Published January 13, 2025
| Version 0.6.3
Software
Open
scikit-bio/scikit-bio: scikit-bio 0.6.3
Creators
- Jai Ram Rideout1
- Greg Caporaso2
- Evan Bolyen
- Daniel McDonald3
- Yoshiki Vázquez Baeza4
- Jorge Cañardo Alastuey
- Anders Pitman
- Jamie Morton
- Qiyun Zhu5
- Jose Navas6
- Kestrel Gorlick
- Justine Debelius
- Zech Xu7
- Matt Aton
- llcooljohn
- Joshua Shorenstein8
- Laurent Luce
- Will Van Treuren
- John Chase
- charudatta-navare
- Antonio Gonzalez7
- Colin J. Brislawn
- Weronika Patena9
- Karen Schwarzberg
- teravest
- Jens Reeder
- Igor Sfiligoi10
- shiffer1
- nbresnick
- Dr. K. D. Murray11
- 1. @onecodex
- 2. @qiime2
- 3. UCSD - Dept. of Pediatrics
- 4. @BiomeSense
- 5. Arizona State University
- 6. University of California, San Diego
- 7. UCSD
- 8. Invitae, Inc.
- 9. Princeton University
- 10. San Diego Supercomputing Center
- 11. Max Planck Institute for Biology Tübingen
Description
We are excited to announce scikit-bio 0.6.3!
This is a massive upgrade, despite minor version change. Release highlights include:
- Significantly improved the tree and phylogenetics module (
skbio.tree
), with:- Optimized the
TreeNode
class such that it can efficiently handle very large phylogenetic trees. - Added, extended and/or optimized many methods of
TreeNode
. It now features a standard, flexible and scalable API to perform various common tasks in phylogenetics and data science. - Refined and expanded tree comparison metrics, including original, weighted, and variants of Robinson-Foulds distances, path / cophenetic distance and variants. Also added driver functions for computing distances between multiple trees.
- Added and/or optimized minimum evolution (ME) algorithms for phylogenetic reconstruction and rearrangement, including GME (
gme
), BME (bme
), FastNNI, and BNNI (nni
). - Optimized the canonical neighbor joining (NJ) algorithm (
nj
) for phylogenetic reconstruction.
- Optimized the
- Refined the I/O system (
skbio.io
) to improve its efficiency, maintainability and expansibility. Also expanded the tutorial of I/O in scikit-bio. - Allowed the user to specify a random seed or random generator for all stochastic algorithms in scikit-bio to ensure reproducibilty.
- Allowed the user to specify a desired fractional cumulative variance for
pcoa
. - Added support for Python 3.13. Dropped support for Python 3.8.
- Multiple bug fixes and miscellaneous improvements.
Review the changelog for a complete list of the changes. Browse the documentation to learn about what you can do with scikit-bio. Follow @scikitbio for project updates. Thanks for your interest in scikit-bio!
Files
scikit-bio/scikit-bio-0.6.3.zip
Files
(4.9 MB)
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Additional details
Related works
- Is supplement to
- Software: https://github.com/scikit-bio/scikit-bio/tree/0.6.3 (URL)
Software
- Repository URL
- https://github.com/scikit-bio/scikit-bio