| | from transforna import predict_transforna, predict_transforna_all_models |
| |
|
| | seqs = [ |
| | 'AACGAAGCTCGACTTTTAAGG', |
| | 'GTCCACCCCAAAGCGTAGG'] |
| |
|
| | path_to_models = '/path/to/tcga/models/' |
| | sc_preds_id_df = predict_transforna_all_models(seqs,path_to_models = path_to_models) |
| | |
| | |
| | sc_preds_id_df = predict_transforna(seqs, model="seq",trained_on='id',path_to_models = path_to_models) |
| | |
| | sc_preds_df = predict_transforna(seqs, model="seq",path_to_models = path_to_models) |
| | |
| | mc_preds_df = predict_transforna(seqs, model="seq",mc_or_sc='major_class',path_to_models = path_to_models) |
| | |
| | logits_df = predict_transforna(seqs, model="seq",logits_flag=True,path_to_models = path_to_models) |
| | |
| | embedd_df = predict_transforna(seqs, model="seq",embedds_flag=True,path_to_models = path_to_models) |
| | |
| | sim_df = predict_transforna(seqs, model="seq",similarity_flag=True,n_sim=4,path_to_models = path_to_models) |
| | |
| | umaps_df = predict_transforna(seqs, model="seq",umaps_flag=True,path_to_models = path_to_models) |
| |
|
| |
|
| | all_preds_df = predict_transforna_all_models(seqs,path_to_models=path_to_models) |
| | all_preds_df |
| |
|
| | |
| |
|