The code and data supporting the paper: X. F. Zhang, L. Ou-Yang, and H yan (2016) Incorporating prior information into differential network analysis using nonparanormal graphical models.
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README file for Matlab code supporting the paper: X. F. Zhang, L. Ou-Yang, and H yan (2016)
Incorporating prior information into differential network analysis using nonparanormal graphical models.
Contents of this archive
------------------------
This archive contains several folders:
(1) code: source code for computing the sample nonparanormal covariance matrices and solving the pDNA model.
(2) ovarian_cancer: a demo for testing our method using the ovarian cancer gene expression data.
Run "Demo_Ovarian_Cancer.m" in folder "ovarian_cancer" to test the algorithm.
(3) glioblastoma: a demo for testing our method using the glioblastoma gene expression data.
Run "Demo_Glioblastoma.m" in folder "glioblastoma" to test the algorithm.
(4) simulation: a demo for testing our method using the simulated data. Run "Demo_simulation.m" in
folder "simulation" to test the algorithm
Please do not hesitate to contact Dr. Xiao-Fei Zhang <[email protected]> to seek any clarifications
regarding any contents or operation of the archive.
Contact
Xiao-Fei Zhang at [email protected]
[My homepage](http://maths.ccnu.edu.cn/en/info/1077/2795.htm)
School of Mathematics and Statistics, Central China Normal University Wuhan, 430079, China
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