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normR: Regime enrichment calling for ChIP-seq data

Authors :
Gilles Gasparoni
Johannes Helmuth
Thomas Manke
Jan G. Hengstler
Kathrin Gianmoena
Na Li
Cristina Cadenas
Ho Ryun Chung
Laura Arrigoni
Joern Walter
Philip Rosenstiel
Anupam Sinha
Publication Year :
2016
Publisher :
Cold Spring Harbor Laboratory, 2016.

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 normR’s 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

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....d8f5efbff204411d2ee57a3ab0b948c3
Full Text :
https://doi.org/10.1101/082263