A generalized robust allele‐based genetic association test
| Autor: | Lin Zhang, Lei Sun |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Score test Genotype 01 natural sciences General Biochemistry Genetics and Molecular Biology 010104 statistics & probability 03 medical and health sciences Gene Frequency Statistics Covariate Computer Simulation 0101 mathematics Allele Allele frequency Alleles Statistic Genetic association 030304 developmental biology Mathematics 0303 health sciences Models Genetic General Immunology and Microbiology Applied Mathematics Regression analysis General Medicine Hardy–Weinberg principle Regression Phenotype General Agricultural and Biological Sciences |
| Zdroj: | Biometrics. 78:487-498 |
| ISSN: | 1541-0420 0006-341X |
| Popis: | The allele-based association test, comparing allele frequency difference between case and control groups, is locally most powerful. However, application of the classical allelic test is limited in practice, because the method is sensitive to the Hardy–Weinberg equilibrium (HWE) assumption, not applicable to continuous traits, and not easy to account for covariate effect or sample correlation. To develop a generalized robust allelic test, we propose a new allele-based regression model with individual allele as the response variable. We show that the score test statistic derived from this robust and unifying regression framework contains a correction factor that explicitly adjusts for potential departure from HWE, and encompasses the classical allelic test as a special case. When the trait of interest is continuous, the corresponding allelic test evaluates a weighted difference between individual-level allele frequency estimate and sample estimate where the weight is proportional to an individual’s trait value, and the test remains valid under Y - dependent sampling. Finally, the proposed allele-based method can analyze multiple (continuous or binary) phenotypes simultaneously and multi-allelic genetic markers, while accounting for covariate effect, sample correlation and population heterogeneity. To support our analytical findings, we provide empirical evidence from both simulation and application studies. |
| Databáze: | OpenAIRE |
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