What is GWAB?
Advances in human systems genetics enabled to identify tens of thousands genomic loci that are associated with many traits including complex diseases through genome-wide association studies (GWAS). Despite this initial success of GWAS, it is not the magic bullet for human genetics and suffer from several technical limitations like all other methods. One major shortcoming of GWAS is limited statistical power, partly due to the testing numerous hypotheses simultaneously (i.e., testing significance of association of more than million SNPs in a study). In most association studies, no more than a dozen of SNPs pass a conventional significant threshold (e.g., P ≤ 5x10-8) to be reported as confident candidate genes. This limitation can be partly overcome by increasing sample size, which is an expensive option. Alternatively, weak association signals can be boosted by integrating independent functional information such as molecular interactions. In our previous study, we demonstrated that trait-associated genes with sub-threshold significance score can be rescued by network connections to other significant candidates (Genome Research 2011 Jul; 21(7):1109-21). Recently, more researchers started to release whole summary statistics data of their GWAS, thus our methods would be more extensively used. Therefore, we have constructed a web server for the network-based boosting of human GWAS data, GWAB (genome-wide association boosting).