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CHiCAGO: Robust Detection of DNA Looping Interactions in Capture Hi-C data

2015; Cold Spring Harbor Laboratory; Linguagem: Inglês

10.1101/028068

Jonathan Cairns, Paula Freire-Pritchett, Steven W. Wingett, Csilla Várnai, Andrew Dimond, Vincent Plagnol, Daniel R. Zerbino, Stefan Schoenfelder, Biola M. Javierre, Cameron S. Osborne, Peter Fraser, Mikhail Spivakov,

Gene expression and cancer classification

ABSTRACT Capture Hi-C (CHi-C) is a state-of-the art method for profiling chromosomal interactions involving targeted regions of interest (such as gene promoters) globally and at high resolution. Signal detection in CHi-C data involves a number of statistical challenges that are not observed when using other Hi-C-like techniques. We present a background model, and algorithms for normalisation and multiple testing that are specifically adapted to CHi-C experiments, in which many spatially dispersed regions are captured, such as in Promoter CHi-C. We implement these procedures in CHiCAGO ( http://regulatorygenomicsgroup.org/chicago ), an open-source package for robust interaction detection in CHi-C. We validate CHiCAGO by showing that promoter-interacting regions detected with this method are enriched for regulatory features and disease-associated SNPs.