Individual skill
scvi-tools
Probabilistic single-cell RNA-seq with scvi-tools — scVI for a batch-corrected latent space, scANVI for semi-supervised label transfer, and Bayesian differential expression. Reach for this skill to integrate scRNA-seq batches, embed cells for clustering, transfer annotations from a reference onto a query, or score differentially expressed genes per cluster. For spatial deconvolution / mapping use the cell2location, DestVI, or Tangram methods instead.
resources/skills/scvi-tools/SKILL.md
Source commit 357d1a980056e191f380d0e01ec4fbc7cf529d1b
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 3, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 5,493
- Repository last updated
- Nov 8, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-for-science Repository topic
- local-first Repository topic
- reproducible-research Repository topic
- open-science Repository topic
- ai-research Repository topic
- model-agnostic Repository topic
- scientific-ai Repository topic
- desktop-app Repository topic
- ai-workbench Repository topic
- open-source Repository topic
- engineering Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
.catalog_stampasset · 13 bytesSKILL.mdcore · 14,567 bytesSKILL.mdcore · 14,567 bytesSKILL.mdcore · 14,567 bytesSKILL.mdcore · 14,567 bytesSKILL.mdcore · 14,567 bytesSKILL.mdcore · 14,567 bytesSKILL.mdcore · 14,567 byteskernel.pyruns · 4,535 bytestest_kernel.pyruns · 5,264 bytes
Read excerpt
# scvi-tools — scVI / scANVI
scvi-tools (Gayoso et al. 2022, github.com/scverse/scvi-tools, BSD-3-Clause)
wraps a family
of deep generative models for single-cell omics. The scRNA-seq core is **scVI**
(unsupervised batch-corrected latent embedding) and **scANVI** (scVI + a
classifier head for semi-supervised cell-type label transfer). Both expect
**raw integer UMI counts** and emit a low-dimensional `X_scVI` / `X_scANVI`
that drops into the scanpy neighbors → leiden → umap pipeline.
## Setup (any agent, no API key)
This is a **pure skill** — `kernel.py` is deterministic Python and _you_ (the
base model) do all the reasoning. There is no `host` runtime and no LLM API.