Package: qpgraph
Title: Reverse engineering of molecular regulatory networks with
        qp-graphs
Version: 1.20.2
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 (>=
        1.41.2), 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)
LazyData: yes
URL: http://functionalgenomics.upf.edu/qpgraph
biocViews: Microarray, GeneExpression, Transcription, Pathways,
        NetworkInference, GraphAndNetwork, GeneRegulation
Packaged: 2014-08-03 03:19:45 UTC; biocbuild
Built: R 3.1.1; i386-w64-mingw32; 2014-08-03 11:38:10 UTC; windows
Archs: i386, x64
