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Fitting a naturally scaled point system to the ACMG/AMP variant classification guidelines

2020· article· en· 333 citations· W3045929934 on OpenAlex· 10.1002/humu.24088

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A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Opus teacher head0.049
GPT teacher head0.306
Teacher spread
0.258 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Recently, we demonstrated that the qualitative American College of Medical Genetics and Genomics/Association for Medical Pathology (ACMG/AMP) guidelines for evaluation of Mendelian disease gene variants are fundamentally compatible with a quantitative Bayesian formulation. Here, we show that the underlying ACMG/AMP "strength of evidence categories" can be abstracted into a point system. These points are proportional to Log(odds), are additive, and produce a system that recapitulates the Bayesian formulation of the ACMG/AMP guidelines. The strengths of this system are its simplicity and that the connection between point values and odds of pathogenicity allows empirical calibration of the strength of evidence for individual data types. Weaknesses include that a narrow range of prior probabilities is locked in and that the Bayesian nature of the system is inapparent. We conclude that a points-based system has the practical attribute of user-friendliness and can be useful so long as the underlying Bayesian principles are acknowledged.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

The record

Venue
Human Mutation
Topic
Genomics and Rare Diseases
Field
Biochemistry, Genetics and Molecular Biology
Canadian institutions
Funders
National Center for Advancing Translational SciencesNational Cancer InstituteCanadian Institutes of Health ResearchNational Institutes of Health
Keywords
Bayesian probabilityMendelian inheritanceMedical geneticsMendelian randomizationOddsBiologyGenomicsBayes' theoremComputer scienceComputational biologyPoint (geometry)BioinformaticsGeneticsArtificial intelligenceMachine learningGenomeMathematicsGeneGenetic variants
Has abstract in OpenAlex
yes