Abstract
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.
Original language | English |
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Article number | 127 |
Number of pages | 17 |
Journal | Genome Biology |
Volume | 17 |
DOIs | |
Publication status | Published - 15 Jun 2016 |
Keywords
- Gene regulation
- Nuclear organisation
- Promoter-enhancer interactions
- Capture Hi-C
- Convolution background model
- P value weighting