Model-based Analysis of ChIP-Seq (MACS)

Genome Biol. 2008;9(9):R137. doi: 10.1186/gb-2008-9-9-r137. Epub 2008 Sep 17.

Abstract

We present Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer. MACS empirically models the shift size of ChIP-Seq tags, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions. MACS compares favorably to existing ChIP-Seq peak-finding algorithms, and is freely available.

Publication types

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

MeSH terms

  • Algorithms*
  • Cell Line, Tumor
  • Chromatin Immunoprecipitation / methods*
  • Hepatocyte Nuclear Factor 3-alpha / analysis
  • Hepatocyte Nuclear Factor 3-alpha / genetics*
  • Humans
  • Models, Genetic
  • Oligonucleotide Array Sequence Analysis / methods*

Substances

  • FOXA1 protein, human
  • Hepatocyte Nuclear Factor 3-alpha