JointNets R package for Joint Network Estimation, Visualization, Simulation and Evaluation from Heterogeneous Samples
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:
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
Citations
@conference{wang2018jeek,
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}}
}
Support or Contact
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