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.
CITATION STYLE
Salviato, E., Djordjilović, V., Chiogna, M., & Romualdi, C. (2017). SimPATHy: A new method for simulating data from perturbed biological PATHways. Bioinformatics, 33(3), 456–457. https://doi.org/10.1093/bioinformatics/btw642
Mendeley helps you to discover research relevant for your work.