# omicverse/omicverse

A python library for multi omics included bulk, single cell and spatial RNA-seq analysis.

Repository: https://github.com/omicverse/omicverse
Canonical: https://ross.abutalabs.com/products/omicverse
Homepage: https://omicverse.readthedocs.io/en/latest/
Language: Python
License: GPL-3.0
License Family: copyleft
Topics: bioinformatics, omics, bulk-rna-seq, single-cell
Last push: 2026-09-02T11:31:46+00:00

## Health v2 (maintenance only)
Score: 94/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 100, release rhythm 83, longevity 100
- inputs: {"age_days": 1990, "days_push": 0, "days_rel": 36, "gap_med": 32, "n_releases_24m": 16}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1193, forks 147 (observed 2026-09-03T02:15:15.652694+00:00)

## What it is
OmicVerse is a Python library for multi-omics analysis covering bulk, single-cell, and spatial RNA-seq workflows. It is part of the scverse ecosystem and provides an integrated toolkit for transcriptomic data analysis.

## Use cases
- analyze single-cell rna-seq data in python
- bulk rna-seq differential expression analysis
- spatial transcriptomics analysis
- multi-omics integration pipeline
- cluster and annotate single-cell data
- process scRNA-seq count matrices

## When to choose
- you need a unified Python toolkit spanning bulk, single-cell, and spatial transcriptomics
- you want scverse-ecosystem compatibility (AnnData/scanpy-style workflows)
- you need published, actively maintained omics analysis methods in one library

## When to avoid
- you only need a lightweight single-purpose tool for one narrow analysis step
- your workflow is R/Seurat-based and you prefer Bioconductor packages
- GPL-3.0 licensing is incompatible with your project

## Facets
- artifact type: library
- maturity: active
- function: data-science, machine-learning, data-visualization
- domain: bioinformatics, data-science, machine-learning
- platform: python
- tags: omics, single-cell, bulk-rna-seq, spatial-transcriptomics, scverse, genomics, multi-omics

## Member repositories
- omicverse/omicverse (main) score 94

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:15.652694+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 2026-08-30T06:23:05.345181+00:00, confidence not recorded.
  - readme: https://github.com/omicverse/omicverse (fetched 2026-09-03T02:15:15.652694+00:00, sha f87c56c60f1a)
- Data as of 2026-08-30T08:39:29.467469+00:00.