Software
- qpgraph Add-on software package for the
R statistical software to learn
q-order partial graphs (qp-graphs) from multivariate normal data.
qp-graphs are undirected Gaussian graphical Markov models that represent q-order
partial correlations. They are useful for learning undirected
graphical Gaussian Markov models from data sets where the number of
random variables p exceeds the available sample size n as, for
instance, in the case of microarray data where they can be employed
to reverse engineer a molecular regulatory network.
The methods implemented in this package are described in the following articles:
R. Castelo and A. Roverato. A robust procedure for Gaussian graphical model
search from microarray data with p larger than n, Journal of Machine
Learning Research, 7(Dec):2621-2650, 2006.
[abstract and PDF]
R. Castelo and A. Roverato. Reverse engineering molecular regulatory
networks from microarray data with qp-graphs, Journal of Computational
Biology, in press [preprint, supplement].
