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Scientific-ToolingScientific-Tooling/structured-intelligence/skills/genome-variant-annotation/SKILL.md

genome-variant-annotation

Skill4 starsChanged 12 days agoMITView on GitHub

Annotate variants with functional effects using SnpEff or Ensembl VEP, adding gene impact, population frequencies, and clinical significance.

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If SnpEff: run snpEff ann with the appropriate database (e.g., GRCh38.105), producing an annotated VCF and summary stats HTML.

    line 29
  2. Very specific:

    If VEP: run vep with --cache, --merged or --refseq, and add plugins (CADD, gnomAD, ClinVar, LOFTEE).

    line 30
  3. Distinctive:

    Add fields to each variant: gene symbol, consequence, impact tier (HIGH / MODERATE / LOW / MODIFIER), HGVS notation.

    line 31

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Skill: genome-variant-annotation

Use When

  • User wants to annotate variants with gene and transcript impact predictions.
  • User needs to predict functional consequences (missense, nonsense, splice-site, etc.).
  • User wants to add population allele frequencies (gnomAD, 1000 Genomes).
  • User wants to add clinical annotations (ClinVar significance).
  • User needs to compare annotation engines (SnpEff vs VEP).

Inputs

  • Required:
    • Filtered VCF file (.vcf.gz).
  • Optional:
    • Annotator choice: snpeff or vep (default: snpeff).
    • Genome build (default: GRCh38).
    • Cache directory for annotation databases.
    • Additional VEP plugins or fields (e.g., CADD, LOFTEE).
    • Output format (default: VCF).

Workflow

  1. If SnpEff: run snpEff ann with the appropriate database (e.g., GRCh38.105), producing an annotated VCF and summary stats HTML.
  2. If VEP: run vep with --cache, --merged or --refseq, and add plugins (CADD, gnomAD, ClinVar, LOFTEE).
  3. Add fields to each variant: gene symbol, consequence, impact tier (HIGH / MODERATE / LOW / MODIFIER), HGVS notation.
  4. Optionally add population allele frequencies from gnomAD.
  5. Generate summary statistics: variants by impact category, genes with HIGH-impact variants.

Output Contract

  • Annotated VCF file (.vcf.gz).
  • Annotation summary: HTML report (SnpEff) or stats file (VEP).
  • Variant impact distribution (HIGH, MODERATE, LOW, MODIFIER counts).

Limits

  • SnpEff and VEP annotation databases must be pre-downloaded to the cache directory.
  • VEP plugins (CADD, LOFTEE, gnomAD) require separate data file downloads.
  • Annotation databases must match the reference genome build (GRCh37 vs GRCh38).
  • VEP is generally slower but more configurable than SnpEff.
  • Large VCFs (millions of variants) may require significant memory and runtime.
  • Common failure cases:
    • SnpEff database name not matching the reference build (e.g., using hg19 when VCF is on GRCh38).
    • VEP cache directory missing or not matching the installed VEP version.
    • VEP plugin data files (CADD, LOFTEE) not downloaded or path misconfigured.

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