Systematic evaluation of factors influencing ChIP-seq fidelity

The authors analyze how sequencing depth, choice of control sample, paired-end versus single-end reads and the selection of peak-calling algorithm influence the interpretation of chromatin immunoprecipitation–sequencing (ChIP-seq) experiments. 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.