Epimetheus - a multi-profile normalizer for epigenomic sequencing data

Abstract Background Exponentially increasing numbers of NGS-based epigenomic datasets in public repositories like GEO constitute an enormous source of information that is invaluable for integrative and comparative studies of gene regulatory mechanisms. One of today’s challenges for such studies is t...

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Main Authors: Mohamed-Ashick M. Saleem, Marco-Antonio Mendoza-Parra, Pierre-Etienne Cholley, Matthias Blum, Hinrich Gronemeyer
Format: Article
Language:English
Published: BMC 2017-05-01
Series:BMC Bioinformatics
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12859-017-1655-3
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author Mohamed-Ashick M. Saleem
Marco-Antonio Mendoza-Parra
Pierre-Etienne Cholley
Matthias Blum
Hinrich Gronemeyer
author_facet Mohamed-Ashick M. Saleem
Marco-Antonio Mendoza-Parra
Pierre-Etienne Cholley
Matthias Blum
Hinrich Gronemeyer
author_sort Mohamed-Ashick M. Saleem
collection DOAJ
description Abstract Background Exponentially increasing numbers of NGS-based epigenomic datasets in public repositories like GEO constitute an enormous source of information that is invaluable for integrative and comparative studies of gene regulatory mechanisms. One of today’s challenges for such studies is to identify functionally informative local and global patterns of chromatin states in order to describe the regulatory impact of the epigenome in normal cell physiology and in case of pathological aberrations. Critically, the most preferred Chromatin ImmunoPrecipitation-Sequencing (ChIP-Seq) is inherently prone to significant variability between assays, which poses significant challenge on comparative studies. One challenge concerns data normalization to adjust sequencing depth variation. Results Currently existing tools either apply linear scaling corrections and/or are restricted to specific genomic regions, which can be prone to biases. To overcome these restrictions without any external biases, we developed Epimetheus, a genome-wide quantile-based multi-profile normalization tool for histone modification data and related datasets. Conclusions Epimetheus has been successfully used to normalize epigenomics data in previous studies on X inactivation in breast cancer and in integrative studies of neuronal cell fate acquisition and tumorigenic transformation; Epimetheus is freely available to the scientific community.
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spelling doaj.art-2c1efb53551044dab1f3c9cc062fc74d2022-12-21T18:56:49ZengBMCBMC Bioinformatics1471-21052017-05-011811910.1186/s12859-017-1655-3Epimetheus - a multi-profile normalizer for epigenomic sequencing dataMohamed-Ashick M. Saleem0Marco-Antonio Mendoza-Parra1Pierre-Etienne Cholley2Matthias Blum3Hinrich Gronemeyer4Equipe Labellisée Ligue Contre le Cancer, Department of Functional Genomics and Cancer, Institut de Génétique et de Biologie Moléculaire et CellulaireEquipe Labellisée Ligue Contre le Cancer, Department of Functional Genomics and Cancer, Institut de Génétique et de Biologie Moléculaire et CellulaireEquipe Labellisée Ligue Contre le Cancer, Department of Functional Genomics and Cancer, Institut de Génétique et de Biologie Moléculaire et CellulaireEquipe Labellisée Ligue Contre le Cancer, Department of Functional Genomics and Cancer, Institut de Génétique et de Biologie Moléculaire et CellulaireEquipe Labellisée Ligue Contre le Cancer, Department of Functional Genomics and Cancer, Institut de Génétique et de Biologie Moléculaire et CellulaireAbstract Background Exponentially increasing numbers of NGS-based epigenomic datasets in public repositories like GEO constitute an enormous source of information that is invaluable for integrative and comparative studies of gene regulatory mechanisms. One of today’s challenges for such studies is to identify functionally informative local and global patterns of chromatin states in order to describe the regulatory impact of the epigenome in normal cell physiology and in case of pathological aberrations. Critically, the most preferred Chromatin ImmunoPrecipitation-Sequencing (ChIP-Seq) is inherently prone to significant variability between assays, which poses significant challenge on comparative studies. One challenge concerns data normalization to adjust sequencing depth variation. Results Currently existing tools either apply linear scaling corrections and/or are restricted to specific genomic regions, which can be prone to biases. To overcome these restrictions without any external biases, we developed Epimetheus, a genome-wide quantile-based multi-profile normalization tool for histone modification data and related datasets. Conclusions Epimetheus has been successfully used to normalize epigenomics data in previous studies on X inactivation in breast cancer and in integrative studies of neuronal cell fate acquisition and tumorigenic transformation; Epimetheus is freely available to the scientific community.http://link.springer.com/article/10.1186/s12859-017-1655-3ChIP-seqEpigenomeQuantile-based data normalizationMulti-sample analysis
spellingShingle Mohamed-Ashick M. Saleem
Marco-Antonio Mendoza-Parra
Pierre-Etienne Cholley
Matthias Blum
Hinrich Gronemeyer
Epimetheus - a multi-profile normalizer for epigenomic sequencing data
BMC Bioinformatics
ChIP-seq
Epigenome
Quantile-based data normalization
Multi-sample analysis
title Epimetheus - a multi-profile normalizer for epigenomic sequencing data
title_full Epimetheus - a multi-profile normalizer for epigenomic sequencing data
title_fullStr Epimetheus - a multi-profile normalizer for epigenomic sequencing data
title_full_unstemmed Epimetheus - a multi-profile normalizer for epigenomic sequencing data
title_short Epimetheus - a multi-profile normalizer for epigenomic sequencing data
title_sort epimetheus a multi profile normalizer for epigenomic sequencing data
topic ChIP-seq
Epigenome
Quantile-based data normalization
Multi-sample analysis
url http://link.springer.com/article/10.1186/s12859-017-1655-3
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AT pierreetiennecholley epimetheusamultiprofilenormalizerforepigenomicsequencingdata
AT matthiasblum epimetheusamultiprofilenormalizerforepigenomicsequencingdata
AT hinrichgronemeyer epimetheusamultiprofilenormalizerforepigenomicsequencingdata