56	 C |0     5     0     2     |A

57	   |0.31  0.2   0.05  0.03  |

58	   |Gln   Pro   Arg   Leu   |

59	-----------------------------

60	 C |1     2     0     14    |C

61	   |0.48  0.1   0.37  0.1   |

62	   |His   Pro   Arg   Leu   |

63	-----------------------------

64	 C |5     2     0     5     |G

65	   |0.69  0.55  0.08  0.55  |

66	   |Gln   Pro   Arg   Leu   |

67	-----------------------------

68	 C |0     2     0     5     |T

69	   |0.52  0.16  0.42  0.1   |

70	   |His   Pro   Arg   Leu   |

71	-----------------------------

72	 G |5     11    8     3     |A

73	   |0.7   0.22  0.09  0.17  |

74	   |Glu   Ala   Gly   Val   |

75	-----------------------------

76	 G |3     10    2     4     |C

77	   |0.41  0.25  0.4   0.2   |

78	   |Asp   Ala   Gly   Val   |

79	-----------------------------

80	 G |12    1     5     5     |G

81	   |0.3   0.34  0.13  0.34  |

82	   |Glu   Ala   Gly   Val   |

83	-----------------------------

84	 G |5     3     5     5     |T

85	   |0.59  0.19  0.38  0.29  |

86	   |Asp   Ala   Gly   Val   |

87	-----------------------------

88	 T |0     7     0     1     |A

89	   |0.62  0.12  0.3   0.11  |

90	   |End   Ser   End   Leu   |

91	-----------------------------

92	 T |4     2     0     2     |C

93	   |0.47  0.17  0.57  0.49  |

94	   |Tyr   Ser   Cys   Phe   |

95	-----------------------------

96	 T |0     2     1     1     |G

97	   |0.09  0.13  1     0.11  |

98	   |End   Ser   Trp   Leu   |

99	-----------------------------

100	 T |1     1     0     0     |T

101	   |0.53  0.19  0.43  0.51  |

102	   |Tyr   Ser   Cys   Phe   |

103	-----------------------------

0	The codon usage summary shows the number times that each codon appears in the sequence, as well as the frequency with which the organism (E. coli in this case) from which the codon table was compiled uses that codon for that amino acid.  This type of summary may come in handy, for example, when planning to express a protein recombinantly.

1	You may also want to run, for example, only the selected region of a sequence, and you may want to use single-letter amino acid codes:

>Direct Submission

0	1     agg gaa ccg tca cct cct gat tgc aga ggg tgt gag gct cct ccc   45

1

2	46    tga gag tta aag gtg agt cca tga agg atg aag ata ctg cca cca   90

3	                                           M   K   I   L   P   P    6

4	91    aca ctg agg gtc ccc agg agg tac ata gcc ttt gag gtg atc agt   135

5	7      T   L   R   V   P   R   R   Y   I   A   F   E   V   I   S    21

6	136   gag agg gag ctc tca agg gag gaa ctt gtc tcc ctc ata tgg gat   180

7	22     E   R   E   L   S   R   E   E   L   V   S   L   I   W   D    36

8	181   agc tgc ctc aag ctg cat ggg gag tgt gaa aca tca aat ttc cgt   225

9	37     S   C   L   K   L   H   G   E   C   E   T   S   N   F   R    51

10	226   tta tgg ctc atg aag ctc tgg agg ttc gat ttt cca gac gcc gtc   270

11	52     L   W   L   M   K   L   W   R   F   D   F   P   D   A   V    66

12	271   agg gtg agg ggc ata ctc cag tgc cag agg ggc tat gag agg agg   315

13	67     R   V   R   G   I   L   Q   C   Q   R   G   Y   E   R   R    81

14	316   gtc atg atg gcc ctc aca tgc gcc cac cac cac agc ggg gtg agg   360

15	82     V   M   M   A   L   T   C   A   H   H   H   S   G   V   R    96

16	361   gtc gcc atc cac atc ctc ggc ctt tca ggg acg ata cgc tcg gca   405

17	97     V   A   I   H   I   L   G   L   S   G   T   I   R   S   A    111

18	406   aca caa aag ttt att aaa cct tcc aag aaa gat aaa tac tga tta   450

19	112    T   Q   K   F   I   K   P   S   K   K   D   K   Y

20	451   aaa tct tca tca cat gac tca tga tta cat aaa tta tcc atc aat   495

21

496   aaa   498


Restriction Enzyme Browser

When running a restriction map on a nucleic acid sequence, it may be useful to show enzymes available from a particular company.  For example, many scientific departments have a contract deal with companies such as Promega or Boehringer-Mannheim with an on-site freezer from which enzymes and reagents may be obtained with no delay.

Restriction enzymes may be browsed by manufacturer by choosing a manufacturer and pressing the [image] button on the restriction map dialog.  You may also examine restriction enzymes at any time by choosing “View Restriction Enzymes by Manufacturer” from the “Options” menu.

The following dialog will appear:

In this example, all restriction enzymes available from Stratagene are listed on the left and KpnI is highlighted.  The recognition sequence for KpnI is shown on top, isoschizomers are shown below that, and other companies are shown which also carry KpnI.  The numbers in parentheses next to each company name specify the month and year in which the information for that company was last updated.  BioEdit uses the gcgenz table supplied by ReBase, the restriction enzyme database on the World Wide Web: http://www.neb.com/rebase/

This table may be updated by downloading the most recent version of the gcgenz.* table from rebase, naming it “enzyme.tab”, and replacing the old table file in the “tables” directory of the BioEdit installation folder.

0	Note:  The table must be in the gcgenz format.  You may open the “ enzyme.tab” file from the tables folder to see what the format looks like, or see Restriction Maps.  The restriction enzyme table file must be named “enzyme.tab” and must be located in the “tables” folder in order to be recognized by BioEdit.


line plot of matrix data rows and columns
 1-D Plots of Matrix Data Rows and Columns

When looking at data from a 2-D matrix, such as that generated from a mutual information analysis, it can be tedious or even overwhelming to look at tables of numbers to pick out high scores.  To help view this type of data, the matrix plotter was created.  The matrix plotter, however, plots data as a darkness intensity on a scale of 1 byte (0 to 255).  Subtle differences between different data points are sometimes difficult to see, such as the mutual information often seen between the two residues of a base-pair and a third residue of a nucleotide triplet.  For this reason, BioEdit offers the option to plot rows or columns of a matrix along a 1-dimensional line area graph.  Consider the following example:

A matrix plot of mutual information data from an alignment of bacterial RNaseP RNAs is shown below (E. coli serving as the mask)  In this plot, it would be extremely difficult to pick out a particular base triplet, namely a triplet between base pair 94-104 and nucleotide 316, although the base pair 94-104 is clearly visible.  The figure below is a partial view of a full Mxy table from a bacterial RNase P RNA alignment, plotted with a forced data point size of 3x3 pixels.  Position 94-104 is shown at the mouse arrow.  Position 94-316 is in the center of the small red box toward the right side.

That nucleotide 316 might interact with positions 94 and 104 is not obvious on this plot.  A 1-D area graph of rows of this matrix may be produced by choosing “Line Graph of Rows” from the “Plot” menu of an open plot.

Note:  This option is only available from within an open matrix plot.

When the graph comes up, it will show a contour plot of Row 1.  To examine the data in another row, the up and down arrow keys may be used to scroll through the rows, or the row to examine may be entered directly into the “Row” window at the top of the graph form.

A plot of row 316 is shown below.  Note the position of the blue cross.  The data at any position may be viewed by clicking the mouse on the graph for that value.  The lines of the blue cross will intersect at the peak of the data point, and x, y, and the data value will be shown in the upper left corner of the form.

This plot shows that there is a relatively high level of information between 316 and 104, and between 316 and 94.  In the above example, position 104 has been selected, and the upper left shows that the Mxy value for 104-316 is 0.306.  The data may also be vied by column by selecting “columns” for the X-axis (above).

The current version of BioEdit allows the use of a numbering mask which differs from the sequence mask when running comparative analyses.  This allows for easier navigation of data when, for example, only a part of a molecule is analyzed, and it is convenient to refer to the numbering scheme of a reference sequence or structure that represents the whole molecule.  Also, the numbering in the actual alignment may be used even when a sequence mask is used, to allow for reference to the alignment when analyzing positional data.  Because of this, the latest release (v5.0.0 or above) has updated the line plot to report the row or column number which actually appears in the data file, rather than the absolute row or column (for example, the first row in the matrix might be 234, rather than 1, and the second may be 300, rather than 2).

For information on this type of analysis, see mutual information and The basis of phylogenetic comparative analysis.


Plasmid drawing with BioEdit

BioEdit provides tools for simple plasmid drawing and annotation in a fairly quick and easy manner.  The following vector map for pBluescript SK+ (Stratagene) was drawn in a few minutes using BioEdit.  The features in this particular map were basically copied from the map provided by Stratagene.  Creating a new vector is just as simple, though.

With the BioEdit plasmid drawing utility, sequences may be automatically converted into circular plasmids with easy automated positional marking.  Features, polylinker and restriction sites may be easily added through the use of dialogs.   When a sequence is made into a plasmid map, a restriction map is silently run in the background, so restriction sites may be added by simply selecting from a dialog.  They are added to the correct position on the map automatically.  The plasmid utility also provides simple drawing and labeling tools.  These need to be improved and expanded, however.  Labels and drawn objects may be moved and scaled with the mouse.  To edit an object’s properties, double click on the object.  This release of BioEdit only supports circular maps.

To create a plasmid from a DNA sequence, choose "Create Plasmid from Sequence" either from the "Sequence" menu, or from the "Nucleic Acid" submenu of the "Sequence" menu.  When this option is chosen, a restriction map will be run using the common commercial enzymes and stored in memory.  When the plasmid first comes up it will simply be a circle with 10 positional markings and a title in the center.

Restriction sites:

To add restriction sites, choose "Restriction Sites" from the "Vector" menu.  The following dialog will appear:  (There will not initially be anything in the "Show" dialog)

To display restriction enzymes on the map, select any enzymes desired on the right side (the "Don't Show" box) and move them to the left using the [image] button.  When "Apply & Close" is pressed, these sites will be added to the map.  An enzyme is specified as being a single-cutter (unique) by a "U" after the cut site.  If there is no "U", then the first cut position is shown.  Only enzymes which cut 5 or fewer times are shown.  To remove enzyme positions from the map, highlight the enzyme(s) in the "Show" box and press the [image] button to move them to the other side.

Positional marks:

The following dialog can be brought up with the "Positional Marks" option under the "Vector" menu:

Positional markings may be added individually by moving them to the "Show" box, or a set number of divisional markings may be applied.  To have no marks at all, choose "none" at the top of the "Divide into:" drop-down list.

Features:

To add a feature such as an antibiotic resistance marker, choose "Add Feature" from the "Vector" menu.  the following dialog appears:

The choices of type are Normal Arrow, Wide Arrow, Normal Box and Wide Box.  All of the features in the above example are of the "normal" width.  If the feature is an arrow, the direction of the arrow will be determined by the start and end positions, and whether or not it crosses position 1 (the origin).

When features or enzymes are added, their respective labels are added on the outside, centered as well as possible over the site.  The labels may then be selected with the selector tool and moved, scaled or edited.

General Vector properties:

Properties of the vector may be modified by choosing "Properties" from the "Vector" menu:

A polylinker may be added to the bottom by specifying the beginning and end positions.  The polylinker is shown in "Courier New" font.

Features may be edited, added or deleted with this dialog.  To edit or delete an existing feature, choose the feature in the "Features" drop-down and press the appropriate button.  A new feature may be added by pressing the "Add New" button.

At this time only circular, single line plasmids are available.  This will be expanded later.

The "Font" buttons change the indicated default font.  The fonts of feature labels may be changed independent of each other, but positional markings are not created as individual selectable objects.

Drawing tools:

Very simple drawing tools are available which behave more or less like standard drawing tools in most programs.  The order of objects may be changed in the "Arrange" menu, and objects may be grouped and ungrouped from the "Arrange" menu.

Note:  Scaling grouped objects does not work well, as the objects are scaled independently of each other.

To edit an object's properties, double-click on the object, or select the object and choose "Object Properties" from the "Edit" menu.

Cut / Copy / Paste:

When an object(s) is copied in the plasmid utility, a structure is copied into memory for the use of BioEdit, and a bitmap of the object or objects is copied to the clipboard.  Objects may therefore be pasted into other applications as bitmap images.

Printing:

When printing, the map is drawn to the printer at the printer's resolution to avoid the pixellation that occurs with a screen-resolution bitmap.  The print interface is not very advanced, however.  A left margin and top margin may be specified in the "Print Setup" dialog (from the "File" menu)

At this time there is no support for scaling output to the printer to defined print dimensions.  The size of the printed figure is determined by the ratio of printer resolution to screen resolution.  The full width of a screen set at 800 x 600 resolution corresponds to roughly 8.3 inches, which is pretty close to the width of a normal paper page (8.5 inches).  The plasmid itself scales slightly small on the printer, and I’m currently trying to figure out why.  The size relative to an 800 x 600 resolution screen is fairly close, however.

Moving the vector:

The vector may be moved around the page by first selecting it with the mouse (a dotted box will be drawn around it to indicate it is selected), then dragging it with the mouse to its new location.  All of the labels and objects on the page will be moved accordingly.


Installing TreeView
Installing TreeView:

TreeView is a phylogenetic tree viewing program written by Roderic D.M. Page.  Previous versions of BioEdit included a distribution of the TreeView executable and supporting libraries in the apps folder.  At the request of the author full TreeView installation is now distributed with BioEdit.  This installation is contained within the file called TreeView.zip.

To install TreeView, unzip the file to a temporary directory, then run the program called "setup.exe" which will be created.  TreeView will install itself on your system.

To configure TreeView to run through the accessory apps menu of BioEdit, choose  Add/Remove/Modify an Accessory Application from the Accessory Application menu.  In the "Name of Accessory" box, type “TreeView”.  Press "Specify" next to the “Program” Box and browse to the new location for the TreeView.exe program.  Check the box called “Prompt for input file”.  In the “General Description” box, type “TreeView version 1.5.2.  Copyright Roderic D.M. Page, 1998. r.page@bio.gla.ac.uk.  http://www.taxonomy.zoology.gla.ac.uk/rod/rod.html” without any carriage returns.  Then press “Add / Modify” at the bottom of the dialog.  Upon closing the window, you will be prompted to have BioEdit close and restart.  For more information on installing accessory applications, see Configuring and Using External Applications.


Toggling between nucleotide and protein views

To control the way translation handles gaps , make sure the “Toggle Translation Control” option is checked from the “View” menu, and that the “Force contiguous codons” and “Ignore gaps that split codons” checkboxes are visible on the control bar of an alignment document.

When working with nucleotide sequences that code for proteins, BioEdit allows the toggling back and forth between nucleotide and protein sequences, with each view reflecting any gaps inserted or deleted in either view.  The nucleotide information is retained when toggling back from a protein view (it is not re-translated degenerately).

To switch back and forth between nucleotide and protein views of protein-encoding nucleic acids, first trim the 5’ end of the sequence(s) to the start codon and make sure the coding region is in frame 1.  Then either select the sequences to toggle and choose “Toggle Translation” from the Sequence” menu, or choose “Toggle Translation” from the “Alignment” menu (in which case all sequences will be automatically selected and toggled).  The sequences may be aligned in either view.  Additionally, if the protein view is Clustal-aligned, the underlying nucleotide sequences will be updated with the proper gaps.

Note 1:  When saving an alignment, if the sequences are toggled on the protein view, the nucleotide sequences, not the proteins, are saved.

Note 2:  This feature is only functional when the starting sequences are nucleic acid.  If the starting sequences are protein, then this feature does not do anything when chosen, because the coding region of a protein cannot be known by examining the amino acid sequence alone.  The feature can be used on degenerate reverse translations by first reverse-translating the sequences, then choosing this menu option.

Note 3:  There are three available modes for handling gaps placed in nucleotide sequences which either split codons internally or occur as singles or pairs.  A gap in a protein sequence will correspond to three gaps in the encoding nucleotide sequence.  However, if a one or two gaps are placed in a nucleotide sequence, or gaps are placed directly within a codon (in frame 1), there is a problem.  BioEdit handles this in one of three ways, depending upon the options chosen:

To alter the options for translation toggling, the “Translation Toggle Control” option under the “View” menu must be checked.  When this menu item is checked, there will be two checkboxes on the right side of the top panel of the alignment  window.  The available options are:

1.  Force all gaps to occur in groups of three and to only occur between codon (not within codons).  In this mode, if a gap is introduced inside a codon, the nucleotides downstream are shifted left until a full codon is produced.  If this results in a single or double gap (or if one is manually put between two codons), the gap is extended to three places to make a single amino acid size gap.  This will cause gap positions to automatically change if they are not introduced as triplets between codons.  It is easiest to simply align the sequences by their protein translations.

** This mode is active when the “Force contiguous codons” checkbox is checked.

2.  Ignore gaps that split codons.  In this mode, rather than trying to “fix” the sequences, any gaps that occur within codons or occur don’t make a whole amino acid gap are simply ignored in the protein translation.  They are still retained in the nucleotide sequence, however, and will still be there when the proteins are toggled back to the nucleotides.

** This mode is active when the “Ignore gaps that split codons” checkbox is checked

Mode 1 and 2 cannot be active at the same time.

3.  Neither mode.  This is active when neither checkbox is checked.  In this mode, no attempt to fix sequence edits is made, but gaps are not ignored in translating.  Any gap that is not a multiple of three will cause a frameshift.  A gap that occurs within a codon (in frame 1) will cause the translation to see an “X” rather than a valid amino acid.

** This mode is active when neither of the above checkboxes is checked.


Preferences for translation output and ORF searching

To set parameters for ORF searching or the format of translations of nucleic acid sequences via the Sequence->Nucleic Acid->Translate-> ... menu options, choose Options->Preferences->ORFs:

ORF searching:  The start codon used for ORF searching will generally be ATG, however, you may wish to search allowing for alternative start codons.  To allow more than one start codon at a time, type in the codons separated by a “;”.  For example, to allow ATG and TTG, type “ATG;TTG” in the start codon box.  The same syntax is used for stop codons.  If you would like to allow read-through of a codon (for example, UGA), remove It from the list.  The preferences will be saved for all subsequent searches.

When searching for ORFs, only sequences with selected titles are searched, and the search begins after the last selected nucleotide.  To search, choose Edit->Find Next ORF, or Sequence->Nucleic Acid->Find Next ORF.

Formatted nucleic acid translations are performed by choosing Sequence->Nucleic Acid->Translate, then either Frame 1, Frame 2, Frame 3, or Selected.  If the “Show codon usage” box is checked, a summary table is reported as described in Nucleic acid translation with codon usage


Customizing menu shortcuts

Preferred menu shortcuts may be created for any menu item or sub-menu item (but not to a third level).  Shortcuts may only be customized for alignment document windows, however.  For example, if Ctrl+Y was set to be a shortcut for “copy”, when working in the text editor, Ctrl+C would still be the copy shortcut

To set shortcuts, choose View->Customize Menu Shortcuts.  To set a shortcut, simply scroll to the menu item of interest, select it with the mouse, then press the particular key combination you would like to use to activate it.  To completely remove a shortcut, highlight an item and press “Clear Entry”


Splitting the window view

It may be convenient to edit two different parts of an alignment at one time.  To allow for this, BioEdit offers two ways of splitting the document into two synchronized windows, one that splits the window vertically and the other which splits it horizontally.

