intervene

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

https://github.com/asntech/intervene

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 1 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
    3 of 6 committers (50.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.8%) to scientific vocabulary

Keywords

genome-analysis heatmaps venn-diagram visualization
Last synced: 9 months ago · JSON representation

Repository

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

Basic Info
  • Host: GitHub
  • Owner: asntech
  • License: other
  • Language: Python
  • Default Branch: master
  • Homepage: http://intervene.rtfd.io/
  • Size: 20.3 MB
Statistics
  • Stars: 143
  • Watchers: 5
  • Forks: 30
  • Open Issues: 21
  • Releases: 0
Topics
genome-analysis heatmaps venn-diagram visualization
Created over 9 years ago · Last pushed over 2 years ago
Metadata Files
Readme License

README.rst

.. image:: https://raw.githubusercontent.com/asntech/intervene/master/docs/img/intervene_logo.png
   	:target: http://intervene.readthedocs.org
   	
Intervene
-----------

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



.. image:: https://img.shields.io/pypi/pyversions/intervene.svg
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.. image:: https://img.shields.io/pypi/v/intervene.svg
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	:target: https://anaconda.org/bioconda/intervene

.. image:: https://static.pepy.tech/badge/intervene
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Documentation
=============

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

.. figure:: http://intervene.readthedocs.io/en/latest/_images/Intervene_sketch.png
   :width: 800px
   :align: left

Installation
============

Quick installation using Conda
------------------------------

.. code-block:: bash

	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:

	* Python (=> 3.3 ): https://www.python.org/
	* BedTools (Latest version): https://github.com/arq5x/bedtools2
	* pybedtools (>= 0.7.9): https://daler.github.io/pybedtools/
	* Pandas (>= 0.16.0): http://pandas.pydata.org/
	* Seaborn (>= 0.7.1): http://seaborn.pydata.org/
	* R (>= 3.0): https://www.r-project.org/
	* R packages including UpSetR (v1.4.0), corrplot

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.

.. code-block:: bash

    conda install -c bioconda bedtools

Please read the instructions at https://github.com/arq5x/bedtools2 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.

.. code-block:: R

    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:

.. code-block:: bash

    git clone https://bitbucket.org/CBGR/intervene.git
    cd intervene
    python setup.py sdist install

Install development version from `GitHub`
-----------------------------------------
If you have `git` installed, use this:

.. code-block:: bash

    git clone https://github.com/asntech/intervene.git
    cd intervene
    python setup.py sdist install

How to use Intervene
====================
Once you have installed Intervene, you can type:

.. code-block:: bash

	intervene --help

This will show the following help message.

.. code-block:: bash

	usage: intervene  [options]
	    
	positional arguments :
	  {venn,upset,pairwise}
	                        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  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:

.. code-block:: bash
	
	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.

.. code-block:: bash

	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 https://github.com/asntech/intervene/tree/master/intervene/example_data and point to it using ``-i`` instead of ``--test``.

.. code-block:: bash

	./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).

.. figure:: http://intervene.readthedocs.io/en/latest/_images/Intervene_plots.png
   :width: 800px
   :align: left

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 https://asntech.shinyapps.io/intervene or https://intervene.shinyapps.io/intervene

The source code for the Shiny app is available at https://github.com/asntech/intervene-shiny

Support
========
If you have questions, or found any bug in the program, please write to us at ``azez.khan[at]gmail.com``

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``

Owner

  • Name: Aziz Khan
  • Login: asntech
  • Kind: user
  • Location: Palo Alto, California
  • Company: Stanford University

Computational biologist interested in gene regulation, machine learning, regulatory genomics and epigenomics

GitHub Events

Total
  • Issues event: 2
  • Watch event: 12
  • Issue comment event: 2
  • Fork event: 1
Last Year
  • Issues event: 2
  • Watch event: 12
  • Issue comment event: 2
  • Fork event: 1

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 201
  • Total Committers: 6
  • Avg Commits per committer: 33.5
  • Development Distribution Score (DDS): 0.04
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Aziz a****n@g****m 193
mvdbeek m****k@g****m 2
Anthony Mathelier a****r@n****o 2
Aziz Khan a****k@b****o 2
Aziz Khan a****k@A****l 1
Luca Venturini L****i@t****k 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 9 months ago

All Time
  • Total issues: 62
  • Total pull requests: 4
  • Average time to close issues: 11 months
  • Average time to close pull requests: over 1 year
  • Total issue authors: 51
  • Total pull request authors: 3
  • Average comments per issue: 2.58
  • Average comments per pull request: 0.75
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 0
  • Average time to close issues: 1 minute
  • Average time to close pull requests: N/A
  • Issue authors: 2
  • Pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • clouds-drift (5)
  • dllahr (3)
  • asntech (3)
  • unique379 (2)
  • mortunco (2)
  • unique379r (2)
  • whiteorchid (1)
  • JianWang2016 (1)
  • jsanmig (1)
  • nouratb (1)
  • jaqx008 (1)
  • vschulz (1)
  • scalavision (1)
  • danli349 (1)
  • ashleymaeconard (1)
Pull Request Authors
  • asntech (2)
  • mvdbeek (1)
  • chrisamiller (1)
Top Labels
Issue Labels
enhancement (9) new-feature (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 74 last-month
  • Total docker downloads: 89
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 19
  • Total maintainers: 1
pypi.org: intervene

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

  • Versions: 19
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 74 Last month
  • Docker Downloads: 89
Rankings
Docker downloads count: 2.8%
Stargazers count: 6.8%
Forks count: 7.4%
Dependent packages count: 10.0%
Average: 10.7%
Downloads: 15.6%
Dependent repos count: 21.7%
Maintainers (1)
Last synced: 9 months ago

Dependencies

requirements.txt pypi
  • matplotlib *
  • numpy *
  • pandas *
  • pybedtools *
  • scipy *
  • seaborn *
setup.py pypi
  • matplotlib *
  • numpy *
  • pandas *
  • pybedtools *
  • scipy *
  • seaborn *