tooluniverse-single-cell

Single-cell RNA-seq analysis with scanpy/anndata : h5ad data loading.

What this skill does for you

Single-cell RNA-seq analysis with scanpy/anndata : h5ad data loading, scRNA-seq quality control and QC gating (n_genes_by_counts, total_counts, mitochondrial percent / pct_counts_mt, pct_counts_ribo, doublet detection with Scrublet/scDblFinder, ambient RNA / SoupX awareness, empty-droplet filtering, MAD-based thresholds), normalization, dimensionality reduction (PCA, UMAP, t-SNE), clustering (Leiden, Louvain), marker gene identification, cell-type annotation, pseudotime/trajectory analysis. Use for any scRNA-seq workflow, including deciding which cells to filter, flag, or investigate before downstream analysis.

Quoted from the skill description in the pinned source

Who made it

Publishermims-harvard

Repositorytooluniverse

Installs325as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the tooluniverse-single-cell skill from mims-harvard/tooluniverse.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: 40aabf8fbe7b153061f76eeb4be70415dc6f1126. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: 40aabf8fbe7b153061f76eeb4be70415dc6f1126. Raw findings: 1. Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: 40aabf8fbe7b153061f76eeb4be70415dc6f1126. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/mims-harvard/tooluniverse
Pinned skill file: View source at revision
Revision: 40aabf8fbe7b153061f76eeb4be70415dc6f1126
Package hash: sha256:445fa9dffdb52ddf224c25f140cc95d1e6041b8866341c3fb05ff3bd44ec6327
Licence: Apache-2.0