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

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Klein, Hans-Ulrich ; Schäfer, Martin ; Porse, Bo T ; Hasemann, Marie S ; Ickstadt, Katja ; Dugas, Martin. / Integrative analysis of histone ChIP-seq and transcription data using Bayesian mixture models. In: Bioinformatics. 2014 ; Vol. 30, No. 8. pp. 1154-62.

Bibtex

@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 = "1",
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",

}

RIS

TY - JOUR

T1 - Integrative analysis of histone ChIP-seq and transcription data using Bayesian mixture models

AU - Klein, Hans-Ulrich

AU - Schäfer, Martin

AU - Porse, Bo T

AU - Hasemann, Marie S

AU - Ickstadt, Katja

AU - Dugas, Martin

N1 - 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.

PY - 2014/1/22

Y1 - 2014/1/22

N2 - 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.

AB - 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.

U2 - 10.1093/bioinformatics/btu003

DO - 10.1093/bioinformatics/btu003

M3 - Journal article

VL - 30

SP - 1154

EP - 1162

JO - Bioinformatics

JF - Bioinformatics

SN - 1367-4803

IS - 8

ER -

ID: 42873015