bioRxivBioinformaticsPreprint
normR: Regime enrichment calling for ChIP-seq data
Johannes HelmuthiD, Na LiiD, Laura ArrigoniiD, Kathrin GianmoenaiD, Cristina CadenasiD, Gilles GasparoniiD, Anupam N. SinhaiD, Philip C RosenstieliD, Jörn WalteriD, Jan Georg HengstleriD, Thomas MankeiD, Ho‐Ryun ChungiD
Abstract
ChIP-seq probes genome-wide localization of DNA-associated proteins. To mitigate technical biases ChIP-seq read densities are normalized to read densities obtained by a control. Our statistical framework \"normR\" achieves a sensitive normalization by accounting for the effect of putative protein-bound regions on the overall read statistics. Here, we demonstrate normRs suitability in three studies: (i) calling enrichment for high (H3K4me3) and low (H3K36me3) signal-to-ratio data; (ii) identifying two previously undescribed H3K27me3 and H3K9me3 heterochromatic regimes of broad and peak enrichment; and (iii) calling differential H3K4me3 or H3K27me3-enrichment between HepG2 hepatocarcinoma cells and primary human Hepatocytes. normR is readily available on http://bioconductor.org/packages/normr
- organism: human
- assay: ChIP-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 15
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