Charlie F Rowlands, Alice Garrett, Sophie Allen, Miranda Durkie, George J Burghel, Rachel Robinson, Alison Callaway, Joanne Field, Bethan Frugtniet, Sheila Palmer-Smith, Jonathan Grant, Judith Pagan, Trudi McDevitt, Terri P McVeigh, Helen Hanson, Nicola Whiffin, Michael Jones, Clare Turnbull
{"title":"PS4-似然比计算器:在变异分类中灵活分配病例对照数据的证据权重。","authors":"Charlie F Rowlands, Alice Garrett, Sophie Allen, Miranda Durkie, George J Burghel, Rachel Robinson, Alison Callaway, Joanne Field, Bethan Frugtniet, Sheila Palmer-Smith, Jonathan Grant, Judith Pagan, Trudi McDevitt, Terri P McVeigh, Helen Hanson, Nicola Whiffin, Michael Jones, Clare Turnbull","doi":"10.1136/jmg-2024-110034","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The 2015 American College of Medical Genetics/Association of Molecular Pathology (ACMG/AMP) variant classification framework specifies that case-control observations can be scored as 'strong' evidence (PS4) towards pathogenicity.</p><p><strong>Methods: </strong>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 prespecified OR thresholds. Model 1 represents the hypothesis of association between variant and phenotype (eg, OR≥5) and model 2 represents the hypothesis of non-association (eg, OR≤1).</p><p><strong>Results: </strong>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 data sets generated for more common phenotypes and smaller data sets more typical in very rare disease variant evaluation.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":16237,"journal":{"name":"Journal of Medical Genetics","volume":" ","pages":"983-991"},"PeriodicalIF":3.5000,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11503184/pdf/","citationCount":"0","resultStr":"{\"title\":\"The PS4-likelihood ratio calculator: flexible allocation of evidence weighting for case-control data in variant classification.\",\"authors\":\"Charlie F Rowlands, Alice Garrett, Sophie Allen, Miranda Durkie, George J Burghel, Rachel Robinson, Alison Callaway, Joanne Field, Bethan Frugtniet, Sheila Palmer-Smith, Jonathan Grant, Judith Pagan, Trudi McDevitt, Terri P McVeigh, Helen Hanson, Nicola Whiffin, Michael Jones, Clare Turnbull\",\"doi\":\"10.1136/jmg-2024-110034\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The 2015 American College of Medical Genetics/Association of Molecular Pathology (ACMG/AMP) variant classification framework specifies that case-control observations can be scored as 'strong' evidence (PS4) towards pathogenicity.</p><p><strong>Methods: </strong>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 prespecified OR thresholds. Model 1 represents the hypothesis of association between variant and phenotype (eg, OR≥5) and model 2 represents the hypothesis of non-association (eg, OR≤1).</p><p><strong>Results: </strong>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 data sets generated for more common phenotypes and smaller data sets more typical in very rare disease variant evaluation.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":16237,\"journal\":{\"name\":\"Journal of Medical Genetics\",\"volume\":\" \",\"pages\":\"983-991\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11503184/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Medical Genetics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1136/jmg-2024-110034\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Genetics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/jmg-2024-110034","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
The PS4-likelihood ratio calculator: flexible allocation of evidence weighting for case-control data in variant classification.
Background: The 2015 American College of Medical Genetics/Association of Molecular Pathology (ACMG/AMP) variant classification framework specifies that case-control observations can be scored as 'strong' evidence (PS4) towards pathogenicity.
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 prespecified OR thresholds. Model 1 represents the hypothesis of association between variant and phenotype (eg, OR≥5) and model 2 represents the hypothesis of non-association (eg, OR≤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 data sets generated for more common phenotypes and smaller data sets 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.
期刊介绍:
Journal of Medical Genetics is a leading international peer-reviewed journal covering original research in human genetics, including reviews of and opinion on the latest developments. Articles cover the molecular basis of human disease including germline cancer genetics, clinical manifestations of genetic disorders, applications of molecular genetics to medical practice and the systematic evaluation of such applications worldwide.