{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "58d0ddef",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-25T07:56:09.807344Z",
     "iopub.status.busy": "2025-03-25T07:56:09.807239Z",
     "iopub.status.idle": "2025-03-25T07:56:09.963914Z",
     "shell.execute_reply": "2025-03-25T07:56:09.963487Z"
    }
   },
   "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 = \"Lupus_(Systemic_Lupus_Erythematosus)\"\n",
    "\n",
    "# Input paths\n",
    "tcga_root_dir = \"../../input/TCGA\"\n",
    "\n",
    "# Output paths\n",
    "out_data_file = \"../../output/preprocess/Lupus_(Systemic_Lupus_Erythematosus)/TCGA.csv\"\n",
    "out_gene_data_file = \"../../output/preprocess/Lupus_(Systemic_Lupus_Erythematosus)/gene_data/TCGA.csv\"\n",
    "out_clinical_data_file = \"../../output/preprocess/Lupus_(Systemic_Lupus_Erythematosus)/clinical_data/TCGA.csv\"\n",
    "json_path = \"../../output/preprocess/Lupus_(Systemic_Lupus_Erythematosus)/cohort_info.json\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d525a32d",
   "metadata": {},
   "source": [
    "### Step 1: Initial Data Loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9a07215e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-25T07:56:09.965194Z",
     "iopub.status.busy": "2025-03-25T07:56:09.965051Z",
     "iopub.status.idle": "2025-03-25T07:56:09.969994Z",
     "shell.execute_reply": "2025-03-25T07:56:09.969601Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Available TCGA directories:\n",
      "['TCGA_Liver_Cancer_(LIHC)', 'TCGA_Lower_Grade_Glioma_(LGG)', 'TCGA_lower_grade_glioma_and_glioblastoma_(GBMLGG)', 'TCGA_Lung_Adenocarcinoma_(LUAD)', 'TCGA_Lung_Cancer_(LUNG)', 'TCGA_Lung_Squamous_Cell_Carcinoma_(LUSC)', 'TCGA_Melanoma_(SKCM)', 'TCGA_Mesothelioma_(MESO)', 'TCGA_Ocular_melanomas_(UVM)', 'TCGA_Ovarian_Cancer_(OV)', 'TCGA_Pancreatic_Cancer_(PAAD)', 'TCGA_Pheochromocytoma_Paraganglioma_(PCPG)', 'TCGA_Prostate_Cancer_(PRAD)', 'TCGA_Rectal_Cancer_(READ)', 'TCGA_Sarcoma_(SARC)', 'TCGA_Stomach_Cancer_(STAD)', 'TCGA_Testicular_Cancer_(TGCT)', 'TCGA_Thymoma_(THYM)', 'TCGA_Thyroid_Cancer_(THCA)', 'TCGA_Uterine_Carcinosarcoma_(UCS)', '.DS_Store', 'CrawlData.ipynb', 'TCGA_Acute_Myeloid_Leukemia_(LAML)', 'TCGA_Adrenocortical_Cancer_(ACC)', 'TCGA_Bile_Duct_Cancer_(CHOL)', 'TCGA_Bladder_Cancer_(BLCA)', 'TCGA_Breast_Cancer_(BRCA)', 'TCGA_Cervical_Cancer_(CESC)', 'TCGA_Colon_and_Rectal_Cancer_(COADREAD)', 'TCGA_Colon_Cancer_(COAD)', 'TCGA_Endometrioid_Cancer_(UCEC)', 'TCGA_Esophageal_Cancer_(ESCA)', 'TCGA_Glioblastoma_(GBM)', 'TCGA_Head_and_Neck_Cancer_(HNSC)', 'TCGA_Kidney_Chromophobe_(KICH)', 'TCGA_Kidney_Clear_Cell_Carcinoma_(KIRC)', 'TCGA_Kidney_Papillary_Cell_Carcinoma_(KIRP)', 'TCGA_Large_Bcell_Lymphoma_(DLBC)']\n",
      "No directories found related to Lupus (Systemic Lupus Erythematosus) in the TCGA dataset.\n",
      "TCGA primarily contains cancer datasets, while Lupus is an autoimmune disease.\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "\n",
    "# Review subdirectories to find the most relevant match for Lupus (Systemic Lupus Erythematosus)\n",
    "all_dirs = os.listdir(tcga_root_dir)\n",
    "\n",
    "# Print all available directories for debugging\n",
    "print(\"Available TCGA directories:\")\n",
    "print(all_dirs)\n",
    "\n",
    "# Looking for directories related to Lupus or autoimmune diseases\n",
    "lupus_related_dirs = [d for d in all_dirs if \"lupus\" in d.lower() or \"autoimmune\" in d.lower()]\n",
    "\n",
    "if len(lupus_related_dirs) > 0:\n",
    "    # If we found related directories, choose the most specific one\n",
    "    selected_dir = lupus_related_dirs[0]\n",
    "    selected_path = os.path.join(tcga_root_dir, selected_dir)\n",
    "    \n",
    "    # Get paths to the clinical and genetic data files\n",
    "    clinical_file_path, genetic_file_path = tcga_get_relevant_filepaths(selected_path)\n",
    "    \n",
    "    # Load the data files\n",
    "    clinical_data = pd.read_csv(clinical_file_path, index_col=0, sep='\\t')\n",
    "    genetic_data = pd.read_csv(genetic_file_path, index_col=0, sep='\\t')\n",
    "    \n",
    "    # Print the column names of the clinical data\n",
    "    print(\"Clinical data columns:\")\n",
    "    print(clinical_data.columns.tolist())\n",
    "    \n",
    "    # Also print basic information about both datasets\n",
    "    print(\"\\nClinical data shape:\", clinical_data.shape)\n",
    "    print(\"Genetic data shape:\", genetic_data.shape)\n",
    "else:\n",
    "    print(\"No directories found related to Lupus (Systemic Lupus Erythematosus) in the TCGA dataset.\")\n",
    "    print(\"TCGA primarily contains cancer datasets, while Lupus is an autoimmune disease.\")\n",
    "    \n",
    "    # Mark this task as completed with no suitable directory found\n",
    "    is_gene_available = False\n",
    "    is_trait_available = False\n",
    "    validate_and_save_cohort_info(\n",
    "        is_final=False, \n",
    "        cohort=\"TCGA\", \n",
    "        info_path=json_path,\n",
    "        is_gene_available=is_gene_available,\n",
    "        is_trait_available=is_trait_available\n",
    "    )"
   ]
  }
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