To split the window vertically, choose View->Split Window Vertically.  Shown below is a split view of part of the prokaryotic 16S rRNA alignment.  The two sides share a vertical scroll bar, but scroll independently of each other in the horizontal direction.  The window spit may be resized with the mouse.

To split the window horizontally, choose View->Split Window Horizontally.  Shown below is another split view of part of the prokaryotic 16S rRNA alignment.  The two windows remain attached, but have independent vertical and horizontal scrolling


Search for conserved regions in an alignment

Sometimes it might be useful to locate regions of several sequences which are well conserved, even though there is a high degree of variation in most of the sequences.  For example, one might want to create universal PCR primers that would likely work to amplify a sequence from an organism based upon a series of homologous sequences.  BioEdit looks for stretches of low average “entropy” (defined as Hx = Σ(fbx*log(f(bx))), where fbx is the frequency of residue b at position x and the sum is taken over all possible residue types).

To search for conserved regions within an alignment (for example, to find possible targets for PCR primers), select the sequences you want included in the analysis, and choose Alignment->Find Conserved Regions.

The following dialog appears:

Don’t allow gaps: No gaps in any sequence will be allowed for a reported region

Limit gaps in any segment to x:   For a region to be reported as conserved, no sequence may have more than x gaps in that region.

Limit max contiguous gaps to x:  For a region to be reported as conserved, no sequence may have more than x gaps in a row, regardless of how many total gaps are allowed.

Minimum length:  This is the actual number of residues that must be present within the region in every sequence (not including gaps), regardless of the number of gaps allowed.

Max average entropy:  The maximum average entropy (Hx/n, where n is the length of the segment) allowed.

Max entropy per position:  A maximum entropy may be specified for every position which is greater or less than the maximum average entropy.

Allow x exceptions:  If this is chosen, x exceptions to the per-position max entropy will be allowed in each reported segment.

Reports:

A text report or a series of alignments (Fasta report) may be chosen (or both).  If a series of alignments is chosen, it is a good idea to first run the search with only a text report to make sure to choose parameters which only result in very few regions being detected, since BioEdit only allows 20 open alignment documents at a time.

Sample output for a text report:  The following search was done on 75 16S ribosomal sequences from methanogenic Archaea.  Compare the output for the first region to the example for information-based shading in the alignment window.

