Imakaev, MaximFudenberg, GeoffreyMcCord, Rachel PattonNaumova, NataliaGoloborodko, AntonLajoie, Bryan R.Dekker, JobMirny, Leonid A.2022-08-232022-08-232012-09-022012-09-05Nat Methods. 2012 Sep 2. doi: 10.1038/nmeth.2148. [Epub ahead of print]</p>1548-710510.1038/nmeth.214822941365https://hdl.handle.net/20.500.14038/49867Extracting 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.en-USChromosome PositioningChromosomesDNAGenomicsNucleic Acid ConformationGenetics and GenomicsSystems BiologyJournal Articlehttps://escholarship.umassmed.edu/sysbio_pubs/143295204sysbio_pubs/14