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

  • Yiwen Chen
  • , Clifford A. Meyer
  • , Tao Liu
  • , Wei Li
  • , Jun S. Liu
  • , Xiaole Shirley Liu
  • Harvard University
  • Baylor College of Medicine
  • Tongji University

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

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.

Original languageEnglish
Article numberR11
JournalGenome Biology
Volume12
Issue number2
DOIs
StatePublished - Feb 1 2011

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