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bioRxiv · 10.1101/214361

Removing unwanted variation between samples in Hi-C experiments

Fletez-Brant, K.·Qiu, Y.·Gorkin, D. U.·Hu, M.·Hansen, K. D.
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Abstract

Hi-C data is commonly normalized using single sample processing methods, with focus on comparisons between regions within a given contact map. Here, we aim to compare contact maps across different samples. We demonstrate that unwanted variation, of likely technical origin, is present in Hi-C data with replicates from different individuals, and that properties of this unwanted variation changes across the contact map. We present BNBC, a method for normalization and batch correction of Hi-C data and show that it substantially improves comparisons across samples, including in a QTL analysis as well as differential enrichment across cell types.

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Fletez-Brant, K., Qiu, Y., Gorkin, D. U., Hu, M., Hansen, K. D.. 2017-11-06. Removing unwanted variation between samples in Hi-C experiments. https://doi.org/10.1101/214361

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