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# Path Configuration
from tools.preprocess import *
# Processing context
trait = "Liver_Cancer"
cohort = "GSE209875"
# Input paths
in_trait_dir = "../DATA/GEO/Liver_Cancer"
in_cohort_dir = "../DATA/GEO/Liver_Cancer/GSE209875"
# Output paths
out_data_file = "./output/preprocess/3/Liver_Cancer/GSE209875.csv"
out_gene_data_file = "./output/preprocess/3/Liver_Cancer/gene_data/GSE209875.csv"
out_clinical_data_file = "./output/preprocess/3/Liver_Cancer/clinical_data/GSE209875.csv"
json_path = "./output/preprocess/3/Liver_Cancer/cohort_info.json"
# First print directory contents
print("Files in directory:")
print(os.listdir(in_cohort_dir))
# Get file paths for soft and matrix files
files = os.listdir(in_cohort_dir)
soft_files = [f for f in files if ('soft' in f.lower() or 'soft.gz' in f.lower())]
matrix_files = [f for f in files if ('matrix' in f.lower() or 'matrix.gz' in f.lower())]
print("\nFound files:")
print("SOFT files:", soft_files)
print("Matrix files:", matrix_files)
if len(soft_files) > 0 and len(matrix_files) > 0:
soft_file = os.path.join(in_cohort_dir, soft_files[0])
matrix_file = os.path.join(in_cohort_dir, matrix_files[0])
# Get background info and clinical data from matrix file
background_info, clinical_data = get_background_and_clinical_data(matrix_file)
# Get unique values for each clinical feature row
clinical_features = get_unique_values_by_row(clinical_data)
# Print background info
print("\nBackground Information:")
print(background_info)
print("\nClinical Features and Sample Values:")
print(json.dumps(clinical_features, indent=2))
else:
print("\nRequired SOFT and/or matrix files not found in directory") |