scvi-lda
CommunityTopic modeling for single-cell RNA-seq with LDA
Authortony-zhelonkin
Version1.0.0
Installs0
System Documentation
What problem does it solve?
AmortizedLDA provides a scalable topic modeling approach to discover latent transcriptional programs across single-cell RNA-seq data, treating cells as documents and genes as words.
Core Features & Use Cases
- Discover shared transcriptional programs across cell types.
- Identify gene modules and intermediate cell states with interpretable topic space.
- Compare topic structures across conditions or batches using scvi-tools.
Quick Start
Remove MT genes from counts, set up anndata with a counts layer, train AmortizedLDA, and retrieve per-cell topic proportions and gene-topic distributions.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: scvi-lda Download link: https://github.com/tony-zhelonkin/SciAgent-toolkit/archive/main.zip#scvi-lda Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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