scanpy

Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.

1.51x

Quality

75%

Does it follow best practices?

Impact

82%

1.51x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./scientific-skills/scanpy/SKILL.md

Evaluation results

54%

14%

Single-Cell QC Pipeline for Tumor Microenvironment Study

QC filtering and metrics

Criteria

Without context

With context

MT- prefix identification

100%

calculate_qc_metrics with qc_vars

100%

filter_cells min_genes threshold

50%

100%

filter_genes min_cells threshold

100%

MT% cell filter

100%

QC violin plot

QC violin jitter

Normalize to 1e4

Log transform

Save raw counts

Save filtered output

100%

Scatter QC plots

94%

26%

Downstream Analysis for PBMC Single-Cell Dataset

Normalization to clustering pipeline

Criteria

Without context

With context

HVG n_top_genes

100%

Regress out covariates

100%

Scale max_value

100%

PCA arpack solver

100%

Neighbors n_neighbors

100%

Neighbors n_pcs

100%

Leiden not Louvain

100%

Multiple resolutions

100%

Wilcoxon method

100%

Save h5ad

100%

Export metadata CSVs

100%

PCA variance ratio plot

100%

46%

Publication Figure Suite for Single-Cell Manuscript

Publication-quality visualization

Criteria

Without context

With context

DPI 300 setting

100%

PDF format

100%

frameon=False

100%

figures directory

100%

use_raw=True for gene expression

100%

legend_loc on data

100%

Multiple marker genes per type

100%

Dot plot included

100%

Heatmap included

100%

facecolor white

100%

legend_fontoutline

100%

Repository: K-Dense-AI/claude-scientific-skills
Commit: 25e1c0f

Evaluated: about 2 months ago
Agent: Claude Code
Model: Claude Sonnet 4.6

Table of Contents

Single-Cell QC Pipeline for Tumor Microenvironment Study Downstream Analysis for PBMC Single-Cell Dataset Publication Figure Suite for Single-Cell Manuscript

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