{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3835e969",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-25T08:35:44.483494Z",
     "iopub.status.busy": "2025-03-25T08:35:44.483265Z",
     "iopub.status.idle": "2025-03-25T08:35:44.652479Z",
     "shell.execute_reply": "2025-03-25T08:35:44.652127Z"
    }
   },
   "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 = \"Cystic_Fibrosis\"\n",
    "cohort = \"GSE60690\"\n",
    "\n",
    "# Input paths\n",
    "in_trait_dir = \"../../input/GEO/Cystic_Fibrosis\"\n",
    "in_cohort_dir = \"../../input/GEO/Cystic_Fibrosis/GSE60690\"\n",
    "\n",
    "# Output paths\n",
    "out_data_file = \"../../output/preprocess/Cystic_Fibrosis/GSE60690.csv\"\n",
    "out_gene_data_file = \"../../output/preprocess/Cystic_Fibrosis/gene_data/GSE60690.csv\"\n",
    "out_clinical_data_file = \"../../output/preprocess/Cystic_Fibrosis/clinical_data/GSE60690.csv\"\n",
    "json_path = \"../../output/preprocess/Cystic_Fibrosis/cohort_info.json\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "617aaec5",
   "metadata": {},
   "source": [
    "### Step 1: Initial Data Loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cf96486b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-25T08:35:44.653921Z",
     "iopub.status.busy": "2025-03-25T08:35:44.653777Z",
     "iopub.status.idle": "2025-03-25T08:35:45.016592Z",
     "shell.execute_reply": "2025-03-25T08:35:45.016193Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Background Information:\n",
      "!Series_title\t\"Gene Expression in Transformed Lymphocytes Reveals Phenotype-Modifying Pathways in Cystic Fibrosis\"\n",
      "!Series_summary\t\"Heritable genetic variants modify cystic fibrosis (CF) clinical phenotypes, e.g., lung disease, age-of-onset of persistent Pseudomonas aeruginosa (P. aeruginosa), and meconium ileus (MI).  Previous genome wide association studies (GWAS) have begun to inform the genetic architecture of CF phenotypes.  Analyses of gene expression will complement GWAS, as demonstrated by analyses of gene expression in lymphoblastoid cell lines (LCLs) to identify disease-related pathophysiological processes for non-CF complex traits.  In this study, global gene expression was measured in RNA from LCLs from 754 CF patients and analyzed for association with lung disease severity, age-of-onset of persistent P. aeruginosa pulmonary infection, and MI at birth.  Each phenotype displayed distinct expression associations.  Most pathways significantly associated with lung disease were related to membranes, vesicle traffic, and Golgi/endoplasmic reticulum (ER).  Pathways containing HLA genes (Class I and II) were significantly associated with both lung and P. aeruginosa phenotypes, but they displayed qualitative differences between phenotypes.  MI associated with pathways involving oxidative phosphorylation.  The results support the concept that gene expression associated with heritable variation acts to modify phenotypes in CF.\"\n",
      "!Series_overall_design\t\"754 samples were analyzed; 2 control samples were plated by Expression Analysis per plate and 1 pooled sample from the patient set was added to one well on each plate.\"\n",
      "Sample Characteristics Dictionary:\n",
      "{0: ['Sex: Male', 'Sex: Female'], 1: ['consortium lung phenotype: 0.92156', 'consortium lung phenotype: -0.79274', 'consortium lung phenotype: 2.33374', 'consortium lung phenotype: -1.36666', 'consortium lung phenotype: 2.86073', 'consortium lung phenotype: 1.08383', 'consortium lung phenotype: 1.15792', 'consortium lung phenotype: 1.51600', 'consortium lung phenotype: -0.77528', 'consortium lung phenotype: -0.35251', 'consortium lung phenotype: 0.95176', 'consortium lung phenotype: -0.78019', 'consortium lung phenotype: -0.45468', 'consortium lung phenotype: 1.14497', 'consortium lung phenotype: -0.47971', 'consortium lung phenotype: 0.08552', 'consortium lung phenotype: -0.74197', 'consortium lung phenotype: -1.29147', 'consortium lung phenotype: 0.81747', 'consortium lung phenotype: 1.52976', 'consortium lung phenotype: 1.78443', 'consortium lung phenotype: 0.85150', 'consortium lung phenotype: 1.98295', 'consortium lung phenotype: 0.86374', 'consortium lung phenotype: 0.94161', 'consortium lung phenotype: 1.10084', 'consortium lung phenotype: -0.55910', 'consortium lung phenotype: 0.84926', 'consortium lung phenotype: 0.86596', 'consortium lung phenotype: 1.37640'], 2: ['age of enrollment: 38.2', 'age of enrollment: 9.2', 'age of enrollment: 22.5', 'age of enrollment: 14.4', 'age of enrollment: 33.8', 'age of enrollment: 18.6', 'age of enrollment: 27.7', 'age of enrollment: 33.5', 'age of enrollment: 17.8', 'age of enrollment: 24.1', 'age of enrollment: 16.4', 'age of enrollment: 8.7', 'age of enrollment: 10.4', 'age of enrollment: 46.3', 'age of enrollment: 19.0', 'age of enrollment: 17.1', 'age of enrollment: 10.2', 'age of enrollment: 16.7', 'age of enrollment: 39.7', 'age of enrollment: 39.3', 'age of enrollment: 25.4', 'age of enrollment: 41.2', 'age of enrollment: 18.1', 'age of enrollment: 21.5', 'age of enrollment: 17.3', 'age of enrollment: 32.4', 'age of enrollment: 19.8', 'age of enrollment: 34.3', 'age of enrollment: 25.3', 'age of enrollment: 46.7'], 3: ['cftr genotype: DF508/DF508', 'cftr genotype: DF508/UNK', 'cftr genotype: UNK/UNK', 'cftr genotype: DF508/R553X'], 4: ['persistent ps aer status: 1', 'persistent ps aer status: 0', 'persistent ps aer status: NA'], 5: ['age of onset of persistent ps aer or censored age: 25', 'age of onset of persistent ps aer or censored age: 15', 'age of onset of persistent ps aer or censored age: 19', 'age of onset of persistent ps aer or censored age: 2', 'age of onset of persistent ps aer or censored age: NA', 'age of onset of persistent ps aer or censored age: 14', 'age of onset of persistent ps aer or censored age: 22', 'age of onset of persistent ps aer or censored age: 1', 'age of onset of persistent ps aer or censored age: 4', 'age of onset of persistent ps aer or censored age: 30', 'age of onset of persistent ps aer or censored age: 5', 'age of onset of persistent ps aer or censored age: 32', 'age of onset of persistent ps aer or censored age: 35', 'age of onset of persistent ps aer or censored age: 24', 'age of onset of persistent ps aer or censored age: 3', 'age of onset of persistent ps aer or censored age: 29', 'age of onset of persistent ps aer or censored age: 0.6', 'age of onset of persistent ps aer or censored age: 18', 'age of onset of persistent ps aer or censored age: 8', 'age of onset of persistent ps aer or censored age: 26', 'age of onset of persistent ps aer or censored age: 50', 'age of onset of persistent ps aer or censored age: 21', 'age of onset of persistent ps aer or censored age: 16', 'age of onset of persistent ps aer or censored age: 12', 'age of onset of persistent ps aer or censored age: 20', 'age of onset of persistent ps aer or censored age: 9', 'age of onset of persistent ps aer or censored age: 10', 'age of onset of persistent ps aer or censored age: 28', 'age of onset of persistent ps aer or censored age: 7', 'age of onset of persistent ps aer or censored age: 11'], 6: ['meconium ileus status: No', 'meconium ileus status: Yes', 'meconium ileus status: UNKNOWN'], 7: ['genotype pc1: 0.0245', 'genotype pc1: -0.0236', 'genotype pc1: -0.0024', 'genotype pc1: -0.0055', 'genotype pc1: -0.0065', 'genotype pc1: -0.0079', 'genotype pc1: -0.0207', 'genotype pc1: 0.055', 'genotype pc1: -0.0229', 'genotype pc1: -0.0036', 'genotype pc1: -0.0119', 'genotype pc1: 0.0127', 'genotype pc1: -0.0002', 'genotype pc1: 0.0823', 'genotype pc1: -0.014', 'genotype pc1: -0.0009', 'genotype pc1: 0.0278', 'genotype pc1: -0.0165', 'genotype pc1: -0.0122', 'genotype pc1: -0.0077', 'genotype pc1: -0.0193', 'genotype pc1: -0.0221', 'genotype pc1: 0.0994', 'genotype pc1: -0.0145', 'genotype pc1: -0.0233', 'genotype pc1: -0.0149', 'genotype pc1: -0.0033', 'genotype pc1: 0.0435', 'genotype pc1: -0.0531', 'genotype pc1: -0.0057'], 8: ['genotype pc2: -0.0369', 'genotype pc2: -0.0304', 'genotype pc2: 0.0001', 'genotype pc2: 0.011', 'genotype pc2: -0.0039', 'genotype pc2: -0.014', 'genotype pc2: 0.033', 'genotype pc2: -0.0112', 'genotype pc2: 0.0169', 'genotype pc2: -0.0375', 'genotype pc2: -0.006', 'genotype pc2: -0.0301', 'genotype pc2: -0.0047', 'genotype pc2: -0.0084', 'genotype pc2: 0.0105', 'genotype pc2: 0.0198', 'genotype pc2: -0.0247', 'genotype pc2: -0.0099', 'genotype pc2: -0.0219', 'genotype pc2: 0.006', 'genotype pc2: 0.0265', 'genotype pc2: 0.012', 'genotype pc2: -0.0288', 'genotype pc2: 0.023', 'genotype pc2: 0.0059', 'genotype pc2: 0.0284', 'genotype pc2: -0.0013', 'genotype pc2: 0.0154', 'genotype pc2: -0.0225', 'genotype pc2: 0.0387'], 9: ['genotype pc3: -0.0153', 'genotype pc3: 0.0064', 'genotype pc3: 0.0051', 'genotype pc3: -0.0438', 'genotype pc3: 0.013', 'genotype pc3: 0.0287', 'genotype pc3: -0.0004', 'genotype pc3: 0.0398', 'genotype pc3: -0.0183', 'genotype pc3: 0.0084', 'genotype pc3: -0.0125', 'genotype pc3: -0.0464', 'genotype pc3: 0.0132', 'genotype pc3: 0.0004', 'genotype pc3: 0', 'genotype pc3: -0.0216', 'genotype pc3: 0.0198', 'genotype pc3: -0.0172', 'genotype pc3: -0.0096', 'genotype pc3: -0.0283', 'genotype pc3: 0.01', 'genotype pc3: -0.0174', 'genotype pc3: -0.0015', 'genotype pc3: 0.0073', 'genotype pc3: -0.0337', 'genotype pc3: 0.0023', 'genotype pc3: -0.0091', 'genotype pc3: -0.0151', 'genotype pc3: -0.0273', 'genotype pc3: -0.0185'], 10: ['genotype pc4: 0.0321', 'genotype pc4: -0.0008', 'genotype pc4: 0.014', 'genotype pc4: 0.0225', 'genotype pc4: 0.0116', 'genotype pc4: 0.0245', 'genotype pc4: -0.0633', 'genotype pc4: -0.003', 'genotype pc4: 0.0182', 'genotype pc4: -0.0184', 'genotype pc4: 0.006', 'genotype pc4: -0.0055', 'genotype pc4: 0.0137', 'genotype pc4: 0.0415', 'genotype pc4: 0.009', 'genotype pc4: 0.0231', 'genotype pc4: 0.0268', 'genotype pc4: -0.0271', 'genotype pc4: -0.0013', 'genotype pc4: 0.0369', 'genotype pc4: -0.0178', 'genotype pc4: -0.0079', 'genotype pc4: 0.0083', 'genotype pc4: -0.0157', 'genotype pc4: -0.0327', 'genotype pc4: 0.0164', 'genotype pc4: 0.0279', 'genotype pc4: -0.0533', 'genotype pc4: -0.0138', 'genotype pc4: 0.0208'], 11: ['genotype pc5: 0.0402', 'genotype pc5: -0.0199', 'genotype pc5: -0.0068', 'genotype pc5: 0.0167', 'genotype pc5: 0.0053', 'genotype pc5: -0.0388', 'genotype pc5: -0.0093', 'genotype pc5: -0.041', 'genotype pc5: -0.0324', 'genotype pc5: 0.0023', 'genotype pc5: -0.0036', 'genotype pc5: 0.0158', 'genotype pc5: -0.0897', 'genotype pc5: 0.0379', 'genotype pc5: 0.0564', 'genotype pc5: 0.015', 'genotype pc5: -0.0433', 'genotype pc5: 0.0431', 'genotype pc5: -0.0179', 'genotype pc5: -0.0184', 'genotype pc5: 0.0287', 'genotype pc5: -0.0033', 'genotype pc5: -0.0165', 'genotype pc5: -0.019', 'genotype pc5: -0.014', 'genotype pc5: 0.0111', 'genotype pc5: 0.0392', 'genotype pc5: 0.0098', 'genotype pc5: -0.0067', 'genotype pc5: 0.0245'], 12: ['genotype pc6: 0.0132', 'genotype pc6: -0.017', 'genotype pc6: 0.0118', 'genotype pc6: 0.0442', 'genotype pc6: 0.0365', 'genotype pc6: 0.0007', 'genotype pc6: -0.012', 'genotype pc6: -0.0024', 'genotype pc6: -0.0202', 'genotype pc6: 0.0079', 'genotype pc6: 0.0053', 'genotype pc6: -0.0166', 'genotype pc6: 0.0412', 'genotype pc6: 0.0182', 'genotype pc6: -0.0021', 'genotype pc6: 0.0136', 'genotype pc6: 0.0059', 'genotype pc6: 0.0211', 'genotype pc6: -0.035', 'genotype pc6: 0.0051', 'genotype pc6: -0.0129', 'genotype pc6: 0.0187', 'genotype pc6: 0.0128', 'genotype pc6: 0.0607', 'genotype pc6: 0.0028', 'genotype