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The statistical significance of the motif. MEME usually finds the most statistically significant (low E-value) motifs first. It is unusual to consider a motif with an E-value larger than 0.05 significant so, as an additional indicator, MEME displays these partially transparent.

The E-value of a motif is based on its log likelihood ratio, width, sites, the background letter frequencies (given in the command line summary), and the size of the training set.

The E-value is an estimate of the expected number of motifs with the given log likelihood ratio (or higher), and with the same width and site count, that one would find in a similarly sized set of random sequences (sequences where each position is independent and letters are chosen according to the background letter frequencies).

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The width of the motif. Each motif describes a pattern of a fixed width, as no gaps are allowed in MEME motifs.

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Submit your motif to another MEME Suite program or download in various text formats or as a logo.

Supported Programs
Tomtom
Tomtom is a tool for searching for similar known motifs. [manual]
MAST
MAST is a tool for searching biological sequence databases for sequences that contain one or more of a group of known motifs. [manual]
FIMO
FIMO is a tool for searching biological sequence databases for sequences that contain one or more known motifs. [manual]
GOMO
GOMO is a tool for identifying possible roles (Gene Ontology terms) for DNA binding motifs. [manual]
SpaMo
SpaMo is a tool for inferring possible transcription factor complexes by finding motifs with enriched spacings. [manual]
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The log likelihood ratio of the motif.The log likelihood ratio is the logarithm of the ratio of the probability of the occurrences of the motif given the motif model (likelihood given the motif) versus their probability given the background model (likelihood given the null model). (Normally the background model is a 0-order Markov model using the background letter frequencies, but higher order Markov models may be specified via the -bfile option to MEME.).

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The information content of the motif in bits. It is equal to the sum of the uncorrected information content, R(), in the columns of the pwm. This is equal relative entropy of the motif relative to a uniform background frequency model.

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The relative entropy of the motif.

re = llr / (sites * ln(2))

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The Bayes Threshold.

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The strand used for the motif site.

+
The motif site was found in the sequence as it was supplied.
-
The motif site was found in the reverse complement of the supplied sequence.
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The position in the sequence where the motif site starts. If a motif started right at the begining of a sequence it would be described as starting at position 1.

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The probability that an equal or better site would be found in a random sequence of the same length conforming to the background letter frequencies.

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A motif site with the 10 flanking letters on either side.

When the site is not on the given strand then the site and both flanks are reverse complemented so they align.

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The name of the sequences as given in the FASTA file.

The number to the left of the sequence name is the ordinal of the sequence.

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This is the combined match p-value.

The combined match p-value is defined as the probability that a random sequence (with the same length and conforming to the background) would have motif-sequence match p-values such that the product is smaller or equal to the value calulated for the sequence under test.

The motif-sequence match p-value is defined as the probability that a random sequence (with the same length and conforming to the background) would have a match to the motif under test with a score greater or equal to the largest found in the sequence under test.

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This diagram shows the location of motif sites.

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Motif1
p-value8.23e-7
Start23
End33
Scanned Site
Motif1
p-value8.23e-7
Start23
End33
.
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E-value:
Site Count:
Width:
StandardReverse Complement
Log Likelihood Ratio:
Information Content:
Relative Entropy:
Bayes Threshold:

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

If you use MEME in your research, please cite the following paper:
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. [pdf]

