Background Within the 2015 American College of Medical Genetics/Association of Molecular Pathology (ACMG/AMP) variant classification framework, case-control observations can only be scored dichotomously as "strong" evidence (PS4) towards pathogenicity or "nil". Methods We developed the PS4-likelihood ratio calculator (PS4-LRCalc) for quantitative evidence assignment based on the observed variant frequencies in cases and controls. Binomial likelihoods are computed for two models, each defined by pre-specified odds ratio (OR) thresholds. Model one represents the hypothesis of association between variant and phenotype (e.g. OR greater than or equal to 5) and model two represents the hypothesis of non-association (e.g. OR greater than or equal to 1). Results PS4-LRCalc enables continuous quantitation of evidence for variant classification expressed as a likelihood ratio (LR), which can be log-converted into log LR (evidence points). Using PS4-LRCalc, observed data can be used to quantify evidence towards either pathogenicity or benignity. Variants can also be evaluated against models of different penetrance. The approach is applicable to balanced datasets generated for more common phenotypes and smaller datasets more typical in very rare disease variant evaluation. Conclusion PS4-LRCalc enables flexible evidence quantitation on a continuous scale for observed case-control data. The converted LR is amenable to incorporation into the now widely used 2018 updated Bayesian ACMG/AMP framework.

The authors have declared no competing interest.

C.F.R. and S.A. are supported by CG-MAVE, CRUK Programme Award (EDDPGM-Nov22/100004). A.G., and H.H. are supported by CRUK Catalyst Award CanGene-CanVar (C61296/A27223). NW is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (220134/Z/20/Z).

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