Man pages for ff98li/scRGNet
Perform scRNA-seq Analysis using Single-cell Graphical Neural Network (scGNN) Framework
| AE | Feature auto encoder class |
| calculate_knn_graph | Isolation forest based KNN graph |
| GCNModelAE | GCN Model Auto-enccoder |
| GCNModelVAE | GCN Model Variational Auto-enccoder auto-encoding variational... |
| gene_counts | scRNA-seq gene expression counts from GSE138852 |
| gene_counts_small | A subset of GSE138852 scRNA-seq gene expression counts |
| generateNetwork | Infer a cell-cell network from the encoded space using... |
| GraphCovolution | Graph Convolutional Neural Network Layer |
| InnerProductDecoder | Inner Product Decoder |
| loss_function_gcn | GCN Loss function |
| loss_function_graph | Loss function regularised by the graph information |
| plotCellNet | Cell network plotting function |
| plotDegree | Show Degree Distribution in Network |
| plotLog | Log-log plot of Network |
| preprocessCSV | Pre-process scRNA-seq Count Matrix in CSV File |
| regulation_mse_loss_function | Regulation MSE Loss Function |
| runFeatureAE | Main function of running scGNN feature auto-encoder |
| runLTMG | Get discretised regulatory signals from LTMG model |
| runscRGNet | Launch Shiny webtool |
| scDataset | scRNA-seq dataset class |
| setHardware | A hardware setter to run the model |
| setHyperParams | Hyper-parameter setter |
| train | Main Training Model |
| vallina_mse_loss_function | Vallina MSE |
