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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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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. |
format | Online Article Text |
id | pubmed-4117744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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