The name of the database (file name) that contains the motif.

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A name for the motif that is unique in the motif database file.

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An alternate name of the motif that may be provided in the motif database file.

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For statistical test methods, splitting the sorted input sequences into two partitions at this rank gives the optimal p-value. Sequences at and above this rank were treated as "positives", and sequences with larger rank were treated as "negatives" when applying the statistical test that gives the optimal p-value. For regression methods (spearman and linreg), the optimal split is the one that yields the maximum value of Spearman's rho (spearman) or the minimum mean squared error (linreg).

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The (optimal) enrichment p-value of the motif according to the statistical test.

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The corrected (optimal) enrichment p-value of the motif according to the statistical test. This is the (optimal) enrichment p-value adjusted for multiple tests using a Bonferroni correction. The number of multiple tests is given at the start of this section. If the p-value is p and the number of multiple tests is n, then the corrected p-value is 1 - (1-p)**n.

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The value of Spearman's correlation coefficient. It varies between +1 and -1. These values occur when the two ranks are perfectly correlated (+1) or anti-correlated (-1).

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The value of the mean squared error of the linear regression of X vs Y.

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The slope of the regression line: Y = mX + b.

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The Y-intercept of the regression line: Y = mX + b.

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AME (Analysis of Motif Enrichment)

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 AME in your research, please cite the following paper:
Robert McLeay and Timothy L. Bailey, "Motif Enrichment Analysis: A unified framework and method evaluation", BMC Bioinformatics, 11:165, 2010, doi:10.1186/1471-2105-11-165.

Enriched Motifs   |   Input Files   |   Program information

Enriched Motifs

Database 
ID 
Name 
Split 
p-value 
Corrected p-value 
Spearman's Rho 
Mean-squared-error 

Input Files

Sequences

DatabaseSourceSequence Count

Motifs

DatabaseSourceMotif Count
AME version
(Release date: )
Copyright © Robert McLeay r.mcleay@imb.uq.edu.au & Timothy Bailey t.bailey@imb.uq.edu.au, 2009.
Reference
Robert McLeay and Timothy L. Bailey, "Motif Enrichment Analysis: A unified framework and method evaluation", BMC Bioinformatics, 11:165, 2010, doi:10.1186/1471-2105-11-165.
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