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.
Profile →npx skills add xuzhougeng/wisp-science --skill scvi-tools --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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-dimension
What does the scvi-tools skill do?
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.
How do I install it?
Run `npx skills add xuzhougeng/wisp-science --skill scvi-tools --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From xuzhougeng/wisp-science, a repository with 895 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.