Example.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ec8ca799",
   "metadata": {},
   "outputs": [],
   "source": [
    "from HLAGuessr.processing import Processing\n",
    "from HLAGuessr.test_model import CrossValidation\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "09dacef7",
   "metadata": {},
   "outputs": [],
   "source": [
    "chain = ['alpha','beta']\n",
    "delimiter = '\\t'\n",
    "hla_threshold=1\n",
    "main_path = os.path.join(os.getcwd(),'HLAGuessr/')\n",
    "grouping = True\n",
    "untyped = False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "417c6145",
   "metadata": {},
   "source": [
    "#### Cross-validating classifier with typed dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "105f8cec",
   "metadata": {},
   "outputs": [],
   "source": [
    "alpha_input = main_path + 'Example_validation_data/alpha_all_files.tsv.gz'\n",
    "beta_input = main_path + 'Example_validation_data/beta_all_files.tsv.gz'\n",
    "hla_input = main_path + 'Example_validation_data/HLA_grouped_patients.tsv'\n",
    "hla_target = 'A*02:01'\n",
    "solver = 'liblinear'\n",
    "penalty = 'l1'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "12cb1f9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "dm = Processing(chain,alpha_input,beta_input,delimiter,grouping)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3288ddd5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "8it [00:00, 161.78it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n"
     ]
    }
   ],
   "source": [
    "cv = CrossValidation(hla_target,hla_input,chain,dm.ps,dm.data_test,grouping,hla_threshold,solver,penalty,untyped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c3727fc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>HLA</th>\n",
       "      <th>AUC</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>precision</th>\n",
       "      <th>sensitivity</th>\n",
       "      <th>specificity</th>\n",
       "      <th>chain</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A*02:01</td>\n",
       "      <td>0.982143</td>\n",
       "      <td>0.869565</td>\n",
       "      <td>0.772727</td>\n",
       "      <td>0.944444</td>\n",
       "      <td>0.821429</td>\n",
       "      <td>alpha+beta</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       HLA       AUC  accuracy  precision  sensitivity  specificity  \\\n",
       "0  A*02:01  0.982143  0.869565   0.772727     0.944444     0.821429   \n",
       "\n",
       "        chain  \n",
       "0  alpha+beta  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cv.df_summary"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c28c149a",
   "metadata": {},
   "source": [
    "#### Type individual from input repertoire"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f0bbede3",
   "metadata": {},
   "outputs": [],
   "source": [
    "from HLAGuessr.load_model import PreprocessedModel\n",
    "from HLAGuessr.evaluate_data import GetProbabilities\n",
    "import HLAGuessr.model_tools as mt\n",
    "import pandas as pd, numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6e9e41fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "alpha_input = main_path + 'Example_validation_data/alpha_example.tsv'\n",
    "beta_input = main_path + 'Example_validation_data/beta_example.tsv'\n",
    "grouping = False\n",
    "untyped = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3297992b",
   "metadata": {},
   "outputs": [],
   "source": [
    "dm = Processing(chain,alpha_input,beta_input,delimiter,grouping)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "62a4f3cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Get current working directory :  /home/ruiz/Scripts/HLA_Guessr_package\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "print('Get current working directory : ', os.getcwd())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "24d8ac6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "f_params = main_path + 'Training_data/classifier_params_alpha+beta.tsv'\n",
    "df_param = pd.read_csv(f_params,delimiter='\\t')\n",
    "hla_set = list(df_param['HLA'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "111cacf7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Individual 17_B:\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "A*01:01  -> Probability: 0.9999999999748646\t Final_classification: True\t AUC: 1.0\t Accuracy: 0.8536585365853658\t Precision: 0.625\t Sensitivity: 1.0\t Specificity: 0.8064516129032258\n"
     ]
    },
    {
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "A*02:01  -> Probability: 1.0\t Final_classification: True\t AUC: 0.9782608695652176\t Accuracy: 0.8536585365853658\t Precision: 0.7727272727272727\t Sensitivity: 0.9444444444444444\t Specificity: 0.782608695652174\n"
     ]
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    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "A*03:01  -> Probability: 0.9891907774409804\t Final_classification: True\t AUC: 0.9243697478991596\t Accuracy: 0.7073170731707317\t Precision: 0.3529411764705882\t Sensitivity: 0.8571428571428571\t Specificity: 0.6764705882352942\n"
     ]
    },
