scrna-orchestrator

Why This Exists

Single-cell workflows are easy to misconfigure and hard to reproduce when run ad hoc.

• Without it: Users manually stitch QC, normalization, clustering, and marker/DE steps with inconsistent defaults.
• With it: One command produces a consistent report.md, figures, tables, and reproducibility bundle.
• Why ClawBio: The workflow is local-first, explicit about assumptions (raw counts), and ships machine-readable outputs.

Core Capabilities

1. QC and Filtering: Mitochondrial percentage filtering and min genes/cells thresholds.
2. Preprocessing: Library-size normalization, log1p, and HVG selection.
3. Embedding and Clustering: PCA, neighbors graph, UMAP, Leiden clustering.
4. Cluster Markers: Wilcoxon cluster-vs-rest marker detection.
5. Optional Group DE (v1): Two-group Wilcoxon DE on any obs column.
6. Optional Volcano Plot: Generate DE volcano plot with --de-volcano.
7. Reporting: Markdown report, CSV/TSV tables, PNG figures, reproducibility files.

Input Formats

Format	Extension	Required Fields	Example
AnnData raw counts	.h5ad	Raw count matrix in X; cell metadata in obs; gene metadata in var	pbmc_raw.h5ad
Demo mode	n/a	none	python clawbio.py run scrna --demo

Notes:

• Processed/normalized/scaled .h5ad inputs are rejected with an actionable error.
• pbmc3k_processed-style inputs are out of scope for this skill.