Model-based Analysis of ChIP-Seq (MACS)

Overview

Journal Genome Biol

Specialties Biology
Genetics

Date 2008 Sep 19

PMID 18798982

Citations 9553

Authors

Yong Zhang

Tao Liu

Clifford A Meyer

Jerome Eeckhoute

David S Johnson

Bradley E Bernstein

Chad Nusbaum

Richard M Myers

Myles Brown

Wei Li

X Shirley Liu

Affiliations

Soon will be listed here.

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.

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