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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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Detalles Bibliográficos
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
Descripción
Sumario: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.