causal-genomicslisted

# Causal Genomics ## Version Compatibility Reference examples assume recent stable releases of the preferred tools, especially `summary-statistics` and the other tools listed below. Before using code or command patterns, verify installed versions match the environment: - Python: `python -c "import <module>; print(<module>.__version__)"` - CLI: `<tool> --version` - If signatures differ, inspect the installed help or API and adapt the pattern instead of retrying unchanged. ## Overview Workflow for fine-mapping, colocalization, mediation, pleiotropy analysis, and Mendelian randomization. ## When To Use This Skill - use when the task is causal variant, trait-to-gene, or mediation-style genomic inference - use when GWAS and QTL summary data must be integrated - use when the user needs statistical evidence about shared signals or directionality assumptions ## Quick Route - If the input is raw or minimally processed data, start with validation and QC before any modeling. - If the input is already processed, skip directly to the first workflow step that matches the user goal. - If the user asks for a biological conclusion, always produce at least one QC or confidence artifact alongside the final result. ## Progressive Disclosure - Read `references/technical_reference.md` when you need deeper tool-selection rules, environment adaptation notes, or extra validation guidance. - Keep `SKILL.md` as the main execution path and load the reference file only when the task or fail