MM-ChIP enables integrative analysis of cross-platform and between-laboratory ChIP-chip or ChIP-seq data

被引：92

作者：

Chen, Yiwen ^{[1
,2
]}

Meyer, Clifford A. ^{[1
,2
]}

Liu, Tao ^{[1
,2
]}

Li, Wei ^{[3
,4
]}

Liu, Jun S. ^{[5
]}

Liu, Xiaole Shirley ^{[1
,2
]}

机构：

[1] Dana Farber Canc Inst, Dept Biostat & Computat Biol, Boston, MA 02115 USA

[2] Harvard Univ, Sch Publ Hlth, Boston, MA 02115 USA

[3] Baylor Coll Med, Div Biostat, Dan L Duncan Canc Ctr, Dept Mol & Cellular Biol, Houston, TX 77030 USA

[4] Tongji Univ, Dept Bioinformat, Sch Life Sci & Technol, Shanghai 200092, Peoples R China

[5] Harvard Univ, Dept Stat, Cambridge, MA 02138 USA

来源：

GENOME BIOLOGY | 2011年 / 12卷 / 02期

关键词：

GENOME-WIDE ANALYSIS; CHROMATIN STATE; JOINT ANALYSIS; BINDING-SITES; INSIGHTS; MODEL; MAPS;

D O I：

10.1186/gb-2011-12-2-r11

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

The ChIP-chip and ChIP-seq techniques enable genome-wide mapping of in vivo protein-DNA interactions and chromatin states. The cross-platform and between-laboratory variation poses a challenge to the comparison and integration of results from different ChIP experiments. We describe a novel method, MM-ChIP, which integrates information from cross-platform and between-laboratory ChIP-chip or ChIP-seq datasets. It improves both the sensitivity and the specificity of detecting ChIP-enriched regions, and is a useful meta-analysis tool for driving discoveries from multiple data sources.

引用

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