Journal Article

W-ChIPMotifs: a web application tool for <i>de novo</i> motif discovery from ChIP-based high-throughput data

Victor X. Jin, Jeff Apostolos, Naga Satya Venkateswara Ra Nagisetty and Peggy J. Farnham

in Bioinformatics

Volume 25, issue 23, pages 3191-3193
Published in print December 2009 | ISSN: 1367-4803
Published online October 2009 | e-ISSN: 1460-2059 | DOI: https://dx.doi.org/10.1093/bioinformatics/btp570

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Summary: W-ChIPMotifs is a web application tool that provides a user friendly interface for de novo motif discovery. The web tool is based on our previous ChIPMotifs program which is a de novo motif finding tool developed for ChIP-based high-throughput data and incorporated various ab initio motif discovery tools such as MEME, MaMF, Weeder and optimized the significance of the detected motifs by using a bootstrap resampling statistic method and a Fisher test. Use of a randomized statistical model like bootstrap resampling can significantly increase the accuracy of the detected motifs. In our web tool, we have modified the program in two aspects: (i) we have refined the P-value with a Bonferroni correction; (ii) we have incorporated the STAMP tool to infer phylogenetic information and to determine the detected motifs if they are novel and known using the TRANSFAC and JASPAR databases. A comprehensive result file is mailed to users.

Availability: http://motif.bmi.ohio-state.edu/ChIPMotifs. Data used in the article may be downloaded from http://motif.bmi.ohio-state.edu/ChIPMotifs/examples.shtml.

Contact: victor.jin@osumc.edu

Journal Article.  1451 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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