Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework
Open accessAbstract
Purpose We evaluated the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant pathogenicity guidelines for internal consistency and compatibility with Bayesian statistical reasoning.Methods The ACMG/AMP criteria were translated into a naive Bayesian classifier, assuming four levels of evidence and exponentially scaled odds of pathogenicity. We tested this framework with a range of prior probabilities and odds of pathogenicity.Results We modeled the ACMG/AMP guidelines using biologically plausible assumptions. Most ACMG/AMP combining criteria were compatible. One ACMG/AMP likely pathogenic combination was mathematically equivalent to pathogenic and one ACMG/AMP pathogenic combination was actually likely pathogenic. We modeled combinations that include evidence for and against pathogenicity, showing that our approach scored some combinations as pathogenic or likely pathogenic that ACMG/AMP would designate as variant of uncertain significance (VUS).Conclusion By transforming the ACMG/AMP guidelines into a Bayesian framework, we provide a mathematical foundation for what was a qualitative heuristic. Only 2 of the 18 existing ACMG/AMP evidence combinations were mathematically inconsistent with the overall framework. Mixed combinations of pathogenic and benign evidence could yield a likely pathogenic, likely benign, or VUS result. This quantitative framework validates the approach adopted by the ACMG/AMP, provides opportunities to further refine evidence categories and combining rules, and supports efforts to automate components of variant pathogenicity assessments.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The estimated prevalence of pathogenic variants in the gnomAD reference set was 4.41%.
“This procedure yielded a prior probability of pathogenicity (prevalence in the data set) of 4.41%, higher than that estimated previously for an exome of a healthy individual19 using a similar procedure but lower than the prevalence of 10% assumed by Tavtigian et al.9 for clinical sequencing data.”
From Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria (2022) · cites this paper as [9]
Under reasonable assumptions, a positive likelihood ratio of pathogenicity was used to quantify the strength of evidence corresponding to a supporting level, and the strength of evidence required for moderate, strong, and very strong rose exponentially.
“Under reasonable assumptions, we used a positive likelihood ratio of pathogenicity to quantify the strength of evidence that corresponds to a supporting level of evidence and established that, within this framework, the strength of evidence required for moderate, strong, and very strong rose exponentially.9”
From Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria (2022) · cites this paper as [9]
The authors previously modeled the ACMG/AMP rules for combining evidence and showed how they fit a probabilistic framework.
“We have previously modeled the ACMG/AMP rules for combining evidence and showed how they fit a probabilistic framework.9”
From Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria (2022) · cites this paper as [9]
These fractions were smaller than the experience-based prior probability assumed by Tavtigian et al. (10%) and the prior probability estimated in this study using the gnomAD set (4.41%).
“These fractions were smaller than the experience-based prior probability assumed by Tavtigian et al.9 (10%) and the prior probability that was estimated in this study using the gnomAD set (4.41%).”
From Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria (2022) · cites this paper as Tavtigian et al.9
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Richards, S., Aziz, N., Bale, S., Bick, D., Das, S., Gastier-Foster, J., Grody, W. W., Hegde, M., Lyon, E., Spector, E., et al. (2015) · Genetics in Medicine · doi:10.1038/gim.2015.30 · Cited by 32,594 · see citing works
Plon, S. E., Eccles, D. M., Easton, D., Foulkes, W. D., Genuardi, M., Greenblatt, M. S., Hogervorst, F. B. L., Hoogerbrugge, N., Spurdle, A. B., Tavtigian, S. V., et al. (2008) · Human Mutation · doi:10.1002/humu.20880 · Cited by 912 · see citing works
