scverse

scverse Foundational tools for single-cell omics data analysis

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import scanpy as sc

sc.pl.umap(data, color='clusters')

Core packages

SnapATAC2

SnapATAC2 is a scalable and modular pipeline for analyzing single-cell ATAC-seq data, enabling efficient preprocessing, dimensionality reduction, clustering, and integration with single-cell RNA-seq.

AnnData

anndata is a Python package for handling annotated data matrices in memory and on disk, positioned between pandas and xarray. anndata offers a broad range of computationally efficient features including, among others, sparse data support, lazy operations, and GPU support.

decoupler

decoupler is a framework containing different enrichment statistical methods to extract biologically driven scores from omics data within a unified framework.

MuData

MuData is a format for annotated multimodal datasets where each modality is represented by an AnnData object. MuData's reference implementation is in Python, and the cross-language functionality is achieved via HDF5-based .h5mu files with libraries in R and Julia.

Muon

muon is a Python framework for multimodal omics analysis. It provides functionality for working with multimodal data, including preprocessing, integration, and visualization.

Pertpy

Pertpy is a framework for analyzing large-scale single-cell perturbation experiments. It harmonizes datasets, automates metadata annotation, calculates perturbation distances, and analyzes cellular responses to genetic modifications, drugs, and environmental changes.

rapids-singlecell

rapids-singlecell is a GPU-accelerated single-cell analysis library that serves as a drop-in replacement for scanpy, squidpy, and decoupler.

Scanpy

Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It includes preprocessing, visualization, clustering, trajectory inference and differential expression testing. The Python-based implementation efficiently deals with datasets of more than one million cells.

Scirpy

Scirpy is a scalable toolkit to analyse T-cell receptor or B-cell receptor repertoires from single-cell RNA sequencing data. It seamlessly integrates with scanpy and provides various modules for data import, analysis and visualization.

scvi-tools

scvi-tools is a library for developing and deploying machine learning models based on PyTorch and AnnData. With an emphasis on probabilistic models, scvi-tools streamlines the development process via training, data management, and user interface abstractions. scvi-tools also contains easy-to-use implementations of more than 14 state-of-the-art probabilistic models in the field.

SpatialData

SpatialData is a data framework that comprises a FAIR storage format and a collection of python libraries for performant access, alignment, and processing of uni- and multi-modal spatial omics datasets.

Squidpy

Squidpy is a tool for the analysis and visualization of spatial molecular data. It builds on top of scanpy and anndata, from which it inherits modularity and scalability. It provides analysis tools that leverages the spatial coordinates of the data, as well as tissue images if available.

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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.