exampleDataGraph

<p>(first one being the shared graph and second and third being task specific 1 and 2 graphs)
The graphs are generated from two related random graphs and the underlaying high dimensional gaussian distribution
generates the exampleData dataset. exampleDataGraph serves as a groundtruth to compare in demo(synthetic).</p>

datasets

This is an R implementation of a constrained l1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models (SIMULE). The SIMULE algorithm can be used to estimate multiple related precision matrices. For instance, it can identify context-specific gene networks from multi-context gene expression datasets. By performing data-driven network inference from high-dimensional and heterogenous data sets, this tool can help users effectively translate aggregated data into knowledge that take the form of graphs among entities. Please run demo(simuleDemo) to learn the basic functions provided by this package. For further details, please read the original paper: Beilun Wang, Ritambhara Singh, Yanjun Qi (2017) <DOI:10.1007/s10994-017-5635-7>.

exampleDataGraph: A simulated toy dataset that includes 3 igraph objects

Description

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