********************************************************************************
MEME - Motif discovery tool
********************************************************************************
MEME version 2.0 (Release date: 1996/11/17 00:39:06)
For further information on how to interpret these results or to get
a copy of the MEME software please access http://www.sdsc.edu/MEME.
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://www.sdsc.edu/MEME.
********************************************************************************
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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
********************************************************************************
DATAFILE= meme.14072.data (deleted by web version of MEME)
ALPHABET= ACDEFGHIKLMNPQRSTVWY
Sequence name Length Sequence name Length
------------- ------ ------------- ------
GI|404390|BBS|135491 168 GI|895868 189
GI|206115 189 GI|1079295|PIR||S52354 184
********************************************************************************
********************************************************************************
EXPLANATION OF RESULTS
********************************************************************************
For each motif that it discovers in the training set, MEME prints the
following information:
Summary Line
This line gives the width (`width') and expected number of occurrences in
the training set (`sites') of the motif. MEME numbers the motifs
consecutively from one as it finds them. MEME usually finds the most
statistically significant motifs first. Each motif describes a pattern of
a fixed width--no gaps are allowed in MEME motifs. MEME estimates
the number of places the motif occurs in the training set. This need
not be an integer value.
Simplified Motif Letter-probability Matrix
MEME motifs are represented by letter-probability matrices that
specify the probability of each possible letter appearing at each
possible position in an occurrence of the motif. In order to make it
easier to see which letters are most likely in each of the columns of
the motif, the simplified motif shows the letter probabilities multiplied
by 10 rounded to the nearest integer. Zeros are replaced by ":" (the
colon) for readability.
Information Content Diagram
The information content diagram provides an idea of which positions
in the motif are most highly conserved. Each column (position) in a
motif can be characterized by the amount of information it contains
(measured in bits). Highly conserved positions in the motif have high
information; positions where all letters are equally likely have low
information. The diagram is printed so that each column lines up with
the same column in the simplified motif letter-probability matrix above
it. Summing the information content for each position in the motif
gives the total information content of the motif (shown in parentheses
to the left of the diagram). This gives a measure of the usefulness of
the motif for database searches. For a motif to be useful for database
searches, it must as a rule contain at least log_2(N) bits of
information where N is the number of sequences in the database
being searched. For example, to effectively search a database
containing 100,000 sequences for occurrences of a single motif, the
motif should have an IC of at least 16.6 bits. Motifs with lower
information content are still useful when a family of sequences shares
more than one motif since they can be combined in multiple motif
searches (using MAST).
Multilevel Consensus Sequence
The multilevel consensus sequence corresponding to the motif is an
aid in remembering and understanding the motif. It is calculated from
the motif letter-probability matrix as follows. Separately for each
column of the motif, the letters in the alphabet are sorted in
decreasing order by the probability with which they are expected to
occur in that position of motif occurrences. The sorted letters are
then printed vertically with the most probable letter on top. Only
letters with probabilities of 0.2 or higher at that position in the motif
are printed. As an example, the multilevel consensus sequence of
motif 2 in the sample output is:
Multilevel LITGAASGIG
consensus V GS
sequence G
This multilevel consensus sequence says several things about the
motif. First, the most likely form of the motif can be read from the top
line as LITGAASGIG. Second, that only letter L has probability
more than 0.2 in position 1 of the motif, both I and V have probability
greater than 0.2 in position 2, etc. Third, a rough approximation of the
motif can be made by converting the multilevel consensus sequence
into the Prosite signature
L-[IV]-T-G-[AG]-[ASG]-S-G-I-G. The multilevel
consensus sequence is printed so that each column lines up with
the same column in the simplified motif and information content
diagrams above it.
Possible Examples of the Motif
As a further aid in understanding the motif, MEME displays a list of
possible occurrences of the motif in the training set. This list is made
by converting the motif letter-probability matrix into a
position-dependent scoring matrix (log-odds matrix) and using that
to compute a match score between each position in the training set
and the motif. All positions which score above a threshold score are
listed. (The threshold score is chosen by MEME such that the
expected number of non-motif positions listed in error will equal the
number of actual motif positions not listed.) The format of the list is
sequence name, starting position of the (putative) occurrence, match
score of the position, and the actual sequence including the ten
positions before and after the motif occurrence (`site').