BioEdit version 4.7.1

0	Conserved region search

1	Alignment file: Q:\Ribosomal_RNA\some_methanos.bio

2	5/10/99 8:57:33 PM

3	Minimum segment length (actual for each sequence): 15

4	Maximum average entropy: 0.2

5	Maximum entropy per position: 0.2

6	Gaps limited to 2 per segment

7	Contiguous gaps limited to 1 in any segment

8	2 conserved regions found

9	Region 1: Position 755 to 774

10	Consensus:

11	755 AUUAGAUACCCGGGUAGUCC 774

12	Segment Length: 20

13	Average entropy (Hx): 0.0155

14	Position 755     : 0.0000

15	Position 756     : 0.0000

16	Position 757     : 0.0000

17	Position 758     : 0.0708

18	Position 759     : 0.0000

19	Position 760     : 0.0000

20	Position 761     : 0.0000

21	Position 762     : 0.0000

22	Position 763     : 0.0000

23	Position 764     : 0.0708

24	Position 765     : 0.0000

25	Position 766     : 0.1679

26	Position 767     : 0.0000

27	Position 768     : 0.0000

28	Position 769     : 0.0000

29	Position 770     : 0.0000

30	Position 771     : 0.0000

31	Position 772     : 0.0000

32	Position 773     : 0.0000

33	Position 774     : 0.0000

34	Region 2: Position 1206 to 1222

35	Consensus:

36	1206 ACACGCGGGCUACAAUG 1222

37	Segment Length: 17

38	Average entropy (Hx): 0.0182

39	Position 1206    : 0.0000

40	Position 1207    : 0.0000

41	Position 1208    : 0.0000

42	Position 1209    : 0.0000

43	Position 1210    : 0.0708

44	Position 1211    : 0.0708

45	Position 1212    : 0.0000

46	Position 1213    : 0.1679

47	Position 1214    : 0.0000

48	Position 1215    : 0.0000

49	Position 1216    : 0.0000

50	Position 1217    : 0.0000

51	Position 1218    : 0.0000

52	Position 1219    : 0.0000

53	Position 1220    : 0.0000

54	Position 1221    : 0.0000

55	Position 1222    : 0.0000

0	A less stringent search might find many regions, for example, for the same alignment:

BioEdit version 4.7.1

0	Conserved region search

1	Alignment file: Q:\Ribosomal_RNA\some_methanos.bio

2	5/10/99 9:34:06 PM

3	Minimum segment length (actual for each sequence): 10

4	Maximum average entropy: 0.4

5	Maximum entropy per position: 0.4 with 2 exceptions allowed

6	Gaps limited to 2 per segment

7	Contiguous gaps limited to 1 in any segment

8	36 conserved regions found

9	Region 1: Position 109 to 119

10	Consensus:

11	109 GUGGAUAACCU 119

12	Segment Length: 11

13	Average entropy (Hx): 0.2456

14	Position 109     : 0.3927

15	Position 110     : 0.0000

16	Position 111     : 0.0000

17	Position 112     : 0.0000

18	Position 113     : 0.8192

19	Position 114     : 0.3927

20	Position 115     : 0.1230

21	Position 116     : 0.0000

22	Position 117     : 0.3927

23	Position 118     : 0.5817

24	Position 119     : 0.0000

25	Region 2: Position 143 to 153

26	Consensus:

27	143 GGGAAACUGGG 153

28	Segment Length: 11

29	Average entropy (Hx): 0.1266

30	Position 143     : 0.0000

31	Position 144     : 0.0000

32	Position 145     : 0.2082

33	Position 146     : 0.0708

34	Position 147     : 0.0000

35	Position 148     : 0.0000

36	Position 149     : 0.0000

37	Position 150     : 0.0000

38	Position 151     : 0.0708

39	Position 152     : 0.5930

40	Position 153     : 0.4494

41	Region 3: Position 248 to 258

42	Consensus:

43	248 AUUAG-GUAGU 258

44	Segment Length: 11

45	Average entropy (Hx): 0.1347

46	Position 248     : 0.0000

47	Position 249     : 0.0000

48	Position 250     : 0.6164

49	Position 251     : 0.0000

50	Position 252     : 0.0000

51	Position 253     : 0.0708

52	Position 254     : 0.0000

53	Position 255     : 0.0000

54	Position 256     : 0.7948

55	Position 257     : 0.0000

56	Position 258     : 0.0000

57	Region 4: Position 311 to 326

58	Consensus:

59	311 GAGCCCGGAGAUGGAU 326

60	Segment Length: 16

61	Average entropy (Hx): 0.1886

62	Position 311     : 0.2783

63	Position 312     : 0.0708

64	Position 313     : 0.1230

65	Position 314     : 0.0000

66	Position 315     : 0.0000

67	Position 316     : 0.1679

68	Position 317     : 0.1230

69	Position 318     : 0.0708

70	Position 319     : 0.0000

71	Position 320     : 0.0000

72	Position 321     : 0.2082

73	Position 322     : 0.1230

74	Position 323     : 0.1230

75	Position 324     : 0.0000

76	Position 325     : 0.5352

77	Position 326     : 1.1950

78	Region 5: Position 328 to 338

79	Consensus:

80	328 CUGAGACACGG 338

81	Segment Length: 11

82	Average entropy (Hx): 0.1799

83	Position 328     : 0.0000

84	Position 329     : 0.0000

85	Position 330     : 0.0000

86	Position 331     : 0.0000

87	Position 332     : 0.0000

88	Position 333     : 0.0000

89	Position 334     : 0.0000

90	Position 335     : 0.0000

91	Position 336     : 1.0841

92	Position 337     : 0.1414

93	Position 338     : 0.7533

94	Region 6: Position 341 to 354

95	Consensus:

96	341 CCAGGCCCUACGGG 354

97	Segment Length: 14

98	Average entropy (Hx): 0.1020

99	Position 341     : 0.0000

100	Position 342     : 0.5859

101	Position 343     : 0.4360

102	Position 344     : 0.0708

103	Position 345     : 0.0708

104	Position 346     : 0.0708

105	Position 347     : 0.0000

106	Position 348     : 0.0708

107	Position 349     : 0.0000

108	Position 350     : 0.0000

109	Position 351     : 0.0000

110	Position 352     : 0.0000

111	Position 353     : 0.0000

112	Position 354     : 0.1230

113	Region 7: Position 357 to 375

114	Consensus:

115	357 GCAGCAGGCGCGAAACCUC 375

116	Segment Length: 19

117	Average entropy (Hx): 0.1049

118	Position 357     : 0.2082

119	Position 358     : 0.0000

120	Position 359     : 0.0000

121	Position 360     : 0.0000

122	Position 361     : 0.0000

123	Position 362     : 0.0000

124	Position 363     : 0.0000

125	Position 364     : 0.0000

126	Position 365     : 0.0000

127	Position 366     : 0.0000

128	Position 367     : 0.0000

129	Position 368     : 0.0000

130	Position 369     : 0.2452

131	Position 370     : 0.0000

132	Position 371     : 0.0000

133	Position 372     : 0.8495

134	Position 373     : 0.0000

135	Position 374     : 0.0000

136	Position 375     : 0.6909

137	Region 8: Position 463 to 477

138	Consensus:

139	463 AAGGGCUGGGCAAGA 477

140	Segment Length: 15

141	Average entropy (Hx): 0.1497

142	Position 463     : 0.0708

143	Position 464     : 0.0708

144	Position 465     : 0.0000

145	Position 466     : 0.2449

146	Position 467     : 0.0708

147	Position 468     : 0.1230

148	Position 469     : 0.8529

149	Position 470     : 0.0000

150	Position 471     : 0.0000

151	Position 472     : 0.0000

152	Position 473     : 0.0000

153	Position 474     : 0.1230

154	Position 475     : 0.0000

155	Position 476     : 0.0708

156	Position 477     : 0.6182

157	Region 9: Position 492 to 506

158	Consensus:

159	492 CGCGGUAACACCGGC 506

160	Segment Length: 15

161	Average entropy (Hx): 0.1003

162	Position 492     : 0.1414

163	Position 493     : 0.0708

164	Position 494     : 0.0000

165	Position 495     : 0.0000

166	Position 496     : 0.0000

167	Position 497     : 0.0000

168	Position 498     : 0.0000

169	Position 499     : 0.0000

170	Position 500     : 0.5352

171	Position 501     : 0.0000

172	Position 502     : 0.0000

173	Position 503     : 0.0000

174	Position 504     : 0.0000

175	Position 505     : 0.4169

176	Position 506     : 0.3395

177	Region 10: Position 527 to 541

178	Consensus:

179	527 UUAUUGGGCCUAAAG 541

180	Segment Length: 15

181	Average entropy (Hx): 0.0872

182	Position 527     : 0.0000

183	Position 528     : 0.0000

184	Position 529     : 0.0000

185	Position 530     : 0.2082

186	Position 531     : 0.0000

187	Position 532     : 0.0000

188	Position 533     : 0.0000

189	Position 534     : 0.0000

190	Position 535     : 0.6607

191	Position 536     : 0.4397

192	Position 537     : 0.0000

193	Position 538     : 0.0000

194	Position 539     : 0.0000

195	Position 540     : 0.0000

196	Position 541     : 0.0000

197	Region 11: Position 627 to 637

198	Consensus:

199	627 CGGGAGAGGUA 637

200	Segment Length: 11

201	Average entropy (Hx): 0.2644

202	Position 627     : 0.1934

203	Position 628     : 0.0708

204	Position 629     : 0.0000

205	Position 630     : 0.0708

206	Position 631     : 0.0708

207	Position 632     : 0.0000

208	Position 633     : 0.0000

209	Position 634     : 0.0000

210	Position 635     : 0.0000

211	Position 636     : 1.0881

212	Position 637     : 1.4149

213	Region 12: Position 651 to 665

214	Consensus:

215	651 GGGUAGGGGUGAAAU 665

216	Segment Length: 15

217	Average entropy (Hx): 0.1185

218	Position 651     : 0.0000

219	Position 652     : 0.1230

220	Position 653     : 0.0000

221	Position 654     : 0.0000

222	Position 655     : 0.0000

223	Position 656     : 0.0000

224	Position 657     : 0.6666

225	Position 658     : 0.6780

226	Position 659     : 0.0708

227	Position 660     : 0.0000

228	Position 661     : 0.0708

229	Position 662     : 0.1679

230	Position 663     : 0.0000

231	Position 664     : 0.0000

232	Position 665     : 0.0000

233	Region 13: Position 681 to 691

234	Consensus:

235	681 GGACCACCUGU 691

236	Segment Length: 11

237	Average entropy (Hx): 0.1673

238	Position 681     : 0.1414

239	Position 682     : 0.0000

240	Position 683     : 0.0000

241	Position 684     : 0.0000

242	Position 685     : 0.2452

243	Position 686     : 0.2082

244	Position 687     : 0.0000

245	Position 688     : 0.0000

246	Position 689     : 0.6408

247	Position 690     : 0.6051

248	Position 691     : 0.0000

249	Region 14: Position 693 to 702

250	Consensus:

251	693 GCGAAGGCGU 702

252	Segment Length: 10

253	Average entropy (Hx): 0.1802

254	Position 693     : 0.0000

255	Position 694     : 0.0000

256	Position 695     : 0.0000

257	Position 696     : 0.0000

258	Position 697     : 0.0000

259	Position 698     : 0.3927

260	Position 699     : 0.0000

261	Position 700     : 0.0000

262	Position 701     : 0.6051

263	Position 702     : 0.8044

264	Region 15: Position 720 to 733

265	Consensus:

266	720 GACGGUGAGGGACG 733

267	Segment Length: 14

268	Average entropy (Hx): 0.1698

269	Position 720     : 0.0000

270	Position 721     : 0.0000

271	Position 722     : 0.0000

272	Position 723     : 0.7594

273	Position 724     : 0.0000

274	Position 725     : 0.2082

275	Position 726     : 0.2082

276	Position 727     : 0.0000

277	Position 728     : 0.0000

278	Position 729     : 0.2382

279	Position 730     : 0.2449

280	Position 731     : 0.0000

281	Position 732     : 0.0000

282	Position 733     : 0.7182

283	Region 16: Position 735 to 744

284	Consensus:

285	735 AAGCUAGGGG 744

286	Segment Length: 10

287	Average entropy (Hx): 0.1614

288	Position 735     : 0.0000

289	Position 736     : 0.1679

290	Position 737     : 0.0000

291	Position 738     : 0.0000

292	Position 739     : 0.6931

293	Position 740     : 0.6824

294	Position 741     : 0.0000

295	Position 742     : 0.0000

296	Position 743     : 0.0000

297	Position 744     : 0.0708

298	Region 17: Position 747 to 775

299	Consensus:

300	747 CGAACCGGAUUAGAUACCCGGGUAGUCCU 775

301	Segment Length: 29

302	Average entropy (Hx): 0.0636

303	Position 747     : 0.0000

304	Position 748     : 0.4169

305	Position 749     : 0.0000

306	Position 750     : 0.0000

307	Position 751     : 0.0000

308	Position 752     : 0.1679

309	Position 753     : 0.0000

310	Position 754     : 0.2082

311	Position 755     : 0.0000

312	Position 756     : 0.0000

313	Position 757     : 0.0000

314	Position 758     : 0.0708

315	Position 759     : 0.0000

316	Position 760     : 0.0000

317	Position 761     : 0.0000

318	Position 762     : 0.0000

319	Position 763     : 0.0000

320	Position 764     : 0.0708

321	Position 765     : 0.0000

322	Position 766     : 0.1679

323	Position 767     : 0.0000

324	Position 768     : 0.0000

325	Position 769     : 0.0000

326	Position 770     : 0.0000

327	Position 771     : 0.0000

328	Position 772     : 0.0000

329	Position 773     : 0.0000

330	Position 774     : 0.0000

331	Position 775     : 0.7417

332	Region 18: Position 777 to 789

333	Consensus:

334	777 GCCGUAAACGAUG 789

335	Segment Length: 13

336	Average entropy (Hx): 0.1478

337	Position 777     : 0.0000

338	Position 778     : 0.0000

339	Position 779     : 0.2783

340	Position 780     : 0.0000

341	Position 781     : 0.0000

342	Position 782     : 0.0000

343	Position 783     : 0.0000

344	Position 784     : 0.0000

345	Position 785     : 0.0000

346	Position 786     : 0.7187

347	Position 787     : 0.7160

348	Position 788     : 0.0000

349	Position 789     : 0.2082

350	Region 19: Position 826 to 840

351	Consensus:

352	826 GUGCCGAAGGGAAGC 840

353	Segment Length: 15

354	Average entropy (Hx): 0.1384

355	Position 826     : 0.2788

356	Position 827     : 0.1230

357	Position 828     : 0.0000

358	Position 829     : 0.0000

359	Position 830     : 0.0000

360	Position 831     : 0.0708

361	Position 832     : 0.7770

362	Position 833     : 0.0000

363	Position 834     : 0.0000

364	Position 835     : 0.1934

365	Position 836     : 0.0000

366	Position 837     : 0.0000

367	Position 838     : 0.0000

368	Position 839     : 0.4397

369	Position 840     : 0.1934

370	Region 20: Position 852 to 868

371	Consensus:

372	852 CCGCCUGGGAAGUACGG 868

373	Segment Length: 17

374	Average entropy (Hx): 0.1135

375	Position 852     : 0.1414

376	Position 853     : 0.1679

377	Position 854     : 0.6607

378	Position 855     : 0.0000

379	Position 856     : 0.0000

380	Position 857     : 0.0708

381	Position 858     : 0.0000

382	Position 859     : 0.0000

383	Position 860     : 0.0708

384	Position 861     : 0.7474

385	Position 862     : 0.0000

386	Position 863     : 0.0000

387	Position 864     : 0.0708

388	Position 865     : 0.0000

389	Position 866     : 0.0000

390	Position 867     : 0.0000

391	Position 868     : 0.0000

392	Region 21: Position 942 to 952

393	Consensus:

394	942 AACGCCGGACA 952

395	Segment Length: 11

396	Average entropy (Hx): 0.1619

397	Position 942     : 0.0000

398	Position 943     : 0.0000

399	Position 944     : 0.0000

400	Position 945     : 0.0000

401	Position 946     : 0.0000

402	Position 947     : 0.0708

403	Position 948     : 0.0000

404	Position 949     : 0.0000

405	Position 950     : 0.7942

406	Position 951     : 0.9163

407	Position 952     : 0.0000

408	Region 22: Position 983 to 994

409	Consensus:

410	983 CAGGCUGAAGAC 994

411	Segment Length: 12

412	Average entropy (Hx): 0.3368

413	Position 983     : 0.1230

414	Position 984     : 0.3669

415	Position 985     : 0.3927

416	Position 986     : 0.1230

417	Position 987     : 0.9765

418	Position 988     : 0.0708

419	Position 989     : 0.2788

420	Position 990     : 0.0000

421	Position 991     : 1.0599

422	Position 992     : 0.0000

423	Position 993     : 0.3395

424	Position 994     : 0.3102

425	Region 23: Position 1007 to 1027

426	Consensus:

427	1007 GCUGAGAGGAGGUGCAUGGCC 1027

428	Segment Length: 21

429	Average entropy (Hx): 0.0765

430	Position 1007    : 0.0708

431	Position 1008    : 0.0000

432	Position 1009    : 0.3485

433	Position 1010    : 0.0000

434	Position 1011    : 0.0000

435	Position 1012    : 0.0000

436	Position 1013    : 0.0000

437	Position 1014    : 0.0000

438	Position 1015    : 0.0000

439	Position 1016    : 0.6051

440	Position 1017    : 0.0708

441	Position 1018    : 0.0000

442	Position 1019    : 0.4397

443	Position 1020    : 0.0000

444	Position 1021    : 0.0000

445	Position 1022    : 0.0000

446	Position 1023    : 0.0000

447	Position 1024    : 0.0000

448	Position 1025    : 0.0000

449	Position 1026    : 0.0000

450	Position 1027    : 0.0708

451	Region 24: Position 1030 to 1044

452	Consensus:

453	1030 CGUCAGCUCGUACCG 1044

454	Segment Length: 15

455	Average entropy (Hx): 0.1305

456	Position 1030    : 0.0000

457	Position 1031    : 0.0000

458	Position 1032    : 0.3669

459	Position 1033    : 0.0000

460	Position 1034    : 0.2082

461	Position 1035    : 0.0000

462	Position 1036    : 0.6909

463	Position 1037    : 0.0000

464	Position 1038    : 0.0000

465	Position 1039    : 0.0000

466	Position 1040    : 0.0000

467	Position 1041    : 0.0000

468	Position 1042    : 0.0000

469	Position 1043    : 0.6909

470	Position 1044    : 0.0000

471	Region 25: Position 1046 to 1066

472	Consensus:

473	1046 GAGGCGUCCUGUUAAGUCAGG 1066

474	Segment Length: 21

475	Average entropy (Hx): 0.0825

476	Position 1046    : 0.0000

477	Position 1047    : 0.0000

478	Position 1048    : 0.6923

479	Position 1049    : 0.0000

480	Position 1050    : 0.0000

481	Position 1051    : 0.6909

482	Position 1052    : 0.0000

483	Position 1053    : 0.0000

484	Position 1054    : 0.0000

485	Position 1055    : 0.0000

486	Position 1056    : 0.0000

487	Position 1057    : 0.0000

488	Position 1058    : 0.0000

489	Position 1059    : 0.2788

490	Position 1060    : 0.0000

491	Position 1061    : 0.0000

492	Position 1062    : 0.0000

493	Position 1063    : 0.0000

494	Position 1064    : 0.0000

495	Position 1065    : 0.0000

496	Position 1066    : 0.0708

497	Region 26: Position 1068 to 1086

498	Consensus:

499	1068 AACGAGCGAGACCCGCGCC 1086

500	Segment Length: 19

501	Average entropy (Hx): 0.0900

502	Position 1068    : 0.0000

503	Position 1069    : 0.0000

504	Position 1070    : 0.0000

505	Position 1071    : 0.0000

506	Position 1072    : 0.0000

507	Position 1073    : 0.0000

508	Position 1074    : 0.0000

509	Position 1075    : 0.1230

510	Position 1076    : 0.0000

511	Position 1077    : 0.0000

512	Position 1078    : 0.0000

513	Position 1079    : 0.0000

514	Position 1080    : 0.0000

515	Position 1081    : 0.0000

516	Position 1082    : 0.6923

517	Position 1083    : 0.7533

518	Position 1084    : 0.0000

519	Position 1085    : 0.0000

520	Position 1086    : 0.1414

521	Region 27: Position 1156 to 1165

522	Consensus:

523	1156 GAGGAAGGAG 1165

524	Segment Length: 10

525	Average entropy (Hx): 0.1407

526	Position 1156    : 0.0000

527	Position 1157    : 0.0000

528	Position 1158    : 0.0000

529	Position 1159    : 0.0000

530	Position 1160    : 0.0708

531	Position 1161    : 0.1230

532	Position 1162    : 0.0000

533	Position 1163    : 0.0000

534	Position 1164    : 0.6269

535	Position 1165    : 0.5859

536	Region 28: Position 1172 to 1183

537	Consensus:

538	1172 ACGGUAGGUCAG 1183

539	Segment Length: 12

540	Average entropy (Hx): 0.1554

541	Position 1172    : 0.0708

542	Position 1173    : 0.0000

543	Position 1174    : 0.0000

544	Position 1175    : 0.5511

545	Position 1176    : 0.2783

546	Position 1177    : 0.0000

547	Position 1178    : 0.0000

548	Position 1179    : 0.0000

549	Position 1180    : 0.0708

550	Position 1181    : 0.0000

551	Position 1182    : 0.8935

552	Position 1183    : 0.0000

553	Region 29: Position 1185 to 1197

554	Consensus:

555	1185 AUGCCCCGAAUCU 1197

556	Segment Length: 13

557	Average entropy (Hx): 0.1779

558	Position 1185    : 0.0000

559	Position 1186    : 0.0000

560	Position 1187    : 0.0000

561	Position 1188    : 0.0000

562	Position 1189    : 0.0000

563	Position 1190    : 0.0000

564	Position 1191    : 0.2449

565	Position 1192    : 0.0708

566	Position 1193    : 0.0000

567	Position 1194    : 0.1679

568	Position 1195    : 0.1230

569	Position 1196    : 0.6926

570	Position 1197    : 1.0133

571	Region 30: Position 1201 to 1224

572	Consensus:

573	1201 GGGCUACACGCGGGCUACAAUGGC 1224

574	Segment Length: 24

575	Average entropy (Hx): 0.1006

576	Position 1201    : 0.0000

577	Position 1202    : 0.0000

578	Position 1203    : 0.0708

579	Position 1204    : 0.0000

580	Position 1205    : 0.6026

581	Position 1206    : 0.0000

582	Position 1207    : 0.0000

583	Position 1208    : 0.0000

584	Position 1209    : 0.0000

585	Position 1210    : 0.0708

586	Position 1211    : 0.0708

587	Position 1212    : 0.0000

588	Position 1213    : 0.1679

589	Position 1214    : 0.0000

590	Position 1215    : 0.0000

591	Position 1216    : 0.0000

592	Position 1217    : 0.0000

593	Position 1218    : 0.0000

594	Position 1219    : 0.0000

595	Position 1220    : 0.0000

596	Position 1221    : 0.0000

597	Position 1222    : 0.0000

598	Position 1223    : 0.2449

599	Position 1224    : 1.1859

600	Region 31: Position 1227 to 1238

601	Consensus:

602	1227 GGACAAUGGGUU 1238

603	Segment Length: 12

604	Average entropy (Hx): 0.2099

605	Position 1227    : 0.1934

606	Position 1228    : 0.2382

607	Position 1229    : 0.0708

608	Position 1230    : 0.0000

609	Position 1231    : 0.0000

610	Position 1232    : 0.0000

611	Position 1233    : 0.0000

612	Position 1234    : 0.0000

613	Position 1235    : 0.0000

614	Position 1236    : 0.0000

615	Position 1237    : 0.8815

616	Position 1238    : 1.1352

617	Region 32: Position 1279 to 1297

618	Consensus:

619	1279 UAGUUCGGAUCGAGGGCUG 1297

620	Segment Length: 19

621	Average entropy (Hx): 0.1401

622	Position 1279    : 0.2449

623	Position 1280    : 0.0000

624	Position 1281    : 0.0000

625	Position 1282    : 0.0000

626	Position 1283    : 0.1679

627	Position 1284    : 0.1230

628	Position 1285    : 0.0000

629	Position 1286    : 0.3395

630	Position 1287    : 0.0000

631	Position 1288    : 0.0000

632	Position 1289    : 0.6454

633	Position 1290    : 0.0000

634	Position 1291    : 0.8044

635	Position 1292    : 0.0000

636	Position 1293    : 0.0000

637	Position 1294    : 0.1679

638	Position 1295    : 0.1679

639	Position 1296    : 0.0000

640	Position 1297    : 0.0000

641	Region 33: Position 1299 to 1309

642	Consensus:

643	1299 AACUCGCCCUC 1309

644	Segment Length: 11

645	Average entropy (Hx): 0.1650

646	Position 1299    : 0.0000

647	Position 1300    : 0.0000

648	Position 1301    : 0.0000

649	Position 1302    : 0.4611

650	Position 1303    : 0.0000

651	Position 1304    : 0.1679

652	Position 1305    : 0.1679

653	Position 1306    : 0.0000

654	Position 1307    : 0.0000

655	Position 1308    : 1.0183

656	Position 1309    : 0.0000

657	Region 34: Position 1311 to 1336

658	Consensus:

659	1311 UGAAGCUGGAAUCCGUAGUAAUCGCG 1336

660	Segment Length: 26

661	Average entropy (Hx): 0.0672

662	Position 1311    : 0.0000

663	Position 1312    : 0.0000

664	Position 1313    : 0.0000

665	Position 1314    : 0.0000

666	Position 1315    : 0.1230

667	Position 1316    : 0.0000

668	Position 1317    : 0.1679

669	Position 1318    : 0.0000

670	Position 1319    : 0.0000

671	Position 1320    : 0.0000

672	Position 1321    : 0.0000

673	Position 1322    : 0.0000

674	Position 1323    : 0.6051

675	Position 1324    : 0.2788

676	Position 1325    : 0.0000

677	Position 1326    : 0.0000

678	Position 1327    : 0.0000

679	Position 1328    : 0.0000

680	Position 1329    : 0.0000

681	Position 1330    : 0.0000

682	Position 1331    : 0.0000

683	Position 1332    : 0.0000

684	Position 1333    : 0.0000

685	Position 1334    : 0.0000

686	Position 1335    : 0.0708

687	Position 1336    : 0.5004

688	Region 35: Position 1349 to 1384

689	Consensus:

690	1349 GCGGUGAAUACGUCCCUGCUCCUUGCACACACCGCC 1384

691	Segment Length: 36

692	Average entropy (Hx): 0.0819

693	Position 1349    : 0.0000

694	Position 1350    : 0.0000

695	Position 1351    : 0.0000

696	Position 1352    : 0.0000

697	Position 1353    : 0.0000

698	Position 1354    : 0.0000

699	Position 1355    : 0.0000

700	Position 1356    : 0.0000

701	Position 1357    : 0.0000

702	Position 1358    : 0.8610

703	Position 1359    : 0.6593

704	Position 1360    : 0.0000

705	Position 1361    : 0.0000

706	Position 1362    : 0.0000

707	Position 1363    : 0.0000

708	Position 1364    : 0.0000

709	Position 1365    : 0.0000

710	Position 1366    : 0.3102

711	Position 1367    : 0.0000

712	Position 1368    : 0.0000

713	Position 1369    : 0.1679

714	Position 1370    : 0.2788

715	Position 1371    : 0.3102

716	Position 1372    : 0.0000

717	Position 1373    : 0.0000

718	Position 1374    : 0.0000

719	Position 1375    : 0.0000

720	Position 1376    : 0.0000

721	Position 1377    : 0.0000

722	Position 1378    : 0.0000

723	Position 1379    : 0.0000

724	Position 1380    : 0.0000

725	Position 1381    : 0.1230

726	Position 1382    : 0.0000

727	Position 1383    : 0.1679

728	Position 1384    : 0.0708

729	Region 36: Position 1388 to 1397

730	Consensus:

731	1388 CACACCACCC 1397

732	Segment Length: 10

733	Average entropy (Hx): 0.1936

734	Position 1388    : 0.1679

735	Position 1389    : 0.0000

736	Position 1390    : 0.6909

737	Position 1391    : 0.6269

738	Position 1392    : 0.0000

739	Position 1393    : 0.0000

740	Position 1394    : 0.0000

741	Position 1395    : 0.3797

742	Position 1396    : 0.0000

743	Position 1397    : 0.0708


Information-based shading

The following view shows an information-based shaded view of an alignment of 75 16S rRNA sequences from methanogenic Archaea.  The region shown was picked by an entropy/information-based search for conserved regions.

Compare this view to the split-window view below it showing the same alignment with this region compared to a less well-conserved region


Positional Nucleotide Numerical Summary

This small routine simply lists the number of occurrences of each nucleotide at each position of a nucleic acid alignment.  This was simply added because I needed it for something immediately and didn’t see a reason to remove it (which is also why it’s only for nucleotides right now -- maybe I’ll expand it later, but it’s not a priority right now).  If a mask is used, only the mask positions are summarized, and if a numbering mask is used, each position is numbered according to the corresponding position of the numbering mask.  Example output:

