EMBOSS: emast

emast

Wiki

The master copies of EMBOSS documentation are available at http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.

Please help by correcting and extending the Wiki pages.

Function

Motif detection

Description

EMBASSY MEME is a suite of application wrappers to the original meme v3.0.14 applications written by Timothy Bailey. meme v3.0.14 must be installed on the same system as EMBOSS and the location of the meme executables must be defined in your path for EMBASSY MEME to work.

Usage:
ememe [options] mfile outfile

The outfile parameter is new to EMBASSY MEME. The output is always written to .

MAST: Motif Alignment and Search Tool

MAST is a tool for searching biological sequence databases for sequences that contain one or more of a group of known motifs.

A motif is a sequence pattern that occurs repeatedly in a group of related protein or DNA sequences. Motifs are represented as position-dependent scoring matrices that describe the score of each possible letter at each position in the pattern. Individual motifs may not contain gaps. Patterns with variable-length gaps must be split into two or more separate motifs before being submitted as input to MAST.

MAST takes as input a file containing the descriptions of one or more motifs and searches a sequence database that you select for sequences that match the motifs. The motif file can be the output of the MEME motif discovery tool or any file in the appropriate format.

MAST outputs three things:

1. The names of the high-scoring sequences sorted by the strength of the combined match of the sequence to all of the motifs in the group.
2. Motif diagrams showing the order and spacing of the motifs within each matching sequence.
3. Detailed annotation of each matching sequence showing the sequence and the locations and strengths of matches to the motifs.

MAST works by calculating match scores for each sequence in the database compared with each of the motifs in the group of motifs you provide. For each sequence, the match scores are converted into various types of p-values and these are used to determine the overall match of the sequence to the group of motifs and the probable order and spacing of occurrences of the motifs in the sequence.

Algorithm

Please read the file README distributed with the original MEME.

Usage

Here is a sample session with emast

% emast ex1.html ex1.out Motif detection Print results for sequences with E-value [10]: Show motif matches with p-value < mt [0.0001]:

Go to the input files for this example
Go to the output files for this example

EXAMPLES:

Please note the examples below are unedited excerpts of the original MEME documentation. Bear in mind the EMBASSY and original MEME options may differ in practice (see "1. Command-line arguments").

The following examples assume that file "meme.results" is the output of a MEME run containing at least 3 motifs and file SwissProt is a copy of the Swiss-Prot database on your local disk. DNA_DB is a copy of a DNA database on your local disk.

1) Annotate the training set:
mast meme.results

2) Find sequences matching the motif and annotate them in the SwissProt database:
mast meme.results -d SwissProt

3) Show sequences with weaker combined matches to motifs.
mast meme.results -d SwissProt -ev 200

4) Indicate weaker matches to single motifs in the annotation so that sequences with weak matches to the motifs (but perhaps with the "correct" order and spacing) can be seen:
mast meme.results -d SwissProt -w

5) Include a nominal order and spacing of the first three motifs in the calculation of the sequence p-values to increase the sensitivity of the search for matching sequences:
mast meme.results -d SwissProt -diag "9-[2]-61-[1]-62-[3]-91"

6) Use only the first and third motifs in the search:
mast meme.results -d SwissProt -m 1 -m 3

7) Use only the first two motifs in the search:
mast meme.results -d SwissProt -c 2

8) Search DNA sequences using protein motifs, adjusting p-values and E-values for each sequence by that sequence's composition:
mast meme.results -d DNA_DB -dna -comp

Command line arguments

Where possible, the same command-line qualifier names and parameter order is used as in the original mast. There are however several unavoidable differences and these are clearly documented in the "Notes" section below.

Most of the options in the original mast are given in ACD as "advanced" or "additional" options. -options must be specified on the command-line in order to be prompted for a value for "additional" options but "advanced" options will never be prompted for.

Please note that one only of -stdin or -d should be specified. If you set both, then -d will be used. This behaviour could have been enforced at the level of the ACD file by using an ACD select: or list: type but this would have been inconsistent with the original meme, which has two separate options.

