It often seems, however, that the last factor to be considered is the hypothesis of the underlying disease model. Much like choosing a statistical test, each study design is coupled with a specific hypothesis and corresponding assumptions that are tested. Linkage (co-segregation of a genomic region with disease), candidate gene (association of a specific allele within a gene of interest), GWAS (association of common variants), and sequencing (identification of low frequency alleles) carry with them a null hypothesis that can be rejected when the study is sufficiently powered.
In 2000, when the march toward GWAS began, Terwilliger and Göring presented arguments against the common disease/common variant hypothesis, and they recently published an updated perspective on this argument.
Terwilliger JD, Göring HH. Update to Terwilliger and Göring's "Gene mapping in the 20th and 21st centuries" (2000): gene mapping when rare variants are common and common variants are rare. Hum Biol. 2009 Dec;81(5-6):729-33.
I have to admit that GWAS bashing is always a fun read, and the authors go the extra mile by citing references to all those who are now suddenly adopting their view in light of new sequencing technologies. I would however like to point out that the authors could easily find themselves cited in a future publication that denotes the folly of whole-genome sequencing… After all, there are so many possible explanations for the missing heritability of common diseases – why should we expect the multiple rare-variant/common disease hypothesis to be the holy grail?
Besides, EVERYONE knows its all due to methylation. :)