If you’d like to see your tool included here, please open a pull request!

With ecosystem, we mean the broader single-cell related tools that operate on AnnData. If your tool doesn’t do this, but is useful for analysing single cell data we also accept light wrappers for some tools in scanpy.external.


Interactive manifold viewers.



RNA velocity

Spatial Transcriptomics Tools

  • squidpy Helmholtz Munich

    Squidpy is a comprehensive toolkit for working with spatial single cell omics data.

  • PASTE Princeton

    PASTE is a computational method to align and integrate spatial transcriptomics data across adjacent tissue slices by leveraging both gene expression similarity and spatial distances between spots.

Multimodal integration

  • MUON and MuData EMBL/ DKFZ

    MUON, and it’s associated data structure MuData are designed to organise, analyse, visualise, and exchange multimodal data. MUON enables a range of analyses for ATAC and CITE-seq, from data preprocessing to flexible multi-omics alignment.

Adaptive immune receptor repertoire (AIRR)

  • scirpy Medical University of Innsbruck

    scirpy is a scanpy extension to expore single-cell T-cell receptor (TCR) and B-cell receptor (BCR) repertoires.

  • dandelion University of Cambridge

    dandelion is a single-cell BCR-seq network analysis package that integrates with transcriptomic data analyzed via scanpy.

Long reads

  • Swan UC Irvine

    Swan is a Python library designed for the analysis and visualization of transcriptomes, especially with long-read transcriptomes in mind. Users can add transcriptomes from different datasets and explore distinct splicing and expression patterns across datasets.

Analysis methods


  • scvi-tools Berkeley

    scvi-tools hosts deep generative models (DGM) for end-to-end analysis of single-cell omics data (e.g., scVI, scANVI, totalVI). It also contains several primitives to build novel DGMs.

Fate mapping

  • CellRank Helmholtz Munich

    CellRank is a toolkit to uncover cellular dynamics based on scRNA-seq data with RNA velocity annotation by detecting initial and terminal populations, inferring fate potentials and uncovering gene expression trends towards specific terminal populations.

Differential expression

Data integration

Modeling perturbations

Feature selection

  • triku 🦔 Biodonostia Health Research Institute

  • CIARA Helmholtz Munich

    CIARA is an algorithm for feature selection, that aims for the identification of rare cell types via scRNA-Seq data in scanpy.

Annotation/ Enrichment Analysis

Analyses using curated prior knowledge

  • decoupler is a collection of footprint enrichment methods that allows to infer transcription factor or pathway activities. Institute for Computational Biomedicine, Heidelberg University

  • Cubé Harvard University

    Intuitive Nonparametric Gene Network Search Algorithm that learns from existing biological pathways & multiplicative gene interference patterns.