Standard (Mandatory) qualifiers: [-mfile] infile If -d is not given, MAST looks for database specified inside of . -ev float [10] Print results for sequences with E-value (Any numeric value) -mt float [0.0001] Show motif matches with p-value < mt (Any numeric value) [-outfile] outfile [*.emast] MAST program output file Additional (Optional) qualifiers: -dfile infile If -d is not given, MAST looks for database specified inside of . -afile infile Input file is assumed to contain motifs in the format output by bin/make_logodds and is their alphabet; -d or -stdin must be specified when this option is used. -bfile infile The random model uses the letter frequencies given in instead of the non-redundant database frequencies. The format of is the same as that for the MEME -bfile opton; see the MEME documentation for details. Sample files are given in directory tests: tests/nt.freq and tests/na.freq in the MEME distribution.) -smax integer [-1] Print results for no more than sequences (Any integer value) -stdin boolean [N] The default is to read the database specified inside . -text boolean [N] Default is hypertext (HTML) format -dna boolean [N] Translate DNA sequences to protein -comp boolean [N] The random model uses the letter frequencies in the current target sequence instead of the non-redundant database frequencies. This causes p-values and E-values to be compensated individually for the actual composition of each sequence in the database. This option can increase search time substantially due to the need to compute a different score distribution for each high-scoring sequence. -rank integer [-1] Print results starting with best (Any integer value) -best boolean [N] Include only the best motif in diagrams -remcorr boolean [N] Remove highly correlated motifs from query -brief boolean [N] Brief output: do not print documentation. -b boolean [N] Print only sections I and II -nostatus boolean [N] Do not print progress report -hitlist boolean [N] If you specify the -hitlist switch to MAST, the motif 'diagram' takes the form of a comma separated list of motif occurrences ('hits'). Each 'hit' has the format: where is the strand (+ or - for DNA, blank for protein), is the motif number, is the starting position of the hit, is the ending position of the hit, and is the position p-value of the hit. Advanced (Unprompted) qualifiers: -c integer [-1] Only use the first motifs (Any integer value) -sep boolean [N] Score reverse complement DNA strand as a separate sequence -norc boolean [N] Do not score reverse complement DNA strand -w boolean [N] Show weak matches (mt as motif file name. (Any string is accepted) -df string Print as database name. (Any string is accepted) -minseqs integer [-1] Lower bound on number of sequences in db (Any integer value) -mev float [-1] Use only motifs with E-values less than (Any numeric value) -m integer [-1] Overrides value set by using -mev. (Any integer value) -diag string See on-line documentation for a valid example. (Any string is accepted) Associated qualifiers: "-outfile" associated qualifiers -odirectory2 string Output directory General qualifiers: -auto boolean Turn off prompts -stdout boolean Write first file to standard output -filter boolean Read first file from standard input, write first file to standard output -options boolean Prompt for standard and additional values -debug boolean Write debug output to program.dbg -verbose boolean Report some/full command line options -help boolean Report command line options. More information on associated and general qualifiers can be found with -help -verbose -warning boolean Report warnings -error boolean Report errors -fatal boolean Report fatal errors -die boolean Report dying program messages

Standard (Mandatory) qualifiers Allowed values Default

[-mfile]
(Parameter 1) If -d <database> is not given, MAST looks for database specified inside of <mfile>. Input file Required

-ev Print results for sequences with E-value Any numeric value 10

-mt Show motif matches with p-value < mt Any numeric value 0.0001

[-outfile]
(Parameter 2) MAST program output file Output file <*>.emast

Additional (Optional) qualifiers Allowed values Default

-dfile If -d <database> is not given, MAST looks for database specified inside of <mfile>. Input file Required

-afile Input file <mfile> is assumed to contain motifs in the format output by bin/make_logodds and <a> is their alphabet; -d <database> or -stdin must be specified when this option is used. Input file Required

-bfile The random model uses the letter frequencies given in <bfile> instead of the non-redundant database frequencies. The format of <bfile> is the same as that for the MEME -bfile opton; see the MEME documentation for details. Sample files are given in directory tests: tests/nt.freq and tests/na.freq in the MEME distribution.) Input file Required

-smax Print results for no more than <smax> sequences Any integer value -1

-stdin The default is to read the database specified inside <mfile>. Boolean value Yes/No No

-text Default is hypertext (HTML) format Boolean value Yes/No No

-dna Translate DNA sequences to protein Boolean value Yes/No No

-comp The random model uses the letter frequencies in the current target sequence instead of the non-redundant database frequencies. This causes p-values and E-values to be compensated individually for the actual composition of each sequence in the database. This option can increase search time substantially due to the need to compute a different score distribution for each high-scoring sequence. Boolean value Yes/No No

-rank Print results starting with <rank> best Any integer value -1

-best Include only the best motif in diagrams Boolean value Yes/No No

-remcorr Remove highly correlated motifs from query Boolean value Yes/No No

-brief Brief output: do not print documentation. Boolean value Yes/No No

-b Print only sections I and II Boolean value Yes/No No

-nostatus Do not print progress report Boolean value Yes/No No

-hitlist If you specify the -hitlist switch to MAST, the motif 'diagram' takes the form of a comma separated list of motif occurrences ('hits'). Each 'hit' has the format: <strand><motif> <start> <end> <p-value> where <strand> is the strand (+ or - for DNA, blank for protein), <motif> is the motif number, <start> is the starting position of the hit, <end> is the ending position of the hit, and <p-value> is the position p-value of the hit. Boolean value Yes/No No

Advanced (Unprompted) qualifiers Allowed values Default

-c Only use the first <c> motifs Any integer value -1

-sep Score reverse complement DNA strand as a separate sequence Boolean value Yes/No No

-norc Do not score reverse complement DNA strand Boolean value Yes/No No

-w Show weak matches (mt<p-value<mt*10) in angle brackets Boolean value Yes/No No

-seqp The default is to use POSITION p-values. Boolean value Yes/No No

-mf Print <mf> as motif file name. Any string is accepted An empty string is accepted

-df Print <df> as database name. Any string is accepted An empty string is accepted

-minseqs Lower bound on number of sequences in db Any integer value -1

-mev Use only motifs with E-values less than <mev> Any numeric value -1

-m Overrides value set by using -mev. Any integer value -1

-diag See on-line documentation for a valid example. Any string is accepted An empty string is accepted

