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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:
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.
Go to the input files for this example
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:
2) Find sequences matching the motif and annotate them in the SwissProt database:
3) Show sequences with weaker combined matches to motifs.
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:
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:
6) Use only the first and third motifs in the search:
7) Use only the first two motifs in the search:
8) Search DNA sequences using protein motifs, adjusting p-values and E-values for each sequence by that sequence's composition:
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.
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
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.
Note: If -d 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]
MAST outputs a file containing:
Each section of the results file contains an explanation of how to interpret
them.
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
The following additional options are provided:
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.
(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.
Please report all bugs to the EMBOSS bug team (emboss-bug © emboss.open-bio.org) not to the original author.
Jon Ison
Please report all bugs to the EMBOSS bug team (emboss-bug © 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.
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 output files for this example EXAMPLES:
mast meme.results
mast meme.results -d SwissProt
mast meme.results -d SwissProt -ev 200
mast meme.results -d SwissProt -w
mast meme.results -d SwissProt -diag "9-[2]-61-[1]-62-[3]-91"
mast meme.results -d SwissProt -m 1 -m 3
mast meme.results -d SwissProt -c 2
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.
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-mfile]
(Parameter 1)infile
If -d <database> is not given, MAST looks for database specified inside of <mfile>.
Input file
Required
-ev
float
Print results for sequences with E-value
Any numeric value
10
-mt
float
Show motif matches with p-value < mt
Any numeric value
0.0001
[-outfile]
(Parameter 2)outfile
MAST program output file
Output file
<*>.emast
Additional (Optional) qualifiers
-dfile
infile
If -d <database> is not given, MAST looks for database specified inside of <mfile>.
Input file
Required
-afile
infile
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
infile
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
integer
Print results for no more than <smax> sequences
Any integer value
-1
-stdin
boolean
The default is to read the database specified inside <mfile>.
Boolean value Yes/No
No
-text
boolean
Default is hypertext (HTML) format
Boolean value Yes/No
No
-dna
boolean
Translate DNA sequences to protein
Boolean value Yes/No
No
-comp
boolean
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
integer
Print results starting with <rank> best
Any integer value
-1
-best
boolean
Include only the best motif in diagrams
Boolean value Yes/No
No
-remcorr
boolean
Remove highly correlated motifs from query
Boolean value Yes/No
No
-brief
boolean
Brief output: do not print documentation.
Boolean value Yes/No
No
-b
boolean
Print only sections I and II
Boolean value Yes/No
No
-nostatus
boolean
Do not print progress report
Boolean value Yes/No
No
-hitlist
boolean
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
-c
integer
Only use the first <c> motifs
Any integer value
-1
-sep
boolean
Score reverse complement DNA strand as a separate sequence
Boolean value Yes/No
No
-norc
boolean
Do not score reverse complement DNA strand
Boolean value Yes/No
No
-w
boolean
Show weak matches (mt<p-value<mt*10) in angle brackets
Boolean value Yes/No
No
-seqp
boolean
The default is to use POSITION p-values.
Boolean value Yes/No
No
-mf
string
Print <mf> as motif file name.
Any string
-df
string
Print <df> as database name.
Any string
-minseqs
integer
Lower bound on number of sequences in db
Any integer value
-1
-mev
float
Use only motifs with E-values less than <mev>
Any numeric value
-1
-m
integer
Overrides value set by using -mev.
Any integer value
-1
-diag
string
See on-line documentation for a valid example.
Any string
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2
-odirectory_outfilestring
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
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.
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MOTIF FORMAT
MAST can search using (multiple) motifs contained in
Motif file format
ALPHABET= alphabet
log-odds matrix: alength= alength w= w
row_1
row_2
...
row_w
ALPHABET=
followed by alphabet, a list containing the letters used in the motifs.
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.
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]
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LENGTH = 105 COMBINED P-VALUE = 6.93e-02 E-VALUE = 1.2<BR>
DIAGRAM: 105<PRE>
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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: emboss4.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
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
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:
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.
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 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.
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.
References
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
eiprscan
Motif detection
elipop
Prediction of lipoproteins
ememe
Multiple EM for Motif Elicitation
ememetext
Multiple EM for Motif Elicitation. Text file only
epestfind
Finds 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
Searches 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
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.
European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
History
None.
Target users
This program is intended to be used by everyone and everything, from naive users to embedded scripts.