mievformer
mievformer is a Python package for learning cellular microenvironments from spatial transcriptomics. Its standard workflow uses reference-probability correspondence analysis (CA) for niche clustering and UMAP, with sample-conditional CA for joint analysis of multiple spatial slices.
Installation
pip install mievformer
Documentation
For detailed usage instructions, tutorials, and API reference, please visit the documentation:
https://kojikoji.github.io/mievformer_package/index.html
Quick start
import mievformer as mf
# Single slice: ordinary reference-probability CA.
adata = mf.optimize_nicheformer(adata, model_path="model.pth")
# Multiple slices: batch-conditioned training and sample-conditional CA.
adata = mf.optimize_nicheformer(
adata,
model_path="multibatch_model.pth",
batch_key="sample",
)
License
MIT License
1 maintainer
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