
                                   emast 



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:
   -d                  infile     If -d  is not given, MAST looks
                                  for database specified inside of .
   -a                  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 standard output
   -filter             boolean    Read standard input, write 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

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; }
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  TD.c8 { background: green; color: white; }
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  B.red { color: red; }
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  TH.red { color: red; }
  B.blue { color: blue; }
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  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.

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  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; }
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  TD.c5 { background: lime; color: black; }
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  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 = 6.96e-02  E-VALUE =      1.3<BR>
  DIAGRAM: 105<PRE>


</PRE>

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  <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 = 2.43e-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>
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  File: crp0.s

>ce1cg
TAATGTTTGTGCTGGTTTTTGTGGCATCGGGCGAGAATAGCGCGTGGTGTGAAAGACTGTTTTTTTGATCGTTTTCACA
A
AAATGGAAGTCCACAGTCTTGACAG
>ara
GACAAAAACGCGTAACAAAAGTGTCTATAATCACGGCAGAAAAGTCCACATTGATTATTTGCACGGCGTCACACTTTGC
T
ATGCCATAGCATTTTTATCCATAAG
>bglr1
ACAAATCCCAATAACTTAATTATTGGGATTTGTTATATATAACTTTATAAATTCCTAAAATTACACAAAGTTAATAACT
G
TGAGCATGGTCATATTTTTATCAAT
>crp
CACAAAGCGAAAGCTATGCTAAAACAGTCAGGATGCTACAGTAATACATTGATGTACTGCATGTATGCAAAGGACGTCA
C
ATTACCGTGCAGTACAGTTGATAGC
>cya
ACGGTGCTACACTTGTATGTAGCGCATCTTTCTTTACGGTCAATCAGCAAGGTGTTAAATTGATCACGTTTTAGACCAT
T
TTTTCGTCGTGAAACTAAAAAAACC
>deop2
AGTGAATTATTTGAACCAGATCGCATTACAGTGATGCAAACTTGTAAGTAGATTTCCTTAATTGTGATGTGTATCGAAG
T
GTGTTGCGGAGTAGATGTTAGAATA
>gale
GCGCATAAAAAACGGCTAAATTCTTGTGTAAACGATTCCACTAATTTATTCCATGTCACACTTTTCGCATCTTTGTTAT
G
CTATGGTTATTTCATACCATAAGCC
>ilv
GCTCCGGCGGGGTTTTTTGTTATCTGCAATTCAGTACAAAACGTGATCAACCCCTCAATTTTCCCTTTGCTGAAAAATT
T
TCCATTGTCTCCCCTGTAAAGCTGT
>lac
AACGCAATTAATGTGAGTTAGCTCACTCATTAGGCACCCCAGGCTTTACACTTTATGCTTCCGGCTCGTATGTTGTGTG
G
AATTGTGAGCGGATAACAATTTCAC
>male
ACATTACCGCCAATTCTGTAACAGAGATCACACAAAGCGACGGTGGGGCGTAGGGGCAAGGAGGATGGAAAGAGGTTGC
C
GTATAAAGAAACTAGAGTCCGTTTA
>malk
GGAGGAGGCGGGAGGATGAGAACACGGCTTCTGTGAACTAAACCGAGGTCATGTAAGGAATTTCGTGATGTTGCTTGCA
A
AAATCGTGGCGATTTTATGTGCGCA
>malt
GATCAGCGTCGTTTTAGGTGAGTTGTTAATAAAGATTTGGAATTGTGACACAGTGCAAATTCAGACACATAAAAAAACG
T
CATCGCTTGCATTAGAAAGGTTTCT
>ompa
GCTGACAAAAAAGATTAAACATACCTTATACAAGACTTTTTTTTCATATGCCTGACGGAGTTCACACTTGTAAGTTTTC
A
ACTACGTTGTAGACTTTACATCGCC
>tnaa
TTTTTTAAACATTAAAATTCTTACGTAATTTATAATCTTTAAAAAAAGCATTTAATATTGCTCCCCGAACGATTGTGAT
T
CGATTCACATTTAAACAATTTCAGA
>uxu1
CCCATGAGAGTGAAATTGTTGTGATGTGGTTAACCCAATTAGAATTCGGGATTGACATGTCTTACCAAAAGGTAGAACT
T
ATACGCCATCTCATCCGATGCAAGC
>pbr322
CTGGCTTAACTATGCGGCATCAGAGCAGATTGTACTGAGAGTGCACCATATGCGGTGTGAAATACCGCACAGATGCGTA
A
GGAGAAAATACCGCATCAGGCGCTC
>trn9cat
CTGTGACGGAAGATCACTTCGCAGAATAAATAAATCCTGGTGTCCCTGTTGATACCGGGAAGCCCTGGGCCAACTTTTG
G
CGAAAATGAGACGTTGATCGGCACG
>tdc
GATTTTTATACTTTAACTTGTTGATATTTAAAGGTATTTAATTGTAATAACGATACTCTGGAAAGTATTGAAAGTTAAT
T
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.

See also

    Program name                         Description
   antigenic      Finds antigenic sites in proteins
   digest         Protein proteolytic enzyme or reagent cleavage digest
   ememe          Motif detection
   epestfind      Finds PEST motifs as potential proteolytic cleavage sites
   fuzzpro        Protein pattern search
   fuzztran       Protein pattern search after translation
   helixturnhelix Report nucleic acid binding motifs
   oddcomp        Find protein sequence regions with a biased composition
   omeme          Motif detection
   patmatdb       Search a protein sequence with a motif
   patmatmotifs   Search a PROSITE motif database with a protein sequence
   pepcoil        Predicts coiled coil regions
   preg           Regular expression search of a protein sequence
   pscan          Scans proteins using PRINTS
   sigcleave      Reports protein signal cleavage sites

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 © rfcgr.mrc.ac.uk)
   MRC Rosalind Franklin Centre for Genomics Research Wellcome Trust
   Genome Campus, Hinxton, Cambridge, CB10 1SB, 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.