Standard (Mandatory) qualifiers	Allowed values	Default
[-mfile] (Parameter 1)	If -d <database> is not given, MAST looks for database specified inside of <mfile>.	Input file	Required
-ev	Print results for sequences with E-value	Any numeric value	10
-mt	Show motif matches with p-value < mt	Any numeric value	0.0001
[-outfile] (Parameter 2)	MAST program output file	Output file	<>*.emast
Additional (Optional) qualifiers	Allowed values	Default
-dfile	If -d <database> is not given, MAST looks for database specified inside of <mfile>.	Input file	Required
-afile	Input file <mfile> is assumed to contain motifs in the format output by bin/make_logodds and <a> is their alphabet; -d <database> or -stdin must be specified when this option is used.	Input file	Required
-bfile	The random model uses the letter frequencies given in <bfile> instead of the non-redundant database frequencies. The format of <bfile> is the same as that for the MEME -bfile opton; see the MEME documentation for details. Sample files are given in directory tests: tests/nt.freq and tests/na.freq in the MEME distribution.)	Input file	Required
-smax	Print results for no more than <smax> sequences	Any integer value	-1
-stdin	The default is to read the database specified inside <mfile>.	Boolean value Yes/No	No
-text	Default is hypertext (HTML) format	Boolean value Yes/No	No
-dna	Translate DNA sequences to protein	Boolean value Yes/No	No
-comp	The random model uses the letter frequencies in the current target sequence instead of the non-redundant database frequencies. This causes p-values and E-values to be compensated individually for the actual composition of each sequence in the database. This option can increase search time substantially due to the need to compute a different score distribution for each high-scoring sequence.	Boolean value Yes/No	No
-rank	Print results starting with <rank> best	Any integer value	-1
-best	Include only the best motif in diagrams	Boolean value Yes/No	No
-remcorr	Remove highly correlated motifs from query	Boolean value Yes/No	No
-brief	Brief output: do not print documentation.	Boolean value Yes/No	No
-b	Print only sections I and II	Boolean value Yes/No	No
-nostatus	Do not print progress report	Boolean value Yes/No	No
-hitlist	If you specify the -hitlist switch to MAST, the motif 'diagram' takes the form of a comma separated list of motif occurrences ('hits'). Each 'hit' has the format: <strand><motif> <start> <end> <p-value> where <strand> is the strand (+ or - for DNA, blank for protein), <motif> is the motif number, <start> is the starting position of the hit, <end> is the ending position of the hit, and <p-value> is the position p-value of the hit.	Boolean value Yes/No	No
Advanced (Unprompted) qualifiers	Allowed values	Default
-c	Only use the first <c> motifs	Any integer value	-1
-sep	Score reverse complement DNA strand as a separate sequence	Boolean value Yes/No	No
-norc	Do not score reverse complement DNA strand	Boolean value Yes/No	No
-w	Show weak matches (mt<p-value<mt*10) in angle brackets	Boolean value Yes/No	No
-seqp	The default is to use POSITION p-values.	Boolean value Yes/No	No
-mf	Print <mf> as motif file name.	Any string is accepted	An empty string is accepted
-df	Print <df> as database name.	Any string is accepted	An empty string is accepted
-minseqs	Lower bound on number of sequences in db	Any integer value	-1
-mev	Use only motifs with E-values less than <mev>	Any numeric value	-1
-m	Overrides value set by using -mev.	Any integer value	-1
-diag	See on-line documentation for a valid example.	Any string is accepted	An empty string is accepted

Input file format




Input files for usage example 
File: ex1.html

<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<HTML>
<HEAD>
<meta http-equiv="Content-Type" content="text/html; charset=ISO-8859-1">
<TITLE>MEME</TITLE>
<STYLE type="text/css">
  TD.invisible { color: '#D5F0FF'; }
  TD.c0 { background: aqua; color: black; }
  TD.cw0 { background: aqua; color: black; font: 50% sans-serif; }
  TD.c1 { background: blue; color: white; }
  TD.cw1 { background: blue; color: white; font: 50% sans-serif; }
  TD.c2 { background: red; color: white; }
  TD.cw2 { background: red; color: white; font: 50% sans-serif; }
  TD.c3 { background: fuchsia; color: black; }
  TD.cw3 { background: fuchsia; color: black; font: 50% sans-serif; }
  TD.c4 { background: yellow; color: black; }
  TD.cw4 { background: yellow; color: black; font: 50% sans-serif; }
  TD.c5 { background: lime; color: black; }
  TD.cw5 { background: lime; color: black; font: 50% sans-serif; }
  TD.c6 { background: teal; color: white; }
  TD.cw6 { background: teal; color: white; font: 50% sans-serif; }
  TD.c7 { background: #444444; color: white; }
  TD.cw7 { background: #444444; color: white; font: 50% sans-serif; }
  TD.c8 { background: green; color: white; }
  TD.cw8 { background: green; color: white; font: 50% sans-serif; }
  TD.c9 { background: silver; color: black; }
  TD.cw9 { background: silver; color: black; font: 50% sans-serif; }
  TD.c10 { background: purple; color: white; }
  TD.cw10 { background: purple; color: white; font: 50% sans-serif; }
  TD.c11 { background: olive; color: black; }
  TD.cw11 { background: olive; color: black; font: 50% sans-serif; }
  TD.c12 { background: navy; color: white; }
  TD.cw12 { background: navy; color: white; font: 50% sans-serif; }
  TD.c13 { background: maroon; color: white; }
  TD.cw13 { background: maroon; color: white; font: 50% sans-serif; }
  TD.c14 { background: black; color: white; }
  TD.cw14 { background: black; color: white; font: 50% sans-serif; }
  TD.c15 { background: white; color: black; }
  TD.cw15 { background: white; color: black; font: 50% sans-serif; }
  B.red { color: red; }
  TD.red { color: red; }
  TH.red { color: red; }
  B.blue { color: blue; }
  TD.blue { color: blue; }
  TH.blue { color: blue; }
  B.orange { color: orange; }
  TD.orange { color: orange; }
  TH.orange { color: orange; }
  B.green { color: green; }
  TD.green { color: green; }


  [Part of this file has been deleted for brevity]

for use by database search programs such as MAST.  This matrix is a
log-odds matrix calculated
by taking the log (base 2) of the ratio <TT>p/f</TT> at each position in
the motif where <TT>p</TT> is the probability of a particular letter at that
position in the motif, and <TT>f</TT> is the background frequency of the
letter (given in the <A HREF=#command_doc>command line summary</A> section.)
Each entry in the matrix is multiplied by 100 and rounded to the nearest
integer before printing.
This is the same matrix that is used above in computing the <I>p</I>-values
of the occurrences of the motif in the <A HREF=#sites_doc2>Occurrences of the
Motif</A> and <A HREF=#diagrams_doc2>Block Diagrams of Motif Occurrences</A>
sections.

