title: Broad-Enrich: functional interpretation of large sets of broad genomic regions.
abstract: BACKGROUND
  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.
  
  
  METHODS
  http://broad-enrich.med.umich.edu for Web version and R package.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
authors.forename: Raymond G
authors.initials: RG
authors.lastname: Cavalcante
authors.affiliation: Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
authors.forename: Chee
authors.initials: C
authors.lastname: Lee
authors.affiliation: Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
authors.forename: Ryan P
authors.initials: RP
authors.lastname: Welch
authors.affiliation: Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
authors.forename: Snehal
authors.initials: S
authors.lastname: Patil
authors.affiliation: Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
authors.forename: Terry
authors.initials: T
authors.lastname: Weymouth
authors.affiliation: Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
authors.forename: Laura J
authors.initials: LJ
authors.lastname: Scott
authors.affiliation: Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
authors.forename: Maureen A
authors.initials: MA
authors.lastname: Sartor
mesh_terms: D002460:Cell Line; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D056426:Genetic Loci; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D006657:Histones / Q000378:metabolism*; D006801:Humans; D016015:Logistic Models; D017422:Sequence Analysis, DNA; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D006657:Histones; D014157:Transcription Factors