(network_type, adata, threshold, k,
data_path, data_name, split, seed, train_gene_set_size,
set2conditions, default_pert_graph=True, pert_list=None)
| 609 | return df_edge_list |
| 610 | |
| 611 | def get_similarity_network(network_type, adata, threshold, k, |
| 612 | data_path, data_name, split, seed, train_gene_set_size, |
| 613 | set2conditions, default_pert_graph=True, pert_list=None): |
| 614 | |
| 615 | if network_type == 'co-express': |
| 616 | df_out = get_coexpression_network_from_train(adata, threshold, k, |
| 617 | data_path, data_name, split, |
| 618 | seed, train_gene_set_size, |
| 619 | set2conditions) |
| 620 | elif network_type == 'go': |
| 621 | if default_pert_graph: |
| 622 | server_path = 'https://dataverse.harvard.edu/api/access/datafile/6934319' |
| 623 | #tar_data_download_wrapper(server_path, |
| 624 | #os.path.join(data_path, 'go_essential_all'), |
| 625 | #data_path) |
| 626 | df_jaccard = pd.read_csv(os.path.join(data_path, |
| 627 | 'go_essential_all/go_essential_all.csv')) |
| 628 | |
| 629 | else: |
| 630 | df_jaccard = make_GO(data_path, pert_list, data_name) |
| 631 | |
| 632 | df_out = df_jaccard.groupby('target').apply(lambda x: x.nlargest(k + 1, |
| 633 | ['importance'])).reset_index(drop = True) |
| 634 | |
| 635 | return df_out |
| 636 | |
| 637 | def get_coexpression_network_from_train(adata, threshold, k, data_path, |
| 638 | data_name, split, seed, train_gene_set_size, |
no test coverage detected