Model-based Analysis of ChIP-Seq (MACS)

Other free copies

• National Institutes of Health (ncbi.nlm.nih.gov)Preprint · Web page
• Massachusetts Institute of Technology (hdl.handle.net)Preprint · Web 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.