@article{a517977b267d403ebf38fa7740d204ed,
title = "Integrative analysis of histone ChIP-seq and transcription data using Bayesian mixture models",
abstract = "Histone modifications are a key epigenetic mechanism to activate or repress the transcription of genes. Datasets of matched transcription data and histone modification data obtained by ChIP-seq exist, but methods for integrative analysis of both data types are still rare. Here, we present a novel bioinformatics approach to detect genes that show different transcript abundances between two conditions putatively caused by alterations in histone modification.",
author = "Hans-Ulrich Klein and Martin Sch{\"a}fer and Porse, {Bo T} and Hasemann, {Marie S} and Katja Ickstadt and Martin Dugas",
note = " D-48149 M{\"u}nster, Mathematical Institute, Heinrich Heine University, D-40225 D{\"u}sseldorf, Germany, The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, Biotech Research and Innovation Center (BRIC), Danish Stem Cell Centre (DanStem), Faculty of Health Sciences, University of Copenhagen, DK-2200 Copenhagen, Denmark and Faculty of Statistics, TU Dortmund University, D-44221 Dortmund, Germany.",
year = "2014",
month = jan,
day = "22",
doi = "10.1093/bioinformatics/btu003",
language = "English",
volume = "30",
pages = "1154--62",
journal = "Bioinformatics",
issn = "1367-4803",
publisher = "Oxford University Press",
number = "8",
}