In future pathway analysis platforms, computational efficiency will be highly-valued given the impressive granularity of next-generation sequencing data. In addition, investigators may wish to use different genomic data sets, pathway annotation databases, and analytical parameters depending on study resources and goals; as such, tools that are flexible to various study approaches will maximize their impact. Finally, given that genes constitute only 1–2% of the human genome, strategies to leverage both genic and non-genic data for pathway analysis may provide increased power to detect meaningful functional sets.
