Existing disease candidate gene prioritization methodologies mine biological and functional information about candidate genes, and we believe that our ToppGene Suite can complement these existing approaches by applying novel methods that mine mouse phenotype data and PPIN. Through various examples, we demonstrate that ToppGene Suite is capable of identifying true candidate genes. However, it needs to be emphasized that our aim is not to prove that ToppGene Suite-prioritized genes are true disease genes but rather to aid in selection of a subset of most likely disease gene candidates from larger sets of disease-implicated genes identified by high-throughput genome-wide techniques like linkage analysis and microarray analysis. As the functional annotations of human and mouse genes and the quality of PPIN improves, we envisage a proportional increase in the performance of ToppGene Suite and strongly believe that it will be a valuable adjunct to wet lab experiments in human genetics and disease research. We further hypothesize that integrating the rankings obtained using functional annotations and PPIN-based approaches may improve the prioritization of disease genes.
