Overview

Methods

Abnormality([n_in, model, loss_fn, metrics, ...])	Estimator to quantify the abnormality of a cell's expression profile.
Individuality([n_neighbors, radius, ...])	Computes the individuality of each observation in the data set according to [Wagner2019].
Classifier([n_in, model, loss_fn, metrics, seed])	Classifier to classify a cell as epithelial or non-epithelial cell.

Datasets

breastCancerAtlas([force_load])	Flow cytometry dataset with annotated epithelial cells in ['celltype', 'celltype_class'] of ad.obs.
breastCancerAtlasRaw([force_load])	Raw flow cytometry dataset.
aml_and_healthy([force_load])	AML dataset with cells from healthy and AML patients.
aml_annotated_celltypes([force_load])	AML dataset with cells from healthy donors to show case classification.