The name of the database (file name) that contains the motif.
A name for the motif that is unique in the motif database file.
An alternate name of the motif that may be provided in the motif database file.
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).
The (optimal) enrichment p-value of the motif according to the statistical test.
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.
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).
The value of the mean squared error of the linear regression of X vs Y.
The slope of the regression line: Y = mX + b.
The Y-intercept of the regression line: Y = mX + b.
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.
Logo | Database | ID | Name | Split | p-value | Corrected p-value | Spearman's Rho | Mean-squared-error | m | b |
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Database | Source | Sequence Count |
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Database | Source | Motif Count |
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