CHiCAGO: Capture HiC Analysis of Genomic Organisation

CHiCAGO is a set of tools for calling significant interactions in Capture HiC data, such as Promoter Capture HiC.

The statistical foundations of CHiCAGO

CHiCAGO uses a convolution background model accounting for both random ‘Brownian collisions’ between chromatin fragments (that are distance-dependent) and ‘technical noise’. It borrows information across interactions (with appropriate normalisation) to estimate these background 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.

The software

CHiCAGO consists of an open-source R package (Chicago), a data package with subsets of published Promoter Capture HiC datasets for training purposes (PCHiCdata) and a set of command line tools for pre-processing and post-processing (chicagoTools). All of these, along with detailed documentation, are available from this bitbucket repository:


The R packages are also part of the Bioconductor 3.3 release (requires R version >= 3.3.0). However, as Bioconductor releases only happen twice a year, the package versions found on Bitbucket may be more recent. Bitbucket can also be used to install the packages with R versions >= 3.2.

The Chicago package vignette in HTML format can also be viewed here (opens in a new window).

Compatibility notices!
(1) Chicago is currently not compatible with bedtools v2.26 due to BED format compliance checking introduced in this version. Please do not upgrade from v2.25 while we are working to resolve this issue.
(2) Chicago is incompatible with R package Delaporte v2.3.0 that appeared on CRAN on 2 June 2016 (earlier versions are fine). The compatible updated Delaporte v2.3.1 is now available on CRAN – many thanks to package author Avraham Adler for cooperation. Please check that you are running a compatible version.

The paper

CHiCAGO is presented in this paper:

Cairns J* / Freire-Pritchett P*, Wingett SW, Várnai C, Dimond A, Plagnol V, Zerbino D, Schoenfelder S, Javierre B-M, Osborne C, Fraser P, Spivakov M. CHiCAGO: Robust Detection of DNA Looping Interactions in Capture Hi-C data. Genome Biology. 2016. 17:127.


CHiCAGO has been mainly developed by Jonathan Cairns, Paula Freire Pritchett and Mikhail Spivakov in our group, with invaluable contributions from Steven Wingett (Babraham Bioinformatics / Nuclear Dynamics ISP) and great ideas from Vincent Plagnol (UCL) and Daniel Zerbino (EMBL-EBI).

The package has so far been extensively tested on Promoter Capture HiC data from our collaborators at Babraham Institute (Fraser and Rugg-Gunn groups, with special thanks to Stefan Schoenfelder and Biola-Maria Javierre) and at KCL (Cameron Osborne).


For specific issues, please submit a report on Bitbucket:


If you have any general feedback on CHiCAGO or would like to collaborate, please don’t hesitate to drop a line to Mikhail (mikhail.spivakov/babraham.ac.uk).

Chicago schematic