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====================================================================== deepTools

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user-friendly tools for the normalization and visualization of deep-sequencing data

deepTools addresses the challenge of handling the large amounts of data that are now routinely generated from DNA sequencing centers. To do so, deepTools contains useful modules to process the mapped reads data to create coverage files in standard bedGraph and bigWig file formats. By doing so, deepTools allows the creation of normalized coverage files or the comparison between two files (for example, treatment and control). Finally, using such normalized and standardized files, multiple visualizations can be created to identify enrichments with functional annotations of the genome.

For support, questions, or feature requests contact: deeptools@googlegroups.com

Citation: Fidel Ramírez, Friederike Dündar, Sarah Diehl, Björn A. Grüning, and Thomas Manke. deepTools: a flexible platform for exploring deep-sequencing data. Nucl. Acids Res. first published online May 5, 2014 doi:10.1093/nar/gku365

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Our documentation contains more information on why we built deepTools, details on the individual tool scopes and usages and an introduction to our deepTools Galaxy web server. Please see also the FAQ, which we update regularly. For more specific troubleshooting, feedback, and tool suggestions, contact us via deeptools@googlegroups.com


Installation

deepTools are available for:

  • command line usage
  • integration into Galaxy servers

Details on the installation routines can be found here.

Linux/Mac Installation

Galaxy installation

Linux/Mac Installation

The easiest way to install deepTools is by using python pip or easy_install tools:

Requirements: Python 2.7, numpy, scipy (http://www.scipy.org/install.html), bx-python, pysam, and pyBigWig

Commands:

  $ pip install deeptools --user

Done.

Using anaconda:

Anaconda already comes with scipy, numpy and matplotlib, making installation very quick. To install using either Anaconda or Miniconda:

$ conda install -c bioconda deeptools

Note that deepTools does not (yet) work with python3.

Another option is to clone the repository:

$ git clone https://github.com/fidelram/deepTools
$ cd deepTools
$ python setup.py install

By default, the script will install the python library and executable codes globally, which means you need to be root or administrator of the machine to complete the installation. If you need to provide a nonstandard install prefix, or any other nonstandard options, you can provide many command line options to the install script.

$ python setup.py --help

For example, to install under a specific location use:

$ python setup.py install --prefix <target directory>

To install into your home directory, use:

$ python setup.py install --user

Galaxy Installation

deepTools can be easily integrated into Galaxy. All wrappers and dependencies are available in the Galaxy Tool Shed.

Installation via Galaxy API (recommended)

At first generate an API Key for your admin user and run the the installation script:

python ./scripts/api/install_tool_shed_repositories.py --api YOUR_API_KEY -l http://localhost --url http://toolshed.g2.bx.psu.edu/ -o bgruening -r <revision> --name deeptools --tool-deps --repository-deps --panel-section-name deepTools

The -r argument specifies the version of deepTools. You can get the latest revsion number from the test tool shed or with the following command:

hg identify http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools

You can watch the installation status under: Top Panel → Admin → Manage installed tool shed repositories

Installation via web browser

  • go to the admin page
  • select Search and browse tool sheds
  • Galaxy tool shed → Sequence Analysis → deeptools
  • install deeptools

remember: for support, questions, or feature requests contact: deeptools@googlegroups.com


This tool suite is developed by the Bioinformatics Facility at the Max Planck Institute for Immunobiology and Epigenetics, Freiburg.

Wiki Start Page | deepTools Galaxy | FAQ

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Tools to process and analyze deep sequencing data.

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