Self-citationInSiGHT, O. B. O., Thompson, B. A., Spurdle, A. B., Plazzer, J., Greenblatt, M. S., Akagi, K., Al‐Mulla, F., Bapat, B. V., Bernstein, I., Capellá, G., et al. (2013) · Nature Genetics · doi:10.1038/ng.2854 · Cited by 468 · see citing works
Self-citationEaston, D. F., Deffenbaugh, A. M., Pruss, D., Frye, C., Wenstrup, R. J., Allen-Brady, K., Tavtigian, S. V., Monteiro, A. N. A., Iversen, E. S., Couch, F. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/521032 · Cited by 455 · see citing works
Self-citationGoldgar, D. E., Easton, D. F., Deffenbaugh, A. M., Monteiro, Á. N. A., Tavtigian, S. V., & Couch, F. J. (2004) · The American Journal of Human Genetics · doi:10.1086/424388 · Cited by 391 · see citing works
Self-citationTavtigian, S. V., Byrnes, G. B., Goldgar, D. E., & Thomas, A. (2008) · Human Mutation · doi:10.1002/humu.20896 · Cited by 228 · see citing works
Self-citationAnalysis of missense variation in human BRCA1 in the context of interspecific sequence variation
Abkevich, V., Zharkikh, A., Deffenbaugh, A. M., Frank, D., Chen, Y., Shattuck, D., Skolnick, M. H., Gutin, A., & Tavtigian, S. V. (2004) · Journal of Medical Genetics · doi:10.1136/jmg.2003.015867 · Cited by 157 · see citing works
Self-citationA Full-Likelihood Method for the Evaluation of Causality of Sequence Variants from Family Data
Thompson, D. J., Easton, D. F., & Goldgar, D. E. (2003) · The American Journal of Human Genetics · doi:10.1086/378100 · Cited by 141 · see citing works
Thompson, B. A., Goldgar, D. E., Paterson, C. A., Clendenning, M., Walters, R., Arnold, S., Parsons, M. T., Walsh, M. D., Gallinger, S., Haile, R. W., et al. (2012) · Human Mutation · doi:10.1002/humu.22213 · Cited by 95 · see citing works
Self-citationThompson, B. A., Greenblatt, M. S., Vallee, M. P., Herkert, J. C., Tessereau, C., Young, E. L., Adzhubey, I. A., Li, B., Bell, R., Feng, B., et al. (2013) · Human Mutation · doi:10.1002/humu.22214 · Cited by 95 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Riggs, E. R., Andersen, E., Cherry, A. M., Kantarci, S., Kearney, H. M., Patel, A., Raca, G., Ritter, D., South, S. T., Thorland, E. C., et al. (2019) · Genetics in Medicine · doi:10.1038/s41436-019-0686-8 · Cited by 1,789 · see citing works
Recommendations for interpreting the loss of function PVS1 ACMG/AMP variant criterion
Tayoun, A. N. A., Pesaran, T. F., DiStefano, M. T., Oza, A. M., Rehm, H. L., Biesecker, L. G., Harrison, S. M., & ClinGen Sequence Variant Interpretation Working Group (ClinGen SVI) (2018) · Human Mutation · doi:10.1002/humu.23626 · Cited by 893 · see citing works
Self-citationBrnich, S. E., Tayoun, A. N. A., Couch, F. J., Cutting, G. R., Greenblatt, M. S., Heinen, C. D., Kanavy, D., Luo, X., McNulty, S. M., Starita, L. M., et al. (2019) · Genome Medicine · doi:10.1186/s13073-019-0690-2 · Cited by 645 · see citing works
Self-citationPejaver, V., Byrne, A. B., Feng, B.-J., Pagel, K. A., Mooney, S. D., Karchin, R., O’Donnell-Luria, A., Harrison, S. M., Tavtigian, S. V., Greenblatt, M. S., et al. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.10.013 · Cited by 589 · see citing works
Self-citationExpert specification of the ACMG/AMP variant interpretation guidelines for genetic hearing loss
Oza, A. M., DiStefano, M. T., Hemphill, S. E., Cushman, B. J., Grant, A. R., Siegert, R. K., Shen, J., Chapin, A., Boczek, N. J., Schimmenti, L. A., et al. (2018) · Human Mutation · doi:10.1002/humu.23630 · Cited by 487 · see citing works
Genome-wide prediction of disease variant effects with a deep protein language model
Brandes, N., Goldman, G., Wang, C. H., Ye, C., & Ntranos, V. (2023) · Nature Genetics · doi:10.1038/s41588-023-01465-0 · Cited by 459 · see citing works
Kelly, M., Caleshu, C. A., Morales, A., Buchan, J. G., Wolf, Z. T., Harrison, S. M., Cook, S. A., Dillon, M. W., Garcia, J., Haverfield, E. V., et al. (2018) · Genetics in Medicine · doi:10.1038/gim.2017.218 · Cited by 365 · see citing works
Self-citationFitting a naturally scaled point system to the ACMG/AMP variant classification guidelines
Tavtigian, S. V., Harrison, S. M., Boucher, K. M., & Biesecker, L. G. (2020) · Human Mutation · doi:10.1002/humu.24088 · Cited by 365 · see citing works
