Systematic evaluation of factors influencing ChIP-seq fidelity

Yiwen Chen, Nicolas Negre, Qunhua Li, Joanna O. Mieczkowska, Matthew Slattery, Tao Liu, Yong Zhang, Tae Kyung Kim, Housheng Hansen He, Jennifer Zieba, Yijun Ruan, Peter J. Bickel, Richard M. Myers, Barbara J. Wold, Kevin P. White, Jason D. Lieb, X. Shirley Liu

Research output: Contribution to journalArticlepeer-review

120 Scopus citations


We evaluated how variations in sequencing depth and other parameters influence interpretation of chromatin immunoprecipitation-sequencing (ChIP-seq) experiments. Using Drosophila melanogaster S2 cells, we generated ChIP-seq data sets for a site-specific transcription factor (Suppressor of Hairy-wing) and a histone modification (H3K36me3). We detected a chromatin-state bias: open chromatin regions yielded higher coverage, which led to false positives if not corrected. This bias had a greater effect on detection specificity than any base-composition bias. Paired-end sequencing revealed that single-end data underestimated ChIP-library complexity at high coverage. Removal of reads originating at the same base reduced false-positives but had little effect on detection sensitivity. Even at mappable-genome coverage depth of ∼1 read per base pair, ∼1% of the narrow peaks detected on a tiling array were missed by ChIP-seq. Evaluation of widely used ChIP-seq analysis tools suggests that adjustments or algorithm improvements are required to handle data sets with deep coverage.

Original languageEnglish (US)
Pages (from-to)609-614
Number of pages6
JournalNature methods
Issue number6
StatePublished - Jun 2012

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology


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