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par Vincent Daubin - 9 janvier 2018

Effective normalization for copy number variation in Hi-C data

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.