PAST: Pathway Association Studies Tool

Background: In recent years, a bioinformatics method for interpreting GWAS data using metabolic pathway analysis has been developed and successfully used to find significant pathways and mechanisms explaining phenotypic traits of interest in plants. However, the many scripts implementing this method were not straightforward to use, had to be customized for each project, required user supervision, and took more than 24 hours to process data. PAST (Pathway Association Study Tool), a new implementation of this method, has been developed to address these concerns. Results: PAST is implemented as a package for the R language. Two user-interfaces are provided; PAST can be run by loading the package in R and calling its methods, or by using an R Shiny guided user interface. In testing, PAST completed analyses in approximately one hour by processing data in parallel. PAST has many user-specified options for maximum customization. PAST produces the same results as the previously developed method. Conclusions: In order to promote a powerful new method of pathway analysis that interprets GWAS data to find biological mechanisms associated with traits of interest, we developed a more accessible and user friendly tool. This tool is more efficient and requires less knowledge of programming languages to use than previous methods. Moreover, it produces similar results in significantly less time. These attributes make PAST accessible to researchers interested in associating metabolic pathways with GWAS datasets to better understand the genetic architecture and mechanisms affecting phenotype.