Position-dependent Scoring Matrix
The position-dependent scoring matrix corresponding to the motif is
printed for use by database search programs such as MAST. This
matrix is a log-odds matrix calculated by taking the log (base 2) of
the ratio p/f at each position in the motif where p is the probability
of a particular letter at that position in the motif, and f is the average
frequency of that letter in the training set. The scoring matrix is
printed "sideways"--columns correspond to the letters in the
alphabet (in the same order as shown in the simplified motif) and
rows corresponding to the positions of the motif, position one first.
The scoring matrix is preceded by a line starting with "log-odds
matrix:" and containing the length of the alphabet, width of the motif,
number of characters in the training set and the scoring threshold
used in the list of possible motif examples.
Motif Letter-probability Matrix
The motif itself is a position-dependent letter-probability matrix
giving, for each position in the pattern, the probabilities of each
possible letter occurring there. The letter-probability matrix is printed
"sideways"--columns correspond to the letters in the alphabet (in
the same order as shown in the simplified motif) and rows
corresponding to the positions of the motif, position one first. The
motif is preceded by a line starting with "letter-probability matrix:" and
containing the length of the alphabet, width of the motif and number of
characters in the training set.
********************************************************************************
********************************************************************************
MOTIF 1 width = 14 sites = 4.0
********************************************************************************
Simplified A :::::7::8:::::
motif letter- C ::::::::::::::
probability D ::::::::::::::
matrix E ::::::::::::::
F :::2::::::::::
G 9:::1:9:::::::
H ::::::::::::::
I :::::1::::::::
K :1::::::::::::
L :::::::8::::::
M ::::::::::::::
N ::::::::::9:1:
P ::::::::::::::
Q ::::::::::::::
R :8::::::::::::
S ::::6::::8:86:
T ::::1::::1:11:
V ::::::::::::::
W ::9::::::::::9
Y :::6::::::::::
bits 5.9
5.3
4.7
4.1 * *
Information 3.6 * * *
content 3.0 ** * *
(51.7 bits) 2.4 *** * * * *
1.8 **** ******* *
1.2 **************
0.6 **************
0.0 --------------
Multilevel GRWYSAGLASNSSW
consensus F
sequence
---------------------------------------------------------------------------
Possible examples of motif 1 in the training set
---------------------------------------------------------------------------
Sequence name Start Score Site
------------- ----- ----- --------------
GI|404390|BBS|135491 19 52.87 QPNFQPDKFL GRWFSAGLASNSSW LQEKKAALSM
GI|895868 41 54.61 QPNFQQDKFL GRWYSAGLASNSSW FREKKAVLYM
GI|206115 41 54.61 QPNFQQDKFL GRWYSAGLASNSSW FREKKELLFM
GI|1079295|PIR||S52354 36 44.58 QPDFQKEKVL GKWYGIGLASNSNW FKDRKSHMKM
---------------------------------------------------------------------------
log-odds matrix: alength= 20 w= 14 n= 678 bayes= 7.3966
-1.905 -3.125 -2.494 -3.240 -4.244 3.684 -2.961 -4.307 -3.073 -4.697 -3.565 -2.202 -3.793 -3.473 -3.009 -2.420 -3.394 -3.794 -3.509 -3.810
