Benchmarking differential abundance methods for finding condition-specific prototypical cells in multi-sample single-cell datasets.

Based on our benchmarking study, we provide a set of recommendations for the optimal usage of single-cell DA testing methods in practice, particularly with respect to factors such as the presence of technical noise (for example batch effects), dataset size, and hyperparameter sensitivity.