Perspectives on genome‐wide multi‐stage family‐based association studies

Abstract

With the establishment of large consortiums of researchers, genome-wide association (GWA) studies have become increasingly popular and feasible. Although most of these association studies focus on unrelated individuals, a lot of advantages can be exploited by including families in the analysis as well. To overcome the additional genotyping cost, multi-stage designs are particularly useful. In this article, I offer a perspective view on genome-wide family-based association analyses, both within a model-based and model-free paradigm. I highlight how multi-stage designs and analysis techniques, which are quite popular in clinical epidemiology, can enter GWA settings. I furthermore discuss how they have proven successful in reducing analysis complexity, and in overcoming one of the most cumbersome statistical hurdles in the genome-wide context, namely controlling increased false positives due to multiple testing.