title: A statistical model of ChIA-PET data for accurate detection of chromatin 3D interactions.
abstract: Identification of three-dimensional (3D) interactions between regulatory elements across the genome is crucial to unravel the complex regulatory machinery that orchestrates proliferation and differentiation of cells. ChIA-PET is a novel method to identify such interactions, where physical contacts between regions bound by a specific protein are quantified using next-generation sequencing. However, determining the significance of the observed interaction frequencies in such datasets is challenging, and few methods have been proposed. Despite the fact that regions that are close in linear genomic distance have a much higher tendency to interact by chance, no methods to date are capable of taking such dependency into account. Here, we propose a statistical model taking into account the genomic distance relationship, as well as the general propensity of anchors to be involved in contacts overall. Using both real and simulated data, we show that the previously proposed statistical test, based on Fisher's exact test, leads to invalid results when data are dependent on genomic distance. We also evaluate our method on previously validated cell-line specific and constitutive 3D interactions, and show that relevant interactions are significant, while avoiding over-estimating the significance of short nearby interactions.
authors.affiliation: Institute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, N-0424 Oslo, Norway jonaspau@ifi.uio.no.
authors.forename: Jonas
authors.initials: J
authors.lastname: Paulsen
authors.affiliation: Department of Tumor Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, PO Box 4950, Nydalen, N-0424 Oslo, Norway.
authors.forename: Einar A
authors.initials: EA
authors.lastname: Rødland
authors.affiliation: Statistics for Innovation, Norwegian Computing Center, N-0314 Oslo, Norway.
authors.forename: Lars
authors.initials: L
authors.lastname: Holden
authors.affiliation: Statistics for Innovation, Norwegian Computing Center, N-0314 Oslo, Norway.
authors.forename: Marit
authors.initials: M
authors.lastname: Holden
authors.affiliation: Institute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, N-0424 Oslo, Norway Department of Tumor Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, PO Box 4950, Nydalen, N-0424 Oslo, Norway jonaspau@ifi.uio.no.
authors.forename: Eivind
authors.initials: E
authors.lastname: Hovig
mesh_terms: D002843:Chromatin / Q000737:chemistry*; D050676:Core Binding Factor Alpha 2 Subunit / Q000235:genetics; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D015233:Models, Statistical; D017422:Sequence Analysis, DNA
chemical_list: D002843:Chromatin; D050676:Core Binding Factor Alpha 2 Subunit
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