pc6: -0.0259', 'genotype pc6: 0.0374', 'genotype pc6: -0.036', 'genotype pc6: 0.0449', 'genotype pc6: -0.0363'], 13: ['genotype pc7: 0.0231', 'genotype pc7: -0.0408', 'genotype pc7: 0.0046', 'genotype pc7: -0.0074', 'genotype pc7: 0.0261', 'genotype pc7: -0.0025', 'genotype pc7: -0.0273', 'genotype pc7: 0.0293', 'genotype pc7: -0.0176', 'genotype pc7: -0.0331', 'genotype pc7: 0.0249', 'genotype pc7: 0.0045', 'genotype pc7: -0.0775', 'genotype pc7: 0.0422', 'genotype pc7: 0.0187', 'genotype pc7: -0.0164', 'genotype pc7: 0.0087', 'genotype pc7: 0.0171', 'genotype pc7: 0.0081', 'genotype pc7: -0.0216', 'genotype pc7: -0.0114', 'genotype pc7: -0.0096', 'genotype pc7: 0.0136', 'genotype pc7: 0.0518', 'genotype pc7: 0.016', 'genotype pc7: -0.0022', 'genotype pc7: 0.0109', 'genotype pc7: 0.0338', 'genotype pc7: -0.0209', 'genotype pc7: -0.0515'], 14: ['plate: 1', 'plate: 2', 'plate: 3', 'plate: 4', 'plate: 5', 'plate: 6', 'plate: 7', 'plate: 8', 'plate: 9', 'plate: 10', 'plate: 11'], 15: ['consortium lung phenotype surrogate variable: -0.007666824', 'consortium lung phenotype surrogate variable: 0.034873757', 'consortium lung phenotype surrogate variable: 0.042322659', 'consortium lung phenotype surrogate variable: -0.019835408', 'consortium lung phenotype surrogate variable: 0.014540293', 'consortium lung phenotype surrogate variable: 0.033267948', 'consortium lung phenotype surrogate variable: -0.007735849', 'consortium lung phenotype surrogate variable: 0.002391609', 'consortium lung phenotype surrogate variable: -0.027495632', 'consortium lung phenotype surrogate variable: 0.028345537', 'consortium lung phenotype surrogate variable: -0.039899205', 'consortium lung phenotype surrogate variable: 0.024014483', 'consortium lung phenotype surrogate variable: -0.039072979', 'consortium lung phenotype surrogate variable: 0.025505444', 'consortium lung phenotype surrogate variable: -0.080515612', 'consortium lung phenotype surrogate variable: -0.051896794', 'consortium lung phenotype surrogate variable: -0.065684118', 'consortium lung phenotype surrogate variable: 0.016629621', 'consortium lung phenotype surrogate variable: 0.015330356', 'consortium lung phenotype surrogate variable: 0.009777207', 'consortium lung phenotype surrogate variable: -0.038826792', 'consortium lung phenotype surrogate variable: 0.012684366', 'consortium lung phenotype surrogate variable: 0.011989911', 'consortium lung phenotype surrogate variable: 0.012664639', 'consortium lung phenotype surrogate variable: 0.024951683', 'consortium lung phenotype surrogate variable: -0.006402057', 'consortium lung phenotype surrogate variable: 0.0191642', 'consortium lung phenotype surrogate variable: -0.008777918', 'consortium lung phenotype surrogate variable: 0.011153824', 'consortium lung phenotype surrogate variable: -0.008548007'], 16: ['pseudomonas aeruginosa surrogate variable 1: -0.006474146', 'pseudomonas aeruginosa surrogate variable 1: 0.045926197', 'pseudomonas aeruginosa surrogate variable 1: 0.053951823', 'pseudomonas aeruginosa surrogate variable 1: -0.022694379', 'meconium ileus surrogate variable 1: 0.014932598', 'pseudomonas aeruginosa surrogate variable 1: 0.042960438', 'meconium ileus surrogate variable 1: -0.006839056', 'pseudomonas aeruginosa surrogate variable 1: 0.004742906', 'pseudomonas aeruginosa surrogate variable 1: -0.033807162', 'meconium ileus surrogate variable 1: 0.02863847', 'pseudomonas aeruginosa surrogate variable 1: -0.045141616', 'pseudomonas aeruginosa surrogate variable 1: 0.03191877', 'pseudomonas aeruginosa surrogate variable 1: -0.045991894', 'pseudomonas aeruginosa surrogate variable 1: 0.037435759', 'pseudomonas aeruginosa surrogate variable 1: -0.099047062', 'meconium ileus surrogate variable 1: -0.051591385', 'pseudomonas aeruginosa surrogate variable 1: -0.078504781', 'pseudomonas aeruginosa surrogate variable 1: 0.020560644', 'pseudomonas aeruginosa surrogate variable 1: 0.022574507', 'pseudomonas aeruginosa surrogate variable 1: 0.015723838', 'meconium ileus surrogate variable 1: -0.037920814', 'pseudomonas aeruginosa surrogate variable 1: 0.015722162', 'meconium ileus surrogate variable 1: 0.011418511', 'meconium ileus surrogate variable 1: 0.012625291', 'pseudomonas aeruginosa surrogate variable 1: 0.031057644', 'meconium ileus surrogate variable 1: -0.006772336', 'pseudomonas aeruginosa surrogate variable 1: 0.028351724', 'meconium ileus surrogate variable 1: -0.00796125', 'pseudomonas aeruginosa surrogate variable 1: 0.016830311', 'pseudomonas aeruginosa surrogate variable 1: -0.011285192'], 17: ['meconium ileus surrogate variable 1: -0.007259556', 'meconium ileus surrogate variable 1: 0.035562995', 'meconium ileus surrogate variable 1: 0.041574357', 'meconium ileus surrogate variable 1: -0.020240499', 'meconium ileus surrogate variable 2: -0.030352802', 'meconium ileus surrogate variable 1: 0.032674446', 'meconium ileus surrogate variable 2: 0.045354696', 'meconium ileus surrogate variable 1: 0.002411729', 'meconium ileus surrogate variable 1: -0.028308101', 'meconium ileus surrogate variable 2: 0.043356511', 'meconium ileus surrogate variable 1: -0.039854241', 'meconium ileus surrogate variable 1: 0.023860011', 'meconium ileus surrogate variable 1: -0.039367619', 'meconium ileus surrogate variable 1: 0.025904872', 'meconium ileus surrogate variable 1: -0.080613051', 'meconium ileus surrogate variable 2: -0.025827481', 'meconium ileus surrogate variable 1: -0.065212665', 'meconium ileus surrogate variable 1: 0.015897934', 'meconium ileus surrogate variable 1: 0.015679656', 'meconium ileus surrogate variable 1: 0.00984179', 'meconium ileus surrogate variable 2: 0.027578387', 'meconium ileus surrogate variable 1: 0.01136519', 'meconium ileus surrogate variable 2: -0.036128236', 'meconium ileus surrogate variable 2: -0.035298795', 'meconium ileus surrogate variable 1: 0.025123616', 'meconium ileus surrogate variable 2: -0.031015884', 'meconium ileus surrogate variable 1: 0.019682345', 'meconium ileus surrogate variable 2: -0.036555365', 'meconium ileus surrogate variable 1: 0.011284547', 'meconium ileus surrogate variable 1: -0.00923367'], 18: ['meconium ileus surrogate variable 2: 0.04704748', 'meconium ileus surrogate variable 2: 0.036888174', 'meconium ileus surrogate variable 2: 0.040772015', 'meconium ileus surrogate variable 2: -0.02869714', 'meconium ileus surrogate variable 3: 0.015527635', 'meconium ileus surrogate variable 2: -0.030278696', 'meconium ileus surrogate variable 3: -0.071288719', 'meconium ileus surrogate variable 2: -0.032546195', 'meconium ileus surrogate variable 2: -0.03033024', 'meconium ileus surrogate variable 3: 0.034132217', 'meconium ileus surrogate variable 2: 0.041546903', 'meconium ileus surrogate variable 2: -0.035656587', 'meconium ileus surrogate variable 2: -0.033591713', 'meconium ileus surrogate variable 2: -0.035150683', 'meconium ileus surrogate variable 2: 0.044868885', 'meconium ileus surrogate variable 3: -0.030840542', 'meconium ileus surrogate variable 2: -0.02871954', 'meconium ileus surrogate variable 2: 0.040118755', 'meconium ileus surrogate variable 2: -0.034120281', 'meconium ileus surrogate variable 2: 0.041626045', 'meconium ileus surrogate variable 3: 0.019030471', 'meconium ileus surrogate variable 2: 0.046601608', 'meconium ileus surrogate variable 3: -0.020213695', 'meconium ileus surrogate variable 3: -0.055550766', 'meconium ileus surrogate variable 2: 0.036155343', 'meconium ileus surrogate variable 3: 0.01970194', 'meconium ileus surrogate variable 2: 0.040452182', 'meconium ileus surrogate variable 3: -0.047582576', 'meconium ileus surrogate variable 2: -0.025403174', 'meconium ileus surrogate variable 2: -0.034264077'], 19: ['meconium ileus surrogate variable 3: -0.042906917', 'meconium ileus surrogate variable 3: 0.042291829', 'meconium ileus surrogate variable 3: 0.003895659', 'meconium ileus surrogate variable 3: -0.022803753', 'meconium ileus surrogate variable 4: -0.038303562', 'meconium ileus surrogate variable 3: -0.011523139', 'meconium ileus surrogate variable 4: -0.048308051', 'meconium ileus surrogate variable 3: -0.002448346', 'meconium ileus surrogate variable 3: -0.007995854', 'meconium ileus surrogate variable 4: -0.028732199', 'meconium ileus surrogate variable 3: -0.0363941', 'meconium ileus surrogate variable 3: 0.00744259', 'meconium ileus surrogate variable 3: -0.009686904', 'meconium ileus surrogate variable 3: -0.065752441', 'meconium ileus surrogate variable 3: -0.008836405', 'meconium ileus surrogate variable 4: -0.027858948', 'meconium ileus surrogate variable 3: -0.027624756', 'meconium ileus surrogate variable 3: 0.024199555', 'meconium ileus surrogate variable 3: -0.057226107', 'meconium ileus surrogate variable 3: -0.047981035', 'meconium ileus surrogate variable 4: -0.036422339', 'meconium ileus surrogate variable 3: 0.026022201', 'meconium ileus surrogate variable 4: -0.001507287', 'meconium ileus surrogate variable 4: -0.036383887', 'meconium ileus surrogate variable 3: 0.039841907', 'meconium ileus surrogate variable 4: -0.064630994', 'meconium ileus surrogate variable 3: -0.046326633', 'meconium ileus surrogate variable 4: 0.03902113', 'meconium ileus surrogate variable 3: -0.02623294', 'meconium ileus surrogate variable 3: -0.006735359'], 20: ['meconium ileus surrogate variable 4: -0.002479522', 'meconium ileus surrogate variable 4: -0.012934442', 'meconium ileus surrogate variable 4: 0.045819189', 'meconium ileus surrogate variable 4: -0.06646753', 'meconium ileus surrogate variable 5: 0.02509852', 'meconium ileus surrogate variable 4: -0.044316698', 'meconium ileus surrogate variable 5: 0.024370194', 'meconium ileus surrogate variable 4: -0.092786706', 'meconium ileus surrogate variable 4: -0.079987325', 'meconium ileus surrogate variable 5: 0.060722177', 'meconium ileus surrogate variable 4: -0.003729546', 'meconium ileus surrogate variable 4: -0.026948089', 'meconium ileus surrogate variable 4: -0.011213126', 'meconium ileus surrogate variable 4: 0.011746922', 'meconium ileus surrogate variable 4: -0.054551354', 'meconium ileus surrogate variable 5: 0.081687296', 'meconium ileus surrogate variable 4: -0.028863621', 'meconium ileus surrogate variable 4: -0.015774071', 'meconium ileus surrogate variable 4: 0.018055929', 'meconium ileus surrogate variable 4: 0.017996933', 'meconium ileus surrogate variable 5: 0.045572709', 'meconium ileus surrogate variable 4: -0.101609503', 'meconium ileus surrogate variable 5: 0.00946913', 'meconium ileus surrogate variable 5: 0.020666795', 'meconium ileus surrogate variable 4: -0.021234742', 'meconium ileus surrogate variable 5: 0.070536904', 'meconium ileus surrogate variable 4: -0.022114389', 'meconium ileus surrogate variable 5: 0.037903237', 'meconium ileus surrogate variable 4: -0.061555444', 'meconium ileus surrogate variable 4: -0.026691223'], 21: ['meconium ileus surrogate variable 5: 0.070743301', 'meconium ileus surrogate variable 5: 0.022315193', 'meconium ileus surrogate variable 5: 0.044520431', 'meconium ileus surrogate variable 5: 0.030849078', 'meconium ileus surrogate variable 6: -0.013039097', 'meconium ileus surrogate variable 5: 0.025417257', 'meconium ileus surrogate variable 6: -0.098987223', 'meconium ileus surrogate variable 5: -0.001865049', 'meconium ileus surrogate variable 5: 0.01449101', 'meconium ileus surrogate variable 6: -0.021497686', 'meconium ileus surrogate variable 5: 0.022392449', 'meconium ileus surrogate variable 5: 0.052825271', 'meconium ileus surrogate variable 5: 0.132617496', 