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "A*11:01  -> Probability: 0.2341610071533627\t Final_classification: False\t AUC: 0.9523809523809524\t Accuracy: 0.951219512195122\t Precision: 0.8333333333333334\t Sensitivity: 0.8333333333333334\t Specificity: 0.9714285714285714\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "A*23:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
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    {
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "A*24:02  -> Probability: 0.014058213350666725\t Final_classification: False\t AUC: 0.9915966386554622\t Accuracy: 0.975609756097561\t Precision: 1.0\t Sensitivity: 0.8571428571428571\t Specificity: 1.0\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "A*25:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "A*26:01  -> Probability: 0.3268626532197631\t Final_classification: False\t AUC: 0.9649122807017544\t Accuracy: 0.951219512195122\t Precision: 0.6\t Sensitivity: 1.0\t Specificity: 0.9473684210526316\n"
     ]
    },
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "A*29:02  -> Probability: 0.19519016295766342\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.926829268292683\t Precision: 0.5714285714285714\t Sensitivity: 1.0\t Specificity: 0.918918918918919\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "A*31:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
    {
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "A*32:01  -> Probability: 0.13239128384839147\t Final_classification: False\t AUC: 0.782051282051282\t Accuracy: 0.951219512195122\t Precision: 0.0\t Sensitivity: 0.0\t Specificity: 1.0\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "A*33:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "A*34:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "A*68:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "A*68:02  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "B*07:02  -> Probability: 0.9995801100068824\t Final_classification: True\t AUC: 1.0\t Accuracy: 0.926829268292683\t Precision: 0.7692307692307693\t Sensitivity: 1.0\t Specificity: 0.9032258064516128\n"
     ]
    },
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "B*08:01  -> Probability: 0.9999992885629184\t Final_classification: True\t AUC: 1.0\t Accuracy: 0.902439024390244\t Precision: 0.6\t Sensitivity: 1.0\t Specificity: 0.8857142857142857\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "B*14:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "B*14:02  -> Probability: 0.008947490282379322\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.975609756097561\t Precision: 0.5\t Sensitivity: 1.0\t Specificity: 0.975\n"
     ]
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "B*15:01  -> Probability: 0.0027561519527220897\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.902439024390244\t Precision: 0.2\t Sensitivity: 1.0\t Specificity: 0.9\n"
     ]
    },
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      "0it [00:00, ?it/s]                                        | 0/1 [00:00<?, ?it/s]\n",
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "B*18:01  -> Probability: 0.0015901743623864188\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.8780487804878049\t Precision: 0.2857142857142857\t Sensitivity: 1.0\t Specificity: 0.8717948717948718\n"
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      "0it [00:00, ?it/s]                                        | 0/1 [00:00<?, ?it/s]\n",
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "B*27:05  -> Probability: 0.008186549869561445\t Final_classification: False\t AUC: 0.9871794871794872\t Accuracy: 0.951219512195122\t Precision: 0.5\t Sensitivity: 1.0\t Specificity: 0.9487179487179488\n"
     ]
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "B*35:01  -> Probability: 0.02103262671727841\t Final_classification: False\t AUC: 1.0\t Accuracy: 1.0\t Precision: 1.0\t Sensitivity: 1.0\t Specificity: 1.0\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "B*35:02  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
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      "8it [00:00, 231.55it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "B*35:03  -> Probability: 0.5006660011173608\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.926829268292683\t Precision: 0.4\t Sensitivity: 1.0\t Specificity: 0.9230769230769232\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "B*37:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "B*38:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "B*39:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
    {
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "B*40:01  -> Probability: 0.002887786138990285\t Final_classification: False\t AUC: 0.9871794871794872\t Accuracy: 0.902439024390244\t Precision: 0.3333333333333333\t Sensitivity: 1.0\t Specificity: 0.8974358974358975\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "B*40:02  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
    {
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     "output_type": "stream",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "B*44:02  -> Probability: 0.015143399844745335\t Final_classification: False\t AUC: 0.9722222222222222\t Accuracy: 0.902439024390244\t Precision: 0.5714285714285714\t Sensitivity: 0.8\t Specificity: 0.9166666666666666\n"
