Agnostic GWAS data provide a unique opportunity for hypothesis driven candidate gene exploration, but the sheer size and complexity of GWAS data can be difficult to manage. Although it may not be difficult to find which SNPs of a gene are directly included in a GWAS panel, it is harder to determine which additional SNPs are tagged by the panel, particularly when examining multiple ethnic groups where linkage disequilibrium (LD) structure and allele frequencies differ. There are a growing array of tools for gene annotation (e.g. identifying regulatory elements, alternative splicing, miRNA-binding sites), but many researchers may find it difficult to gather and employ these algorithms. Finally, while such tools predict putative functional regions for the Reference Sequence, they do not necessarily consider if the alternative alleles of SNPs in that sequence are likely to have different consequences.
