JointNets R package for Joint Network Estimation, Visualization, Simulation and Evaluation from Heterogeneous Samples

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jointNets R package: a Suite of Fast and Scalable Tools for Learning Multiple Sparse Gaussian Graphical Models from Heterogeneous Data with Additional Knowledge

JointNets R in CRAN : URL

Github Site: URL

Talk slide by Zhaoyang about the jointnet implementations:

  • URL

  • Youtube Talk by Zhaoyang about the jointnet implementations: URL

Demo GUI Run:


Demo Visualization of a few learned networks:

  • DIFFEE on one gene expression dataset about breast cancer


  • JEEK on one simulated data about samples from multiple contexts and nodes with extra spatial information


  • SIMULE on one word based text dataset including multiple categories



  • SIMULE on one multi-context Brain fMRI dataset


  • Demo downstream task using learned graphs for classification, e.g., on a two class text dataset, we get


  • With Zoom In/Out function


  • With Multiple window design, legend, title coloring schemes


Flow charts of the code design (functional and module level) in jointnets package

multisGGM multisGGM


  Author = {Wang, Beilun and Sekhon, Arshdeep and Qi, Yanjun},
  Booktitle = {Proceedings of The 35th International Conference on Machine Learning (ICML)},
  Title = {A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models},
  Year = {2018}}

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