Summary of numbers of nucleotides at each position

0	Alignment: I:\BioEdit\Bac_Prot_genesclust.gb

1	Mask Sequence: Escherichi

2	Positions reflect sequence: Escherichi

3	Position	A	G	C	U	GAP

4	     1	3	1	1	0	8

5	     2	0	1	0	4	8

6	     3	0	4	0	1	8

7	     4	2	3	1	1	6

8	     5	0	0	0	7	6

9	     6	0	6	0	1	6

10	     7	6	1	1	0	5

11	     8	5	1	1	1	5

12	     9	4	2	2	0	5

13	     10	2	1	4	1	5

14	     11	3	1	0	4	5

15	     12	1	5	1	1	5

16	     13	6	4	1	1	1

17	     14	3	2	2	5	1

18	     15	0	6	3	3	1

19	     16	1	1	5	6	0

20	     17	0	0	0	13	0

21	     18	0	7	0	6	0

22	     19	8	0	5	0	0

23	     20	4	4	5	0	0

24	     21	4	5	4	0	0

25	     22	6	2	5	0	0

26	     23	4	5	3	1	0

27	     24	3	2	3	5	0

28	     25	3	8	1	1	0

29	     26	9	4	0	0	0

30	     27	8	0	3	2	0

31	     28	6	0	6	1	0

32	     29	6	4	0	3	0

33	     30	1	4	5	3	0

34	     31	2	1	10	0	0

35	     32	1	11	0	1	0

36	     33	1	1	1	10	0

37	     34	3	1	9	0	0

38	     35	0	0	0	13	0

39	     36	0	11	0	2	0

40	     37	2	0	11	0	0

41	     38	2	6	0	5	0

42	     39	2	5	0	6	0

43	     40	9	1	3	0	0

44	     41	4	3	6	0	0

45	     42	4	0	6	3	0

46	     43	5	0	8	0	0

47	     44	2	5	6	0	0

48	     45	0	5	5	3	0

49	     46	6	5	1	1	0

50	     47	5	3	3	2	0

51	     48	5	2	3	3	0

52	     49	1	8	4	0	0

53	     50	12	0	0	1	0

54	     51	4	3	1	5	0

55	     52	0	0	0	13	0

56	     53	0	0	0	13	0

57	     54	0	0	0	13	0

58	     55	5	3	5	0	0

59	     56	7	2	4	0	0

60	     57	2	5	3	3	0

61	     58	5	3	2	3	0

62	     59	5	1	5	2	0

63	     60	2	2	4	5	0

64	     61	4	8	1	0	0

65	     62	0	0	3	10	0

66	     63	0	9	1	3	0

67	     64	1	4	1	7	0

68	     65	1	1	0	11	0

69	     66	0	4	1	8	0

70	     67	4	3	6	0	0

71	     68	8	4	1	0	0

72	     69	3	4	2	4	0

73	     70	4	1	6	2	0

74	     71	6	4	2	1	0

75	     72	0	4	4	5	0

76	     73	2	5	6	0	0

77	     74	2	6	5	0	0

78	     75	2	5	5	1	0

79	     76	5	0	6	2	0

80	     77	4	3	4	2	0

81	     78	1	4	5	3	0

82	     79	3	1	9	0	0

83	     80	1	11	1	0	0

84	     81	0	0	4	9	0

85	     82	4	8	0	1	0

86	     83	2	0	6	5	0

87	     84	2	8	0	3	0

88	     85	5	7	0	1	0

89	     86	2	6	1	4	0

90	     87	1	3	7	2	0

91	     88	6	2	5	0	0

92	     89	3	6	4	0	0

93	     90	0	2	8	3	0

94	     91	4	0	7	2	0

95	     92	1	5	5	2	0

96	     93	1	4	3	5	0

97	     94	3	3	4	3	0

98	     95	8	1	2	2	0

99	     96	2	3	4	4	0

100	     97	4	3	3	3	0

101	     98	1	0	0	12	0

102	     99	0	6	0	7	0

103	     100	6	5	2	0	0

104	     101	2	0	3	8	0

105	     102	0	7	5	1	0

106	     103	7	4	2	0	0

107	     104	0	0	1	12	0

108	     105	0	6	0	7	0

109	     106	1	0	8	4	0

110	     107	7	1	0	5	0

111	     108	0	5	1	7	0

112	     109	1	7	2	3	0

113	     110	2	4	3	4	0

114	     111	0	5	4	4	0

115	     112	2	1	9	1	0

116	     113	1	8	1	3	0

117	     114	1	4	0	8	0

118	     115	6	4	3	0	0

119	     116	7	4	1	1	0

120	     117	4	2	4	3	0

121	     118	8	4	1	0	0

122	     119	10	3	0	0	0

123	     120	0	1	11	1	0

124	     121	6	6	1	0	0

125	     122	7	5	0	1	0

126	     123	5	1	7	0	0

127	     124	3	4	6	0	0

128	     125	3	0	4	6	0

129	     126	1	8	2	2	0

130	     127	4	6	3	0	0

131	     128	5	5	3	0	0

132	     129	3	3	5	2	0

133	     130	1	2	9	1	0

134	     131	8	2	3	0	0

135	     132	1	2	1	9	0

136	     133	3	0	9	1	0

137	     134	0	2	9	2	0

138	     135	0	10	3	0	0

139	     136	1	0	12	0	0

140	     137	2	11	0	0	0

141	     138	1	0	0	12	0

142	     139	2	6	4	1	0

143	     140	1	0	3	9	0

144	     141	0	10	0	3	0

145	     142	0	13	0	0	0

146	     143	0	12	1	0	0

147	     144	0	1	12	0	0

148	     145	2	1	7	3	0

149	     146	0	0	0	13	0

150	     147	0	8	0	5	0

151	     148	8	5	0	0	0

152	     149	0	4	3	6	0

153	     150	0	5	7	1	0

154	     151	5	8	0	0	0

155	     152	0	0	1	12	0

156	     153	0	8	0	5	0

157	     154	6	7	0	0	0

158	     155	0	8	5	0	0

159	     156	0	5	8	0	0

160	     157	6	0	1	0	6

161	     158	6	1	0	0	6

162	     159	6	0	0	1	6

163	     160	12	0	1	0	0

164	     161	11	1	1	0	0

165	     162	11	0	1	1	0

166	     163	9	3	1	0	0

167	     164	8	1	4	0	0

168	     165	3	3	6	1	0

169	     166	3	8	1	1	0

170	     167	1	0	0	12	0

171	     168	0	9	0	4	0

172	     169	5	6	2	0	0

173	     170	5	8	0	0	0

174	     171	5	0	6	2	0

175	     172	5	2	6	0	0

176	     173	5	5	0	3	0

177	     174	1	3	5	4	0

178	     175	0	13	0	0	0

179	     176	0	0	13	0	0

180	     177	0	13	0	0	0

181	     178	0	9	3	1	0

182	     179	4	0	0	9	0

183	     180	0	9	0	4	0

184	     181	3	6	3	1	0

185	     182	6	2	1	4	0

186	     183	4	6	1	2	0

187	     184	0	0	13	0	0

188	     185	0	13	0	0	0

189	     186	0	0	0	13	0

190	     187	12	0	1	0	0

191	     188	13	0	0	0	0

192	     189	0	0	12	1	0

193	     190	3	0	10	0	0

194	     191	4	8	0	1	0

195	     192	3	2	0	8	0

196	     193	6	6	1	0	0

197	     194	0	0	0	13	0

198	     195	0	7	0	6	0

199	     196	11	1	1	0	0

200	     197	11	1	1	0	0

201	     198	11	1	0	1	0

202	     199	0	0	13	0	0

203	     200	0	13	0	0	0

204	     201	0	0	0	13	0

205	     202	0	1	12	0	0

206	     203	2	4	0	7	0

207	     204	0	9	0	4	0

208	     205	6	3	4	0	0

209	     206	0	0	2	11	0

210	     207	0	8	1	4	0

211	     208	1	0	12	0	0

212	     209	1	12	0	0	0

213	     210	1	0	0	12	0

214	     211	2	7	4	0	0

215	     212	10	1	1	1	0

216	     213	5	3	1	4	0

217	     214	6	4	2	1	0

218	     215	1	3	3	6	0

219	     216	0	6	4	3	0

220	     217	1	3	1	8	0

221	     218	0	0	1	12	0

222	     219	0	5	0	8	0

223	     220	1	1	10	1	0

224	     221	2	9	1	1	0

225	     222	1	3	1	8	0

226	     223	2	4	7	0	0

227	     224	6	0	1	6	0

228	     225	2	7	1	3	0

229	     226	5	1	7	0	0

230	     227	5	5	0	3	0

231	     228	1	3	3	6	0

232	     229	6	0	7	0	0

233	     230	7	1	0	5	0

234	     231	2	8	1	2	0

235	     232	4	3	6	0	0

236	     233	9	4	0	0	0

237	     234	2	1	4	6	0

238	     235	1	5	7	0	0

239	     236	6	3	1	3	0

240	     237	3	5	1	4	0

241	     238	1	0	12	0	0

242	     239	0	0	1	12	0

243	     240	0	12	0	1	0

244	     241	2	4	7	0	0

245	     242	2	2	8	1	0

246	     243	2	8	2	1	0

247	     244	2	7	4	0	0

248	     245	1	3	8	1	0

249	     246	1	8	4	0	0

250	     247	7	2	1	3	0

251	     248	4	3	0	6	0

252	     249	2	6	2	3	0

253	     250	0	9	4	0	0

254	     251	10	0	0	3	0

255	     252	0	4	0	9	0

256	     253	4	4	0	5	0

257	     254	1	0	0	12	0

258	     255	0	4	0	9	0

259	     256	2	9	2	0	0

260	     257	1	0	0	12	0

261	     258	0	11	0	2	0

262	     259	4	8	0	1	0

263	     260	0	0	0	13	0

264	     261	0	8	0	5	0

265	     262	3	4	6	0	0

266	     263	0	4	0	9	0

267	     264	0	6	0	7	0

268	     265	0	13	0	0	0

269	     266	0	0	10	3	0

270	     267	0	13	0	0	0

271	     268	5	0	8	0	0

272	     269	5	4	0	4	0

273	     270	4	4	1	4	0

274	     271	8	1	4	0	0

275	     272	8	0	5	0	0

276	     273	7	5	1	0	0

277	     274	4	8	1	0	0

278	     275	1	10	2	0	0

279	     276	0	2	11	0	0

280	     277	4	7	1	1	0

281	     278	0	2	4	7	0

282	     279	0	8	2	3	0

283	     280	2	9	2	0	0

284	     281	0	6	3	4	0

285	     282	0	6	5	2	0

286	     283	2	9	1	1	0

287	     284	13	0	0	0	0

288	     285	7	1	1	4	0

289	     286	1	5	7	0	0

290	     287	0	0	4	9	0

291	     288	0	12	0	1	0

292	     289	5	8	0	0	0

293	     290	10	1	2	0	0

294	     291	2	0	4	7	0

295	     292	7	0	2	4	0

296	     293	11	1	0	1	0

297	     294	0	0	7	6	0

298	     295	4	6	3	0	0

299	     296	6	1	6	0	0

300	     297	4	6	1	2	0

301	     298	3	5	4	1	0

302	     299	8	1	3	1	0

303	     300	5	6	2	0	0

304	     301	3	0	9	1	0

305	     302	1	0	1	11	0

306	     303	1	9	1	2	0

307	     304	4	5	3	1	0

308	     305	4	3	5	1	0

309	     306	1	6	3	3	0

310	     307	4	3	6	0	0

311	     308	10	3	0	0	0

312	     309	6	3	1	3	0

313	     310	3	5	4	1	0

314	     311	5	2	1	5	0

315	     312	1	5	2	5	0

316	     313	2	0	9	2	0

317	     314	0	0	1	12	0

318	     315	0	9	1	3	0

319	     316	2	8	3	0	0

320	     317	7	3	0	3	0

321	     318	3	3	3	4	0

322	     319	6	3	2	1	1

323	     320	9	1	2	0	1

324	     321	5	3	2	2	1

325	     322	1	4	7	0	1

326	     323	0	1	3	8	1

327	     324	0	10	1	1	1

328	     325	0	0	5	7	1

329	     326	0	5	0	7	1

330	     327	0	10	0	2	1

331	     328	4	2	6	0	1

332	     329	4	6	2	0	1

333	     330	2	3	3	4	1

334	     331	3	0	8	1	1

335	     332	4	8	0	0	1

336	     333	2	1	2	7	1

337	     334	2	2	7	1	1

338	     335	4	1	2	5	1

339	     336	0	6	1	5	1

340	     337	3	2	5	2	1

341	     338	3	3	1	5	1

342	     339	2	6	3	1	1

343	     340	2	4	6	0	1

344	     341	4	7	0	1	1

345	     342	3	1	2	6	1

346	     343	1	3	6	1	2

347	     344	2	3	1	5	2

348	     345	0	7	3	1	2

349	     346	2	7	2	0	2

350	     347	3	4	4	0	2

351	     348	1	4	3	3	2

352	     349	3	3	5	0	2

353	     350	5	1	4	1	2

354	     351	3	6	1	1	2

355	     352	5	1	4	1	2

356	     353	3	5	3	0	2

357	     354	2	1	4	4	2

358	     355	5	2	2	0	4

359	     356	2	5	2	0	4

360	     357	0	3	5	1	4


ABI Autosequencer Trace Files

BioEdit version 4.7.0 and above will read ABI model 377 trace files.  I am not yet familiar with older ABI files or .SCF files, so there is currently no support for these files.  Much of the information needed to decipher ABI files was obtained from the ABIView web page (author David H. Klatte).  Information for printout headers was figured out using a hex editor and the information from David Klatte as a starting point.

To open an ABI trace file, simply open the file as if you are opening any other file in BioEdit.  As with alignment and plasmid files, the file format will be automatically detected (you may use the *.abi filter if the file(s) is/are named with a .abi extension).  When an ABI file is opened, the (editable) sequence will be extracted into a new sequence/alignment document and the trace will be displayed in a separate window.  An ABI file contains a duplicate sequence that allows both editing of the sequence and preservation of the original base-calls  The non-editable sequence is displayed in the trace window upon first opening a trace.  The following example shows the sample.abi file that comes with the BioEdit installation opened with the windows tiled:

The mouse may be used to select any part of the trace and partial sequence may be copied from the trace window.  Alternatively, the entire sequence may be copied or exported as raw text or Fasta.

Vertical scaling resizes proportionately when the window is resized.  The entire trace may be zoomed via the Zoom menu, and horizontal scaling may be changed separately from the Horizontal Scale menu.

To edit the sequence, you must first switch to the editable sequence by choosing View->Editable sequence.  Individual basecalls may be edited by highlighting the base with the mouse and typing over it.  Saving the edited sequence will not alter the non-editable sequence, and the non-editable sequence may be viewed at any time by choosing View->Non-editable sequence.  The non-editable sequence is always shown by default upon first opening an ABI file.  The editable sequence, however, is the one extracted to a sequence document.  The edited sequence may be reverted at any time by choosing Edit->Revert edited to non-editable sequence.

You can view some of the relevant header information from the file by choosing File->info.

The trace and sequence may be reverse-complemented by choosing View->Reverse complement.

A printout of the trace looks similar to an ABI Prism printout.  For most purposes, simply choosing “Print” from the “File” menu will produce a formatted print of desirable scaling.  However horizontal and vertical scaling may be changed for printing via the “Print Scaling” menu under the “File” menu.  A set of presets may be chosen, or any exact scaling may be specified (as %) by choosing “other”.

The following picture is similar to what can be expected for page one of a printout of the sample.abi file:


Searching functions

The following search options are available under the Edit menu.  These functions were never originally conceived very well and have evolved sort of sloppily.  Searching functionality is lacking in BioEdit at this time and is in need of improvement.

Find

Find Next

Find in Titles

Find in Next Title

Find Next ORF

Search for user-defined motif


Simple search: Find and Find Next

This is a very simple search function and needs to be improved.  The menu option for simple searching is found under Edit->Find.  A standard search dialog is presented which allows for searching of exact text strings (either case sensitive or insensitive) within selected sequences.  The search is always performed downwards from the beginning of the document, and only includes sequences whose titles are selected (the search is performed only upon the sequences, and does not include titles).  When the text is found, the first instance encountered is highlighted in the document window.  The current search position is remembered.  To continue the search to find the next instance, select Edit->Find Again (F3, by default).  If Edit->Find is chosen again, the search position is reset to the beginning of the document.


Find in Titles and Find in Next Title

To highlight all titles containing specific text, choose Edit->Find in Titles.  To highlight the next title (either up or down) containing specific text, choose Edit->Find in Next Title.  The search is started at the last selected title in the specified direction.


Find Next ORF

When searching for ORFs, only sequences with selected titles are searched, and the search begins after the last selected nucleotide.  To search, choose Edit->Find Next ORF, or Sequence->Nucleic Acid->Find Next ORF.  The search is performed according to the parameters specified in the ORFs page of the preferences dialog.  When an ORF is found, the sequence is highlighted in the document window.


Search for user-defined motif

BioEdit 4.7.8 and above allows searching for user-defined sequence patterns according to single-letter designations of nucleotides and amino acids.  To search for a sequence within selected sequences, choose Edit->Search for user-defined motif.  The following dialog appears:

Enter the text to search for in the input box and choose the type of search.

In all four search types, a ‘*’ is a wildcard and can be used to specify a residue of any identity.  A gap is specified by ‘-’, ‘~’ or ‘.’.

Search type:

Nucleic Acid:  Assumes that the sequences being searched are all nucleic acid sequences.  The search is case insensitive, and depends only upon residue identity.  DNA and RNA are treated identically and a T is seen as identical tot a U. Gaps are ignored.  The following convention is followed for degenerate residue specifications:

R = A or G

Y = C or T/U

K = G or T/U

S = G or C

M = A or C

W = A or T/U

B = G, C or T/U

V = A, G or C

D = A, G or T/U

H = A, C or T/U

N = A, G, C or T/U

Degenerate matching is one-way.  An ‘R’ in the query will match an ‘R’, ‘A’ or ‘G’ in the target, but neither an ‘A’ nor a ‘G’ in the query will match an ‘R’ in the target (an ‘R’ will always match an ‘R’, however). For example: the query ‘aggryknncc**u’ will match all of the following sequences:

aggacgttccttt

aggguuuuccuuu

agggcgccccttt

Amino Acid:  Assumes that the sequences being searched are all amino acid sequences.  The search is case insensitive, and depends only upon residue identity. Gaps are ignored.  The following convention is followed for degenerate residue specifications:

X = any of the twenty standard amino acids

B = D or N

Z = E or Q

Like for nucleic acids, degenerate matching is one-way.  A ‘B’ in the query will match a ‘B’, ‘D’ or ‘N’ in the target, but neither a ‘D’ nor a ‘N’ in the query will match an ‘B’ in the target (a ‘B’ will always match an ‘B’, however).

Standard one-letter amino acid codes are as follows:

A = Ala = alanine

C = Cys = cysteine

D = Asp = aspartate

E = Glu = glutamate

F = Phe = phenylalanine

G = Gly = glycine

H = His = histidine

I = Ile = isoleucine

K = Lys = lysine

L = leu = leucine

M = Met = methionine

N = Asn = asparagine

P = Pro = proline

Q = Gln = glutamine

R = Arg = arginine

S = Ser = serine

T = Thr = threonine

V = Val = valine

W = Trp = tryptophan

Y = Tyr = tyrosine

Exact text match:

A case insensitive search is performed, however, gaps (‘-’, ‘~’ or ‘.’) are ignored and ‘*’ represents any character.  Note that a ‘T’ and a ‘U’ are different, even if the sequence type is nucleic acid, and no degenerate identities are considered.

Exact including gaps:

Like an exact text match, but gaps are not ignored.  A gap is still a ‘-’, ‘~’ or ‘.’, however, and the search does not have to exactly specify the gap character present.  A ‘*’ is still a wildcard in this search and may be used to specify a character of any identity.


PHI-BLAST

The following description is copied directly from the PHI-BLAST information page at:

http://www2.ncbi.nlm.nih.gov/BLAST/phiblast.html

For the paper describing PHI-BLAST, see:

Zhang, Zheng, Alejandro A. Schäffer, Webb Miller, Thomas L. Madden, David J. Lipman, Eugene V. Koonin, and Stephen F. Altschul (1998), "Protein sequence similarity searches using patterns as seeds", Nucleic Acids Res.26:3986-3990.

PHI-BLAST (Pattern-Hit Initiated BLAST) is a search

program that combines matching of regular expressions

with local alignments surrounding the match.

The most important features of the program have been

incorporated into the BLAST software framework

partly for user convenience and partly so that

PHI-BLAST may be combined seamlessly with PSI-BLAST.

Other features that do not fit into the BLAST framework

will be released later as a separate program and/or

separate Web page query options.

One very restrictive way to identify protein motifs

is by regular expressions that must contain each instance

of the motif. The PROSITE database is a compilation of

restricted regular expressions that describe protein motifs.

Given a protein sequence S and a regular expression pattern P

occurring in S, PHI-BLAST helps answer the question:

What other protein sequences both contain an occurrence of P

and are homologous to S in the vicinity of the pattern occurrences?

PHI-BLAST may be preferable to just searching for pattern occurrences

because it filters out those cases where the pattern occurrence is

probably random and not indicative of homology.

PHI-BLAST may be preferable to other flavors of BLAST because

it is faster and because it allows the user to express

a rigid pattern occurrence requirement.

The pattern search methods in PHI-BLAST are based on the

algorithms in:

R. Baeza-Yates and G. Gonnet, Communications of the ACM 35(1992), pp. 74-82.

S. Wu and U. Manber, Communications of the ACM 35(1992), pp. 83-91.

The calculation of local alignments is done using a method

very similar to (and much of the same code as) gapped BLAST.

However, the method of evaluating statistical significance is different, and

is described below.

In the stand-alone mode the typical PHI-BLAST usage looks like:

  blastpgp -i  -k  -p patseedp

  where -i is followed by the file containing the query in FASTA format

  where -k is followed by the file containing the pattern in a syntax given below

  and "patseedp" indicates the mode of usage,  not representing any file.

The syntax for the query sequence is FASTA format as for all other

BLAST queries. The syntax for patterns follows the rules of

PROSITE and is documented in detail below.

The specified pattern is not required to be in the PROSITE list.

Most of the other BLAST flags can be used with PHI-BLAST.

One important exception is that PHI-BLAST requires gapped

alignments (i.e. forbids -g F in the flags) because ungapped

alignments do not make sense for almost all patterns in PROSITE.

There is a second mode of PHI-BLAST usage that is important when

the specified pattern occurs more than 1 time in the query.

In this case, the user may be interested in restricting the

search for local alignments to a subset of the pattern occurrences.

This can be done with a search that looks like:

   blastpgp -i  -k  -p seedp

  where -i is followed by the file containing the query in FASTA format

  where -k is followed by the file containing the pattern in a syntax given below

  and "patseedp" indicates the mode of usage,  not representing any file.

in which case the use of the "seedp" option requires the user to

specify the location(s) of the interesting pattern occurrence(s)

in the pattern file. The syntax for how to specify pattern

occurrences is below. When there are multiple pattern occurrences in the

query it may be important to decide how many are of interest because

the E-value for matches is effectively multiplied by the number

of interesting pattern occurrences.

The PHI-BLAST Web page supports only the "patseedp" option.

PHI-BLAST is integrated with PSI-BLAST. In the command-line

mode, PSI-BLAST can be invoked by using the -j option, as usual.

When this is done as:

   blastpgp -i  -k  -p patseedp -j

  where -i is followed by the file containing the query in FASTA format

  where -k is followed by the file containing the pattern in a syntax given below

  and "patseedp" indicates the mode of usage,  not representing any file.

then the first round of searching uses PHI-BLAST and all subsequent

rounds use PSI-BLAST.

In the Web page setting, the user must explicitly invoke one round

at a time, and the PHI-BLAST Web page provides the option to

initiate a PSI-BLAST round with the PHI-BLAST results.

To describe a combined usage, use the term "PHI-PSI-BLAST"

(Pattern-Hit Initiated, Position-Specific Iterated BLAST).

Determining statistical significance.

When a query sequence Q matches a database sequence D in PHI-BLAST,

it is useful to subdivide Q and D into 3 disjoint pieces

    Qleft Qpattern Qright

    Dleft Dpattern Dright

The substrings Qpattern and Dpattern contain the pattern specified

in the pattern file. The pieces Qpattern and Dpattern are aligned

and that alignment is displayed as part of the PHI-BLAST output,

but the score for that alignment is mostly ignored.

The "reduced" score r of an alignment is the sum of the scores obtained

by aligning  Qleft with Dleft and by aligning Qright with Dright.

The expected number of alignments with a reduced score >= x

is given by:

       CN(Lambda*x + 1)e^(-Lambda *x)

where:

C and Lambda are "constants" depending on the score matrix and the

gap costs.

N is (number of occurrences of pattern in database) * (number of

      occurrences of pattern in Q)

e is the base of the natural logarithm.

It is important to understand that this method of computing

the statistical significance of a PHI-BLAST alignment is mathematically

different from the method used for BLAST and PSI-BLAST alignments.

However, both methods provide E-values, so they the E_values are

displayed with a similar output syntax.

