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Foundational tools for single-cell omics data analysis
import scanpy as sc
sc.pl.umap(data, color='clusters')
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Core packages
Logo for AnnData
AnnData

Standard for annotated matrices

Logo for MuData
MuData

Multimodal data format

Logo for SpatialData
SpatialData

Spatial data format

Logo for Scanpy
Scanpy

Single-cell analysis framework

Logo for Muon
Muon

Multi-omics analysis framework

Logo for Squidpy
Squidpy

Spatial single-cell analysis

Logo for scvi-tools
scvi-tools

Single-cell machine learning framework

Logo for Scirpy
Scirpy

Single-cell immune sequencing analysis framework

Logo for SnapATAC2
SnapATAC2

Single-cell ATAC analysis framework

Logo for rapids-singlecell
rapids-singlecell

GPU-accelerated framework for scRNA analysis

Logo for Pertpy
Pertpy

Perturbation data analysis framework

Logo for decoupler
decoupler

Enrichment analysis framework

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Ecosystem

A broader ecosystem of packages builds on the scverse core packages. These tools implement models and analytical approaches to tackle challenges in spatial omics, regulatory genomics, trajectory inference, visualization, and more.

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Mission

Scverse is a consortium of foundational tools (mostly in Python) for omics data in life sciences. It has been founded to ensure the long-term maintenance of these core tools.

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Team

Scverse is a community project currently governed by the developers of the core packages. Please reach out if you’d like to be involved!

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References

scverse tools are used in research and industry projects across the globe and are cited in thousands of academic publications. If they are useful in your work, please cite the scverse paper along with the individual packages you used.

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