jMOSAiCS: joint analysis of multiple ChIP-seq datasets.

jMOSAiCS: joint analysis of multiple ChIP-seq datasets.
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JMosaics:多个芯片序列数据集的联合分析。

DOI:
10.1186/gb-2013-14-4-r38
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发表时间:
2013-04-29
期刊:
影响因子:
12.3
通讯作者:
Keleş S
Keleş S
中科院分区:
生物学1区
文献类型:
--
作者:
Zeng X;Sanalkumar R;Bresnick EH;Li H;Chang Q;Keleş S

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CHIP-SEQ技术使体内蛋白质-DNA相互作用和染色质状态的基因组图谱成为可能。目前用于芯片序列分析的分析方法在很大程度上是面向单一样本调查的,在旨在确定跨多个数据集的组合浓缩模式的比较环境中的适用性有限。我们描述了一种新的概率方法jMOSAiCS,用于联合分析多个芯片序列数据集。我们通过广泛的数据驱动的计算实验和在红系分化过程中组蛋白修饰GATA1占据的片段的案例研究来证明它的有效性。JMOSAiCS是开源软件,可以从BioConductor下载。
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.
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