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Attribute
Single-Cell & Spatial Biology

scArches

Helmholtz Munich (Theis Lab)
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CategorySingle-Cell & Spatial Biology
CompanyHelmholtz Munich (Theis Lab)
PriceFree Open Source
StatusStatus not confirmed
AvailabilityAvailable on GitHub and PyPI
Last checked20/09/2026
FeaturesArchitectural surgery updating reference neural networks with query-specific parameters, Preserves privacy and eliminates batch effects during cross-study integration, Extensible to scRNA-seq, scATAC-seq, and spatial transcriptomics datasets, Integrates with scvi-tools and Scanpy ecosystems
Entry typeOpen Source Software
Access modeOpen Source
AI roleTransfer Learning & Atlas Mapping
Input dataNot recorded
Output dataNot recorded
Licence conditionsBSD-3-Clause
Commercial eligibilityOpen source release
Compute requirements1x GPU (CUDA-enabled) recommended
ValidationNot recorded
TypeTransfer learning framework for single-cell atlases
Intended useNot recorded
CompatibilityNot recorded
ManufacturerHelmholtz Munich / Technical University of Munich
Biological applicationCell-type annotation, patient disease state mapping, and cell atlas expansion
Research workflowQuery single-cell dataset -> map onto reference embedding -> transfer cell annotations
Evidence levelPeer-reviewed research (Nature Biotechnology 2021)
Integration evidencehttps://github.com/theislab/scarches
Laboratory handoffIdentifies novel aberrant disease cell states for targeted drug screening