Work

A computational strategy to adjust for copy number in tumor Hi-C data

Year: 2016

Type: article

Abstract: MOTIVATION: The Hi-C technology was designed to decode the three-dimensional conformation of the genome. Despite progress towards more and more accurate contact maps, several systematic biases have been demonstrated to affect the resulting data matrix. Here we report a new source of bias that can arise in tumor Hi-C data, which is related to the copy number of genomic DNA. To address this bias, we designed a chromosome-adjusted iterative correction method called caICB. Our caICB correction method leads to significant improvements when compared with the original iterative correction in terms of eliminating copy number bias. AVAILABILITY AND IMPLEMENTATION: The method is available at https://bitbucket.org/mthjwu/hicapp CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.

Source: Bioinformatics

DOI: 10.1093/bioinformatics/btw540

Authors: Hua-Jun Wu, Franziska Michor

Institutions: Harvard University, Dana-Farber Cancer Institute, Dana-Farber/Harvard Cancer Center

Language: English

Topic: Genomics and Chromatin Dynamics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: bronze

Funders: National Institutes of Health, National Cancer Institute

Awards: Evolution and Treatment Response of Brain, Breast, and Hematologic Malignancies, G8910415956