title: 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 atmusic.gersteinlab.org. MUSIC first filters the ChIP-Seq read-depth signal for systematic noise from non-uniformmappability, 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.
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
authors.forename: Arif
authors.initials: A
authors.lastname: Harmanci
authors.forename: Joel
authors.initials: J
authors.lastname: Rozowsky
authors.forename: Mark
authors.initials: M
authors.lastname: Gerstein
mesh_terms: D000465:Algorithms; D042002:Chromatin Assembly and Disassembly; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D015870:Gene Expression; D006801:Humans; D020014:K562 Cells; D012319:RNA Polymerase II / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results; D017421:Sequence Analysis / Q000379:methods
chemical_list: D012319:RNA Polymerase II