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Suggest Scanpy/Python commands for basic scRNA QC (filtering, mito, UMI).
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Basé sur la classification professionnelle SOC
Manage the BioAPEX current-feature workflow from scoping through review and completion
Turn an analysis request into a Slurm-ready execution plan with commands, resource assumptions, and job structure.
Scale a buffer recipe to a target volume and compute component masses/volumes.
Save a fetched summary or document to the knowledge base for later retrieval (e.g. after PubMed/UniProt lookup).
Interpret scRNA clusters using marker genes and suggest cell type or state.
Critically evaluate a perturbation hypothesis — challenge assumptions, propose negative controls, and flag confounders.
| name | scanpy_qc_commands |
| description | Suggest Scanpy/Python commands for basic scRNA QC (filtering, mito, UMI). |
| category | bio/single_cell_rna |
| version | 1 |
| requires_tools | ["python_repl"] |
| requires_network | false |
| user_invocable | true |
| species | any |
| modality | single_cell_rna |
| stage | qc |
| stability | experimental |
| safety_level | low |
User wants ready-to-run Scanpy (or AnnData) code for QC: calculate_QC_metrics, filter cells/genes, normalize.
Default thresholds: If not given, use common defaults (e.g. mito < 20%, min_genes 200, min_cells 2).
Code: Use python_repl or output a code block with:
Present: Copy-pastable code and one-line note on adjusting thresholds.
