emast



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   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 crp0.s
Motif detection
Print results for sequences with E-value [10]:
Show motif matches with p-value < mt [0.0001]:
MAST program output directory [mast_out]:
Writing results to output directory 'mast_out/'.



   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.

Motif detection
Version: EMBOSS:6.6.0.0

   Standard (Mandatory) qualifiers:
  [-mfile]             infile     If -d  is not given, MAST looks
                                  for database specified inside of .
  [-sfile]             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)
  [-outdirname]        outdir     [mast_out] MAST program output directory

   Additional (Optional) qualifiers:
   -dblist             boolean    [N] If provided, -sfile is a list of files
   -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.)
   -stdin              boolean    [N] The default is to read the database
                                  specified inside .
   -[no]text           boolean    [Y] Default is text, HTML and XML
   -[no]html           boolean    [Y] Default is text, HTML and XML
   -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.
   -best               boolean    [N] Include only the best motif in diagrams
   -remcorr            boolean    [N] Remove highly correlated motifs from
                                  query
   -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
   -weak               boolean    [N] Show weak matches (mt as motif file name.
(Any string)
   -df                 string     Print  as database name. (Any string)
   -dl                 string     Print

   as link to search sequence names. (Any string) -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) -[no]overwrite boolean [Y] The
          default is to overwrite existing files Associated qualifiers:
          "-outdirname" associated qualifiers -extension3 string Default
          file extension 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 and exit. 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 -version boolean Report
          version number and exit

Input file format





Input files for usage example

File: ex1.html


<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.or
g/TR/html4/loose.dtd">
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>MEME</title>
<style type="text/css">

    /* START INCLUDED FILE "meme.css" */
        /* The following is the content of meme.css */
        body { background-color:white; font-size: 12px; font-family: Verdana, Ar
ial, Helvetica, sans-serif;}

        div.help {
          display: inline-block;
          margin: 0px;
          padding: 0px;
          width: 12px;
          height: 13px;
          cursor: pointer;
          background-image: url("help.gif");
          background-image: url("data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA
AwAAAANAQMAAACn5x0BAAAAAXNSR0IArs4c6QAAAAZQTFRFAAAAnp6eqp814gAAAAF0Uk5TAEDm2GYAA
AABYktHRACIBR1IAAAACXBIWXMAAAsTAAALEwEAmpwYAAAAB3RJTUUH2gMJBQgGYqhNZQAAACZJREFUC
Ndj+P+BoUGAoV+AYeYEEGoWYGgTYGgRAAm2gRGQ8f8DAOnhC2lYnqs6AAAAAElFTkSuQmCC");
        }

        div.help2 {
          color: #999;
          display: inline-block;
          width: 12px;
          height: 12px;
          border: 1px solid #999;
          font-size: 13px;
          line-height:12px;
          font-family: Helvetica, sans-serif;
          font-weight: bold;
          font-style: normal;
          cursor: pointer;
        }
        div.help2:hover {
          color: #000;
          border-color: #000;
        }

        p.spaced { line-height: 1.8em;}

        span.citation { font-family: "Book Antiqua", "Palatino Linotype", serif;
 color: #004a4d;}

        p.pad { padding-left: 30px; padding-top: 5px; padding-bottom: 10px;}

        td.jump { font-size: 13px; color: #ffffff; background-color: #00666a;
          font-family: Georgia, "Times New Roman", Times, serif;}

        a.jump { margin: 15px 0 0; font-style: normal; font-variant: small-caps;


  [Part of this file has been deleted for brevity]