-3.037 -2.650 -3.801 -3.310 -4.310 -3.694 -1.508 -3.654 0.393 -3.569 -3.070 -2.646 -3.401 -1.590 3.985 -3.185 -3.147 -3.992 -2.765 -3.564
-3.882 -3.158 -3.951 -4.079 -1.203 -4.088 -3.276 -3.860 -3.868 -2.504 -2.686 -3.733 -4.408 -3.472 -3.444 -4.048 -3.899 -3.450 6.066 -1.424
-2.131 -1.946 -2.986 -2.846 2.404 -3.372 0.190 -2.147 -2.735 -1.884 -1.526 -2.446 -3.166 -2.450 -2.497 -2.288 -2.595 -2.120 -0.035 4.150
-0.588 -1.351 -2.073 -2.676 -3.292 1.014 -2.299 -3.353 -2.470 -3.512 -2.572 -1.235 -2.724 -2.404 -2.584 3.069 0.180 -2.658 -3.422 -3.099
3.156 -0.681 -3.204 -2.796 -2.244 -1.662 -2.681 0.794 -2.756 -1.770 -1.213 -2.800 -3.457 -2.678 -2.766 -0.780 -1.546 -0.370 -2.771 -2.758
-1.905 -3.125 -2.494 -3.240 -4.244 3.684 -2.961 -4.307 -3.073 -4.697 -3.565 -2.202 -3.793 -3.473 -3.009 -2.420 -3.394 -3.794 -3.509 -3.810
-2.954 -2.588 -4.488 -3.867 -1.229 -4.373 -3.110 -0.653 -3.609 3.171 0.142 -3.954 -3.762 -2.910 -3.228 -3.706 -2.896 -1.237 -2.655 -2.625
3.442 -0.792 -3.318 -3.044 -2.945 -1.581 -2.985 -2.579 -3.109 -2.801 -2.002 -2.946 -3.516 -2.973 -3.037 -0.750 -1.740 -1.262 -3.133 -3.325
-1.320 -1.685 -2.839 -3.366 -3.314 -2.618 -2.762 -3.484 -2.813 -3.664 -2.735 -1.663 -3.072 -2.929 -2.788 3.403 0.481 -3.228 -3.435 -3.131
-3.382 -3.021 -1.855 -3.618 -3.546 -3.228 -0.760 -3.145 -2.883 -4.005 -3.141 4.229 -3.698 -2.470 -3.202 -1.736 -2.448 -3.556 -3.121 -3.237
-1.320 -1.685 -2.839 -3.366 -3.314 -2.618 -2.762 -3.484 -2.813 -3.664 -2.735 -1.663 -3.072 -2.929 -2.788 3.403 0.481 -3.228 -3.435 -3.131
-1.322 -1.680 -1.380 -2.208 -3.112 -2.155 -1.793 -3.268 -1.962 -3.418 -2.469 1.077 -2.762 -2.054 -2.214 3.108 0.692 -3.129 -3.272 -2.743
-3.882 -3.158 -3.951 -4.079 -1.203 -4.088 -3.276 -3.860 -3.868 -2.504 -2.686 -3.733 -4.408 -3.472 -3.444 -4.048 -3.899 -3.450 6.066 -1.424
letter-probability matrix: alength= 20 w= 14 n= 678
0.019534 0.002082 0.009182 0.006599 0.002126 0.890941 0.002879 0.002844 0.006953 0.003535 0.001949 0.010016 0.003654 0.003671 0.006448 0.013794 0.005650 0.004639 0.001172 0.002331
0.008913 0.002894 0.003712 0.006284 0.002031 0.005356 0.007888 0.004472 0.076802 0.007729 0.002747 0.007362 0.004798 0.013539 0.821883 0.008114 0.006707 0.004044 0.001962 0.002764
0.004963 0.002035 0.003346 0.003690 0.017495 0.004078 0.002315 0.003875 0.004005 0.016170 0.003584 0.003465 0.002387 0.003674 0.004768 0.004460 0.003982 0.005891 0.893638 0.012179
0.016698 0.004715 0.006529 0.008670 0.213133 0.006695 0.025586 0.012705 0.008784 0.024841 0.008009 0.008456 0.005644 0.007457 0.009196 0.015113 0.009832 0.014806 0.013022 0.580109
0.048665 0.007122 0.012297 0.009755 0.004112 0.140004 0.004557 0.005507 0.010556 0.008038 0.003879 0.019578 0.007672 0.007699 0.008653 0.619355 0.067296 0.010195 0.001245 0.003815
0.651950 0.011329 0.005615 0.008979 0.008503 0.021911 0.003496 0.097572 0.008656 0.026883 0.009953 0.006614 0.004616 0.006367 0.007629 0.042977 0.020344 0.049818 0.001955 0.004833
0.019534 0.002082 0.009182 0.006599 0.002126 0.890941 0.002879 0.002844 0.006953 0.003535 0.001949 0.010016 0.003654 0.003671 0.006448 0.013794 0.005650 0.004639 0.001172 0.002331
