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Broad-Enrich: functional interpretation of large sets of broad genomic regions

Motivation: Functional enrichment testing facilitates the interpretation of Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) data in terms of pathways and other biological contexts. Previous methods developed and used to test for key gene sets affected in ChIP-seq expe...

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Autores principales: Cavalcante, Raymond G., Lee, Chee, Welch, Ryan P., Patil, Snehal, Weymouth, Terry, Scott, Laura J., Sartor, Maureen A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147897/
https://www.ncbi.nlm.nih.gov/pubmed/25161225
http://dx.doi.org/10.1093/bioinformatics/btu444
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author Cavalcante, Raymond G.
Lee, Chee
Welch, Ryan P.
Patil, Snehal
Weymouth, Terry
Scott, Laura J.
Sartor, Maureen A.
author_facet Cavalcante, Raymond G.
Lee, Chee
Welch, Ryan P.
Patil, Snehal
Weymouth, Terry
Scott, Laura J.
Sartor, Maureen A.
author_sort Cavalcante, Raymond G.
collection PubMed
description Motivation: Functional enrichment testing facilitates the interpretation of Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) data in terms of pathways and other biological contexts. Previous methods developed and used to test for key gene sets affected in ChIP-seq experiments treat peaks as points, and are based on the number of peaks associated with a gene or a binary score for each gene. These approaches work well for transcription factors, but histone modifications often occur over broad domains, and across multiple genes. Results: To incorporate the unique properties of broad domains into functional enrichment testing, we developed Broad-Enrich, a method that uses the proportion of each gene’s locus covered by a peak. We show that our method has a well-calibrated false-positive rate, performing well with ChIP-seq data having broad domains compared with alternative approaches. We illustrate Broad-Enrich with 55 ENCODE ChIP-seq datasets using different methods to define gene loci. Broad-Enrich can also be applied to other datasets consisting of broad genomic domains such as copy number variations. Availability and implementation: http://broad-enrich.med.umich.edu for Web version and R package. Contact: sartorma@umich.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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spelling pubmed-41478972014-09-02 Broad-Enrich: functional interpretation of large sets of broad genomic regions Cavalcante, Raymond G. Lee, Chee Welch, Ryan P. Patil, Snehal Weymouth, Terry Scott, Laura J. Sartor, Maureen A. Bioinformatics Eccb 2014 Proceedings Papers Committee Motivation: Functional enrichment testing facilitates the interpretation of Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) data in terms of pathways and other biological contexts. Previous methods developed and used to test for key gene sets affected in ChIP-seq experiments treat peaks as points, and are based on the number of peaks associated with a gene or a binary score for each gene. These approaches work well for transcription factors, but histone modifications often occur over broad domains, and across multiple genes. Results: To incorporate the unique properties of broad domains into functional enrichment testing, we developed Broad-Enrich, a method that uses the proportion of each gene’s locus covered by a peak. We show that our method has a well-calibrated false-positive rate, performing well with ChIP-seq data having broad domains compared with alternative approaches. We illustrate Broad-Enrich with 55 ENCODE ChIP-seq datasets using different methods to define gene loci. Broad-Enrich can also be applied to other datasets consisting of broad genomic domains such as copy number variations. Availability and implementation: http://broad-enrich.med.umich.edu for Web version and R package. Contact: sartorma@umich.edu Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2014-09-01 2014-08-22 /pmc/articles/PMC4147897/ /pubmed/25161225 http://dx.doi.org/10.1093/bioinformatics/btu444 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Eccb 2014 Proceedings Papers Committee
Cavalcante, Raymond G.
Lee, Chee
Welch, Ryan P.
Patil, Snehal
Weymouth, Terry
Scott, Laura J.
Sartor, Maureen A.
Broad-Enrich: functional interpretation of large sets of broad genomic regions
title Broad-Enrich: functional interpretation of large sets of broad genomic regions
title_full Broad-Enrich: functional interpretation of large sets of broad genomic regions
title_fullStr Broad-Enrich: functional interpretation of large sets of broad genomic regions
title_full_unstemmed Broad-Enrich: functional interpretation of large sets of broad genomic regions
title_short Broad-Enrich: functional interpretation of large sets of broad genomic regions
title_sort broad-enrich: functional interpretation of large sets of broad genomic regions
topic Eccb 2014 Proceedings Papers Committee
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147897/
https://www.ncbi.nlm.nih.gov/pubmed/25161225
http://dx.doi.org/10.1093/bioinformatics/btu444
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