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 3.5.5beta2 (Release date: 2006-07-06 13:07:44 -0700 (Thu, 06 Jul 2006))

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

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.nbcr.net.


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= tests/common/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 tests/common/crp0.s -dna -nmotifs 3 -minw 6 -maxw 50 -maxiter 20 -dir /home/t.bailey/MEME/SVNROOT/trunk/INSTALLED 

model:  mod=         zoops    nmotifs=         3    evt=           inf
object function=  E-value of product of p-values
width:  minw=            6    maxw=           50    minic=        0.00
width:  wg=             11    ws=              1    endgaps=       yes
nsites: minsites=        2    maxsites=       18    wnsites=       0.8
theta:  prob=            1    spmap=         uni    spfuzz=        0.5
em:     prior=   dirichlet    b=            0.01    maxiter=        20
        distance=    1e-05
data:   n=            1890    N=              18
strands: +
sample: seed=            0    seqfrac=         1
Letter frequencies in dataset:
A 0.303 C 0.183 G 0.209 T 0.306 
Background letter frequencies (from dataset with add-one prior applied):
A 0.303 C 0.183 G 0.209 T 0.306 

P N
MOTIF 1     width = 19     sites = 17     llr = 175     E-value = 4.1e-009

SimplifiedA:::28331512:1818244
pos.-specificC211:1242:2219:914:1
probabilityG:6:8:2242631:2:11::
matrixT8391141331381111466
bits 2.5
2.2
2.0
1.7  
Information 1.5   
content 1.2     
(14.8 bits)1.0        
0.7            
0.5             
0.2                 
0.0
Multilevel TGTGATCGAGGTCACACTT
consensus TAATTCTTAA
sequence GCC
NAME   START P-VALUE    SITES 
ompa513.07e-07 TTTTCATATGCCTGACGGAGTTCACACTTGTAAGTTTTC
male173.07e-07 CCGCCAATTCTGTAACAGAGATCACACAAAGCGACGGTG
deop2104.90e-07 AGTGAATTATTTGAACCAGATCGCATTACAGTGATGCA
ara586.87e-07 ACATTGATTATTTGCACGGCGTCACACTTTGCTATGCCA
lac121.31e-06 ACGCAATTAATGTGAGTTAGCTCACTCATTAGGCACCCC
tdc792.63e-06 TGAAAGTTAATTTGTGAGTGGTCGCACATATCCTGTT
bglr1792.89e-06 AGTTAATAACTGTGAGCATGGTCATATTTTTATCAAT
tnaa743.18e-06 CCCGAACGATTGTGATTCGATTCACATTTAAACAATTTC
ce1cg643.18e-06 AGACTGTTTTTTTGATCGTTTTCACAAAAATGGAAGTCC
pbr322563.49e-06 CCATATGCGGTGTGAAATACCGCACAGATGCGTAAGGAG
crp665.04e-06 ACTGCATGTATGCAAAGGACGTCACATTACCGTGCAGTA
gale457.17e-06 ATTCCACTAATTTATTCCATGTCACACTTTTCGCATCTT
uxu1202.24e-05 GTGAAATTGTTGTGATGTGGTTAACCCAATTAGAATTCG
malt443.26e-05 GATTTGGAATTGTGACACAGTGCAAATTCAGACACATAA
cya533.26e-05 ATCAGCAAGGTGTTAAATTGATCACGTTTTAGACCATTT
malk645.00e-05 TAAGGAATTTCGTGATGTTGCTTGCAAAAATCGTGGCGA
ilv425.36e-05 CAGTACAAAACGTGATCAACCCCTCAATTTTCCCTTTGC

Motif 1 block diagrams

NameLowest
p-value
   Motifs
ompa 3.1e-07

1
male 3.1e-07

1
deop2 4.9e-07

1
ara 6.9e-07

1
lac 1.3e-06

1
tdc 2.6e-06

1
bglr1 2.9e-06

1
tnaa 3.2e-06

1
ce1cg 3.2e-06

1
pbr322 3.5e-06

1
crp 5e-06

1
gale 7.2e-06

1
uxu1 2.2e-05

1
malt 3.3e-05

1
cya 3.3e-05

1
malk 5e-05

1
ilv 5.4e-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


to known motifs in JASPAR database:
Motif 1 regular expression

T[GT]TGA[TA][CAG][GTC][AT][GC][GTC]TCACA[CT][TA][TA]




Time  2.44 secs.