     ]
    },
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "B*44:03  -> Probability: 0.0013840741489607163\t Final_classification: False\t AUC: 0.9789915966386554\t Accuracy: 0.8780487804878049\t Precision: 0.5833333333333334\t Sensitivity: 1.0\t Specificity: 0.8529411764705882\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "B*49:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "B*50:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "B*51:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "B*52:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "B*55:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "B*58:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "C*02:02  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "C*03:03  -> Probability: 0.6992614888592706\t Final_classification: False\t AUC: 0.6730769230769231\t Accuracy: 0.8780487804878049\t Precision: 0.2\t Sensitivity: 0.5\t Specificity: 0.8974358974358975\n"
     ]
    },
    {
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     "output_type": "stream",
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      "0it [00:00, ?it/s]                                        | 0/1 [00:00<?, ?it/s]\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "C*03:04  -> Probability: 0.27985189515024284\t Final_classification: False\t AUC: 0.8445945945945946\t Accuracy: 0.951219512195122\t Precision: 0.75\t Sensitivity: 0.75\t Specificity: 0.972972972972973\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "C*04:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "C*05:01  -> Probability: 0.25870298822831855\t Final_classification: False\t AUC: 0.8857142857142858\t Accuracy: 0.8780487804878049\t Precision: 0.5714285714285714\t Sensitivity: 0.6666666666666666\t Specificity: 0.9142857142857144\n"
     ]
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "C*06:02  -> Probability: 0.5948735418659703\t Final_classification: False\t AUC: 0.9189189189189187\t Accuracy: 0.7804878048780488\t Precision: 0.3076923076923077\t Sensitivity: 1.0\t Specificity: 0.7567567567567568\n"
     ]
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    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "C*07:01  -> Probability: 0.9999968314903769\t Final_classification: True\t AUC: 0.8903225806451613\t Accuracy: 0.926829268292683\t Precision: 0.8888888888888888\t Sensitivity: 0.8\t Specificity: 0.967741935483871\n"
     ]
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "C*07:02  -> Probability: 0.9988221157471511\t Final_classification: True\t AUC: 0.971264367816092\t Accuracy: 0.8780487804878049\t Precision: 0.7333333333333333\t Sensitivity: 0.9166666666666666\t Specificity: 0.8620689655172413\n"
     ]
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    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "C*08:02  -> Probability: 0.029286612246643886\t Final_classification: False\t AUC: 0.6025641025641026\t Accuracy: 0.902439024390244\t Precision: 0.25\t Sensitivity: 0.5\t Specificity: 0.9230769230769232\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "C*12:02  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "C*12:03  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "C*14:02  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "C*15:05  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "C*16:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "C*17:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DPB1*01:01  -> Probability: 0.5344026391374381\t Final_classification: False\t AUC: 0.8513513513513513\t Accuracy: 0.8536585365853658\t Precision: 0.375\t Sensitivity: 0.75\t Specificity: 0.8648648648648649\n"
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DPB1*02:01  -> Probability: 0.7282784688667312\t Final_classification: False\t AUC: 0.8880952380952382\t Accuracy: 0.8048780487804879\t Precision: 0.4166666666666667\t Sensitivity: 0.8333333333333334\t Specificity: 0.8\n"
     ]
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DPB1*03:01  -> Probability: 0.12221941380982636\t Final_classification: False\t AUC: 0.9797297297297298\t Accuracy: 0.8780487804878049\t Precision: 0.4444444444444444\t Sensitivity: 1.0\t Specificity: 0.8648648648648649\n"
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    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DPB1*04:01  -> Probability: 0.7837606548187512\t Final_classification: False\t AUC: 0.9047619047619048\t Accuracy: 0.8048780487804879\t Precision: 0.7878787878787878\t Sensitivity: 0.9629629629629628\t Specificity: 0.5\n"
     ]
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      "8it [00:00, 190.84it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DPB1*04:02  -> Probability: 0.9999999999988549\t Final_classification: True\t AUC: 0.9761904761904762\t Accuracy: 0.8780487804878049\t Precision: 0.5454545454545454\t Sensitivity: 1.0\t Specificity: 0.8571428571428571\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DPB1*05:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DPB1*10:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DPB1*11:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DPB1*13:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DPB1*17:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQA1*01:01  -> Probability: 0.18831012418692517\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.975609756097561\t Precision: 0.875\t Sensitivity: 1.0\t Specificity: 0.9705882352941176\n"