0.009439 0.003021 0.002306 0.004272 0.017184 0.003345 0.002598 0.035795 0.004794 0.825778 0.025451 0.002972 0.003736 0.005422 0.005539 0.005653 0.007980 0.027299 0.002118 0.005299
0.795188 0.010494 0.005188 0.007561 0.005231 0.023181 0.002834 0.009417 0.006778 0.013162 0.005760 0.005981 0.004430 0.005192 0.006322 0.043887 0.017785 0.026829 0.001521 0.003261
0.029314 0.005647 0.007232 0.006046 0.004050 0.011297 0.003306 0.005029 0.008321 0.007234 0.003465 0.014555 0.006024 0.005351 0.007515 0.780879 0.082902 0.006869 0.001234 0.003731
0.007018 0.002237 0.014298 0.005077 0.003450 0.007399 0.013243 0.006364 0.007931 0.005713 0.002614 0.864240 0.003904 0.007358 0.005640 0.022155 0.010887 0.005470 0.001534 0.003466
0.029314 0.005647 0.007232 0.006046 0.004050 0.011297 0.003306 0.005029 0.008321 0.007234 0.003465 0.014555 0.006024 0.005351 0.007515 0.780879 0.082902 0.006869 0.001234 0.003731
0.029264 0.005670 0.019874 0.013493 0.004660 0.015562 0.006473 0.005844 0.015015 0.008581 0.004165 0.097224 0.007472 0.009815 0.011185 0.636122 0.095960 0.007357 0.001381 0.004881
0.004963 0.002035 0.003346 0.003690 0.017495 0.004078 0.002315 0.003875 0.004005 0.016170 0.003584 0.003465 0.002387 0.003674 0.004768 0.004460 0.003982 0.005891 0.893638 0.012179
Time 7.30 secs.
********************************************************************************
MOTIF 2 width = 11 sites = 4.0
********************************************************************************
Simplified A :::::::::::
motif letter- C :::::::::a:
probability D :::::::9:::
matrix E :::::::::::
F ::8::::::::
G :::::::::::
H :::::::::::
I 721:::::::4
K ::::::::7::
L 1::8::::::1
M ::::::::::3
N :::::::::::
P ::::8:5::::
Q :::::8::1::
R ::::::::1::
S :::::::::::
T ::::::3::::
V 17::::::::1
W :::::::::::
Y :::::::::::
bits 5.9
5.3
4.7 *
4.1 *
Information 3.6 *
content 3.0 * * * *
(40.6 bits) 2.4 *** ** * **
1.8 ***********
1.2 ***********
0.6 ***********
0.0 -----------
Multilevel IVFLPQPDKCI
consensus T M
sequence
------------------------------------------------------------------------
Possible examples of motif 2 in the training set
------------------------------------------------------------------------
Sequence name Start Score Site
------------- ----- ----- -----------
GI|404390|BBS|135491 155 42.24 CKAQGFTEDS IVFLPQTDKCM TEQ
GI|895868 177 42.52 SKAQGLTEED IVFLPQPDKCI QE
GI|206115 177 42.52 SKDQGLTEED IVFLPQPDKCI QE
GI|1079295|PIR||S52354 171 30.17 AKSQGLADDN IIILPHTDQCM TEA
------------------------------------------------------------------------
log-odds matrix: alength= 20 w= 11 n= 690 bayes= 7.42206
-2.716 -2.578 -3.951 -3.962 -2.214 -4.272 -3.746 3.680 -3.559 -0.461 -0.519 -3.558 -4.316 -3.652 -3.830 -3.458 -2.514 0.886 -3.351 -2.827
-1.239 -1.535 -3.692 -3.465 -2.350 -3.927 -3.011 1.701 -3.467 -1.329 -1.181 -3.546 -3.524 -3.471 -3.247 -3.249 -1.662 3.347 -3.590 -3.428
-3.008 -2.123 -4.220 -4.159 4.298 -4.384 -3.197 -0.060 -4.151 -1.102 -1.276 -3.965 -3.894 -4.020 -4.178 -3.224 -3.497 -1.823 -1.606 -0.356
