Autor(en)
Zeng, Xin; Sanalkumar, Rajendran; Bresnick, Emery H; Li, Hongda; Chang, Qiang; Keles, Suenduez
Titel
jMOSAiCS: joint analysis of multiple ChIP-seq datasets
Teil von
  • Genome biology, 2013-01-01, Vol.14 (4), p.R38-R38
Ort / Verlag
LONDON: BMC
Links zum Volltext
Quelle
BioMedCentral
Beschreibungen
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].
Format
Sprache(n)
Englisch
Identifikator(en)
ISSN: 1474-760X
ISSN: 1465-6906
ISSN: 1474-760X
ISSN: 1465-6914
DOI: 10.1186/gb-2013-14-4-r38

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