This repo accompanies the paper "Adversarial learning enables unbiased organism-wide cross-species alignment of single-cell RNA data at scale"
https://www.biorxiv.org/content/10.1101/2024.08.11.607498v2.full
This repo contains three installable modules:
pai: An API for inference of cell-type embeddings and cell-types labels from scRNA datasets - supports H5AD formats downloadable from cellxcgene
pai_soma_data: A wrapper for TileDB needed for exploring the scREF atlas we provide here on the example notebooks we provide on TileDB in the public notebooks at Phenomic/Reading from scREF and scREF-mu
ml_benchmarking: Code needed to run and evaluate ML models on the scREF and scREF-mu banchmark
Everything is released under an MIT license, please feel free to use it, but please cite us as we have cited others.