Self-citationWalker, L., de la Hoya, M., Wiggins, G., Lindy, A., Vincent, L., Parsons, M., Canson, D., Bis-Brewer, D. M., Cass, A., Tchourbanov, A., et al. (2023) · American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.06.002 · Cited by 331 · see citing works
Self-citationRates and Classification of Variants of Uncertain Significance in Hereditary Disease Genetic Testing
Chen, E. Y., Facio, F. M., Aradhya, K., Rojahn, S., Hatchell, K. E., Aguilar, S. J., Ouyang, K., Saitta, S. C., Hanson‐Kahn, A., Nakousi‐Capurro, N., et al. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.39571 · Cited by 238 · see citing works
GestaltMatcher facilitates rare disease matching using facial phenotype descriptors
Hsieh, T.-C., Bar-Haim, A., Moosa, S., Ehmke, N., Gripp, K. W., Pantel, J. T., Danyel, M., Mensah, M. A., Horn, D., Rosnev, S., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-01010-x · Cited by 233 · see citing works
Overview of Specifications to the ACMG/AMP Variant Interpretation Guidelines
Harrison, S. M., Biesecker, L. G., & Rehm, H. L. (2019) · Current Protocols in Human Genetics · doi:10.1002/cphg.93 · Cited by 232 · see citing works
Self-citationGenomic Diagnosis of Rare Pediatric Disease in the United Kingdom and Ireland
Wright, C. F., Campbell, P. H., Eberhardt, R. Y., Aitken, S., Perrett, D., Brent, S., Danecek, P., Gardner, E. J., Chundru, V. K., Lindsay, S., et al. (2023) · New England Journal of Medicine · doi:10.1056/nejmoa2209046 · Cited by 222 · see citing works
Updated recommendation for the benign stand‐alone ACMG/AMP criterion
Ghosh, R., Harrison, S. M., Rehm, H. L., Plon, S. E., Biesecker, L. G., & on behalf of ClinGen Sequence Variant Interpretation Working Group (2018) · Human Mutation · doi:10.1002/humu.23642 · Cited by 174 · see citing works
Self-citationSeo, G. H., Kim, T. H., Park, J.-Y., Lee, J., Kim, S., Won, D., Oh, A., Lee, Y., Choi, I. H., Choi, J., et al. (2020) · Clinical Genetics · doi:10.1111/cge.13848 · Cited by 174 · see citing works
Specifications of the ACMG/AMP variant interpretation guidelines for germline TP53 variants
Fortuño, C., Lee, K., Olivier, M., Pesaran, T. F., Mai, P. L., de Andrade, K. C., Attardi, L. D., Crowley, S. B., Evans, D. G., Feng, B., et al. (2020) · Human Mutation · doi:10.1002/humu.24152 · Cited by 170 · see citing works
Gene‐specific criteria for PTEN variant curation: Recommendations from the ClinGen PTEN Expert Panel
Mester, J. L., Ghosh, R., Pesaran, T. F., Huether, R., Karam, R., Hruska, K. S., Costa, H. A., Lachlan, K. L., Ngeow, J. Y. Y., Barnholtz‐Sloan, J. S., et al. (2018) · Human Mutation · doi:10.1002/humu.23636 · Cited by 157 · see citing works
Luo, X., Feurstein, S., Mohan, S., Porter, C. C., Jackson, S. A., Keel, S., Chicka, M., Brown, A. L., Kesserwan, C., Agarwal, A., et al. (2019) · Blood Advances · doi:10.1182/bloodadvances.2019000644 · Cited by 130 · see citing works
Parsons, M., Tudini, E., Li, H.-Y., Hahnen, E., Wappenschmidt, B., Feliubadaló, L., Aalfs, C., Agata, S., Aittomäki, K., Alducci, E., et al. (2019) · Human Mutation · doi:10.1002/humu.23818 · Cited by 15 · see citing works
Brlek, P., Bulić, L., Bračić, M., Projić, P., Škaro, V., Shah, N. D., Shah, P. S., & Primorac, D. (2024) · Cells · doi:10.3390/cells13060504 · Cited by 141 · see citing works
Massively parallel functional testing of MSH2 missense variants conferring Lynch syndrome risk
Jia, X., Burugula, B. B., Chen, V., Lemons, R. M., Jayakody, S., Maksutova, M., & Kitzman, J. O. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.12.003 · Cited by 133 · see citing works
Tamborero, D., Dienstmann, R., Rachid, M. H., Boekel, J., López‐Fernández, A., Jonsson, M., Razzak, A., Braña, I., Petris, L. D., Yachnin, J., et al. (2022) · Nature Cancer · doi:10.1038/s43018-022-00332-x · Cited by 131 · see citing works
Walsh, R., Mazzarotto, F., Whiffin, N., Buchan, R. J., Midwinter, W., Wilk, A., Li, N., Felkin, L. E., Ingold, N., Govind, R., et al. (2019) · Genome Medicine · doi:10.1186/s13073-019-0616-z · Cited by 120 · see citing works
