GAT: a simulation framework for testing the association of genomic intervals

Andreas Heger, Caleb Webber, Martin Goodson, Chris P Ponting, Gerton Lunter

Research output: Contribution to journalArticlepeer-review


MOTIVATION: 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.

SUMMARY: 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.

AVAILABILITY: GAT's source code, documentation and tutorials are available at

Original languageEnglish
Pages (from-to)2046-8
Number of pages3
Issue number16
Publication statusPublished - 15 Aug 2013


  • Binding Sites
  • Chromatin Immunoprecipitation
  • Computer Simulation
  • Deoxyribonuclease I
  • Genomics
  • Sequence Analysis, DNA
  • Software
  • Transcription Factors


Dive into the research topics of 'GAT: a simulation framework for testing the association of genomic intervals'. Together they form a unique fingerprint.

Cite this