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from tools.preprocess import * |
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trait = "Head_and_Neck_Cancer" |
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tcga_root_dir = "../DATA/TCGA" |
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out_data_file = "./output/preprocess/3/Head_and_Neck_Cancer/TCGA.csv" |
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out_gene_data_file = "./output/preprocess/3/Head_and_Neck_Cancer/gene_data/TCGA.csv" |
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out_clinical_data_file = "./output/preprocess/3/Head_and_Neck_Cancer/clinical_data/TCGA.csv" |
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json_path = "./output/preprocess/3/Head_and_Neck_Cancer/cohort_info.json" |
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cohort_dir = os.path.join(tcga_root_dir, 'TCGA_Head_and_Neck_Cancer_(HNSC)') |
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clinical_file, genetic_file = tcga_get_relevant_filepaths(cohort_dir) |
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clinical_df = pd.read_csv(clinical_file, index_col=0, sep='\t') |
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genetic_df = pd.read_csv(genetic_file, 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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is_gene_available = len(genetic_df.columns) > 0 |
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is_trait_available = len(clinical_df.columns) > 0 |
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validate_and_save_cohort_info( |
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is_final=False, |
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cohort="TCGA", |
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info_path=json_path, |
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is_gene_available=is_gene_available, |
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is_trait_available=is_trait_available |
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) |
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candidate_age_cols = ['age_at_initial_pathologic_diagnosis'] |
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candidate_gender_cols = ['gender'] |
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print("Candidate age columns:", candidate_age_cols) |
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print("Candidate gender columns:", candidate_gender_cols) |
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age_col = 'age_at_initial_pathologic_diagnosis' if 'age_at_initial_pathologic_diagnosis' in ['age_at_initial_pathologic_diagnosis'] else None |
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gender_col = 'gender' if 'gender' in ['gender'] else None |
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print(f"Chosen age column: {age_col}") |
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print(f"Chosen gender column: {gender_col}") |
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clinical_df = tcga_select_clinical_features(clinical_df, trait, age_col, gender_col) |
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normalized_genetic_df = 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_genetic_df.to_csv(out_gene_data_file) |
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linked_data = pd.merge(normalized_genetic_df.T, clinical_df, left_index=True, right_index=True) |
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linked_data = handle_missing_values(linked_data, trait) |
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is_biased, linked_data = judge_and_remove_biased_features(linked_data, trait) |
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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=len(normalized_genetic_df.columns) > 0, |
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is_trait_available=trait in linked_data.columns, |
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is_biased=is_biased, |
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df=linked_data, |
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note="Data from TCGA Head and Neck Cancer (HNSC) cohort" |
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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) |