Iterative correction of Hi-C data reveals hallmarks of chromosome organization

UMMS Affiliation

Program in Systems Biology; Department of Biochemistry and Molecular Pharmacology



Document Type


Medical Subject Headings

Chromosome Positioning; Chromosomes; DNA; Genomics; Nucleic Acid Conformation


Genetics and Genomics | Systems Biology


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.


Citation: Nat Methods. 2012 Sep 2. doi: 10.1038/nmeth.2148. [Epub ahead of print]

Related Resources

Link to article in PubMed

Journal Title

Nature methods

PubMed ID