Iterative correction of Hi-C data reveals hallmarks of chromosome organization
McCord, Rachel Patton
Lajoie, Bryan R.
Mirny, Leonid A.
UMass Chan AffiliationsDepartment of Biochemistry and Molecular Pharmacology
Program in Systems Biology
Nucleic Acid Conformation
Genetics and Genomics
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AbstractExtracting 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.
SourceNat Methods. 2012 Sep 2. doi: 10.1038/nmeth.2148. [Epub ahead of print]
Permanent Link to this Itemhttp://hdl.handle.net/20.500.14038/49867
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