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Integrative analysis of histone ChIP-seq and transcription data using Bayesian mixture models

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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.
Original languageEnglish
JournalBioinformatics
Volume30
Issue number8
Pages (from-to)1154-62
ISSN1367-4803
DOIs
Publication statusPublished - 22 Jan 2014

Bibliographical note

D-48149 Münster, Mathematical Institute, Heinrich Heine University, D-40225 Düsseldorf, 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.

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