Iterative correction of Hi-C data reveals hallmarks of chromosome organization View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-10

AUTHORS

Maxim Imakaev, Geoffrey Fudenberg, Rachel Patton McCord, Natalia Naumova, Anton Goloborodko, Bryan R Lajoie, Job Dekker, Leonid A Mirny

ABSTRACT

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. More... »

PAGES

999

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nmeth.2148

    DOI

    http://dx.doi.org/10.1038/nmeth.2148

    DIMENSIONS

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/22941365


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