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+# PathCNN: Interpretable convolutional neural networks for survival prediction and pathway analysis applied to glioblastoma
+
+Jung Hun Oh <sup>1,†,∗</sup>, Wookjin Choi <sup>2,†</sup>, Euiseong Ko <sup>3</sup>, Mingon Kang <sup>3,∗</sup>, Allen Tannenbaum <sup>4</sup> and Joseph O. Deasy <sup>1</sup>  
+
+<sup>1</sup>Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA, 
+<sup>2</sup>Department of Computer Science, Virginia State University, Petersburg, USA, 
+<sup>3</sup>Department of Computer Science, University of Nevada, Las Vegas, USA and 
+<sup>4</sup>Departments of Computer Science and Applied Mathematics & Statistics, Stony Brook University, New York, USA  
+
+<sup>*</sup>To whom correspondence should be addressed.  
+<sup>†</sup>The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.  
+
+Contact: <ohj@mskcc.org> or <mingon.kang@unlv.edu>
+
+![PathCNN](img/pathcnn.png)
+
+1. Model Building  
+   - PathCNN.py  
+
+2. GradCAM  
+   - PathCNN_GradCAM_modeling.py: to generate a model for GradCAM (PathCNN_model.h5)
+   - PathCNN_GradCAM.py: to generate GradCAM images and a resultant file (pathcnn_gradcam.csv)
+
+3. Multi-omics data
+   - GBM multi-omics data including mRNA expression, CNV, and DNA methylation were downloaded from the CBioPortal database.
+   - Pathway information was downloaded from the KEGG database.
+   - PCA was performed for each pathway in individual omics types.
+   
+   Five PCs in each omics type are in the following files:
+   - PCA_EXP.xlsx, PCA_CNV.xlsx, PCA_MT.xlsx
+   
+   Clinival variables are in the following file:
+   - Clinical.xlsx