The scoring matrix is printed "sideways"--columns
correspond to the letters in the alphabet (in the same order as shown in
the simplified motif) and rows corresponding to the positions of the motif,
position one first.  The scoring matrix is preceded by a line starting with
"log-odds matrix:" and containing the length of the alphabet, width
of the motif, number of characters in the training set and a scoring 
threshold.

<P>
<LI> <A NAME=pspm_doc2 HREF=#pspm1><H4>
Position-Specific Probability Matrix</H4></A>

The motif itself is a position-specific probability matrix giving,
for each position in the pattern, the observed frequency 
("probability") of each possible letter.  
The probability matrix is printed "sideways"--columns
correspond to the letters in the alphabet (in the same order as shown in
the simplified motif) and rows corresponding to the positions of the motif,
position one first.
The motif is preceded by a line starting with
"letter-probability matrix:" and containing the length of the alphabet, width
of the motif, number of occurrences of the motif, and the E-value of the
motif.
<p>
<b>Note:</b> Earlier versions
of MEME gave the posterior probabilities--the probability after applying
a prior on letter frequencies--rather than the observed frequencies.
These versions of MEME also gave the number of <I>possible</I>
positions for the motif rather than the actual number of occurrences.
The output from these earlier versions of MEME can be distinguished
by "n=" rather than "nsites=" in the line preceding the matrix.

</UL>
<HR><TABLE SUMMARY='buttons' ALIGN=LEFT CELLSPACING=0><TR>
  <TD BGCOLOR='#DDDDFF'><A HREF="#top_buttons"><B>Go to top</B></A></TABLE><BR>
</FORM>
</BODY>
</HTML>

MOTIF FORMAT

MAST can search using (multiple) motifs contained in

a MEME output file,
a GCG profile file,
two or more GCG profile filess concatenated together, or
a file with the following format.

Motif file format

  
       ALPHABET= alphabet
       log-odds matrix: alength= alength w= w
       row_1
       row_2
       ...
       row_w

A motif is represented by a position-dependent scoring matrix.

A scoring matrix is preceded by a line starting with the words log-odds matrix: and specifying alength, the length of the alphabet (number of columns in the scoring matrix), and the w, the width of the motif (number of rows in the scoring matrix).

The following w lines (no blank lines allowed) contain the rows of the scoring matrix. Row i, column j of the matrix gives the score for the j-th letter in alphabet appearing at position i in an occurrence of the motif.

The spaces after the equals signs and the colon are required.

The number of letters in alphabet must equal alength.

Any number of additional motifs may follow the first one.

The motif file must contain a line starting with

              ALPHABET=

followed by alphabet, a list containing the letters used in the motifs.

The order of the letters in alphabet must be the same as the order of the columns of scores in the motifs. The order need not be alphabetical and case does not matter, but there should be no spaces in alphabet.

The letters in alphabet must be a subset of either the IUB/IUPAC DNA (ABCDGHKMNRSTUVWY) or protein (ABCDEFGHIKLMNPQRSTUVWXYZ) alphabets. DNA alphabets must contain at least the letters ACGT. Protein alphabets must contain at least the letters ACDEFGHIKLMNPQRSTVWY. All other letters in the alphabets are optional. If any of the optional letters are missing from alphabet, MAST automatically generates scores for them by taking the weighted average of the scores for the letters which the missing letter could match. (The weights are the frequencies of the replaced letters in the appropriate non-redundant database.) Replacements for the optional letters are given in the following table.

LETTERS MATCHED BY OPTIONAL LETTERS

      =================================================
      optional          matches 
      letter      DNA             protein 
      =================================================
       B          CGT             DN 
       D          AGT
       H          ACT
       K          GT
       M          AC
       N          ACGT
       R          AG
       S          CG
       U          T               ACDEFGHIKLMNPQRSTVWY 
       V          CAG
       W          AT
       X                          ACDEFGHIKLMNPQRSTVWY 
       Y          CT
       Z                          EQ 
       *          ACGT            ACDEFGHIKLMNPQRSTVWY
       -          ACGT            ACDEFGHIKLMNPQRSTVWY
      =================================================

EXAMPLE

Here is an example of a DNA motif file that contains two motifs.

Sample motif file

  
          ALPHABET= ACGT
          log-odds matrix: alength= 4 w= 9
           -4.275  -0.182  -4.195   1.408
           -4.296  -1.487   1.880  -0.816
           -2.160  -1.492  -4.171   1.474
           -0.810  -4.076   1.872  -2.164
            1.537  -1.487  -4.195  -4.205
            0.113   0.340  -0.237  -0.209
           -0.454   0.923   0.390  -0.834
           -1.336  -0.082   0.905   0.100
            0.674  -4.183   0.130  -0.201
          log-odds matrix: alength= 4 w= 6
           -2.032   0.324   1.371  -0.781
           -0.409   0.560  -0.250   0.119
           -4.274  -0.519  -0.260   1.167
           -2.188   2.300  -4.191  -2.465
            1.265  -4.111  -0.267  -2.180
           -1.977   2.158  -1.661  -2.071

In the example above, because the order of the letters in alphabet is ACGT, the first column of each motif gives the scores for the letter A at each position in the motif, the second column gives the scores for C and so forth.

