| # Path Configuration | |
| from tools.preprocess import * | |
| # Processing context | |
| trait = "Bipolar_disorder" | |
| # Input paths | |
| tcga_root_dir = "../DATA/TCGA" | |
| # Output paths | |
| out_data_file = "./output/preprocess/1/Bipolar_disorder/TCGA.csv" | |
| out_gene_data_file = "./output/preprocess/1/Bipolar_disorder/gene_data/TCGA.csv" | |
| out_clinical_data_file = "./output/preprocess/1/Bipolar_disorder/clinical_data/TCGA.csv" | |
| json_path = "./output/preprocess/1/Bipolar_disorder/cohort_info.json" | |
| import os | |
| import pandas as pd | |
| # Step 1: Check directories in tcga_root_dir for anything relevant to "Bipolar_disorder" | |
| search_terms = ["bipolar", "bipolar_disorder", "mania"] | |
| dir_list = os.listdir(tcga_root_dir) | |
| matching_dir = None | |
| for d in dir_list: | |
| d_lower = d.lower() | |
| if any(term in d_lower for term in search_terms): | |
| # Found a match, select this directory | |
| matching_dir = d | |
| break | |
| if matching_dir is None: | |
| # No matching directory found. Mark the dataset as skipped. | |
| validate_and_save_cohort_info( | |
| is_final=False, | |
| cohort="TCGA", | |
| info_path=json_path, | |
| is_gene_available=False, | |
| is_trait_available=False | |
| ) | |
| else: | |
| # 2. Identify the clinicalMatrix and PANCAN files | |
| cohort_dir = os.path.join(tcga_root_dir, matching_dir) | |
| clinical_file_path, genetic_file_path = tcga_get_relevant_filepaths(cohort_dir) | |
| # 3. Load both data files | |
| clinical_df = pd.read_csv(clinical_file_path, index_col=0, sep='\t') | |
| genetic_df = pd.read_csv(genetic_file_path, index_col=0, sep='\t') | |
| # 4. Print the column names of the clinical data | |
| print("Clinical Data Columns:") | |
| print(clinical_df.columns.tolist()) |