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DISCOVER co-occurrence and mutual exclusivity analysis for cancer genomics data

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DISCOVER

DISCOVER is a novel statistical method for analysing co-occurrence and mutual exclusivity in cancer genomics data. The details of this method are described in our paper A novel independence test for somatic alterations in cancer shows that biology drives mutual exclusivity but chance explains most co-occurrence (Genome Biology 2016 17:261).

Installation

DISCOVER is available for both Python and R.

Python

The easiest way to install the DISCOVER Python package is by using Miniconda or Anaconda. We provide precompiled DISCOVER packages for 64-bit Linux, Windows, and Mac OS X. The following steps assume that Miniconda or Anaconda has been installed.

To create a new conda environment containing DISCOVER and its dependencies, execute the following command in a terminal (Linux/Mac OS X) or command prompt (Windows).

conda create -n discover -c https://ccb.nki.nl/software/discover/repos/conda discover

This environment can be activated using:

conda activate discover

Note that this environment contains the bare minimum to use DISCOVER. It does not, for example, include IPython. Trying to run IPython anyway might start a version installed in a different environment, and hence, importing DISCOVER will not succeed. Consult the conda documentation to find out how to install additional packages (such as IPython). Alternatively, DISCOVER can be installed in an existing environment as follows.

conda install -c https://ccb.nki.nl/software/discover/repos/conda discover

Check the documentation for instructions on how to use this package.

R

We provide precompiled R packages for Windows and Mac OS X, as well as a source package for installation on Linux. Installation on Linux requires gfortran version 5.1 or later. To install the DISCOVER package, execute the following in an R session.

options(repos=c(getOption("repos"), "https://ccb.nki.nl/software/discover/repos/r"))
install.packages("discover")

Check the documentation for instructions on how to use this package.

Documentation