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
Our wiki page 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. It also contains an FAQ section that we update regularly. For more specific troubleshooting, feedback, and tool suggestions, contact us via deeptools@googlegroups.com
deepTools are available for:
- command line usage
- integration into Galaxy servers
Details on the installation routines can be found here.
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) installed
Commands:
$ pip install deeptools
Done.
A second 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>
The easiest way to get numpy and scipy dependencies is to install the Anaconda Scientific Python Distribution. After installation, open a terminal ("Applications" → "Terminal") and follow the General Installation
If individual installation of the dependencies is preferred, follow those steps:
Requirement: Python 2.7 installed
Download the packages and install them using dmg images:
- http://sourceforge.net/projects/numpy/files/NumPy/
- http://sourceforge.net/projects/scipy/files/scipy/
Then open terminal ("Applications" → "Terminal") and follow the General Installation
deepTools can be easily integrated into Galaxy. All wrappers and dependencies are available in the Galaxy Tool Shed.
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:8080 --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
- 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.