P N
MOTIF 2     width = 16     sites = 5     llr = 73     E-value = 2.8e+002

SimplifiedA:24:a6aa:62:4:4:
pos.-specificC:24:::::2:66:a::
probabilityGa6:a:4::22246:4:
matrixT::2:::::62::::2a
bits 2.5 
2.2   
2.0   
1.7       
Information 1.5        
content 1.2        
(21.0 bits)1.0           
0.7            
0.5                
0.2                
0.0
Multilevel GGAGAAAATACCGCAT
consensus ACGCGAGAG
sequence CTGTGT
NAME   START P-VALUE    SITES 
pbr322811.97e-09 AGATGCGTAAGGAGAAAATACCGCATCAGGCGCTC
ce1cg306.07e-09 TGTGGCATCGGGCGAGAATAGCGCGTGGTGTGAAAG
trn9cat792.41e-07 GCCAACTTTTGGCGAAAATGAGACGTTGATCGGCAC
ara364.44e-07 TATAATCACGGCAGAAAAGTCCACATTGATTATTTG
malk156.06e-07 GAGGCGGGAGGATGAGAACACGGCTTCTGTGAACTA

Motif 2 block diagrams

NameLowest
p-value
   Motifs
pbr322 2e-09

2
ce1cg 6.1e-09

2
trn9cat 2.4e-07

2
ara 4.4e-07

2
malk 6.1e-07

2
SCALE
| | | |
1 25 50 75

Motif 2 in BLOCKS format


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


Motif 2 position-specific probability matrix


to known motifs in JASPAR database:
Motif 2 regular expression

G[GAC][ACT]GA[AG]AA[TCG][AGT][CAG][CG][GA]C[AGT]T




Time  3.92 secs.


P N
MOTIF 3     width = 6     sites = 2     llr = 19     E-value = 4.1e+002

SimplifiedA::::::
pos.-specificCa:aaaa
probabilityG::::::
matrixT:a::::
bits 2.5     
2.2     
2.0     
1.7      
Information 1.5      
content 1.2      
(14.0 bits)1.0      
0.7      
0.5      
0.2      
0.0
Multilevel CTCCCC
consensus
sequence
NAME   START P-VALUE    SITES 
tnaa616.22e-05 TTTAATATTGCTCCCCGAACGATTGT
ilv896.22e-05 TTTCCATTGTCTCCCCTGTAAAGCTG

Motif 3 block diagrams

NameLowest
p-value
   Motifs
tnaa 6.2e-05

3
ilv 6.2e-05

3
SCALE
| | | | |
1 25 50 75 100

Motif 3 in BLOCKS format


to BLOCKS multiple alignment processor.
Motif 3 position-specific scoring matrix


Motif 3 position-specific probability matrix


to known motifs in JASPAR database:
Motif 3 regular expression

CTCCCC




Time  5.24 secs.


P N
SUMMARY OF MOTIFS


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

NameCombined
p-value
   Motifs
ce1cg 3.53e-08

2
1
ara 4.36e-07

2
1
bglr1 2.39e-03

1
crp 3.00e-03

1
cya 5.36e-02

1
deop2 2.02e-03

1
gale 2.00e-03

1
ilv 1.75e-03

1
3
lac 1.44e-04

1
male 6.55e-04

1
malk 3.11e-05

2
1
malt 3.65e-02

1
ompa 8.90e-04

1
tnaa 1.69e-04

3
1
uxu1 1.34e-02

1
pbr322 1.63e-08

1
2
trn9cat 1.27e-03

2
tdc 6.25e-03

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

Motif summary in machine readable format.
Stopped because nmotifs = 3 reached.


CPU: tlb-sayonara.imb.uq.edu.au


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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