Physical Sciences and Mathematics Commons^™

A Powerful Statistical Framework For Generalization Testing In Gwas, With Application To The Hchs/Sol, Tamar Sofer, Ruth Heller, Marina Bogomolov, Christy L. Avery, Mariaelisa Graff, Kari E. North, Alex Reiner, Timothy A. Thornton, Kenneth Rice, Yoav Benjamini, Cathy C. Laurie, Kathleen F. Kerr

UW Biostatistics Working Paper Series

In GWAS, “generalization” is the replication of genotype-phenotype association in a population with different ancestry than the population in which it was first identified. The standard for reporting findings from a GWAS requires a two-stage design, in which discovered associations are replicated in an independent follow-up study. Current practices for declaring generalizations rely on testing associations while controlling the Family Wise Error Rate (FWER) in the discovery study, then separately controlling error measures in the follow-up study. While this approach limits false generalizations, we show that it does not guarantee control over the FWER or False Discovery Rate (FDR) of …