I'm not sure. I'm looking for just a group of SNPs that just gives a good representation of said gene. eQTL might be useful in terms of seeing what affects the ultimate expression of the protein the gene codes for (and identifying SNPs that are crucial for the expression), but does that necessarily give a representative picture of the gene itself? What I've done so far is just go to SNPedia, search for the gene (for example, IFITM3) and took all SNPs that SNPedia has deemed relevant to that gene. Is this not the best way to do this?
The basic thing I'm trying to do is this: I'm comparing 3 diseases, and I would like to see if there is any difference in genetic variants in the candidate genes that I've chosen for these diseases based on pathophysiology. I don't have enough data for a GWAS, so I'm going with a candidate gene based approach. That's my reason for wanting these "representative" SNPs from each gene.
I've already used PLINK to extract those SNPedia SNPs from my genomic data, but I'm still wondering if there is a better way of making sure that I can optimize my choice of SNPs for this purpose.