Fayer, S., Horton, C., Dines, J. N., Rubin, A. F., Richardson, M. E., McGoldrick, K., Hernandez, F., Pesaran, T. F., Karam, R., Shirts, B. H., et al. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.11.001 · Cited by 112 · see citing works
Biesecker, L. G., Byrne, A. B., Harrison, S. M., Pesaran, T. F., Schäffer, A. A., Shirts, B. H., Tavtigian, S. V., & Rehm, H. L. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.11.009 · Cited by 107 · see citing works
Self-citationChinn, I., Chan, A. Y., Chen, K., Chou, J., Dorsey, M., Hajjar, J., Jongco, A., Keller, M., Kobrynski, L., Kumánovics, A., et al. (2019) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2019.09.009 · Cited by 87 · see citing works
Amendola, L. M., Muenzen, K., Biesecker, L. G., Bowling, K. M., Cooper, G. M., Dorschner, M. O., Driscoll, C. C., Foreman, A. K. M., Golden‐Grant, K. L., Greally, J. M., et al. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.09.011 · Cited by 106 · see citing works
Self-citationParsons, M. T., de la Hoya, M., Richardson, M. E., Tudini, E., Anderson, M. G., Berkofsky‐Fessler, W., Caputo, S. M., Chan, R. C., Cline, M., Feng, B., et al. (2024) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2024.07.013 · Cited by 104 · see citing works
Self-citationWalsh, R., Lahrouchi, N., Tadros, R., Kyndt, F., Glinge, C., Postema, P. G., Amin, A. S., Nannenberg, E. A., Ware, J. S., Whiffin, N., et al. (2020) · Genetics in Medicine · doi:10.1038/s41436-020-00946-5 · Cited by 99 · see citing works
Germ line predisposition variants occur in myelodysplastic syndrome patients of all ages
Feurstein, S. K., Trottier, A. M., Estrada‐Merly, N., Pozsgai, M. J., McNeely, K. E., Drazer, M. W., Ruhle, B. C., Sadera, K., Koppayi, A. L., Scott, B. L., et al. (2022) · Blood · doi:10.1182/blood.2022015790 · Cited by 96 · see citing works
The genetics and pathogenesis of CAKUT
Kolvenbach, C. M., Shril, S., & Hildebrandt, F. (2023) · Nature Reviews Nephrology · doi:10.1038/s41581-023-00742-9 · Cited by 95 · see citing works
Stepwise ABC system for classification of any type of genetic variant
Houge, G., Laner, A., Çırak, S., de Leeuw, N., Scheffer, H., & den Dunnen, J. T. (2021) · European Journal of Human Genetics · doi:10.1038/s41431-021-00903-z · Cited by 92 · see citing works
Rapid genomic sequencing for genetic disease diagnosis and therapy in intensive care units: a review
Kingsmore, S. F., Nofsinger, R. R., & Ellsworth, K. (2024) · npj Genomic Medicine · doi:10.1038/s41525-024-00404-0 · Cited by 89 · see citing works
Quinodoz, M., Peter, V. G., Cisarova, K. V., Royer‐Bertrand, B., Stenson, P. D., Cooper, D. N., Unger, S., Superti‐Furga, A., & Rivolta, C. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.01.006 · Cited by 87 · see citing works
PEDIA: prioritization of exome data by image analysis
Hsieh, T., Mensah, M. A., Pantel, J. T., Aguilar, D., Bar, O., Bayat, A., Becerra-Solano, L. E., Bentzen, H. B., Biskup, S., Borisov, O., et al. (2019) · Genetics in Medicine · doi:10.1038/s41436-019-0566-2 · Cited by 88 · see citing works
Nicora, G., Zucca, S., Limongelli, I., Bellazzi, R., & Magni, P. (2022) · Scientific Reports · doi:10.1038/s41598-022-06547-3 · Cited by 59 · see citing works
Deep CRISPR mutagenesis characterizes the functional diversity of TP53 mutations
Funk, J. S., Klimovich, M., Drangenstein, D., Pielhoop, O., Hunold, P., Borowek, A., Noeparast, M., Pavlakis, E., Neumann, M. M., Balourdas, D.-I., et al. (2025) · Nature Genetics · doi:10.1038/s41588-024-02039-4 · Cited by 92 · see citing works
Bergquist, T. R., Stenton, S. L., Nadeau, E. A. W., Byrne, A. B., Greenblatt, M. S., Harrison, S. M., Tavtigian, S. V., O’Donnell‐Luria, A., Biesecker, L. G., Predrag Radivojac, A., et al. (2025) · Genetics in Medicine · doi:10.1016/j.gim.2025.101402 · Cited by 87 · see citing works
Self-citationOn behalf of the Brotman Baty Institute Mutational Scanning Working Group, Gelman, H., Dines, J. N., Berg, J., Berger, A. H., Brnich, S., Hisama, F. M., James, R. G., Rubin, A. F., Shendure, J., et al. (2019) · Genome Medicine · doi:10.1186/s13073-019-0698-7 · Cited by 81 · see citing works
Clinical Interpretation of Sequence Variants
Zhang, J., Yao, Y., He, H., & Shen, J. (2020) · Current Protocols in Human Genetics · doi:10.1002/cphg.98 · Cited by 81 · see citing works
