# Path Configuration | |
from tools.preprocess import * | |
# Processing context | |
trait = "Kidney_Clear_Cell_Carcinoma" | |
cohort = "GSE102807" | |
# Input paths | |
in_trait_dir = "../DATA/GEO/Kidney_Clear_Cell_Carcinoma" | |
in_cohort_dir = "../DATA/GEO/Kidney_Clear_Cell_Carcinoma/GSE102807" | |
# Output paths | |
out_data_file = "./output/preprocess/3/Kidney_Clear_Cell_Carcinoma/GSE102807.csv" | |
out_gene_data_file = "./output/preprocess/3/Kidney_Clear_Cell_Carcinoma/gene_data/GSE102807.csv" | |
out_clinical_data_file = "./output/preprocess/3/Kidney_Clear_Cell_Carcinoma/clinical_data/GSE102807.csv" | |
json_path = "./output/preprocess/3/Kidney_Clear_Cell_Carcinoma/cohort_info.json" | |
# Get file paths | |
soft_file_path, matrix_file_path = geo_get_relevant_filepaths(in_cohort_dir) | |
# Get background info and clinical data from SOFT file instead of matrix file | |
background_info, clinical_data = get_background_and_clinical_data(soft_file_path) | |
# Get unique values for each clinical feature | |
unique_values_dict = get_unique_values_by_row(clinical_data) | |
# Print background information | |
print("Background Information:") | |
print(background_info) | |
print("\nSample Characteristics:") | |
print(json.dumps(unique_values_dict, indent=2)) | |
# Gene expression data availability | |
is_gene_available = False # Based on metadata, this appears to be ChIP-seq data, not gene expression | |
# Define variable rows and conversion functions | |
trait_row = None # No clinical trait info available | |
age_row = None # No age info available | |
gender_row = None # No gender info available | |
def convert_trait(x): | |
return None | |
def convert_age(x): | |
return None | |
def convert_gender(x): | |
return None | |
# Save metadata | |
validate_and_save_cohort_info( | |
is_final=False, | |
cohort=cohort, | |
info_path=json_path, | |
is_gene_available=is_gene_available, | |
is_trait_available=(trait_row is not None) | |
) |