Summary: 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 approaches.
Availability and implementation: The simPATHy is an R package, it is open source and freely available on CRAN.
Contacts: elisa.salviato.2@studenti.unipd.it or chiara.romualdi@unipd.it
Supplementary information: Supplementary data are available at Bioinformatics online.