# scikit-bio/scikit-bio

scikit-bio: a community-driven Python library for bioinformatics, providing versatile data structures, algorithms and educational resources.

Repository: https://github.com/scikit-bio/scikit-bio
Canonical: https://ross.abutalabs.com/products/scikit-bio
Homepage: https://scikit.bio
Language: Python
License: BSD-3-Clause
License Family: permissive
Topics: bioinformatics, computational-biology
Last push: 2026-08-25T15:01:57+00:00

## Health v2 (maintenance only)
Score: 86/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 62, longevity 100
- inputs: {"age_days": 4646, "days_push": 8, "days_rel": 93, "gap_med": 104, "n_releases_24m": 6}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1229, forks 338 (observed 2026-08-28T04:04:03.683983+00:00)

## What it is
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
- artifact type: library
- maturity: active
- function: data-science, math, parser, data-visualization
- domain: bioinformatics, data-science, education
- platform: python, windows, cli
- tags: bioinformatics, microbiome, sequence-analysis, phylogenetics, diversity-analysis, ordination, multiple-sequence-alignment, genomics, ecology, bsd-license, linux, macos

## Member repositories
- scikit-bio/scikit-bio (main) score 86

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:03.683983+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:15:08.302696+00:00, confidence not recorded.
  - readme: https://github.com/scikit-bio/scikit-bio (fetched 2026-08-28T04:04:03.683983+00:00, sha c5e2a0391b73)
  - homepage: https://scikit.bio (fetched 2026-08-29T12:23:00.928156+00:00, sha e9b1d251fa08)
  - site_page: https://scikit.bio/install.html (fetched 2026-08-29T12:23:00.931414+00:00, sha e6ec4b678ecb)
  - site_page: https://scikit.bio/about.html (fetched 2026-08-29T12:23:00.935596+00:00, sha b76e7ff5c0cb)
  - registry_pypi: https://pypi.org/pypi/scikit-bio/json (fetched 2026-08-29T12:23:00.945200+00:00, sha ee9e64753a74)
- Data as of 2026-08-30T08:39:29.467469+00:00.