We are no longer accepting new tools on this page. Instead, please submit your tool to the scverse ecosystem package listing.


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.

  • bento 🍱 UC San Diego

    Bento is an accessible Python toolkit for performing subcellular analysis of spatial transcriptomics data.

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 framework to uncover cellular dynamics based on single-cell data. It incorporates modalities such as RNA velocity, pseudotime, developmental potential, real-time information, etc.

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.