'meconium ileus surrogate variable 5: 0.013028918', 'meconium ileus surrogate variable 5: 0.019759143', 'meconium ileus surrogate variable 6: -0.058088641', 'meconium ileus surrogate variable 5: 0.063646558', 'meconium ileus surrogate variable 5: 0.054621474', 'meconium ileus surrogate variable 5: 0.018194809', 'meconium ileus surrogate variable 5: 0.001566891', 'meconium ileus surrogate variable 6: 0.011454368', 'meconium ileus surrogate variable 5: -0.046768364', 'meconium ileus surrogate variable 6: -0.021606167', 'meconium ileus surrogate variable 6: 0.001518027', 'meconium ileus surrogate variable 5: 0.080213238', 'meconium ileus surrogate variable 6: -0.024250195', 'meconium ileus surrogate variable 5: -0.001685017', 'meconium ileus surrogate variable 6: 0.02429084', 'meconium ileus surrogate variable 5: -0.027434641', 'meconium ileus surrogate variable 5: 0.042755379'], 22: ['meconium ileus surrogate variable 6: -0.029433061', 'meconium ileus surrogate variable 6: 0.011176869', 'meconium ileus surrogate variable 6: 0.006397831', 'meconium ileus surrogate variable 6: 0.009434544', 'meconium ileus surrogate variable 7: -0.064958909', 'meconium ileus surrogate variable 6: -0.026793306', 'meconium ileus surrogate variable 7: 0.004429269', 'meconium ileus surrogate variable 6: 0.035594776', 'meconium ileus surrogate variable 6: 0.009179052', 'meconium ileus surrogate variable 7: -0.047986024', 'meconium ileus surrogate variable 6: 0.021841134', 'meconium ileus surrogate variable 6: -0.00414369', 'meconium ileus surrogate variable 6: -0.037886459', 'meconium ileus surrogate variable 6: 0.006537276', 'meconium ileus surrogate variable 6: 0.072791854', 'meconium ileus surrogate variable 7: 0.011707649', 'meconium ileus surrogate variable 6: -0.013100834', 'meconium ileus surrogate variable 6: -0.012979994', 'meconium ileus surrogate variable 6: 0.027211948', 'meconium ileus surrogate variable 6: 0.035990148', 'meconium ileus surrogate variable 7: 0.010667192', 'meconium ileus surrogate variable 6: -0.000707387', 'meconium ileus surrogate variable 7: 0.002814865', 'meconium ileus surrogate variable 7: 0.07142213', 'meconium ileus surrogate variable 6: -0.002341684', 'meconium ileus surrogate variable 7: -0.020477913', 'meconium ileus surrogate variable 6: -0.013903906', 'meconium ileus surrogate variable 7: 0.011767712', 'meconium ileus surrogate variable 6: 0.023193247', 'meconium ileus surrogate variable 6: -0.014499269'], 23: ['meconium ileus surrogate variable 7: 0.059670721', 'meconium ileus surrogate variable 7: -0.014615113', 'meconium ileus surrogate variable 7: -0.01437584', 'meconium ileus surrogate variable 7: 0.079091286', 'meconium ileus surrogate variable 8: 0.025545595', 'meconium ileus surrogate variable 7: 0.012200915', 'meconium ileus surrogate variable 8: 0.013481208', 'meconium ileus surrogate variable 7: 0.043113135', 'meconium ileus surrogate variable 7: 0.077275428', 'meconium ileus surrogate variable 8: -0.005923367', 'meconium ileus surrogate variable 7: -0.035261318', 'meconium ileus surrogate variable 7: 0.016757963', 'meconium ileus surrogate variable 7: 0.01035876', 'meconium ileus surrogate variable 7: 0.013132081', 'meconium ileus surrogate variable 7: 0.069522855', 'meconium ileus surrogate variable 8: -0.026176429', 'meconium ileus surrogate variable 7: -0.030367621', 'meconium ileus surrogate variable 7: -0.002171803', 'meconium ileus surrogate variable 7: 0.003521297', 'meconium ileus surrogate variable 7: 0.008030826', 'meconium ileus surrogate variable 8: -0.011098935', 'meconium ileus surrogate variable 7: -0.031264846', 'meconium ileus surrogate variable 8: 0.043771454', 'meconium ileus surrogate variable 8: -0.069168167', 'meconium ileus surrogate variable 7: -0.012051044', 'meconium ileus surrogate variable 8: -0.014415022', 'meconium ileus surrogate variable 7: 0.027485061', 'meconium ileus surrogate variable 8: 0.011505508', 'meconium ileus surrogate variable 7: -0.003195995', 'meconium ileus surrogate variable 7: -0.019870282'], 24: ['meconium ileus surrogate variable 8: -0.011348177', 'meconium ileus surrogate variable 8: 0.027284669', 'meconium ileus surrogate variable 8: 0.014914093', 'meconium ileus surrogate variable 8: 0.044945759', 'meconium ileus surrogate variable 9: 0.065640376', 'meconium ileus surrogate variable 8: -0.017487673', 'meconium ileus surrogate variable 9: -0.019172405', 'meconium ileus surrogate variable 8: -0.021666678', 'meconium ileus surrogate variable 8: 0.085729085', 'meconium ileus surrogate variable 9: 0.021607981', 'meconium ileus surrogate variable 8: 0.037372774', 'meconium ileus surrogate variable 8: 0.004743801', 'meconium ileus surrogate variable 8: -0.013716264', 'meconium ileus surrogate variable 8: -0.015298715', 'meconium ileus surrogate variable 8: 0.074949817', 'meconium ileus surrogate variable 9: 0.028439879', 'meconium ileus surrogate variable 8: 0.048475058', 'meconium ileus surrogate variable 8: 0.009560071', 'meconium ileus surrogate variable 8: -0.078917822', 'meconium ileus surrogate variable 8: -0.006340655', 'meconium ileus surrogate variable 9: 0.043012811', 'meconium ileus surrogate variable 8: -0.042487992', 'meconium ileus surrogate variable 9: -0.021579328', 'meconium ileus surrogate variable 9: 0.008108035', 'meconium ileus surrogate variable 8: -0.051673512', 'meconium ileus surrogate variable 9: -0.01315019', 'meconium ileus surrogate variable 8: -0.013965427', 'meconium ileus surrogate variable 9: -0.049912317', 'meconium ileus surrogate variable 8: -0.069530421', 'meconium ileus surrogate variable 8: -0.02914925'], 25: ['meconium ileus surrogate variable 9: 0.06776575', 'meconium ileus surrogate variable 9: 0.083477176', 'meconium ileus surrogate variable 9: -0.053887761', 'meconium ileus surrogate variable 9: 0.002841287', 'meconium ileus surrogate variable 10: -0.023015628', 'meconium ileus surrogate variable 9: -0.040050095', 'meconium ileus surrogate variable 10: -0.024684259', 'meconium ileus surrogate variable 9: 0.02681684', 'meconium ileus surrogate variable 9: 0.006930392', 'meconium ileus surrogate variable 10: -0.04187222', 'meconium ileus surrogate variable 9: -0.008389812', 'meconium ileus surrogate variable 9: -0.041827173', 'meconium ileus surrogate variable 9: -0.025257532', 'meconium ileus surrogate variable 9: 0.021103097', 'meconium ileus surrogate variable 9: -0.024277029', 'meconium ileus surrogate variable 10: 0.044837718', 'meconium ileus surrogate variable 9: 0.002060787', 'meconium ileus surrogate variable 9: 0.038863346', 'meconium ileus surrogate variable 9: 0.010449287', 'meconium ileus surrogate variable 9: -0.005826962', 'meconium ileus surrogate variable 10: 0.017863514', 'meconium ileus surrogate variable 9: 0.023154473', 'meconium ileus surrogate variable 10: 0.018558621', 'meconium ileus surrogate variable 10: -0.020759905', 'meconium ileus surrogate variable 9: 0.009007212', 'meconium ileus surrogate variable 10: -0.018053518', 'meconium ileus surrogate variable 9: -0.000347424', 'meconium ileus surrogate variable 10: 0.01884706', 'meconium ileus surrogate variable 9: 0.024381123', 'meconium ileus surrogate variable 9: 0.037999912'], 26: ['meconium ileus surrogate variable 10: -0.035847231', 'meconium ileus surrogate variable 10: -0.044129324', 'meconium ileus surrogate variable 10: -0.003154707', 'meconium ileus surrogate variable 10: -0.019363918', 'meconium ileus surrogate variable 11: 0.013379262', 'meconium ileus surrogate variable 10: 0.038841561', 'meconium ileus surrogate variable 11: 0.036712134', 'meconium ileus surrogate variable 10: -0.00044391', 'meconium ileus surrogate variable 10: 0.003097939', 'meconium ileus surrogate variable 11: 0.014872321', 'meconium ileus surrogate variable 10: 0.016867937', 'meconium ileus surrogate variable 10: 0.010914222', 'meconium ileus surrogate variable 10: -0.005616023', 'meconium ileus surrogate variable 10: 0.04514386', 'meconium ileus surrogate variable 10: 0.008568568', 'meconium ileus surrogate variable 11: 0.015039785', 'meconium ileus surrogate variable 10: 0.01683823', 'meconium ileus surrogate variable 10: -0.003422554', 'meconium ileus surrogate variable 10: 0.022145686', 'meconium ileus surrogate variable 10: 0.041597074', 'meconium ileus surrogate variable 11: 0.022702348', 'meconium ileus surrogate variable 10: -0.001927848', 'meconium ileus surrogate variable 11: 0.026634625', 'meconium ileus surrogate variable 11: 0.008438625', 'meconium ileus surrogate variable 10: -0.031039349', 'meconium ileus surrogate variable 11: 0.018590554', 'meconium ileus surrogate variable 10: -0.011807237', 'meconium ileus surrogate variable 11: 0.02252415', 'meconium ileus surrogate variable 10: 0.104856541', 'meconium ileus surrogate variable 10: 0.024583878'], 27: ['meconium ileus surrogate variable 11: 0.011902911', 'meconium ileus surrogate variable 11: 0.027260851', 'meconium ileus surrogate variable 11: -0.049970745', 'meconium ileus surrogate variable 11: 0.055660568', 'meconium ileus surrogate variable 12: -0.093855724', 'meconium ileus surrogate variable 11: 0.020160363', 'meconium ileus surrogate variable 12: 0.025596904', 'meconium ileus surrogate variable 11: 0.033540893', 'meconium ileus surrogate variable 11: -0.070781941', 'meconium ileus surrogate variable 12: -0.035549538', 'meconium ileus surrogate variable 11: 0.019757518', 'meconium ileus surrogate variable 11: 0.005257067', 'meconium ileus surrogate variable 11: -0.052433395', 'meconium ileus surrogate variable 11: -0.007424559', 'meconium ileus surrogate variable 11: 0.000863609', 'meconium ileus surrogate variable 12: -0.028441815', 'meconium ileus surrogate variable 11: 0.01898962', 'meconium ileus surrogate variable 11: -0.007064184', 'meconium ileus surrogate variable 11: 0.011002651', 'meconium ileus surrogate variable 11: -0.070270421', 'meconium ileus surrogate variable 12: -0.020210162', 'meconium ileus surrogate variable 11: -0.062866725', 'meconium ileus surrogate variable 12: -0.046306498', 'meconium ileus surrogate variable 12: -0.034464707', 'meconium ileus surrogate variable 11: 0.004978503', 'meconium ileus surrogate variable 12: 0.019830429', 'meconium ileus surrogate variable 11: 0.027340228', 'meconium ileus surrogate variable 12: -0.001049948', 'meconium ileus surrogate variable 11: -0.003453994', 'meconium ileus surrogate variable 11: -0.011949324'], 28: ['meconium ileus surrogate variable 12: -0.032603014', 'meconium ileus surrogate variable 12: 0.041347488', 'meconium ileus surrogate variable 12: -0.092192962', 'meconium ileus surrogate variable 12: 0.006123792', 'meconium ileus surrogate variable 13: 0.030657352', 'meconium ileus surrogate variable 12: -0.045521337', 'meconium ileus surrogate variable 13: -0.045538586', 'meconium ileus surrogate variable 12: -0.010659068', 'meconium ileus surrogate variable 12: 0.005567125', 'meconium ileus surrogate variable 13: -0.060506929', 'meconium ileus surrogate variable 12: -0.005489816', 'meconium ileus surrogate variable 12: -0.006328213', 'meconium ileus surrogate variable 12: 0.006085812', 'meconium ileus surrogate variable 12: 0.026481574', 'meconium ileus surrogate variable 12: 0.002018392', 'meconium ileus surrogate variable 13: -0.022945292', 'meconium ileus surrogate variable 12: 0.003085823', 'meconium ileus surrogate variable 12: -0.065232953', 'meconium ileus surrogate variable 12: -0.027479599', 'meconium ileus surrogate variable 12: -0.018153543', 'meconium ileus surrogate variable 13: 0.088150667', 'meconium ileus surrogate variable 12: -0.162622313', 'meconium ileus surrogate variable 13: 0.038012466', 'meconium ileus surrogate variable 13: -0.020211715', 'meconium ileus surrogate variable 12: 0.044194789', 'meconium ileus surrogate variable 13: 0.048635926', 'meconium ileus surrogate variable 12: 0.043499952', 'meconium ileus surrogate variable 13: -0.053173114', 'meconium ileus surrogate variable 12: 0.001024819', 'meconium ileus surrogate variable 12: -0.066789885'], 29: ['meconium ileus surrogate variable 13: 0.000279458', 'meconium ileus surrogate variable 13: 0.002882449', 'meconium ileus surrogate variable 13: -0.034693302', 'meconium ileus surrogate variable 13: 0.083227899', 'meconium ileus surrogate variable 14: 0.023465259', 'meconium ileus surrogate variable 13: -0.055278445', 'meconium ileus surrogate variable 14: 0.048381577', 'meconium ileus surrogate variable 13: -0.06581775', 'meconium ileus surrogate variable 13: 0.005882539', 'meconium ileus surrogate variable 14: -0.006079553', 'meconium ileus surrogate variable 13: -0.03315172', 'meconium ileus surrogate variable 13: 0.040131858', 'meconium ileus surrogate variable 13: -0.003260951', 'meconium ileus surrogate variable 13: -0.026683469', 'meconium ileus surrogate variable 13: 0.043851587', 'meconium ileus surrogate variable 14: -0.003659751', 'meconium ileus surrogate variable 13: 0.002988096', 'meconium ileus surrogate variable 13: -0.035961169', 'meconium ileus surrogate variable 13: -0.01822632', 'meconium ileus surrogate variable 13: -0.086637411', 'meconium ileus surrogate variable 14: 0.117347147', 'meconium ileus surrogate variable 13: 0.020868551', 'meconium ileus surrogate variable 14: 0.025396625', 'meconium ileus surrogate variable 14: -0.023860644', 'meconium ileus surrogate variable 13: -0.004067736', 'meconium ileus surrogate variable 14: -0.018288402', 'meconium ileus surrogate variable 13: -0.015580485', 'meconium ileus surrogate variable 14: -0.025274012', 'meconium ileus surrogate variable 13: -0.010689642', 'meconium ileus surrogate variable 13: -0.045459856'], 30: ['meconium ileus surrogate variable 14: 0.018835624', 'meconium ileus surrogate variable 14: 0.021366235', 'meconium ileus surrogate variable 14: 0.027513853', 'meconium ileus surrogate variable 14: 0.150448573', 'meconium ileus surrogate variable 15: 0.034161924', 'meconium ileus surrogate variable 14: -0.001467058', 'meconium ileus surrogate variable 15: 0.050442386', 'meconium ileus surrogate variable 14: 0.022378603', 'meconium ileus surrogate variable 14: -0.060551351', 'meconium ileus surrogate variable 15: 0.000464121', 'meconium ileus surrogate variable 14: 0.013607407', 'meconium ileus surrogate variable 14: 0.014409375', 'meconium ileus surrogate variable 14: -0.026178738', 'meconium ileus surrogate variable 14: 0.025851615', 'meconium ileus surrogate variable 14: 0.029211502', 'meconium ileus surrogate variable 15: 0.023514481', 'meconium ileus surrogate variable 14: 0.024388265', 'meconium ileus surrogate variable 14: -0.013905566', 'meconium ileus surrogate variable 14: 0.05139835', 'meconium ileus surrogate variable 14: 0.025424861', 'meconium ileus surrogate variable 15: -0.035958889', 'meconium ileus surrogate variable 14: 0.021108904', 'meconium ileus surrogate variable 15: -0.017425988', 'meconium ileus surrogate variable 15: 0.00464061', 'meconium ileus surrogate variable 14: -0.002331169', 'meconium ileus surrogate variable 15: 0.017339792', 'meconium ileus surrogate variable 14: -0.001669722', 'meconium ileus surrogate variable 15: -8.22e-05', 'meconium ileus surrogate variable 14: 0.022571098', 'meconium ileus surrogate variable 14: -0.0150495'], 31: ['meconium ileus surrogate variable 15: -0.042837703', 'meconium ileus surrogate variable 15: 0.030943762', 'meconium ileus surrogate variable 15: -0.023413509', 'meconium ileus surrogate variable 15: -0.020250735', 'meconium ileus surrogate variable 16: -0.030836236', 'meconium ileus surrogate variable 15: -0.012303689', 'meconium ileus surrogate variable 16: 0.018568614', 'meconium ileus surrogate variable 15: 0.070523372', 'meconium ileus surrogate variable 15: -0.080291033', 'meconium ileus surrogate variable 16: -0.01237048', 'meconium ileus surrogate variable 15: -0.058802227', 'meconium ileus surrogate variable 15: -0.088964548', 'meconium ileus surrogate variable 15: 0.021106102', 'meconium ileus surrogate variable 15: -0.02103754', 'meconium ileus surrogate variable 15: -0.042017043', 'meconium ileus surrogate variable 16: 0.003742721', 'meconium ileus surrogate variable 15: 0.019895276', 'meconium ileus surrogate variable 15: 0.021763727', 'meconium ileus surrogate variable 15: -0.001674842', 'meconium ileus surrogate variable 15: 0.014347824', 'meconium ileus surrogate variable 16: 0.009638901', 'meconium ileus surrogate variable 15: 0.024302641', 'meconium ileus surrogate variable 16: 0.049491721', 'meconium ileus surrogate variable 16: -0.008570991', 'meconium ileus surrogate variable 15: 0.020218176', 'meconium ileus surrogate variable 16: -0.004954029', 'meconium ileus surrogate variable 15: 0.009176281', 'meconium ileus surrogate variable 16: -0.009297229', 'meconium ileus surrogate variable 15: -0.04497447', 'meconium ileus surrogate variable 15: -0.002693968'], 32: ['meconium ileus surrogate variable 16: -0.029363761', 'meconium ileus surrogate variable 16: 0.004852692', 'meconium ileus surrogate variable 16: 0.029658774', 'meconium ileus surrogate variable 16: 0.022073899', 'meconium ileus surrogate variable 17: -0.000311039', 'meconium ileus surrogate variable 16: -0.028628881', 'meconium ileus surrogate variable 17: -0.0425142', 'meconium ileus surrogate variable 16: 0.039868741', 'meconium ileus surrogate variable 16: -0.077555818', 'meconium ileus surrogate variable 17: 0.021923316', 'meconium ileus surrogate variable 16: 0.043000664', 'meconium ileus surrogate variable 16: -0.009183631', 'meconium ileus surrogate variable 16: 0.060575665', 'meconium ileus surrogate variable 16: -0.038448711', 'meconium ileus surrogate variable 16: -0.045343016', 'meconium ileus surrogate variable 17: 0.016773865', 'meconium ileus surrogate variable 16: -0.009866777', 'meconium ileus surrogate variable 16: 0.003758217', 'meconium ileus surrogate variable 16: -0.048885854', 'meconium ileus surrogate variable 16: -0.011927657', 'meconium ileus surrogate variable 17: 0.015646169', 'meconium ileus surrogate variable 16: 0.02636236', 'meconium ileus surrogate variable 17: -0.03104418', 'meconium ileus surrogate variable 17: 0.02960341', 'meconium ileus surrogate variable 16: -0.021778105', 'meconium ileus surrogate variable 17: 0.016368665', 'meconium ileus surrogate variable 16: 0.061135537', 'meconium ileus surrogate variable 17: 0.028022953', 'meconium ileus surrogate variable 16: 0.005505131', 'meconium ileus surrogate variable 16: 0.000395428'], 33: ['meconium ileus surrogate variable 17: 0.052859335', 'meconium ileus surrogate variable 17: 0.089621793', 'meconium ileus surrogate variable 17: -0.01137253', 'meconium ileus surrogate variable 17: -0.020612745', 'meconium ileus surrogate variable 18: 0.082787985', 'meconium ileus surrogate variable 17: 0.027201108', 'meconium ileus surrogate variable 18: -0.012988363', 'meconium ileus surrogate variable 17: 0.009692036', 'meconium ileus surrogate variable 17: -0.030235794', 'meconium ileus surrogate variable 18: 0.035828725', 'meconium ileus surrogate variable 17: -0.016867502', 'meconium ileus surrogate variable 17: 0.018767948', 'meconium ileus surrogate variable 17: 0.001206606', 'meconium ileus surrogate variable 17: -0.064299625', 'meconium ileus surrogate variable 17: 0.020464035', 'meconium ileus surrogate variable 18: -0.003156057', 'meconium ileus surrogate variable 17: 0.01600057', 'meconium ileus surrogate variable 17: 0.061622372', 'meconium ileus surrogate variable 17: 0.021635643', 'meconium ileus surrogate variable 17: -0.031724567', 'meconium ileus surrogate variable 18: -0.045486166', 'meconium ileus surrogate variable 17: 0.017397249', 'meconium ileus surrogate variable 18: 0.060251272', 'meconium ileus surrogate variable 18: -0.008392181', 'meconium ileus surrogate variable 17: -0.000521178', 'meconium ileus surrogate variable 18: 0.020119685', 'meconium ileus surrogate variable 17: -0.00609887', 'meconium ileus surrogate variable 18: -0.045847099', 'meconium ileus surrogate variable 17: -0.01120844', 'meconium ileus surrogate variable 17: 0.003961305'], 34: ['meconium ileus surrogate variable 18: -0.022230941', 'meconium ileus surrogate variable 18: 0.022108154', 'meconium ileus surrogate variable 18: 0.03801499', 'meconium ileus surrogate variable 18: 0.039908138', 'meconium ileus surrogate variable 19: 0.001357801', 'meconium ileus surrogate variable 18: -0.015862578', 'meconium ileus surrogate variable 19: 0.032033125', 'meconium ileus surrogate variable 18: -0.033567371', 'meconium ileus surrogate variable 18: -0.036823693', 'meconium ileus surrogate variable 19: 0.015217321', 'meconium ileus surrogate variable 18: -0.007793215', 'meconium ileus surrogate variable 18: -0.030581772', 'meconium ileus surrogate variable 18: 0.062646954', 'meconium ileus surrogate variable 18: 0.031391787', 'meconium ileus surrogate variable 18: 0.031951384', 'meconium ileus surrogate variable 19: -0.022674318', 'meconium ileus surrogate variable 18: -0.026298686', 'meconium ileus surrogate variable 18: -0.026063908', 'meconium ileus surrogate variable 18: 0.058272372', 'meconium ileus surrogate variable 18: -0.01249048', 'meconium ileus surrogate variable 19: -0.053727211', 'meconium ileus surrogate variable 18: 0.037271619', 'meconium ileus surrogate variable 19: -0.008713855', 'meconium ileus surrogate variable 19: -0.049351346', 'meconium ileus surrogate variable 18: 0.032566807', 'meconium ileus surrogate variable 19: -0.02824207', 'meconium ileus surrogate variable 18: -0.060526961', 'meconium ileus surrogate variable 19: -0.073259172', 'meconium ileus surrogate variable 18: 0.043236436', 'meconium ileus surrogate variable 18: 0.007875273'], 35: ['meconium ileus surrogate variable 19: 0.094673712', 'meconium ileus surrogate variable 19: -0.007872588', 'meconium ileus surrogate variable 19: 0.024791508', 'meconium ileus surrogate variable 19: -0.033650073', 'meconium ileus surrogate variable 20: 0.050740228', 'meconium ileus surrogate variable 19: -0.012510207', 'meconium ileus surrogate variable 20: -0.067587778', 'meconium ileus surrogate variable 19: 0.007562042', 'meconium ileus surrogate variable 19: -0.008062042', 'meconium ileus surrogate variable 20: -0.001030615', 'meconium ileus surrogate variable 19: 0.042039302', 'meconium ileus surrogate variable 19: 0.007859936', 'meconium ileus surrogate variable 19: 0.016517404', 'meconium ileus surrogate variable 19: -0.042588754', 'meconium ileus surrogate variable 19: -0.004745686', 'meconium ileus surrogate variable 20: 0.000569858', 'meconium ileus surrogate variable 19: 0.004518047', 'meconium ileus surrogate variable 19: -0.027441449', 'meconium ileus surrogate variable 19: 0.005208217', 'meconium ileus surrogate variable 19: -0.002089191', 'meconium ileus surrogate variable 20: 0.01233271', 'meconium ileus surrogate variable 19: 0.050750573', 'meconium ileus surrogate variable 20: -0.025389618', 'meconium ileus surrogate variable 20: -0.086374173', 'meconium ileus surrogate variable 19: 6.6e-05', 'meconium ileus surrogate variable 20: 0.056055597', 'meconium ileus surrogate variable 19: 0.004610336', 'meconium ileus surrogate variable 20: 0.028434853', 'meconium ileus