MUSIC: Identification of Enriched Regions in ChIP-Seq Experiments using a Mappability-Corrected Multiscale Signal Processing Framework

Abstract

We present MUSIC, a signal processing approach for identification of enriched regions in ChIP-Seq data, available at music.gersteinlab.org. MUSIC first filters the ChIP-Seq read-depth signal for systematic noise from non-uniform mappability, which fragments enriched regions. Then it performs a multiscale decomposition, using median filtering, identifying enriched regions at multiple length scales. This is useful given the wide range of scales probed in ChIP-Seq assays. MUSIC performs favorably in terms of accuracy and reproducibility compared with other methods. In particular, analysis of RNA Polymerase II data reveals a clear distinction between the stalled and elongating forms of the polymerase.