scikit-bio/scikit-bio
scikit-bio: a community-driven Python library for bioinformatics, providing versatile data structures, algorithms and educational resources. observed · 2026-08-28
Health v2 · maintenance only
86/100
- Activity 99
- Release rhythm 62
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 104
- age_days: 4646
- days_rel: 93
- days_push: 8
- n_releases_24m: 6
Adoption not part of the score
1229 stars · 338 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
scikit-bio is an open-source, BSD-licensed Python library providing data structures, algorithms, and educational resources for bioinformatics. It supports tasks like sequence analysis, phylogenetic tree construction, diversity metrics, and ordination across genomics, microbiomics, ecology, and evolutionary biology.
Use cases
- compute beta diversity like weighted UniFrac on a feature table with a phylogenetic tree
- build a phylogenetic tree from sequences using neighbor joining
- perform pairwise sequence alignment and build a multiple sequence alignment
- run PCoA ordination on a distance matrix and plot it with sample metadata
- read and manipulate biological sequences and Newick trees in Python
- teach bioinformatics algorithms with documented examples in a classroom
- calculate sequence distance metrics such as Hamming distance
- analyze microbiome data as part of a QIIME 2 workflow
When to choose
- you need a Python library for biological data structures like sequences, alignments, trees, and distance matrices
- you are doing microbiome or ecology analysis requiring diversity metrics and ordination
- you want well-documented, education-friendly implementations of bioinformatics algorithms
- you are building on projects like QIIME 2 or Qiita that depend on scikit-bio
- you need cross-platform (Linux/macOS/Windows) Python 3.10+ bioinformatics tooling installable via pip or conda
When to avoid
- you need a full interactive analysis platform rather than a library (consider QIIME 2 or Galaxy)
- you require very recent or niche bioinformatics methods not yet implemented in scikit-bio
- you work outside Python or need high-performance compiled pipelines with their own runtimes
- you need a specific older Python version, since scikit-bio requires Python 3.10+
Facets
library · maturity active
data-science math parser data-visualization bioinformatics data-science education python windows cli bioinformatics microbiome sequence-analysis phylogenetics diversity-analysis ordination multiple-sequence-alignment genomics ecology bsd-license linux macos
5 sources
- readme: https://github.com/scikit-bio/scikit-bio · fetched 2026-08-28 · c5e2a0391b73
- homepage: https://scikit.bio · fetched 2026-08-29 · e9b1d251fa08
- site_page: https://scikit.bio/install.html · fetched 2026-08-29 · e6ec4b678ecb
- site_page: https://scikit.bio/about.html · fetched 2026-08-29 · b76e7ff5c0cb
- registry_pypi: https://pypi.org/pypi/scikit-bio/json · fetched 2026-08-29 · ee9e64753a74
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| scikit-bio/scikit-bio | main | 86 |
For agents
markdown · JSON · MCP: product_card(name="scikit-bio/scikit-bio")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem