Single-cell analysis in Python. Scales to >100M cells.
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Nov 12, 2026 - Python
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Single-cell analysis in Python. Scales to >100M cells.
python data-science machine-learning bioinformatics transcriptomics visualize-data scanpy anndata scverse
Deep probabilistic analysis of single-cell and spatial omics data
deep-learning scrna-seq variational-autoencoder variational-bayes single-cell-genomics single-cell-rna-seq deep-generative-model cite-seq human-cell-atlas scverse
Annotated data.
Spatial Single Cell Analysis in Python
data-visualization spatial-analysis image-analysis single-cell-genomics single-cell-rna-seq spatial-transcriptomics squidpy scverse
rapids-singlecell: GPU-accelerated framework for scRNA analysis
An open and interoperable data framework for spatial omics data
Electronic Health Record Analysis with Python.
epidemiology physionet ehr electronic-health-record clinical-data omop mimic scverse electronic-medical-record
Single-cell perturbation analysis
python bioinformatics computational-biology drug-discovery scrna-seq crispr single-cell differential-expression perturbation anndata scverse differential-abundance perturb-seq
Accessible and interoperable whole slide image analysis for digital pathology in Python
python bioinformatics deep-learning medical-imaging cell-segmentation digital-pathology pathology whole-slide-imaging computational-pathology histopathology spatialdata foundation-models scverse
Python package to perform enrichment analysis from omics data.
python data-science bioinformatics enrichment numba transcriptomics single-cell enrichment-analysis spatial-transcriptomics scverse
muon is a multimodal omics Python framework
muon scrna-seq multi-omics multimodal-data cite-seq scanpy scatac-seq anndata multimodal-omics-analysis mudata scverse
Infer copy number variation (CNV) from scRNA-seq data. Plays nicely with Scanpy.
Multimodal Data (.h5mu) implementation for Python
A single cell transcriptomics pipeline for QC, integration and making the data presentable
workflow quality-control integration pipeline nextflow clustering dimensionality-reduction single-cell nf-core scverse
Accelerated, Python-only, single-cell integration benchmarking metrics
CREsted is a Python package for training sequence-based deep learning models on scATAC-seq data, for capturing enhancer code and for designing cell type-specific sequences.
Notebooks used in scvi-tools tutorials
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