Evaluation of the power and type I error of recently proposed family-based tests of association for rare variants

被引:2
作者
Allison Hainline
Carolina Alvarez
Alexander Luedtke
Brian Greco
Andrew Beck
Nathan L Tintle
机构
[1] Baylor University,Department of Statistics
[2] Florida International University,Department of Biostatistics
[3] University of California,Divison of Biostatistics
[4] Berkeley,Department of Mathematics and Statistics
[5] Grinnell College,Department of Mathematics
[6] Loyola University Chicago,Department of Mathematics, Statistics and Computer Science
[7] Dordt College,undefined
关键词
Rare Variant; Kinship Matrix; Rare Genetic Variation; GAW18 Data; Simulated Phenotype;
D O I
10.1186/1753-6561-8-S1-S36
中图分类号
学科分类号
摘要
Until very recently, few methods existed to analyze rare-variant association with binary phenotypes in complex pedigrees. We consider a set of recently proposed methods applied to the simulated and real hypertension phenotype as part of the Genetic Analysis Workshop 18. Minimal power of the methods is observed for genes containing variants with weak effects on the phenotype. Application of the methods to the real hypertension phenotype yielded no genes meeting a strict Bonferroni cutoff of significance. Some prior literature connects 3 of the 5 most associated genes (p <1 × 10−4) to hypertension or related phenotypes. Further methodological development is needed to extend these methods to handle covariates, and to explore more powerful test alternatives.
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