Note: If -d is not given, MAST looks for database specified inside of < mfile >

Creates file (unless [-stdout] given) after stripping ".html" from the end of < mfile >:

mast.< mfile >[.< database >][.c< count >][.m< motif >]+[.rank< rank >][.ev< ev >][.mt< mt >][.b]

Output file format

Output files for usage example

File: ex1.out

<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<HTML>
<HEAD>
<meta http-equiv="Content-Type" content="text/html; charset=ISO-8859-1">
<TITLE>MAST</TITLE>
<STYLE type="text/css">
  TD.invisible { color: '#D5F0FF'; }
  TD.c0 { background: aqua; color: black; }
  TD.cw0 { background: aqua; color: black; font: 50% sans-serif; }
  TD.c1 { background: blue; color: white; }
  TD.cw1 { background: blue; color: white; font: 50% sans-serif; }
  TD.c2 { background: red; color: white; }
  TD.cw2 { background: red; color: white; font: 50% sans-serif; }
  TD.c3 { background: fuchsia; color: black; }
  TD.cw3 { background: fuchsia; color: black; font: 50% sans-serif; }
  TD.c4 { background: yellow; color: black; }
  TD.cw4 { background: yellow; color: black; font: 50% sans-serif; }
  TD.c5 { background: lime; color: black; }
  TD.cw5 { background: lime; color: black; font: 50% sans-serif; }
  TD.c6 { background: teal; color: white; }
  TD.cw6 { background: teal; color: white; font: 50% sans-serif; }
  TD.c7 { background: #444444; color: white; }
  TD.cw7 { background: #444444; color: white; font: 50% sans-serif; }
  TD.c8 { background: green; color: white; }
  TD.cw8 { background: green; color: white; font: 50% sans-serif; }
  TD.c9 { background: silver; color: black; }
  TD.cw9 { background: silver; color: black; font: 50% sans-serif; }
  TD.c10 { background: purple; color: white; }
  TD.cw10 { background: purple; color: white; font: 50% sans-serif; }
  TD.c11 { background: olive; color: black; }
  TD.cw11 { background: olive; color: black; font: 50% sans-serif; }
  TD.c12 { background: navy; color: white; }
  TD.cw12 { background: navy; color: white; font: 50% sans-serif; }
  TD.c13 { background: maroon; color: white; }
  TD.cw13 { background: maroon; color: white; font: 50% sans-serif; }
  TD.c14 { background: black; color: white; }
  TD.cw14 { background: black; color: white; font: 50% sans-serif; }
  TD.c15 { background: white; color: black; }
  TD.cw15 { background: white; color: black; font: 50% sans-serif; }
  B.red { color: red; }
  TD.red { color: red; }
  TH.red { color: red; }
  B.blue { color: blue; }
  TD.blue { color: blue; }
  TH.blue { color: blue; }
  B.orange { color: orange; }
  TD.orange { color: orange; }
  TH.orange { color: orange; }
  B.green { color: green; }
  TD.green { color: green; }


  [Part of this file has been deleted for brevity]


<HR>
<A NAME=a17></A>ilv <TABLE SUMMARY='buttons' ALIGN=LEFT CELLSPACING=0><TR>
  <TD BGCOLOR='#DDDD88'><A HREF='#s17'>S</A>
  <TD BGCOLOR='#DDFFDD'><A HREF='#d17'>D</A>
  <TD BGCOLOR='#FFFFFF'><A HREF='#bh'>?</A></TABLE><BR CLEAR=LEFT>
  <BR>
  LENGTH = 105  COMBINED P-VALUE = 6.93e-02  E-VALUE =      1.2<BR>
  DIAGRAM: 105<PRE>


</PRE>

<HR>
<A NAME=a18></A>trn9cat <TABLE SUMMARY='buttons' ALIGN=LEFT CELLSPACING=0><TR>
  <TD BGCOLOR='#DDDD88'><A HREF='#s18'>S</A>
  <TD BGCOLOR='#DDFFDD'><A HREF='#d18'>D</A>
  <TD BGCOLOR='#FFFFFF'><A HREF='#bh'>?</A></TABLE><BR CLEAR=LEFT>
  <BR>
  LENGTH = 105  COMBINED P-VALUE = 2.42e-01  E-VALUE =      4.4<BR>
  DIAGRAM: 105<PRE></PRE>

<A NAME=debug></A><HR><CENTER><H3>Debugging Information</H3></CENTER><HR>
<PRE>


CPU: emboss6.ebi.ac.uk
Time 0.001999 secs.