Rules for pattern syntax for PHI-BLAST.

The syntax for patterns in PHI-BLAST follows the conventions

of PROSITE. When using the stand-alone program, it

is permissible to have multiple patterns in a file separated

by a blank line between patterns. When using the Web-page

only one pattern is allowed per query.

Valid protein characters for PHI-BLAST patterns:

    ABCDEFGHIKLMNPQRSTVWXYZU

Valid DNA characters for PHI-BLAST patterns:

    ACGT

Other useful delimiters:

    [ ]    means any one of the characters enclosed in the brackets

        e.g., [LFYT] means one occurrence of L or F or Y or T

    -      means nothing (this is a spacer character used by PROSITE)

    x with nothing following means any residue

    x(5)  means 5 positions in which any residue is allowed (and similarly for any other

          single number in parentheses after x)

    x(2,4) means 2 to 4 positions where any residue is allowed,

           and similarly for any other two numbers separated by a comma;

           the first number should be < the second number.

    >      can occur only at the end of a pattern and means nothing

           it may occur before a period

           (another spacer used by PROSITE)

    .      may be used at the end of the pattern and means nothing

When using the stand-alone program, the pattern should

be in a file, with the first line starting:

 ID

followed by 2 spaces and a text string giving the pattern a name.

There should also be a line starting

 PA

followed by 2 spaces followed by the pattern description.

All other PROSITE codes in the first two columns are allowed,

but only the HI code, described below is relevant to PHI-BLAST.

Here is an example from PROSITE.

ID   CNMP_BINDING_2; PATTERN.

AC   PS00889;

DT   OCT-1993 (CREATED); OCT-1993 (DATA UPDATE); NOV-1995 (INFO UPDATE).

DE   Cyclic nucleotide-binding domain signature 2.

PA   [LIVMF]-G-E-x-[GAS]-[LIVM]-x(5,11)-R-[STAQ]-A-x-[LIVMA]-x-[STACV].

NR   /RELEASE=32,49340;

NR   /TOTAL=57(36); /POSITIVE=57(36); /UNKNOWN=0(0); /FALSE_POS=0(0);

NR   /FALSE_NEG=1; /PARTIAL=1;

CC   /TAXO-RANGE=??EP?; /MAX-REPEAT=2;

The line starting

    ID

gives the pattern a name.

The lines starting

     AC, DT, DE, NR, NR, CC

are relevant to PROSITE users, but irrelevant to PHI-BLAST.

These lines are tolerated, but ignored by PHI-BLAST.

The line starting

     PA

describes the pattern as:

      one of LIVMF

followed by

      G

followed by

      E

followed by

      any single character

followed by

      one of GAS

followed by

      one of LIVM

followed by

      any 5 to 11 characters

followed by

      R

followed by

      one of STAQ

followed by

      A

followed by

      any single character

followed by

      one of LIVMA

followed by

      any single character

followed by

      one of STACV

In this case the pattern ends with a period.

It can end with nothing after the last specifying symbol

or any number of > signs or periods or combination thereof.

Here is another example, illustrating the use of an HI line.

ID    ER_TARGET; PATTERN.

PA  [KRHQSA]-[DENQ]-E-L>.

HI (19 22)

HI (201 204)

In this example, the HI lines specify that the pattern

occurs twice, once from positions 19 through 22 in the

sequence and once from positions 201 through 204 in the

sequence.

These specifications are relevant when stand-alone PHI-BLAST is

used with the

     seedp

option, in which the interesting occurrences of the pattern

in the sequence are specified. In this case the

HI lines specify which occurrence(s) of the pattern

should be used to find good alignments.

In general, the seedp option is more useful than the

standard patternp option ONLY when the

pattern occurs K > 1 times in the sequence AND

the user is interested in matching to J < K of those

occurrences.

Then using the HI lines enables the user to specify which

occurrences are of interest.


Prosite profile and pattern scans

Automated links to web pages (saved locally in the apps folder) are provided for Prosite profile and pattern scans.  For more information about Prosite, see:

http://www.expasy.ch/prosite/

A profilescan compares a protein or nucleic acid sequence against a profile  library.

A pattern scan scans a protein sequence for the occurrence of patterns stored in the Prosite database.

Both of these options may be found under Sequence->World Wide Web.

For a paper describing the Prosite database, see:

Hofmann, K., Bucher, P., Falquet, L., and Bairoch, A. (1999) The PROSITE database, its status in 1999. Nucleic Acids Res. 27:215-219.


nnPredict protein secondary structure prediction

Please note:  The following brief information is taken directly from http://www.cmpharm.ucsf.edu/~nomi/nnpredict-instrucs.html

I am not qualified to discuss neural networks and parallel processing and BioEdit does not perform any protein structure prediction, but simply provides a link to this program through the World Wide Web.

nnpredict is a program which uses a neural-network approach for predicting the secondary structure type for each residue in an amino acid sequence. nnpredict was written by Donald Kneller (Copyright (C) 1991 Regents of the University of California), and a WWW interface (the interface linked to by BioEdit) was written by Nomi Harris (nomi@cgl.ucsf.edu, nlharris@lbl.gov).

For papers describing the algorithm and distributed processing methodology, see:

D. G. Kneller, F. E. Cohen and R. Langridge (1990) "Improvements in Protein Secondary Structure Prediction by an Enhanced Neural Network" J. Mol. Biol. (214) 171-182.

J. L. McClelland and D. E. Rumelhart. (1988) "Explorations in Parallel Distributed Processing" vol 3. pp 318-362. MIT Press, Cambridge MA.


Exporting as Rich Text

An alignment shaded for identities and similarities may be exported in rich text format, preserving the residue highlighting as long as the file is viewed with Word 97 or newer or another word processor that supports highlighting in rich text.  The alignment is shaded according to the current settings for shaded graphic views, and exporting in this format may also be done directly from the shaded graphic view form.  To export an alignment as rich text directly from a document, choose File->Export->Rich text with current shaded view settings.


Characters considered to be valid residues
User-defined valid residue characters / General Preferences

A researcher may wish to use characters in a sequence which are not defined in nature, that are ambiguous, or that simply hold a position, but are not known to be a residue or a gap.  For this reason, there is an option to explicitly define which characters are considered to be valid for the purposes of calculations such as similarity shading and generation of an identity matrix.  There are separate lists of valid residues for amino acid and nucleic acid sequences.  To see or change the current settings for what is considered a "true" residue, choose "Options->Preferences->General.  The following screen should appear:

The default set of characters is AGUCT for nucleic acids and ACDEFGHIKLMNPQRSTVWY for amino acids.  By default, gap characters are not included, but may be included by selecting them on the right and pressing the "<<" button to move them over to the right.  Regardless of whether gap characters are included as valid residues for the purposes of shading calculations, '-', '~' and '.' characters are always treated as gaps internally.  Also, although gaps may be included for the purposes of calculations (they may viewed as a mismatch on the basis that two homologous sequences differ at a position where one contains a base and the other has lost it [or the other is an insertion], gaps are still not shaded as identities, since in reality they are not true physical entities.


Substitution / Similarity Matrices
Substitution Score Matrices

When trying to construct the most likely alignment between two (or more) sequences assumed to be homologous (i.e., derived from the same ancestral sequence), criteria are needed to specify the level of "similarity" between two aligned residues in order to assess their contribution to the quality of the overall alignment.  Although the level of similarity between two residues is not literally meaningful (they are either identical or not, and they either occupy a position in each respective sequence that is the same relative to the ancestral sequence, or they do not), we do not have the data for the ancestral sequence(s) nor the evolutionary steps that led to the current sequences, and we need a system that allows us to estimate the likelihood that one residue has been substituted for another through natural selection (some reflection of the frequency we can expect to see residue a substituted for residue b).   A collection of similarity values that compares every combination of available residues is called a substitution matrix.  For a general introduction to the generation of scoring matrices and basic sequence alignment, I would recommend reference 1 (below)

BioEdit provides a small collection of common substitution matrices for optimal pairwise alignment and for shading similar amino acids in the alignment document view and in the graphic alignment view.

The following matrices are provided and can be found in the BioEdit/apps folder in plain text format:

BLOSUM62:  A commonly used matrix developed by Henikoff and Henikoff (2), which is suggested to be more sensitive than the older PAM matrices (3) for database searching (4) and is the default matrix used by the NCBI BLAST program.

The BLOSUM62 matrix supplied with BioEdit 5.0.6 was obtained from:

ftp://ncbi.nlm.nih.gov/repository/blocks/unix/blosum/BLOSUM/blosum62.bla

PAM40, PAM80, PAM120 and PAM250:  Current PAM matrices, as generated by the PAM program -- see:

http://www.cmbi.kun.nl/bioinf/tools/pam.shtml

PAM is an acronym for "Point Accepted Mutation" (3).  One PAM unit is the evolutionary "time", or divergence, that results in 1 amino acid substitution per 100 amino acids of protein on average (1%).  Larger PAM values indicate greater evolutionary divergence. The PAM matrices were derived from alignments of closely related amino acid sequences, then extrapolated to reflect evolutionary times of n PAM units for a PAMn matrix (the PAM120 matrix gives an indication of the relative expected substitutions frequencies of all residue combinations in 120 PAM units of evolutionary distance).  The number scores in these matrices are the "log odds" ratio of the frequency observed of each substitution (in a given amount of evolutionary "time") to the probability of finding the match randomly, or log(qna,b/pa,pb), where qa,b is the observed frequency of a substitution in n units of evolution of residue a to residue b, and pa and pb are the individual probabilities of finding residue a and b, respectively.  The PAM250 matrix, then, reflects the frequency we could expect a given amino acid to change to another relative to the random chance of finding the two amino acids when there have been a total of 250 substitutions over time per 100 residues.

DAYHOFF:  The "DAYHOFF" matrix provided with BioEdit is an integer-rounded version of the original Dayhoff PAM-250 matrix (3) that I downloaded in it's current form off of the WWW.  For the original PAM250 matrix, see (3) and/or refer to:

http://www.inf.ethz.ch/personal/hallett/drive/node160.html

This matrix is only included in case someone has an interest in using it for BLAST searching for any reason.  It has largely been replaced by more recent PAM matrices generated with updated databases, however, and for database searching, the BLOSUM matrices are generally considered better (4).

IDENTIFY and MATCH:  These matrices are simply for all-or nothing identity-based alignment or shading.  For shading, they are identical.  For alignment, the IDENTIFY matrix has a mismatch value of -10000 and a match score of  1 in all cases, which will select exclusively for stretches of exact matches.  For Optimal alignment allowing the ends to slide, this will find a region of overlap between two identical amino acid sequences which are incomplete (one or both is missing residues on one end).  If used with the local BLAST tool, this matrix will select for only exact local matches, with no internal mismatches.  The MATCH matrix has a match score of 1 and a mismatch score of -1 in all cases, and can be used with BLAST to search for amino acid sequences based only upon identity, but not absolutely bound to no internal mismatches.

GONNET:  Yet another PAM250 matrix, as recommended by (5).

1.  Durbin, R, Eddy, S., Krogh, A. and Mitchison, G. (1998)  Biological Sequence Analysis : Probabilistic Models of Proteins and Nucleic Acids.  Cambridge : Cambridge University Press.

2.  Henikoff, S. and Henikoff, J.G. (1992) Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci U S A 89(22): 10915-10919.

3.  Dayhoff, M. O., Schwartz, R. M. and Orcutt, B. C. (1978) A model of evolutionary change in proteins. matrices for detecting distant relationships In M. O. Dayhoff, (ed.), Atlas of protein sequence and structure, volume 5, pp. 345-358 National biomedical research foundation Washington DC.

4.  Henikoff, S. and Henikoff, J.G. (1993) Performance evaluation of amino acid substitution matrices. Proteins 17(1): 49-61.

5. Gonnet, G.H., Cohen, M.A. and Benner S.A. (1992) Exhaustive matching of the entire

0	protein sequence database. Science 256(5062): 1443-5.

0	The scoring matrices supplied are shown below:

BLOSUM62:

