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/INO_up800.s
ALPHABET= ACGT
Sequence name            Weight Length  Sequence name            Weight Length  
-------------            ------ ------  -------------            ------ ------  
CHO1                     1.0000    800  CHO2                     1.0000    800  
FAS1                     1.0000    800  FAS2                     1.0000    800  
ACC1                     1.0000    800  INO1                     1.0000    800  
OPI3                     1.0000    800  

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/INO_up800.s -mod zoops -dna -revcomp -bfile /home/meme/meme.3.0.6/tests/yeast.nc.6.freq -nmotifs 2 

model:  mod=         zoops    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=        7    wnsites=       0.8
theta:  prob=            1    spmap=         uni    spfuzz=        0.5
em:     prior=   dirichlet    b=            0.01    maxiter=        50
        distance=    1e-05
data:   n=            5600    N=               7
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 /home/meme/meme.3.0.6/tests/yeast.nc.6.freq):
A 0.324 C 0.176 G 0.176 T 0.324 

P N
MOTIF 1     width = 16     sites = 7     llr = 113     E-value = 4.9e-002

SimplifiedA931::::9:a:::31:
pos.-specificC1413:1a:a:::7649
probabilityG:3:::::::::a3:4:
matrixT::77a9:1::a::1:1
bits 2.5   
2.3   
2.0   
1.8     
Information 1.5        
content 1.3          
(23.2 bits)1.0             
0.8               
0.5                
0.3                
0.0
Multilevel ACTTTTCACATGCCCC
consensus ACGAG
sequence G
NAME STRAND START P-VALUE    SITES 
INO1-6202.22e-10 AATAGACAATACTTTTCACATGCCGCATTTAGCCGC
CHO2+3504.67e-09 CAATTGCCACACTTTTCTCATGCCGCATTCATTATT
ACC1+799.66e-09 CGCCCGTTAAAATCTTCACATGGCCCGGCCGCGCGC
FAS1+912.21e-08 CGACGGCCAAAAACTTCACATGCCGCCCAGCCAAGC
CHO1+6363.90e-08 CACGCCTTTGAGCTTTCACATGGACCCATCTAAAGA
OPI3-5851.08e-07 AACCGGTGCAACTTTCCACATGCACTCTCATTGACA
FAS2+5631.49e-07 TTATCTCCCGCGTTTTCACATGCTACCTCATTCGCC

Motif 1 block diagrams

NameLowest
p-value
   Motifs
INO1 2.2e-10

-1
CHO2 4.7e-09

+1
ACC1 9.7e-09

+1
FAS1 2.2e-08

+1
CHO1 3.9e-08

+1
OPI3 1.1e-07

-1
FAS2 1.5e-07

+1
SCALE
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
1 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 525 550 575 600 625 650 675 700 725 750 775

Motif 1 in BLOCKS format


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


Motif 1 position-specific probability matrix






Time  2.20 secs.


P N
MOTIF 2     width = 15     sites = 7     llr = 98     E-value = 1.1e+002

SimplifiedA:4:4::73:3:1:aa
pos.-specificCa111:61::1::9::
probabilityG::9491:77:a11::
matrixT:4::131:36:7:::
bits 2.5  
2.3  
2.0    
1.8     
Information 1.5         
content 1.3         
(20.1 bits)1.0         
0.8           
0.5             
0.3               
0.0
Multilevel CAGAGCAGGTGTCAA
consensus TGTATA
sequence
NAME STRAND START P-VALUE    SITES 
CHO2-1043.70e-10 AACTTTGGATCTGGGCAGGTGTCAAAGTAAGAACT
OPI3+5663.51e-09 CCTTGATGACCAGGGTAGGTGTCAATGAGAGTGCA
ACC1+5853.34e-07 AATTCAGATTCAGAGCAAGAGACAAGAAACTTCCC
CHO1-303.64e-07 TATTTTGCTGCTGATCAAGTGTCAAATAATATTGT
FAS1-546.38e-07 TGTTGGAGGCCAGGGGAGTAGTGAACCGTGCCTGC
FAS2+2726.87e-07 TCGTTGTTGTCCCAGCCGTTGTCAAAACGCGTTAA
INO1+7149.35e-07 AAGCGCACCTCTGCGTTGGCGGCAATGTTAATTTG

Motif 2 block diagrams

NameLowest
p-value
   Motifs
CHO2 3.7e-10

-2
OPI3 3.5e-09

+2
ACC1 3.3e-07

+2
CHO1 3.6e-07

-2
FAS1 6.4e-07

-2
FAS2 6.9e-07

+2
INO1 9.3e-07

+2
SCALE
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
1 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 525 550 575 600 625 650 675 700 725 750 775

Motif 2 in BLOCKS format


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


Motif 2 position-specific probability matrix






Time  4.28 secs.


P N
SUMMARY OF MOTIFS


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

NameCombined
p-value
   Motifs
CHO1 6.36e-07

-2
+1
+1
CHO2 1.16e-10

-2
+1
FAS1 6.32e-07

-2
+1
FAS2 4.10e-06

+2
+1
ACC1 1.57e-07

+1
+2
INO1 1.14e-08

-1
-1
+2
OPI3 2.04e-08

+2
+2
-1
+1
SCALE
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
1 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 525 550 575 600 625 650 675 700 725 750 775

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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