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CHiCAGO: Capture HiC Analysis of Genomic Organisation

CHiCAGO is a set of tools for Capture HiC data analysis.

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.

This repository contains the following files:

  • The Chicago R package
  • The PCHiCdata R data package with small example Promoter Capture HiC datasets for mouse and human
  • chicagoTools: scripts for preparing input files, running Chicago and processing the output

Please refer to the Chicago R package vignette and the chicagoTools README file for more information.

Compatibility notices

  • CHiCAGO is not compatible with R package Delaporte v2.3.0. The compatibility issue has been kindly fixed but Delaporte package author in all subsequent versions.

  • 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.

News

  • Version 1.1.5: Default values of tlb.minProxOEPerBin and tlb.minProxB2BPerBin have changed. No action is required unless you specified non-default values, or wish to re-run the pipeline on old chicagoData objects. See the NEWS file for more details.

Installation instructions

  1. Make sure that you have R version >= 3.1.2. chicagoTools requires some additional dependencies: bedtools, perl and python >= 2.7 need to be pre-installed and added to PATH, plus the R package argparser is required - install with the R code:
install.packages("argparser")
  1. Get the chicagoTools scripts by downloading the repository (downloads tab on left-hand menu). These scripts do not need to be installed further - see chicagoTools/README.md.

  2. Install the R packages. An easy way to do this is by using functionality in devtools - run the following R code:

install.packages("devtools")
library(devtools)
install_bitbucket("chicagoTeam/Chicago", subdir="Chicago")

Optionally, install the PCHiCdata package at the same time:

install_bitbucket("chicagoTeam/Chicago", subdir="PCHiCdata")

(This strategy downloads the repository multiple times. To avoid this, you can manually install Chicago's dependencies, then install the packages from the source directories using R CMD INSTALL or install.packages().)

The R packages are also part of Bioconductor 3.3, and installation using biocLite() is available. However, as Bioconductor releases only happen twice a year, more recent versions of the R packages may be available from here.

If you encounter any problems, please post an issue or email the developers. In the email, include output from the R command sessionInfo(), along with any error messages encountered.

Contact information

Chicago is mainly developed and maintained by:

We are based at the Regulatory Genomics Group, Babraham Institute, Cambridge UK.

More details (including the full credits) can be found at regulatorygenomicsgroup.org/chicago.