{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c0fa5988",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import os\n",
    "sys.path.append(os.path.abspath(os.path.join(os.getcwd(), '../..')))\n",
    "\n",
    "# Path Configuration\n",
    "from tools.preprocess import *\n",
    "\n",
    "# Processing context\n",
    "trait = \"Hypertension\"\n",
    "\n",
    "# Input paths\n",
    "tcga_root_dir = \"../../input/TCGA\"\n",
    "\n",
    "# Output paths\n",
    "out_data_file = \"../../output/preprocess/Hypertension/TCGA.csv\"\n",
    "out_gene_data_file = \"../../output/preprocess/Hypertension/gene_data/TCGA.csv\"\n",
    "out_clinical_data_file = \"../../output/preprocess/Hypertension/clinical_data/TCGA.csv\"\n",
    "json_path = \"../../output/preprocess/Hypertension/cohort_info.json\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32d4b483",
   "metadata": {},
   "source": [
    "### Step 1: Initial Data Loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e780da67",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "# Step 1: Look for directories related to Hypertension\n",
    "tcga_subdirs = os.listdir(tcga_root_dir)\n",
    "print(f\"Available TCGA subdirectories: {tcga_subdirs}\")\n",
    "\n",
    "# Look for directories related to Hypertension\n",
    "target_dir = None\n",
    "hypertension_related_terms = [\"Hypertension\", \"Blood Pressure\", \"Cardiovascular\"]\n",
    "\n",
    "for subdir in tcga_subdirs:\n",
    "    for term in hypertension_related_terms:\n",
    "        if term.lower() in subdir.lower():\n",
    "            target_dir = subdir\n",
    "            break\n",
    "    if target_dir:\n",
    "        break\n",
    "\n",
    "if target_dir is None:\n",
    "    print(f\"No suitable directory found for {trait}.\")\n",
    "    # Mark the task as completed by creating a JSON record indicating data is not available\n",
    "    validate_and_save_cohort_info(is_final=False, cohort=\"TCGA\", info_path=json_path, \n",
    "                                  is_gene_available=False, is_trait_available=False)\n",
    "    exit()  # Exit the program\n",
    "\n",
    "# Step 2: Get file paths for the selected directory\n",
    "cohort_dir = os.path.join(tcga_root_dir, target_dir)\n",
    "clinical_file_path, genetic_file_path = tcga_get_relevant_filepaths(cohort_dir)\n",
    "\n",
    "print(f\"Selected directory: {target_dir}\")\n",
    "print(f\"Clinical data file: {clinical_file_path}\")\n",
    "print(f\"Genetic data file: {genetic_file_path}\")\n",
    "\n",
    "# Step 3: Load clinical and genetic data\n",
    "clinical_df = pd.read_csv(clinical_file_path, index_col=0, sep='\\t')\n",
    "genetic_df = pd.read_csv(genetic_file_path, index_col=0, sep='\\t')\n",
    "\n",
    "# Step 4: Print column names of clinical data\n",
    "print(\"\\nClinical data columns:\")\n",
    "print(clinical_df.columns.tolist())\n",
    "\n",
    "# Additional basic information\n",
    "print(f\"\\nClinical data shape: {clinical_df.shape}\")\n",
    "print(f\"Genetic data shape: {genetic_df.shape}\")"
   ]
  }
 ],
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 "nbformat": 4,
 "nbformat_minor": 5
}