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Marius1311 merged 1 commit into from
Apr 28, 2025
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Update docstrings and README #2

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4 changes: 1 addition & 3 deletions README.md
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[badge-tests]: https://github.com/quadbio/cellmapper/actions/workflows/test.yaml/badge.svg
[badge-docs]: https://img.shields.io/readthedocs/cellmapper

k-NN-based mapping of cells across representations to tranfer labels, embeddings and expression values. Works for millions of cells, on CPU and GPU, across molecular modalities, between spatial and non-spatial data, for arbitrary query and reference datasets.
k-NN-based mapping of cells across representations to tranfer labels, embeddings and expression values. Works for millions of cells, on CPU and GPU, across molecular modalities, between spatial and non-spatial data, for arbitrary query and reference datasets. Using `faiss` to compute k-NN graphs, CellMapper takes about 30 seconds to transfer cell type labels from 1.5M cells to 1.5M cells on a single RTX 4090 with 60 GB CPU memory.

## Getting started

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## Contact

For questions and help requests, you can reach out in the [scverse discourse][].
If you found a bug, please use the [issue tracker][].

## Citation

Please cite this GitHub repo if you find CellMapper useful for your research.

[uv]: https://github.com/astral-sh/uv
[scverse discourse]: https://discourse.scverse.org/
[issue tracker]: https://github.com/quadbio/cellmapper/issues
[tests]: https://github.com/quadbio/cellmapper/actions/workflows/test.yaml
[documentation]: https://cellmapper.readthedocs.io
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16 changes: 8 additions & 8 deletions src/cellmapper/cellmapper.py
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Expand Up @@ -235,14 +235,14 @@ def compute_mappping_matrix(

Parameters
----------
n_neighbors
Number of nearest neighbors.
use_rep
Data representation based on which to find nearest neighbors.
use_rapids
Whether to use cuML and cuPy for GPU-accelerated nearest neighbor search.
batch_size
Batch size for processing rows during Jaccard computation.
method
Method to use for computing the mapping matrix. Options include:
- "jaccard": Jaccard similarity. Inspired by GLUE: Cao et al., Nature Biotechnology, 2022: https://www.nature.com/articles/s41587-022-01284-4
- "gaussian": Gaussian kernel with adaptive bandwith. Loosely inspired by MAGIC: Van Dijk et al., Cell, 2018: https://www.sciencedirect.com/science/article/pii/S0092867418307244?via%3Dihub
- "scarches": scArches kernel. Inspired by scArches: Lotfollahi et al., Nature Biotechnology, 2021: https://www.nature.com/articles/s41587-021-01001-7
- "inverse_distance": Inverse distance kernel.
- "random": Random kernel, useful for testing.
- "hnoca": HNOCA kernel. Inspired by HNOCA-tools: He et al., Nature 2024: https://www.nature.com/articles/s41586-024-08172-8

Returns
-------
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