New Bioconductor package: qpgraph
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Robert Castelo ★ 3.4k
@rcastelo
Last seen 11 days ago
Barcelona/Universitat Pompeu Fabra
Dear list, a new package called 'qpgraph' has recently become part of the current development version of Bioconductor (version 2.4). 'qpraph' aids in reverse engineering molecular regulatory networks from microarray data using a formalism called qp-graphs. q-order partial correlation graphs, or qp-graphs for short, 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. You can find an example on how to use it to build a network model of a transcriptional regulatory network in the accompanying vignette (qpTxRegNet.pdf). The description of the approach and further examples can be found in the main text and web supplementary material of the recently published article: R. Castelo and A. Roverato. Reverse engineering molecular regulatory networks from microarray data with qp-graphs, Journal of Computational Biology, 16(2):213-227, 2009. [preprint: http://functionalgenomics.upf.edu/CasRovJCB09.pdf] [supplement: http://functionalgenomics.upf.edu/supplements/qpgraph] We will try to address any question you may have about the package and its methodology and look forward to your comments and suggestions. Best wishes, Robert Castelo.
Microarray Network Microarray Network • 862 views
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