Johnston, J. J., Dirksen, R. T., Girard, T., Gonsalves, S. G., Hopkins, P. M., Riazi, S., Saddic, L., Sambuughin, N., Saxena, R., Stowell, K. M., et al. (2021) · Genetics in Medicine · doi:10.1038/s41436-021-01125-w · Cited by 81 · see citing works
Self-citationPreston, C. G., Wright, M. W., Madhavrao, R., Harrison, S. M., Goldstein, J., Luo, X., Wand, H., Wulf, B., Cheung, G., Mandell, M. E., et al. (2022) · Genome Medicine · doi:10.1186/s13073-021-01004-8 · Cited by 81 · see citing works
Self-citationAlankarage, D., Ip, E., Szot, J., Munro, J. T., Blue, G., Harrison, K., Cuny, H., Enriquez, A., Troup, M., Humphreys, D., et al. (2018) · Genetics in Medicine · doi:10.1038/s41436-018-0296-x · Cited by 77 · see citing works
Çubuk, C., Garrett, A., Choi, S., King, L., Loveday, C., Torr, B., Burghel, G. J., Durkie, M., Callaway, A., Robinson, R., et al. (2021) · Genetics in Medicine · doi:10.1038/s41436-021-01265-z · Cited by 79 · see citing works
Brnich, S. E., Rivera-Munoz, E. A., & Berg, J. S. (2018) · Human Mutation · doi:10.1002/humu.23609 · Cited by 76 · see citing works
Identification of pathogenic variant enriched regions across genes and gene familiesPreprint
Pérez‐Palma, E., May, P., Iqbal, S., Niestroj, L., Du, J., Heyne, H., Lal, J. C., O’Donnell‐Luria, A., Nürnberg, P., Palotie, A. V., et al. (2019) · Genome Research · doi:10.1101/gr.252601.119 · Cited by 76 · see citing works
Mazzarotto, F., Olivotto, I., Boschi, B., Girolami, F., Poggesi, C., Barton, P. J. R., & Walsh, R. (2020) · Journal of the American Heart Association · doi:10.1161/jaha.119.015473 · Cited by 74 · see citing works
AutoPVS1: An automatic classification tool for PVS1 interpretation of null variants
Xiang, J., Peng, J., Baxter, S. M., & Peng, Z. (2020) · Human Mutation · doi:10.1002/humu.24051 · Cited by 73 · see citing works
The Clinical Genome Resource (ClinGen): Advancing genomic knowledge through global curation
Andersen, E., Azzariti, D. R., Babb, L., Berg, J. S., Biesecker, L. G., Bly, Z., Buchanan, A. H., DiStefano, M. T., Gong, L., Harrison, S. M., et al. (2024) · Genetics in Medicine · doi:10.1016/j.gim.2024.101228 · Cited by 72 · see citing works
Self-citationDECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data
Foreman, J., Perrett, D., Mazaika, E., Hunt, S. E., Ware, J. S., & Firth, H. V. (2023) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-102822-100509 · Cited by 68 · see citing works
Shifting landscapes of human MTHFR missense-variant effects
Weile, J., Kishore, N., Sun, S., Maaieh, R., Verby, M., Li, R., Fotiadou, I., Kitaygorodsky, J., Wu, Y., Holenstein, A., et al. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.05.009 · Cited by 67 · see citing works
Self-citationRowlands, C. F., Thomas, H. B., Lord, J., Wai, H. A., Arno, G., Beaman, G. M., Sergouniotis, P. I., Gomes-Silva, B., Campbell, C., Gossan, N. C., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-99747-2 · Cited by 66 · see citing works
Functional evaluation and clinical classification of BRCA2 variants
Huang, H., Hu, C., Na, J., Hart, S. N., Gnanaolivu, R. D., Abozaid, M., Rao, T., Tecleab, Y. A., Ambrosone, C. B., Yao, S., et al. (2025) · Nature · doi:10.1038/s41586-024-08388-8 · Cited by 66 · see citing works
Sharo, A. G., Hu, Z., Sunyaev, S. R., & Brenner, S. E. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.12.007 · Cited by 65 · see citing works
Stawiński, P., & Płoski, R. (2024) · Clinical Genetics · doi:10.1111/cge.14516 · Cited by 65 · see citing works
Walsh, M. F., Ritter, D., Kesserwan, C. A., Sonkin, D., Chakravarty, D., Chao, E., Ghosh, R., Kemel, Y. M., Wu, G., Lee, K., et al. (2018) · Human Mutation · doi:10.1002/humu.23640 · Cited by 65 · see citing works
Tsai, G. J., Rañola, J. M. O., Smith, C., Garrett, L. T., Bergquist, T. R., Casadei, S., Bowen, D. J., & Shirts, B. H. (2018) · Genetics in Medicine · doi:10.1038/s41436-018-0335-7 · Cited by 65 · see citing works
High-throughput functional evaluation of BRCA2 variants of unknown significance
Ikegami, M., Kohsaka, S., Ueno, T., Momozawa, Y., Inoue, S., Tamura, K., Shimomura, A., Hosoya, N., Kobayashi, H., Tanaka, S., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16141-8 · Cited by 62 · see citing works