              For use with <a href="http://blocks.fhcrc.org/blocks">BLOCKS tools
</a>.
            </dd>
<dt>
<a name="format_FASTA_doc"></a>FASTA Format</dt>
<dd>
              The FASTA format as described <a href="http://meme.nbcr.net/meme/d
oc/fasta-format.html">here</a>.
            </dd>
<dt>
<a name="format_raw_doc"></a>Raw Format</dt>
<dd>
              Just the sites of the sequences that contributed to the motif. One
 site per line.
            </dd>
</dl>
</div>
<a name="sites_doc"></a><h5 class="doc">Sites</h5>
<div class="doc"><p>
            MEME displays the occurrences (sites) of the motif in the training s
et. The sites are shown aligned with each other, and the ten sequence
            positions preceding and following each site are also shown. Each sit
e is identified by the name of the sequence where it occurs,
            the strand (if both strands of DNA sequences are being used), and th
e position in the sequence where the site begins.  When the DNA strand
            is specified, '+' means the sequence in the training set, and '-' me
ans the reverse complement of the training set sequence.
            (For '-' strands, the 'start' position is actually the position on t
he <b>positive</b> strand where the site ends.) The sites are <b>listed
              in order of increasing statistical significance</b> (<i>p</i>-valu
e).  The <i>p</i>-value of a site is computed from the the match score of
            the site with the <a href="#format_PSSM_doc">position specific scori
ng matrix</a> for the motif. The <i>p</i>-value gives the probability of a
            random string (generated from the background letter frequencies) hav
ing the same match score or higher. (This is referred to as the
            <b>position <i>p</i>-value</b> by the MAST algorithm.)
          </p></div>
<a name="diagrams_doc"></a><h5 class="doc">Block Diagrams</h5>
<div class="doc"><p>
            The occurrences of the motif in the training set sequences are shown
 as coloured blocks on a line. One diagram is printed for each
            sequence showing all the sites contributating to that motif in that
sequence. The sequences are <b>listed in the same order as in the input</b>
            to make it easier to compare multiple block diagrams. Additionally t
he best <i>p</i>-value for the sequence/motif combination is
            listed though this may not be in ascending order as with the sites.
The <i>p</i>-value of an occurrence is the probability of a single
            random subsequence the length of the motif, generated according to t
he 0-order background model, having a score at least as high as
            the score of the occurrence. When the DNA strand is specified '+', i
t means the motif appears from left to right on the sequence, and '-'
            means the motif appears from right to left on the complementary stra
nd. A sequence position scale is shown at the end of each table of
            block diagrams.
          </p></div>
<a name="combined_doc"></a><h5>Combined Block Diagrams</h5>
<div class="doc">
<p>
            The motif occurrences shown in the motif summary <b>may not be exact
ly the same as those reported in each motif section</b> because
            only motifs with a position <em>p</em>-value of 0.0001 that don't ov
erlap other, more significant motif occurrences are shown.
          </p>
<p>
            See the documentation for <a href="http://meme.nbcr.net/meme/mast-ou
tput.html">MAST output</a> for the definition of position and
            combined <em>p</em>-values.
          </p>
</div>
</div></span><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br
><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br
><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><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: 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

Directory: mast_out

          This directory contains output files, for example mast.txt
          mast.html and mast.xml.

File: mast_out/mast.txt

********************************************************************************
MAST - Motif Alignment and Search Tool
********************************************************************************
        MAST version 4.7.0 (Release date: Wed Sep 28 17:30:10 EST 2011)

        For further information on how to interpret these results or to get
        a copy of the MAST software please access http://meme.nbcr.net.
********************************************************************************


********************************************************************************
REFERENCE
********************************************************************************
        If you use this program in your research, please cite:

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


********************************************************************************
DATABASE AND MOTIFS
********************************************************************************
        DATABASE ./crp0.s (nucleotide)
        Last updated on Mon Jul 15 19:00:07 2013
        Database contains 18 sequences, 1890 residues

        Scores for positive and reverse complement strands are combined.

        MOTIFS ../../data/memenew/ex1.html (nucleotide)
        MOTIF WIDTH BEST POSSIBLE MATCH
        ----- ----- -------------------
          1    15   TGTGAACGAGCTCAC

        Random model letter frequencies (from non-redundant database):
        A 0.274 C 0.225 G 0.225 T 0.274
********************************************************************************


********************************************************************************
SECTION I: HIGH-SCORING SEQUENCES
********************************************************************************
        - Each of the following 18 sequences has E-value less than 10.
        - The E-value of a sequence is 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.
        - The combined p-value of a sequence measures the strength of the
          match of the sequence to all the motifs and is calculated by


  [Part of this file has been deleted for brevity]


  LENGTH = 105  COMBINED P-VALUE = 1.09e-02  E-VALUE =      0.2
  DIAGRAM: 65_[+1]_25

                                                                      [+1]
                                                                      6.0e-05
                                                                      TGTGAACGAG
                                                                      ++  ++++++
1    CACAAAGCGAAAGCTATGCTAAAACAGTCAGGATGCTACAGTAATACATTGATGTACTGCATGTATGCAAAGGAC



     CTCAC
      ++++
76   GTCACATTACCGTGCAGTACAGTTGATAGC


bglr1

  LENGTH = 105  COMBINED P-VALUE = 1.92e-02  E-VALUE =     0.35
  DIAGRAM: 105



malk

  LENGTH = 105  COMBINED P-VALUE = 3.23e-02  E-VALUE =     0.58
  DIAGRAM: 105



ilv

  LENGTH = 105  COMBINED P-VALUE = 5.93e-02  E-VALUE =      1.1
  DIAGRAM: 105



trn9cat

  LENGTH = 105  COMBINED P-VALUE = 1.14e-01  E-VALUE =        2
  DIAGRAM: 105


********************************************************************************


CPU: peterlenovo
Time 0.012000 secs.

