期刊
PLOS ONE
卷 6, 期 5, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0019416
关键词
-
资金
- NIH/NHLBI [T32 HL07183-34, R01 HL074745]
Genome-wide association studies of gene-environment interaction (GxE GWAS) are becoming popular. As with main effects GWAS, quantile-quantile plots (QQ-plots) and Genomic Control are being used to assess and correct for population substructure. However, in G x E work these approaches can be seriously misleading, as we illustrate; QQ-plots may give strong indications of substructure when absolutely none is present. Using simulation and theory, we show how and why spurious QQ-plot inflation occurs in G x E GWAS, and how this differs from main-effects analyses. We also explain how simple adjustments to standard regression-based methods used in G x E GWAS can alleviate this problem.
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