RSAT peak-motifs: motif analysis in full-size ChIP-seq datasets

Nucleic Acids Res. 2012 Feb;40(4):e31. doi: 10.1093/nar/gkr1104. Epub 2011 Dec 8.

Abstract

ChIP-seq is increasingly used to characterize transcription factor binding and chromatin marks at a genomic scale. Various tools are now available to extract binding motifs from peak data sets. However, most approaches are only available as command-line programs, or via a website but with size restrictions. We present peak-motifs, a computational pipeline that discovers motifs in peak sequences, compares them with databases, exports putative binding sites for visualization in the UCSC genome browser and generates an extensive report suited for both naive and expert users. It relies on time- and memory-efficient algorithms enabling the treatment of several thousand peaks within minutes. Regarding time efficiency, peak-motifs outperforms all comparable tools by several orders of magnitude. We demonstrate its accuracy by analyzing data sets ranging from 4000 to 1,28,000 peaks for 12 embryonic stem cell-specific transcription factors. In all cases, the program finds the expected motifs and returns additional motifs potentially bound by cofactors. We further apply peak-motifs to discover tissue-specific motifs in peak collections for the p300 transcriptional co-activator. To our knowledge, peak-motifs is the only tool that performs a complete motif analysis and offers a user-friendly web interface without any restriction on sequence size or number of peaks.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Chromatin Immunoprecipitation*
  • Embryonic Stem Cells / metabolism
  • Mice
  • Nucleotide Motifs
  • Regulatory Elements, Transcriptional*
  • Sequence Analysis, DNA*
  • Software*
  • Transcription Factors / metabolism
  • User-Computer Interface
  • p300-CBP Transcription Factors / metabolism

Substances

  • Transcription Factors
  • p300-CBP Transcription Factors