clinical-variant-prioritizer

Turn a genotype set into a prioritised list of clinically relevant variants, the way a clinical genome analyst would: screen catalogued disease-gene panels, then rank what is carried by how much it matters, not by how loud the raw ClinVar label is.

This skill implements the pathogenicity-screening stage of Whole Genome Interpretation for a Family of Five (Corpas et al., Front Genet 2021): variants are filtered through OMIM-morbid, ACMG-SF and Hereditary-Cancer panels, intersected with ClinVar significance and gnomAD population frequency, and classified by inheritance model and zygosity.

Why it is not a raw ClinVar lookup

A raw lookup reports a label. This skill reports actionability. The same "pathogenic" allele means very different things depending on context:

Context	Category
Dominant / risk gene, allele carried	actionable
Recessive gene, homozygous	affected
Recessive gene, heterozygous	carrier (reproductive-risk only)
Uncertain / conflicting ClinVar	uncertain (flagged, not acted on)
Benign allele carried	benign
Variant not carried	reference

A heterozygous carrier of a common, recessive, benign-spectrum allele is not an actionable finding, even when ClinVar shows "pathogenic" submissions. Saying so plainly is the point.

Interface

from api import run

result = run(
    {"rs28941785": "CT", "rs1800562": "GG"},   # rsid -> genotype
    options={"panel_path": "..."},              # optional custom panel
)

run() returns:

• summary: panel_size, loci_tested, loci_carried, reference, not_tested, and per-category counts (actionable, affected, carriers, uncertain, benign).
• findings: ranked list (highest priority first); each carries gene, HGVS, consequence, genotype, zygosity, ClinVar significance + review status, gnomAD frequency, condition, inheritance, panel membership, category and a plain-language rationale.
• headline, method, disclaimer.

Panel

data/clinical_panel.json is a curated set of catalogued clinical loci, each shipping its ClinVar significance, ClinVar review status, gnomAD frequency, consequence, condition and inheritance model, so the screen is deterministic and offline-reproducible (no per-call ClinVar/gnomAD/VEP network round-trips). Extend it by adding entries; keys may be rsids or stable variant ids for WGS-only variants not present on arrays.

Limitations

Array-based input covers only catalogued loci and misses most rare variants; a clean screen is not a clean genome. Heterozygous calls do not establish phase. Confirm any finding with an accredited clinical assay. Research and educational use only; not a clinical diagnosis.

Test

python -m pytest tests/ -q