Bio Stats ML Reporting

Aggregate results, train ML models, and produce reports with validated references.

Instructions

1. Join outputs in DuckDB and build feature tables.
2. Train baseline models and evaluate with cross-validation.
3. Generate reports and validate references.

Quick Reference

Task	Action
Run workflow	Follow the steps in this skill and capture outputs.
Validate inputs	Confirm required inputs and reference data exist.
Review outputs	Inspect reports and QC gates before proceeding.
Tool docs	See docs/README.md.

Input Requirements

Prerequisites:

• Tools available in the active environment (Pixi/conda/system). See docs/README.md for expected tools.
• Results tables and metadata are available. Inputs:
• results/.parquet or results/.tsv
• metadata.tsv

Output

• results/bio-stats-ml-reporting/models/
• results/bio-stats-ml-reporting/metrics.tsv
• results/bio-stats-ml-reporting/report.md
• results/bio-stats-ml-reporting/logs/

Quality Gates

• Model performance sanity checks pass.
• Reference validation passes.
• On failure: retry with alternative parameters; if still failing, record in report and exit non-zero.
• Verify input tables are readable and schema-consistent.

Examples

Example 1: Expected input layout

results/*.parquet or results/*.tsv
metadata.tsv

Troubleshooting

Issue: Missing inputs or reference databases Solution: Verify paths and permissions before running the workflow.

Issue: Low-quality results or failed QC gates Solution: Review reports, adjust parameters, and re-run the affected step.