Removing unwanted variation between samples in Hi-C experiments.
Brief Bioinform
; 25(3)2024 Mar 27.
Article
in En
| MEDLINE
| ID: mdl-38711367
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.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Quantitative Trait Loci
Limits:
Humans
Language:
En
Journal:
Brief Bioinform
Journal subject:
BIOLOGIA
/
INFORMATICA MEDICA
Year:
2024
Document type:
Article
Affiliation country:
Estados Unidos