Jain, S., Bakolitsa, C., Brenner, S. E., Predrag Radivojac, A., Moult, J., Repo, S., Hoskins, R. A., Andreoletti, G., Barsky, D., Chellapan, A., et al. (2024) · Genome biology · doi:10.1186/s13059-023-03113-6 · Cited by 68 · see citing works
Management of Secondary Genomic Findings
Katz, A. E., Nussbaum, R. L., Solomon, B. D., Rehm, H. L., Williams, M. S., & Biesecker, L. G. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.05.002 · Cited by 60 · see citing works
Self-citationJohnston, J. J., Dirksen, R. T., Girard, T., Hopkins, P. M., Kraeva, N., Mungunsukh, O., Radenbaugh, K. B., Riazi, S., Robinson, R. L., Saddic, L., et al. (2022) · Human Molecular Genetics · doi:10.1093/hmg/ddac145 · Cited by 60 · see citing works
Self-citationSystematic misclassification of missense variants in BRCA1 and BRCA2 “coldspots”
Dines, J. N., Shirts, B. H., Slavin, T. P., Walsh, T., King, M., Fowler, D. M., & Pritchard, C. C. (2020) · Genetics in Medicine · doi:10.1038/s41436-019-0740-6 · Cited by 60 · see citing works
Garrett, A., Durkie, M., Callaway, A., Burghel, G. J., Robinson, R., Drummond, J., Torr, B., Çubuk, C., Berry, I. R., Wallace, A. J., et al. (2020) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2020-107248 · Cited by 59 · see citing works
Richardson, M. E., Hu, C., Lee, K. Y., LaDuca, H., Fulk, K., Durda, K. M., Deckman, A., Goldgar, D. E., Monteiro, Á. N. A., Gnanaolivu, R. D., et al. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.02.005 · Cited by 58 · see citing works
Evaluating the impact of in silico predictors on clinical variant classification
Wilcox, E. H., Sarmady, M., Wulf, B., Wright, M. W., Rehm, H. L., Biesecker, L. G., & Tayoun, A. N. A. (2021) · Genetics in Medicine · doi:10.1016/j.gim.2021.11.018 · Cited by 58 · see citing works
Self-citationSaturation genome editing of BAP1 functionally classifies somatic and germline variants
Waters, A. J., Brendler-Spaeth, T., Smith, D., Offord, V., Tan, H. K., Zhao, Y., Obolenski, S., Nielsen, M., van Doorn, R., Murphy, J.-E., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01799-3 · Cited by 57 · see citing works
A functional assay–based procedure to classify mismatch repair gene variants in Lynch syndrome
Drost, M., Tiersma, Y., Thompson, B. A., Frederiksen, J. H., Keijzers, G., Glubb, D. M., Kathe, S. D., Osinga, J., Westers, H., Pappas, L. M., et al. (2018) · Genetics in Medicine · doi:10.1038/s41436-018-0372-2 · Cited by 56 · see citing works
Self-citationArtificial Intelligence and Cardiovascular Genetics
Krittanawong, C., Johnson, K. W., Choi, E., Kaplin, S. L., Venner, E., Murugan, M., Wang, Z., Glicksberg, B. S., Amos, C. I., Schatz, M. C., et al. (2022) · Life · doi:10.3390/life12020279 · Cited by 59 · see citing works
Navigating the nuances of clinical sequence variant interpretation in Mendelian disease
Strande, N. T., Brnich, S. E., Roman, T. S., & Berg, J. S. (2018) · Genetics in Medicine · doi:10.1038/s41436-018-0100-y · Cited by 54 · see citing works
Wang, Y., Xu, Y., Zhou, C., Cheng, Y., Qiao, N., Shang, Q., Xia, L., Song, J., Gao, C., Qiao, Y., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-02912-z · Cited by 52 · see citing works
Garrett, A., Callaway, A., Durkie, M., Çubuk, C., Alikian, M., Burghel, G., Robinson, R., Izatt, L., Talukdar, S., Side, L., et al. (2020) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2019-106759 · Cited by 45 · see citing works
Feurstein, S. K., Adegunsoye, A., Mojsilovic, D., Vij, R., DePersia, A., Rajagopal, P. S., Osman, A. E. G., Collins, R. H., Kim, R. H., Gore, S. D., et al. (2020) · Blood Advances · doi:10.1182/bloodadvances.2020001721 · Cited by 52 · see citing works
Clinical Variant Reclassification in Hereditary Disease Genetic Testing
Kobayashi, Y., Chen, E. Y., Facio, F. M., Metz, H. C., Poll, S. R., Swartzlander, D. B., Johnson, B. A., & Aradhya, S. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.44526 · Cited by 51 · see citing works
UniProt genomic mapping for deciphering functional effects of missense variants
