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Article

Bayesian Effect Size Ranking to Prioritise Genetic Risk Variants in Common Diseases for Follow-Up Studies.

Genetic epidemiology - 1 Jan 2025

Crouch Daniel J M, Inshaw Jamie R J, Robertson Catherine C, Ng Esther, Zhang Jia-Yuan, Chen Wei-Min, Onengut-Gumuscu Suna, Cutler Antony J, Sidore Carlo, Cucca Francesco, Pociot Flemming, Concannon Patrick, Rich Stephen S, Todd John A

Abstract excerpt

Biological datasets often consist of thousands or millions of variables, e.g. genetic variants or biomarkers, and when sample sizes are large it is common to find many associated with an outcome of interest, for example, disease risk in a GWAS, at high levels of statistical significance, but with very small effects. The False Discovery Rate (FDR) is used to identify effects of interest based on ranking variables...

Topics

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Bayes Theorem
Diabetes Mellitus, Type 1
Follow-Up Studies
Genetic Predisposition to Disease

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Genetic Variation

Genome-Wide Association Study

Mendelian Randomization Analysis

Polymorphism, Single Nucleotide

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Identifiers

PMID: 39749473
DOI: 10.1002/gepi.22608
PMCID: PMC11696485

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