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ChIP-Enrich: gene set enrichment testing for ChIP-seq data

Gene set enrichment testing can enhance the biological interpretation of ChIP-seq data. Here, we develop a method, ChIP-Enrich, for this analysis which empirically adjusts for gene locus length (the length of the gene body and its surrounding non-coding sequence). Adjustment for gene locus length is...

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Autores principales: Welch, Ryan P., Lee, Chee, Imbriano, Paul M., Patil, Snehal, Weymouth, Terry E., Smith, R. Alex, 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/PMC4117744/
https://www.ncbi.nlm.nih.gov/pubmed/24878920
http://dx.doi.org/10.1093/nar/gku463
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author Welch, Ryan P.
Lee, Chee
Imbriano, Paul M.
Patil, Snehal
Weymouth, Terry E.
Smith, R. Alex
Scott, Laura J.
Sartor, Maureen A.
author_facet Welch, Ryan P.
Lee, Chee
Imbriano, Paul M.
Patil, Snehal
Weymouth, Terry E.
Smith, R. Alex
Scott, Laura J.
Sartor, Maureen A.
author_sort Welch, Ryan P.
collection PubMed
description Gene set enrichment testing can enhance the biological interpretation of ChIP-seq data. Here, we develop a method, ChIP-Enrich, for this analysis which empirically adjusts for gene locus length (the length of the gene body and its surrounding non-coding sequence). Adjustment for gene locus length is necessary because it is often positively associated with the presence of one or more peaks and because many biologically defined gene sets have an excess of genes with longer or shorter gene locus lengths. Unlike alternative methods, ChIP-Enrich can account for the wide range of gene locus length-to-peak presence relationships (observed in ENCODE ChIP-seq data sets). We show that ChIP-Enrich has a well-calibrated type I error rate using permuted ENCODE ChIP-seq data sets; in contrast, two commonly used gene set enrichment methods, Fisher's exact test and the binomial test implemented in Genomic Regions Enrichment of Annotations Tool (GREAT), can have highly inflated type I error rates and biases in ranking. We identify DNA-binding proteins, including CTCF, JunD and glucocorticoid receptor α (GRα), that show different enrichment patterns for peaks closer to versus further from transcription start sites. We also identify known and potential new biological functions of GRα. ChIP-Enrich is available as a web interface (http://chip-enrich.med.umich.edu) and Bioconductor package.
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spelling pubmed-41177442015-05-18 ChIP-Enrich: gene set enrichment testing for ChIP-seq data Welch, Ryan P. Lee, Chee Imbriano, Paul M. Patil, Snehal Weymouth, Terry E. Smith, R. Alex Scott, Laura J. Sartor, Maureen A. Nucleic Acids Res Methods Online Gene set enrichment testing can enhance the biological interpretation of ChIP-seq data. Here, we develop a method, ChIP-Enrich, for this analysis which empirically adjusts for gene locus length (the length of the gene body and its surrounding non-coding sequence). Adjustment for gene locus length is necessary because it is often positively associated with the presence of one or more peaks and because many biologically defined gene sets have an excess of genes with longer or shorter gene locus lengths. Unlike alternative methods, ChIP-Enrich can account for the wide range of gene locus length-to-peak presence relationships (observed in ENCODE ChIP-seq data sets). We show that ChIP-Enrich has a well-calibrated type I error rate using permuted ENCODE ChIP-seq data sets; in contrast, two commonly used gene set enrichment methods, Fisher's exact test and the binomial test implemented in Genomic Regions Enrichment of Annotations Tool (GREAT), can have highly inflated type I error rates and biases in ranking. We identify DNA-binding proteins, including CTCF, JunD and glucocorticoid receptor α (GRα), that show different enrichment patterns for peaks closer to versus further from transcription start sites. We also identify known and potential new biological functions of GRα. ChIP-Enrich is available as a web interface (http://chip-enrich.med.umich.edu) and Bioconductor package. Oxford University Press 2014-09-01 2014-05-30 /pmc/articles/PMC4117744/ /pubmed/24878920 http://dx.doi.org/10.1093/nar/gku463 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods Online
Welch, Ryan P.
Lee, Chee
Imbriano, Paul M.
Patil, Snehal
Weymouth, Terry E.
Smith, R. Alex
Scott, Laura J.
Sartor, Maureen A.
ChIP-Enrich: gene set enrichment testing for ChIP-seq data
title ChIP-Enrich: gene set enrichment testing for ChIP-seq data
title_full ChIP-Enrich: gene set enrichment testing for ChIP-seq data
title_fullStr ChIP-Enrich: gene set enrichment testing for ChIP-seq data
title_full_unstemmed ChIP-Enrich: gene set enrichment testing for ChIP-seq data
title_short ChIP-Enrich: gene set enrichment testing for ChIP-seq data
title_sort chip-enrich: gene set enrichment testing for chip-seq data
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4117744/
https://www.ncbi.nlm.nih.gov/pubmed/24878920
http://dx.doi.org/10.1093/nar/gku463
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