models-scrna-seq

This document covers core models for analyzing single-cell RNA sequencing data in scvi-tools.

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Content

# Single-Cell RNA-seq Models

This document covers core models for analyzing single-cell RNA sequencing data in scvi-tools.

## scVI (Single-Cell Variational Inference)

**Purpose**: Unsupervised analysis, dimensionality reduction, and batch correction for scRNA-seq data.

**Key Features**:
- Deep generative model based on variational autoencoders (VAE)
- Learns low-dimensional latent representations that capture biological variation
- Automatically corrects for batch effects and technical covariates
- Enables normalized gene expression estimation
- Supports differential expression analysis

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