Since modern GWAS involve a level of multiple comparisons that are unprecedented in biology, it is important to consider the nature of the trade-off between false-positive and false-negative results. As discussed in Drgon et al. (2011), many GWAS using so-called “template” approaches that demand individual SNPs with p values <10×8 to achieve “genome-wide significance” are so stringent in attempts to reduce false positive findings that they are often unable to identify any significant effects at all (e.g. providing a large number of false negative results instead). Changing the statistical criteria or approach to reduce these false negatives, but in the context of identification of multiple SNP markers in each locus, and replication across multiple samples and multiple marker densities, provides confidence that the loci that are repeatedly identified are in fact truly associated with drug dependence (for a discussion of these alternative approaches such as the clustering strategy see (Drgon, et al., 2010)). The result of this approach has been a high degree of replication across studies. Table 2 presents an analysis from Uhl et al. (2008) which identified 50