-2.954 -2.588 -4.488 -3.867 -1.229 -4.373 -3.110 -0.653 -3.609 3.171 0.142 -3.954 -3.762 -2.910 -3.228 -3.706 -2.896 -1.237 -2.655 -2.625
-1.545 -2.922 -2.854 -2.753 -3.471 -3.049 -2.559 -3.338 -2.562 -3.167 -2.961 -2.991 4.068 -2.374 -2.749 -2.106 -2.373 -2.917 -3.861 -3.746
-2.373 -2.827 -3.112 -1.006 -3.730 -3.925 0.999 -3.347 -2.244 -2.576 -1.360 -2.085 -3.031 4.271 -1.745 -2.688 -2.719 -3.251 -2.736 -3.396
-1.001 -2.078 -2.328 -2.204 -3.029 -2.444 -2.143 -2.586 -2.043 -2.775 -2.202 -2.023 3.357 -1.920 -2.282 -1.065 2.151 -2.149 -3.412 -3.163
-3.103 -3.516 4.067 -0.896 -4.000 -3.519 -2.340 -3.937 -3.606 -4.255 -3.588 -0.751 -4.389 -3.174 -3.636 -3.102 -3.578 -3.722 -3.771 -3.540
-2.505 -3.201 -2.851 -1.957 -4.226 -3.399 -1.727 -3.312 3.675 -3.404 -2.592 -2.079 -3.498 0.882 0.145 -2.698 -2.504 -3.305 -3.331 -3.251
-3.681 5.723 -5.165 -4.891 -4.665 -5.299 -4.504 -4.116 -5.303 -4.736 -3.791 -4.858 -5.360 -4.975 -4.742 -4.608 -3.903 -4.567 -5.323 -5.235
-2.276 -2.000 -4.386 -3.992 -1.197 -4.129 -3.267 2.864 -3.636 0.016 3.789 -3.686 -4.049 -3.300 -3.636 -3.364 -2.218 0.327 -2.588 -2.394
letter-probability matrix: alength= 20 w= 11 n= 690
0.011139 0.003041 0.003345 0.004000 0.008683 0.003588 0.001672 0.721491 0.004964 0.066620 0.016099 0.003912 0.002544 0.003241 0.003650 0.006715 0.010401 0.118983 0.001307 0.004605
0.030991 0.006267 0.004003 0.005646 0.007899 0.004559 0.002783 0.182937 0.005291 0.036513 0.010176 0.003946 0.004406 0.003674 0.005466 0.007764 0.018772 0.654762 0.001108 0.003037
0.009093 0.004171 0.002777 0.003490 0.792144 0.003321 0.002446 0.053995 0.003293 0.042734 0.009523 0.002951 0.003409 0.002512 0.002867 0.007896 0.005263 0.018192 0.004382 0.025541
0.009439 0.003021 0.002306 0.004272 0.017184 0.003345 0.002598 0.035795 0.004794 0.825778 0.025451 0.002972 0.003736 0.005422 0.005539 0.005653 0.007980 0.027299 0.002118 0.005299
0.025080 0.002396 0.007155 0.009245 0.003632 0.008379 0.003805 0.005566 0.009908 0.010211 0.002963 0.005795 0.849806 0.007861 0.007718 0.017140 0.011466 0.008519 0.000918 0.002435
0.014123 0.002560 0.005984 0.031041 0.003036 0.004565 0.044810 0.005530 0.012352 0.015376 0.008987 0.010862 0.006197 0.786743 0.015486 0.011456 0.009022 0.006762 0.002002 0.003104
0.036567 0.004303 0.010301 0.013533 0.004936 0.012742 0.005078 0.009372 0.014189 0.013399 0.005012 0.011338 0.519243 0.010772 0.010672 0.035270 0.263857 0.014513 0.001254 0.003648
0.008517 0.001588 0.867471 0.033510 0.002519 0.006046 0.004429 0.003675 0.004803 0.004803 0.001919 0.027379 0.002418 0.004515 0.004173 0.008596 0.004974 0.004878 0.000977 0.002810
0.012887 0.001975 0.007170 0.016061 0.002152 0.006573 0.006775 0.005668 0.747264 0.008662 0.003827 0.010903 0.004484 0.075106 0.057376 0.011371 0.010474 0.006514 0.001326 0.003433
0.005706 0.959604 0.001442 0.002102 0.001588 0.001761 0.000988 0.003246 0.001482 0.003441 0.001667 0.001589 0.001234 0.001296 0.001940 0.003026 0.003972 0.002716 0.000333 0.000868
0.015111 0.004541 0.002475 0.003918 0.017577 0.003964 0.002330 0.409798 0.004705 0.092728 0.318758 0.003579 0.003062 0.004138 0.004175 0.007169 0.012771 0.080764 0.002219 0.006219
Time 12.92 secs.