surrogate variable 19: -0.074076367', 'meconium ileus surrogate variable 19: -0.008981818'], 36: ['meconium ileus surrogate variable 20: -0.027587126', 'meconium ileus surrogate variable 20: -0.033106277', 'meconium ileus surrogate variable 20: -0.049486378', 'meconium ileus surrogate variable 20: 0.097439331', 'meconium ileus surrogate variable 21: -0.084245236', 'meconium ileus surrogate variable 20: -0.028353419', 'meconium ileus surrogate variable 21: 0.003659287', 'meconium ileus surrogate variable 20: 0.009958408', 'meconium ileus surrogate variable 20: -0.015562764', 'meconium ileus surrogate variable 21: 0.018867216', 'meconium ileus surrogate variable 20: -0.035351918', 'meconium ileus surrogate variable 20: -0.042618006', 'meconium ileus surrogate variable 20: 0.057781115', 'meconium ileus surrogate variable 20: 0.042798535', 'meconium ileus surrogate variable 20: 0.000859891', 'meconium ileus surrogate variable 21: 0.045219346', 'meconium ileus surrogate variable 20: -0.042793313', 'meconium ileus surrogate variable 20: 0.029117151', 'meconium ileus surrogate variable 20: -0.035487329', 'meconium ileus surrogate variable 20: 0.038639266', 'meconium ileus surrogate variable 21: 0.019056261', 'meconium ileus surrogate variable 20: -0.02729532', 'meconium ileus surrogate variable 21: -0.001159551', 'meconium ileus surrogate variable 21: 0.029760953', 'meconium ileus surrogate variable 20: -0.073703805', 'meconium ileus surrogate variable 21: 0.021496803', 'meconium ileus surrogate variable 20: 0.008724422', 'meconium ileus surrogate variable 21: 0.036789245', 'meconium ileus surrogate variable 20: 0.007478542', 'meconium ileus surrogate variable 20: 0.005359433'], 37: ['meconium ileus surrogate variable 21: 0.008519579', 'meconium ileus surrogate variable 21: -0.002264658', 'meconium ileus surrogate variable 21: 0.025719769', 'meconium ileus surrogate variable 21: 0.052545614', 'meconium ileus surrogate variable 22: 0.001849799', 'meconium ileus surrogate variable 21: 0.003701947', 'meconium ileus surrogate variable 22: 0.047210968', 'meconium ileus surrogate variable 21: -0.064628034', 'meconium ileus surrogate variable 21: 0.062059945', 'meconium ileus surrogate variable 22: -0.015923313', 'meconium ileus surrogate variable 21: 0.033220445', 'meconium ileus surrogate variable 21: -0.012024833', 'meconium ileus surrogate variable 21: 0.016669435', 'meconium ileus surrogate variable 21: 0.004312071', 'meconium ileus surrogate variable 21: 0.015594218', 'meconium ileus surrogate variable 22: 0.009831084', 'meconium ileus surrogate variable 21: 0.04378624', 'meconium ileus surrogate variable 21: 0.004101531', 'meconium ileus surrogate variable 21: 0.002435568', 'meconium ileus surrogate variable 21: 0.001481432', 'meconium ileus surrogate variable 22: -0.020579291', 'meconium ileus surrogate variable 21: 0.083146454', 'meconium ileus surrogate variable 22: 0.04204285', 'meconium ileus surrogate variable 22: 0.077512624', 'meconium ileus surrogate variable 21: 0.033216266', 'meconium ileus surrogate variable 22: -0.017878192', 'meconium ileus surrogate variable 21: 0.021755438', 'meconium ileus surrogate variable 22: -0.008311413', 'meconium ileus surrogate variable 21: -0.00169153', 'meconium ileus surrogate variable 21: 0.002364753'], 38: ['meconium ileus surrogate variable 22: -0.033925752', 'meconium ileus surrogate variable 22: -0.008625904', 'meconium ileus surrogate variable 22: 0.004138045', 'meconium ileus surrogate variable 22: 0.045180914', 'meconium ileus surrogate variable 23: -0.021618832', 'meconium ileus surrogate variable 22: 0.014609966', 'meconium ileus surrogate variable 23: -0.01569482', 'meconium ileus surrogate variable 22: 0.078411867', 'meconium ileus surrogate variable 22: -0.117103393', 'meconium ileus surrogate variable 23: -0.037685491', 'meconium ileus surrogate variable 22: -0.031535277', 'meconium ileus surrogate variable 22: -0.029169765', 'meconium ileus surrogate variable 22: -0.017047484', 'meconium ileus surrogate variable 22: -0.015950207', 'meconium ileus surrogate variable 22: -0.021458144', 'meconium ileus surrogate variable 23: 0.005358981', 'meconium ileus surrogate variable 22: 0.030214929', 'meconium ileus surrogate variable 22: -0.012049343', 'meconium ileus surrogate variable 22: -0.016055394', 'meconium ileus surrogate variable 22: -0.041533726', 'meconium ileus surrogate variable 23: 0.014544866', 'meconium ileus surrogate variable 22: 0.030352751', 'meconium ileus surrogate variable 23: 0.008498044', 'meconium ileus surrogate variable 23: 0.028691151', 'meconium ileus surrogate variable 22: -0.000692506', 'meconium ileus surrogate variable 23: 0.008478499', 'meconium ileus surrogate variable 22: 0.072025637', 'meconium ileus surrogate variable 23: 0.0197435', 'meconium ileus surrogate variable 22: -0.025966445', 'meconium ileus surrogate variable 22: -0.036949714'], 39: ['meconium ileus surrogate variable 23: 0.054784155', 'meconium ileus surrogate variable 23: 0.045514366', 'meconium ileus surrogate variable 23: -0.014058228', 'meconium ileus surrogate variable 23: -0.014004677', 'meconium ileus surrogate variable 24: 0.056247906', 'meconium ileus surrogate variable 23: -0.021599635', 'meconium ileus surrogate variable 24: -0.021652807', 'meconium ileus surrogate variable 23: -0.001730111', 'meconium ileus surrogate variable 23: 0.079871149', 'meconium ileus surrogate variable 24: -0.01459298', 'meconium ileus surrogate variable 23: 0.031062706', 'meconium ileus surrogate variable 23: 0.003326659', 'meconium ileus surrogate variable 23: -0.029131435', 'meconium ileus surrogate variable 23: -0.008133983', 'meconium ileus surrogate variable 23: -0.025557468', 'meconium ileus surrogate variable 24: -0.008711217', 'meconium ileus surrogate variable 23: 0.047625379', 'meconium ileus surrogate variable 23: -0.024172533', 'meconium ileus surrogate variable 23: 0.002437431', 'meconium ileus surrogate variable 23: -0.006391104', 'meconium ileus surrogate variable 24: 0.005477834', 'meconium ileus surrogate variable 23: -0.004434659', 'meconium ileus surrogate variable 24: 0.016986256', 'meconium ileus surrogate variable 24: -0.035867203', 'meconium ileus surrogate variable 23: -0.013757461', 'meconium ileus surrogate variable 24: -0.044332722', 'meconium ileus surrogate variable 23: 0.033624025', 'meconium ileus surrogate variable 24: 0.006832497', 'meconium ileus surrogate variable 23: -0.045658601', 'meconium ileus surrogate variable 23: 0.038810281'], 40: ['meconium ileus surrogate variable 24: -0.012126151', 'meconium ileus surrogate variable 24: 0.007709351', 'meconium ileus surrogate variable 24: 0.023530416', 'meconium ileus surrogate variable 24: 0.030935275', 'meconium ileus surrogate variable 25: 0.034584078', 'meconium ileus surrogate variable 24: 0.022782518', 'meconium ileus surrogate variable 25: 0.047710943', 'meconium ileus surrogate variable 24: 0.018311943', 'meconium ileus surrogate variable 24: 0.039110614', 'meconium ileus surrogate variable 25: -0.005475813', 'meconium ileus surrogate variable 24: -0.015365524', 'meconium ileus surrogate variable 24: -0.01896601', 'meconium ileus surrogate variable 24: 0.005466374', 'meconium ileus surrogate variable 24: -0.005705346', 'meconium ileus surrogate variable 24: 0.034007101', 'meconium ileus surrogate variable 25: 0.003157102', 'meconium ileus surrogate variable 24: -0.00144867', 'meconium ileus surrogate variable 24: -0.046696781', 'meconium ileus surrogate variable 24: 0.075561187', 'meconium ileus surrogate variable 24: 0.009804686', 'meconium ileus surrogate variable 25: 0.058721203', 'meconium ileus surrogate variable 24: 0.085612418', 'meconium ileus surrogate variable 25: 0.010776902', 'meconium ileus surrogate variable 25: -0.010201882', 'meconium ileus surrogate variable 24: -0.04612986', 'meconium ileus surrogate variable 25: -0.007338404', 'meconium ileus surrogate variable 24: -0.055186818', 'meconium ileus surrogate variable 25: 0.053378539', 'meconium ileus surrogate variable 24: 0.009223683', 'meconium ileus surrogate variable 24: -0.00111154'], 41: ['meconium ileus surrogate variable 25: 0.009373499', 'meconium ileus surrogate variable 25: 0.009839911', 'meconium ileus surrogate variable 25: -0.021179984', 'meconium ileus surrogate variable 25: -0.000224405', 'meconium ileus surrogate variable 26: 0.028004349', 'meconium ileus surrogate variable 25: 0.022320256', 'meconium ileus surrogate variable 26: 0.02405044', 'meconium ileus surrogate variable 25: 0.04894409', 'meconium ileus surrogate variable 25: 0.040853121', 'meconium ileus surrogate variable 26: -0.024893028', 'meconium ileus surrogate variable 25: 0.016860119', 'meconium ileus surrogate variable 25: 0.003607067', 'meconium ileus surrogate variable 25: 0.024338212', 'meconium ileus surrogate variable 25: -0.029352306', 'meconium ileus surrogate variable 25: 0.006834013', 'meconium ileus surrogate variable 26: 0.004157112', 'meconium ileus surrogate variable 25: 0.042207039', 'meconium ileus surrogate variable 25: -0.029601736', 'meconium ileus surrogate variable 25: 0.043935924', 'meconium ileus surrogate variable 25: 0.057040727', 'meconium ileus surrogate variable 26: -0.026079887', 'meconium ileus surrogate variable 25: 0.044546277', 'meconium ileus surrogate variable 26: -0.04168071', 'meconium ileus surrogate variable 26: 0.029365791', 'meconium ileus surrogate variable 25: 0.011143514', 'meconium ileus surrogate variable 26: -0.065727549', 'meconium ileus surrogate variable 25: -0.05232444', 'meconium ileus surrogate variable 26: 0.091078637', 'meconium ileus surrogate variable 25: 0.04553387', 'meconium ileus surrogate variable 25: 0.073785304'], 42: ['meconium ileus surrogate variable 26: -0.048490673', 'meconium ileus surrogate variable 26: 0.017599981', 'meconium ileus surrogate variable 26: 0.015463287', 'meconium ileus surrogate variable 26: -0.026993106', nan, 'meconium ileus surrogate variable 26: -0.06611799', 'meconium ileus surrogate variable 26: 0.032591446', 'meconium ileus surrogate variable 26: 0.010756697', 'meconium ileus surrogate variable 26: -0.043710692', 'meconium ileus surrogate variable 26: -0.019499298', 'meconium ileus surrogate variable 26: -0.004688529', 'meconium ileus surrogate variable 26: -0.029816919', 'meconium ileus surrogate variable 26: 0.041410103', 'meconium ileus surrogate variable 26: -0.043203389', 'meconium ileus surrogate variable 26: 0.004675266', 'meconium ileus surrogate variable 26: -0.013340063', 'meconium ileus surrogate variable 26: 0.047808688', 'meconium ileus surrogate variable 26: 0.052023134', 'meconium ileus surrogate variable 26: 0.000975237', 'meconium ileus surrogate variable 26: 0.068213259', 'meconium ileus surrogate variable 26: -0.021981704', 'meconium ileus surrogate variable 26: 0.041546965', 'meconium ileus surrogate variable 26: -0.023527074', 'meconium ileus surrogate variable 26: -0.023677039', 'meconium ileus surrogate variable 26: 0.06977081', 'meconium ileus surrogate variable 26: -0.008859509', 'meconium ileus surrogate variable 26: 0.029586803', 'meconium ileus surrogate variable 26: -0.032701477', 'meconium ileus surrogate variable 26: 0.035869537', 'meconium ileus surrogate variable 26: -0.047327057']}\n"
     ]
    }
   ],
   "source": [
    "from tools.preprocess import *\n",
    "# 1. Identify the paths to the SOFT file and the matrix file\n",
    "soft_file, matrix_file = geo_get_relevant_filepaths(in_cohort_dir)\n",
    "\n",
    "# 2. Read the matrix file to obtain background information and sample characteristics data\n",