McGarvey, P. B., Nightingale, A., Luo, J., Huang, H., Martin, M. J., & Wu, C. H. (2019) · Human Mutation · doi:10.1002/humu.23738 · Cited by 49 · see citing works
Comparative analysis of functional assay evidence use by ClinGen Variant Curation Expert Panels
Kanavy, D., McNulty, S. M., Jairath, M. K., Brnich, S. E., Bizon, C., Powell, B. C., & Berg, J. S. (2019) · Genome Medicine · doi:10.1186/s13073-019-0683-1 · Cited by 50 · see citing works
O’Neill, M. J., Ng, C., Aizawa, T., Sala, L., Bains, S., Winbo, A., Ullah, R., Shen, Q., Tan, C.-Y., Kozek, K. A., et al. (2024) · Circulation · doi:10.1161/circulationaha.124.069828 · Cited by 46 · see citing works
TAPES: A tool for assessment and prioritisation in exome studies
Xavier, A., Scott, R. J., & Talseth‐Palmer, B. A. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007453 · Cited by 45 · see citing works
Favalli, V., Tini, G., Bonetti, E., Vozza, G., Guida, A., Gandini, S., Pelicci, P. G., & Mazzarella, L. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.03.010 · Cited by 45 · see citing works
Li, H.-Y., LaDuca, H., Pesaran, T., Chao, E. C., Dolinsky, J. S., Parsons, M., Spurdle, A., Polley, E., Shimelis, H., Hart, S., et al. (2019) · Genetics in Medicine · doi:10.1038/s41436-019-0729-1 · Cited by 45 · see citing works
Bianco, S. D., Parca, L., Petrizzelli, F., Biagini, T., Giovannetti, A., Liorni, N., Napoli, A., Carella, M., Procaccio, V., Lott, M. T., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-40797-7 · Cited by 44 · see citing works
DeRoin, L., Silva, M. C. D. A., Petras, K. S., Arndt, K., Phillips, N., Wanjari, P., Subramanian, H. P., Montes, D. M., McElherne, J., Theissen, M., et al. (2022) · Human Mutation · doi:10.1002/humu.24374 · Cited by 43 · see citing works
Fortuño, C., James, P. A., Young, E. L., Feng, B., Olivier, M., Pesaran, T. F., Tavtigian, S. V., & Spurdle, A. B. (2018) · Human Mutation · doi:10.1002/humu.23553 · Cited by 43 · see citing works
Self-citationGenotype–phenotype associations in a large PRPH2 ‐related retinopathy cohort
Reeves, M. J., Goetz, K., Guan, B., Ullah, E., Blain, D., Zein, W. M., Tumminia, S. J., & Hufnagel, R. B. (2020) · Human Mutation · doi:10.1002/humu.24065 · Cited by 43 · see citing works
A fatal case of COQ7‐associated primary coenzyme Q10 deficiency
Kwong, A. K., Chiu, A. T. G., Tsang, M. H., Lun, K., Rodenburg, R. J., Smeitink, J. A. M., Chung, B. H., & Fung, C. (2019) · JIMD Reports · doi:10.1002/jmd2.12032 · Cited by 42 · see citing works
The use of precision diagnostics for monogenic diabetes: a systematic review and expert opinion
Murphy, R., Colclough, K., Pollin, T. I., Iklé, J. M., Svalastoga, P., Maloney, K. A., Saint‐Martin, C., Molnes, J., PMDI, A., Tobias, D. K., et al. (2023) · Communications Medicine · doi:10.1038/s43856-023-00369-8 · Cited by 53 · see citing works
Horton, C., Hoang, L., Zimmermann, H., Young, C. C., Grzybowski, J., Durda, K. M., Vuong, H., Burks, D. J., Cass, A. A., LaDuca, H., et al. (2023) · JAMA Oncology · doi:10.1001/jamaoncol.2023.5586 · Cited by 41 · see citing works
Self-citationAllelic prevalence and geographic distribution of cerebrotendinous xanthomatosis
Pramparo, T., Steiner, R. D., Rodems, S., & Jenkinson, C. P. (2023) · Orphanet Journal of Rare Diseases · doi:10.1186/s13023-022-02578-1 · Cited by 40 · see citing works
Multiplexed assays of variant effect for clinical variant interpretation
McEwen, A. E., Tejura, M., Fayer, S., Starita, L. M., & Fowler, D. M. (2025) · Nature Reviews Genetics · doi:10.1038/s41576-025-00870-x · Cited by 41 · see citing works
Variants of Uncertain Significance
Morales, A., & Hershberger, R. E. (2018) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.118.002169 · Cited by 40 · see citing works
Using Somatic Mutations from Tumors to Classify Variants in Mismatch Repair Genes
Shirts, B. H., Konnick, E. Q., Upham, S. L., Walsh, T., Rañola, J. M. O., Jacobson, A. L., King, M., Pearlman, R., Hampel, H., & Pritchard, C. C. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.05.001 · Cited by 39 · see citing works
LEAP: Using machine learning to support variant classification in a clinical setting
