Part of this discrepancy is likely due to problems inherent in the assessment of genetic variation. Although recent technological advances have enabled large-scale whole-genome sequencing (WGS) in some studies, most large GWAS have relied on DNA microarray (chip array) analysis, which only genotypes a subset of all genetic variation. In fact, microarray construction must balance numerous factors, like allele frequency, accuracy of genotyping and marker physical position, as well as purported functional role of the polymorphisms.2 Likewise, the identification of the genetic variants themselves has not been a uniform, standardized search, but has instead been conditioned by the search method (expressed sequence tag searches, gene-region searches, etc), and also by the genotyped population, with some variants common in one human population being rare or absent in others.6,7 As a result, a GWAS can provide the most-associated variant as the “best available marker”, rather than as the “probable causal variant”. Similarly, even in the case of WGS, non-random association of specific alleles at specific positions (known as “Linkage Disequilibrium” - LD),8 complicates the problem of detecting the variant effectively associated with a disease or phenotype in a “haplotype block”.