Discovered Motifs   |   Motif Locations   |   Program information

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Discovered Motifs

1.
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E-value: 8.7e-023
Site Count: 65
Width: 14
StandardReverse Complement
Log Likelihood Ratio: 443
Information Content: 9.5
Relative Entropy: 9.8
Bayes Threshold: 5.87247
Name 
Name 
Strand 
Strand 
Start 
Start 
p-value 
p-value 
Sites 
Sites 
95.Af95+223.34e-7TCATGACGGTGTGAGGTGGTGAAAA
62.Af62+221.30e-6AGGCTTAAAGGTGAGGTGGTAGAAA
3.Af3+226.03e-6GAAAATACGCAGGAGGTGGTGTTAA
1.Af1+237.19e-6TTTTCTAATTTGGAGGTGTTTAGA
73.Af73+178.57e-6TTCAAGCTTGAGGAGGAGGTTTACGTGAGG
31.Af31+238.57e-6TCAAGAAATCTGGAGGTGTTGTGA
18.Af18+231.02e-5CGGACTTTAAGGGGGGAGTTTAGA
99.Af99-101.40e-5GCAGGGTAGAATGGGGAGGTATAAACCTTTACC
35.Af35+201.63e-5GCAATCGCTAAGGAGGAGGGATTAAGA
72.Af72+52.20e-5AGGCGGGAGATGGTTGAGTTTATCAGAA
54.Af54+192.20e-5TGTTTTTGACTTAAGGAGGGAAGAGAAA
68.Af68+212.55e-5TTGCCATGAAGCAAGGTGGTGGAAGA
79.Af79+132.94e-5CTCGAGAAGGTTGAGGAGCTTAAGGGGTGATAAA
32.Af32+202.94e-5GATGATTTGATGAAGGAGGTGATGACA
21.Af21+213.38e-5ATTGGAATTCTGGAGGTGATGTTAAA
65.Af65+233.88e-5CGCTACATGATGGAGGTGTGCAGA
56.Af56+234.45e-5CGCTGGGACTACGGGGTGGTAAGA
86.Af86+105.09e-5GTTGACTCGGTCAGAAGGTTGAAAGAAGTGGTT
45.Af45+25.09e-5CTGGAGAAGATTAGAAAGAATCTGC
53.Af53+116.62e-5AGGCCTGTGCAGGAGGAAGTAATAAGGAGAATAT
98.Af98+197.52e-5TCTGAAGCACAGGAGGAAGATAAAGGCA
28.Af28-67.52e-5AAAAACCAGCTTGGGGTGGTCAACGTCAA
97.Af97+228.51e-5TAAAAGGTTGAGGAGGAAGTTTGCA
82.Af82-118.51e-5CCTTAAATTGGCCGGGTGGTAAAAATAGGTTTTT
27.Af27-88.51e-5AAGCGACAAATGGAGGAGTAATAAATTTTTC
77.Af77-59.61e-5CCAAAAGTTTTTGAGGAAGTCTTAACAA
52.Af52+239.61e-5ATGAGATTCAGGGAGGTGTACAGA
10.Af10-19.61e-5TCTCAAATCGTTCAGGAAGGGGAA
58.Af58+31.08e-4CGATGGGGAGGATGGGTTGATAGTTT
49.Af49+231.08e-4GGATGAGGAACTGAGGTGATTGGA
71.Af71+231.37e-4TACGCTGAGGGTGAGGAAGATTGG
39.Af39+141.37e-4TTGGAAATCGTTGAAGAGGTGGAGGAGTACGTA
38.Af38+231.71e-4TGATATAGTAGAAGGGTGGTTTGA
36.Af36-31.71e-4TCTCGGTTGATGAAGGGGATTAGAGC
40.Af40+171.91e-4AAAATCAAGCTTGGAGTGGTGAGAGAGATA
11.Af11+231.91e-4TTCAATAAAAAAGGGGTGGTGGTA
51.Af51+222.37e-4TGGGCCTGGAGTAGGGGGGTGTAGA
57.Af57+182.63e-4TCCGGTGTCAGTGAGAAGGGGATCGACAA
6.Af6+192.92e-4CTGGTACCACTTCAGGAAGGTGTAACAA
89.Af89+213.23e-4GGAGATTCTTGTCAGGTGGTTTCAAA
78.Af78+223.23e-4AAGGAGCTTCTGGAGGCGATTTAAA
43.Af43+113.56e-4CAGCGGTCATTGCAGCTGGAGAAATATACTGGGG
74.Af74+193.93e-4AAGGGCGATAGAGAGGATGTTTGAGCTA
8.Af8+163.93e-4GATCGAAGATGCGAAGAGGGCTGAGAGGTTA
64.Af64-34.32e-4AAGAAGAACGCTCAGCAGGTTAAAGT
9.Af9+205.71e-4GTTATAGCCTATAAAGAGGTGGAAGCA
84.Af84-16.82e-4TCTTTCTGTCATGAGGGAGGCAGG
69.Af69+226.82e-4GATATACGCACCAAGGAGGGAGAGA
5.Af5+56.82e-4GTACGGAAGGTACTGAAGCTGTTGGAGG
48.Af48+127.44e-4AAAGATATATGGCGGGAGCGAAACTCTTCACTCC
23.Af23+28.10e-4AGGGAGAGGCTCAAGCTTAAGAAAT
19.Af19-208.10e-4TCTATCAGAAAGTTTAAATTAAGCATT
13.Af13+38.10e-4TTTGAAGAAGAGGAGGCACGTCATTC
76.Af76+219.56e-4TGCAAAAAGAGAAAGGTGAGATGACA
59.Af59+101.04e-3GAGACGATTTACAGCAGGGCAAATCTGAGAGAG
37.Af37+211.04e-3AAAAACTGCCTGAAGGTGTAAGAGCA
30.Af30+51.04e-3TCCCGGCGGGGGCATGGAATTTTTAATG
44.Af44+211.21e-3AATGAGTTCGTAGGGATGATGGAACA
14.Af14-81.53e-3CCTTAAAAAAAGGAGGGATATAAAAAATTTT
2.Af2-91.64e-3GAATCCCCTCTTAAGCAGAGATGAGTGCTAAA
29.Af29+101.89e-3TCGAGGAACTTGAGAAGCTCGTCGGATTGAAAT
24.Af24-61.89e-3GTTGCTTGAGTCGAGGATTTATAAAACTA
93.Af93+132.03e-3ACCTCAAGAAGGCGGCTGAGATAATCAGGGAGTA
46.Af46+172.83e-3GGCCTGAGGCCCGAGAAAGTTATGAGGGAG
22.Af22-72.83e-3ATCGTAAATCTCGAGAAAGGTTTCAACAAG
E-value 
Sites 
Width 
More 
Submit/Download 
2.4.7e+003634
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⇢
3.2.3e+00479
↧
⇢

