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scVI-tools single-cell modeling

Fits probabilistic models for single-cell omics: batch integration, annotation, CITE-seq, and differential expression.

Source Download skill
Repository
K-Dense-AI/scientific-agent-skills
Stars
55,780
Licence
MIT
Files
9 files

What it does

This skill teaches an AI agent how to use scvi-tools, a Python library for building statistical models of single-cell biology data. Once installed, the agent knows which model fits which kind of data (RNA, ATAC, protein, methylation, spatial), how the input data must be prepared (for example, raw unnormalized counts for most RNA models), and what checks to run before and after training. It also points to reference files for specialized models and gives a sample workflow for integrating and clustering RNA data. It does not replace standard preprocessing tools like Scanpy for routine exploration.

Great for

  • Bioinformaticians integrating multiple single-cell RNA-seq batches or samples
  • Researchers annotating cells from partial labels or mapping onto a reference atlas
  • Analysts working with CITE-seq or RNA plus ATAC multimodal data who need model-based uncertainty

Skip it if

  • Simple exploratory clustering or standard preprocessing, where Scanpy alone is enough and simpler
  • Clinical or diagnostic decisions: the skill itself notes that its checks do not establish convergence or biological validity
  • Anyone feeding log-normalized or ratio data into models that require raw counts, since this produces misleading results

Try asking

  • “Integrate these three single-cell RNA batches with scVI and cluster the latent space”
  • “Annotate my cells using a partially labelled reference with scANVI”
  • “Run differential expression on this trained model and explain the posterior results”
  • “Set up a totalVI model for my CITE-seq RNA and protein counts”
Step-by-step guide: how to use scVI-tools single-cell modelingInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 9 original files, the MIT licence and an attribution note.

    scvi-tools.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip scvi-tools.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip scvi-tools.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Give the agent your raw count data and describe the batch or sample column so it can set up the model correctly
  • Ask the agent to check seed stability and retention of known biology, not just how well the UMAP looks mixed
  • Review the agent's QC thresholds yourself, since the skill leaves those choices to the experiment

What's inside

  • references/differential-expression.md
  • references/models-atac-seq.md
  • references/models-multimodal.md
  • references/models-scrna-seq.md
  • references/models-spatial.md
  • references/models-specialized.md
  • references/theoretical-foundations.md
  • references/workflows.md
  • SKILL.md

Redistributed unmodified from K-Dense-AI/scientific-agent-skills under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.