06_snp_bayesian_networks_power_FFM1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <p style=\"text-align: justify;\"><div class=\"alert alert-info\" role=\"alert\">Bayesian networks: tabu algorithm</div></p>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `Ana González Guerra` \n",
    "\n",
    "### ` Student of the master in Data Science at the University of Cantabria` "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Index<a class=\"anchor\" id=\"index\"></a>\n",
    "* [Loading data](#1)\n",
    "    * [Genetic predictors](#3)\n",
    "    * [Target variables](#4)\n",
    "* [Construction of the Bayesian network using the tabu algorithm](#2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook we will build a Bayesian network with the genetic variables as predictors and with the variable W1.2MedDifWRelFFM1 as the target variable (it was the variable with the best accuracy in Random Forest and probably the one that best summarizes the information of the performance in physical exercise)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading data <a class=\"anchor\" id=\"1\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* [Returning to the index of contents](#index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Genetic predictors <a class=\"anchor\" id=\"3\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* [Returning to the index of contents](#index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>rs10034661</th><th scope=col>rs10063949</th><th scope=col>rs1024610</th><th scope=col>rs1024611</th><th scope=col>rs1042713</th><th scope=col>rs1045485</th><th scope=col>rs10491003</th><th scope=col>rs1049305</th><th scope=col>rs1049434</th><th scope=col>rs10497520</th><th scope=col>...</th><th scope=col>rs8111989</th><th scope=col>rs8192678</th><th scope=col>rs824205</th><th scope=col>rs833070</th><th scope=col>rs884736</th><th scope=col>rs921943</th><th scope=col>rs9469199</th><th scope=col>rs970547</th><th scope=col>rs9902453</th><th scope=col>rs9939609</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>G:G</td><td>C:T</td><td>A:T</td><td>T:T</td><td>A:A</td><td>C:G</td><td>G:G</td><td>C:G</td><td>A:T</td><td>C:T</td><td>...</td><td>C:T</td><td>A:G</td><td>G:G</td><td>A:G</td><td>C:T</td><td>A:G</td><td>A:G</td><td>A:A</td><td>A:G</td><td>A:A</td></tr>\n",
       "\t<tr><td>G:G</td><td>C:T</td><td>A:T</td><td>C:T</td><td>A:G</td><td>G:G</td><td>G:G</td><td>G:G</td><td>A:A</td><td>C:C</td><td>...</td><td>C:T</td><td>A:G</td><td>A:G</td><td>A:G</td><td>C:T</td><td>A:G</td><td>G:G</td><td>A:G</td><td>A:G</td><td>T:T</td></tr>\n",
       "\t<tr><td>G:G</td><td>T:T</td><td>A:T</td><td>T:T</td><td>A:G</td><td>G:G</td><td>G:G</td><td>C:G</td><td>A:A</td><td>C:C</td><td>...</td><td>C:T</td><td>A:G</td><td>G:G</td><td>A:G</td><td>C:T</td><td>A:A</td><td>G:G</td><td>A:G</td><td>A:G</td><td>A:A</td></tr>\n",
       "\t<tr><td>G:G</td><td>T:T</td><td>T:T</td><td>C:T</td><td>A:G</td><td>G:G</td><td>G:G</td><td>C:C</td><td>A:T</td><td>C:C</td><td>...</td><td>C:T</td><td>A:G</td><td>G:G</td><td>A:G</td><td>C:T</td><td>A:G</td><td>G:G</td><td>A:A</td><td>A:A</td><td>A:A</td></tr>\n",
       "\t<tr><td>G:G</td><td>C:T</td><td>T:T</td><td>C:T</td><td>G:G</td><td>C:C</td><td>G:G</td><td>C:G</td><td>T:T</td><td>C:C</td><td>...</td><td>C:T</td><td>A:G</td><td>G:G</td><td>G:G</td><td>T:T</td><td>G:G</td><td>G:G</td><td>A:A</td><td>A:G</td><td>A:T</td></tr>\n",
       "\t<tr><td>G:G</td><td>C:T</td><td>T:T</td><td>C:T</td><td>A:G</td><td>G:G</td><td>G:G</td><td>C:G</td><td>A:T</td><td>C:C</td><td>...</td><td>C:T</td><td>A:G</td><td>G:G</td><td>G:G</td><td>C:T</td><td>A:G</td><td>G:G</td><td>A:G</td><td>G:G</td><td>T:T</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll}\n",
       " rs10034661 & rs10063949 & rs1024610 & rs1024611 & rs1042713 & rs1045485 & rs10491003 & rs1049305 & rs1049434 & rs10497520 & ... & rs8111989 & rs8192678 & rs824205 & rs833070 & rs884736 & rs921943 & rs9469199 & rs970547 & rs9902453 & rs9939609\\\\\n",
       "\\hline\n",
       "\t G:G & C:T & A:T & T:T & A:A & C:G & G:G & C:G & A:T & C:T & ... & C:T & A:G & G:G & A:G & C:T & A:G & A:G & A:A & A:G & A:A\\\\\n",
       "\t G:G & C:T & A:T & C:T & A:G & G:G & G:G & G:G & A:A & C:C & ... & C:T & A:G & A:G & A:G & C:T & A:G & G:G & A:G & A:G & T:T\\\\\n",
       "\t G:G & T:T & A:T & T:T & A:G & G:G & G:G & C:G & A:A & C:C & ... & C:T & A:G & G:G & A:G & C:T & A:A & G:G & A:G & A:G & A:A\\\\\n",
       "\t G:G & T:T & T:T & C:T & A:G & G:G & G:G & C:C & A:T & C:C & ... & C:T & A:G & G:G & A:G & C:T & A:G & G:G & A:A & A:A & A:A\\\\\n",
       "\t G:G & C:T & T:T & C:T & G:G & C:C & G:G & C:G & T:T & C:C & ... & C:T & A:G & G:G & G:G & T:T & G:G & G:G & A:A & A:G & A:T\\\\\n",
       "\t G:G & C:T & T:T & C:T & A:G & G:G & G:G & C:G & A:T & C:C & ... & C:T & A:G & G:G & G:G & C:T & A:G & G:G & A:G & G:G & T:T\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| rs10034661 | rs10063949 | rs1024610 | rs1024611 | rs1042713 | rs1045485 | rs10491003 | rs1049305 | rs1049434 | rs10497520 | ... | rs8111989 | rs8192678 | rs824205 | rs833070 | rs884736 | rs921943 | rs9469199 | rs970547 | rs9902453 | rs9939609 |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| G:G | C:T | A:T | T:T | A:A | C:G | G:G | C:G | A:T | C:T | ... | C:T | A:G | G:G | A:G | C:T | A:G | A:G | A:A | A:G | A:A |\n",
       "| G:G | C:T | A:T | C:T | A:G | G:G | G:G | G:G | A:A | C:C | ... | C:T | A:G | A:G | A:G | C:T | A:G | G:G | A:G | A:G | T:T |\n",
       "| G:G | T:T | A:T | T:T | A:G | G:G | G:G | C:G | A:A | C:C | ... | C:T | A:G | G:G | A:G | C:T | A:A | G:G | A:G | A:G | A:A |\n",
       "| G:G | T:T | T:T | C:T | A:G | G:G | G:G | C:C | A:T | C:C | ... | C:T | A:G | G:G | A:G | C:T | A:G | G:G | A:A | A:A | A:A |\n",
       "| G:G | C:T | T:T | C:T | G:G | C:C | G:G | C:G | T:T | C:C | ... | C:T | A:G | G:G | G:G | T:T | G:G | G:G | A:A | A:G | A:T |\n",
       "| G:G | C:T | T:T | C:T | A:G | G:G | G:G | C:G | A:T | C:C | ... | C:T | A:G | G:G | G:G | C:T | A:G | G:G | A:G | G:G | T:T |\n",
       "\n"
      ],
      "text/plain": [
       "  rs10034661 rs10063949 rs1024610 rs1024611 rs1042713 rs1045485 rs10491003\n",
       "1 G:G        C:T        A:T       T:T       A:A       C:G       G:G       \n",
       "2 G:G        C:T        A:T       C:T       A:G       G:G       G:G       \n",
       "3 G:G        T:T        A:T       T:T       A:G       G:G       G:G       \n",
       "4 G:G        T:T        T:T       C:T       A:G       G:G       G:G       \n",
       "5 G:G        C:T        T:T       C:T       G:G       C:C       G:G       \n",
       "6 G:G        C:T        T:T       C:T       A:G       G:G       G:G       \n",
       "  rs1049305 rs1049434 rs10497520 ... rs8111989 rs8192678 rs824205 rs833070\n",
       "1 C:G       A:T       C:T        ... C:T       A:G       G:G      A:G     \n",
       "2 G:G       A:A       C:C        ... C:T       A:G       A:G      A:G     \n",
       "3 C:G       A:A       C:C        ... C:T       A:G       G:G      A:G     \n",
       "4 C:C       A:T       C:C        ... C:T       A:G       G:G      A:G     \n",
       "5 C:G       T:T       C:C        ... C:T       A:G       G:G      G:G     \n",
       "6 C:G       A:T       C:C        ... C:T       A:G       G:G      G:G     \n",
       "  rs884736 rs921943 rs9469199 rs970547 rs9902453 rs9939609\n",
       "1 C:T      A:G      A:G       A:A      A:G       A:A      \n",
       "2 C:T      A:G      G:G       A:G      A:G       T:T      \n",
       "3 C:T      A:A      G:G       A:G      A:G       A:A      \n",
       "4 C:T      A:G      G:G       A:A      A:A       A:A      \n",
       "5 T:T      G:G      G:G       A:A      A:G       A:T      \n",
       "6 C:T      A:G      G:G       A:G      G:G       T:T      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "handle_genetic <- read.csv('handle_genetic_fusion_28_04_20.csv')\n",
    "head(handle_genetic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Target variables <a class=\"anchor\" id=\"4\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* [Returning to the index of contents](#index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>W1MaxWAbs</th><th scope=col>W1MaxWRel</th><th scope=col>W1maxRPM</th><th scope=col>W1MedWAbs</th><th scope=col>W1MedWRel</th><th scope=col>W1medRPM</th><th scope=col>W2MaxWAbs</th><th scope=col>W2MaxWRel</th><th scope=col>W2maxRPM</th><th scope=col>W2MedWAbs</th><th scope=col>...</th><th scope=col>W2DifWRelFFM1</th><th scope=col>W2DifWRelFFM2</th><th scope=col>W1.2MaxDifWAbs</th><th scope=col>W1.2MaxDifWRel</th><th scope=col>W1.2MaxDifWRelFFM1</th><th scope=col>W1.2MaxDifWRelFFM2</th><th scope=col>W1.2MedDifWAbs</th><th scope=col>W1.2MedDifWRel</th><th scope=col>W1.2MedDifWRelFFM1</th><th scope=col>W1.2MedDifWRelFFM2</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>0</th><td>398        </td><td> 8.747253  </td><td>122        </td><td>206        </td><td>4.527473   </td><td>100        </td><td>397        </td><td>8.725275   </td><td>122        </td><td>224        </td><td>...        </td><td> 4.479981  </td><td> 4.544592  </td><td>  1        </td><td> 0.02197802</td><td> 0.02589585</td><td> 0.02626932</td><td>-18        </td><td>-0.39560440</td><td>-0.46612522</td><td>-0.47284774</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>511        </td><td> 8.964912  </td><td>128        </td><td>294        </td><td>5.157895   </td><td>109        </td><td>523        </td><td>9.175439   </td><td>122        </td><td>295        </td><td>...        </td><td> 4.552187  </td><td> 4.889881  </td><td>-12        </td><td>-0.21052632</td><td>-0.23958880</td><td>-0.25736216</td><td> -1        </td><td>-0.01754386</td><td>-0.01996573</td><td>-0.02144685</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>524        </td><td>10.174757  </td><td>130        </td><td>262        </td><td>5.087379   </td><td>107        </td><td>476        </td><td>9.242718   </td><td>125        </td><td>245        </td><td>...        </td><td> 4.958966  </td><td> 5.566747  </td><td> 48        </td><td> 0.93203883</td><td> 1.03043453</td><td> 1.15672661</td><td> 17        </td><td> 0.33009709</td><td> 0.36494556</td><td> 0.40967401</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>541        </td><td> 8.868852  </td><td>128        </td><td>351        </td><td>5.754098   </td><td>118        </td><td>472        </td><td>7.737705   </td><td>130        </td><td>333        </td><td>...        </td><td> 2.792441  </td><td> 3.020719  </td><td> 69        </td><td> 1.13114754</td><td> 1.38617564</td><td> 1.49949379</td><td> 18        </td><td> 0.29508197</td><td> 0.36161104</td><td> 0.39117229</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>547        </td><td> 9.596491  </td><td>143        </td><td>291        </td><td>5.105263   </td><td>116        </td><td>169        </td><td>2.964912   </td><td>130        </td><td>302        </td><td>...        </td><td>-3.215855  </td><td>-3.248973  </td><td>378        </td><td> 6.63157895</td><td> 9.13979775</td><td> 9.23392354</td><td>-11        </td><td>-0.19298246</td><td>-0.26597295</td><td>-0.26871206</td></tr>\n",
       "\t<tr><th scope=row>11</th><td>553        </td><td> 9.701754  </td><td>133        </td><td>365        </td><td>6.403509   </td><td>121        </td><td>556        </td><td>9.754386   </td><td>136        </td><td>355        </td><td>...        </td><td> 4.113095  </td><td> 4.408965  </td><td> -3        </td><td>-0.05263158</td><td>-0.06138948</td><td>-0.06580544</td><td> 10        </td><td> 0.17543860</td><td> 0.20463161</td><td> 0.21935148</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllllllllllllllllllllllllllllllllll}\n",
       "  & W1MaxWAbs & W1MaxWRel & W1maxRPM & W1MedWAbs & W1MedWRel & W1medRPM & W2MaxWAbs & W2MaxWRel & W2maxRPM & W2MedWAbs & ... & W2DifWRelFFM1 & W2DifWRelFFM2 & W1.2MaxDifWAbs & W1.2MaxDifWRel & W1.2MaxDifWRelFFM1 & W1.2MaxDifWRelFFM2 & W1.2MedDifWAbs & W1.2MedDifWRel & W1.2MedDifWRelFFM1 & W1.2MedDifWRelFFM2\\\\\n",
       "\\hline\n",
       "\t0 & 398         &  8.747253   & 122         & 206         & 4.527473    & 100         & 397         & 8.725275    & 122         & 224         & ...         &  4.479981   &  4.544592   &   1         &  0.02197802 &  0.02589585 &  0.02626932 & -18         & -0.39560440 & -0.46612522 & -0.47284774\\\\\n",
       "\t4 & 511         &  8.964912   & 128         & 294         & 5.157895    & 109         & 523         & 9.175439    & 122         & 295         & ...         &  4.552187   &  4.889881   & -12         & -0.21052632 & -0.23958880 & -0.25736216 &  -1         & -0.01754386 & -0.01996573 & -0.02144685\\\\\n",
       "\t7 & 524         & 10.174757   & 130         & 262         & 5.087379    & 107         & 476         & 9.242718    & 125         & 245         & ...         &  4.958966   &  5.566747   &  48         &  0.93203883 &  1.03043453 &  1.15672661 &  17         &  0.33009709 &  0.36494556 &  0.40967401\\\\\n",
       "\t8 & 541         &  8.868852   & 128         & 351         & 5.754098    & 118         & 472         & 7.737705    & 130         & 333         & ...         &  2.792441   &  3.020719   &  69         &  1.13114754 &  1.38617564 &  1.49949379 &  18         &  0.29508197 &  0.36161104 &  0.39117229\\\\\n",
       "\t9 & 547         &  9.596491   & 143         & 291         & 5.105263    & 116         & 169         & 2.964912    & 130         & 302         & ...         & -3.215855   & -3.248973   & 378         &  6.63157895 &  9.13979775 &  9.23392354 & -11         & -0.19298246 & -0.26597295 & -0.26871206\\\\\n",
       "\t11 & 553         &  9.701754   & 133         & 365         & 6.403509    & 121         & 556         & 9.754386    & 136         & 355         & ...         &  4.113095   &  4.408965   &  -3         & -0.05263158 & -0.06138948 & -0.06580544 &  10         &  0.17543860 &  0.20463161 &  0.21935148\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | W1MaxWAbs | W1MaxWRel | W1maxRPM | W1MedWAbs | W1MedWRel | W1medRPM | W2MaxWAbs | W2MaxWRel | W2maxRPM | W2MedWAbs | ... | W2DifWRelFFM1 | W2DifWRelFFM2 | W1.2MaxDifWAbs | W1.2MaxDifWRel | W1.2MaxDifWRelFFM1 | W1.2MaxDifWRelFFM2 | W1.2MedDifWAbs | W1.2MedDifWRel | W1.2MedDifWRelFFM1 | W1.2MedDifWRelFFM2 |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 0 | 398         |  8.747253   | 122         | 206         | 4.527473    | 100         | 397         | 8.725275    | 122         | 224         | ...         |  4.479981   |  4.544592   |   1         |  0.02197802 |  0.02589585 |  0.02626932 | -18         | -0.39560440 | -0.46612522 | -0.47284774 |\n",
       "| 4 | 511         |  8.964912   | 128         | 294         | 5.157895    | 109         | 523         | 9.175439    | 122         | 295         | ...         |  4.552187   |  4.889881   | -12         | -0.21052632 | -0.23958880 | -0.25736216 |  -1         | -0.01754386 | -0.01996573 | -0.02144685 |\n",
       "| 7 | 524         | 10.174757   | 130         | 262         | 5.087379    | 107         | 476         | 9.242718    | 125         | 245         | ...         |  4.958966   |  5.566747   |  48         |  0.93203883 |  1.03043453 |  1.15672661 |  17         |  0.33009709 |  0.36494556 |  0.40967401 |\n",
       "| 8 | 541         |  8.868852   | 128         | 351         | 5.754098    | 118         | 472         | 7.737705    | 130         | 333         | ...         |  2.792441   |  3.020719   |  69         |  1.13114754 |  1.38617564 |  1.49949379 |  18         |  0.29508197 |  0.36161104 |  0.39117229 |\n",
       "| 9 | 547         |  9.596491   | 143         | 291         | 5.105263    | 116         | 169         | 2.964912    | 130         | 302         | ...         | -3.215855   | -3.248973   | 378         |  6.63157895 |  9.13979775 |  9.23392354 | -11         | -0.19298246 | -0.26597295 | -0.26871206 |\n",
       "| 11 | 553         |  9.701754   | 133         | 365         | 6.403509    | 121         | 556         | 9.754386    | 136         | 355         | ...         |  4.113095   |  4.408965   |  -3         | -0.05263158 | -0.06138948 | -0.06580544 |  10         |  0.17543860 |  0.20463161 |  0.21935148 |\n",
       "\n"
      ],
      "text/plain": [
       "   W1MaxWAbs W1MaxWRel W1maxRPM W1MedWAbs W1MedWRel W1medRPM W2MaxWAbs\n",
       "0  398        8.747253 122      206       4.527473  100      397      \n",
       "4  511        8.964912 128      294       5.157895  109      523      \n",
       "7  524       10.174757 130      262       5.087379  107      476      \n",
       "8  541        8.868852 128      351       5.754098  118      472      \n",
       "9  547        9.596491 143      291       5.105263  116      169      \n",
       "11 553        9.701754 133      365       6.403509  121      556      \n",
       "   W2MaxWRel W2maxRPM W2MedWAbs ... W2DifWRelFFM1 W2DifWRelFFM2 W1.2MaxDifWAbs\n",
       "0  8.725275  122      224       ...  4.479981      4.544592       1           \n",
       "4  9.175439  122      295       ...  4.552187      4.889881     -12           \n",
       "7  9.242718  125      245       ...  4.958966      5.566747      48           \n",
       "8  7.737705  130      333       ...  2.792441      3.020719      69           \n",
       "9  2.964912  130      302       ... -3.215855     -3.248973     378           \n",
       "11 9.754386  136      355       ...  4.113095      4.408965      -3           \n",
       "   W1.2MaxDifWRel W1.2MaxDifWRelFFM1 W1.2MaxDifWRelFFM2 W1.2MedDifWAbs\n",
       "0   0.02197802     0.02589585         0.02626932        -18           \n",
       "4  -0.21052632    -0.23958880        -0.25736216         -1           \n",
       "7   0.93203883     1.03043453         1.15672661         17           \n",
       "8   1.13114754     1.38617564         1.49949379         18           \n",
       "9   6.63157895     9.13979775         9.23392354        -11           \n",
       "11 -0.05263158    -0.06138948        -0.06580544         10           \n",
       "   W1.2MedDifWRel W1.2MedDifWRelFFM1 W1.2MedDifWRelFFM2\n",
       "0  -0.39560440    -0.46612522        -0.47284774       \n",
       "4  -0.01754386    -0.01996573        -0.02144685       \n",
       "7   0.33009709     0.36494556         0.40967401       \n",
       "8   0.29508197     0.36161104         0.39117229       \n",
       "9  -0.19298246    -0.26597295        -0.26871206       \n",
       "11  0.17543860     0.20463161         0.21935148       "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "handle_target <- read.csv('handle_target_fusion_31_03_20.csv', row.name = 1)\n",
    "\n",
    "head(handle_target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>W1.2MedDifWRelFFM1</th><th scope=col>rs10034661</th><th scope=col>rs10063949</th><th scope=col>rs1024610</th><th scope=col>rs1024611</th><th scope=col>rs1042713</th><th scope=col>rs1045485</th><th scope=col>rs10491003</th><th scope=col>rs1049305</th><th scope=col>rs1049434</th><th scope=col>...</th><th scope=col>rs8111989</th><th scope=col>rs8192678</th><th scope=col>rs824205</th><th scope=col>rs833070</th><th scope=col>rs884736</th><th scope=col>rs921943</th><th scope=col>rs9469199</th><th scope=col>rs970547</th><th scope=col>rs9902453</th><th scope=col>rs9939609</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>-0.46612522</td><td>G:G        </td><td>C:T        </td><td>A:T        </td><td>T:T        </td><td>A:A        </td><td>C:G        </td><td>G:G        </td><td>C:G        </td><td>A:T        </td><td>...        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>A:G        </td><td>C:T        </td><td>A:G        </td><td>A:G        </td><td>A:A        </td><td>A:G        </td><td>A:A        </td></tr>\n",
       "\t<tr><td>-0.01996573</td><td>G:G        </td><td>C:T        </td><td>A:T        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>G:G        </td><td>G:G        </td><td>A:A        </td><td>...        </td><td>C:T        </td><td>A:G        </td><td>A:G        </td><td>A:G        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>A:G        </td><td>A:G        </td><td>T:T        </td></tr>\n",
       "\t<tr><td> 0.36494556</td><td>G:G        </td><td>T:T        </td><td>A:T        </td><td>T:T        </td><td>A:G        </td><td>G:G        </td><td>G:G        </td><td>C:G        </td><td>A:A        </td><td>...        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>A:G        </td><td>C:T        </td><td>A:A        </td><td>G:G        </td><td>A:G        </td><td>A:G        </td><td>A:A        </td></tr>\n",
       "\t<tr><td> 0.36161104</td><td>G:G        </td><td>T:T        </td><td>T:T        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>G:G        </td><td>C:C        </td><td>A:T        </td><td>...        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>A:G        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>A:A        </td><td>A:A        </td><td>A:A        </td></tr>\n",
       "\t<tr><td>-0.26597295</td><td>G:G        </td><td>C:T        </td><td>T:T        </td><td>C:T        </td><td>G:G        </td><td>C:C        </td><td>G:G        </td><td>C:G        </td><td>T:T        </td><td>...        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>G:G        </td><td>T:T        </td><td>G:G        </td><td>G:G        </td><td>A:A        </td><td>A:G        </td><td>A:T        </td></tr>\n",
       "\t<tr><td> 0.20463161</td><td>G:G        </td><td>C:T        </td><td>T:T        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>G:G        </td><td>C:G        </td><td>A:T        </td><td>...        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>G:G        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>A:G        </td><td>G:G        </td><td>T:T        </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll}\n",
       " W1.2MedDifWRelFFM1 & rs10034661 & rs10063949 & rs1024610 & rs1024611 & rs1042713 & rs1045485 & rs10491003 & rs1049305 & rs1049434 & ... & rs8111989 & rs8192678 & rs824205 & rs833070 & rs884736 & rs921943 & rs9469199 & rs970547 & rs9902453 & rs9939609\\\\\n",
       "\\hline\n",
       "\t -0.46612522 & G:G         & C:T         & A:T         & T:T         & A:A         & C:G         & G:G         & C:G         & A:T         & ...         & C:T         & A:G         & G:G         & A:G         & C:T         & A:G         & A:G         & A:A         & A:G         & A:A        \\\\\n",
       "\t -0.01996573 & G:G         & C:T         & A:T         & C:T         & A:G         & G:G         & G:G         & G:G         & A:A         & ...         & C:T         & A:G         & A:G         & A:G         & C:T         & A:G         & G:G         & A:G         & A:G         & T:T        \\\\\n",
       "\t  0.36494556 & G:G         & T:T         & A:T         & T:T         & A:G         & G:G         & G:G         & C:G         & A:A         & ...         & C:T         & A:G         & G:G         & A:G         & C:T         & A:A         & G:G         & A:G         & A:G         & A:A        \\\\\n",
       "\t  0.36161104 & G:G         & T:T         & T:T         & C:T         & A:G         & G:G         & G:G         & C:C         & A:T         & ...         & C:T         & A:G         & G:G         & A:G         & C:T         & A:G         & G:G         & A:A         & A:A         & A:A        \\\\\n",
       "\t -0.26597295 & G:G         & C:T         & T:T         & C:T         & G:G         & C:C         & G:G         & C:G         & T:T         & ...         & C:T         & A:G         & G:G         & G:G         & T:T         & G:G         & G:G         & A:A         & A:G         & A:T        \\\\\n",
       "\t  0.20463161 & G:G         & C:T         & T:T         & C:T         & A:G         & G:G         & G:G         & C:G         & A:T         & ...         & C:T         & A:G         & G:G         & G:G         & C:T         & A:G         & G:G         & A:G         & G:G         & T:T        \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| W1.2MedDifWRelFFM1 | rs10034661 | rs10063949 | rs1024610 | rs1024611 | rs1042713 | rs1045485 | rs10491003 | rs1049305 | rs1049434 | ... | rs8111989 | rs8192678 | rs824205 | rs833070 | rs884736 | rs921943 | rs9469199 | rs970547 | rs9902453 | rs9939609 |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| -0.46612522 | G:G         | C:T         | A:T         | T:T         | A:A         | C:G         | G:G         | C:G         | A:T         | ...         | C:T         | A:G         | G:G         | A:G         | C:T         | A:G         | A:G         | A:A         | A:G         | A:A         |\n",
       "| -0.01996573 | G:G         | C:T         | A:T         | C:T         | A:G         | G:G         | G:G         | G:G         | A:A         | ...         | C:T         | A:G         | A:G         | A:G         | C:T         | A:G         | G:G         | A:G         | A:G         | T:T         |\n",
       "|  0.36494556 | G:G         | T:T         | A:T         | T:T         | A:G         | G:G         | G:G         | C:G         | A:A         | ...         | C:T         | A:G         | G:G         | A:G         | C:T         | A:A         | G:G         | A:G         | A:G         | A:A         |\n",
       "|  0.36161104 | G:G         | T:T         | T:T         | C:T         | A:G         | G:G         | G:G         | C:C         | A:T         | ...         | C:T         | A:G         | G:G         | A:G         | C:T         | A:G         | G:G         | A:A         | A:A         | A:A         |\n",
       "| -0.26597295 | G:G         | C:T         | T:T         | C:T         | G:G         | C:C         | G:G         | C:G         | T:T         | ...         | C:T         | A:G         | G:G         | G:G         | T:T         | G:G         | G:G         | A:A         | A:G         | A:T         |\n",
       "|  0.20463161 | G:G         | C:T         | T:T         | C:T         | A:G         | G:G         | G:G         | C:G         | A:T         | ...         | C:T         | A:G         | G:G         | G:G         | C:T         | A:G         | G:G         | A:G         | G:G         | T:T         |\n",
       "\n"
      ],
      "text/plain": [
       "  W1.2MedDifWRelFFM1 rs10034661 rs10063949 rs1024610 rs1024611 rs1042713\n",
       "1 -0.46612522        G:G        C:T        A:T       T:T       A:A      \n",
       "2 -0.01996573        G:G        C:T        A:T       C:T       A:G      \n",
       "3  0.36494556        G:G        T:T        A:T       T:T       A:G      \n",
       "4  0.36161104        G:G        T:T        T:T       C:T       A:G      \n",
       "5 -0.26597295        G:G        C:T        T:T       C:T       G:G      \n",
       "6  0.20463161        G:G        C:T        T:T       C:T       A:G      \n",
       "  rs1045485 rs10491003 rs1049305 rs1049434 ... rs8111989 rs8192678 rs824205\n",
       "1 C:G       G:G        C:G       A:T       ... C:T       A:G       G:G     \n",
       "2 G:G       G:G        G:G       A:A       ... C:T       A:G       A:G     \n",
       "3 G:G       G:G        C:G       A:A       ... C:T       A:G       G:G     \n",
       "4 G:G       G:G        C:C       A:T       ... C:T       A:G       G:G     \n",
       "5 C:C       G:G        C:G       T:T       ... C:T       A:G       G:G     \n",
       "6 G:G       G:G        C:G       A:T       ... C:T       A:G       G:G     \n",
       "  rs833070 rs884736 rs921943 rs9469199 rs970547 rs9902453 rs9939609\n",
       "1 A:G      C:T      A:G      A:G       A:A      A:G       A:A      \n",
       "2 A:G      C:T      A:G      G:G       A:G      A:G       T:T      \n",
       "3 A:G      C:T      A:A      G:G       A:G      A:G       A:A      \n",
       "4 A:G      C:T      A:G      G:G       A:A      A:A       A:A      \n",
       "5 G:G      T:T      G:G      G:G       A:A      A:G       A:T      \n",
       "6 G:G      C:T      A:G      G:G       A:G      G:G       T:T      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ind_med <- cbind(handle_target['W1.2MedDifWRelFFM1'],handle_genetic)\n",
    "\n",
    "rownames(ind_med) <- NULL\n",
    "\n",
    "head(ind_med)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>W1.2MedDifWRelFFM1Bin</th><th scope=col>W1.2MedDifWRelFFM1</th><th scope=col>rs10034661</th><th scope=col>rs10063949</th><th scope=col>rs1024610</th><th scope=col>rs1024611</th><th scope=col>rs1042713</th><th scope=col>rs1045485</th><th scope=col>rs10491003</th><th scope=col>rs1049305</th><th scope=col>...</th><th scope=col>rs8111989</th><th scope=col>rs8192678</th><th scope=col>rs824205</th><th scope=col>rs833070</th><th scope=col>rs884736</th><th scope=col>rs921943</th><th scope=col>rs9469199</th><th scope=col>rs970547</th><th scope=col>rs9902453</th><th scope=col>rs9939609</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0          </td><td>-0.46612522</td><td>G:G        </td><td>C:T        </td><td>A:T        </td><td>T:T        </td><td>A:A        </td><td>C:G        </td><td>G:G        </td><td>C:G        </td><td>...        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>A:G        </td><td>C:T        </td><td>A:G        </td><td>A:G        </td><td>A:A        </td><td>A:G        </td><td>A:A        </td></tr>\n",
       "\t<tr><td>0          </td><td>-0.01996573</td><td>G:G        </td><td>C:T        </td><td>A:T        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>G:G        </td><td>G:G        </td><td>...        </td><td>C:T        </td><td>A:G        </td><td>A:G        </td><td>A:G        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>A:G        </td><td>A:G        </td><td>T:T        </td></tr>\n",
       "\t<tr><td>0          </td><td> 0.36494556</td><td>G:G        </td><td>T:T        </td><td>A:T        </td><td>T:T        </td><td>A:G        </td><td>G:G        </td><td>G:G        </td><td>C:G        </td><td>...        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>A:G        </td><td>C:T        </td><td>A:A        </td><td>G:G        </td><td>A:G        </td><td>A:G        </td><td>A:A        </td></tr>\n",
       "\t<tr><td>0          </td><td> 0.36161104</td><td>G:G        </td><td>T:T        </td><td>T:T        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>G:G        </td><td>C:C        </td><td>...        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>A:G        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>A:A        </td><td>A:A        </td><td>A:A        </td></tr>\n",
       "\t<tr><td>0          </td><td>-0.26597295</td><td>G:G        </td><td>C:T        </td><td>T:T        </td><td>C:T        </td><td>G:G        </td><td>C:C        </td><td>G:G        </td><td>C:G        </td><td>...        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>G:G        </td><td>T:T        </td><td>G:G        </td><td>G:G        </td><td>A:A        </td><td>A:G        </td><td>A:T        </td></tr>\n",
       "\t<tr><td>0          </td><td> 0.20463161</td><td>G:G        </td><td>C:T        </td><td>T:T        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>G:G        </td><td>C:G        </td><td>...        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>G:G        </td><td>C:T        </td><td>A:G        </td><td>G:G        </td><td>A:G        </td><td>G:G        </td><td>T:T        </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll}\n",
       " W1.2MedDifWRelFFM1Bin & W1.2MedDifWRelFFM1 & rs10034661 & rs10063949 & rs1024610 & rs1024611 & rs1042713 & rs1045485 & rs10491003 & rs1049305 & ... & rs8111989 & rs8192678 & rs824205 & rs833070 & rs884736 & rs921943 & rs9469199 & rs970547 & rs9902453 & rs9939609\\\\\n",
       "\\hline\n",
       "\t 0           & -0.46612522 & G:G         & C:T         & A:T         & T:T         & A:A         & C:G         & G:G         & C:G         & ...         & C:T         & A:G         & G:G         & A:G         & C:T         & A:G         & A:G         & A:A         & A:G         & A:A        \\\\\n",
       "\t 0           & -0.01996573 & G:G         & C:T         & A:T         & C:T         & A:G         & G:G         & G:G         & G:G         & ...         & C:T         & A:G         & A:G         & A:G         & C:T         & A:G         & G:G         & A:G         & A:G         & T:T        \\\\\n",
       "\t 0           &  0.36494556 & G:G         & T:T         & A:T         & T:T         & A:G         & G:G         & G:G         & C:G         & ...         & C:T         & A:G         & G:G         & A:G         & C:T         & A:A         & G:G         & A:G         & A:G         & A:A        \\\\\n",
       "\t 0           &  0.36161104 & G:G         & T:T         & T:T         & C:T         & A:G         & G:G         & G:G         & C:C         & ...         & C:T         & A:G         & G:G         & A:G         & C:T         & A:G         & G:G         & A:A         & A:A         & A:A        \\\\\n",
       "\t 0           & -0.26597295 & G:G         & C:T         & T:T         & C:T         & G:G         & C:C         & G:G         & C:G         & ...         & C:T         & A:G         & G:G         & G:G         & T:T         & G:G         & G:G         & A:A         & A:G         & A:T        \\\\\n",
       "\t 0           &  0.20463161 & G:G         & C:T         & T:T         & C:T         & A:G         & G:G         & G:G         & C:G         & ...         & C:T         & A:G         & G:G         & G:G         & C:T         & A:G         & G:G         & A:G         & G:G         & T:T        \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| W1.2MedDifWRelFFM1Bin | W1.2MedDifWRelFFM1 | rs10034661 | rs10063949 | rs1024610 | rs1024611 | rs1042713 | rs1045485 | rs10491003 | rs1049305 | ... | rs8111989 | rs8192678 | rs824205 | rs833070 | rs884736 | rs921943 | rs9469199 | rs970547 | rs9902453 | rs9939609 |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 0           | -0.46612522 | G:G         | C:T         | A:T         | T:T         | A:A         | C:G         | G:G         | C:G         | ...         | C:T         | A:G         | G:G         | A:G         | C:T         | A:G         | A:G         | A:A         | A:G         | A:A         |\n",
       "| 0           | -0.01996573 | G:G         | C:T         | A:T         | C:T         | A:G         | G:G         | G:G         | G:G         | ...         | C:T         | A:G         | A:G         | A:G         | C:T         | A:G         | G:G         | A:G         | A:G         | T:T         |\n",
       "| 0           |  0.36494556 | G:G         | T:T         | A:T         | T:T         | A:G         | G:G         | G:G         | C:G         | ...         | C:T         | A:G         | G:G         | A:G         | C:T         | A:A         | G:G         | A:G         | A:G         | A:A         |\n",
       "| 0           |  0.36161104 | G:G         | T:T         | T:T         | C:T         | A:G         | G:G         | G:G         | C:C         | ...         | C:T         | A:G         | G:G         | A:G         | C:T         | A:G         | G:G         | A:A         | A:A         | A:A         |\n",
       "| 0           | -0.26597295 | G:G         | C:T         | T:T         | C:T         | G:G         | C:C         | G:G         | C:G         | ...         | C:T         | A:G         | G:G         | G:G         | T:T         | G:G         | G:G         | A:A         | A:G         | A:T         |\n",
       "| 0           |  0.20463161 | G:G         | C:T         | T:T         | C:T         | A:G         | G:G         | G:G         | C:G         | ...         | C:T         | A:G         | G:G         | G:G         | C:T         | A:G         | G:G         | A:G         | G:G         | T:T         |\n",
       "\n"
      ],
      "text/plain": [
       "  W1.2MedDifWRelFFM1Bin W1.2MedDifWRelFFM1 rs10034661 rs10063949 rs1024610\n",
       "1 0                     -0.46612522        G:G        C:T        A:T      \n",
       "2 0                     -0.01996573        G:G        C:T        A:T      \n",
       "3 0                      0.36494556        G:G        T:T        A:T      \n",
       "4 0                      0.36161104        G:G        T:T        T:T      \n",
       "5 0                     -0.26597295        G:G        C:T        T:T      \n",
       "6 0                      0.20463161        G:G        C:T        T:T      \n",
       "  rs1024611 rs1042713 rs1045485 rs10491003 rs1049305 ... rs8111989 rs8192678\n",
       "1 T:T       A:A       C:G       G:G        C:G       ... C:T       A:G      \n",
       "2 C:T       A:G       G:G       G:G        G:G       ... C:T       A:G      \n",
       "3 T:T       A:G       G:G       G:G        C:G       ... C:T       A:G      \n",
       "4 C:T       A:G       G:G       G:G        C:C       ... C:T       A:G      \n",
       "5 C:T       G:G       C:C       G:G        C:G       ... C:T       A:G      \n",
       "6 C:T       A:G       G:G       G:G        C:G       ... C:T       A:G      \n",
       "  rs824205 rs833070 rs884736 rs921943 rs9469199 rs970547 rs9902453 rs9939609\n",
       "1 G:G      A:G      C:T      A:G      A:G       A:A      A:G       A:A      \n",
       "2 A:G      A:G      C:T      A:G      G:G       A:G      A:G       T:T      \n",
       "3 G:G      A:G      C:T      A:A      G:G       A:G      A:G       A:A      \n",
       "4 G:G      A:G      C:T      A:G      G:G       A:A      A:A       A:A      \n",
       "5 G:G      G:G      T:T      G:G      G:G       A:A      A:G       A:T      \n",
       "6 G:G      G:G      C:T      A:G      G:G       A:G      G:G       T:T      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "W1.2MedDifWRelFFM1Bin <- factor(as.numeric(handle_target['W1.2MedDifWRelFFM1']>=median(handle_target$W1.2MedDifWRelFFM1)))\n",
    "\n",
    "ind_med <- cbind(W1.2MedDifWRelFFM1Bin, ind_med)\n",
    "\n",
    "head(ind_med)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>W1.2MedDifWRelFFM1Bin</th><th scope=col>rs10034661</th><th scope=col>rs10063949</th><th scope=col>rs1024610</th><th scope=col>rs1024611</th><th scope=col>rs1042713</th><th scope=col>rs1045485</th><th scope=col>rs10491003</th><th scope=col>rs1049305</th><th scope=col>rs1049434</th><th scope=col>...</th><th scope=col>rs8111989</th><th scope=col>rs8192678</th><th scope=col>rs824205</th><th scope=col>rs833070</th><th scope=col>rs884736</th><th scope=col>rs921943</th><th scope=col>rs9469199</th><th scope=col>rs970547</th><th scope=col>rs9902453</th><th scope=col>rs9939609</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0  </td><td>G:G</td><td>C:T</td><td>A:T</td><td>T:T</td><td>A:A</td><td>C:G</td><td>G:G</td><td>C:G</td><td>A:T</td><td>...</td><td>C:T</td><td>A:G</td><td>G:G</td><td>A:G</td><td>C:T</td><td>A:G</td><td>A:G</td><td>A:A</td><td>A:G</td><td>A:A</td></tr>\n",
       "\t<tr><td>0  </td><td>G:G</td><td>C:T</td><td>A:T</td><td>C:T</td><td>A:G</td><td>G:G</td><td>G:G</td><td>G:G</td><td>A:A</td><td>...</td><td>C:T</td><td>A:G</td><td>A:G</td><td>A:G</td><td>C:T</td><td>A:G</td><td>G:G</td><td>A:G</td><td>A:G</td><td>T:T</td></tr>\n",
       "\t<tr><td>0  </td><td>G:G</td><td>T:T</td><td>A:T</td><td>T:T</td><td>A:G</td><td>G:G</td><td>G:G</td><td>C:G</td><td>A:A</td><td>...</td><td>C:T</td><td>A:G</td><td>G:G</td><td>A:G</td><td>C:T</td><td>A:A</td><td>G:G</td><td>A:G</td><td>A:G</td><td>A:A</td></tr>\n",
       "\t<tr><td>0  </td><td>G:G</td><td>T:T</td><td>T:T</td><td>C:T</td><td>A:G</td><td>G:G</td><td>G:G</td><td>C:C</td><td>A:T</td><td>...</td><td>C:T</td><td>A:G</td><td>G:G</td><td>A:G</td><td>C:T</td><td>A:G</td><td>G:G</td><td>A:A</td><td>A:A</td><td>A:A</td></tr>\n",
       "\t<tr><td>0  </td><td>G:G</td><td>C:T</td><td>T:T</td><td>C:T</td><td>G:G</td><td>C:C</td><td>G:G</td><td>C:G</td><td>T:T</td><td>...</td><td>C:T</td><td>A:G</td><td>G:G</td><td>G:G</td><td>T:T</td><td>G:G</td><td>G:G</td><td>A:A</td><td>A:G</td><td>A:T</td></tr>\n",
       "\t<tr><td>0  </td><td>G:G</td><td>C:T</td><td>T:T</td><td>C:T</td><td>A:G</td><td>G:G</td><td>G:G</td><td>C:G</td><td>A:T</td><td>...</td><td>C:T</td><td>A:G</td><td>G:G</td><td>G:G</td><td>C:T</td><td>A:G</td><td>G:G</td><td>A:G</td><td>G:G</td><td>T:T</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll}\n",
       " W1.2MedDifWRelFFM1Bin & rs10034661 & rs10063949 & rs1024610 & rs1024611 & rs1042713 & rs1045485 & rs10491003 & rs1049305 & rs1049434 & ... & rs8111989 & rs8192678 & rs824205 & rs833070 & rs884736 & rs921943 & rs9469199 & rs970547 & rs9902453 & rs9939609\\\\\n",
       "\\hline\n",
       "\t 0   & G:G & C:T & A:T & T:T & A:A & C:G & G:G & C:G & A:T & ... & C:T & A:G & G:G & A:G & C:T & A:G & A:G & A:A & A:G & A:A\\\\\n",
       "\t 0   & G:G & C:T & A:T & C:T & A:G & G:G & G:G & G:G & A:A & ... & C:T & A:G & A:G & A:G & C:T & A:G & G:G & A:G & A:G & T:T\\\\\n",
       "\t 0   & G:G & T:T & A:T & T:T & A:G & G:G & G:G & C:G & A:A & ... & C:T & A:G & G:G & A:G & C:T & A:A & G:G & A:G & A:G & A:A\\\\\n",
       "\t 0   & G:G & T:T & T:T & C:T & A:G & G:G & G:G & C:C & A:T & ... & C:T & A:G & G:G & A:G & C:T & A:G & G:G & A:A & A:A & A:A\\\\\n",
       "\t 0   & G:G & C:T & T:T & C:T & G:G & C:C & G:G & C:G & T:T & ... & C:T & A:G & G:G & G:G & T:T & G:G & G:G & A:A & A:G & A:T\\\\\n",
       "\t 0   & G:G & C:T & T:T & C:T & A:G & G:G & G:G & C:G & A:T & ... & C:T & A:G & G:G & G:G & C:T & A:G & G:G & A:G & G:G & T:T\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| W1.2MedDifWRelFFM1Bin | rs10034661 | rs10063949 | rs1024610 | rs1024611 | rs1042713 | rs1045485 | rs10491003 | rs1049305 | rs1049434 | ... | rs8111989 | rs8192678 | rs824205 | rs833070 | rs884736 | rs921943 | rs9469199 | rs970547 | rs9902453 | rs9939609 |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 0   | G:G | C:T | A:T | T:T | A:A | C:G | G:G | C:G | A:T | ... | C:T | A:G | G:G | A:G | C:T | A:G | A:G | A:A | A:G | A:A |\n",
       "| 0   | G:G | C:T | A:T | C:T | A:G | G:G | G:G | G:G | A:A | ... | C:T | A:G | A:G | A:G | C:T | A:G | G:G | A:G | A:G | T:T |\n",
       "| 0   | G:G | T:T | A:T | T:T | A:G | G:G | G:G | C:G | A:A | ... | C:T | A:G | G:G | A:G | C:T | A:A | G:G | A:G | A:G | A:A |\n",
       "| 0   | G:G | T:T | T:T | C:T | A:G | G:G | G:G | C:C | A:T | ... | C:T | A:G | G:G | A:G | C:T | A:G | G:G | A:A | A:A | A:A |\n",
       "| 0   | G:G | C:T | T:T | C:T | G:G | C:C | G:G | C:G | T:T | ... | C:T | A:G | G:G | G:G | T:T | G:G | G:G | A:A | A:G | A:T |\n",
       "| 0   | G:G | C:T | T:T | C:T | A:G | G:G | G:G | C:G | A:T | ... | C:T | A:G | G:G | G:G | C:T | A:G | G:G | A:G | G:G | T:T |\n",
       "\n"
      ],
      "text/plain": [
       "  W1.2MedDifWRelFFM1Bin rs10034661 rs10063949 rs1024610 rs1024611 rs1042713\n",
       "1 0                     G:G        C:T        A:T       T:T       A:A      \n",
       "2 0                     G:G        C:T        A:T       C:T       A:G      \n",
       "3 0                     G:G        T:T        A:T       T:T       A:G      \n",
       "4 0                     G:G        T:T        T:T       C:T       A:G      \n",
       "5 0                     G:G        C:T        T:T       C:T       G:G      \n",
       "6 0                     G:G        C:T        T:T       C:T       A:G      \n",
       "  rs1045485 rs10491003 rs1049305 rs1049434 ... rs8111989 rs8192678 rs824205\n",
       "1 C:G       G:G        C:G       A:T       ... C:T       A:G       G:G     \n",
       "2 G:G       G:G        G:G       A:A       ... C:T       A:G       A:G     \n",
       "3 G:G       G:G        C:G       A:A       ... C:T       A:G       G:G     \n",
       "4 G:G       G:G        C:C       A:T       ... C:T       A:G       G:G     \n",
       "5 C:C       G:G        C:G       T:T       ... C:T       A:G       G:G     \n",
       "6 G:G       G:G        C:G       A:T       ... C:T       A:G       G:G     \n",
       "  rs833070 rs884736 rs921943 rs9469199 rs970547 rs9902453 rs9939609\n",
       "1 A:G      C:T      A:G      A:G       A:A      A:G       A:A      \n",
       "2 A:G      C:T      A:G      G:G       A:G      A:G       T:T      \n",
       "3 A:G      C:T      A:A      G:G       A:G      A:G       A:A      \n",
       "4 A:G      C:T      A:G      G:G       A:A      A:A       A:A      \n",
       "5 G:G      T:T      G:G      G:G       A:A      A:G       A:T      \n",
       "6 G:G      C:T      A:G      G:G       A:G      G:G       T:T      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>82</li>\n",
       "\t<li>179</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 82\n",
       "\\item 179\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 82\n",
       "2. 179\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1]  82 179"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ind_med$W1.2MedDifWRelFFM1 <- NULL\n",
