Discovering homotypic binding events at high spatial resolution

Bioinformatics. 2010 Dec 15;26(24):3028-34. doi: 10.1093/bioinformatics/btq590. Epub 2010 Oct 21.

Abstract

Motivation: Clusters of protein-DNA interaction events involving the same transcription factor are known to act as key components of invertebrate and mammalian promoters and enhancers. However, detecting closely spaced homotypic events from ChIP-Seq data is challenging because random variation in the ChIP fragmentation process obscures event locations.

Results: The Genome Positioning System (GPS) can predict protein-DNA interaction events at high spatial resolution from ChIP-Seq data, while retaining the ability to resolve closely spaced events that appear as a single cluster of reads. GPS models observed reads using a complexity penalized mixture model and efficiently predicts event locations with a segmented EM algorithm. An optional mode permits GPS to align common events across distinct experiments. GPS detects more joint events in synthetic and actual ChIP-Seq data and has superior spatial resolution when compared with other methods. In addition, the specificity and sensitivity of GPS are superior to or comparable with other methods.

Availability: http://cgs.csail.mit.edu/gps.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Binding Sites
  • Chromatin Immunoprecipitation / methods*
  • DNA-Binding Proteins / metabolism*
  • Genome
  • Models, Statistical
  • Sequence Analysis, DNA
  • Transcription Factors / metabolism

Substances

  • DNA-Binding Proteins
  • Transcription Factors