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scanpy

8.7

by davila7

69Favorites
411Upvotes
0Downvotes

Single-cell RNA-seq analysis. Load .h5ad/10X data, QC, normalization, PCA/UMAP/t-SNE, Leiden clustering, marker genes, cell type annotation, trajectory, for scRNA-seq analysis.

bioinformatics

8.7

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0

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Data & Analytics

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Quick Review

Excellent single-cell RNA-seq analysis skill with comprehensive coverage of scanpy workflows. The Description clearly communicates all major capabilities (QC, normalization, dimensionality reduction, clustering, marker genes, cell type annotation, trajectory). The SKILL.md provides extensive task knowledge including code examples for all workflow steps, parameter guidance, and best practices. Structure is very clear with a logical flow from quick start through standard workflow to advanced tasks, with well-organized references to supporting files. The skill addresses a highly specialized bioinformatics domain where a CLI agent would struggle significantly - scRNA-seq analysis requires domain expertise, multi-step workflows, and careful parameter tuning. Minor improvement possible: could add a brief troubleshooting section or more explicit decision trees for parameter selection, but overall this is a highly effective, production-ready skill that meaningfully reduces token costs for complex single-cell analyses.

LLM Signals

Description coverage9
Task knowledge10
Structure9
Novelty9

GitHub Signals

18,073
1,635
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71
Last commit 0 days ago

Publisher

davila7

davila7

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davila7

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