Title
Iterative correction of Hi-C data reveals hallmarks of chromosome organization
UMMS Affiliation
Program in Systems Biology; Department of Biochemistry and Molecular Pharmacology
Publication Date
2012-09-02
Document Type
Article
Subjects
Chromosome Positioning; Chromosomes; DNA; Genomics; Nucleic Acid Conformation
Disciplines
Genetics and Genomics | Systems Biology
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.
DOI of Published Version
10.1038/nmeth.2148
Source
Nat Methods. 2012 Sep 2. doi: 10.1038/nmeth.2148. [Epub ahead of print]
Journal/Book/Conference Title
Nature methods
Related Resources
PubMed ID
22941365
Repository Citation
Imakaev M, Fudenberg G, McCord RP, Naumova N, Goloborodko A, Lajoie BR, Dekker J, Mirny LA. (2012). Iterative correction of Hi-C data reveals hallmarks of chromosome organization. Program in Systems Biology Publications. https://doi.org/10.1038/nmeth.2148. Retrieved from https://escholarship.umassmed.edu/sysbio_pubs/14