I recently heard that the GWAS regions can be used to identify putatively functional SNPs. for example, if I have a list of GWAS SNPs, say for Breast cancer from some studies and I have a set of mutations from my own study on breast cancer, and if my set of mutations fall within the same region as the mutations described in one of the GWAS studies. Then these mutations may be potentially functional. I am focussing on missense mutations, so that makes things a bit easy.
Could anyone help me in directing in this line, if anyone has followed such an approach in past.
Like, what how far the SNPs can lie from the SNPs identified in GWAS, from where to get the SNPs from GWAS for particular disease or may be better, does a tool already exists to do this?
A key concept you need to be aware of when comparing SNPs is linkage disequilibrium (LD). The idea behind LD is that during recombination, SNPs which are closer to each other are more likely to be inherited together. These LD blocks can be of various size, therefore one should use the LD structure, not the genomic distance in order to evaluate whether or not two SNPs are tagging the same signal. The NCBIs Phenotype-Genoype Integrator contains the largest selection of trait-associated SNPs that I am aware of. I hope this is at least of partial help to you.