mast ../../data/memenew/ex1.html -ev 10.000000 -mt 0.000100
</PRE>
<A NAME=bh></A>
<A NAME=sbh></A>
<A NAME=dbh></A>
<A NAME=abh></A>
<HR><CENTER><H3>Button Help</H3></CENTER><HR>
<TABLE SUMMARY='buttons' ALIGN=LEFT CELLSPACING=0><TR>
  <TD BGCOLOR='#DDDDFF'><A HREF='#bh'>E</A></TABLE>Links to Entrez database at <A HREF='http://www.ncbi.nlm.nih.gov'>NCBI</A> <BR CLEAR=LEFT>
<TABLE SUMMARY='buttons' ALIGN=LEFT CELLSPACING=0><TR>
  <TD BGCOLOR='#DDDD88'><A HREF='#sbh'>S</A></TABLE>Links to sequence scores (<A HREF='#sec_i'>section I</A>) <BR CLEAR=LEFT>
<TABLE SUMMARY='buttons' ALIGN=LEFT CELLSPACING=0><TR>
  <TD BGCOLOR='#DDFFDD'><A HREF='#dbh'>D</A></TABLE>Links to motif diagrams (<A HREF='#sec_ii'>section II</A>) <BR CLEAR=LEFT>
<TABLE SUMMARY='buttons' ALIGN=LEFT CELLSPACING=0><TR>
  <TD BGCOLOR='#FFDDDD'><A HREF='#abh'>A</A></TABLE>Links to sequence/motif annotated alignments (<A HREF='#sec_iii'>section III</A>) <BR CLEAR=LEFT>
<TABLE SUMMARY='buttons' ALIGN=LEFT CELLSPACING=0><TR>
  <TD BGCOLOR='#FFFFFF'><A HREF='#bh'>?</A></TABLE>This information <BR CLEAR=LEFT>

<HR><TABLE SUMMARY='buttons' ALIGN=LEFT CELLSPACING=0><TR>
  <TD BGCOLOR='#DDDDFF'><A HREF='#top_buttons'><B>Go to top</B></A></TABLE><BR>
</BODY>
</HTML>

File: crp0.s

>ce1cg
TAATGTTTGTGCTGGTTTTTGTGGCATCGGGCGAGAATAGCGCGTGGTGTGAAAGACTGTTTTTTTGATCGTTTTCACAA
AAATGGAAGTCCACAGTCTTGACAG
>ara
GACAAAAACGCGTAACAAAAGTGTCTATAATCACGGCAGAAAAGTCCACATTGATTATTTGCACGGCGTCACACTTTGCT
ATGCCATAGCATTTTTATCCATAAG
>bglr1
ACAAATCCCAATAACTTAATTATTGGGATTTGTTATATATAACTTTATAAATTCCTAAAATTACACAAAGTTAATAACTG
TGAGCATGGTCATATTTTTATCAAT
>crp
CACAAAGCGAAAGCTATGCTAAAACAGTCAGGATGCTACAGTAATACATTGATGTACTGCATGTATGCAAAGGACGTCAC
ATTACCGTGCAGTACAGTTGATAGC
>cya
ACGGTGCTACACTTGTATGTAGCGCATCTTTCTTTACGGTCAATCAGCAAGGTGTTAAATTGATCACGTTTTAGACCATT
TTTTCGTCGTGAAACTAAAAAAACC
>deop2
AGTGAATTATTTGAACCAGATCGCATTACAGTGATGCAAACTTGTAAGTAGATTTCCTTAATTGTGATGTGTATCGAAGT
GTGTTGCGGAGTAGATGTTAGAATA
>gale
GCGCATAAAAAACGGCTAAATTCTTGTGTAAACGATTCCACTAATTTATTCCATGTCACACTTTTCGCATCTTTGTTATG
CTATGGTTATTTCATACCATAAGCC
>ilv
GCTCCGGCGGGGTTTTTTGTTATCTGCAATTCAGTACAAAACGTGATCAACCCCTCAATTTTCCCTTTGCTGAAAAATTT
TCCATTGTCTCCCCTGTAAAGCTGT
>lac
AACGCAATTAATGTGAGTTAGCTCACTCATTAGGCACCCCAGGCTTTACACTTTATGCTTCCGGCTCGTATGTTGTGTGG
AATTGTGAGCGGATAACAATTTCAC
>male
ACATTACCGCCAATTCTGTAACAGAGATCACACAAAGCGACGGTGGGGCGTAGGGGCAAGGAGGATGGAAAGAGGTTGCC
GTATAAAGAAACTAGAGTCCGTTTA
>malk
GGAGGAGGCGGGAGGATGAGAACACGGCTTCTGTGAACTAAACCGAGGTCATGTAAGGAATTTCGTGATGTTGCTTGCAA
AAATCGTGGCGATTTTATGTGCGCA
>malt
GATCAGCGTCGTTTTAGGTGAGTTGTTAATAAAGATTTGGAATTGTGACACAGTGCAAATTCAGACACATAAAAAAACGT
CATCGCTTGCATTAGAAAGGTTTCT
>ompa
GCTGACAAAAAAGATTAAACATACCTTATACAAGACTTTTTTTTCATATGCCTGACGGAGTTCACACTTGTAAGTTTTCA
ACTACGTTGTAGACTTTACATCGCC
>tnaa
TTTTTTAAACATTAAAATTCTTACGTAATTTATAATCTTTAAAAAAAGCATTTAATATTGCTCCCCGAACGATTGTGATT
CGATTCACATTTAAACAATTTCAGA
>uxu1
CCCATGAGAGTGAAATTGTTGTGATGTGGTTAACCCAATTAGAATTCGGGATTGACATGTCTTACCAAAAGGTAGAACTT
ATACGCCATCTCATCCGATGCAAGC
>pbr322
CTGGCTTAACTATGCGGCATCAGAGCAGATTGTACTGAGAGTGCACCATATGCGGTGTGAAATACCGCACAGATGCGTAA
GGAGAAAATACCGCATCAGGCGCTC
>trn9cat
CTGTGACGGAAGATCACTTCGCAGAATAAATAAATCCTGGTGTCCCTGTTGATACCGGGAAGCCCTGGGCCAACTTTTGG
CGAAAATGAGACGTTGATCGGCACG
>tdc
GATTTTTATACTTTAACTTGTTGATATTTAAAGGTATTTAATTGTAATAACGATACTCTGGAAAGTATTGAAAGTTAATT
TGTGAGTGGTCGCACATATCCTGTT

MAST outputs a file containing:

* the version of MAST and the date it was built,
* the reference to cite if you use MAST in your research,
* a description of the database and motifs used in the search,
* an explanation of the results,
* high-scoring sequences--sequences matching the group of motifs above a stated level of statistical significance,
* motif diagrams showing the order and spacing of occurrences of the motifs in the high-scoring sequences and
* annotated sequences showing the positions and p-values of all motif occurrences in each of the high-scoring sequences.

