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- Title
Removing unwanted variation between samples in Hi-C experiments.
- Authors
Fletez-Brant, Kipper; Qiu, Yunjiang; Gorkin, David U; Hu, Ming; Hansen, Kasper D
- Abstract
Hi-C data are 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 change across the contact map. We present band-wise normalization and batch correction, a method for normalization and batch correction of Hi-C data and show that it substantially improves comparisons across samples, including in a quantitative trait loci analysis as well as differential enrichment across cell types.
- Subjects
LOCUS (Genetics); SAMPLING (Process)
- Publication
Briefings in Bioinformatics, 2024, Vol 25, Issue 3, p1
- ISSN
1467-5463
- Publication type
Article
- DOI
10.1093/bib/bbae217