revise-svc 0.0.4

Spatial transcriptomics benchmarking and annotation toolkit.

REVISE

REVISE is a Python toolkit for reconstruct and analyse spatial transcriptomics (ST) data at single-cell resolution across diverse ST platforms.

Visit our documentation for installation, tutorials, examples and more.

Highlights

• Benchmark module: Reproducible evaluation pipelines for simulated or public datasets, enabling method-to-method comparisons.
• Application module: Annotation, reconstruction, and downstream analyses for real ST data.

Quick Start

If you just need the published Python package:

pip install revise-svc

Example

import anndata as ad
from revise.application import SpSvc

st = ad.read_h5ad("data/spatial.h5ad")
sc = ad.read_h5ad("data/single_cell_reference.h5ad")
config = ...

svc = SpSvc(st, sc, config=config, logger=None)
svc.annotate()
svc.reconstruct()

Repository Layout

• revise/application: SVC workflows for real datasets.
• revise/benchmark: SVC variants for benchmarking studies.
• revise/methods: Algorithm implementations and model components.
• revise/tools: Distance metrics, logging helpers, and general utilities.
• conf: Example configurations and experiment parameters.

License

REVISE is released under the MIT License (see LICENSE).