Web-enabled classification of SNPs for genome-wide association studies

Whole genome association studies of the genetic under-pinnings of complex phenotypes, and human diseases in particular, have been steadily gaining momentum over the past several years. Yet, the number of polymorphic sites in the human genome, including, but not limited to, Single Nucleotide Polymorphisms (SNPs) is so large that identifying the combination of these few that have a significant effect on the condition of interest remains an overwhelming task. In this manuscript we present a new networked solution, and a program GeneNAB implementing it, to the computational identification and ranking of SNPs likely to be relevant for the phenotype of interest, genome-wide. We expect that the output of this program will be useful to guide further laboratory and clinical studies of these SNPs.