title: Iterative correction of Hi-C data reveals hallmarks of chromosome organization.
abstract: Extracting biologically meaningful information from chromosomal interactions obtained with genome-wide chromosome conformation capture (3C) analyses requires the elimination of systematic biases. We present a computational pipeline that integrates a strategy to map sequencing reads with a data-driven method for iterative correction of biases, yielding genome-wide maps of relative contact probabilities. We validate this ICE (iterative correction and eigenvector decomposition) technique on published data obtained by the high-throughput 3C method Hi-C, and we demonstrate that eigenvector decomposition of the obtained maps provides insights into local chromatin states, global patterns of chromosomal interactions, and the conserved organization of human and mouse chromosomes.
authors.affiliation: Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
authors.forename: Maxim
authors.initials: M
authors.lastname: Imakaev
authors.forename: Geoffrey
authors.initials: G
authors.lastname: Fudenberg
authors.forename: Rachel Patton
authors.initials: RP
authors.lastname: McCord
authors.forename: Natalia
authors.initials: N
authors.lastname: Naumova
authors.forename: Anton
authors.initials: A
authors.lastname: Goloborodko
authors.forename: Bryan R
authors.initials: BR
authors.lastname: Lajoie
authors.forename: Job
authors.initials: J
authors.lastname: Dekker
authors.forename: Leonid A
authors.initials: LA
authors.lastname: Mirny
mesh_terms: D002843:Chromatin / Q000737:chemistry; D002874:Chromosome Mapping / Q000379:methods*; D002877:Chromosomes, Human / Q000737:chemistry*; D057166:High-Throughput Screening Assays / Q000379:methods*; D006801:Humans; D009690:Nucleic Acid Conformation
chemical_list: D002843:Chromatin