Lai, C., Zimmer, A. D., O'Connor, R., Kim, S., Chan, R., van den Akker, J., Zhou, A. Y., Topper, S., & Mishne, G. (2020) · Human Mutation · doi:10.1002/humu.24011 · Cited by 38 · see citing works
Kountouris, P., Stephanou, C., Lederer, C. W., Traeger‐Synodinos, J., Bento, C., Harteveld, C. L., Fylaktou, I., Koopmann, T. T., Halim‐Fikri, H., Michailidou, K., et al. (2021) · Human Mutation · doi:10.1002/humu.24280 · Cited by 39 · see citing works
Spier, I., Yin, X., Richardson, M. E., Pineda, M., Laner, A., Ritter, D., Boyle, J., Mur, P., Hansen, T. V. O., Shi, X., et al. (2023) · Genetics in Medicine · doi:10.1016/j.gim.2023.100992 · Cited by 38 · see citing works
Self-citationForeman, J., Brent, S., Perrett, D., Bevan, A. P., Hunt, S. E., Cunningham, F. M., Hurles, M. E., & Firth, H. V. (2022) · Human Mutation · doi:10.1002/humu.24340 · Cited by 38 · see citing works
Considerations in assessing germline variant pathogenicity using cosegregation analysis
Belman, S., Parsons, M. T., Spurdle, A. B., Goldgar, D. E., & Feng, B. (2020) · Genetics in Medicine · doi:10.1038/s41436-020-0920-4 · Cited by 37 · see citing works
Junior, P. C. M. L., Nepomuceno, T. C., de Souza, M. L. M., Machado, G. F., Veloso, M. D., Henriques, T. B., dos Santos, D. Z., Ribeiro, I. G., Ribeiro, R. S., Rangel, L. B. A., et al. (2020) · Genetics in Medicine · doi:10.1038/s41436-020-00991-0 · Cited by 37 · see citing works
Geck, R. C., Powell, N. R., & Dunham, M. J. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.01.003 · Cited by 37 · see citing works
Ross, J. E., Zhang, B. M., Lee, K., Mohan, S., Branchford, B. R., Bray, P. F., Dugan, S. N., Freson, K., Heller, P. G., Kahr, W. H. A., et al. (2021) · Blood Advances · doi:10.1182/bloodadvances.2020003712 · Cited by 36 · see citing works
Saturation-scale functional evidence supports clinical variant interpretation in Lynch syndrome
Scott, A. J., Hernandez, F., Chamberlin, A. C., Smith, C., Karam, R., & Kitzman, J. O. (2022) · Genome biology · doi:10.1186/s13059-022-02839-z · Cited by 37 · see citing works
Critical assessment of missense variant effect predictors on disease-relevant variant data
Rastogi, R., Chung, R., Li, S., Li, C., Lee, K., Woo, J., Kim, D., Keum, C., Babbi, G., Martelli, P. L., et al. (2025) · Human Genetics · doi:10.1007/s00439-025-02732-2 · Cited by 36 · see citing works
- Authors
- Tavtigian, S. V., Greenblatt, M. S., Harrison, S. M., Nussbaum, R. L., Prabhu, S. A., Boucher, K. M., & Biesecker, L. G.
- Affiliations
- University of Utah (US)
- University of Vermont (US)
- Harvard University (US)
- Invitae (United States) (US)
- Stanford University (US)
- National Institutes of Health (US)
- Corresponding author
- Tavtigian, Sean V.
- ORCID
- Venue
- Genetics in Medicine
- Publisher
- Elsevier BV
- Published
- 2018-09
- Volume
- 20
- Issue
- 9
- Pages
- 1054-1060
- ISSN
- 1098-3600 (ISSN-L)
- PMC
- PMC6336098
- OpenAlex
- W2781534540
- Cited by
- 590
- References
- 10
- Citations by year
- 2026: 113 · 2025: 81 · 2024: 77 · 2023: 72 · 2022: 84 · 2021: 57 · 2020: 48 · 2019: 37 · 2018: 18 · 2016: 1
- FWCI
- 24.53
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Genetics in Medicine (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- University of Connecticut
- Johns Hopkins University
- Wellcome Trust
- Huntsman Cancer Institute (P30CA042014)
- Invitae
- University of Cambridge
- National Institutes of Health
- University of North Carolina at Chapel Hill
- School of Medicine
- National Human Genome Research Institute (HG200388 03, U41HG009650, U41HG006834, U01HG007436, HG200387, HG200388, U01HG007437, U41HG009649, ZIAHG200388, U24HG009650, ZIAHG200387)
- National Cancer Institute (R01CA164944, R01CA121245, P30CA042014)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › BRCA gene mutations in cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- variant pathogenicity assessment, Bayesian classification, naive Bayesian classifier, variants of uncertain significance, combining rules, prior probability
- MeSH terms
- Bayes Theorem, Genetic Testing, Humans, Software, Genetic Variation, Genome, Human, Sequence Analysis, DNA, Computational Biology, Genomics, High-Throughput Nucleotide Sequencing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
