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jMOSAiCS:多个ChIP-seq数据集的联合分析

jMOSAiCS: joint analysis of multiple ChIP-seq datasets.

作者信息

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

出版信息

Genome Biol. 2013 Apr 29;14(4):R38. doi: 10.1186/gb-2013-14-4-r38.

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.

摘要

染色质免疫沉淀测序(ChIP-seq)技术能够在全基因组范围内绘制体内蛋白质与DNA的相互作用以及染色质状态。当前用于ChIP-seq分析的方法主要针对单样本研究,在旨在识别多个数据集中富集组合模式的比较分析中适用性有限。我们描述了一种新的概率方法jMOSAiCS,用于联合分析多个ChIP-seq数据集。我们通过一系列数据驱动的计算实验以及对红细胞分化过程中GATA1占据片段上组蛋白修饰的案例研究,证明了它的实用性。jMOSAiCS是开源软件,可从生物导体(Bioconductor)获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74f5/4053760/ee4e74904b4f/gb-2013-14-4-r38-1.jpg

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