scrna-preprocessing-clustering
Standard scRNA-seq preprocessing and clustering with Scanpy. Use for QC, normalization, HVG selection, PCA, neighbor graph construction, UMAP, Leiden clustering, and export of an analysis-ready AnnData object.
npx skills add BioTender-max/awesome-bio-agent-skills --skill scrna-preprocessing-clustering --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# scRNA Preprocessing And Clustering ## Version Compatibility Reference examples assume: - `scanpy` 1.10+ - `anndata` 0.10+ - `pandas` 2.2+ - `matplotlib` 3.8+ Before using code patterns, verify installed versions match the environment: - Python: `python -c "import scanpy, anndata; print(scanpy.__version__, anndata.__version__)"` - If signatures differ, inspect the installed API and adapt the pattern instead of retrying unchanged. ## Overview Use this skill to turn raw or minimally processed scRNA-seq data into an analysis-ready object with: - QC-filtered cells and genes - normalized expression values - highly variable genes - PCA and UMAP embeddings - Leiden clusters - saved `h5ad` artifact for annotation, DE, integration, or trajectory analysis ## When To Use This Skill - raw 10x matrices, filtered count matrices, or `h5ad` inputs need standard preprocessing - the user wants UMAP, clustering, or marker discovery - downstream tasks depend on a stable single-cell object rather than ad hoc plots ## Quick Route - If the input is already a processed `h5ad`, inspect `adata.raw`, embeddings, cluster columns, and QC columns before rerunning preprocessing. - If the input is raw counts, do
- Version Compatibility
- Overview
- When To Use This Skill
- Quick Route
- Progressive Disclosure
- Default Rules
- Expected Inputs
- Expected Outputs
- Preferred Tools
- Starter Pattern
- Workflow
- 1. Load and validate the object
- 2. Compute QC metrics and inspect distributions
- 3. Filter cells and genes
What does the scrna-preprocessing-clustering skill do?
Standard scRNA-seq preprocessing and clustering with Scanpy. Use for QC, normalization, HVG selection, PCA, neighbor graph construction, UMAP, Leiden clustering, and export of an analysis-ready AnnData object.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill scrna-preprocessing-clustering --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.