Package: qpgraph
Title: Reverse engineering of molecular regulatory networks with
        qp-graphs
Version: 1.18.9
Author: R. Castelo and A. Roverato
Description: 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.
Depends: R (>= 3.0.0)
Imports: methods, parallel, Matrix (>= 1.0), annotate, graph (>=
        1.40.1), Biobase, GGBase, AnnotationDbi, mvtnorm, qtl,
        Rgraphviz
Suggests: BiocStyle, genefilter, org.EcK12.eg.db
Enhances: rlecuyer, snow, Category, GOstats
Maintainer: Robert Castelo <robert.castelo@upf.edu>
License: GPL (>= 2)
biocViews: Microarray, GeneExpression, Transcription, Pathways,
        NetworkInference, GraphsAndNetworks, GeneRegulation
LazyData: yes
URL: http://functionalgenomics.upf.edu/qpgraph
Packaged: 2014-02-26 08:14:15 UTC; biocbuild
Built: R 3.0.2; i386-w64-mingw32; 2014-02-26 14:16:00 UTC; windows
Archs: i386, x64
