Details

Autor(en) / Beteiligte

• Zeng, Xin
• Sanalkumar, Rajendran
• Bresnick, Emery H
• Li, Hongda
• Chang, Qiang
• Keleş, Sündüz

Titel

jMOSAiCS: joint analysis of multiple ChIP-seq datasets

Ist Teil von

• Genome biology, 2013-04, Vol.14 (4), p.R38-R38

Ort / Verlag

England: BioMed Central Ltd

Erscheinungsjahr

2013

Link zum Volltext

Quelle

SpringerLink

Beschreibungen/Notizen

• The ChIP-seq technique enables genome-wide mapping of in vivo protein-DNA interactions and chromatin states. Current analytical approaches for ChIP-seq analysis are largely geared towards single-sample investigations, and have limited applicability in comparative settings that aim to identify combinatorial patterns of enrichment across multiple datasets. We describe a novel probabilistic method, jMOSAiCS, for jointly analyzing multiple ChIP-seq datasets. We demonstrate its usefulness with a wide range of data-driven computational experiments and with a case study of histone modifications on GATA1-occupied segments during erythroid differentiation. jMOSAiCS is open source software and can be downloaded from Bioconductor 1.