CHiCAGO: robust detection of DNA looping interactions in Capture Hi-C data

By Jonathan M. Cairns, P. Freire-Pritchett, Steven W. Wingett, C. Várnai, Andrew Dimond, V. Plagnol, Daniel R. Zerbino, Stefan Schoenfelder, B. Javierre, Cameron S. Osborne and 2 more. Genome Biology, 2015

388 citations recorded by the source corpus.

Capture Hi-C (CHi-C) is a 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. 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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/3379936deabeace0ac423da831757d7ba6dbf95b

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In Molecular Biology

1. Ming Hu
2. Bing Ren
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Citations in the corpus

• GeneHancer: genome-wide integration of enhancers and target genes in GeneCards (2017, background): “Yet, there are ample reports for the successful use of this and related chromosome conformation capture methods for such purposes (78, 79).”
• Genome-wide mapping and analysis of chromosome architecture (2016, methodology): “Later on, a statistical model based on a convolution of negative binomial and Poisson distributions was proposed to account for background distribution in the Capture-HiC data 85 .”