Each section of the results file contains an explanation of how to interpret them.

Match Scores

The match score of a motif to a position in a sequence is the sum of the score from each column of the position-dependent scoring matrix corresponding to the letter at that position in the sequence. For example, if the sequence is

  
  TAATGTTGGTGCTGGTTTTTGTGGCATCGGGCGAGAATAGCGC
     ========

and the motif is represented by the position-dependent scoring matrix (where each row of the matrix corresponds to a position in the motif)

  
  =========|=================================
  POSITION |   A        C        G        T
  =========|=================================
    1      | 1.447    0.188   -4.025   -4.095 
    2      | 0.739    1.339   -3.945   -2.325 
    3      | 1.764   -3.562   -4.197   -3.895 
    4      | 1.574   -3.784   -1.594   -1.994 
    5      | 1.602   -3.935   -4.054   -1.370 
    6      | 0.797   -3.647   -0.814    0.215 
    7      |-1.280    1.873   -0.607   -1.933 
    8      |-3.076    1.035    1.414   -3.913 
  =========|=================================

then the match score of the fourth position in the sequence (underlined) would be found by summing the score for T in position 1, G in position 2 and so on until G in position 8. So the match score would be

    score = -4.095 + -3.945 + -3.895 + -1.994
            + -4.054 + -0.814 + -1.933 + 1.414 
          = -19.316

The match scores for other positions in the sequence are calculated in the same way. Match scores are only calculated if the match completely fits within the sequence. Match scores are not calculated if the motif would overhang either end of the sequence.

P-values

MAST reports all matches of a sequence to a motif or group of motifs in terms of the p-value of the match. MAST considers the p-values of four types of events:

position p-value: the match of a single position within a sequence to a given motif,
sequence p-value: the best match of any position within a sequence to a given motif,
combined p-value: the combined best matches of a sequence to a group of motifs, and
E-value: observing a combined p-value at least as small in a random database of the same size.

All p-values are based on a random sequence model that assumes each position in a random sequence is generated according to the average letter frequencies of all sequences in the the appropriate (peptide or nucleotide) non-redundant database (ftp://ncbi.nlm.nih.gov/blast/db/) on September 22, 1996. This can be overridden in two ways:

1) -bfile < bfile >

The random model uses the letter frequencies given in < bfile > instead of the non-redundant database frequencies. The format of < bfile > is the same as that for the MEME -bfile opton; see the MEME documentation for details. Sample files are given in directory tests: tests/nt.freq and tests/na.freq.)

2) -comp

The random model uses the letter frequencies in the current target sequence instead of the non-redundant database frequencies. This causes p-values and E-values to be compensated individually for the actual composition of each sequence in the database. This option can increase search time substantially due to the need to compute a different score distribution for each high-scoring sequence.

Position p-value

The p-value of a match of a given position within a sequence to a motif is defined as the probability of a randomly selected position in a randomly generated sequence having a match score at least as large as that of the given position.

Sequence p-value

The p-value of a match of a sequence to a motif is defined as the probability of a randomly generated sequence of the same length having a match score at least as large as the largest match score of any position in the sequence.

Combined p-value

The p-value of a match of a sequence to a group of motifs is defined as the probability of a randomly generated sequence of the same length having sequence p-values whose product is at least as small as the product of the sequence p-values of the matches of the motifs to the given sequence.

E-value

The E-value of the match of a sequence in a database to a a group of motifs is defined as the expected number of sequences in a random database of the same size that would match the motifs as well as the sequence does and is equal to the combined p-value of the sequence times the number of sequences in the database.

High-scoring Sequences

MAST lists the names and part of the descriptive text of all sequences whose E-value is less than E. Sequences shorter than one or more of the motifs are skipped. The sequences are sorted by increasing E-value. The value of E is set to 10 for the WEB server but is user-selectable in the down-loadable version of MAST.

Motif Diagrams

Motif diagrams show the order and spacing of non-overlapping matches to the motifs in each high-scoring sequence. Motif occurrences are determined based on the position p-value of matches to the motif. Strong matches (p-value < M) are shown in square brackets (`[ ]'), weak matches (M < p-value < M × 10) are shown in angle brackets (`< >') and the length of non-motif sequence ("spacer") is shown between dashes (`-'). For example,

  
          27-[3]-44-< 4 >-99-[1]-7

shows an initial spacer of length 27, followed by a strong match to motif 3, a spacer of length 44, a weak match to motif 4, a spacer of length 99, a strong match to motif 1 and a final non-motif sequence of length 7. The value of M is 0.0001 for the WEB server but is user-selectable in the down-loadable version of MAST.

Note: If you specify the -hit_list switch to MAST, the motif "diagram" takes the form of a comma separated list of motif occurrences ("hits"). Each "hit" has the format: < strand >< motif > < start > < end > < p-value > where

< strand > is the strand (+ or - for DNA, blank for protein),
< motif > is the motif number,
< start > is the starting position of the hit,
< end > is the ending position of the hit, and
< p-value > is the position p-value of the hit.

