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Seqinspector: position-based navigation through the ChIP-seq data landscape to identify gene expression regulators

BACKGROUND: The regulation of gene expression in eukaryotic cells is a complex process that involves epigenetic modifications and the interaction of DNA with multiple transcription factors. This process can be studied with unprecedented sensitivity using a combination of chromatin immunoprecipitatio...

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Autores principales: Piechota, Marcin, Korostynski, Michal, Ficek, Joanna, Tomski, Andrzej, Przewlocki, Ryszard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751710/
https://www.ncbi.nlm.nih.gov/pubmed/26868127
http://dx.doi.org/10.1186/s12859-016-0938-4
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author Piechota, Marcin
Korostynski, Michal
Ficek, Joanna
Tomski, Andrzej
Przewlocki, Ryszard
author_facet Piechota, Marcin
Korostynski, Michal
Ficek, Joanna
Tomski, Andrzej
Przewlocki, Ryszard
author_sort Piechota, Marcin
collection PubMed
description BACKGROUND: The regulation of gene expression in eukaryotic cells is a complex process that involves epigenetic modifications and the interaction of DNA with multiple transcription factors. This process can be studied with unprecedented sensitivity using a combination of chromatin immunoprecipitation and next-generation DNA sequencing (ChIP-seq). Available ChIP-seq data can be further utilized to interpret new gene expression profiling experiments. RESULTS: Here, we describe seqinspector, a tool that accepts any set of genomic coordinates from ChIP-seq or RNA-seq studies to identify shared transcriptional regulators. The presented web resource includes a large collection of publicly available ChIP-seq and RNA-seq experiments (>1300 tracks) performed on transcription factors, histone modifications, RNA polymerases, enhancers and insulators in humans and mice. Over-representation is calculated based on the coverage computed directly from indexed files storing ChIP-seq data (bigwig). Therefore, seqinspector is not limited to pre-computed sets of gene promoters. CONCLUSION: The tool can be used to identify common gene expression regulators for sets of co-expressed transcripts (including miRNAs, lncRNAs or any novel unannotated RNAs) or for sets of ChIP-seq peaks to identify putative protein-protein interactions or transcriptional co-factors. The tool is available at http://seqinspector.cremag.org. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-0938-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-47517102016-02-13 Seqinspector: position-based navigation through the ChIP-seq data landscape to identify gene expression regulators Piechota, Marcin Korostynski, Michal Ficek, Joanna Tomski, Andrzej Przewlocki, Ryszard BMC Bioinformatics Software BACKGROUND: The regulation of gene expression in eukaryotic cells is a complex process that involves epigenetic modifications and the interaction of DNA with multiple transcription factors. This process can be studied with unprecedented sensitivity using a combination of chromatin immunoprecipitation and next-generation DNA sequencing (ChIP-seq). Available ChIP-seq data can be further utilized to interpret new gene expression profiling experiments. RESULTS: Here, we describe seqinspector, a tool that accepts any set of genomic coordinates from ChIP-seq or RNA-seq studies to identify shared transcriptional regulators. The presented web resource includes a large collection of publicly available ChIP-seq and RNA-seq experiments (>1300 tracks) performed on transcription factors, histone modifications, RNA polymerases, enhancers and insulators in humans and mice. Over-representation is calculated based on the coverage computed directly from indexed files storing ChIP-seq data (bigwig). Therefore, seqinspector is not limited to pre-computed sets of gene promoters. CONCLUSION: The tool can be used to identify common gene expression regulators for sets of co-expressed transcripts (including miRNAs, lncRNAs or any novel unannotated RNAs) or for sets of ChIP-seq peaks to identify putative protein-protein interactions or transcriptional co-factors. The tool is available at http://seqinspector.cremag.org. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-0938-4) contains supplementary material, which is available to authorized users. BioMed Central 2016-02-12 /pmc/articles/PMC4751710/ /pubmed/26868127 http://dx.doi.org/10.1186/s12859-016-0938-4 Text en © Piechota et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Piechota, Marcin
Korostynski, Michal
Ficek, Joanna
Tomski, Andrzej
Przewlocki, Ryszard
Seqinspector: position-based navigation through the ChIP-seq data landscape to identify gene expression regulators
title Seqinspector: position-based navigation through the ChIP-seq data landscape to identify gene expression regulators
title_full Seqinspector: position-based navigation through the ChIP-seq data landscape to identify gene expression regulators
title_fullStr Seqinspector: position-based navigation through the ChIP-seq data landscape to identify gene expression regulators
title_full_unstemmed Seqinspector: position-based navigation through the ChIP-seq data landscape to identify gene expression regulators
title_short Seqinspector: position-based navigation through the ChIP-seq data landscape to identify gene expression regulators
title_sort seqinspector: position-based navigation through the chip-seq data landscape to identify gene expression regulators
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751710/
https://www.ncbi.nlm.nih.gov/pubmed/26868127
http://dx.doi.org/10.1186/s12859-016-0938-4
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