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Detecting chromosomal interactions in Capture Hi-C data with CHiCAGO and companion tools.

Accepted version
Peer-reviewed

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Authors

Freire-Pritchett, Paula 
Ray-Jones, Helen 
Eijsbouts, Chris Q 
Orchard, William R 

Abstract

Capture Hi-C is widely used to obtain high-resolution profiles of chromosomal interactions involving, at least on one end, regions of interest such as gene promoters. Signal detection in Capture Hi-C data is challenging and cannot be adequately accomplished with tools developed for other chromosome conformation capture methods, including standard Hi-C. Capture Hi-C Analysis of Genomic Organization (CHiCAGO) is a computational pipeline developed specifically for Capture Hi-C analysis. It implements a statistical model accounting for biological and technical background components, as well as bespoke normalization and multiple testing procedures for this data type. Here we provide a step-by-step guide to the CHiCAGO workflow that is aimed at users with basic experience of the command line and R. We also describe more advanced strategies for tuning the key parameters for custom experiments and provide guidance on data preprocessing and downstream analysis using companion tools. In a typical experiment, CHiCAGO takes ~2-3 h to run, although pre- and postprocessing steps may take much longer.

Description

Keywords

Chromatin, Chromosomes, Models, Statistical, Software

Journal Title

Nat Protoc

Conference Name

Journal ISSN

1754-2189
1750-2799

Volume Title

16

Publisher

Springer Science and Business Media LLC
Sponsorship
Wellcome Trust (107881/Z/15/Z)
Medical Research Council (MC_UU_00002/4)