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from tools.preprocess import * |
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trait = "Hepatitis" |
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tcga_root_dir = "../DATA/TCGA" |
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out_data_file = "./output/preprocess/3/Hepatitis/TCGA.csv" |
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out_gene_data_file = "./output/preprocess/3/Hepatitis/gene_data/TCGA.csv" |
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out_clinical_data_file = "./output/preprocess/3/Hepatitis/clinical_data/TCGA.csv" |
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json_path = "./output/preprocess/3/Hepatitis/cohort_info.json" |
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cohort_dir = os.path.join(tcga_root_dir, 'TCGA_Liver_Cancer_(LIHC)') |
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clinical_file_path, genetic_file_path = tcga_get_relevant_filepaths(cohort_dir) |
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clinical_data = pd.read_csv(clinical_file_path, index_col=0, sep='\t') |
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genetic_data = 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_data.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": { |
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"age_at_initial_pathologic_diagnosis": ["65", "73", "51", "48", "59"] |
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}, |
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"days_to_birth": { |
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"days_to_birth": ["-23725", "-26645", "-18615", "-17520", "-21535"] |
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} |
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} |
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print("Age columns preview:") |
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print(age_preview) |
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gender_preview = { |
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"gender": { |
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"gender": ["MALE", "FEMALE", "MALE", "FEMALE", "MALE"] |
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} |
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} |
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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_features = pd.DataFrame() |
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clinical_features[trait] = clinical_data['viral_hepatitis_serology'].map( |
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lambda x: 1 if isinstance(x, str) and any(v in x.upper() for v in ['POSITIVE', 'POS', '+']) else 0 |
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) |
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if age_col: |
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clinical_features['Age'] = clinical_data[age_col].astype(float) |
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if gender_col: |
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clinical_features['Gender'] = clinical_data[gender_col].map(lambda x: 1 if x.upper() == 'MALE' else 0) |
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os.makedirs(os.path.dirname(out_clinical_data_file), exist_ok=True) |
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clinical_features.to_csv(out_clinical_data_file) |
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normalized_gene_df = normalize_gene_symbols_in_index(genetic_data) |
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os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) |
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normalized_gene_df.to_csv(out_gene_data_file) |
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linked_data = pd.merge( |
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clinical_features, |
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normalized_gene_df.T, |
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left_index=True, |
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right_index=True, |
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how='inner' |
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) |
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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 = "Contains molecular data from liver cancer patients with hepatitis status and demographics." |
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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) |