title: GAT: a simulation framework for testing the association of genomic intervals.
abstract: BACKGROUND
  A common question in genomic analysis is whether two sets of genomic intervals overlap significantly. This question arises, for example, when interpreting ChIP-Seq or RNA-Seq data in functional terms. Because genome organization is complex, answering this question is non-trivial.
  
  
  CONCLUSIONS
  We present Genomic Association Test (GAT), a tool for estimating the significance of overlap between multiple sets of genomic intervals. GAT implements a null model that the two sets of intervals are placed independently of one another, but allows each set's density to depend on external variables, for example, isochore structure or chromosome identity. GAT estimates statistical significance based on simulation and controls for multiple tests using the false discovery rate.
  
  
  BACKGROUND
  GAT's source code, documentation and tutorials are available at http://code.google.com/p/genomic-association-tester.
authors.affiliation: MRC CGAT Programme and Functional Genomics Unit, MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK. andreas.heger@dpag.ox.ac.uk
authors.forename: Andreas
authors.initials: A
authors.lastname: Heger
authors.forename: Caleb
authors.initials: C
authors.lastname: Webber
authors.forename: Martin
authors.initials: M
authors.lastname: Goodson
authors.forename: Chris P
authors.initials: CP
authors.lastname: Ponting
authors.forename: Gerton
authors.initials: G
authors.lastname: Lunter
mesh_terms: D001665:Binding Sites; D047369:Chromatin Immunoprecipitation; D003198:Computer Simulation; D003850:Deoxyribonuclease I; D023281:Genomics / Q000379:methods*; D017422:Sequence Analysis, DNA; D012984:Software; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D014157:Transcription Factors; D003850:Deoxyribonuclease I