Variant-to-Assay

Rare-disease researchers can know that a variant is pathogenic yet still not know what to measure next. I investigated how often public functional evidence can be matched to pathogenic or likely pathogenic protein-truncating variants in neurodevelopmental-disease genes, and built Variant-to-Assay (VTA), an evidence-first analysis that normalizes variant representations, checks transcript and assay context, and evaluates whether existing evidence addresses the specific biological question. In a versioned census of 15,930 public ClinVar variants across 964 genes, only variants 199 of 15,930 variants (1.25%) had an automatically identifiable exact protein-edit match under the frozen mapping rules. When evidence is insufficient, VTA identifies the remaining mechanistic uncertainty and produces a first-measurement plan, essential controls, outcome-dependent next steps, or an explicit abstention. A provisional retrospective routing pilot tied simple NMD and fixed-gene baselines, so VTA does not claim superior biological prediction. Its supported contribution is an auditable decision layer downstream of resources such as MaveDB, MaveMD and ClinMAVE, connecting existing evidence to the next experimental decision.