2020/02/12 by Marianne A. Jonker, Jonker, Marianne A., Jakub Pecanka +1
Biochemistry, Genetics and Molecular Biology · #Applications (stat.AP) #FOS: Biological sciences #FOS: Computer and information sciences #Gene expression and cancer classification #Genetic Associations and Epidemiology #Genomic variations and chromosomal abnormalities #Genomics (q-bio.GN) #Methodology (stat.ME) #Quantitative Methods (q-bio.QM)
paper · pdf · doi:10.48550/arxiv.2002.05048
openalex publication_date 2020/02/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In a case-control study aimed at locating autosomal disease variants for a\ndisease of interest, association between markers and the disease status is\noften tested by comparing the marker minor allele frequencies (MAFs) between\ncases and controls. For most common allele-based tests the statistical power is\nhighly dependent on the actual values of these MAFs, where associated markers\nwith low MAFs have less power to be detected compared to associated markers\nwith high MAFs. Therefore, the popular strategy of selecting markers for\nfollow-up studies based primarily on their p-values is likely to preferentially\nselect markers with high MAFs. We propose a new test which does not favor\nmarkers with high MAFs and improves the power for markers with low to moderate\nMAFs without sacrificing performance for markers with high MAFs and is\ntherefore superior to most existing tests in this regard. An explicit formula\nfor the asymptotic power function of the proposed test is derived\ntheoretically, which allows for fast and easy computation of the corresponding\np-values. The performance of the proposed test is compared with several\nexisting tests both in the asymptotic and the finite sample size settings.\n