Journal
NATURE METHODS
Volume 9, Issue 10, Pages 999-+Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/NMETH.2148
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Funding
- US National Cancer Institute Physical Sciences-Oncology Center at MIT [U54CA143874]
- US National Institutes of Health [HG003143, F32GM100617]
- W.M. Keck Foundation
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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.
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