Finally, developing strategies are targeting specific pathway-based challenges. For example, machine learning approaches [11, 59] attempt to identify the most informative subsets of genes within pathways for association. Networks have been effective in studies of rare variants, as with the identification of a synaptogenesis gene network affected by rare CNVs in autism [60]. Pathway-based methods for studying rare variants using genomic-region-based mapping and self-contained tests are also evolving [61, 62]. Indeed, the appeal of pathways and networks will continue to expand as their associated tools progress to analyze a variety of data through user-friendly platforms.
