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Type I error rates and calculated using (A) the η statistic, (B) q-value, and (C) FDR value across various correction strategies. For each correction type, a vertical line has been drawn at the median value, although this is off the scale for the “No correction” approach in plots (B,C). Additionally, “Our methods” 1 and 2 have the same median value in plots (B,C). In (A), the scale on the x-axis is designed to demonstrate how the various correction methods all vastly outperform the model without any correction. In (B,C), the x-axis scale has focused in on the three correction methods to better demonstrate the gain resulting from our approach.

Type I error rates and calculated using (A) the η statistic, (B) q-value, and (C) FDR value across various correction strategies. For each correction type, a vertical line has been drawn at the median value, although this is off the scale for the “No correction” approach in plots (B,C). Additionally, “Our methods” 1 and 2 have the same median value in plots (B,C). In (A), the scale on the x-axis is designed to demonstrate how the various correction methods all vastly outperform the model without any correction. In (B,C), the x-axis scale has focused in on the three correction methods to better demonstrate the gain resulting from our approach.

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Genome-wide association (GWA) studies have become a standard approach for discovering and validating genomic polymorphisms putatively associated with phenotypes of interest. Accounting for population structure in GWA studies is critical to attain unbiased parameter measurements and control Type I error. One common approach to accounting for populat...

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