Weighted multiple testing procedures in genome-wide association studies

Abstract

Multiple testing procedures controlling the false discovery rate (FDR) are increasingly used in the context of genome wide association studies (GWAS), and weighted multiple testing procedures that incorporate covariate information are efficient to improve the power to detect associations. In this work, we evaluate some recent weighted multiple testing procedures in the specific context of GWAS through a simulation study. We also present a new efficient procedure called wBHa that prioritizes the detection of genetic variants with low minor allele frequencies while maximizing the overall detection power. The results indicate good performance of our procedure compared to other weighted multiple testing procedures. In particular, in all simulated settings, wBHa tends to outperform other procedures in detecting rare variants while maintaining good overall power. The use of the different procedures is illustrated with a real dataset.

Keywords: False discovery rate; Genome wide association studies; Weighted MTP.

Figure 1. Overall power comparison in scenario 1, with independent markers (ρ = 0), for different m and m₁ values.

Panels A and B display results for quantitative and binary traits, respectively. Vertical bars illustrate standard errors.

Figure 2. Overall power comparison in scenario 1, with simulations based on real data, for different m₁ values.

Vertical bars illustrate standard errors.

Figure 3. Power comparison in subgroup of rare variants in scenario 1 with independent markers ( ρ = 0), for different m and m₁ values.

Panels A and B display results for quantitative and binary traits, respectively. Vertical bars illustrate standard errors.

Figure 4. Power comparison in subgroup of rare variants in scenario 1, with simulations based on real data, for different m₁ values.

Vertical bars illustrate standard errors.

Figure 5. FDR comparison in scenario 1, with independent markers ( ρ = 0), for different m and m₁ values.

Panels A and B display results for quantitative and binary traits, respectively. Red dashed line corresponds to target FDR level (5%). Vertical bars illustrate standard errors.

Figure 6. FDR comparison in scenario 1, with correlated markers, for different ρ and m₁ values with m = 8000.

Panels A and B display results for quantitative and binary traits, respectively. Red dashed line corresponds to target FDR level (5%). Vertical bars illustrate standard errors.

Figure 7. Number of rejected SNPs for subgroups of SNPs for each procedure.

Figure 8. Venn diagram of selected SNPs for all procedures.