bio-workflows-biomarker-pipeline
End-to-end biomarker discovery workflow from expression data to validated biomarker panels. Covers feature selection with Boruta/LASSO, classifier training with nested CV, and SHAP interpretation. Use when building and validating diagnostic or prognostic biomarker signatures from omics data.
npx skills add BioTender-max/awesome-bio-agent-skills --skill biomarker-pipeline --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: matplotlib 3.8+, numpy 1.26+, pandas 2.2+, scanpy 1.10+, scikit-learn 1.4+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Biomarker Discovery Pipeline **"Build a validated biomarker panel from my omics data"** → Orchestrate feature selection (Boruta/LASSO), nested cross-validation classifier training, and SHAP interpretation to produce a robust, validated biomarker signature. Complete pipeline from expression data to validated biomarker panels with classifier. ## Workflow Overview ``` Expression matrix + Metadata | v [1. Data Preparation] -----> StandardScaler, train/test split | v [2. Feature Selection] ----> Boruta or LASSO stability selection | v [3. Model Training] -------> RandomForest/XGBoost with nested CV | v [4. Model Interpretation] -> SHAP values, feature importance | v [5. Validation] -----------> Hold-out test, bootstrap CI | v Validated bioma
- Version Compatibility
- Workflow Overview
- Step 1: Data Preparation
- Step 2: Feature Selection
- Option A: Boruta (All-Relevant Selection)
- Option B: LASSO Stability Selection
- Step 3: Model Training with Nested CV
- Step 4: Model Interpretation
- Step 5: Final Validation
- Parameter Recommendations
- Troubleshooting
- Export Results
- Related Skills
What does the bio-workflows-biomarker-pipeline skill do?
End-to-end biomarker discovery workflow from expression data to validated biomarker panels. Covers feature selection with Boruta/LASSO, classifier training with nested CV, and SHAP interpretation. Use when building and validating diagnostic or prognostic biomarker signatures from omics data.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill biomarker-pipeline --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.