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CHiCAGO / Capture HiC Analysis of Genomic Organisation

A set of tools for calling significant interactions in Capture Hi-C data, such as Promoter Capture Hi-C. CHiCAGO uses a convolution noise model accounting for both ‘Brownian’ (distance-dependent) and ‘technical’ noise. It borrows information across interactions (with appropriate normalisation) to estimate these noise components separately on different subsets of data. CHiCAGO then performs a p-value weighting procedure based on the expected true positive rates at different distance ranges (estimated from data), with scores representing soft-thresholded -log weighted p-values. CHiCAGO consists of an open-source R package (Chicago), a data package with subsets of published Promoter Capture Hi-C datasets for training purposes (PCHiCdata) and a set of command line tools for pre-processing and post-processing (chicagoTools).