meme.ino_up800.oops

EM算法的改进

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MEME - Motif discovery tool
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MEME version 3.5.3 (Release date: 2006-03-08 09:30:25 +1000 (Wed, 08 Mar 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.
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REFERENCE
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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.
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TRAINING SET
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DATAFILE= /home/tbailey/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  
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COMMAND LINE SUMMARY
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This information can also be useful in the event you wish to report a
problem with the MEME software.

command: meme /home/tbailey/tests/INO_up800.s -mod oops -dna -revcomp -bfile /home/tbailey/tests/yeast.nc.6.freq -nostatus -nmotifs 2 

model:  mod=          oops    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=        7    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/tbailey/tests/yeast.nc.6.freq):
A 0.324 C 0.176 G 0.176 T 0.324 
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MOTIF  1	width =   12   sites =   7   llr = 95   E-value = 2.0e-001
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	Motif 1 Description
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Simplified        A  :::9:a::::3:
pos.-specific     C  ::a:9:11691a
probability       G  ::::1::94:4:
matrix            T  aa:1::9::11:

         bits    2.5   *        *
                 2.3   *        *
                 2.0   * *  *   *
                 1.8   * *  * * *
Information      1.5 *** ** *** *
content          1.3 *** ****** *
(19.5 bits)      1.0 ********** *
                 0.8 ********** *
                 0.5 ********** *
                 0.3 ************
                 0.0 ------------

Multilevel           TTCACATGCCGC
consensus                    G A 
sequence                         
                                 
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	Motif 1 sites sorted by position p-value
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Sequence name            Strand  Start   P-value                Site  
-------------            ------  ----- ---------            ------------
INO1                         -    620  1.85e-08 GACAATACTT TTCACATGCCGC ATTTAGCCGC
FAS1                         +     95  1.85e-08 GGCCAAAAAC TTCACATGCCGC CCAGCCAAGC
ACC1                         +     83  1.52e-07 CGTTAAAATC TTCACATGGCCC GGCCGCGCGC
CHO2                         +    354  2.52e-07 TGCCACACTT TTCTCATGCCGC ATTCATTATT
CHO1                         +    611  4.23e-07 ACTTTGAACG TTCACACGGCAC CCTCACGCCT
FAS2                         +    567  9.43e-07 CTCCCGCGTT TTCACATGCTAC CTCATTCGCC
OPI3                         +    340  3.32e-06 CCAAGCCTCC TTCAGATCGCTC TTGTCGACCG
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	Motif 1 block diagrams
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SEQUENCE NAME            POSITION P-VALUE  MOTIF DIAGRAM
-------------            ----------------  -------------
INO1                              1.8e-08  619_[-1]_169
FAS1                              1.8e-08  94_[+1]_694
ACC1                              1.5e-07  82_[+1]_706
CHO2                              2.5e-07  353_[+1]_435
CHO1                              4.2e-07  610_[+1]_178
FAS2                              9.4e-07  566_[+1]_222
OPI3                              3.3e-06  339_[+1]_449
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	Motif 1 in BLOCKS format
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BL   MOTIF 1 width=12 seqs=7
INO1                     (  620) TTCACATGCCGC  1 
FAS1                     (   95) TTCACATGCCGC  1 
ACC1                     (   83) TTCACATGGCCC  1 
CHO2                     (  354) TTCTCATGCCGC  1 
CHO1                     (  611) TTCACACGGCAC  1 
FAS2                     (  567) TTCACATGCTAC  1 
OPI3                     (  340) TTCAGATCGCTC  1 
//

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	Motif 1 position-specific scoring matrix
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log-odds matrix: alength= 4 w= 12 n= 5523 bayes= 9.62205 E= 2.0e-001 
  -945   -945   -945    162 
  -945   -945   -945    162 
  -945    251   -945   -945 
   140   -945   -945   -118 
  -945    229    -30   -945 
   162   -945   -945   -945 
  -945    -30   -945    140 
  -945    -30    229   -945 
  -945    170    129   -945 
  -945    229   -945   -118 
   -18    -30    129   -118 
  -945    251   -945   -945 
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	Motif 1 position-specific probability matrix
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letter-probability matrix: alength= 4 w= 12 nsites= 7 E= 2.0e-001 
 0.000000  0.000000  0.000000  1.000000 
 0.000000  0.000000  0.000000  1.000000 
 0.000000  1.000000  0.000000  0.000000 
 0.857143  0.000000  0.000000  0.142857 
 0.000000  0.857143  0.142857  0.000000 
 1.000000  0.000000  0.000000  0.000000 
 0.000000  0.142857  0.000000  0.857143 
 0.000000  0.142857  0.857143  0.000000