# theislab/single-cell-best-practices

https://www.sc-best-practices.org

Repository: https://github.com/theislab/single-cell-best-practices
Canonical: https://ross.abutalabs.com/products/single-cell-best-practices
Homepage: https://www.sc-best-practices.org
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Topics: book, rna-seq, single-cell, tutorial
Last push: 2026-08-26T08:20:08+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 8, longevity 100
- inputs: {"age_days": 1846, "days_push": 7, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1253, forks 277 (observed 2026-08-28T04:04:08.777468+00:00)

## What it is
An open-source Jupyter book teaching best practices for single-cell RNA-seq and multi-modal single-cell analysis, accompanying a Nature Reviews Genetics expert recommendation. It provides executable notebooks with Conda environments covering the full single-cell analysis workflow.

## Use cases
- learn single-cell RNA-seq analysis best practices
- tutorial for analyzing scRNA-seq data with Python
- how to preprocess and quality-control single-cell data
- guide for multi-modal single-cell analysis workflows
- reproducible notebooks for single-cell genomics
- learn Scanpy-based single-cell analysis

## When to choose
- you are a beginner or analyst learning single-cell analysis end to end
- you want executable, reproducible notebooks with recommended tools
- you need a citable, community-reviewed reference for single-cell workflows

## When to avoid
- you need production software rather than teaching material
- you require R-only workflows (the book is primarily Python-based)
- you need a maintained tool with guaranteed long-term support - the project is actively seeking maintainers

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, data-science, machine-learning
- domain: bioinformatics, tutorials, education
- platform: python, jvm
- tags: jupyter-book, single-cell-rna-seq, genomics, scanpy, bioinformatics-tutorial

## Member repositories
- theislab/single-cell-best-practices (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:08.777468+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 2026-08-30T05:07:30.776195+00:00, confidence not recorded.
  - readme: https://github.com/theislab/single-cell-best-practices (fetched 2026-08-28T04:04:08.777468+00:00, sha c85c3c326e71)
  - homepage: https://www.sc-best-practices.org (fetched 2026-08-29T12:18:19.998612+00:00, sha 57dd2157f19e)
- Data as of 2026-08-30T08:39:29.467469+00:00.