********************************************************************************
MOTIF 3 width = 9 sites = 4.0
********************************************************************************
Simplified A :::2:::::
motif letter- C :::::::::
probability D ::::6:9::
matrix E ::a::::9:
F :::::1::1
G :::::::::
H :::::::::
I 11:::::::
K :::::::::
L :::::::::
M :::::::::
N ::::2::::
P :::::::::
Q :::::::::
R :::::::::
S :::1:::::
T :::6:::::
V 88:::::::
W :::::::::
Y :::::8::8
bits 5.9
5.3
4.7
4.1
Information 3.6 *
content 3.0 * ****
(34.0 bits) 2.4 *** *****
1.8 *** *****
1.2 *********
0.6 *********
0.0 ---------
Multilevel VVETDYDEY
consensus N
sequence
----------------------------------------------------------------------
Possible examples of motif 3 in the training set
----------------------------------------------------------------------
Sequence name Start Score Site
------------- ----- ----- ---------
GI|404390|BBS|135491 98 31.66 PHWGSTYSVS VVETDYDHY ALLYSQGSKG
GI|895868 120 31.81 PHSGSIHSVS VVEANYDEY ALLFSRGTKG
GI|206115 120 35.16 PHWGSFHSLS VVETDYDEY AFLFSKGTKG
GI|1079295|PIR||S52354 115 34.12 PRYGSEHDMR VVETNYDEY ILMYTVKTKG
----------------------------------------------------------------------
log-odds matrix: alength= 20 w= 9 n= 698 bayes= 7.43879
-1.125 -1.561 -3.567 -3.351 -2.499 -3.703 -2.862 0.255 -3.382 -1.701 -1.493 -3.499 -3.387 -3.388 -3.106 -3.100 -1.660 3.590 -3.570 -3.494
-1.125 -1.561 -3.567 -3.351 -2.499 -3.703 -2.862 0.255 -3.382 -1.701 -1.493 -3.499 -3.387 -3.388 -3.106 -3.100 -1.660 3.590 -3.570 -3.494
-4.680 -5.426 -1.985 3.944 -5.867 -5.084 -4.280 -5.184 -5.077 -5.997 -5.243 -4.067 -6.021 -3.462 -5.260 -5.192 -5.137 -5.331 -5.546 -5.630
1.066 -1.317 -2.794 -2.822 -2.994 -2.199 -2.463 -2.119 -2.453 -2.938 -1.724 -1.633 -2.842 -2.198 -2.530 -0.042 3.381 -1.620 -3.170 -3.193
-2.420 -3.187 3.471 -0.841 -3.759 -2.013 -1.243 -3.891 -2.088 -4.084 -3.419 2.430 -3.280 -1.885 -2.658 -1.539 -2.220 -3.642 -3.697 -2.972
-3.020 -2.682 -3.650 -3.706 0.511 -3.774 -0.703 -2.867 -3.442 -2.566 -2.315 -3.050 -3.797 -3.100 -3.176 -3.117 -3.339 -2.868 -0.624 4.646
-3.103 -3.516 4.067 -0.896 -4.000 -3.519 -2.340 -3.937 -3.606 -4.255 -3.588 -0.751 -4.389 -3.174 -3.636 -3.102 -3.578 -3.722 -3.771 -3.540
-3.350 -4.868 -1.363 3.829 -4.967 -4.070 0.327 -4.542 -2.894 -4.865 -4.080 -2.830 -4.495 -2.198 -3.504 -3.617 -3.717 -4.332 -4.886 -4.356
-3.020 -2.682 -3.650 -3.706 0.511 -3.774 -0.703 -2.867 -3.442 -2.566 -2.315 -3.050 -3.797 -3.100 -3.176 -3.117 -3.339 -2.868 -0.624 4.646
letter-probability matrix: alength= 20 w= 9 n= 698
0.033540 0.006154 0.004365 0.006108 0.007124 0.005323 0.003086 0.067164 0.005611 0.028206 0.008195 0.004075 0.004845 0.003893 0.006028 0.008605 0.018803 0.774854 0.001124 0.002900