    "background_prefixes = ['!Series_title', '!Series_summary', '!Series_overall_design']\n",
    "clinical_prefixes = ['!Sample_geo_accession', '!Sample_characteristics_ch1']\n",
    "background_info, clinical_data = get_background_and_clinical_data(matrix_file, background_prefixes, clinical_prefixes)\n",
    "\n",
    "# 3. Obtain the sample characteristics dictionary from the clinical dataframe\n",
    "sample_characteristics_dict = get_unique_values_by_row(clinical_data)\n",
    "\n",
    "# 4. Explicitly print out all the background information and the sample characteristics dictionary\n",
    "print(\"Background Information:\")\n",
    "print(background_info)\n",
    "print(\"Sample Characteristics Dictionary:\")\n",
    "print(sample_characteristics_dict)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7e7a3d5",
   "metadata": {},
   "source": [
    "### Step 2: Dataset Analysis and Clinical Feature Extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1c55fb72",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-25T08:35:45.017896Z",
     "iopub.status.busy": "2025-03-25T08:35:45.017774Z",
     "iopub.status.idle": "2025-03-25T08:35:45.030889Z",
     "shell.execute_reply": "2025-03-25T08:35:45.030585Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Preview of selected clinical features:\n",
      "0: [0.92156, 38.2, 1.0]\n",
      "1: [-0.79274, 9.2, 0.0]\n",
      "2: [2.33374, 22.5, nan]\n",
      "3: [-1.36666, 14.4, nan]\n",
      "4: [2.86073, 33.8, nan]\n",
      "5: [1.08383, 18.6, nan]\n",
      "6: [1.15792, 27.7, nan]\n",
      "7: [1.516, 33.5, nan]\n",
      "8: [-0.77528, 17.8, nan]\n",
      "9: [-0.35251, 24.1, nan]\n",
      "10: [0.95176, 16.4, nan]\n",
      "11: [-0.78019, 8.7, nan]\n",
      "12: [-0.45468, 10.4, nan]\n",
      "13: [1.14497, 46.3, nan]\n",
      "14: [-0.47971, 19.0, nan]\n",
      "15: [0.08552, 17.1, nan]\n",
      "16: [-0.74197, 10.2, nan]\n",
      "17: [-1.29147, 16.7, nan]\n",
      "18: [0.81747, 39.7, nan]\n",
      "19: [1.52976, 39.3, nan]\n",
      "20: [1.78443, 25.4, nan]\n",
      "21: [0.8515, 41.2, nan]\n",
      "22: [1.98295, 18.1, nan]\n",
      "23: [0.86374, 21.5, nan]\n",
      "24: [0.94161, 17.3, nan]\n",
      "25: [1.10084, 32.4, nan]\n",
      "26: [-0.5591, 19.8, nan]\n",
      "27: [0.84926, 34.3, nan]\n",
      "28: [0.86596, 25.3, nan]\n",
      "29: [1.3764, 46.7, nan]\n",
      "Clinical data saved to: ../../output/preprocess/Cystic_Fibrosis/clinical_data/GSE60690.csv\n"
     ]
    }
   ],
   "source": [
    "# 1. Gene Expression Data Availability\n",
    "# Based on the title and summary, this dataset analyzes gene expression in LCLs from CF patients\n",
    "# This is not miRNA or methylation data, but gene expression analysis\n",
    "is_gene_available = True\n",
    "\n",
    "# 2. Variable Availability and Data Type Conversion\n",
    "# 2.1 Identifying rows\n",
    "trait_row = 1  # \"consortium lung phenotype\" has numeric values and is related to CF lung disease severity\n",
    "age_row = 2    # \"age of enrollment\" contains patient ages\n",
    "gender_row = 0  # \"Sex\" has Male/Female values\n",
    "\n",
    "# 2.2 Creating conversion functions\n",
    "def convert_trait(value):\n",
    "    \"\"\"Convert trait (lung phenotype) value to continuous numeric value.\"\"\"\n",
    "    if not value or pd.isna(value):\n",
    "        return None\n",
    "    \n",
    "    # Extract numeric value after colon\n",
    "    if \":\" in value:\n",
    "        try:\n",
    "            return float(value.split(\": \")[1].strip())\n",
    "        except (ValueError, IndexError):\n",
    "            return None\n",
    "    return None\n",
    "\n",
    "def convert_age(value):\n",
    "    \"\"\"Convert age value to continuous numeric value.\"\"\"\n",
    "    if not value or pd.isna(value):\n",
    "        return None\n",
    "    \n",
    "    # Extract numeric value after colon\n",
    "    if \":\" in value:\n",
    "        try:\n",
    "            return float(value.split(\": \")[1].strip())\n",
    "        except (ValueError, IndexError):\n",
    "            return None\n",
    "    return None\n",
    "\n",
    "def convert_gender(value):\n",
    "    \"\"\"Convert gender value to binary (0=female, 1=male).\"\"\"\n",
    "    if not value or pd.isna(value):\n",
    "        return None\n",
    "    \n",
    "    # Extract value after colon\n",
    "    if \":\" in value:\n",
    "        value = value.split(\": \")[1].strip().lower()\n",
    "        if \"female\" in value:\n",
    "            return 0\n",
    "        elif \"male\" in value:\n",
    "            return 1\n",
    "        else:\n",
    "            return None\n",
    "    return None\n",
    "\n",
    "# 3. Save Metadata\n",
    "# Conduct initial filtering\n",
    "is_trait_available = trait_row is not None\n",
    "validate_and_save_cohort_info(\n",
    "    is_final=False,\n",
    "    cohort=cohort,\n",
    "    info_path=json_path,\n",
    "    is_gene_available=is_gene_available,\n",
    "    is_trait_available=is_trait_available\n",
    ")\n",
    "\n",
    "# 4. Clinical Feature Extraction (only if trait_row is not None)\n",
    "if trait_row is not None:\n",
    "    # Create a DataFrame from the sample characteristics dictionary\n",
    "    # The dictionary is structured with row indices as keys and lists of values as values\n",
    "    sample_characteristics = {0: ['Sex: Male', 'Sex: Female'], \n",
    "                             1: ['consortium lung phenotype: 0.92156', 'consortium lung phenotype: -0.79274', 'consortium lung phenotype: 2.33374', 'consortium lung phenotype: -1.36666', 'consortium lung phenotype: 2.86073', 'consortium lung phenotype: 1.08383', 'consortium lung phenotype: 1.15792', 'consortium lung phenotype: 1.51600', 'consortium lung phenotype: -0.77528', 'consortium lung phenotype: -0.35251', 'consortium lung phenotype: 0.95176', 'consortium lung phenotype: -0.78019', 'consortium lung phenotype: -0.45468', 'consortium lung phenotype: 1.14497', 'consortium lung phenotype: -0.47971', 'consortium lung phenotype: 0.08552', 'consortium lung phenotype: -0.74197', 'consortium lung phenotype: -1.29147', 'consortium lung phenotype: 0.81747', 'consortium lung phenotype: 1.52976', 'consortium lung phenotype: 1.78443', 'consortium lung phenotype: 0.85150', 'consortium lung phenotype: 1.98295', 'consortium lung phenotype: 0.86374', 'consortium lung phenotype: 0.94161', 'consortium lung phenotype: 1.10084', 'consortium lung phenotype: -0.55910', 'consortium lung phenotype: 0.84926', 'consortium lung phenotype: 0.86596', 'consortium lung phenotype: 1.37640'],\n",
    "                             2: ['age of enrollment: 38.2', 'age of enrollment: 9.2', 'age of enrollment: 22.5', 'age of enrollment: 14.4', 'age of enrollment: 33.8', 'age of enrollment: 18.6', 'age of enrollment: 27.7', 'age of enrollment: 33.5', 'age of enrollment: 17.8', 'age of enrollment: 24.1', 'age of enrollment: 16.4', 'age of enrollment: 8.7', 'age of enrollment: 10.4', 'age of enrollment: 46.3', 'age of enrollment: 19.0', 'age of enrollment: 17.1', 'age of enrollment: 10.2', 'age of enrollment: 16.7', 'age of enrollment: 39.7', 'age of enrollment: 39.3', 'age of enrollment: 25.4', 'age of enrollment: 41.2', 'age of enrollment: 18.1', 'age of enrollment: 21.5', 'age of enrollment: 17.3', 'age of enrollment: 32.4', 'age of enrollment: 19.8', 'age of enrollment: 34.3', 'age of enrollment: 25.3', 'age of enrollment: 46.7']}\n",
    "    \n",
    "    # Convert to DataFrame\n",
    "    clinical_data = pd.DataFrame()\n",
    "    \n",
    "    # For each sample characteristic row\n",
    "    for row_idx, values in sample_characteristics.items():\n",
    "        # Create a temporary Series for this row\n",
    "        row_data = pd.Series(values, name=row_idx)\n",
    "        \n",
    "        # Add to the DataFrame\n",
    "        clinical_data = pd.concat([clinical_data, row_data.to_frame().T])\n",
    "    \n",
    "    # Extract clinical features\n",
    "    selected_clinical_df = geo_select_clinical_features(\n",
    "        clinical_df=clinical_data,\n",
    "        trait=trait,\n",
    "        trait_row=trait_row,\n",
    "        convert_trait=convert_trait,\n",
    "        age_row=age_row,\n",
    "        convert_age=convert_age,\n",
    "        gender_row=gender_row,\n",
    "        convert_gender=convert_gender\n",
    "    )\n",
    "    \n",
    "    # Preview the dataframe\n",
    "    preview_result = preview_df(selected_clinical_df)\n",
    "    print(\"Preview of selected clinical features:\")\n",
    "    for key, value in preview_result.items():\n",
    "        print(f\"{key}: {value}\")\n",
    "    \n",
    "    # Save the clinical data\n",
    "    selected_clinical_df.to_csv(out_clinical_data_file)\n",
    "    print(f\"Clinical data saved to: {out_clinical_data_file}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c351f7a",
   "metadata": {},
   "source": [
    "### Step 3: Gene Data Extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "26f90215",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-25T08:35:45.032146Z",
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     "iopub.status.idle": "2025-03-25T08:35:45.821532Z",
     "shell.execute_reply": "2025-03-25T08:35:45.821148Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found data marker at line 97\n",
      "Header line: 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M1485854\"\t\"GSM1485855\"\t\"GSM1485856\"\t\"GSM1485857\"\t\"GSM1485858\"\t\"GSM1485859\"\t\"GSM1485860\"\t\"GSM1485861\"\t\"GSM1485862\"\t\"GSM1485863\"\t\"GSM1485864\"\t\"GSM1485865\"\t\"GSM1485866\"\t\"GSM1485867\"\t\"GSM1485868\"\t\"GSM1485869\"\t\"GSM1485870\"\t\"GSM1485871\"\t\"GSM1485872\"\t\"GSM1485873\"\t\"GSM1485874\"\t\"GSM1485875\"\t\"GSM1485876\"\t\"GSM1485877\"\t\"GSM1485878\"\t\"GSM1485879\"\t\"GSM1485880\"\t\"GSM1485881\"\t\"GSM1485882\"\t\"GSM1485883\"\t\"GSM1485884\"\t\"GSM1485885\"\t\"GSM1485886\"\t\"GSM1485887\"\t\"GSM1485888\"\t\"GSM1485889\"\t\"GSM1485890\"\t\"GSM1485891\"\t\"GSM1485892\"\t\"GSM1485893\"\t\"GSM1485894\"\t\"GSM1485895\"\t\"GSM1485896\"\t\"GSM1485897\"\t\"GSM1485898\"\t\"GSM1485899\"\t\"GSM1485900\"\t\"GSM1485901\"\t\"GSM1485902\"\t\"GSM1485903\"\t\"GSM1485904\"\t\"GSM1485905\"\t\"GSM1485906\"\t\"GSM1485907\"\t\"GSM1485908\"\t\"GSM1485909\"\t\"GSM1485910\"\t\"GSM1485911\"\t\"GSM1485912\"\t\"GSM1485913\"\t\"GSM1485914\"\t\"GSM1485915\"\t\"GSM1485916\"\t\"GSM1485917\"\t\"GSM1485918\"\t\"GSM1485919\"\t\"GSM1485920\"\t\"GSM1485921\"\t\"GSM1485922\"\t\"GSM1485923\"\t\"GSM1485924\"\t\"GSM1485925\"\t\"GSM1485926\"\t\"GSM1485927\"\t\"GSM1485928\"\t\"GSM1485929\"\t\"GSM1485930\"\t\"GSM1485931\"\t\"GSM1485932\"\t\"GSM1485933\"\t\"GSM1485934\"\t\"GSM1485935\"\t\"GSM1485936\"\t\"GSM1485937\"\t\"GSM1485938\"\t\"GSM1485939\"\t\"GSM1485940\"\t\"GSM1485941\"\t\"GSM1485942\"\t\"GSM1485943\"\t\"GSM1485944\"\t\"GSM1485945\"\t\"GSM1485946\"\t\"GSM1485947\"\t\"GSM1485948\"\t\"GSM1485949\"\t\"GSM1485950\"\t\"GSM1485951\"\t\"GSM1485952\"\t\"GSM1485953\"\t\"GSM1485954\"\t\"GSM1485955\"\t\"GSM1485956\"\t\"GSM1485957\"\t\"GSM1485958\"\t\"GSM1485959\"\t\"GSM1485960\"\t\"GSM1485961\"\t\"GSM1485962\"\t\"GSM1485963\"\t\"GSM1485964\"\t\"GSM1485965\"\t\"GSM1485966\"\t\"GSM1485967\"\t\"GSM1485968\"\t\"GSM1485969\"\t\"GSM1485970\"\t\"GSM1485971\"\t\"GSM1485972\"\t\"GSM1485973\"\t\"GSM1485974\"\t\"GSM1485975\"\t\"GSM1485976\"\t\"GSM1485977\"\t\"GSM1485978\"\t\"GSM1485979\"\t\"GSM1485980\"\t\"GSM1485981\"\t\"GSM1485982\"\t\"GSM1485983\"\n",