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQA1*01:02  -> Probability: 0.9999998410025905\t Final_classification: True\t AUC: 0.8229665071770336\t Accuracy: 0.8048780487804879\t Precision: 0.7894736842105263\t Sensitivity: 0.7894736842105263\t Specificity: 0.8181818181818182\n"
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQA1*01:03  -> Probability: 0.5789549179935611\t Final_classification: False\t AUC: 0.938095238095238\t Accuracy: 0.8292682926829268\t Precision: 0.4545454545454545\t Sensitivity: 0.8333333333333334\t Specificity: 0.8285714285714286\n"
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      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQA1*01:04  -> Probability: 0.05508202157349685\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.8536585365853658\t Precision: 0.4\t Sensitivity: 1.0\t Specificity: 0.8378378378378378\n"
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      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQA1*02:01  -> Probability: 0.0972555679345423\t Final_classification: False\t AUC: 0.9942528735632185\t Accuracy: 0.975609756097561\t Precision: 1.0\t Sensitivity: 0.9166666666666666\t Specificity: 1.0\n"
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQA1*03:01  -> Probability: 0.17034357762613805\t Final_classification: False\t AUC: 0.9615384615384616\t Accuracy: 0.8536585365853658\t Precision: 0.25\t Sensitivity: 1.0\t Specificity: 0.8461538461538461\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DQA1*03:02  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
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      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQA1*03:03  -> Probability: 0.4521373468731726\t Final_classification: False\t AUC: 0.9428571428571428\t Accuracy: 0.926829268292683\t Precision: 0.8\t Sensitivity: 0.6666666666666666\t Specificity: 0.9714285714285714\n"
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      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQA1*04:01  -> Probability: 0.3944047455063324\t Final_classification: False\t AUC: 0.8076923076923077\t Accuracy: 0.8780487804878049\t Precision: 0.2\t Sensitivity: 0.5\t Specificity: 0.8974358974358975\n"
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      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQA1*05:01  -> Probability: 0.9999999987254615\t Final_classification: True\t AUC: 1.0\t Accuracy: 0.975609756097561\t Precision: 0.9\t Sensitivity: 1.0\t Specificity: 0.96875\n"
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      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQA1*05:05  -> Probability: 0.3535555588071145\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.926829268292683\t Precision: 0.7272727272727273\t Sensitivity: 1.0\t Specificity: 0.9090909090909092\n"
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      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQB1*02:01  -> Probability: 0.9999999977419387\t Final_classification: True\t AUC: 1.0\t Accuracy: 0.975609756097561\t Precision: 0.9090909090909092\t Sensitivity: 1.0\t Specificity: 0.967741935483871\n"
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQB1*02:02  -> Probability: 0.30349152671906526\t Final_classification: False\t AUC: 0.8958333333333334\t Accuracy: 0.8780487804878049\t Precision: 0.6666666666666666\t Sensitivity: 0.8888888888888888\t Specificity: 0.875\n"
     ]
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQB1*03:01  -> Probability: 0.35808218343947773\t Final_classification: False\t AUC: 0.9285714285714286\t Accuracy: 0.902439024390244\t Precision: 0.9090909090909092\t Sensitivity: 0.7692307692307693\t Specificity: 0.9642857142857144\n"
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     ]
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    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQB1*03:02  -> Probability: 0.18399086786770377\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.926829268292683\t Precision: 0.4\t Sensitivity: 1.0\t Specificity: 0.9230769230769232\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DQB1*03:03  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DQB1*03:19  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DQB1*04:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQB1*04:02  -> Probability: 0.956333970750438\t Final_classification: True\t AUC: 1.0\t Accuracy: 0.926829268292683\t Precision: 0.25\t Sensitivity: 1.0\t Specificity: 0.925\n"
