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JMOSAiCS: joint analysis of multiple ChIP-seq datasets.

ABSTRACT: 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.

SUBMITTER: Zeng X

PROVIDER: S-EPMC4053760 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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jMOSAiCS: joint analysis of multiple ChIP-seq datasets.

Zeng Xin X Sanalkumar Rajendran R Bresnick Emery H EH Li Hongda H Chang Qiang Q Keleş Sündüz S

Genome biology 20130429 4

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 ...[more]

PMID: 23844871

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