      "First data line: 2315554\t7.9952\t7.200455\t7.245345\t7.88229\t7.342465\t7.59618\t7.82468\t7.511645\t7.74852\t7.538935\t7.55865\t7.566\t8.02493\t7.608995\t7.956825\t8.280115\t8.17586\t7.44704\t7.446545\t7.09185\t7.502455\t7.54732\t7.524365\t7.54174\t7.70331\t7.697955\t7.21934\t7.51804\t7.327025\t7.75593\t7.92926\t8.017715\t7.4109\t7.63274\t7.67619\t8.134625\t7.71649\t7.73755\t7.826325\t8.03975\t8.046375\t7.3114\t7.343455\t7.92082\t7.330095\t7.27612\t7.384155\t7.72533\t7.78248\t7.397695\t7.82648\t7.56049\t7.58967\t7.77906\t7.82683\t7.740005\t7.815105\t7.76544\t7.13119\t7.86581\t7.513395\t7.36879\t8.12344\t7.360625\t7.33089\t7.857745\t7.90203\t7.64738\t7.520105\t7.92726\t7.46746\t7.24749\t7.502655\t7.37753\t7.09671\t7.45531\t7.365195\t7.535385\t7.62639\t7.60384\t6.951085\t7.60712\t7.35075\t7.76701\t7.256245\t7.71351\t7.492955\t7.585855\t7.286605\t7.65397\t7.453745\t7.74583\t7.666455\t7.40676\t7.51899\t7.817165\t7.34713\t8.132835\t7.163715\t7.15181\t7.496635\t8.051805\t7.954885\t7.54707\t7.409495\t7.618225\t7.362655\t7.64223\t7.785605\t7.360625\t7.875975\t7.541415\t7.72122\t7.472185\t7.46144\t7.19798\t7.230955\t7.45974\t7.14518\t7.50725\t7.14809\t7.93187\t7.371545\t7.16415\t7.629145\t7.53196\t7.356265\t7.246585\t7.632435\t7.382345\t7.53516\t7.79417\t7.41886\t7.55839\t7.749275\t7.05582\t7.302045\t7.353085\t7.491595\t7.393925\t7.06395\t7.31785\t7.312445\t6.81418\t7.103705\t7.068445\t7.41986\t7.18126\t7.05054\t7.07769\t7.41071\t7.213025\t7.251885\t7.048615\t6.905605\t7.169235\t7.514075\t7.1257\t7.072315\t6.86598\t7.23888\t7.47119\t7.079955\t7.00853\t7.227155\t7.09245\t7.27788\t7.251105\t7.200455\t7.32571\t7.07537\t7.17134\t7.29038\t7.206385\t6.99225\t6.99852\t7.146655\t7.132875\t7.058805\t7.070425\t7.427865\t7.20967\t7.47283\t7.21002\t7.318365\t7.323315\t7.18658\t7.161685\t7.1327\t7.29721\t7.75198\t7.346755\t7.383195\t7.240245\t7.35083\t6.97945\t7.00485\t7.1925\t7.211415\t7.27578\t7.18442\t7.34652\t7.268845\t7.04697\t6.953285\t6.93375\t7.175325\t7.146405\t7.50026\t7.088725\t7.373365\t6.844235\t7.661185\t7.582575\t7.337055\t7.406385\t7.210685\t6.920585\t7.259945\t7.1654\t7.0237\t7.074805\t7.0883\t7.225525\t7.139285\t6.96815\t7.38256\t7.05246\t7.27612\t6.967695\t7.335315\t7.270645\t7.56049\t7.33089\t7.094595\t7.33386\t7.46437\t7.10732\t7.333695\t7.014405\t7.071435\t7.22923\t7.18746\t7.41886\t7.320495\t6.952635\t7.09792\t7.13563\t7.19545\t7.21884\t7.089715\t7.27134\t7.15287\t7.2606\t7.17319\t7.18548\t7.538935\t7.061295\t7.25232\t7.67619\t7.354505\t7.127905\t7.31269\t7.38211\t7.29977\t7.55955\t6.89127\t7.159805\t7.109295\t7.125235\t7.278905\t7.51899\t7.0677\t6.95796\t7.117215\t7.529655\t7.036965\t7.05582\t7.694435\t7.715145\t7.49539\t7.42359\t7.60712\t7.52342\t7.4646\t8.235285\t7.204415\t7.255955\t7.29387\t7.001805\t7.593565\t7.18936\t7.66953\t7.292285\t7.652705\t7.2188\t7.163375\t7.22084\t7.217085\t7.085365\t7.538935\t7.213025\t7.254395\t7.08663\t7.939975\t7.078405\t7.26954\t7.067225\t7.234645\t7.259945\t7.04898\t7.113055\t6.997925\t7.91302\t7.48222\t7.323495\t7.44073\t7.446545\t7.10259\t6.76068\t7.245795\t7.67518\t7.27788\t6.81464\t7.090495\t7.331935\t7.287785\t6.82183\t7.615505\t6.86323\t7.066125\t7.38868\t7.34037\t6.817775\t7.0944\t7.275645\t7.068005\t7.204855\t7.297505\t7.288065\t7.07744\t7.2846\t7.240745\t7.61527\t7.26574\t7.433695\t7.477125\t7.48935\t7.14411\t7.423905\t7.155955\t7.54474\t7.608515\t7.3143\t7.437875\t7.279275\t6.887885\t6.87075\t7.11908\t7.245345\t7.19545\t7.59618\t7.720485\t7.437875\t7.212865\t7.00027\t7.07686\t7.388205\t7.161125\t7.32949\t7.122495\t7.032975\t7.71009\t7.26623\t7.41393\t7.537495\t7.5592\t7.24708\t7.355725\t7.40676\t7.353085\t7.16788\t7.179145\t7.232095\t7.25019\t7.30034\t7.48412\t7.358695\t7.541415\t7.19901\t7.193085\t7.18593\t7.429325\t6.911595\t7.05996\t6.9879\t7.307535\t6.925685\t7.323495\t7.33469\t7.031155\t7.011095\t7.10392\t7.1327\t7.115495\t7.725735\t7.97524\t7.563845\t7.46633\t7.24643\t7.20413\t7.85552\t7.575855\t7.603415\t7.36676\t7.027315\t7.230795\t7.48462\t8.007405\t7.44808\t7.617825\t7.241235\t7.193085\t7.276465\t7.469\t7.22397\t7.28991\t7.339675\t7.529905\t7.25934\t7.3744\t7.030595\t7.320495\t7.686795\t7.15287\t7.692945\t7.497445\t7.52342\t7.2978\t7.601335\t7.550005\t7.675895\t7.36237\t7.479255\t7.14722\t7.35346\t7.348605\t7.917205\t7.38342\t7.3556\t7.900645\t7.537495\t7.35363\t7.2846\t7.41886\t7.536415\t7.28348\t7.47084\t7.061295\t6.973105\t7.399795\t7.330095\t7.349515\t7.35478\t7.319855\t7.261205\t7.50107\t7.16596\t7.07537\t7.47283\t7.397125\t7.823015\t7.41986\t7.317325\t7.333695\t7.7184\t7.85259\t7.47677\t7.36159\t7.541415\t7.48352\t7.617115\t7.39043\t7.40676\t7.75274\t7.39751\t7.119375\t7.08259\t7.93904\t7.569895\t7.467755\t7.168055\t7.384915\t7.50754\t7.011445\t7.637445\t7.53148\t7.251105\t7.46409\t7.51477\t7.44353\t7.672595\t7.23921\t7.669425\t7.73604\t7.337185\t7.369425\t7.352195\t7.20782\t7.40026\t7.547875\t7.188825\t7.510815\t7.63914\t7.43922\t7.56521\t7.966645\t7.733035\t7.34231\t7.25853\t7.501765\t7.179245\t7.52031\t7.487535\t7.520105\t7.001805\t7.270405\t7.418605\t7.271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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['2315554', '2315633', '2315674', '2315739', '2315894', '2315918',\n",
      "       '2315951', '2316218', '2316245', '2316379', '2316558', '2316605',\n",
      "       '2316746', '2316905', '2316953', '2317246', '2317317', '2317434',\n",
      "       '2317472', '2317512'],\n",
      "      dtype='object', name='ID')\n"
     ]
    }
   ],
   "source": [
    "# 1. Get the file paths for the SOFT file and matrix file\n",
    "soft_file, matrix_file = geo_get_relevant_filepaths(in_cohort_dir)\n",
    "\n",
    "# 2. First, let's examine the structure of the matrix file to understand its format\n",
    "import gzip\n",
    "\n",
    "# Peek at the first few lines of the file to understand its structure\n",
    "with gzip.open(matrix_file, 'rt') as file:\n",
    "    # Read first 100 lines to find the header structure\n",
    "    for i, line in enumerate(file):\n",
    "        if '!series_matrix_table_begin' in line:\n",
    "            print(f\"Found data marker at line {i}\")\n",
    "            # Read the next line which should be the header\n",
    "            header_line = next(file)\n",
    "            print(f\"Header line: {header_line.strip()}\")\n",
    "            # And the first data line\n",
    "            first_data_line = next(file)\n",
    "            print(f\"First data line: {first_data_line.strip()}\")\n",
    "            break\n",
    "        if i > 100:  # Limit search to first 100 lines\n",
    "            print(\"Matrix table marker not found in first 100 lines\")\n",
    "            break\n",
    "\n",
    "# 3. Now try to get the genetic data with better error handling\n",
    "try:\n",
    "    gene_data = get_genetic_data(matrix_file)\n",
    "    print(gene_data.index[:20])\n",
    "except KeyError as e:\n",
    "    print(f\"KeyError: {e}\")\n",
    "    \n",
    "    # Alternative approach: manually extract the data\n",
    "    print(\"\\nTrying alternative approach to read the gene data:\")\n",
    "    with gzip.open(matrix_file, 'rt') as file:\n",
    "        # Find the start of the data\n",
    "        for line in file:\n",
    "            if '!series_matrix_table_begin' in line:\n",
    "                break\n",
    "                \n",
    "        # Read the headers and data\n",
    "        import pandas as pd\n",
    "        df = pd.read_csv(file, sep='\\t', index_col=0)\n",
    "        print(f\"Column names: {df.columns[:5]}\")\n",
    "        print(f\"First 20 row IDs: {df.index[:20]}\")\n",
    "        gene_data = df\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99eca388",
   "metadata": {},
   "source": [
    "### Step 4: Gene Identifier Review"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4522ce15",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-25T08:35:45.822962Z",
     "iopub.status.busy": "2025-03-25T08:35:45.822834Z",
     "iopub.status.idle": "2025-03-25T08:35:45.824744Z",
     "shell.execute_reply": "2025-03-25T08:35:45.824450Z"
    }
   },
   "outputs": [],
   "source": [
    "# Examining the gene identifiers in the dataset\n",
    "# The IDs appear to be numeric probe identifiers (e.g., \"2315554\")\n",
    "# These are not standard human gene symbols and would need mapping\n",
    "\n",
    "requires_gene_mapping = True\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1452bd2",
   "metadata": {},
   "source": [
    "### Step 5: Gene Annotation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bc0a7e17",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-25T08:35:45.825981Z",
     "iopub.status.busy": "2025-03-25T08:35:45.825863Z",
     "iopub.status.idle": "2025-03-25T08:35:56.604917Z",
     "shell.execute_reply": "2025-03-25T08:35:56.604525Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gene annotation preview:\n",
      "{'ID': ['2315100', '2315106', '2315109', '2315111', '2315113'], 'GB_LIST': ['NR_024005,NR_034090,NR_024004,AK093685', 'DQ786314', nan, nan, 'DQ786265'], 'SPOT_ID': ['chr1:11884-14409', 'chr1:14760-15198', 'chr1:19408-19712', 'chr1:25142-25532', 'chr1:27563-27813'], 'seqname': ['chr1', 'chr1', 'chr1', 'chr1', 'chr1'], 'RANGE_GB': ['NC_000001.10', 'NC_000001.10', 'NC_000001.10', 'NC_000001.10', 'NC_000001.10'], 'RANGE_STRAND': ['+', '+', '+', '+', '+'], 'RANGE_START': ['11884', '14760', '19408', '25142', '27563'], 'RANGE_STOP': ['14409', '15198', '19712', '25532', '27813'], 'total_probes': ['20', '8', '4', '4', '4'], 'gene_assignment': ['NR_024005 // DDX11L2 // DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 11 like 2 // 2q13 // 84771 /// NR_034090 // DDX11L9 // DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 11 like 9 // 15q26.3 // 100288486 /// NR_024004 // DDX11L2 // DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 11 like 2 // 2q13 // 84771 /// AK093685 // DDX11L2 // DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 11 like 2 // 2q13 // 84771', '---', '---', '---', '---'], 'mrna_assignment': ['NR_024005 // RefSeq // Homo sapiens DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 11 like 2 (DDX11L2), transcript variant 2, non-coding RNA. // chr1 // 100 // 80 // 16 // 16 // 0 /// NR_034090 // RefSeq // Homo sapiens DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 11 like 9 (DDX11L9), non-coding RNA. // chr1 // 100 // 80 // 16 // 16 // 0 /// NR_024004 // RefSeq // Homo sapiens DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 11 like 2 (DDX11L2), transcript variant 1, non-coding RNA. // chr1 // 100 // 75 // 15 // 15 // 0 /// AK093685 // GenBank // Homo sapiens cDNA FLJ36366 fis, clone THYMU2007824. // chr1 // 94 // 80 // 15 // 16 // 0 /// ENST00000513886 // ENSEMBL // cdna:known chromosome:GRCh37:16:61555:64090:1 gene:ENSG00000233614 // chr1 // 100 // 80 // 16 // 16 // 0 /// ENST00000456328 // ENSEMBL // cdna:known chromosome:GRCh37:1:11869:14409:1 gene:ENSG00000223972 // chr1 // 100 // 80 // 16 // 16 // 0 /// ENST00000518655 // ENSEMBL // cdna:known chromosome:GRCh37:1:11869:14409:1 gene:ENSG00000253101 // chr1 // 100 // 80 // 16 // 16 // 0', 'DQ786314 // GenBank // Homo sapiens clone HLS_IMAGE_811138 mRNA sequence. // chr1 // 100 // 38 // 3 // 3 // 0', '---', '---', 'DQ786265 // GenBank // Homo sapiens clone HLS_IMAGE_298685 mRNA sequence. // chr1 // 100 // 100 // 4 // 4 // 0'], 'category': ['main', 'main', '---', '---', 'main']}\n"
     ]
    }
   ],
   "source": [
    "# 1. Use the 'get_gene_annotation' function from the library to get gene annotation data from the SOFT file.\n",
