About scikit-bio#

scikit-bio (canonically pronounced sigh-kit-buy-oh) is a library for working with biological data in Python. scikit-bio is open source BSD-licensed software that is currently under active development.

Adoption#

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

QIIME 2, Qiita, Emperor, tax2tree, ghost-tree, Platypus-Conquistador, An Introduction to Applied Bioinformatics.

License#

scikit-bio is available under the new BSD license. See LICENSE.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.

Team#

Our core development team consists of three lead developers: Dr. Qiyun Zhu at Arizona State University (ASU) (@qiyunzhu), Dr. James Morton at Gutz Analytics (@mortonjt), and Dr. Daniel McDonald at the University of California San Diego (UCSD) (@wasade), one software engineer: Matthew Aton (@mataton) and one bioinformatician: Dr. Lars Hunger (@LarsHunger). Dr. Rob Knight at UCSD (@rob-knight) provides guidance on the development and research. Dr. Greg Caporaso (@gregcaporaso) at Northern Arizona University (NAU), the former leader of the scikit-bio project, serves as an advisor on the current project.

Credits#

We thank the many contributors to scikit-bio. A complete list of contributors to the scikit-bio codebase is available at GitHub. This however may miss the larger community who contributed by testing the software and providing valuable comments, who we hold equal appreciation to.

Wanna contribute? We enthusiastically welcome community contributors! Whether it’s adding new features, improving code, or enhancing documentation, your contributions drive scikit-bio and open-source bioinformatics forward. Start your journey by reading the Contributor’s guidelines.

Funding#

The development of scikit-bio is currently supported by the U.S. Department of Energy, Office of Science under award number DE-SC0024320, awarded to Dr. Qiyun Zhu at ASU (lead PI), Dr. James Morton at Gutz Analytics, and Dr. Rob Knight at UCSD.

Citation#

If you use scikit-bio for any published research, please see our Zenodo page for how to cite.

Collaboration#

For collaboration inquiries and other formal communications, please reach out to Dr. Qiyun Zhu at qiyun.zhu@asu.edu. We welcome academic and industrial partnerships to advance our mission.

Branding#

The logo of scikit-bio was created by Alina Prassas. Vector and bitmap image files are available at the logos directory.

Pre-history#

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 listed below: