Systematic Evaluation of Factors Influencing ChIP-Seq Fidelity
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Author
Negre, Nicolas
Li, Qunhua
Mieczkowska, Joanna O.
Slattery, Matthew
Kim, Tae-Kyung
Zieba, Jennifer
Ruan, Yijun
Bickel, Peter J.
Wold, Barbara J.
Lieb, Jason D.
Zhang, Yong
Myers, Richard M.
White, Kevin P.
Note: Order does not necessarily reflect citation order of authors.
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https://doi.org/10.1038/nmeth.1985Metadata
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Chen, Yiwen, Nicolas Negre, Qunhua Li, Joanna O. Mieczkowska, Matthew Slattery, Tao Liu, Yong Zhang, et al. 2012. Systematic evaluation of factors influencing ChIP-seq fidelity. Nature Methods 9(6): 609-614.Abstract
We performed a systematic evaluation of how variations in sequencing depth and other parameters influence interpretation of Chromatin immunoprecipitation (ChIP) followed by sequencing (ChIP-seq) experiments. Using Drosophila S2 cells, we generated ChIP-seq datasets 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 and 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. The removal of reads originating at the same base reduced false-positives while having little effect on detection sensitivity. Even at a depth of ~1 read/bp coverage of mappable genome, ~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 datasets with deep coverage.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3477507/pdf/Terms of Use
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