Iterative correction of Hi-C data reveals hallmarks of chromosome organization
Authors
Imakaev, MaximFudenberg, Geoffrey
McCord, Rachel Patton
Naumova, Natalia
Goloborodko, Anton
Lajoie, Bryan R.
Dekker, Job
Mirny, Leonid A.
UMass Chan Affiliations
Department of Biochemistry and Molecular PharmacologyProgram in Systems Biology
Document Type
Journal ArticlePublication Date
2012-09-02Keywords
Chromosome PositioningChromosomes
DNA
Genomics
Nucleic Acid Conformation
Genetics and Genomics
Systems Biology
Metadata
Show full item recordAbstract
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.Source
Nat Methods. 2012 Sep 2. doi: 10.1038/nmeth.2148. [Epub ahead of print]DOI
10.1038/nmeth.2148Permanent Link to this Item
http://hdl.handle.net/20.500.14038/49867PubMed ID
22941365Related Resources
Link to article in PubMedae974a485f413a2113503eed53cd6c53
10.1038/nmeth.2148