W-ChIPMotifs: A web application tool for de novo motif discovery from ChIP-based high-throughput data

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

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article numberbtp570
Pages (from-to)3191-3193
Number of pages3
JournalBioinformatics
Volume25
Issue number23
DOIs
StatePublished - Oct 1 2009
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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