Improving MEME via a two-tiered significance analysis

Tanaka, Emi, Bailey, Timothy L. and Keich, Uri (2014) Improving MEME via a two-tiered significance analysis. Bioinformatics, 30 14: 1965-1973. doi:10.1093/bioinformatics/btu163


Author Tanaka, Emi
Bailey, Timothy L.
Keich, Uri
Title Improving MEME via a two-tiered significance analysis
Journal name Bioinformatics   Check publisher's open access policy
ISSN 1367-4811
1367-4803
Publication date 2014-01-01
Year available 2014
Sub-type Article (original research)
DOI 10.1093/bioinformatics/btu163
Open Access Status DOI
Volume 30
Issue 14
Start page 1965
End page 1973
Total pages 9
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Language eng
Formatted abstract
Motivation: With over 9000 unique users recorded in the first half of 2013, MEME is one of the most popular motif-finding tools available. Reliable estimates of the statistical significance of motifs can greatly increase the usefulness of any motif finder. By analogy, it is difficult to imagine evaluating a BLAST result without its accompanying E-value. Currently MEME evaluates its EM-generated candidate motifs using an extension of BLAST’s E-value to the motif-finding context. Although we previously indicated the drawbacks of MEME’s current significance evaluation, we did not offer a practical substitute suited for its needs, especially because MEME also relies on the E-value internally to rank competing candidate motifs.

Results: Here we offer a two-tiered significance analysis that can replace the E-value in selecting the best candidate motif and in evaluating its overall statistical significance. We show that our new approach could substantially improve MEME’s motif-finding performance and would also provide the user with a reliable significance analysis. In addition, for large input sets, our new approach is in fact faster than the currently implemented E-value analysis.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published online ahead of print 24 March 2014

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
Institute for Molecular Bioscience - Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 8 times in Thomson Reuters Web of Science Article | Citations
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Created: Thu, 22 May 2014, 20:31:52 EST by Susan Allen on behalf of Institute for Molecular Bioscience