Rxivist logo

OneD: increasing reproducibility of Hi-C Samples with abnormal karyotypes

By Enrique Vidal, Fran├žois le Dily, Javier Quilez, Ralph Stadhouders, Yasmina Cuartero, Thomas Graf, Marc A. Marti-Renom, Miguel Beato, Guillaume J. Filion

Posted 09 Jun 2017
bioRxiv DOI: 10.1101/148254 (published DOI: 10.1093/nar/gky064)

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 1 kbp. OneD is implemented as an R package available at http://www.github.com/qenvio/dryhic.

Download data

  • Downloaded 562 times
  • Download rankings, all-time:
    • Site-wide: 37,599 out of 118,180
    • In bioinformatics: 4,204 out of 9,572
  • Year to date:
    • Site-wide: 104,053 out of 118,180
  • Since beginning of last month:
    • Site-wide: 96,230 out of 118,180

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide


Sign up for the Rxivist weekly newsletter! (Click here for more details.)