meme.lipocalin.zoops

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/lipocalin.s
ALPHABET= ACDEFGHIKLMNPQRSTVWY
Sequence name            Weight Length  Sequence name            Weight Length  
-------------            ------ ------  -------------            ------ ------  
ICYA_MANSE               1.0000    189  LACB_BOVIN               1.0000    178  
BBP_PIEBR                1.0000    173  RETB_BOVIN               1.0000    183  
MUP2_MOUSE               1.0000    180  
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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/lipocalin.s -mod zoops -protein -nostatus -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=        5    wnsites=       0.8
theta:  prob=            1    spmap=         pam    spfuzz=        120
em:     prior=       megap    b=            4515    maxiter=        50
        distance=    1e-05
data:   n=             903    N=               5

sample: seed=            0    seqfrac=         1
Dirichlet mixture priors file: prior30.plib
Letter frequencies in dataset:
A 0.072 C 0.029 D 0.069 E 0.078 F 0.043 G 0.058 H 0.025 I 0.048 K 0.086 
L 0.087 M 0.018 N 0.053 P 0.032 Q 0.029 R 0.031 S 0.059 T 0.048 V 0.070 
W 0.017 Y 0.050 
Background letter frequencies (from dataset with add-one prior applied):
A 0.072 C 0.029 D 0.068 E 0.077 F 0.043 G 0.057 H 0.026 I 0.048 K 0.086 
L 0.087 M 0.018 N 0.053 P 0.033 Q 0.029 R 0.031 S 0.059 T 0.048 V 0.069 
W 0.017 Y 0.050 
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MOTIF  1	width =   26   sites =   5   llr = 244   E-value = 5.0e-006
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	Motif 1 Description
--------------------------------------------------------------------------------
Simplified        A  :6::2:::::::::22:6:2::2:8:
pos.-specific     C  2:4:::::::::::::::::::::::
probability       D  ::::2::::22:8:::::::::::::
matrix            E  ::222::::2::::2::::2::4:::
                  F  :::::2:::::8::::4:::::::::
                  G  4:::::::2:2:::::::a:::::::
                  H  2::::::::::::::::2:::4::::
                  I  :::2:::::::::2::2::::::42:
                  K  ::::::4:22:::2:4:::2:::::6
                  L  ::2::::::::2:2:::::::::2:2
                  M  ::::::::2::::::::::::::2:2
                  N  :::::::::26:2::2:2::::::::
                  P  :::4:::4::::::::::::::::::
                  Q  2:::::2:::::::2:::::::::::
                  R  :2::::2::2:::::2::::::::::
                  S  :::2222:::::::4:::::::2:::
                  T  :::::2:4:::::::::::4::2:::
                  V  ::2:24:24::::2::2::::::2::
                  W  :::::::::::::2::::::a2::::
                  Y  :2::::::::::::::2::::4::::

         bits    5.9                     *     
                 5.3                     *     
                 4.7                     *     
                 4.1                   * *     
Information      3.5            **     * **    
content          2.9 **     *  ***    ** **  * 
(70.4 bits)      2.3 **** **** *** ***** ** ***
                 1.8 **************************
                 1.2 **************************
                 0.6 **************************
                 0.0 --------------------------

Multilevel           GACPAVKPVDNFDISKFAGTWHEIAK
consensus            CREEDFQTGEDLNKAAIH A YALIL
sequence             HYLIESRVKKG  LENVN E WSM M
                     Q VSSTS MN   VQRY  K  TV  
                         V    R   W            
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	Motif 1 sites sorted by position p-value
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Sequence name             Start   P-value                       Site         
-------------             ----- ---------            --------------------------
BBP_PIEBR                     6  1.34e-24      NVYHD GACPEVKPVDNFDWSNYHGKWWEVAK YPNSVEKYGK
ICYA_MANSE                    7  2.61e-24     GDIFYP GYCPDVKPVNDFDLSAFAGAWHEIAK LPLENENQGK
RETB_BOVIN                    4  1.83e-19        ERD CRVSSFRVKENFDKARFAGTWYAMAK KDPEGLFLQD
LACB_BOVIN                   15  2.99e-18 LLALALTCGA QALIVTQTMKGLDIQKVAGTWYSLAM AASDISLLDA
MUP2_MOUSE                   17  6.78e-17 LCLGLTLVCV HAEEASSTGRNFNVEKINGEWHTIIL ASDKREKIED
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	Motif 1 block diagrams
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SEQUENCE NAME            POSITION P-VALUE  MOTIF DIAGRAM
-------------            ----------------  -------------
BBP_PIEBR                         1.3e-24  5_[1]_142
ICYA_MANSE                        2.6e-24  6_[1]_157
RETB_BOVIN                        1.8e-19  3_[1]_154