mast ../../data/memenew/ex1.html ./crp0.s -oc mast_out/ -ev 10.000000 -mt 0.0001
00

File: mast_out/mast.html

   <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
   "http://www.w3.org/TR/html4/loose.dtd"> <html> <head> <meta
   http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta
   charset="UTF-8"> <meta name="description" content="Motif Alignment and
   Search Tool (MAST) output."> <title>MAST</title> <script
   type="text/javascript"> var motifs = new Array(); motifs["motif_1"] =
   new Motif("1", "nucleotide", "TGTGAACGAGCTCAC", "GTGAGCTCGTTCACA");
   motifs.length = 1; var wrap = undefined;//size to display on one line
   var wrap_timer; var seqmax = 105; var loadedSequences = new Array();
   //draging details var moving_seq; var moving_annobox; var moving_left;
   var moving_width; var moving_both; //drag needles var dnl = null; var
   dnr = null; var drag_is_rc = undefined; //container var cont = null;
   function mouseCoords(ev) { ev = ev || window.event; if(ev.pageX ||
   ev.pageY){ return {x:ev.pageX, y:ev.pageY}; } return { x:ev.clientX +
   document.body.scrollLeft - document.body.clientLeft, y:ev.clientY +
   document.body.scrollTop - document.body.clientTop }; } function setup()
   { rewrap(); window.onresize = delayed_rewrap; } function
   calculate_wrap() { [Part of this file has been deleted for brevity] 1
   GACAAAAACGCGTAACAAAAGTGTCTATAATCACGGCAGAAAAGTCCACATTGATTATTTGCACGGCGTCA
   CACT "> <input type="hidden" id="seq_1_2_hits" value=" 58 motif_1 +
   5.5e-05 + ++ +++++ ++++ "> <input type="hidden" id="seq_1_4_len"
   value="105"> <input type="hidden" id="seq_1_4_desc" value=""> <input
   type="hidden" id="seq_1_4_combined_pvalue" value="1.09e-02"> <input
   type="hidden" id="seq_1_4_type" value="nucleotide"> <input
   type="hidden" id="seq_1_4_segs" value=" 1
   CACAAAGCGAAAGCTATGCTAAAACAGTCAGGATGCTACAGTAATACATTGATGTACTGCATGTATGCAAA
   GGACGTCACATTACCGTGCAGTACAGTTGATAGC "> <input type="hidden"
   id="seq_1_4_hits" value=" 66 motif_1 + 6.0e-05 ++ ++++++ ++++ "> <input
   type="hidden" id="seq_1_3_len" value="105"> <input type="hidden"
   id="seq_1_3_desc" value=""> <input type="hidden"
   id="seq_1_3_combined_pvalue" value="1.92e-02"> <input type="hidden"
   id="seq_1_3_type" value="nucleotide"> <input type="hidden"
   id="seq_1_3_segs" value=" "> <input type="hidden" id="seq_1_3_hits"
   value=" "> <input type="hidden" id="seq_1_11_len" value="105"> <input
   type="hidden" id="seq_1_11_desc" value=""> <input type="hidden"
   id="seq_1_11_combined_pvalue" value="3.23e-02"> <input type="hidden"
   id="seq_1_11_type" value="nucleotide"> <input type="hidden"
   id="seq_1_11_segs" value=" "> <input type="hidden" id="seq_1_11_hits"
   value=" "> <input type="hidden" id="seq_1_8_len" value="105"> <input
   type="hidden" id="seq_1_8_desc" value=""> <input type="hidden"
   id="seq_1_8_combined_pvalue" value="5.93e-02"> <input type="hidden"
   id="seq_1_8_type" value="nucleotide"> <input type="hidden"
   id="seq_1_8_segs" value=" "> <input type="hidden" id="seq_1_8_hits"
   value=" "> <input type="hidden" id="seq_1_17_len" value="105"> <input
   type="hidden" id="seq_1_17_desc" value=""> <input type="hidden"
   id="seq_1_17_combined_pvalue" value="1.14e-01"> <input type="hidden"
   id="seq_1_17_type" value="nucleotide"> <input type="hidden"
   id="seq_1_17_segs" value=" "> <input type="hidden" id="seq_1_17_hits"
   value=" "> </form>
   <br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br
   ><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><b
   r><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><
   span class="sequence" id="ruler" style="visibility:hidden;
   white-space:nowrap;">ACGTN</span> </body> </html>