Annotated Sequences

MAST annotates each high-scoring sequence by printing the sequence along with the position and strength of all the non-overlapping motif occurrences. The four lines above each motif occurrence contain, respectively,

the motif number of the occurrence,
the position p-value of the occurence,
the best possible match to the motif, and
a plus sign (`+') above each letter in the occurrence that has a positive
match score to the motif.

The best possible match to a motif is the sequence of letters which would acheive the highest match score.

Data files

None.

Notes

1. Command-line arguments

The following original MEME options are not supported:

-stdout       : The output is always written to file.
-hit_list     : Use -hitlist instead.

The following additional options are provided:

outfile       : Application output that was normally written to stdout.

2. Installing EMBASSY MEME

The EMBASSY MEME package contains "wrapper" applications providing an EMBOSS-style interface to the applications in the original MEME package version 3.0.14 developed by Timothy L. Bailey. Please read the file README in the EMBASSY MEME package distribution for installation instructions.

3. Installing original MEME

To use EMBASSY MEME, you will first need to download and install the original MEME package:

WWW home:       http://meme.sdsc.edu/meme/
Distribution:   http://meme.nbcr.net/downloads/old_versions/

Please read the file README in the the original MEME package distribution for installation instructions.

4. Setting up MEME

For the EMBASSY MEME package to work, the directory containing the original MEME executables *must* be in your path. For example if you executables were installed to "/usr/local/meme/bin", then type:

set path=(/usr/local/meme/bin/ $path)
rehash

5. Getting help

Once you have installed the original MEME, type

meme > meme.txt 
mast > mast.txt

to retrieve the meme and mast documentation into text files. The same documentation is given here and in the ememe documentation.

Please read the 'Notes' section below for a description of the differences between the original and EMBASSY MEME, particularly which application command line options are supported.

References

(MEME) Timothy L. Bailey and Charles Elkan, "Fitting a mixture model by expectation maximization to discover motifs in biopolymers", Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology, pp. 28-36, AAAI Press, Menlo Park, California, 1994.

(MAST) Timothy L. Bailey and Michael Gribskov, "Combining evidence using p-values: application to sequence homology searches", Bioinformatics, Vol. 14, pp. 48-54, 1998.

Warnings

Diagnostic Error Messages

None.

Exit status

It always exits with status 0.

Known bugs

None.

Program name	Description
antigenic	Finds antigenic sites in proteins
digest	Reports on protein proteolytic enzyme or reagent cleavage sites
echlorop	Reports presence of chloroplast transit peptides
eiprscan	Motif detection
elipop	Prediction of lipoproteins
ememe	Multiple EM for Motif Elicitation
ememetext	Multiple EM for Motif Elicitation. Text file only
enetnglyc	Reports N-glycosylation sites in human proteins
enetoglyc	Reports mucin type GalNAc O-glycosylation sites in mammalian proteins
enetphos	Reports ser, thr and tyr phosphorylation sites in eukaryotic proteins
epestfind	Finds PEST motifs as potential proteolytic cleavage sites
eprop	Reports propeptide cleavage sites in proteins
esignalp	Reports protein signal cleavage sites
etmhmm	Reports transmembrane helices
eyinoyang	Reports O-(beta)-GlcNAc attachment sites
fuzzpro	Search for patterns in protein sequences
fuzztran	Search for patterns in protein sequences (translated)
helixturnhelix	Identify nucleic acid-binding motifs in protein sequences
oddcomp	Identify proteins with specified sequence word composition
omeme	Motif detection
patmatdb	Searches protein sequences with a sequence motif
patmatmotifs	Scan a protein sequence with motifs from the PROSITE database
pepcoil	Predicts coiled coil regions in protein sequences
preg	Regular expression search of protein sequence(s)
pscan	Scans protein sequence(s) with fingerprints from the PRINTS database
sigcleave	Reports on signal cleavage sites in a protein sequence

Author(s)

This program is an EMBOSS conversion of a program written by Sean Eddy as part of his HMMER package.

Although we take every care to ensure that the results of the EMBOSS version are identical to those from the original package, we recommend that you check your inputs give the same results in both versions before publication.

Please report all bugs in the EMBOSS version to the EMBOSS bug team, not to the original author. Jon Ison (jison © ebi.ac.uk)
European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK

This program is an EMBASSY wrapper to a program written by Timothy L. Bailey as part of his meme package.

Please report any bugs to the EMBOSS bug team in the first instance, not to Timothy L. Bailey.

History

None.

Target users

This program is intended to be used by everyone and everything, from naive users to embedded scripts.

Wiki

Function

Description

Algorithm

Usage

EXAMPLES:

Command line arguments

Input file format

Input files for usage example

File: ex1.html

MOTIF FORMAT

Motif file format

LETTERS MATCHED BY OPTIONAL LETTERS

EXAMPLE

Here is an example of a DNA motif file that contains two motifs.

Sample motif file

Output file format

Output files for usage example

File: ex1.out

File: crp0.s

Match Scores

P-values

1) -bfile < bfile >

2) -comp

Position p-value

Sequence p-value

Combined p-value

E-value

High-scoring Sequences

Motif Diagrams

Annotated Sequences

Data files

Notes

1. Command-line arguments

2. Installing EMBASSY MEME

3. Installing original MEME

4. Setting up MEME

5. Getting help

References

Warnings

Diagnostic Error Messages

Exit status

Known bugs

See also

Author(s)

History

Target users