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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 number of sites contributing to the construction of the motif.

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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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Click on the blue symbol below to reveal more information about this motif.

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Click on the blue symbol below to reveal options allowing you to submit this motif to another MEME Suite motif analysis program, to download this motif in various text formats, or to download a sequence "logo" of this motif PNG or EPS format.

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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These are the motif sites predicted by MEME and used to build the motif.

These sites are shown in solid color and hovering the cursor over a site will reveal details about the site. Only sequences that contain a motif site are shown.

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These are the motif sites predicted by MEME plus any additional sites detected using a motif scanning algorithm.

These MEME sites are shown in solid color and additional scanned sites are shown in transparent color. Hovering the cursor over a site will reveal details about the site. Only sequences containing a predicted or scanned motif site are shown.

The scanned sites are predicted using a log-odds scoring matrix constructed from the MEME sites. Only scanned sites with position p-values less than 0.0001 are shown.

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These are the same sites as shown by selecting the "Motif Sites + Scanned Sites" button except that all sequences, including those with no sites, are included in the diagram.

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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 position p-values such that the product is smaller or equal to the value calulated for the sequence under test.

The position 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.

Hovering your mouse over a motif site in the motif location block diagram will show its position p-value and other information about the site.

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This diagram shows the location of motif sites.

Each block shows the position and strength of a motif site. The height of a block gives an indication of the significance of the site as taller blocks are more significant. The height is calculated to be proportional to the negative logarithm of the p-value of the site, truncated at the height for a p-value of 1e-10.

For complementable alphabets (like DNA), sites on the positive strand are shown above the line, sites on the negative strand are shown below.

Placing the cursor over a motif site will reveal more information about the site including its position p-value. (See the help for the p-value column for an explanation of position p-values.)

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The name of the file of sequences input to MEME.

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The position specific priors file used by MEME to find the motifs.

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The alphabet used by the sequences.

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The number of sequences provided as input to MEME.

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The name of the alphabet symbol.

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The frequency of the alphabet symbol in the dataset with a pseudocount so it is never zero.

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The frequency of the alphabet symbol as defined by the background model.

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Motif1
p-value8.23e-7
Start23
End33
Scanned Site
Motif1
p-value8.23e-7
Start23
End33
.
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-suite.org.

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   |   Inputs & Settings   |   Program information

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Discovered Motifs

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Motif Locations

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Inputs & Settings

Sequences

Source
PSP Source
Alphabet
Sequence Count

Background

Other Settings

Motif Site Distribution ZOOPS: Zero or one site per sequence OOPS: Exactly one site per sequence ANR: Any number of sites per sequence
Site Strand Handling This alphabet only has one strand Sites must be on the given strand Sites may be on either strand
Maximum Number of Motifs
Motif E-value Threshold
Minimum Motif Width
Maximum Motif Width
Minimum Sites per Motif
Maximum Sites per Motif
Bias on Number of Sites
Sequence Prior Simple Dirichlet Dirichlets Mix Mega-weight Dirichlets Mix Mega-weight Dirichlets Mix Plus Add One
Sequence Prior Strength
EM Starting Point Source From substrings in input sequences From strings on command line (-cons)
EM Starting Point Map Type Uniform Point Accepted Mutation
EM Starting Point Fuzz
EM Maximum Iterations
EM Improvement Threshold
Trim Gap Open Cost
Trim Gap Extend Cost
End Gap Treatment No cost Same cost as other gaps
Show Advanced Settings Hide Advanced Settings
MEME version
(Release date: )
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