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    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQB1*05:01  -> Probability: 0.04184133319824278\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.951219512195122\t Precision: 0.8\t Sensitivity: 1.0\t Specificity: 0.9393939393939394\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DQB1*05:02  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQB1*05:03  -> Probability: 0.17984453581626225\t Final_classification: False\t AUC: 0.9932432432432432\t Accuracy: 0.8292682926829268\t Precision: 0.3636363636363636\t Sensitivity: 1.0\t Specificity: 0.8108108108108109\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DQB1*06:01  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQB1*06:02  -> Probability: 0.999972300893212\t Final_classification: True\t AUC: 0.9962121212121212\t Accuracy: 0.902439024390244\t Precision: 0.6666666666666666\t Sensitivity: 1.0\t Specificity: 0.8787878787878788\n"
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQB1*06:03  -> Probability: 0.0006816953867110594\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.951219512195122\t Precision: 0.7142857142857143\t Sensitivity: 1.0\t Specificity: 0.9444444444444444\n"
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      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DQB1*06:04  -> Probability: 0.342253521451809\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.975609756097561\t Precision: 0.75\t Sensitivity: 1.0\t Specificity: 0.9736842105263158\n"
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*01:01  -> Probability: 0.05971218461088541\t Final_classification: False\t AUC: 0.9611111111111112\t Accuracy: 0.926829268292683\t Precision: 0.6666666666666666\t Sensitivity: 0.8\t Specificity: 0.9444444444444444\n"
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*01:02  -> Probability: 0.09796550704382342\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.8780487804878049\t Precision: 0.1666666666666666\t Sensitivity: 1.0\t Specificity: 0.875\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DRB1*01:03  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*03:01  -> Probability: 0.9999729561659205\t Final_classification: True\t AUC: 1.0\t Accuracy: 1.0\t Precision: 1.0\t Sensitivity: 1.0\t Specificity: 1.0\n"
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*04:01  -> Probability: 0.01717160906872059\t Final_classification: False\t AUC: 0.9594594594594594\t Accuracy: 0.7317073170731707\t Precision: 0.2666666666666666\t Sensitivity: 1.0\t Specificity: 0.7027027027027027\n"
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    {
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*04:04  -> Probability: 0.09661568443817929\t Final_classification: False\t AUC: 0.975\t Accuracy: 0.975609756097561\t Precision: 0.5\t Sensitivity: 1.0\t Specificity: 0.975\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DRB1*04:05  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DRB1*04:08  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
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      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*07:01  -> Probability: 0.22888074685208676\t Final_classification: False\t AUC: 1.0\t Accuracy: 1.0\t Precision: 1.0\t Sensitivity: 1.0\t Specificity: 1.0\n"
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      "8it [00:00, 189.25it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*08:01  -> Probability: 0.0004654398533308719\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.951219512195122\t Precision: 0.3333333333333333\t Sensitivity: 1.0\t Specificity: 0.95\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DRB1*08:03  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DRB1*08:04  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*09:01  -> Probability: 0.012389280108584816\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.8780487804878049\t Precision: 0.1666666666666666\t Sensitivity: 1.0\t Specificity: 0.875\n"
     ]
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*11:01  -> Probability: 0.19294280746650078\t Final_classification: False\t AUC: 0.9054054054054054\t Accuracy: 0.8048780487804879\t Precision: 0.3\t Sensitivity: 0.75\t Specificity: 0.8108108108108109\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DRB1*11:04  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
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    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*13:01  -> Probability: 0.0008213434848990421\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.8780487804878049\t Precision: 0.5\t Sensitivity: 1.0\t Specificity: 0.8611111111111112\n"
     ]
    },
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*13:02  -> Probability: 0.28116263597726554\t Final_classification: False\t AUC: 1.0\t Accuracy: 0.975609756097561\t Precision: 0.8\t Sensitivity: 1.0\t Specificity: 0.972972972972973\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DRB1*13:03  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    },
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    {
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*14:01  -> Probability: 0.0010006538200200872\t Final_classification: False\t AUC: 1.0\t Accuracy: 1.0\t Precision: 1.0\t Sensitivity: 1.0\t Specificity: 1.0\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DRB1*14:04  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
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    {
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     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*15:01  -> Probability: 0.9999999916553978\t Final_classification: True\t AUC: 1.0\t Accuracy: 0.902439024390244\t Precision: 0.7142857142857143\t Sensitivity: 1.0\t Specificity: 0.8709677419354839\n"
     ]
    },
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     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*15:02  -> Probability: 0.10579390089188373\t Final_classification: False\t AUC: 0.9560810810810813\t Accuracy: 0.926829268292683\t Precision: 0.6\t Sensitivity: 0.75\t Specificity: 0.945945945945946\n"
     ]
    },
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      "0it [00:00, ?it/s]                                        | 0/1 [00:00<?, ?it/s]\n",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 53 candidates, totalling 265 fits\n",
      "DRB1*16:01  -> Probability: 0.20756774947248444\t Final_classification: False\t AUC: 0.9912280701754388\t Accuracy: 0.975609756097561\t Precision: 0.75\t Sensitivity: 1.0\t Specificity: 0.9736842105263158\n",
      "No HLA-related TCRs have been found in your repertoire\n",
      "DRB1*16:02  -> Probability: N/A\t Final_classification: False\t AUC: 0.5\t Accuracy: 1\t Precision: 0\t Sensitivity: 0\t Specificity: 1\n"
     ]
    }
   ],
   "source": [
    "df_final_params = pd.DataFrame()\n",
    "    \n",
    "for p in np.unique(np.array(dm.ps), axis=0):\n",
    "            \n",
    "    print('Individual ' +p[0]+ ':')\n",
    "\n",
    "    for hla_target in hla_set:\n",
    "                \n",
    "        ev = GetProbabilities(hla_target,chain,hla_threshold,dm.ps,dm.data_test,grouping,untyped)\n",
    "        params = ev.classifier_params(df_param,hla_target)\n",
    "        df = mt.print_params(hla_target,ev.hla_prob,params,p[0],ev.hla_output)\n",
    "        df_final_params = pd.concat([df,df_final_params],ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe8ceb5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "17_B\tDQB1*02:01\talpha+beta\n",
    "17_B\tDQB1*06:02\talpha+beta\n",
    "17_B\tDQA1*01:02\talpha+beta\n",
    "17_B\tDQA1*05:01\talpha+beta\n",
    "17_B\tA*01:01\talpha+beta\n",
    "17_B\tA*02:01\talpha+beta\n",
    "17_B\tB*07:02\talpha+beta\n",
    "17_B\tB*08:01\talpha+beta\n",
    "17_B\tC*07:01\talpha+beta\n",
    "17_B\tC*07:02\talpha+beta\n",
    "17_B\tDPB1*04:02\talpha+beta\n",
    "17_B\tDPB1*04:02\talpha+beta\n",
    "17_B\tDRB1*03:01\talpha+beta\n",
    "17_B\tDRB1*15:01\talpha+beta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "83c2bd24",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>HLA</th>\n",
       "      <th>Probability</th>\n",
       "      <th>Final_classification</th>\n",
       "      <th>AUC</th>\n",
       "      <th>Accuracy</th>\n",
       "      <th>Precision</th>\n",
       "      <th>Sensitivity</th>\n",
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       "      <th>3</th>\n",
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       "      <th>26</th>\n",
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       "      <td>True</td>\n",
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       "      <td>0.902439</td>\n",
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       "      <th>38</th>\n",
       "      <td>DQB1*02:01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.97561</td>\n",
       "      <td>0.909091</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.967742</td>\n",
       "      <td>17_B</td>\n",
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       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>DQA1*05:01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.97561</td>\n",
       "      <td>0.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.96875</td>\n",
       "      <td>17_B</td>\n",
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       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>DQA1*01:02</td>\n",
       "      <td>0.999995</td>\n",
       "      <td>True</td>\n",
       "      <td>0.822967</td>\n",
       "      <td>0.804878</td>\n",
       "      <td>0.789474</td>\n",
       "      <td>0.789474</td>\n",
       "      <td>0.818182</td>\n",
       "      <td>17_B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>DPB1*04:02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>True</td>\n",
       "      <td>0.97619</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.545455</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>17_B</td>\n",
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       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>DPB1*04:01</td>\n",
       "      <td>0.986079</td>\n",
       "      <td>True</td>\n",
       "      <td>0.904762</td>\n",
       "      <td>0.804878</td>\n",
       "      <td>0.787879</td>\n",
       "      <td>0.962963</td>\n",
       "      <td>0.5</td>\n",
       "      <td>17_B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>C*07:02</td>\n",
       "      <td>0.999548</td>\n",
       "      <td>True</td>\n",
