title: Integrative Analysis of Histone ChIP-seq and RNA-seq Data.
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.
authors.affiliation: Program in Translational NeuroPsychiatric Genomics, Brigham and Women's Hospital, Boston, Massachusetts.|Harvard Medical School, Boston, Massachusetts.|Institute of Medical Informatics, University of Münster, Münster, Germany.
authors.forename: Hans-Ulrich
authors.initials: HU
authors.lastname: Klein
authors.affiliation: Mathematical Institute, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Schäfer
mesh_terms: D001499:Bayes Theorem; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D006657:Histones / Q000737:chemistry* / Q000378:metabolism*; D006801:Humans; D012313:RNA / Q000235:genetics* / Q000378:metabolism*; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software; D014158:Transcription, Genetic
chemical_list: D006657:Histones; D012313:RNA
keywords: Bayesian mixture model; data integration; differential ChIP-seq analysis; differential gene expression