Cargando…
Behavior of QQ-Plots and Genomic Control in Studies of Gene-Environment Interaction
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[Image: see text]E work these approaches c...
Autores principales: | , , , |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3093379/ https://www.ncbi.nlm.nih.gov/pubmed/21589913 http://dx.doi.org/10.1371/journal.pone.0019416 |
Sumario: | 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[Image: see text]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[Image: see text]E GWAS, and how this differs from main-effects analyses. We also explain how simple adjustments to standard regression-based methods used in G[Image: see text]E GWAS can alleviate this problem. |
---|