rely on gene sets or pathways defined in specific databases (e.g., KEGG, Gene Onotology) to organize SNPs for excess statistical significance within a pathway, while accounting for potential confounders like gene size and LD pattern within those genes. In addition to differences among the methodologies, it is also important to note that an inherent limitation of these approaches is the accuracy with which genes are grouped into pathways. Consequently, given the relative strengths and weaknesses of some existing pathway-based approaches and pathway databases, a combined rank approach has recently been developed for aggregating data across multiple approaches (Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium, 2015). Importantly, these methods can be applied to specific candidate pathways, for example “stress response”, if a particular set of genes is thought to impact an outcome of interest.