    "gene_annotation = get_gene_annotation(soft_file)\n",
    "\n",
    "# 2. Use the 'preview_df' function from the library to preview the data and print out the results.\n",
    "print(\"Gene annotation preview:\")\n",
    "print(preview_df(gene_annotation))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c177d765",
   "metadata": {},
   "source": [
    "### Step 6: Gene Identifier Mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5c1a7a91",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2025-03-25T08:36:09.750910Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gene data index examples (first 5): ['2315554', '2315633', '2315674', '2315739', '2315894']\n",
      "Gene annotation ID examples (first 5): ['2315100', '2315106', '2315109', '2315111', '2315113']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of common IDs between gene data and mapping: 12033\n",
      "Total number of probes in mapping: 9390555\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of probes with gene mappings: 31980\n",
      "Number of probes in filtered mapping: 9084915\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of probes with gene mappings after filtering: 11962\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of gene expression data: (0, 754)\n",
      "Warning: Gene expression data is empty after mapping\n",
      "Gene expression data saved to: ../../output/preprocess/Cystic_Fibrosis/gene_data/GSE60690.csv\n"
     ]
    }
   ],
   "source": [
    "# 1. Determining the mapping between identifiers in the gene expression data and gene annotations\n",
    "# From the previous steps, we saw:\n",
    "# - Gene expression data has numeric identifiers in the 'ID' column (e.g., \"2315554\")\n",
    "# - Gene annotation data has matching IDs and gene information in the 'gene_assignment' column\n",
    "\n",
    "# First, let's check the structure of both datasets\n",
    "print(\"Gene data index examples (first 5):\", list(gene_data.index[:5]))\n",
    "print(\"Gene annotation ID examples (first 5):\", list(gene_annotation['ID'][:5]))\n",
    "\n",
    "# 2. Create mapping dataframe using the built-in function for extracting human gene symbols\n",
    "mapping_df = pd.DataFrame()\n",
    "mapping_df['ID'] = gene_annotation['ID']\n",
    "mapping_df['Gene'] = gene_annotation['gene_assignment'].apply(extract_human_gene_symbols)\n",
    "\n",
    "# Check for ID intersection between gene data and mapping\n",
    "gene_ids_in_data = set(gene_data.index)\n",
    "gene_ids_in_mapping = set(mapping_df['ID'])\n",
    "common_ids = gene_ids_in_data.intersection(gene_ids_in_mapping)\n",
    "print(f\"Number of common IDs between gene data and mapping: {len(common_ids)}\")\n",
    "\n",
    "# Print statistics to verify mapping looks reasonable\n",
    "print(f\"Total number of probes in mapping: {len(mapping_df)}\")\n",
    "print(f\"Number of probes with gene mappings: {mapping_df['Gene'].apply(len).gt(0).sum()}\")\n",
    "\n",
    "# Filter the mapping to only include IDs present in gene_data\n",
    "filtered_mapping = mapping_df[mapping_df['ID'].isin(gene_data.index)]\n",
    "print(f\"Number of probes in filtered mapping: {len(filtered_mapping)}\")\n",
    "print(f\"Number of probes with gene mappings after filtering: {filtered_mapping['Gene'].apply(len).gt(0).sum()}\")\n",
    "\n",
    "# 3. Apply gene mapping to convert probe-level measurements to gene expression using filtered mapping\n",
    "gene_data = apply_gene_mapping(gene_data, filtered_mapping)\n",
    "\n",
    "# Print the shape of the resulting gene expression data\n",
    "print(f\"Shape of gene expression data: {gene_data.shape}\")\n",
    "if not gene_data.empty:\n",
    "    print(\"First 5 gene symbols:\")\n",
    "    print(gene_data.index[:5])\n",
    "else:\n",
    "    print(\"Warning: Gene expression data is empty after mapping\")\n",
    "\n",
    "# Save the gene expression data\n",
    "gene_data.to_csv(out_gene_data_file)\n",
    "print(f\"Gene expression data saved to: {out_gene_data_file}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d326e643",
   "metadata": {},
   "source": [
    "### Step 7: Data Normalization and Linking"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5a865c8b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-25T08:36:09.752609Z",
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     "iopub.status.idle": "2025-03-25T08:36:09.826390Z",
     "shell.execute_reply": "2025-03-25T08:36:09.826014Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Normalized gene data shape: (0, 754)\n",
      "First few genes with their expression values after normalization:\n",
      "Empty DataFrame\n",
      "Columns: [GSM1485230, GSM1485231, GSM1485232, GSM1485233, GSM1485234, GSM1485235, GSM1485236, GSM1485237, GSM1485238, GSM1485239, GSM1485240, GSM1485241, GSM1485242, GSM1485243, GSM1485244, GSM1485245, GSM1485246, GSM1485247, GSM1485248, GSM1485249, GSM1485250, GSM1485251, GSM1485252, GSM1485253, GSM1485254, GSM1485255, GSM1485256, GSM1485257, GSM1485258, GSM1485259, GSM1485260, GSM1485261, GSM1485262, GSM1485263, GSM1485264, GSM1485265, GSM1485266, GSM1485267, GSM1485268, GSM1485269, GSM1485270, GSM1485271, GSM1485272, GSM1485273, GSM1485274, GSM1485275, GSM1485276, GSM1485277, GSM1485278, GSM1485279, GSM1485280, GSM1485281, GSM1485282, GSM1485283, GSM1485284, GSM1485285, GSM1485286, GSM1485287, GSM1485288, GSM1485289, GSM1485290, GSM1485291, GSM1485292, GSM1485293, GSM1485294, GSM1485295, GSM1485296, GSM1485297, GSM1485298, GSM1485299, GSM1485300, GSM1485301, GSM1485302, GSM1485303, GSM1485304, GSM1485305, GSM1485306, GSM1485307, GSM1485308, GSM1485309, GSM1485310, GSM1485311, GSM1485312, GSM1485313, GSM1485314, GSM1485315, GSM1485316, GSM1485317, GSM1485318, GSM1485319, GSM1485320, GSM1485321, GSM1485322, GSM1485323, GSM1485324, GSM1485325, GSM1485326, GSM1485327, GSM1485328, GSM1485329, ...]\n",
      "Index: []\n",
      "\n",
      "[0 rows x 754 columns]\n",
      "Normalized gene data saved to ../../output/preprocess/Cystic_Fibrosis/gene_data/GSE60690.csv\n",
      "Clinical data preview:\n",
      "{'0': [0.92156, 38.2, 1.0], '1': [-0.79274, 9.2, 0.0], '2': [2.33374, 22.5, nan], '3': [-1.36666, 14.4, nan], '4': [2.86073, 33.8, nan], '5': [1.08383, 18.6, nan], '6': [1.15792, 27.7, nan], '7': [1.516, 33.5, nan], '8': [-0.77528, 17.8, nan], '9': [-0.35251, 24.1, nan], '10': [0.95176, 16.4, nan], '11': [-0.78019, 8.7, nan], '12': [-0.45468, 10.4, nan], '13': [1.14497, 46.3, nan], '14': [-0.47971, 19.0, nan], '15': [0.08552, 17.1, nan], '16': [-0.74197, 10.2, nan], '17': [-1.29147, 16.7, nan], '18': [0.81747, 39.7, nan], '19': [1.52976, 39.3, nan], '20': [1.78443, 25.4, nan], '21': [0.8515, 41.2, nan], '22': [1.98295, 18.1, nan], '23': [0.86374, 21.5, nan], '24': [0.94161, 17.3, nan], '25': [1.10084, 32.4, nan], '26': [-0.5591, 19.8, nan], '27': [0.84926, 34.3, nan], '28': [0.86596, 25.3, nan], '29': [1.3764, 46.7, nan]}\n",
      "Linked data shape (before handling missing values): (784, 3)\n",
      "Data after handling missing values: (0, 2)\n",
      "Quartiles for 'Cystic_Fibrosis':\n",
      "  25%: nan\n",
      "  50% (Median): nan\n",
      "  75%: nan\n",
      "Min: nan\n",
      "Max: nan\n",
      "Quartiles for 'Age':\n",
      "  25%: nan\n",
      "  50% (Median): nan\n",
      "  75%: nan\n",
      "Min: nan\n",
      "Max: nan\n",
      "The distribution of the feature 'Age' in this dataset is fine.\n",
      "\n",
      "Abnormality detected in the cohort: GSE60690. Preprocessing failed.\n",
      "Data was determined to be unusable and was not saved\n"
     ]
    }
   ],
   "source": [
    "# 1. Normalize gene symbols in the gene expression data\n",
    "normalized_gene_data = normalize_gene_symbols_in_index(gene_data)\n",
    "print(f\"Normalized gene data shape: {normalized_gene_data.shape}\")\n",
    "print(\"First few genes with their expression values after normalization:\")\n",
    "print(normalized_gene_data.head())\n",
    "\n",
    "# Save the normalized gene data\n",
    "os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True)\n",
    "normalized_gene_data.to_csv(out_gene_data_file)\n",
    "print(f\"Normalized gene data saved to {out_gene_data_file}\")\n",
    "\n",
    "# 2. Link the clinical and genetic data\n",
    "# Use the clinical data that was already processed and saved in previous steps\n",
    "selected_clinical_df = pd.read_csv(out_clinical_data_file, index_col=0)\n",
    "print(\"Clinical data preview:\")\n",
    "print(preview_df(selected_clinical_df))\n",
    "\n",
    "# Link the clinical and genetic data\n",
    "linked_data = geo_link_clinical_genetic_data(selected_clinical_df, normalized_gene_data)\n",
    "print(f\"Linked data shape (before handling missing values): {linked_data.shape}\")\n",
    "\n",
    "# 3. Handle missing values in the linked data\n",
    "linked_data = handle_missing_values(linked_data, trait)\n",
    "print(f\"Data after handling missing values: {linked_data.shape}\")\n",
    "\n",
    "# 4. Determine whether the trait and demographic features are biased\n",
    "# First check if trait is biased\n",
    "trait_type = 'binary' if len(linked_data[trait].unique()) == 2 else 'continuous'\n",
    "if trait_type == \"binary\":\n",
    "    is_trait_biased = judge_binary_variable_biased(linked_data, trait)\n",
    "else:\n",
    "    is_trait_biased = judge_continuous_variable_biased(linked_data, trait)\n",
    "\n",
    "# Check for and remove biased demographic features\n",
    "unbiased_linked_data = linked_data.copy()\n",
    "if \"Age\" in unbiased_linked_data.columns:\n",
    "    age_biased = judge_continuous_variable_biased(unbiased_linked_data, 'Age')\n",
    "    if age_biased:\n",
    "        print(f\"The distribution of the feature \\'Age\\' in this dataset is severely biased.\\n\")\n",
    "        unbiased_linked_data = unbiased_linked_data.drop(columns='Age')\n",
    "    else:\n",
    "        print(f\"The distribution of the feature \\'Age\\' in this dataset is fine.\\n\")\n",
    "\n",
    "if \"Gender\" in unbiased_linked_data.columns:\n",
    "    gender_biased = judge_binary_variable_biased(unbiased_linked_data, 'Gender')\n",
    "    if gender_biased:\n",
    "        print(f\"The distribution of the feature \\'Gender\\' in this dataset is severely biased.\\n\")\n",
    "        unbiased_linked_data = unbiased_linked_data.drop(columns='Gender')\n",
    "    else:\n",
    "        print(f\"The distribution of the feature \\'Gender\\' in this dataset is fine.\\n\")\n",
    "\n",
    "# 5. Conduct final quality validation and save cohort information\n",
    "is_usable = validate_and_save_cohort_info(\n",
    "    is_final=True, \n",
    "    cohort=cohort, \n",
    "    info_path=json_path, \n",
    "    is_gene_available=True, \n",
    "    is_trait_available=True, \n",
    "    is_biased=is_trait_biased, \n",
    "    df=unbiased_linked_data,\n",
    "    note=f\"Dataset contains gene expression data comparing CFBE41o-ΔF508 (CF) cells with CFBE41o−CFTR (control) cells.\"\n",
    ")\n",
    "\n",
    "# 6. If the linked data is usable, save it\n",
    "if is_usable:\n",
    "    os.makedirs(os.path.dirname(out_data_file), exist_ok=True)\n",
    "    unbiased_linked_data.to_csv(out_data_file)\n",
    "    print(f\"Linked data saved to {out_data_file}\")\n",
    "else:\n",
    "    print(\"Data was determined to be unusable and was not saved\")"
   ]
  }
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