   A  R  N  D  C  Q  E  G  H  I  L  K  M  F  P  S  T  W  Y  V  B  Z  X  *

0	A  4 -1 -2 -2  0 -1 -1  0 -2 -1 -1 -1 -1 -2 -1  1  0 -3 -2  0 -2 -1  0 -4

1	R -1  5  0 -2 -3  1  0 -2  0 -3 -2  2 -1 -3 -2 -1 -1 -3 -2 -3 -1  0 -1 -4

2	N -2  0  6  1 -3  0  0  0  1 -3 -3  0 -2 -3 -2  1  0 -4 -2 -3  3  0 -1 -4

3	D -2 -2  1  6 -3  0  2 -1 -1 -3 -4 -1 -3 -3 -1  0 -1 -4 -3 -3  4  1 -1 -4

4	C  0 -3 -3 -3  9 -3 -4 -3 -3 -1 -1 -3 -1 -2 -3 -1 -1 -2 -2 -1 -3 -3 -2 -4

5	Q -1  1  0  0 -3  5  2 -2  0 -3 -2  1  0 -3 -1  0 -1 -2 -1 -2  0  3 -1 -4

6	E -1  0  0  2 -4  2  5 -2  0 -3 -3  1 -2 -3 -1  0 -1 -3 -2 -2  1  4 -1 -4

7	G  0 -2  0 -1 -3 -2 -2  6 -2 -4 -4 -2 -3 -3 -2  0 -2 -2 -3 -3 -1 -2 -1 -4

8	H -2  0  1 -1 -3  0  0 -2  8 -3 -3 -1 -2 -1 -2 -1 -2 -2  2 -3  0  0 -1 -4

9	I -1 -3 -3 -3 -1 -3 -3 -4 -3  4  2 -3  1  0 -3 -2 -1 -3 -1  3 -3 -3 -1 -4

10	L -1 -2 -3 -4 -1 -2 -3 -4 -3  2  4 -2  2  0 -3 -2 -1 -2 -1  1 -4 -3 -1 -4

11	K -1  2  0 -1 -3  1  1 -2 -1 -3 -2  5 -1 -3 -1  0 -1 -3 -2 -2  0  1 -1 -4

12	M -1 -1 -2 -3 -1  0 -2 -3 -2  1  2 -1  5  0 -2 -1 -1 -1 -1  1 -3 -1 -1 -4

13	F -2 -3 -3 -3 -2 -3 -3 -3 -1  0  0 -3  0  6 -4 -2 -2  1  3 -1 -3 -3 -1 -4

14	P -1 -2 -2 -1 -3 -1 -1 -2 -2 -3 -3 -1 -2 -4  7 -1 -1 -4 -3 -2 -2 -1 -2 -4

15	S  1 -1  1  0 -1  0  0  0 -1 -2 -2  0 -1 -2 -1  4  1 -3 -2 -2  0  0  0 -4

16	T  0 -1  0 -1 -1 -1 -1 -2 -2 -1 -1 -1 -1 -2 -1  1  5 -2 -2  0 -1 -1  0 -4

17	W -3 -3 -4 -4 -2 -2 -3 -2 -2 -3 -2 -3 -1  1 -4 -3 -2 11  2 -3 -4 -3 -2 -4

18	Y -2 -2 -2 -3 -2 -1 -2 -3  2 -1 -1 -2 -1  3 -3 -2 -2  2  7 -1 -3 -2 -1 -4

19	V  0 -3 -3 -3 -1 -2 -2 -3 -3  3  1 -2  1 -1 -2 -2  0 -3 -1  4 -3 -2 -1 -4

20	B -2 -1  3  4 -3  0  1 -1  0 -3 -4  0 -3 -3 -2  0 -1 -4 -3 -3  4  1 -1 -4

21	Z -1  0  0  1 -3  3  4 -2  0 -3 -3  1 -1 -3 -1  0 -1 -3 -2 -2  1  4 -1 -4

22	X  0 -1 -1 -1 -2 -1 -1 -1 -1 -1 -1 -1 -1 -1 -2  0  0 -2 -1 -1 -1 -1 -1 -4

23	* -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4  1

24	DAYHOFF (an older PAM250)

25	   A  R  N  D  C  Q  E  G  H  I  L  K  M  F  P  S  T  W  Y  V  B  Z  X  *

26	A  2 -2  0  0 -2  0  0  1 -1 -1 -2 -1 -1 -4  1  1  1 -6 -3  0  0  0  0 -8

27	R -2  6  0 -1 -4  1 -1 -3  2 -2 -3  3  0 -4  0  0 -1  2 -4 -2 -1  0 -1 -8

28	N  0  0  2  2 -4  1  1  0  2 -2 -3  1 -2 -4 -1  1  0 -4 -2 -2  2  1  0 -8

29	D  0 -1  2  4 -5  2  3  1  1 -2 -4  0 -3 -6 -1  0  0 -7 -4 -2  3  3 -1 -8

30	C -2 -4 -4 -5 12 -5 -5 -3 -3 -2 -6 -5 -5 -4 -3  0 -2 -8  0 -2 -4 -5 -3 -8

31	Q  0  1  1  2 -5  4  2 -1  3 -2 -2  1 -1 -5  0 -1 -1 -5 -4 -2  1  3 -1 -8

32	E  0 -1  1  3 -5  2  4  0  1 -2 -3  0 -2 -5 -1  0  0 -7 -4 -2  3  3 -1 -8

33	G  1 -3  0  1 -3 -1  0  5 -2 -3 -4 -2 -3 -5 -1  1  0 -7 -5 -1  0  0 -1 -8

34	H -1  2  2  1 -3  3  1 -2  6 -2 -2  0 -2 -2  0 -1 -1 -3  0 -2  1  2 -1 -8

35	I -1 -2 -2 -2 -2 -2 -2 -3 -2  5  2 -2  2  1 -2 -1  0 -5 -1  4 -2 -2 -1 -8

36	L -2 -3 -3 -4 -6 -2 -3 -4 -2  2  6 -3  4  2 -3 -3 -2 -2 -1  2 -3 -3 -1 -8

37	K -1  3  1  0 -5  1  0 -2  0 -2 -3  5  0 -5 -1  0  0 -3 -4 -2  1  0 -1 -8

38	M -1  0 -2 -3 -5 -1 -2 -3 -2  2  4  0  6  0 -2 -2 -1 -4 -2  2 -2 -2 -1 -8

39	F -4 -4 -4 -6 -4 -5 -5 -5 -2  1  2 -5  0  9 -5 -3 -3  0  7 -1 -4 -5 -2 -8

40	P  1  0 -1 -1 -3  0 -1 -1  0 -2 -3 -1 -2 -5  6  1  0 -6 -5 -1 -1  0 -1 -8

41	S  1  0  1  0  0 -1  0  1 -1 -1 -3  0 -2 -3  1  2  1 -2 -3 -1  0  0  0 -8

42	T  1 -1  0  0 -2 -1  0  0 -1  0 -2  0 -1 -3  0  1  3 -5 -3  0  0 -1  0 -8

43	W -6  2 -4 -7 -8 -5 -7 -7 -3 -5 -2 -3 -4  0 -6 -2 -5 17  0 -6 -5 -6 -4 -8

44	Y -3 -4 -2 -4  0 -4 -4 -5  0 -1 -1 -4 -2  7 -5 -3 -3  0 10 -2 -3 -4 -2 -8

45	V  0 -2 -2 -2 -2 -2 -2 -1 -2  4  2 -2  2 -1 -1 -1  0 -6 -2  4 -2 -2 -1 -8

46	B  0 -1  2  3 -4  1  3  0  1 -2 -3  1 -2 -4 -1  0  0 -5 -3 -2  3  2 -1 -8

47	Z  0  0  1  3 -5  3  3  0  2 -2 -3  0 -2 -5  0  0 -1 -6 -4 -2  2  3 -1 -8

48	X  0 -1  0 -1 -3 -1 -1 -1 -1 -1 -1 -1 -1 -2 -1  0  0 -4 -2 -1 -1 -1 -1 -8

49	* -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8  1

50	PAM250

51	   A  R  N  D  C  Q  E  G  H  I  L  K  M  F  P  S  T  W  Y  V  B  Z  X  *

52	A  2 -2  0  0 -2  0  0  1 -1 -1 -2 -1 -1 -3  1  1  1 -6 -3  0  0  0  0 -8

53	R -2  6  0 -1 -4  1 -1 -3  2 -2 -3  3  0 -4  0  0 -1  2 -4 -2 -1  0 -1 -8

54	N  0  0  2  2 -4  1  1  0  2 -2 -3  1 -2 -3  0  1  0 -4 -2 -2  2  1  0 -8

55	D  0 -1  2  4 -5  2  3  1  1 -2 -4  0 -3 -6 -1  0  0 -7 -4 -2  3  3 -1 -8

56	C -2 -4 -4 -5 12 -5 -5 -3 -3 -2 -6 -5 -5 -4 -3  0 -2 -8  0 -2 -4 -5 -3 -8

57	Q  0  1  1  2 -5  4  2 -1  3 -2 -2  1 -1 -5  0 -1 -1 -5 -4 -2  1  3 -1 -8

58	E  0 -1  1  3 -5  2  4  0  1 -2 -3  0 -2 -5 -1  0  0 -7 -4 -2  3  3 -1 -8

59	G  1 -3  0  1 -3 -1  0  5 -2 -3 -4 -2 -3 -5  0  1  0 -7 -5 -1  0  0 -1 -8

60	H -1  2  2  1 -3  3  1 -2  6 -2 -2  0 -2 -2  0 -1 -1 -3  0 -2  1  2 -1 -8

61	I -1 -2 -2 -2 -2 -2 -2 -3 -2  5  2 -2  2  1 -2 -1  0 -5 -1  4 -2 -2 -1 -8

62	L -2 -3 -3 -4 -6 -2 -3 -4 -2  2  6 -3  4  2 -3 -3 -2 -2 -1  2 -3 -3 -1 -8

63	K -1  3  1  0 -5  1  0 -2  0 -2 -3  5  0 -5 -1  0  0 -3 -4 -2  1  0 -1 -8

64	M -1  0 -2 -3 -5 -1 -2 -3 -2  2  4  0  6  0 -2 -2 -1 -4 -2  2 -2 -2 -1 -8

65	F -3 -4 -3 -6 -4 -5 -5 -5 -2  1  2 -5  0  9 -5 -3 -3  0  7 -1 -4 -5 -2 -8

66	P  1  0  0 -1 -3  0 -1  0  0 -2 -3 -1 -2 -5  6  1  0 -6 -5 -1 -1  0 -1 -8

67	S  1  0  1  0  0 -1  0  1 -1 -1 -3  0 -2 -3  1  2  1 -2 -3 -1  0  0  0 -8

68	T  1 -1  0  0 -2 -1  0  0 -1  0 -2  0 -1 -3  0  1  3 -5 -3  0  0 -1  0 -8

69	W -6  2 -4 -7 -8 -5 -7 -7 -3 -5 -2 -3 -4  0 -6 -2 -5 17  0 -6 -5 -6 -4 -8

70	Y -3 -4 -2 -4  0 -4 -4 -5  0 -1 -1 -4 -2  7 -5 -3 -3  0 10 -2 -3 -4 -2 -8

71	V  0 -2 -2 -2 -2 -2 -2 -1 -2  4  2 -2  2 -1 -1 -1  0 -6 -2  4 -2 -2 -1 -8

72	B  0 -1  2  3 -4  1  3  0  1 -2 -3  1 -2 -4 -1  0  0 -5 -3 -2  3  2 -1 -8

73	Z  0  0  1  3 -5  3  3  0  2 -2 -3  0 -2 -5  0  0 -1 -6 -4 -2  2  3 -1 -8

74	X  0 -1  0 -1 -3 -1 -1 -1 -1 -1 -1 -1 -1 -2 -1  0  0 -4 -2 -1 -1 -1 -1 -8

75	* -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8  1

76	PAM120

77	  A  R  N  D  C  Q  E  G  H  I  L  K  M  F  P  S  T  W  Y  V  B  Z  X  *

78	A  3 -3 -1  0 -3 -1  0  1 -3 -1 -3 -2 -2 -4  1  1  1 -7 -4  0  0 -1 -1 -8

79	R -3  6 -1 -3 -4  1 -3 -4  1 -2 -4  2 -1 -5 -1 -1 -2  1 -5 -3 -2 -1 -2 -8

80	N -1 -1  4  2 -5  0  1  0  2 -2 -4  1 -3 -4 -2  1  0 -4 -2 -3  3  0 -1 -8

81	D  0 -3  2  5 -7  1  3  0  0 -3 -5 -1 -4 -7 -3  0 -1 -8 -5 -3  4  3 -2 -8

82	C -3 -4 -5 -7  9 -7 -7 -4 -4 -3 -7 -7 -6 -6 -4  0 -3 -8 -1 -3 -6 -7 -4 -8

83	Q -1  1  0  1 -7  6  2 -3  3 -3 -2  0 -1 -6  0 -2 -2 -6 -5 -3  0  4 -1 -8

84	E  0 -3  1  3 -7  2  5 -1 -1 -3 -4 -1 -3 -7 -2 -1 -2 -8 -5 -3  3  4 -1 -8

85	G  1 -4  0  0 -4 -3 -1  5 -4 -4 -5 -3 -4 -5 -2  1 -1 -8 -6 -2  0 -2 -2 -8

86	H -3  1  2  0 -4  3 -1 -4  7 -4 -3 -2 -4 -3 -1 -2 -3 -3 -1 -3  1  1 -2 -8

87	I -1 -2 -2 -3 -3 -3 -3 -4 -4  6  1 -3  1  0 -3 -2  0 -6 -2  3 -3 -3 -1 -8

88	L -3 -4 -4 -5 -7 -2 -4 -5 -3  1  5 -4  3  0 -3 -4 -3 -3 -2  1 -4 -3 -2 -8

89	K -2  2  1 -1 -7  0 -1 -3 -2 -3 -4  5  0 -7 -2 -1 -1 -5 -5 -4  0 -1 -2 -8

90	M -2 -1 -3 -4 -6 -1 -3 -4 -4  1  3  0  8 -1 -3 -2 -1 -6 -4  1 -4 -2 -2 -8

91	F -4 -5 -4 -7 -6 -6 -7 -5 -3  0  0 -7 -1  8 -5 -3 -4 -1  4 -3 -5 -6 -3 -8

92	P  1 -1 -2 -3 -4  0 -2 -2 -1 -3 -3 -2 -3 -5  6  1 -1 -7 -6 -2 -2 -1 -2 -8

93	S  1 -1  1  0  0 -2 -1  1 -2 -2 -4 -1 -2 -3  1  3  2 -2 -3 -2  0 -1 -1 -8

94	T  1 -2  0 -1 -3 -2 -2 -1 -3  0 -3 -1 -1 -4 -1  2  4 -6 -3  0  0 -2 -1 -8

95	W -7  1 -4 -8 -8 -6 -8 -8 -3 -6 -3 -5 -6 -1 -7 -2 -6 12 -2 -8 -6 -7 -5 -8

96	Y -4 -5 -2 -5 -1 -5 -5 -6 -1 -2 -2 -5 -4  4 -6 -3 -3 -2  8 -3 -3 -5 -3 -8

97	V  0 -3 -3 -3 -3 -3 -3 -2 -3  3  1 -4  1 -3 -2 -2  0 -8 -3  5 -3 -3 -1 -8

98	B  0 -2  3  4 -6  0  3  0  1 -3 -4  0 -4 -5 -2  0  0 -6 -3 -3  4  2 -1 -8

99	Z -1 -1  0  3 -7  4  4 -2  1 -3 -3 -1 -2 -6 -1 -1 -2 -7 -5 -3  2  4 -1 -8

100	X -1 -2 -1 -2 -4 -1 -1 -2 -2 -1 -2 -2 -2 -3 -2 -1 -1 -5 -3 -1 -1 -1 -2 -8

101	* -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8  1

PAM80

    A   R   N   D   C   Q   E   G   H   I   L   K   M   F   P   S   T   W   Y   V   B   Z   X   *

0	A   4  -4  -1  -1  -4  -2  -1   0  -4  -2  -4  -4  -3  -5   0   1   1  -8  -5   0  -1  -1  -1 -11

1	R  -4   7  -2  -5  -5   0  -4  -6   0  -3  -5   2  -2  -6  -2  -1  -3   0  -7  -5  -3  -1  -3 -11

2	N  -1  -2   5   3  -6  -1   0  -1   2  -3  -5   0  -4  -5  -3   1   0  -5  -3  -4   4   0  -1 -11

3	D  -1  -5   3   6  -9   0   4  -1  -1  -4  -7  -2  -6  -9  -4  -1  -2 -10  -7  -5   5   2  -3 -11

4	C  -4  -5  -6  -9   9  -9  -9  -6  -5  -4  -9  -9  -8  -8  -5  -1  -4 -10  -2  -3  -7  -9  -5 -11

5	Q  -2   0  -1   0  -9   7   2  -4   2  -4  -3  -1  -2  -8  -1  -3  -3  -8  -7  -4   0   5  -2 -11

6	E  -1  -4   0   4  -9   2   6  -2  -2  -3  -6  -2  -4  -9  -3  -2  -3 -11  -6  -4   2   5  -2 -11

7	G   0  -6  -1  -1  -6  -4  -2   6  -5  -6  -7  -4  -5  -6  -3   0  -2 -10  -8  -3  -1  -2  -3 -11

8	H  -4   0   2  -1  -5   2  -2  -5   8  -5  -4  -3  -5  -3  -2  -3  -4  -4  -1  -4   0   1  -2 -11

9	I  -2  -3  -3  -4  -4  -4  -3  -6  -5   7   1  -4   1   0  -5  -4  -1  -8  -3   3  -4  -4  -2 -11

10	L  -4  -5  -5  -7  -9  -3  -6  -7  -4   1   6  -5   2   0  -4  -5  -4  -3  -4   0  -6  -4  -3 -11

11	K  -4   2   0  -2  -9  -1  -2  -4  -3  -4  -5   6   0  -9  -4  -2  -1  -7  -6  -5  -1  -1  -3 -11

12	M  -3  -2  -4  -6  -8  -2  -4  -5  -5   1   2   0   9  -2  -5  -3  -2  -7  -6   1  -5  -3  -2 -11

13	F  -5  -6  -5  -9  -8  -8  -9  -6  -3   0   0  -9  -2   8  -7  -4  -5  -2   4  -4  -7  -8  -5 -11

14	P   0  -2  -3  -4  -5  -1  -3  -3  -2  -5  -4  -4  -5  -7   7   0  -2  -9  -8  -3  -3  -2  -2 -11

15	S   1  -1   1  -1  -1  -3  -2   0  -3  -4  -5  -2  -3  -4   0   4   2  -3  -4  -3   0  -2  -1 -11

16	T   1  -3   0  -2  -4  -3  -3  -2  -4  -1  -4  -1  -2  -5  -2   2   5  -8  -4  -1  -1  -3  -1 -11

17	W  -8   0  -5 -10 -10  -8 -11 -10  -4  -8  -3  -7  -7  -2  -9  -3  -8  13  -2 -10  -7  -9  -7 -11

18	Y  -5  -7  -3  -7  -2  -7  -6  -8  -1  -3  -4  -6  -6   4  -8  -4  -4  -2   9  -5  -4  -6  -4 -11

19	V   0  -5  -4  -5  -3  -4  -4  -3  -4   3   0  -5   1  -4  -3  -3  -1 -10  -5   6  -4  -4  -2 -11

20	B  -1  -3   4   5  -7   0   2  -1   0  -4  -6  -1  -5  -7  -3   0  -1  -7  -4  -4   5   2  -2 -11

21	Z  -1  -1   0   2  -9   5   5  -2   1  -4  -4  -1  -3  -8  -2  -2  -3  -9  -6  -4   2   5  -2 -11

22	X  -1  -3  -1  -3  -5  -2  -2  -3  -2  -2  -3  -3  -2  -5  -2  -1  -1  -7  -4  -2  -2  -2  -3 -11

23	* -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11   1

0	PAM40

    A   R   N   D   C   Q   E   G   H   I   L   K   M   F   P   S   T   W   Y   V   B   Z   X   *

0	A   6  -6  -3  -3  -6  -3  -2  -1  -6  -4  -5  -6  -4  -7  -1   0   0 -12  -7  -2  -3  -2  -3 -15

1	R  -6   8  -5  -9  -7  -1  -8  -8  -1  -5  -8   1  -3  -8  -3  -2  -5  -1  -9  -7  -6  -3  -5 -15

2	N  -3  -5   7   2  -9  -3  -1  -2   1  -4  -6   0  -7  -8  -5   0  -1  -7  -4  -7   6  -2  -3 -15

3	D  -3  -9   2   7 -12  -2   3  -3  -3  -6 -11  -4  -9 -13  -7  -3  -4 -13 -10  -7   6   2  -5 -15

4	C  -6  -7  -9 -12   9 -12 -12  -8  -7  -5 -13 -12 -12 -11  -7  -2  -7 -14  -3  -5 -11 -12  -8 -15

5	Q  -3  -1  -3  -2 -12   8   2  -6   1  -7  -4  -2  -3 -11  -2  -4  -5 -11 -10  -6  -2   6  -4 -15

6	E  -2  -8  -1   3 -12   2   7  -3  -4  -5  -8  -4  -6 -12  -5  -4  -5 -15  -8  -6   2   6  -4 -15

7	G  -1  -8  -2  -3  -8  -6  -3   6  -8  -9  -9  -6  -7  -8  -5  -1  -5 -13 -12  -5  -2  -4  -4 -15

8	H  -6  -1   1  -3  -7   1  -4  -8   9  -8  -5  -5  -9  -5  -3  -5  -6  -6  -3  -6  -1   0  -4 -15

9	I  -4  -5  -4  -6  -5  -7  -5  -9  -8   8  -1  -5   0  -2  -7  -6  -2 -12  -5   2  -5  -5  -4 -15

10	L  -5  -8  -6 -11 -13  -4  -8  -9  -5  -1   7  -7   1  -2  -6  -7  -6  -5  -6  -2  -8  -6  -5 -15

11	K  -6   1   0  -4 -12  -2  -4  -6  -5  -5  -7   6  -1 -12  -6  -3  -2 -10  -8  -8  -2  -3  -4 -15

12	M  -4  -3  -7  -9 -12  -3  -6  -7  -9   0   1  -1  11  -3  -7  -5  -3 -11 -10  -1  -8  -4  -4 -15

13	F  -7  -8  -8 -13 -11 -11 -12  -8  -5  -2  -2 -12  -3   9  -9  -6  -8  -4   2  -7  -9 -12  -7 -15

14	P  -1  -3  -5  -7  -7  -2  -5  -5  -3  -7  -6  -6  -7  -9   8  -1  -3 -12 -12  -5  -6  -3  -4 -15

15	S   0  -2   0  -3  -2  -4  -4  -1  -5  -6  -7  -3  -5  -6  -1   6   1  -4  -6  -5  -1  -4  -2 -15

16	T   0  -5  -1  -4  -7  -5  -5  -5  -6  -2  -6  -2  -3  -8  -3   1   7 -11  -6  -2  -2  -5  -3 -15

17	W -12  -1  -7 -13 -14 -11 -15 -13  -6 -12  -5 -10 -11  -4 -12  -4 -11  13  -4 -14  -9 -13  -9 -15

18	Y  -7  -9  -4 -10  -3 -10  -8 -12  -3  -5  -6  -8 -10   2 -12  -6  -6  -4  10  -6  -6  -8  -7 -15

19	V  -2  -7  -7  -7  -5  -6  -6  -5  -6   2  -2  -8  -1  -7  -5  -5  -2 -14  -6   7  -7  -6  -4 -15

20	B  -3  -6   6   6 -11  -2   2  -2  -1  -5  -8  -2  -8  -9  -6  -1  -2  -9  -6  -7   6   1  -4 -15

21	Z  -2  -3  -2   2 -12   6   6  -4   0  -5  -6  -3  -4 -12  -3  -4  -5 -13  -8  -6   1   6  -4 -15

22	X  -3  -5  -3  -5  -8  -4  -4  -4  -4  -4  -5  -4  -4  -7  -4  -2  -3  -9  -7  -4  -4  -4  -4 -15

23	* -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15   1

0	GONNET

C  S  T  P  A  G  N  D  E  Q  H  R  K  M  I  L  V  F  Y  W  X  *

0	C 12  0  0 -3  0 -2 -2 -3 -3 -2 -1 -2 -3 -1 -1 -2  0 -1  0 -1 -3 -8

1	S  0  2  2  0  1  0  1  0  0  0  0  0  0 -1 -2 -2 -1 -3 -2 -3  0 -8

2	T  0  2  2  0  1 -1  0  0  0  0  0  0  0 -1 -1 -1  0 -2 -2 -4  0 -8

3	P -3  0  0  8  0 -2 -1 -1  0  0 -1 -1 -1 -2 -3 -2 -2 -4 -3 -5 -1 -8

4	A  0  1  1  0  2  0  0  0  0  0 -1 -1  0 -1 -1 -1  0 -2 -2 -4  0 -8

5	G -2  0 -1 -2  0  7  0  0 -1 -1 -1 -1 -1 -4 -4 -4 -3 -5 -4 -4 -1 -8

6	N -2  1  0 -1  0  0  4  2  1  1  1  0  1 -2 -3 -3 -2 -3 -1 -4  0 -8

7	D -3  0  0 -1  0  0  2  5  3  1  0  0  0 -3 -4 -4 -3 -4 -3 -5 -1 -8

8	E -3  0  0  0  0 -1  1  3  4  2  0  0  1 -2 -3 -3 -2 -4 -3 -4 -1 -8

9	Q -2  0  0  0  0 -1  1  1  2  3  1  2  2 -1 -2 -2 -2 -3 -2 -3 -1 -8

10	H -1  0  0 -1 -1 -1  1  0  0  1  6  1  1 -1 -2 -2 -2  0  2 -1 -1 -8

11	R -2  0  0 -1 -1 -1  0  0  0  2  1  5  3 -2 -2 -2 -2 -3 -2 -2 -1 -8

12	K -3  0  0 -1  0 -1  1  0  1  2  1  3  3 -1 -2 -2 -2 -3 -2 -4 -1 -8

13	M -1 -1 -1 -2 -1 -4 -2 -3 -2 -1 -1 -2 -1  4  2  3  2  2  0 -1 -1 -8

14	I -1 -2 -1 -3 -1 -4 -3 -4 -3 -2 -2 -2 -2  2  4  3  3  1 -1 -2 -1 -8

15	L -2 -2 -1 -2 -1 -4 -3 -4 -3 -2 -2 -2 -2  3  3  4  2  2  0 -1 -1 -8

16	V  0 -1  0 -2  0 -3 -2 -3 -2 -2 -2 -2 -2  2  3  2  3  0 -1 -3 -1 -8

17	F -1 -3 -2 -4 -2 -5 -3 -4 -4 -3  0 -3 -3  2  1  2  0  7  5  4 -2 -8

18	Y  0 -2 -2 -3 -2 -4 -1 -3 -3 -2  2 -2 -2  0 -1  0 -1  5  8  4 -2 -8

19	W -1 -3 -4 -5 -4 -4 -4 -5 -4 -3 -1 -2 -4 -1 -2 -1 -3  4  4 14 -4 -8

20	X -3  0  0 -1  0 -1  0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -2 -2 -4 -1 -8

21	* -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 -8  1

0	MATCH

A  R  N  B  D  C  Q  Z  E  G  H  I  L  K  M  F  P  S  T  W  Y  V  X  *

0	A  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

1	R -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

2	N -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

3	B -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

4	D -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

5	C -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

6	Q -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

7	Z -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

8	E -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

9	G -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

10	H -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

11	I -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

12	L -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

13	K -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

14	M -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1

15	F -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1

16	P -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1

17	S -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1

18	T -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1

19	W -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1

20	Y -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1

21	V -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1

22	X -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  0 -1

23	* -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  0

0	IDENTIFY

0	Same as MATCH, with -10000 in place of all of the 1's.


Optimal Pairwise alignment of sequences
Optimal Pairwise Sequence Alignment

BioEdit allows the option for very simple, optimal sequence alignments directly within an alignment document.

