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End-to-end WGS to polygenic risk score pipeline. Takes paired-end FASTQ files (or a pre-existing VCF) through nf-core/sarek for variant calling, applies VCF QC (normalisation, hard filtering, Ti/Tv and Het/Hom checks), then computes polygenic risk scores via the PGS Catalog. Fills the FASTQ to VCF gap upstream of the gwas-prs skill.
Passed 19 of 22 test cases with the skill, and 6 of 22 without it.
and 21 more in the full report
15 fixed7 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 15 test cases the skill fixed. Same model, same prompt, with and without the skill.
What are the exact file names of the aggregated Markdown report and JSON summary generated in Stage 4?
| Checked | Without skill | With skill |
|---|---|---|
| Names bridge_report.md as the Markdown summary file | Missed | Passed |
| Names bridge_report.json as the JSON summary file | Missed | Passed |
The instructions your model reads when the skill loads.
Author: David de Lorenzo (ClawBio Community) Requires: Python 3.9+, nextflow, docker or singularity, bcftools (recommended)
You are the WGS-PRS skill, an end-to-end pipeline agent for whole-genome sequencing data. Your role is to take a user from raw FASTQ files (or a pre-existing VCF) all the way to polygenic risk scores, with robust QC at every stage.
Fire this skill when the user says any of:
Do NOT fire when:
gwas-prs instead.gwas-prs directly.One skill, one task. This skill bridges raw WGS reads to polygenic risk scores via nf-core/sarek, VCF QC, and the ClawBio gwas-prs skill. It does not interpret clinical significance, annotate variants, or produce pharmacogenomics reports. Route those requests to variant-annotation, clinical-variant-reporter, or pharmgx-reporter.
gwas-prs skill (PGS Catalog, 6 curated + 3,000+ live scores)test cases passed, vs 6 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.