jensreeder / scikit-bio

Core objects, functions and statistics for working with biological data in Python.

scikit-bio is an open-source, BSD-licensed Python package providing data structures, algorithms and educational resources for bioinformatics.

To view scikit-bio's documentation, visit scikit-bio.org.

scikit-bio is currently in alpha. We are very actively developing it, and backwards-incompatible interface changes can and will arise. Once the API has started to solidify, we will strive to maintain backwards compatibility. We will provide deprecation warnings wherever possible in the scikit-bio code, documentation, and CHANGELOG.md.

Note: Deprecation warnings will be issued using Python's DeprecationWarning class. Since Python 2.7, these types of warnings are silenced by default. When developing a tool that uses scikit-bio, we recommend enabling the display of deprecation warnings to be informed of upcoming API changes. For details on how to display deprecation warnings, see Python's deprecation warning docs.

Installing

To install the latest release of scikit-bio:

pip install scikit-bio

Equivalently, you can use the conda package manager available in Anaconda or miniconda to install scikit-bio and its dependencies without having to compile them:

conda install scikit-bio

Finally, most of scikit-bio's dependencies (in particular, the ones that are trickier to build) are also available, albeit only for Python 2, in Canopy Express.

You can verify your installation by running the scikit-bio unit tests:

python -m skbio.test

Getting help

To get help with scikit-bio, you should use the skbio tag on StackOverflow (SO). Before posting a question, check out SO's guide on how to ask a question. The scikit-bio developers regularly monitor the skbio SO tag.

Projects using scikit-bio

Some of the projects that we know of that are using scikit-bio are:

• QIIME
• Emperor
• An Introduction to Applied Bioinformatics
• tax2tree
• Qiita
• ghost-tree
• Platypus-Conquistador

If you're using scikit-bio in your own projects, feel free to issue a pull request to add them to this list.

scikit-bio development

If you're interested in getting involved in scikit-bio development, see CONTRIBUTING.md.

See the list of scikit-bio's contributors.

Licensing

scikit-bio is available under the new BSD license. See COPYING.txt for scikit-bio's license, and the licenses directory for the licenses of third-party software that is (either partially or entirely) distributed with scikit-bio.

The pre-history of scikit-bio

scikit-bio began from code derived from PyCogent and QIIME, and the contributors and/or copyright holders have agreed to make the code they wrote for PyCogent and/or QIIME available under the BSD license. The contributors to PyCogent and/or QIIME modules that have been ported to scikit-bio are: Rob Knight (@rob-knight), Gavin Huttley (@gavin-huttley), Daniel McDonald (@wasade), Micah Hamady, Antonio Gonzalez (@antgonza), Sandra Smit, Greg Caporaso (@gregcaporaso), Jai Ram Rideout (@jairideout), Cathy Lozupone (@clozupone), Mike Robeson (@mikerobeson), Marcin Cieslik, Peter Maxwell, Jeremy Widmann, Zongzhi Liu, Michael Dwan, Logan Knecht (@loganknecht), Andrew Cochran, Jose Carlos Clemente (@cleme), Damien Coy, Levi McCracken, Andrew Butterfield, Will Van Treuren (@wdwvt1), Justin Kuczynski (@justin212k), Jose Antonio Navas Molina (@josenavas), Matthew Wakefield (@genomematt) and Jens Reeder (@jensreeder).

Logo

scikit-bio's logo was created by Alina Prassas.