simPATHy: a new method for simulating data from perturbed biological PATHways

In the omic era, one of the main aims is to discover groups of functionally related genes that drive the difference between different conditions. To this end, a plethora of potentially useful multivariate statistical approaches has been proposed, but their evaluation is hindered by the absence of a gold standard. Here, we propose a method for simulating biological data-gene expression, RPKM/FPKM or protein abundances-from two conditions, namely, a reference condition and a perturbation of it. Our approach is built upon probabilistic graphical models and is thus especially suited for testing topological wapproaches.