scikit-bio 0.6.2

We are excited to announce scikit-bio 0.6.2!

Release highlights:

• scikit-bio now has full support for Microsoft Windows.
• Significantly improved the efficiency and functionality of TreeNode for storing and manipulating phylogenetic trees.
• Implemented nearest neighbor interchange (NNI) (nni) for phylogenetic tree rearrangement.
• Implemented alpha diversity metrics: Hill number (hill), Renyi entropy (renyi) and Tsallis entropy (tsallis).
• Enabled ID renaming for classes DissimilarityMatrix and OrdinationResults.

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!

scikit-bio 0.6.1

We are excited to announce scikit-bio 0.6.1!

Release highlights:

• Added module skbio.embedding to provide support for storing and manipulating embeddings for biological objects, such as protein embeddings outputted from protein language models (pLMs).
• Added an efficient sequence alignment path data structure AlignPath to provide a uniform interface for various multiple and pairwise alignment formats.
• Boosted the performance of count subsampling, an essential algorithm for omic data analysis.
• Improved alpha diversity calculation, including new metrics and variants, enriched documentation and literature citations, and edge case treatment.
• Enabled support for NumPy 2.0.

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!

scikit-bio 0.6.0

We are excited to announce scikit-bio 0.6.0!

This release introduces significant enhancements and features, including the launch of a new website, the addition of new modules, classes and algorithms, and support for the latest versions of Python and SciPy. This release also includes various optimizations, bug fixes, and documentation improvements, making it a substantial upgrade for users and developers alike.

Release highlights:

• Launched a new scikit-bio website (scikit.bio) with improved design and documentation.
• Added a data table module and support for BIOM tables.
• Added a sample metadata class and support for numeric and categorical columns.
• Enhanced biological sequence operations, including alphabet, substitution matrix and index conversion.
• Implemented a differential abundance test using Dirichilet multinomial distribution, which mirrors ALDEx2.
• Implemented generalized phylogenetic alpha diversity metrics.
• Adopted NumPy’s new random generator to enable reproducible analysis.
• Support for Python 3.12+ and SciPy 1.11+.
• Improvements of performance, robustness and usability in various functionality.

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!

scikit-bio 0.5.9: Maintenance release

We are excited to announce scikit-bio 0.5.9!

You can review the CHANGELOG.md for a complete description of the changes in this release. To learn about what you can do with scikit-bio, browse our API documentation.

Be sure to follow @scikitbio on twitter for project updates, and as always, thanks for your interest in scikit-bio!

scikit-bio 0.5.8: Maintenance and new Taxdump format

We are excited to announce scikit-bio 0.5.8!

You can review the CHANGELOG.md for a complete description of the changes in this release. To learn about what you can do with scikit-bio, browse our API documentation.

Be sure to follow @scikitbio on twitter for project updates, and as always, thanks for your interest in scikit-bio!

scikit-bio 0.5.7: Performance and maintenance

We are very excited to announce scikit-bio 0.5.7!

You can review the CHANGELOG.md for a complete description of the changes in this release. To learn about what you can do with scikit-bio, browse our API documentation.

Be sure to follow @scikitbio on twitter for project updates, and as always, thanks for your interest in scikit-bio!

scikit-bio 0.5.6: Maintenance and more

We are very excited to announce scikit-bio 0.5.6.

You can review the CHANGELOG.md for a complete description of the changes in this release. To learn about what you can do with scikit-bio, browse our API documentation.

Be sure to follow @scikitbio on twitter for project updates, and as always, thanks for your interest in scikit-bio!

scikit-bio 0.5.5: More compositional methods added

We are very excited to announce scikit-bio 0.5.5. This is a minor release that adds a couple of compositional techniques under skbio.stats.composition namely the alr, and inverse alr transform in addition to easier construction of balance basis through sequential binary partitioning.

You can review the CHANGELOG.md for a complete description of the changes in this release. To learn about what you can do with scikit-bio, browse our API documentation.

Be sure to follow @scikitbio on twitter for project updates, and as always, thanks for your interest in scikit-bio!

scikit-bio 0.5.4: faster pcoa through FSVD

We are very excited to announce scikit-bio 0.5.4. This is a minor release that adds a heuristic-based method to calculate PCoA. For large distance matrices, this option will dramatically reduce the memory footprint and accelerate the compute in skbio.stats.ordination.pcoa.

You can review the CHANGELOG.md for a complete description of the changes in this release. To learn about what you can do with scikit-bio, browse our API documentation.

Be sure to follow @scikitbio on twitter for project updates, and as always, thanks for your interest in scikit-bio!

scikit-bio 0.5.3: TreeNode additions, permdisp, pcoa_biplot and more

We are very excited to announce scikit-bio 0.5.3. This is a minor release that adds a few new features in different modules of scikit-bio. Most notably it adds a few new methods to TreeNode, the permdisp test (to test for homogeneity of dispersions in distance-based comparisons), and pcoa_biplot to create biplots from an existing PCoA matrix.

You can review the CHANGELOG.md for a complete description of the changes in this release. To learn about what you can do with scikit-bio, browse our API documentation.

Be sure to follow @scikitbio on twitter for project updates, and as always, thanks for your interest in scikit-bio!