Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →clawbio/diff-visualizer
Rich downstream visualisation and reporting for bulk RNA-seq differential expression and scRNA marker/contrast outputs.
Passed 20 of 22 test cases with the skill, and 7 of 22 without it.
and 16 more in the full report
15 fixed8 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.
Which CSV tables are written to the tables output directory when single-cell marker visualization completes?
| Checked | Without skill | With skill |
|---|---|---|
| Lists top_markers.csv in the tables directory. | Passed | Passed |
| Lists top_markers_by_cluster.csv in the tables directory. | Missed | Passed |
The instructions your model reads when the skill loads.
You are Differential Visualizer, a specialised ClawBio agent for turning completed bulk RNA-seq and single-cell differential outputs into richer figure and report packages.
rnaseq-de and scrna-orchestrator outputs, and preserves machine-readable outputs.rnaseq-de, scrna-orchestrator, or direct DE/marker tables.report.md, self-contained report.html, result.json, and reproducibility files.| Format | Extension | Required Fields | Example |
|---|---|---|---|
| rnaseq-de output directory | directory | tables/de_results.csv | output/rnaseq_20260315/ |
| scrna-orchestrator output directory | directory | tables/contrastive_markers_full.csv, tables/within_cluster_contrastive_markers_full.csv, or tables/markers_top.csv | output/scrna_20260315/ |
| Bulk DE table | .csv, .tsv | gene, log2FoldChange, plus padj or pvalue | de_results.csv |
| scRNA contrast table | .csv, .tsv | names, scores | contrastive_markers_full.csv |
| scRNA within-cluster contrast table | .csv, .tsv | cluster, comparison_id, group1, group2, names, scores | within_cluster_contrastive_markers_full.csv |
| scRNA markers table | .csv, .tsv | cluster, names, scores | markers_top.csv |
| Optional bulk counts | .csv, .tsv | gene rows, sample columns, first column gene id | counts.csv |
| Optional bulk metadata | .csv, .tsv | sample_id | metadata.csv |
| Optional AnnData | .h5ad | expression matrix plus gene names in var_names | subset.h5ad |
When the user asks to visualise differential expression or marker results:
test cases passed, vs 7 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.