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PMID: 22522655 Published · ppublish English Journal Article Research Support, N.I.H., Extramural

Systematic evaluation of factors influencing ChIP-seq fidelity.

Nature methods ·Vol. 9 ·No. 6 ·2012-06-00 ·Pages 609-14

Chen Y, Negre N, Li Q, Mieczkowska JO, Slattery M, Liu T, Zhang Y, Kim TK, He HH, Zieba J, Ruan Y, Bickel PJ, Myers RM, Wold BJ, White KP, Lieb JD, Liu XS

Abstract

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.

MeSH Terms
Algorithms Animals Chromatin/chemistry Chromatin Immunoprecipitation/methods,standards Drosophila Proteins/genetics Drosophila melanogaster False Positive Reactions Gene Library High-Throughput Nucleotide Sequencing Histone-Lysine N-Methyltransferase/genetics Oligonucleotide Array Sequence Analysis Repressor Proteins/genetics Sensitivity and Specificity
Chemicals
Chromatin Drosophila Proteins Repressor Proteins su(Hw) protein, Drosophila Histone-Lysine N-Methyltransferase
Authors & Affiliations
17 authors, click to expand affiliations / ORCID
Chen Yiwen
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
Negre Nicolas
Li Qunhua
Mieczkowska Joanna O
Slattery Matthew
Liu Tao
Zhang Yong
Kim Tae-Kyung
He Housheng Hansen
Zieba Jennifer
Ruan Yijun
Bickel Peter J
Myers Richard M
Wold Barbara J
White Kevin P
Lieb Jason D
Liu X Shirley
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Article Info
Journal
Nature methods
Abbr.
Nat Methods
ISSN
1548-7105
Published
2012-06-00
Epub
2012-00-22
Pages
609-14
Language
English
Region
United States
NLM ID
101215604
PMCID
PMC3477507
Subset
IM
Grants
NHGRI NIH HHS · U01 HG004264 · United States
NHGRI NIH HHS · U01HG004264 · United States
NHGRI NIH HHS · HG4069 · United States
NHGRI NIH HHS · R01 HG004069 · United States
NHGRI NIH HHS · 3U01HG004270-03S1 · United States
NHGRI NIH HHS · U01 HG004270 · United States
Databases
GEO
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