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scvi-multivi

Integrate paired RNA and ATAC data into a shared latent embedding with cross-modality imputation.

1|Updated Nov 20, 2025
Search Tags:#multimodal#single-cell#scvi-tools#multiome#atac#rna
One-click install
npx skills add https://github.com/tony-zhelonkin/SciAgent-toolkit --skill scvi-multivi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scvi-multivi
Source: https://github.com/tony-zhelonkin/SciAgent-toolkit/tree/main/skills/scvi-multivi
Command: npx skills add https://github.com/tony-zhelonkin/SciAgent-toolkit --skill scvi-multivi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

MultiVI jointly integrates paired and unpaired single-cell RNA and ATAC data using scvi-tools, producing a shared latent embedding with cross-modality imputation. Use when combining 10x Multiome with RNA-only or ATAC-only datasets, when running differential expression plus differential accessibility on joint embeddings, or for multiome batch correction. For ATAC-only analysis use scvi-peakvi; for regulatory TF-to-gene inference on unpaired data use scglue-unpaired-multiomics-integration.

Core Features & Use Cases

  • Joint RNA+ATAC integration with cross-modality imputation producing a shared latent representation.
  • Supports combining 10x Multiome with RNA-only or ATAC-only datasets and joint differential analyses.
  • Provides guidance for data preparation, model configuration, and interpretation of outputs (latent space, imputed modalities).

Quick Start

Prepare an AnnData object with RNA and ATAC modalities and train a scvi-tools MULTIVI model to generate a joint latent embedding and cross-modal imputations.

Frequently Asked Questions about scvi-multivi

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I integrate paired RNA and ATAC data for joint differential analysis?▼

To integrate paired RNA and ATAC data, MultiVI produces a shared latent embedding with cross-modality imputation, enabling joint differential expression and accessibility analyses across combined 10x Multiome datasets.

What is the best way to combine 10x Multiome data with RNA-only or ATAC-only datasets?▼

The best way to combine 10x Multiome with unpaired datasets is using MultiVI to jointly integrate single-cell RNA and ATAC data, yielding a shared latent representation and cross-modal imputations.

Can I use MultiVI for ATAC-only single-cell data integration?▼

No, MultiVI is designed for joint RNA+ATAC integration. For ATAC-only single-cell data integration, you should use scvi-peakvi instead to process your unpaired data.

Do I need a specific AnnData structure to run scvi-tools MultiVI integration?▼

Yes, MultiVI requires proper AnnData structures with explicit modality annotations for RNA and ATAC to successfully configure the scvi-tools model and generate latent representations.

When should I not use MultiVI for multimodal single-cell analysis?▼

Avoid MultiVI for regulatory TF-to-gene inference on unpaired data, where scglue-unpaired-multiomics-integration is more appropriate, or when analyzing strictly ATAC-only datasets.

How does cross-modality imputation work for unpaired single-cell multiome data?▼

Cross-modality imputation works by training a scvi-tools MultiVI model on combined paired and unpaired single-cell RNA and ATAC data, outputting a shared latent space that predicts missing modalities.

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