scVelo

Supports RNA velocity estimation through steady-state models, deep generative modeling, and metabolically labeled transcripts, as cited with papers in Nature Biotechnology and Nature Methods.

Implements an expectation-maximization framework for generalized RNA velocity, enabling analysis of transient cell states in large single-cell datasets, as highlighted in the key features.

Allows estimation of reaction rates for transcription, splicing, and degradation, along with statistical tests to detect different kinetics regimes, per the toolkit's applications.

Developed by Theis Lab with peer-reviewed publications and ongoing support through GitHub discussions and issue tracking, ensuring reliability and community engagement.