RT Journal Article
SR Electronic
T1 Effective normalization for copy number variation in Hi-C data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 167031
DO 10.1101/167031
A1 N. Servant
A1 N. Varoquaux
A1 E. Heard
A1 JP. Vert
A1 E. Barillot
YR 2017
UL http://biorxiv.org/content/early/2017/07/21/167031.abstract
AB Normalization is essential to ensure accurate analysis and proper interpretation of sequencing data. Chromosome conformation data, such as Hi-C, is not different. The most widely used type of normalization of Hi-C data casts estimations of unwanted effects as a matrix balancing problem, relying on the assumption that all genomic regions interact as much as any other. Here, we show that these approaches, while very effective on fully haploid or diploid genome, fail to correct for unwanted effects in the presence of copy number variations. We propose a simple extension to matrix balancing methods that properly models the copy-number variation effects. Our approach can either retain the copy-number variation effects or remove it. We show that this leads to better downstream analysis of the three-dimensional organization of rearranged genome.