Analysis of Hi-C data using SIP effectively identifies loops in organisms from C. elegans to mammals.

ABSTRACT: Chromatin loops are a major component of 3D nuclear organization, visually apparent as intense point-to-point interactions in Hi-C maps. Identification of these loops is a critical part of most Hi-C analyses. However, current methods often miss visually evident CTCF loops in Hi-C data sets from mammals, and they completely fail to identify high intensity loops in other organisms. We present SIP, Significant Interaction Peak caller, and SIPMeta, which are platform independent programs to identify and characterize these loops in a time- and memory-efficient manner. We show that SIP is resistant to noise and sequencing depth, and can be used to detect loops that were previously missed in human cells as well as loops in other organisms. SIPMeta corrects for a common visualization artifact by a

SUBMITTER: Rowley MJ 

PROVIDER: S-EPMC7111518 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature