Command line Training Set First Motif Summary of Motifs Termination Explanation


Search sequence databases with these motifs using MAST.
Submit these motifs to BLOCKS multiple alignment processor.
Build and use a motif-based hidden Markov model (HMM) using Meta-MEME.


MEME - Motif discovery tool

MEME version 3.0 (Release date: 2004/07/16 05:53:30)

For further information on how to interpret these results or to get a copy of the MEME software please access http://meme.sdsc.edu.

This file may be used as input to the MAST algorithm for searching sequence databases for matches to groups of motifs. MAST is available for interactive use and downloading at http://meme.sdsc.edu.


REFERENCE

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

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.


TRAINING SET

DATAFILE= /home/meme/meme.3.0.6/tests/crp0.s
ALPHABET= ACGT
Sequence name            Weight Length  Sequence name            Weight Length  
-------------            ------ ------  -------------            ------ ------  
ce1cg                    1.0000    105  ara                      1.0000    105  
bglr1                    1.0000    105  crp                      1.0000    105  
cya                      1.0000    105  deop2                    1.0000    105  
gale                     1.0000    105  ilv                      1.0000    105  
lac                      1.0000    105  male                     1.0000    105  
malk                     1.0000    105  malt                     1.0000    105  
ompa                     1.0000    105  tnaa                     1.0000    105  
uxu1                     1.0000    105  pbr322                   1.0000    105  
trn9cat                  1.0000    105  tdc                      1.0000    105  

COMMAND LINE SUMMARY

This information can also be useful in the event you wish to report a
problem with the MEME software.

command: meme /home/meme/meme.3.0.6/tests/crp0.s -mod tcm -dna -revcomp -nmotifs 2 

model:  mod=           tcm    nmotifs=         2    evt=           inf
object function=  E-value of product of p-values
width:  minw=            8    maxw=           50    minic=        0.00
width:  wg=             11    ws=              1    endgaps=       yes
nsites: minsites=        2    maxsites=       50    wnsites=       0.8
theta:  prob=            1    spmap=         uni    spfuzz=        0.5
em:     prior=   dirichlet    b=            0.01    maxiter=        50
        distance=    1e-05
data:   n=            1890    N=              18
strands: + -
sample: seed=            0    seqfrac=         1
Letter frequencies in dataset:
A 0.304 C 0.196 G 0.196 T 0.304 
Background letter frequencies (from dataset with add-one prior applied):
A 0.304 C 0.196 G 0.196 T 0.304 

P N
MOTIF 1     width = 19     sites = 18     llr = 196     E-value = 2.8e-004

SimplifiedA:::27222712:18:9333
pos.-specificC212:2262:3119:9:41:
probabilityG:5:8:324234::1:1::1
matrixT848:13122339:111266
bits 2.4
2.1  
1.9  
1.6  
Information 1.4   
content 1.2       
(15.7 bits)0.9        
0.7          
0.5               
0.2                  
0.0
Multilevel TGTGATCGAGGTCACACTT
consensus CTCACGATTAAA
sequence ACCAT
NAME STRAND START P-VALUE    SITES 
ara+582.02e-08 ACATTGATTATTTGCACGGCGTCACACTTTGCTATGCCA
ce1cg+645.44e-07 AGACTGTTTTTTTGATCGTTTTCACAAAAATGGAAGTCC
malt-416.87e-07 TGTGTCTGAATTTGCACTGTGTCACAATTCCAAATCTTT
gale+456.87e-07 ATTCCACTAATTTATTCCATGTCACACTTTTCGCATCTT
ompa+518.61e-07 TTTTCATATGCCTGACGGAGTTCACACTTGTAAGTTTTC
deop2-601.19e-06 CGCAACACACTTCGATACACATCACAATTAAGGAAATCT
male+171.47e-06 CCGCCAATTCTGTAACAGAGATCACACAAAGCGACGGTG
deop2+102.00e-06 AGTGAATTATTTGAACCAGATCGCATTACAGTGATGCA
crp+662.43e-06 ACTGCATGTATGCAAAGGACGTCACATTACCGTGCAGTA
bglr1+793.88e-06 AGTTAATAACTGTGAGCATGGTCATATTTTTATCAAT
ce1cg-175.52e-06 ACGCGCTATTCTCGCCCGATGCCACAAAAACCAGCACAA
tdc+796.54e-06 TGAAAGTTAATTTGTGAGTGGTCGCACATATCCTGTT
pbr322-536.54e-06 CTTACGCATCTGTGCGGTATTTCACACCGCATATGGTGC
lac+129.07e-06 ACGCAATTAATGTGAGTTAGCTCACTCATTAGGCACCCC
cya-509.07e-06 TGGTCTAAAACGTGATCAATTTAACACCTTGCTGATTGA
tnaa+741.06e-05 CCCGAACGATTGTGATTCGATTCACATTTAAACAATTTC
ilv+421.92e-05 CAGTACAAAACGTGATCAACCCCTCAATTTTCCCTTTGC
malk-612.06e-05 CCACGATTTTTGCAAGCAACATCACGAAATTCCTTACAT

