Simulate data from a Gaussian graphical model or a Gaussian Bayesian network in two conditions. Given a covariance matrix of a reference condition simulate plausible disregulations. See Salviato et al. (2017) <doi:10.1093/bioinformatics/btw642>.
Version: |
0.6 |
Depends: |
R (≥ 3.0) |
Imports: |
mvtnorm, gRbase, graph, igraph, ggm, qpgraph, R.utils, htmlwidgets, shiny, shinydashboard , grDevices, graphics |
Suggests: |
knitr, rmarkdown, clipper, topologyGSA |
Published: |
2021-11-23 |
Author: |
Elisa Salviato [aut, cre],
Vera Djordjilovic [aut],
Chiara Romualdi [aut],
Monica Chiogna [aut] |
Maintainer: |
Elisa Salviato <elisa.salviato.88 at gmail.com> |
License: |
AGPL-3 |
NeedsCompilation: |
no |
CRAN checks: |
simPATHy results |