()
| 398 | |
| 399 | ##RWR algorithm for drug-target from transynergy |
| 400 | def process_dpi_RWR(): |
| 401 | |
| 402 | network = nx.read_edgelist(os.path.join(ROOT_DIR, 'data','cell_line_data','PPI','string_network'), delimiter='\t', nodetype=int, |
| 403 | data=(('weight', float),)) |
| 404 | |
| 405 | # genes needed to be included in customized set |
| 406 | # data_dicts = np.load(os.path.join(ROOT_DIR, 'data', 'cell_line_data',"Customized",'input_cellline_data.npy'),allow_pickle=True).item() |
| 407 | # customized = data_dicts['exp'] |
| 408 | data_dicts = np.load(os.path.join(ROOT_DIR, 'data', 'cell_line_data',"CCLE",'input_cellline_data.npy'),allow_pickle=True).item() |
| 409 | ccle = data_dicts['exp'] |
| 410 | |
| 411 | customized = pd.read_csv(os.path.join(ROOT_DIR, 'data', 'cell_line_data',"Customized",'crc_exp.csv'), index_col=0) |
| 412 | tcga = pd.read_csv(os.path.join(ROOT_DIR, 'data', 'cell_line_data',"Customized",'tcga_colon_exp.csv'), index_col=0) |
| 413 | |
| 414 | #column is drugbank id, row is entrez id |
| 415 | drug_target = pd.read_csv(os.path.join(ROOT_DIR, 'results','proessed_dpi.csv'), index_col=0) |
| 416 | drug_target = drug_target.loc[drug_target.index.isin(list(network.nodes)), :] |
| 417 | drug_target = drug_target.loc[drug_target.index.isin(list(ccle.index)), :] |
| 418 | drug_target = drug_target.loc[drug_target.index.isin(list(customized.index)), :] |
| 419 | drug_target = drug_target.loc[drug_target.index.isin(list(tcga.index)), :] |
| 420 | |
| 421 | drug_target.fillna(0.00001, inplace = True) |
| 422 | |
| 423 | # generate I matrix |
| 424 | subnetwork = network.subgraph(list(drug_target.index.values)) |
| 425 | A = (subnetwork.subgraph(c) for c in nx.connected_components(subnetwork)) |
| 426 | subgraphs = list(A) |
| 427 | subgraph = subgraphs[0] |
| 428 | subgraph_nodes = list(subgraph.nodes) |
| 429 | I = pd.DataFrame(np.identity(len(subgraph_nodes)), index=subgraph_nodes, columns=subgraph_nodes) |
| 430 | print("Preparing network propagation kernel") |
| 431 | |
| 432 | drug_target = drug_target.loc[drug_target.index.isin(list(I.index.values)), :] |
| 433 | kernel = network_propagation(subgraph, I, alpha=0.5, symmetric_norm=False, verbose=True) |
| 434 | print("Got network propagation kernel. Start propagate ...") |
| 435 | |
| 436 | genes = I.index.values |
| 437 | propagated_drug_target = network_kernel_propagation(network=subgraph, network_kernel=kernel, |
| 438 | binary_matrix=drug_target.T) |
| 439 | propagated_drug_target = propagated_drug_target.loc[:, list(genes)] |
| 440 | print("Propagation finished") |
| 441 | # propagated_drug_target = standarize_dataframe(propagated_drug_target) |
| 442 | |
| 443 | return propagated_drug_target.T |
| 444 | |
| 445 | |
| 446 | # ## for graphsynergy =============unfinished=============== |
no test coverage detected