       "      <td>0.971264</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.733333</td>\n",
       "      <td>0.916667</td>\n",
       "      <td>0.862069</td>\n",
       "      <td>17_B</td>\n",
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       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>C*07:01</td>\n",
       "      <td>0.999996</td>\n",
       "      <td>True</td>\n",
       "      <td>0.890323</td>\n",
       "      <td>0.926829</td>\n",
       "      <td>0.888889</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.967742</td>\n",
       "      <td>17_B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>B*08:01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.902439</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.885714</td>\n",
       "      <td>17_B</td>\n",
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       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>B*07:02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.926829</td>\n",
       "      <td>0.769231</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.903226</td>\n",
       "      <td>17_B</td>\n",
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       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>A*03:01</td>\n",
       "      <td>0.990296</td>\n",
       "      <td>True</td>\n",
       "      <td>0.92437</td>\n",
       "      <td>0.707317</td>\n",
       "      <td>0.352941</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>0.676471</td>\n",
       "      <td>17_B</td>\n",
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       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>A*02:01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>True</td>\n",
       "      <td>0.978261</td>\n",
       "      <td>0.853659</td>\n",
       "      <td>0.772727</td>\n",
       "      <td>0.944444</td>\n",
       "      <td>0.782609</td>\n",
       "      <td>17_B</td>\n",
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       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>A*01:01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.853659</td>\n",
       "      <td>0.625</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.806452</td>\n",
       "      <td>17_B</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            HLA Probability  Final_classification       AUC  Accuracy  \\\n",
       "3    DRB1*15:01         1.0                  True       1.0  0.902439   \n",
       "20   DRB1*03:01    0.999969                  True       1.0       1.0   \n",
       "26   DQB1*06:02    0.999964                  True  0.996212  0.902439   \n",
       "38   DQB1*02:01         1.0                  True       1.0   0.97561   \n",
       "40   DQA1*05:01         1.0                  True       1.0   0.97561   \n",
       "48   DQA1*01:02    0.999995                  True  0.822967  0.804878   \n",
       "55   DPB1*04:02         1.0                  True   0.97619  0.878049   \n",
       "56   DPB1*04:01    0.986079                  True  0.904762  0.804878   \n",
       "67      C*07:02    0.999548                  True  0.971264  0.878049   \n",
       "68      C*07:01    0.999996                  True  0.890323  0.926829   \n",
       "96      B*08:01         1.0                  True       1.0  0.902439   \n",
       "97      B*07:02         1.0                  True       1.0  0.926829   \n",
       "110     A*03:01    0.990296                  True   0.92437  0.707317   \n",
       "111     A*02:01         1.0                  True  0.978261  0.853659   \n",
       "112     A*01:01         1.0                  True       1.0  0.853659   \n",
       "\n",
       "    Precision Sensitivity Specificity Individual_ID  \n",
       "3    0.714286         1.0    0.870968          17_B  \n",
       "20        1.0         1.0         1.0          17_B  \n",
       "26   0.666667         1.0    0.878788          17_B  \n",
       "38   0.909091         1.0    0.967742          17_B  \n",
       "40        0.9         1.0     0.96875          17_B  \n",
       "48   0.789474    0.789474    0.818182          17_B  \n",
       "55   0.545455         1.0    0.857143          17_B  \n",
       "56   0.787879    0.962963         0.5          17_B  \n",
       "67   0.733333    0.916667    0.862069          17_B  \n",
       "68   0.888889         0.8    0.967742          17_B  \n",
       "96        0.6         1.0    0.885714          17_B  \n",
       "97   0.769231         1.0    0.903226          17_B  \n",
       "110  0.352941    0.857143    0.676471          17_B  \n",
       "111  0.772727    0.944444    0.782609          17_B  \n",
       "112     0.625         1.0    0.806452          17_B  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final_params[df_final_params['Final_classification']==True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "88df5da6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final_params.to_csv('/home/ruiz/example_patient_results.tsv',sep='\\t',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a2f85af3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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