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from tools.preprocess import * |
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trait = "Liver_Cancer" |
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tcga_root_dir = "../DATA/TCGA" |
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out_data_file = "./output/preprocess/3/Liver_Cancer/TCGA.csv" |
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out_gene_data_file = "./output/preprocess/3/Liver_Cancer/gene_data/TCGA.csv" |
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out_clinical_data_file = "./output/preprocess/3/Liver_Cancer/clinical_data/TCGA.csv" |
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json_path = "./output/preprocess/3/Liver_Cancer/cohort_info.json" |
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cohort_name = "TCGA_Liver_Cancer_(LIHC)" |
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cohort_dir = os.path.join(tcga_root_dir, cohort_name) |
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clinical_file_path, genetic_file_path = tcga_get_relevant_filepaths(cohort_dir) |
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clinical_df = pd.read_csv(clinical_file_path, index_col=0, sep='\t') |
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genetic_df = pd.read_csv(genetic_file_path, index_col=0, sep='\t') |
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print("Clinical data columns:") |
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print(clinical_df.columns.tolist()) |
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candidate_age_cols = ['age_at_initial_pathologic_diagnosis', 'days_to_birth'] |
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candidate_gender_cols = ['gender'] |
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age_preview = { |
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'age_at_initial_pathologic_diagnosis': ['67', '52', '64', '55', '60'], |
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'days_to_birth': ['-24672', '-19020', '-23458', '-20148', '-21942'] |
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} |
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gender_preview = { |
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'gender': ['MALE', 'FEMALE', 'MALE', 'FEMALE', 'MALE'] |
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} |
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print("Age columns preview:") |
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print(age_preview) |
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print("\nGender columns preview:") |
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print(gender_preview) |
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age_col = 'age_at_initial_pathologic_diagnosis' |
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gender_col = 'gender' |
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print(f"Selected age column: {age_col}") |
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print(f"Selected gender column: {gender_col}") |
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clinical_data = tcga_select_clinical_features(clinical_df, trait, age_col, gender_col) |
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os.makedirs(os.path.dirname(out_clinical_data_file), exist_ok=True) |
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clinical_data.to_csv(out_clinical_data_file) |
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normalized_gene_data = normalize_gene_symbols_in_index(genetic_df) |
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os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) |
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normalized_gene_data.to_csv(out_gene_data_file) |
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linked_data = pd.concat([clinical_data, normalized_gene_data.T], axis=1, join='inner') |
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linked_data = handle_missing_values(linked_data, trait) |
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trait_biased, linked_data = judge_and_remove_biased_features(linked_data, trait) |
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note = "Data obtained from TCGA liver cancer cohort (LIHC). Trait is determined by sample type (tumor vs normal)." |
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is_usable = validate_and_save_cohort_info( |
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is_final=True, |
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cohort="TCGA", |
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info_path=json_path, |
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is_gene_available=True, |
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is_trait_available=True, |
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is_biased=trait_biased, |
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df=linked_data, |
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note=note |
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) |
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if is_usable: |
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os.makedirs(os.path.dirname(out_data_file), exist_ok=True) |
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linked_data.to_csv(out_data_file) |
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print(f"Linked data saved to: {out_data_file}") |
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else: |
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print("Dataset was not usable and was not saved.") |