pyanglemania

A GPU-ready Python/AnnData port of the R/Bioconductor anglemania package: selects genes whose pairwise correlations stay invariant across batches, for use as integration features (in place of, or alongside, highly-variable genes).

pip install pyanglemania

GPU support is optional and not bundled: pyanglemania dispatches to numpy or cupy based on whatever array adata.X already holds, exactly like rapids-singlecell. To run on a GPU, install cupy for your CUDA version (or get it via rapids-singlecell) and move the data to the device yourself:

pip install "pyanglemania[rapids]"   # pulls cupy-cuda12x

The development environment (including the GPU stack, the tutorial's Harmony/scVI dependencies, and the CUDA headers cupy's JIT needs) is pinned in envs/pyanglemania.yml:

mamba env update -f envs/pyanglemania.yml
pip install -e . --no-build-isolation

import scanpy as sc
import pyanglemania as pa

adata = sc.read_h5ad("data.h5ad")           # raw counts in adata.X (or in a layer)
pa.pp.anglemania(adata, batch_key="batch", max_n_genes=2000)

genes = adata.var_names[adata.var["anglemania_genes"]]

Selected genes land in adata.var["anglemania_genes"] (boolean mask) and adata.uns["anglemania"] (parameters, the ranked gene-pair table, and the gene list). On a GPU, move the layer to the device first — e.g. rapids_singlecell.get.anndata_to_GPU(adata) — and the same call runs on cupy.

See notebooks/tutorial.ipynb for a full walkthrough: simulating multi-batch data, running pp.anglemania, comparing the selected genes against batch-aware highly_variable_genes, and integrating both gene sets with Harmony.

See CLAUDE.md for architecture details and how this maps onto the original R algorithm.

Releases are published to PyPI by .github/workflows/publish.yml using PyPI Trusted Publishing, so no API token lives in this repo. Per release:

1. Bump version in pyproject.toml and commit.
2. git tag v<version> && git push origin v<version>.

The workflow builds the sdist and wheel, runs twine check, verifies the tag matches the package version, and uploads through the pypi GitHub environment. The trusted publisher (owner BIMSBbioinfo, repository pyanglemania, workflow publish.yml, environment pypi) has to be registered once on pypi.org before the first release.