qpgraph

Reverse engineering of molecular regulatory networks with qp-graphs

Bioconductor version: 2.9

q-order partial correlation graphs, or qp-graphs for short, are undirected Gaussian graphical Markov models built from 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.

Author: R. Castelo and A. Roverato

Maintainer: Robert Castelo <robert.castelo at upf.edu>

To install this package, start R and enter:

    source("http://bioconductor.org/biocLite.R")
    biocLite("qpgraph")

To cite this package in a publication, start R and enter:

    citation("qpgraph")

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