scvi-tools — Single-Cell Deep Generative Models

Overview

scvi-tools is a probabilistic modeling framework for single-cell genomics built on PyTorch. It implements variational autoencoders (VAEs) that learn low-dimensional latent representations of cells while explicitly modeling batch effects, count noise distributions, and multi-modal data. All models share a unified API: setup_anndata() to register data, instantiate the model, train(), then extract latent representations, normalized

[Description truncada. Veja o README completo no GitHub.]