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 approaches.



The simPATHy is an R package, it is open source and freely available on CRAN.



elisa.salviato.2@studenti.unipd.it or chiara.romualdi@unipd.it



Supplementary data are available at Bioinformatics online.
Department of Biology, University of Padova, Padova, Italy.
Elisa
E
Salviato
Department of Statistical Sciences, University of Padova, Padova, Italy.
Vera
V
Djordjilovic
Department of Statistical Sciences, University of Padova, Padova, Italy.
Monica
M
Chiogna
Department of Biology, University of Padova, Padova, Italy.
Chiara
C
Romualdi
D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D005786:Gene Expression Regulation; D008954:Models, Biological; D015233:Models, Statistical; D012984:Software