However, in gene-based methods, a consensus has not been reached on the best strategy for SNP information reduction within each gene. A common and simple approach is to represent each gene using the most significant SNP. Since only one SNP P-value is used to represent each gene, the potential effects of multiple association signals for the gene may be missed. In addition, because longer genes are more likely to have significant P-values, this approach may inflate the association test statistic for gene sets that have many long genes. Multiple comparison procedures, such as Sidak’s correction [38], Simes’ correction [39], or False Discovery Rate (FDR) [40], can be used to adjust the most significant P-value (for the number of SNPs located on the gene), but representing genes with the corrected P-values may give overly conservative gene set testing results [5,41].