Motif Locations

Name 
Name 
p-value 
p-value 
Motif Location 
Motif Location 
1.Af12.99e-3
+
-
2.Af22.50e-1
+
-
3.Af33.89e-3
+
-
4.Af42.18e-1
+
-
5.Af52.37e-1
+
-
6.Af61.11e-1
+
-
7.Af74.46e-3
+
-
8.Af81.72e-1
+
-
9.Af91.23e-1
+
-
10.Af106.84e-2
+
-
11.Af111.52e-2
+
-
12.Af129.95e-1
+
-
13.Af131.41e-1
+
-
14.Af144.57e-5
+
-
15.Af158.42e-8
+
-
16.Af164.84e-1
+
-
17.Af175.73e-8
+
-
18.Af187.68e-3
+
-
19.Af195.43e-3
+
-
20.Af204.76e-3
+
-
21.Af211.58e-2
+
-
22.Af224.68e-1
+
-
23.Af238.86e-3
+
-
24.Af246.44e-4
+
-
25.Af253.84e-1
+
-
26.Af263.33e-1
+
-
27.Af271.29e-2
+
-
28.Af282.88e-3
+
-
29.Af291.07e-1
+
-
30.Af301.13e-1
+
-
31.Af312.70e-3
+
-
32.Af321.57e-2
+
-
33.Af334.56e-1
+
-
34.Af347.72e-2
+
-
35.Af352.24e-2
+
-
36.Af363.26e-2
+
-
37.Af373.81e-4
+
-
38.Af387.04e-3
+
-
39.Af393.69e-2
+
-
40.Af407.39e-2
+
-
41.Af417.35e-2
+
-
42.Af425.28e-9
+
-
43.Af434.42e-2
+
-
44.Af441.53e-1
+
-
45.Af452.34e-2
+
-
46.Af465.11e-1
+
-
47.Af474.35e-1
+
-
48.Af488.92e-2
+
-
49.Af491.67e-2
+
-
50.Af501.94e-1
+
-
51.Af511.19e-1
+
-
52.Af527.80e-2
+
-
53.Af534.22e-2
+
-
54.Af544.86e-3
+
-
55.Af554.54e-5
+
-
56.Af565.23e-2
+
-
57.Af571.70e-1
+
-
58.Af584.64e-2
+
-
59.Af593.08e-1
+
-
60.Af608.64e-1
+
-
61.Af614.76e-1
+
-
62.Af629.49e-4
+
-
63.Af633.03e-1
+
-
64.Af641.40e-1
+
-
65.Af653.54e-2
+
-
66.Af665.00e-1
+
-
67.Af678.78e-1
+
-
68.Af683.37e-2
+
-
69.Af692.92e-1
+
-
70.Af704.16e-8
+
-
71.Af719.31e-2
+
-
72.Af727.41e-3
+
-
73.Af735.33e-3
+
-
74.Af748.74e-2
+
-
75.Af752.44e-3
+
-
76.Af769.06e-2
+
-
77.Af771.90e-2
+
-
78.Af781.72e-1
+
-
79.Af792.80e-2
+
-
80.Af807.43e-1
+
-
81.Af811.16e-2
+
-
82.Af821.84e-2
+
-
83.Af831.12e-1
+
-
84.Af841.06e-1
+
-
85.Af855.19e-1
+
-
86.Af861.64e-2
+
-
87.Af871.15e-1
+
-
88.Af884.60e-1
+
-
89.Af895.18e-2
+
-
90.Af907.02e-7
+
-
91.Af911.36e-1
+
-
92.Af924.71e-2
+
-
93.Af931.33e-1
+
-
94.Af944.16e-1
+
-
95.Af951.04e-3
+
-
96.Af962.94e-2
+
-
97.Af972.36e-2
+
-
98.Af982.52e-2
+
-
99.Af991.14e-2
+
-
100.Af1002.16e-8
+
-
MEME version
4.10.0 (Release date: Wed May 21 10:35:36 2014 +1000)
Reference
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.
Command line summary