Iterative Correction of Hi-C Data Reveals Hallmarks of Chromosome Organization
McCord, Rachel Patton
Lajoie, Bryan R.
MetadataShow full item record
CitationImakaev, Maxim, Geoffrey Fudenberg, Rachel Patton McCord, Natalia Naumova, Anton Goloborodko, Bryan R. Lajoie, Job Dekker, and Leonid A Mirny. 2013. “Iterative Correction of Hi-C Data Reveals Hallmarks of Chromosome Organization.” Nature methods 9 (10): 10.1038/nmeth.2148. doi:10.1038/nmeth.2148. http://dx.doi.org/10.1038/nmeth.2148.
AbstractExtracting biologically meaningful information from chromosomal interactions obtained with genome-wide chromosome conformation capture (3C) analyses requires elimination of systematic biases. We present a pipeline that integrates a strategy for mapping of sequencing reads and a data-driven method for iterative correction of biases, yielding genome-wide maps of relative contact probabilities. We validate ICE (Iterative Correction and Eigenvector decomposition) on published Hi-C data, and 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.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:11878982