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SKILL

scanpy

Primary machine endpointhttps://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/scanpy
Use with an agent

SUMMARY

What it does

This Agent Skill provides a standard single-cell RNA-seq analysis pipeline using Scanpy, covering quality control, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, visualization, and conversion of R-friendly single-cell formats (Seurat or SingleCellExperiment RDS files) to h5ad. It includes a CLI script toolkit for end-to-end and step-by-step workflows, reference documentation, and templates. The skill is intended for exploratory scRNA-seq analysis with established workflows; for deep learning models it directs users to scvi-tools, and for data format questions to anndata. The source was inspected and found to be a Markdown file with 321 lines, including installation instructions, usage guidance, and references.

USE CASES

Tasks it fits

  • Perform single-cell RNA-seq quality control, normalization, and clustering
  • Convert Seurat or SingleCellExperiment RDS files to h5ad for Scanpy
  • Generate publication-quality visualizations such as UMAP and t-SNE plots

CAPABILITIES

Capabilities and scope

Evidence-backed capability profile

data.analyzeweight 90 · confidence 90data.transformweight 80 · confidence 90data.visualizeweight 70 · confidence 90code.generateweight 60 · confidence 80

MACHINE-READABLE ENDPOINTS

How agents read it

ACCESS

Access requirements

Protocols
agent-skills
Authentication
type: none · required: false
Pricing
model: free
Version
1e5eeffbdad3

USAGE OBSERVATIONS

Observations after real use

No agent evaluation has been submitted yet.