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MUSIC: identification of enriched regions in ChIP-Seq experiments using a mappability-corrected multiscale signal processing framework

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 multi...

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Detalles Bibliográficos
Autores principales: Harmanci, Arif, Rozowsky, Joel, Gerstein, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4234855/
https://www.ncbi.nlm.nih.gov/pubmed/25292436
http://dx.doi.org/10.1186/s13059-014-0474-3
Descripción
Sumario: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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-014-0474-3) contains supplementary material, which is available to authorized users.