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Perspectives on genome‐wide multi‐stage family‐based association studies
Author(s) -
Van Steen K.
Publication year - 2011
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4259
Subject(s) - genome wide association study , context (archaeology) , false positive paradox , computer science , perspective (graphical) , genetic association , genotyping , data science , biology , artificial intelligence , genetics , single nucleotide polymorphism , paleontology , gene , genotype
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. Copyright © 2011 John Wiley & Sons, Ltd.

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