Integrative Analysis of Histone ChIP‐seq and RNA‐seq Data. (1st July 2016)

• Record Type: Journal Article
• Authors: Klein, Hans‐Ulrich; Schäfer, Martin
• Editors: Haines, Jonathan L.; Korf, Bruce R.; Morton, Cynthia C.; Seidman, Christine E.; Seidman, J.G.; Smith, Douglas R.
• Is Part Of: Current protocols in human genetics. Volume 90(2016)
• Page Start: 20.3.1
• Page End: 20.3.16
• Publication Date: 2016-07-01
• Subjects: Bayesian mixture model -- data integration -- differential ChIP‐seq analysis -- differential gene expression; Human genetics -- Laboratory manuals; Genetic Techniques; Human genetics; Laboratory manuals; 599.935028
• DOI: 10.1002/cphg.17
• Languages: English
• ISSNs: 1934-8258

Abstract

Abstract: The R package epigenomix has been designed to detect differentially transcribed gene isoforms that, in addition, exhibit altered histone modifications at their respective genomic loci. The package provides methods to map histone ChIP‐seq profiles to isoforms and estimate their transcript abundances from RNA‐seq data. Based on the differences observed between case and control samples in the RNA‐seq and ChIP‐seq data, a correlation measure is calculated for each isoform. The distribution of this correlation measure is further investigated by a Bayesian mixture model to (i) reveal the relationship between the studied histone modification and transcriptional activity, and (ii) detect specific isoforms with differences in both transcription values and histone modifications. The method is designed for experiments with a few or no replicates, and is superior to separate analyses of both data types in that setting. This unit illustrates the integrative analysis of ChIP‐seq and RNA‐seq data with epigenomix. © 2016 by John Wiley & Sons, Inc.