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Updated: Mar 16, 2026
Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
A computational strategy to adjust for copy number in tumor Hi-C data
Hua-Jun Wu1, Franziska Michor1
1Department of Computational Biology and Biostatistics, Dana-Farber Cancer Institute, and Department of Biostatistics, Harvard School of Public Health, Boston, MA 02215, USA.
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: michor@jimmy.harvard.eduSupplementary information: Supplementary data are available at Bioinformatics online.
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