Motif 1 block diagrams

NameLowest
p-value
   Motifs
ara 2e-08

+1
ce1cg 5.5e-06

-1
+1
malt 6.9e-07

-1
gale 6.9e-07

+1
ompa 8.6e-07

+1
deop2 1.2e-06

+1
-1
male 1.5e-06

+1
crp 2.4e-06

+1
bglr1 3.9e-06

+1
tdc 6.5e-06

+1
pbr322 6.5e-06

-1
lac 9.1e-06

+1
cya 9.1e-06

-1
tnaa 1.1e-05

+1
ilv 1.9e-05

+1
malk 2.1e-05

-1
SCALE
| | | |
1 25 50 75

Motif 1 in BLOCKS format


to BLOCKS multiple alignment processor.
Motif 1 position-specific scoring matrix


Motif 1 position-specific probability matrix






Time  1.51 secs.


P N
MOTIF 2     width = 11     sites = 5     llr = 63     E-value = 4.9e+003

SimplifiedA:::6aa:::::
pos.-specificC2::::::2:::
probabilityG8:a4::::a:2
matrixT:a::::a8:a8
bits 2.4  
2.1  
1.9  
1.6        
Information 1.4        
content 1.2          
(18.2 bits)0.9           
0.7           
0.5           
0.2           
0.0
Multilevel GTGAAATTGTT
consensus CGCG
sequence
NAME STRAND START P-VALUE    SITES 
uxu1+109.04e-07 CCCATGAGAGTGAAATTGTTGTGATGTGGT
lac-959.04e-07 GTGAAATTGTTATCCGCTCAC
lac+772.07e-06 CGTATGTTGTGTGGAATTGTGAGCGGATAAC
gale-312.07e-06 GAATAAATTAGTGGAATCGTTTACACAAGAA
tnaa-942.97e-06 TCTGAAATTGTTTAAATGTGAA

Motif 2 block diagrams

NameLowest
p-value
   Motifs
uxu1 9e-07

+2
lac 2.1e-06

+2
-2
gale 2.1e-06

-2
tnaa 3e-06

-2
SCALE
| | | | |
1 25 50 75 100

Motif 2 in BLOCKS format


to BLOCKS multiple alignment processor.
Motif 2 position-specific scoring matrix


Motif 2 position-specific probability matrix






Time  2.31 secs.


P N
SUMMARY OF MOTIFS


Combined block diagrams: non-overlapping sites with p-value < 0.0001

NameCombined
p-value
   Motifs
ce1cg 1.17e-04

-1
+1
ara 1.94e-05

+1
bglr1 1.81e-03

+1
crp 2.53e-03

+1
cya 1.15e-03

-1
deop2 8.27e-04

+1
-1
gale 8.39e-07

-2
+1
ilv 1.31e-02

+1
lac 4.37e-06

+1
+2
-2
male 1.62e-03

+1
malk 6.73e-03

-1
malt 1.76e-05

-1
ompa 9.97e-04

+1
tnaa 1.54e-05

+1
-2
uxu1 3.88e-04

+2
pbr322 5.63e-03

-1
trn9cat 3.22e-01

tdc 1.58e-03

+1
SCALE
| | | | |
1 25 50 75 100

Motif summary in machine readable format.
Stopped because nmotifs = 2 reached.


CPU: chromo


EXPLANATION OF MEME RESULTS

The MEME results consist of:

MOTIFS

For each motif that it discovers in the training set, MEME prints the following information:


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