Author(s): Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS,
Abstract Share this page
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.
This article was published in Genome Biol
and referenced in Journal of Proteomics & Bioinformatics