For alignment of sequences, a version of the general Smith and Waterman (1) algorithm is implemented.  Actually, an algorithm similar to the Meyers and Miller (2) version of  Gotoh's (3) modification of the Smith and Waterman algorithm  (which itself is a derivation of the original Needlman-Wunsch (4) algorithm for optimal pairwise alignment) is used which keeps pointers through all of the paths through the alignment matrix,  allowing traceback of the optimal alignment.

The basic alignment algorithm is this:

0	In the above algorithm, i and j represent the rows and columns of a matrix a x b, where sequence a is written along the vertical and sequence b is written along the horizontal.  sub(ai, bj) is the score (according to the scoring matrix) for pairing residue i in sequence a (ai) with residue j in sequence b (bj).  w1 is the cost, or penalty, of opening a gap.  v is the cost of extending an already opened gap.  Si, j is the total alignment score at position i, j in the matrix S, which holds the overall score at every possible alignment permutation.  Pi,j is the score in a matrix that holds a value for every possible alignment position that is either the overall score at position j of the last row plus a gap initiation penalty, or the value of position j of the last row of matrix P plus a gap extension penalty, whichever is greater. Qi,j is the score in a matrix that holds a value for every possible alignment position that is either the overall score at position i of the last column plus a gap initiation penalty, or the value of position i of the last column of matrix Q plus a gap extension penalty, whichever is greater.  Matrices P and Q allow for a gap penalty system where there is a different penalty applied to extending a gap than there is for initiating one (it is fairly easy to imagine that if a deletion or insertion takes place in a sequence that it could consist of an entire region (perhaps a multiple of 3 for a protein-encoding DNA sequence), and the group of residues may only represent one evolutionary event, in which case a constant gap penalty is not likely to perform as well as an affine gap system).  At every possible path through the main alignment matrix, the P and Q matrices are examined to see if it would yield a higher overall score at that point to open a gap or series of gaps than to try to align another pair of residues at the current i and j positions of the matrix.

1	An actual alignment is constructed by doing three basic things:

2	1.  Calculating the S, P and Q matrices for sequences a and b.

3	2.  Each time a value is filled in for matrix S, store a pointer to which cell in the matrix the score was derived from.  If, at any position in the matrix, the next S is derived by pairing the next two residues, then the pointer for that position stores i-1, j-1.  If the value came from Pi,j, then the pointer points to i-1, j.  If it came from Qi,j, then the pointer points to i, j-1.

4	3.  Since all possible alignment paths have to end at the bottom right cell of the matrix, the optimal alignment can be constructed by tracing the pointers back that ultimately lead to the last cell.

5	The choice of matrix can have a large impact on an alignment.  To align two sequences thought to be closely related, it is probably better to use a matrix reflecting less evolutionary divergence (such as a PAM matrix with a lower n number, e.g.,  PAM120 or PAM80), whereas more distantly related sequences may be better aligned with a more divergent  matrix such as PAM250.  For example, take the following (very) short sequences:  TETSEFLY and TESTSEQ.  We will align them with gap penalties of -8 to open and -2 to extend, and use the BLOSUM62 matrix (the default, which is used by default by BLAST) matrix.  The results are different than if we use, say the PAM80 matrix:

6	sequence a = TETSEFLY

7	sequence b = TESTSEQ

8	If we line them up in our three matrices (plus one more for the pointers) and calculate according to the above algorithm, we get:

0	Tracing back through the pointer numbers in the above matrix gives the following alignment:

1	TETSEFLY

2	TESTSE-Q

3	This is probably not the same as if you had just aligned these short sequences by hand.  But, because of the gap penalties and the matrix, this alignment will tolerate 5 mismatched residues rather than accept an extra gap.  When the PAM80 matrix is used, however, the following alignment is produced:

4	TE-TSEFLY

5	TESTSE--Q

6	Which might be closer to what you'd expect by looking at these sequences.  The matrices calculated to produce this alignment are:

7	Tracing these pointer back gives:

8	TE-TSEFLY

9	TESTSE--Q

10	It is possible to initialize the starting conditions of i=0 for all j or j=0 for all i (or both) with no initial penalty for adding and extending a gap, so that the end of one sequence can slide over the other without penalty until the alignment actually starts.  This is what is done when the menu option "Sequence->Pairwise alignment->Align two sequence (allow ends to slide)" is chosen, as opposed to the option "Align two sequences (optimal GLOBAL alignment)", which penalizes gaps at the ends of sequences the same as internal gaps.

11	For comparison, the BLOSUM62 and PAM80 matrices are shown below.  Notice that the scores for mismatched residues are generally much more negative in the PAM80 matrix than in the BLOSUM62 matrix.

BLOSUM62 scoring matrix

   A  R  N  D  C  Q  E  G  H  I  L  K  M  F  P  S  T  W  Y  V  B  Z  X  *

0	A  4 -1 -2 -2  0 -1 -1  0 -2 -1 -1 -1 -1 -2 -1  1  0 -3 -2  0 -2 -1  0 -4

1	R -1  5  0 -2 -3  1  0 -2  0 -3 -2  2 -1 -3 -2 -1 -1 -3 -2 -3 -1  0 -1 -4

2	N -2  0  6  1 -3  0  0  0  1 -3 -3  0 -2 -3 -2  1  0 -4 -2 -3  3  0 -1 -4

3	D -2 -2  1  6 -3  0  2 -1 -1 -3 -4 -1 -3 -3 -1  0 -1 -4 -3 -3  4  1 -1 -4

4	C  0 -3 -3 -3  9 -3 -4 -3 -3 -1 -1 -3 -1 -2 -3 -1 -1 -2 -2 -1 -3 -3 -2 -4

5	Q -1  1  0  0 -3  5  2 -2  0 -3 -2  1  0 -3 -1  0 -1 -2 -1 -2  0  3 -1 -4

6	E -1  0  0  2 -4  2  5 -2  0 -3 -3  1 -2 -3 -1  0 -1 -3 -2 -2  1  4 -1 -4

7	G  0 -2  0 -1 -3 -2 -2  6 -2 -4 -4 -2 -3 -3 -2  0 -2 -2 -3 -3 -1 -2 -1 -4

8	H -2  0  1 -1 -3  0  0 -2  8 -3 -3 -1 -2 -1 -2 -1 -2 -2  2 -3  0  0 -1 -4

9	I -1 -3 -3 -3 -1 -3 -3 -4 -3  4  2 -3  1  0 -3 -2 -1 -3 -1  3 -3 -3 -1 -4

10	L -1 -2 -3 -4 -1 -2 -3 -4 -3  2  4 -2  2  0 -3 -2 -1 -2 -1  1 -4 -3 -1 -4

11	K -1  2  0 -1 -3  1  1 -2 -1 -3 -2  5 -1 -3 -1  0 -1 -3 -2 -2  0  1 -1 -4

12	M -1 -1 -2 -3 -1  0 -2 -3 -2  1  2 -1  5  0 -2 -1 -1 -1 -1  1 -3 -1 -1 -4

13	F -2 -3 -3 -3 -2 -3 -3 -3 -1  0  0 -3  0  6 -4 -2 -2  1  3 -1 -3 -3 -1 -4

14	P -1 -2 -2 -1 -3 -1 -1 -2 -2 -3 -3 -1 -2 -4  7 -1 -1 -4 -3 -2 -2 -1 -2 -4

15	S  1 -1  1  0 -1  0  0  0 -1 -2 -2  0 -1 -2 -1  4  1 -3 -2 -2  0  0  0 -4

16	T  0 -1  0 -1 -1 -1 -1 -2 -2 -1 -1 -1 -1 -2 -1  1  5 -2 -2  0 -1 -1  0 -4

17	W -3 -3 -4 -4 -2 -2 -3 -2 -2 -3 -2 -3 -1  1 -4 -3 -2 11  2 -3 -4 -3 -2 -4

18	Y -2 -2 -2 -3 -2 -1 -2 -3  2 -1 -1 -2 -1  3 -3 -2 -2  2  7 -1 -3 -2 -1 -4

19	V  0 -3 -3 -3 -1 -2 -2 -3 -3  3  1 -2  1 -1 -2 -2  0 -3 -1  4 -3 -2 -1 -4

20	B -2 -1  3  4 -3  0  1 -1  0 -3 -4  0 -3 -3 -2  0 -1 -4 -3 -3  4  1 -1 -4

21	Z -1  0  0  1 -3  3  4 -2  0 -3 -3  1 -1 -3 -1  0 -1 -3 -2 -2  1  4 -1 -4

22	X  0 -1 -1 -1 -2 -1 -1 -1 -1 -1 -1 -1 -1 -1 -2  0  0 -2 -1 -1 -1 -1 -1 -4

* -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4  1

0	PAM80 scoring matrix

    A   R   N   D   C   Q   E   G   H   I   L   K   M   F   P   S   T   W   Y   V   B   Z   X   *

0	A   4  -4  -1  -1  -4  -2  -1   0  -4  -2  -4  -4  -3  -5   0   1   1  -8  -5   0  -1  -1  -1 -11

1	R  -4   7  -2  -5  -5   0  -4  -6   0  -3  -5   2  -2  -6  -2  -1  -3   0  -7  -5  -3  -1  -3 -11

2	N  -1  -2   5   3  -6  -1   0  -1   2  -3  -5   0  -4  -5  -3   1   0  -5  -3  -4   4   0  -1 -11

3	D  -1  -5   3   6  -9   0   4  -1  -1  -4  -7  -2  -6  -9  -4  -1  -2 -10  -7  -5   5   2  -3 -11

4	C  -4  -5  -6  -9   9  -9  -9  -6  -5  -4  -9  -9  -8  -8  -5  -1  -4 -10  -2  -3  -7  -9  -5 -11

5	Q  -2   0  -1   0  -9   7   2  -4   2  -4  -3  -1  -2  -8  -1  -3  -3  -8  -7  -4   0   5  -2 -11

6	E  -1  -4   0   4  -9   2   6  -2  -2  -3  -6  -2  -4  -9  -3  -2  -3 -11  -6  -4   2   5  -2 -11

7	G   0  -6  -1  -1  -6  -4  -2   6  -5  -6  -7  -4  -5  -6  -3   0  -2 -10  -8  -3  -1  -2  -3 -11

8	H  -4   0   2  -1  -5   2  -2  -5   8  -5  -4  -3  -5  -3  -2  -3  -4  -4  -1  -4   0   1  -2 -11

9	I  -2  -3  -3  -4  -4  -4  -3  -6  -5   7   1  -4   1   0  -5  -4  -1  -8  -3   3  -4  -4  -2 -11

10	L  -4  -5  -5  -7  -9  -3  -6  -7  -4   1   6  -5   2   0  -4  -5  -4  -3  -4   0  -6  -4  -3 -11

11	K  -4   2   0  -2  -9  -1  -2  -4  -3  -4  -5   6   0  -9  -4  -2  -1  -7  -6  -5  -1  -1  -3 -11

12	M  -3  -2  -4  -6  -8  -2  -4  -5  -5   1   2   0   9  -2  -5  -3  -2  -7  -6   1  -5  -3  -2 -11

13	F  -5  -6  -5  -9  -8  -8  -9  -6  -3   0   0  -9  -2   8  -7  -4  -5  -2   4  -4  -7  -8  -5 -11

14	P   0  -2  -3  -4  -5  -1  -3  -3  -2  -5  -4  -4  -5  -7   7   0  -2  -9  -8  -3  -3  -2  -2 -11

15	S   1  -1   1  -1  -1  -3  -2   0  -3  -4  -5  -2  -3  -4   0   4   2  -3  -4  -3   0  -2  -1 -11

16	T   1  -3   0  -2  -4  -3  -3  -2  -4  -1  -4  -1  -2  -5  -2   2   5  -8  -4  -1  -1  -3  -1 -11

17	W  -8   0  -5 -10 -10  -8 -11 -10  -4  -8  -3  -7  -7  -2  -9  -3  -8  13  -2 -10  -7  -9  -7 -11

18	Y  -5  -7  -3  -7  -2  -7  -6  -8  -1  -3  -4  -6  -6   4  -8  -4  -4  -2   9  -5  -4  -6  -4 -11

19	V   0  -5  -4  -5  -3  -4  -4  -3  -4   3   0  -5   1  -4  -3  -3  -1 -10  -5   6  -4  -4  -2 -11

20	B  -1  -3   4   5  -7   0   2  -1   0  -4  -6  -1  -5  -7  -3   0  -1  -7  -4  -4   5   2  -2 -11

21	Z  -1  -1   0   2  -9   5   5  -2   1  -4  -4  -1  -3  -8  -2  -2  -3  -9  -6  -4   2   5  -2 -11

22	X  -1  -3  -1  -3  -5  -2  -2  -3  -2  -2  -3  -3  -2  -5  -2  -1  -1  -7  -4  -2  -2  -2  -3 -11

23	* -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11 -11   1

1.  Smith, T.F. and Waterman, M.S. (1981) Identification of common molecular subsequences. J. Mol. Biol. 147(1):195-7.

0	2.  Myers, E.W. and Miller, W. (1988) Optimal alignments in linear space. Comput. Appl. Biosci. 4(1):11-7.

1	3.  Gotoh, O. (1982) An improved algorithm for matching biological sequences. J. Mol. Biol. 162(3):705-8.

2	4.  Needleman, S.B. and Wunsch, C.D. (1970) A general method applicable to the search for similarities in the amino acid sequence of two proteins. J. Mol. Biol. 48(3):443-53.


Graphical Feature Annotations

It is sometimes convenient to have information about certain elements of a sequence (e.g., exons, introns, helices, motifs, etc.) available for reference in a quick and easy way, without going to external sources such as a notebook, other files, or sources in the literature or on the WWW.  For this reason, functions allowing for the graphical annotation of sequence features were added in version 5.0.0.  Annotations may be done by hand, or automatically from existing GenBank format FEATURES data.  Names and descriptions for features that span any position in a sequence are available right in the alignment window as ToolTips when the mouse arrow is moved over the sequence residues.  The standard GenBank format feature types are used as a basis for internally keeping track of the sequence "type".  If one is willing to adhere to GenBank standards when defining the "description" of each feature, the feature annotation functions of BioEdit can also provide a convenient way to annotate a sequence, or set of sequences, which can be exported in standard GenBank format using the user-defined graphical features to fill in the GenBank FEATURES field.  This can be a useful starting point for a sequence submission using Sequin or BankIt.

When a feature is added to a sequence in BioEdit manually, the "true" positions are calculated and assumed to take precedent over the absolute positions in the alignment, and all future alignment adjustments are handled with these "true" positions in mind.  For example, if 5 gaps are deleted within a feature, the end of a feature is drawn back by five in the alignment, but the absolute number of residues within the feature does not change.  If 3 bases are deleted within the feature, the actual end position of the feature will be moved back by three.  Likewise, when features are added automatically from GenBank information, the positions in the alignment which correspond to the true start and end of each feature are calculated and updated to reflect the correct aligned state of all elements.  BioEdit allows control over the title of the feature, the color, the shape (rectangular, oval, diamond or arrow), the direction (only makes a difference for an arrow), the "type" (either "undefined" or any of the 67 standard GenBank feature types), and reserves space for a description (unlimited in length).

Adding a feature manually

Modifying an existing feature

Deleting features

Annotating sequences automatically from existing GenBank FEATURES data

GenBank FEATURE types

Annotating other sequences based upon an annotated template


Adding, Modifying, or Deleting Features
Adding, modifying and deleting sequence features manually

There are two ways to add or modify sequence features manually:

1.  Highlight the sequence title and choose the menu option "Sequence->Features->Edit Features".  There must be only one sequence title highlighted, or BioEdit will not know which sequence to edit the features from.  The following dialog will appear (which of course would be empty if there were not yet any features added to the sequence

To add a feature, fill in the "name" box with the title of the feature, add a description to the "Desc." box, and specify either the start and end positions in the sequence as if the sequence were a simple, unaligned sequence, or, if the sequence is in an alignment an it is easier to determine the alignment positions, you can specify those instead and BioEdit will figure out the true positions for you.  If you fill them both in, BioEdit will ignore the alignment positions and recalculate them based on the true positions specified.  Note:  If you want a feature to reflect orientation, and the orientation is reverse, specify the start position as the higher number and the end position as the lower number.  Next, choose a color by pressing the "Color" button (you will get a color picker dialog), choose the shape, and specify a type under "Type".  After this, press "Add New" to add the feature to the sequence.  Note that if two features overlap in position, the feature further down in the list will be drawn on top of the one further back in the list.  To change the positions of features in the list, highlight one or more feature titles and press the "Up" or "Down" button.

To modify an existing feature, click the title of the feature on the left and do the same things as for adding a feature.  Instead of pressing "Add New", just press "Modify" (Pressing "Add New" will effectively duplicate the feature).   You may modify elements of multiple features at a time by selecting the titles of all of those features at once.  The elements that are in common to all selected features will show up, while those that are not will not show up.  If a change is made to any element, and "Modify" is pressed, the change will be applied to all selected features.

To delete one or more features, highlight the features and press "Delete".

When finished adding or modifying features, press "Close" at the bottom right of the dialog.

2.  Adding or Modifying a feature from the alignment window:

Adding or modifying a feature from right within the alignment window utilizes a right mouse-click context menu.  For this menu to be available, all of the right mouse-click activated alignment features must be turned off.  This means that the following four buttons must be in the up position (not depressed):

  If any of these buttons is down, right-clicking in the alignment window will add or delete gaps, depending upon which button is down.

