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A tool for intersection and visualization of multiple gene or genomic region sets

Project description


a tool for intersection and visualization of multiple gene or genomic region sets


A detailed documentation is available in different formats: HTML | PDF | ePUB


Quick installation using Conda

conda install -c bioconda intervene

This will install all the dependencies and you are ready to use Intervene.

Install using pip

You can install Intervene from PyPi using pip.

Install from PyPi:

pip install intervene

Note: If you install using pip, make sure to install BEDTools and R packages listed below.

Intervene requires the following Python modules and R packages:

Install BEDTools

We are using pybedtools, which is Python wrapper for BEDTools. So, BEDTools should be installed before using Intervene. It’s recomended to have a latest version, but if you have an older version already install, it should be fine.

A quick installation, if you have conda installed.

conda install -c bioconda bedtools

Please read the instructions at to install BEDTools, and make sure it is on your path and you are able to call bedtools from any directory.

Install required R packages

Intervene rquires three R packages, UpSetR , corrplot for visualization and Cairo to generate high-quality vector and bitmap figures.

install.packages(c("UpSetR", "corrplot", "Cairo"))

Install Intervene from source

You can install a development version by using git from GitHub or Bitbucket.

Install development version from Bitbucket

If you have git installed, use this:

git clone
cd intervene
python sdist install

Install development version from GitHub

If you have git installed, use this:

git clone
cd intervene
python sdist install

How to use Intervene

Once you have installed Intervene, you can type:

intervene --help

This will show the following help message.

usage: intervene <subcommand> [options]

positional arguments <subcommand>:
                        List of subcommands
    venn                Venn diagram of intersection of genomic regions or list sets (upto 6-way).
    upset               UpSet diagram of intersection of genomic regions or list sets.
    pairwise            Pairwise intersection and heatmap of N genomic region sets in <BED/GTF/GFF> format.

optional arguments:
  -h, --help            show this help message and exit
  -v, --version         show program's version number and exit

to see the help for the three subcommands pairwise, venn and upset type:

intervene pairwise --help

intervene venn --help

intervene upset --help

Run Intervene on test data

To run Intervene using example data, use the following commands. To access the test data make sure you have sudo or root access.

intervene pairwise --test

intervene venn --test

intervene upset --test

If you have installed Intervene locally from the source code, you may have problem to find test data. You can download the test data here and point to it using -i instead of --test.

./intervene/intervene venn -i intervene/example_data/ENCODE_hESC/*.bed
./intervene/intervene upset -i intervene/example_data/ENCODE_hESC/*.bed
./intervene/intervene pairwise -i intervene/example_data/dbSUPER_mm9/*.bed

The above three test commands will generate the following three figures (a, b and c).

By default your results will stored in the current working directory with a folder named Intervene_results. If you wish to save the results in a specific folder, you can type:

intervene upset --test --output ~/path/to/your/folder

Interactive Shiny App

Intervene Shiny App is freely available at or

The source code for the Shiny app is available at


If you have questions, or found any bug in the program, please write to us at aziz.khan[at]

Cite Us

If you use Intervene please cite us: Khan A, Mathelier A. Intervene: a tool for intersection and visualization of multiple gene or genomic region sets. BMC Bioinformatics. 2017;18:287. doi: 10.1186/s12859-017-1708-7

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Filename, size & hash SHA256 hash help File type Python version Upload date
intervene-0.6.4.tar.gz (5.5 MB) Copy SHA256 hash SHA256 Source None May 13, 2018

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