Flagship technologies
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QuantBayes: The quantitative omic epidemiology group, et al. “A Bayesian model for quantifying genomic variant evidence sufficiency in Mendelian disease” medRxiv preprint (2025).
DOI | PDF | R package | Application -
Quant: The quantitative omic epidemiology group, et al. “Quantifying prior probabilities for disease-causing variants reveals the top genetic contributors in inborn errors of immunity” medRxiv preprint (2025).
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QV: Lawless, Dylan, et al. “Application of qualifying variants for genomic analysis” In press - Bioinformatics (2026): preprint (2025).
DOI | PDF | Video | Database -
PanelAppRex: The quantitative omic epidemiology group, et al. “PanelAppRex aggregates disease gene panels and facilitates sophisticated search” medRxiv preprint (2025).
Repository | DOI | PDF | Video | Application | Dataset -
Archipelago: Lawless, Dylan, et al. “Archipelago method for variant set association test statistics” Genetic Epidemiology (2026).
Preprint | DOI | PDF | Repository | Application
Currently under review
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Perspective: Hardy-Weinberg a century later and new horizons in clinical genomics. Under review.
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Review: A Bayesian reference model for genetic variant interpretation. Pre-print
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Article: Quant resolves Mendelian disease uncertainty through genome-wide Bayesian inference. Pre-print
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Systematic review: A systematic review of quantitative Bayesian variant causality. Pre-print
Related
- SPHN RDF Omic: van der Horst, E.; Unni, D.; Kopmels, F.; Armida, J.; Touré, V.; Franke, W.; Crameri, K.; Cirillo, E.; Österle, S. “Bridging Clinical and Genomic Knowledge: An Extension of the SPHN RDF Schema for Seamless Integration and FAIRification of Omics Data.” Preprints.org (2023).
DOI | PDF