To add a new feature, highlight the desired span of the feature in the sequence within the alignment window.  Next, right-click the mouse anywhere over the highlighted section and choose "Annotate Selection" in the context menu that comes up.

 The following dialog will appear:

The rest of the options are the same as in adding a feature manually, but the feature positions are specified for you based upon the selection in the alignment window.  You may annotate a block selection by selecting a block of residues that span multiple sequences and doing the same thing.  In this case, the same feature will be applied to the same alignment positions in each sequence, and the "true" positions will be updated independently for each sequence according to the alignment positions.

To modify an existing annotation, right-click anywhere over the annotation, then choose "Update Annotation"  (only visible if you right click over an annotation and only if there is only one annotation spanning that region)  and you will get a dialog like the one above.  Pressing OK will update that annotation, rather than adding a new one.  If you simply right-click over the annotation, the positions in the dialog will reflect the current begin and end of the feature.  If you make a new selection within the annotation before right-clicking, however, the positions in the dialog will reflect the selected positions in the alignment, assuming you want to easily alter the feature positions.  You may also update the same positioned annotations in several sequences at a time this way by selecting a block, right-clicking and choosing "Update Annotation".


Automatic Annotation from GenBank Information
Annotating sequences automatically from existing GenBank FEATURES data

You may have BioEdit automatically add feature annotations from GenBank format FEATURES data, if it is present.  To see if there is FEATURES data in a sequence, double-click on the sequence title, press the [image] button to expand the window, and look at the "FEATURES" box.   If that box is filled in with data formatted similar to the following, then there is data formatted in the expected manner for auto-annotating:

Example of formatting in the GenBank FEATURES field:

FEATURES             Location/Qualifiers

0	     source          1..247

1	                     /organism="Halobacterium salinarum"

2	                     /db_xref="taxon:2242"

3	     NonStdResidue   1

4	                     /non-std-residue="PCA NH3+"

5	     SecStr          10..31

6	                     /note="helix 1"

7	                     /sec_str_type="helix"

8	... etc.

9	To annotate a sequence automatically, highlight the titles of any sequences you want annotated (and that have GenBank FEATURES data), then choose "Sequence->Features->Automatically annotate from GenBank Feature Fields".  You will get the following dialog:

0	The available tags to search for are on the left.  To add a tag or tags to the list of tags to look for, select whatever tags you would like to be included and press the ">>" button (you can move any back to the other side with the "<<" button).  You can add your own tag to look for by typing it into the "Add New Descriptor" box and pressing "Add New Descriptor", but all of the standard GenBank tags should be available in the box on the left.

1	You may choose a default color to apply to all of the features, or you can let BioEdit automatically choose colors for you (they can be edited later).  If BioEdit chooses the colors,  all features of the same type will get the same color.  If you choose a default color all features will be the same color, regardless of type.  You may also choose a default shape.  The default for all features is rectangular.  The available shape options are:  rectangle, oval, diamond and arrow.  If arrow is chosen, then the start and end positions are important for determining orientation of a feature.

2	When BioEdit adds features, it searches through the FEATURES data looking for the specific tags specified in the above dialog.  When it finds one (formatted in the proper place), a new feature is created.  The title will be the feature type plus a number reflecting the present number of that feature in the list (e.g. "exon 1", "intron 1", "exon 2", etc.).  The description will be all of the descriptive data that follows the tag in the file, including carriage returns to keep the formatting correct.  For example, a CDS feature might have the following name and description:

3	Name:

4	CDS 2

5	Description:

6

/label=b0014

0	/gene="dnaK"

1	/product="DnaK protein (heat shock protein 70)"

2	/note="o638; 100 pct identical to DNAK_ECOLI SW: P04475"

3	/codon_start=1

4	/transl_table=11

5	/translation="MGKIIGIDLGTTNSCVAIMDGTTPRVLENAEGDRTTPSIIAYTQ

6	DGETLVGQPAKRQAVTNPQNTLFAIKRLIGRRFQDEEVQRDVSIMPFKIIAADNGDAW

7	VEVKGQKMAPPQISAEVLKKMKKTAEDYLGEPVTEAVITVPAYFNDAQRQATKDAGRI

8	AGLEVKRIINEPTAAALAYGLDKGTGNRTIAVYDLGGGTFDISIIEIDEVDGEKTFEV

9	LATNGDTHLGGEDFDSRLINYLVEEFKKDQGIDLRNDPLAMQRLKEAAEKAKIELSSA

10	QQTDVNLPYITADATGPKHMNIKVTRAKLESLVEDLVNRSIEPLKVALQDAGLSVSDI

11	DDVILVGGQTRMPMVQKKVAEFFGKEPRKDVNPDEAVAIGAAVQGGVLTGDVKDVLLL

12	DVTPLSLGIETMGGVMTTLIAKNTTIPTKHSQVFSTAEDNQSAVTIHVLQGERKRAAD

13	NKSLGQFNLDGINPAPRGMPQIEVTFDIDADGILHVSAKDKNSGKEQKITIKASSGLN

14	EDEIQKMVRDAEANAEADRKFEELVQTRNQGDHLLHSTRKQVEEAGDKLPADDKTAIE

15	SALTALETALKGEDKAAIEAKMQELAQVSQKLMEIAQQQHAQQQTAGADASANNAKDD

DVVDAEFEEVKDKK"

0	BioEdit will place the end toward the left (lower number) and the start toward the right (higher number) for features that are specified as "complement".

1	 For features that are specified as multiple positions with a "join" command, a separate feature will be created for each individual start/end position set.  In this case, the first feature will have the full description field.  Subsequent features created by the join command will have the description "join #<number> to <feature type> <number>" (e.g., "join #4 to CDS 2").


Annotation of sequences based on a template
Annotating other sequences based upon an annotated template

If you are dealing with an alignment of homologous sequences, chances are good that features you will be interested in that have to do with the function of the sequence will be lined up between sequences in a biologically relevant alignment.  Therefore, for features such as RNA or protein helices, functional motifs, or introns, exons and CDS regions, etc. in many, if not most, aligned sequences it may be only necessary to annotate one sequence with the features of interest and then, once the sequences are properly aligned, annotate all of the others based upon the alignment positions of features in the annotated sequence.  This way, even if the actual true positions and lengths of features differs between sequences, but their relative positions in a biologically relevant alignment line up vertically, then annotating correctly aligned sequences becomes much easier than having to annotate each sequence individually.  The true positions for features created in this way are then calculated automatically for you by BioEdit.

To annotate sequences based using another annotated sequence as a template, first move the annotated sequence to the top of the alignment, select the titles of all sequences you want annotated, then choose "Sequence->Features->Annotate selected sequences using the first sequence as a template".


Grouping sequence together
Grouping sequences into groups or families

Sequences may be grouped together to reflect their relationship by highlighting their titles with a group-specific color.  Also, the alignment for grouped sequences may be locked together in order to synchronize alignment adjustments to pre-aligned, closely related sequences when making alignment adjustments based upon new data or added sequences.

To edit sequence groups, choose "Sequence->Sequence groups (or families)".  You will get the following dialog:

You may create groups by typing in the desired group name in the "Name" edit and pressing "Add".  A new group will be created which does not have any sequences in it.  To add sequences to a group, select the group title in the "Group" list and select the desired sequence titles from the far right list entitled "Available sequences not in a group" and press the "<<" button.  You can remove sequence from a group by selecting them on the left and pressing the ">>" button.  Each group has a description and a color.  The title backgrounds in the alignment window will be colored according to the group color if the sequences belong to a group.  You can remove groups by highlighting them in the "Group" list and pressing "Delete Group(s)".


Dot Plots
Dot Plot

A dot plot compares two sequences at every position.  The simplest form of dot plot places one sequence along the X axis and the other along the Y axis of a matrix and placing a dot at every intersecting cell where the current row in one sequence has the same residue as the current column in the other sequence.  In BioEdit, a user defined window is taken, and matches are tabulated along the diagonal (an unbroken alignment of <window size> residues staring at position x, y in the matrix for every x and y).  BioEdit allows a few options.  When you choose to do a dot plot, first select the two sequences to compare, then choose "Sequence-> Dot Plot (pairwise comparison)".  The following dialog will come up:

BioEdit plots a dot at the x and y center point of each scan window (for example, if the sequences were a 100% match, each was 100 bases long, and the window size was 20, there would be a solid line of dots down the center diagonal, but it would start at x, y  = 10, 10, and end at x, y = 90. 90, because the center point of each full window is plotted).

The option "Do full shaded alignment" means that the number of matches down the window length will be tabulated and a dot will be plotted at the window's center point with an intensity of shading proportional to the ratio of matches to the window length, rather than the more traditional all or nothing plotting based upon a threshold of mismatches.

To only plot absolute black and white, uncheck the "Do full shaded alignment" option and specify a mismatch limit.

You may choose to count "similar" residues as matches as well by checking the "Count similar amino acids as well as identities" option.  This option is only available when comparing sequences whose type is defined as "Protein".

You may choose to save the matrix data by pressing the "Save Matrix Output As ... " button and specifying a file name.

BioEdit produces a simple text-based matrix file that is brought up in the matrix plotter which plots a minimum of 1 pixel per data point, so this dot plot function is not suitable for large sequences (even moderately large -- the practical limit is really under 1500 to 2000 residues).

The results will come up in the BioEdit matrix plotter, which is mainly intended for mutual information plots, but is actually suitable for any reasonably small matrix.


Consensus sequence preferences

To set preferences for how consensus sequences are generated, choose "Options->Preferences->Consensus"

To generate a consensus sequence, highlight all sequence titles you want to participate in the calculation, then choose "Alignment->Create Consensus Sequence".


Preferences for optimal pairwise alignment

To set gap penalty parameters for pairwise alignment, and match and mismatch scores for nucleic acid pairwise alignment, choose "Options->Preferences->Pairwise Alignment".

For information on pairwise alignments, see Optimal Pairwise Sequence Alignment


Verbal Confirmation of a Sequence
Verbal confirmation of sequences

If you hand-type a small sequence into the single-sequence editor, for example a primer sequence to be stored in a file and ordered for synthesis, it is sometimes helpful to have someone read back the sequence for you as you verify on paper base by base as they read.  If there is nobody available to read your sequence to you, BioEdit will slowly read a sequence back from within the single sequence editor, highlighting each base as it goes along (amino acid sequences may be read as well).

To read a sequence back from within the single sequence editor, choose "Edit->Read Sequence Back (Press escape to cancel)".

Note:  This is only available from the single sequence editor.  To open a sequence in the single sequence editor, double-click on its title, or highlight its title and choose "Sequence->Edit Sequence".


Sorting Sequences

Sequences in an alignment document may be sorted by the following criteria:

•	Title

•	LOCUS

•	DEFINITION

•	REFERENCES

•	COMMENT

•	ACCESSION

•	PID/NID

•	residue frequency in a selected column(s)

To sort sequences, choose "Sequence->Sort-><sort type>

The first six sort types are alphabetical.

The sort by residue frequency works in the following manner:

1.  The frequency of each residue is determined in each selected column.

2.  The Frequencies of each of the residues in their respective columns are summed across each selected subsequence (the selected segment of each sequence through which the selected columns cut) to produce a score.

3.  The sequences are sorted from highest score to lowest.


Conservation (Dot) Plot
Conservation plot view

Sometimes it can be convenient to plot an alignment with reference to a standard sequence (usually the top one), where any residues down a column which are identical to the standard at that point are plotted as a specific character (usually a dot).  BioEdit offers two basic ways to do this:

1.  Choose "Alignment->Plot identities to first sequence with a dot" to create a whole new sequence alignment document that has identities to the first sequence plotted as a dot.  In this new document, the sequence data for residues converted to dots is not retained, and the new alignment doc is intended only for generating a picture of an alignment.  You may then choose File->Graphic view and uncheck the option for similarity and identity shading to make a figure out of the plot.

2.  For a dynamic view of the alignment which plots identities to a standard sequence as a specific character, press the [image] button on the toolbar, or choose the menu item "View->Conservation Plot".  When the conservation plot button is down, you have the option to specify the character to be used for plotting identities:

  The default is a dot, but theoretically any character can be used.  Realistically, though, a period or space (blank) is generally the easiest to see.

You can at any time change the reference sequence by right-clicking the title of the sequence you would like to have as reference.  The reference sequence is handled internally by its number in the list, though, so if you move the sequence up or down, you will have to right-click its title again.


Anchoring a column to protect aligned regions

It is sometimes useful to be able to lock a column of an alignment without having to worry about accidentally pushing or pulling sequence over that position, although it may be off of the current viewing screen.  BioEdit therefore allows the anchoring of as many columns as necessary to protect regions of an alignment that you don’t want to get messed up.  To anchor a column, depress the add / remove column anchors button ( [image]), then click the mouse over the column you want anchored.  To anchor an entire region, add a column anchor to each side of the region you want protected.  If you want to make sure that no alignment is possible in this region, simply add an anchor to each side, unselect all sequence titles, select all the residues within the region (highlight the region with the mouse by dragging the mouse on the ruler bar over the region, then choose “Sequence->Gaps->Lock Gaps” to lock all the gaps in that region.  That region should be effectively locked until the anchors are removed (or the "“ignore anchors” button is pressed down).

To remove an anchor, depress the [image] button, then click over an existing anchor to remove it.

If you want to adjust the alignment in an anchored region, but don’t feel like resetting all of the anchors, you may depress the “ignore column anchors” button ( [image]) and make your adjustments.  Be sure to hit the “ignore column anchors” button again after the adjustments are finished to turn it off and make the anchors active again.


Phylogenetic Tree Viewer

BioEdit version 5.0.6 contains a very rudimentary phylogenetic tree viewer that will open and view phylip-formatted tree files.  Also, multiple trees may be linked directly to alignment files (up to 50 trees may be linked to one alignment), and phylogenetic tree information, along with the current node and branching pattern, is saved in the BioEdit file format.  The tree viewer also allows flipping of nodes (in a way that does not alter the phylogeny), saving, printing, label-editing, and viewing the tree with or without distance information.  Only a rectangular cladogram view is currently available, however.  For alternative formatting options I recommend using TreeView, which is available on the WWW from Roderic Page at http:://taxonomy.zoology.gla.ac.uk/rod/rod.html.  The installation for TreeView version 1.5.2 is distributed with BioEdit, and the TreeView.zip file can be found in the BioEdit installation folder.

To open a phylip tree in BioEdit, simply choose “File->Open” from anywhere in the program.  BioEdit should automatically figure out that it’s a tree file and open it appropriately.  A sample of how a tree might look in BioEdit is shown below:

You may click the mouse on any node that has a small square ( [image] ) at its junction to flip the tree around that node.  This will reverse the position of all downstream nodes and leaves (the final labels at the very end of each branch) while preserving the overall branch pattern and distances in the tree.

To edit a label, click the mouse on the label on the screen.  The label will go into edit mode, and will become completely selected .  You may then type the label you wish to rplace it with.  When you are done, either select a different place on the tree window with the mouse, or press enter.  To cancel the editing, press <Esc> (the escape key).

Note:  Trees are sometimes written with more than two branches coming off of the same node.  I’ve noticed that trees written by Phylip programs will sometimes have three branches coming directly off the first node.  The BioEdit tree viewer allows more than one branch off of each node (up to 10, actually, just to be safe), but when a tree is opened directly in the BioEdit tree viewer from a file, if the tree has nodes with more than two branches, it is automatically converted to a completely binary tree by creating an extra node of distance 0 at each point where there is more than one branch point from a node.  The tree topology does not change, and this allows one to orient all branch points relative to each other.  Upon opening a tree, the tree is iterated through, moving each branch beyond 2 for any node to it’s own, new node (with a distance of 0 from its parent), until there are no nodes with more than two branches.  When a tree is imported into a BioEdit alignment, however, this conversion is not performed, and the tree is imported directly as it is written.  It is viewed in the same viewer, but the original node organization is retained.

You may save the tree from the File menu (File->Save).  The current version of BioEdit is limited to opening and saving phylip-formatted trees.  In phylip format, the above tree looks something like this:

((P.mirabili: 0.13368,((B.aphidico: 0.6262,(((T.maritima: 1.14167,((((M.genitali: 0.24742,M.pneumoni: 0.43983): 0.88981,(M.capricol: 0.70024,(H.pylori: 1.37587,B.subtilis: 0.53651): 0.19415): 0.0886): 0.04525,(S.PCC6803: 0.87437,((M.tubercul: 0.14643,M.leprae: 0.30498): 0.56324,(M.luteus: 0.65897,(S.bikinien: 0.1209,S.coelicol: 0.01772): 0.29437): 0.14817): 0.59556): 0.14169): 0.18393,(T.pallidum: 1.3449,B.burgdorf: 0.75431): 0.40702): 0.06668): 0.13184,C.burnetti: 0.76309): 0.22955,P.putida: 0.45219): 0.10167): 0.15512,H.influenz: 0.24691): 0.08603): 0,E.coli: 0.12297);

The BioEdit tree viewer supports only one tree at a time, and if a tree file is opened that has multiple trees in it, only the first tree will be loaded.  However, when importing  trees into an alignment file, all of the trees (up to 50 anyway) will be loaded into the alignment (as separate tree entries).

The tree viewer formats a tree to the current size of the viewing window, and does not now support multiple paging, zooming, or manual size specification, so it is only suitable for rather small trees.  Also, printing is rather primitive, and simply scales to the size of the printer page.  Right now, there is no copying to the clipboard.  To produce an image of a tree, I recommend TreeView, which copies trees nicely to the clipboard as a Windows metafile.


Importing Phylogenetic Trees into an alignment

It is sometimes convenient to have a phylogenetic tree handy showing the relationships between sequences in an alignment.  For this reason, BioEdit 5.0.6 and above allows you to import one or more phylogenetic trees into an alignment file (as long as they are phylip-formatted), and to save those trees in a BioEdit-format alignment file.  You may have up to 50 trees in one file.  Normally, only one tree is probably desired, but one might have a set of equivalent trees generated by parsimony methods, or perhaps you want to have trees showing the relationships between sequences in subgroups of an alignment.

To import a tree into a BioEdit alignment, open the alignment (File->Open), then choose “Alignment->Phylogenetic Tree->Import Tree”.  The menu will look something like this:

You will be prompted to specify the tree file to import.  To view the imported tree, choose “Alignment->Phylogenetic Tree->View Tree-> (tree number)”.  For example, if you have three trees associated with an alignment, the menu will look like this:

You may then save your file in BioEdit format and your associated trees will be saved with the file.  Keep in mind that, if a file is not saved, a “Revert to Saved” operation will also remove any trees that were not saved with the file.

You may remove a tree with the “Alignment->Phylogenetic Tree->Remove Tree” option.

You may also open a tree in the tree viewer and choose to associate it with an open alignment file, if it is easier to see the tree to make sure it is the correct one.  To do this, open the tree from the File->Open command from anywhere in the program, make sure you have your alignment file open, then, from the tree viewer, choose “File->Associate Tree With Alignment”.  You will get a dialog that lists all the currently open alignments, from which you can choose the appropriate alignment.