规范化(社会学)
变化(天文学)
统计
样品(材料)
计算机科学
数学
物理
色谱法
化学
人类学
天体物理学
社会学
作者
Kipper Fletez-Brant,Yunjiang Qiu,David U. Gorkin,Ming Hu,Kasper D. Hansen
摘要
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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