File: mast_out/mast.xml

<?xml version='1.0' encoding='UTF-8' standalone='yes'?>
<!DOCTYPE mast[
<!ELEMENT mast (model, alphabet, motifs, sequences, runtime)>
<!ATTLIST mast version CDATA #REQUIRED release CDATA #REQUIRED>
<!ELEMENT model (command_line, max_correlation, remove_correlated, strand_handli
ng, translate_dna, max_seq_evalue,
    adj_hit_pvalue, max_hit_pvalue, max_weak_pvalue, host, when)>
<!ELEMENT command_line (#PCDATA)>
<!ELEMENT max_correlation (#PCDATA)>
<!ELEMENT remove_correlated EMPTY>
<!ATTLIST remove_correlated value (y|n) #REQUIRED>
<!ELEMENT strand_handling EMPTY>
<!ATTLIST strand_handling value (combine|separate|norc|protein) #REQUIRED>
<!ELEMENT translate_dna EMPTY>
<!ATTLIST translate_dna value (y|n) #REQUIRED>
<!ELEMENT max_seq_evalue (#PCDATA)>
<!ELEMENT adj_hit_pvalue EMPTY>
<!ATTLIST adj_hit_pvalue value (y|n) #REQUIRED>
<!ELEMENT max_hit_pvalue (#PCDATA)>
<!ELEMENT max_weak_pvalue (#PCDATA)>
<!ELEMENT host (#PCDATA)>
<!ELEMENT when (#PCDATA)>
<!ELEMENT alphabet (letter+)>
<!ATTLIST alphabet type (amino-acid|nucleotide) #REQUIRED bg_source (preset|file
|sequence_composition) #REQUIRED bg_file CDATA #IMPLIED>
<!ELEMENT letter EMPTY>
<!ATTLIST letter symbol CDATA #REQUIRED ambig (y|n) "n" bg_value CDATA #IMPLIED>
<!ELEMENT motifs (motif+,correlation*,nos*)>
<!ATTLIST motifs source CDATA #REQUIRED name CDATA #REQUIRED last_mod_date CDATA
 #REQUIRED>
<!ELEMENT motif EMPTY>
<!-- num is simply the loading order of the motif, it's superfluous but makes th
ings easier for XSLT -->
<!ATTLIST motif id ID #REQUIRED num CDATA #REQUIRED name CDATA #REQUIRED width C
DATA #REQUIRED
   best_f CDATA #REQUIRED best_r CDATA #IMPLIED bad (y|n) "n">
<!-- for n > 1 motifs there should be (n * (n - 1)) / 2 correlations, obviously
there are none for only 1 motif -->
<!ELEMENT correlation EMPTY>
<!ATTLIST correlation motif_a IDREF #REQUIRED motif_b IDREF #REQUIRED value CDAT
A #REQUIRED>
<!-- nos: Nominal Order and Spacing diagram, a rarely used feature where mast ca
n adjust pvalues for an expected motif spacing -->
<!ELEMENT nos (expect+)>
<!-- length is in the same unit as the motifs, which is not always the same unit
 as the sequence -->
<!ATTLIST nos length CDATA #REQUIRED>
<!-- the expect tags are expected to be ordered by pos ascending -->
<!ELEMENT expect EMPTY>
<!ATTLIST expect pos CDATA #REQUIRED gap CDATA #REQUIRED motif IDREF #REQUIRED>
<!ELEMENT sequences (database+, sequence*)>
<!-- the database tags are expected to be ordered in file specification order --
>
<!ELEMENT database EMPTY>
<!ATTLIST database id ID #REQUIRED num CDATA #REQUIRED source CDATA #REQUIRED na
me CDATA #REQUIRED last_mod_date CDATA #REQUIRED
    seq_count CDATA #REQUIRED residue_count CDATA #REQUIRED type (amino-acid|nuc
leotide) #REQUIRED link CDATA #IMPLIED>
<!-- the sequence tags are expected to be ordered by best combined p-value (of c
ontained score tags) ascending -->
<!ELEMENT sequence (score+,seg*)>
<!ATTLIST sequence id ID #REQUIRED db IDREF #REQUIRED num CDATA #REQUIRED name C
DATA #REQUIRED comment CDATA "" length CDATA #REQUIRED>
<!ELEMENT score EMPTY>


  [Part of this file has been deleted for brevity]