0.033540 0.006154 0.004365 0.006108 0.007124 0.005323 0.003086 0.067164 0.005611 0.028206 0.008195 0.004075 0.004845 0.003893 0.006028 0.008605 0.018803 0.774854 0.001124 0.002900
0.002854 0.000423 0.013067 0.959607 0.000690 0.002044 0.001154 0.001548 0.001733 0.001436 0.000609 0.002750 0.000780 0.003698 0.001354 0.002019 0.001688 0.001599 0.000286 0.000660
0.153230 0.007292 0.007460 0.008814 0.005058 0.015103 0.004068 0.012958 0.010685 0.011965 0.006982 0.014851 0.007069 0.008880 0.008986 0.071661 0.618934 0.020946 0.001483 0.003574
0.013675 0.001995 0.573543 0.034813 0.002975 0.017180 0.009476 0.003795 0.013761 0.005409 0.002157 0.248251 0.005217 0.011037 0.008222 0.025396 0.012748 0.005155 0.001029 0.004165
0.009018 0.002830 0.004121 0.004776 0.057415 0.005067 0.013776 0.007714 0.005383 0.015492 0.004634 0.005565 0.003645 0.004754 0.005744 0.008504 0.005873 0.008816 0.008659 0.818215
0.008517 0.001588 0.867471 0.033510 0.002519 0.006046 0.004429 0.003675 0.004803 0.004803 0.001919 0.027379 0.002418 0.004515 0.004173 0.008596 0.004974 0.004878 0.000977 0.002810
0.007177 0.000622 0.020115 0.885793 0.001288 0.004127 0.028126 0.002416 0.007867 0.003147 0.001364 0.006479 0.002247 0.008882 0.004574 0.006016 0.004518 0.003196 0.000451 0.001596
0.009018 0.002830 0.004121 0.004776 0.057415 0.005067 0.013776 0.007714 0.005383 0.015492 0.004634 0.005565 0.003645 0.004754 0.005744 0.008504 0.005873 0.008816 0.008659 0.818215
Time 18.53 secs.
Stopped because nmotifs = 3 reached.
CPU: c90
********************************************************************************
DEBUG INFORMATION
********************************************************************************
This information can also be useful in the event you wish to report a
problem with the MEME software.
model: mod= zoops nmotifs= 3 chi= 1
width: minw= 12 maxw= 55 shorten= yes
lambda: minsites= 0 maxsites= 4
theta: prob= 1 spmap= pam spfuzz= 120
em: prior= megap b= 7300 maxiter= 20
distance= 0.001
data: n= 730 N= 4
strands: w53
sample: seed= 0 seqfrac= 1
LRT: adj= root
Dirichlet mixture priors file: prior30.plib
Letter frequencies:
A 0.064 C 0.021 D 0.048 E 0.058 F 0.055 G 0.073 H 0.016 I 0.023 K 0.067
L 0.101 M 0.033 N 0.029 P 0.049 Q 0.062 R 0.037 S 0.079 T 0.078 V 0.052
W 0.018 Y 0.037
Non-redundant database letter frequencies:
A 0.073 C 0.018 D 0.052 E 0.062 F 0.040 G 0.069 H 0.022 I 0.056 K 0.058
L 0.092 M 0.023 N 0.046 P 0.051 Q 0.041 R 0.052 S 0.074 T 0.059 V 0.064
W 0.013 Y 0.033
Effective length of alphabet = 20
Entropy of dataset (bits) = -4.17
meme meme.14072.data -protein -mod zoops -nmotifs 3 -adj root -maxw 55 -minw 12 -nostatus -maxiter 20 -maxsize 10000
********************************************************************************
MAST Results are here.
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