bio-experimental-design-batch-design
Designs experiments to minimize and account for batch effects using balanced layouts and blocking strategies. Use when planning multi-batch experiments, assigning samples to sequencing lanes, or designing studies where technical variation could confound biological signals.
npx skills add BioTender-max/awesome-bio-agent-skills --skill batch-design --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.
## Version Compatibility Reference examples tested with: limma 3.58+ Before using code patterns, verify installed versions match. If versions differ: - R: `packageVersion('<pkg>')` then `?function_name` to verify parameters If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Batch Design and Mitigation **"Design experiment to avoid batch effects"** → Plan sample-to-batch assignments that confound biology with technical variation, and apply correction methods post-hoc. - R: `sva::ComBat()`, `limma::removeBatchEffect()` - Python: `scanpy.pp.combat()` for single-cell data ## Core Principle Batch effects are unavoidable. Good design makes them correctable. ## Design Rules 1. **Never confound batch with condition** - Each batch must contain all conditions 2. **Balance samples across batches** - Equal numbers per condition per batch 3. **Randomize within constraints** - Avoid systematic patterns 4. **Include controls** - Same samples across batches if possible ## Balanced Design Example ```r # BAD: Confounded design # Batch 1: All treated samples # Batch 2: All control samples # -
- Version Compatibility
- Core Principle
- Design Rules
- Balanced Design Example
- Sample Assignment
- Detecting Batch Effects
- Correction Methods
- Documenting Design
- Related Skills
What does the bio-experimental-design-batch-design skill do?
Designs experiments to minimize and account for batch effects using balanced layouts and blocking strategies. Use when planning multi-batch experiments, assigning samples to sequencing lanes, or designing studies where technical variation could confound biological signals.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill batch-design --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.