                        <score strand="both" combined_pvalue="8.40e-03" evalue="
0.15"/>
                        <seg start="1">
                                <data>
CCCATGAGAGTGAAATTGTTGTGATGTGGTTAACCCAATTAGAATTCGGGATTGACATGTCTTACCAAAAGGTAG
                                </data>
                                <hit pos="20" gap="19" motif="motif_1" pvalue="4
.6e-05" strand="forward" match="+++++ ++++++ ++"/>
                        </seg>
                </sequence>
                <sequence id="seq_1_5" db="db_1" num="5" name="cya" comment="" l
ength="105">
                        <score strand="both" combined_pvalue="9.17e-03" evalue="
0.16"/>
                        <seg start="1">
                                <data>
ACGGTGCTACACTTGTATGTAGCGCATCTTTCTTTACGGTCAATCAGCAAGGTGTTAAATTGATCACGTTTTAGA
                                </data>
                                <hit pos="53" gap="52" motif="motif_1" pvalue="5
.1e-05" strand="forward" match="+++ ++ + + ++++"/>
                        </seg>
                </sequence>
                <sequence id="seq_1_2" db="db_1" num="2" name="ara" comment="" l
ength="105">
                        <score strand="both" combined_pvalue="9.99e-03" evalue="
0.18"/>
                        <seg start="1">
                                <data>
GACAAAAACGCGTAACAAAAGTGTCTATAATCACGGCAGAAAAGTCCACATTGATTATTTGCACGGCGTCACACT
                                </data>
                                <hit pos="58" gap="57" motif="motif_1" pvalue="5
.5e-05" strand="forward" match="+ ++ +++++ ++++"/>
                        </seg>
                </sequence>
                <sequence id="seq_1_4" db="db_1" num="4" name="crp" comment="" l
ength="105">
                        <score strand="both" combined_pvalue="1.09e-02" evalue="
0.2"/>
                        <seg start="1">
                                <data>
CACAAAGCGAAAGCTATGCTAAAACAGTCAGGATGCTACAGTAATACATTGATGTACTGCATGTATGCAAAGGAC
GTCACATTACCGTGCAGTACAGTTGATAGC
                                </data>
                                <hit pos="66" gap="65" motif="motif_1" pvalue="6
.0e-05" strand="forward" match="++  ++++++ ++++"/>
                        </seg>
                </sequence>
                <sequence id="seq_1_3" db="db_1" num="3" name="bglr1" comment=""
 length="105">
                        <score strand="both" combined_pvalue="1.92e-02" evalue="
0.35"/>
                </sequence>
                <sequence id="seq_1_11" db="db_1" num="11" name="malk" comment="
" length="105">
                        <score strand="both" combined_pvalue="3.23e-02" evalue="
0.58"/>
                </sequence>
                <sequence id="seq_1_8" db="db_1" num="8" name="ilv" comment="" l
ength="105">
                        <score strand="both" combined_pvalue="5.93e-02" evalue="
1.1"/>
                </sequence>
                <sequence id="seq_1_17" db="db_1" num="17" name="trn9cat" commen
t="" length="105">
                        <score strand="both" combined_pvalue="1.14e-01" evalue="
2"/>
                </sequence>
        </sequences>
        <runtime cycles="12000" seconds="0.012"/>
</mast>

          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 MEMENEW

          The EMBASSY MEMENEW package contains "wrapper" applications
          providing an EMBOSS-style interface to the applications in the
          original MEME package version 4.4.0 developed by Timothy L.
          Bailey. Please read the file README in the EMBASSY MEMENEW
          package distribution for installation instructions.

3. Installing original MEME

          To use EMBASSY MEMENEW, 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 MEMENEW 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 MEMENEW,
          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.

See also

   Program name     Description
   antigenic        Find antigenic sites in proteins
   eiprscan         Motif detection
   elipop           Predict lipoproteins
   ememe            Multiple EM for motif elicitation
   ememetext        Multiple EM for motif elicitation, text file only
   epestfind        Find PEST motifs as potential proteolytic cleavage sites
   fuzzpro          Search for patterns in protein sequences
   fuzztran         Search for patterns in protein sequences (translated)
   omeme            Motif detection
   patmatdb         Search protein sequences with a sequence motif
   patmatmotifs     Scan a protein sequence with motifs from the PROSITE
                    database
   preg             Regular expression search of protein sequence(s)
   pscan            Scan protein sequence(s) with fingerprints from the PRINTS
                    database
   sigcleave        Report 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.

          Please report all bugs to the EMBOSS bug team
          (emboss-bug (c) emboss.open-bio.org) not to the original author.
          Jon Ison
          European Bioinformatics Institute, Wellcome Trust Genome Campus,
          Hinxton, Cambridge CB10 1SD, UK

          Please report all bugs to the EMBOSS bug team
          (emboss-bug (c) emboss.open-bio.org) not to the original author.

          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.

Comments

None.