The three-dimensional conformation of genomes is an essential component of their biological activity. The advent of the Hi-C technology enabled an unprecedented progress in our understanding of genome structures. However, Hi-C is subject to systematic biases that can compromise downstream analyses. Several strategies have been proposed to remove those biases, but the issue of abnormal karyotypes received little attention. Many experiments are performed in cancer cell lines, which typically harbor large-scale copy number variations that create visible defects on the raw Hi-C maps. The consequences of these widespread artifacts on the normalized maps are mostly unexplored. We observed that current normalization methods are not robust to the presence of large-scale copy number variations, potentially obscuring biological differences and enhancing batch effects. To address this issue, we developed an alternative approach designed to take into account chromosomal abnormalities. The method, called OneD, increases reproducibility among replicates of Hi-C samples with abnormal karyotype, outperforming previous methods significantly. On normal karyotypes, OneD fared equally well as state-of-the-art methods, making it a safe choice for Hi-C normalization. OneD is fast and scales well in terms of computing resources for resolutions up to 5 kb.

Spanish Ministry of Economy and Competitiveness ‘Centro de Excelencia Severo Ochoa 2013–2017’ [SEV-2012-0208]; ACER (to C.R.G.); EMBO Long-term Fellowship [ALTF 1201-2014 to R.S.]; Marie Curie Individual Fellowship [H2020-MSCA-IF-2014]; European Research Council under the European Union’s Seventh Framework Programme [FP7/2007–2013)/ERC Synergy grant agreement 609989 (4DGenome)]. We acknowledge the support of the CERCA Programme / Generalitat de Catalunya. Funding for open access charge: European Research Council.