Iterative Correction of Hi-C Data Reveals Hallmarks of Chromosome Organization

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Iterative Correction of Hi-C Data Reveals Hallmarks of Chromosome Organization

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Title: Iterative Correction of Hi-C Data Reveals Hallmarks of Chromosome Organization
Author: Imakaev, Maxim; Fudenberg, Geoffrey; McCord, Rachel Patton; Naumova, Natalia; Goloborodko, Anton; Lajoie, Bryan R.; Dekker, Job; Mirny, Leonid A

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Citation: Imakaev, 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.
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Abstract: Extracting 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.
Published Version: doi:10.1038/nmeth.2148
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3816492/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:11878982
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