    "head(ind_med)\n",
    "dim(ind_med)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we do not have the graph given by the expert, we are going to base ourselves on probability to determine the significant relationships with the target variable. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Construction of the Bayesian network using the tabu algorithm<a class=\"anchor\" id=\"2\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* [Returning to the index of contents](#index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "\"package 'bnlearn' was built under R version 3.6.2\"\n",
      "Attaching package: 'bnlearn'\n",
      "\n",
      "The following object is masked from 'package:stats':\n",
      "\n",
      "    sigma\n",
      "\n"
     ]
    }
   ],
   "source": [
    "library(bnlearn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "set.seed(10)\n",
    "tabu <- tabu(ind_med, tabu = 500,iss = 10, score = 'bde')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required namespace: Rgraphviz\n"
     ]
    },
    {
     "data": {
      "image/png": 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IIQnX7b3n3P6+HSDUeCNm5ab5BsCzYVcEaErgtnn1n82AOEl34zSD1q3Q3JoyCa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IuscT23kIJBJMzuYOkIJA2wASmXJ7MgyS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\nqafcgzYqogAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "graphviz.plot(tabu)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "-11659.7431332835"
      ],
      "text/latex": [
       "-11659.7431332835"
      ],
      "text/markdown": [
       "-11659.7431332835"
      ],
      "text/plain": [
       "[1] -11659.74"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bnlearn::score(tabu, data = ind_med,type = 'bde')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Comparison with the randomized model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "[1] \"[W1.2MedDifWRelFFM1Bin][rs10034661][rs10063949][rs1024610][rs1024611][rs1042713][rs1045485][rs10491003][rs1049305][rs1049434][rs10497520][rs1052700][rs1057972][rs10741657][rs10921078][rs10999516][rs11096663][rs11144134][rs11254363][rs1137100][rs1205][rs12150660][rs12255372][rs1260326][rs12613181][rs1420100][rs1420106][rs1481012][rs15705][rs1572312][rs16924573][rs17685][rs17782313][rs1799722][rs1799865][rs1799907][rs1800012][rs1800169][rs1800206][rs1800629][rs1800795][rs1800796][rs1800872][rs1805086][rs1815739][rs182549][rs1906058][rs1956197][rs2016520][rs222158][rs2395182][rs2470893][rs2472297][rs2515941][rs26802][rs2722171][rs28497577][rs3213221][rs3219177][rs331079][rs34124816][rs3925584][rs4073918][rs4410790][rs4654748][rs4880][rs492602][rs4997][rs516115][rs61752479][rs6265][rs660339][rs696217][rs7498665][rs768539][rs9902453][rs1107946|rs1042713][rs11225395|rs1024611][rs1137101|rs11096663][rs1144393|rs10921078][rs11549465|rs1042713:rs1052700][rs11715829|rs1024610:rs1045485:rs11144134][rs13146355|rs10741657:rs11144134][rs1330363|rs1052700][rs13946|rs1137100][rs1516797|rs1049434][rs1676486|rs12613181][rs1800497|rs10063949][rs1800562|rs1052700:rs1799722][rs1801282|rs1045485][rs1862513|rs1049434:rs1057972][rs198851|rs17782313][rs2040410|rs1800795][rs2071856|rs1137100][rs2104772|rs11144134][rs2228059|rs12150660][rs2276109|rs1042713:rs1800012][rs2296135|rs1052700][rs2304795|rs1800169][rs2542729|rs10491003:rs15705:rs1800872][rs2593324|rs1800872][rs35767|rs10741657:rs1800206:rs1906058][rs3752135|rs2722171:rs34124816][rs3768816|rs1956197][rs3811647|rs10063949][rs405509|rs1420100][rs4588|rs182549][rs4675639|rs17782313:rs2515941][rs4789932|rs1481012][rs4919510|rs11254363:rs1799907][rs558129|rs1052700:rs1799907][rs602662|rs1799722:rs1800169:rs222158][rs6133175|rs10063949:rs222158][rs6548238|rs1799722][rs6735530|rs1260326][rs7144481|rs1049434:rs4410790][rs7292407|rs1572312:rs34124816][rs731236|rs1049305][rs7843014|rs11096663:rs16924573:rs3925584][rs7903146|rs1800872][rs7965584|rs11254363:rs696217][rs833070|rs4997][rs921943|rs1956197][rs9469199|rs10491003:rs28497577][rs12934922|rs11225395][rs143383|rs13946][rs1451462|rs11715829][rs1589241|rs1049305:rs13146355][rs1799983|rs1144393][rs1801131|rs1144393][rs1801133|rs10491003:rs1057972:rs1676486][rs1801198|rs11549465][rs1801260|rs1800497][rs2010963|rs1572312:rs1676486][rs211302|rs11225395:rs1799722][rs2241057|rs1799722:rs1862513][rs2253206|rs13946][rs28357094|rs2542729][rs2943641|rs198851][rs3753841|rs1516797:rs2016520:rs2071856][rs4072037|rs2104772][rs4680|rs1107946:rs2395182][rs5186|rs1862513:rs2395182][rs5418|rs1516797][rs646776|rs11715829:rs1330363:rs16924573][rs6552828|rs1800169:rs2304795][rs6570913|rs10497520:rs13946][rs679620|rs1042713:rs2276109][rs716745|rs1800497][rs7454108|rs405509][rs7566605|rs13146355:rs558129][rs8111989|rs1801282][rs8192678|rs3768816][rs884736|rs2040410][rs9939609|rs1052700:rs1572312:rs1805086:rs2016520:rs2593324:rs4675639][rs1800255|rs11254363:rs12934922][rs2070744|rs1801131][rs2368564|rs143383:rs2228059][rs3219178|rs143383:rs1800206][rs33972313|rs1801260][rs3918358|rs1589241:rs1800169][rs4253778|rs2040410:rs4072037][rs4343|rs1801260:rs2296135][rs650108|rs11144134:rs211302][rs659366|rs143383:rs222158:rs35767:rs4997][rs6968554|rs1137101:rs1801198][rs7191721|rs143383][rs7800944|rs11144134:rs1800562:rs2104772:rs4072037][rs824205|rs1107946:rs1260326:rs405509:rs696217:rs7498665:rs8192678][rs970547|rs1801198:rs222158][rs526934|rs1205:rs4343][rs6053005|rs1137101:rs4343][rs7426114|rs1137101:rs12255372:rs1801198:rs3918358][rs7501331|rs2368564][rs7682|rs10063949:rs1956197:rs3219178][rs7775228|rs1420106:rs2070744:rs7566605][rs8065080|rs1451462:rs2070744:rs3219178:rs3753841:rs5418][rs699|rs17782313:rs2304795:rs4880:rs4919510:rs526934:rs61752479][rs7732671|rs6053005]\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "-15039.982260133"
      ],
      "text/latex": [
       "-15039.982260133"
      ],
      "text/markdown": [
       "-15039.982260133"
      ],
      "text/plain": [
       "[1] -15039.98"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "set.seed(1)\n",
    "rnd <- random.graph(nodes = names(ind_med))\n",
    "modelstring(rnd)\n",
    "\n",
    "bnlearn::score(rnd, data = ind_med,type = 'bde')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The score obtained is extremely low, although higher than in the case of the random model. Let's keep the most significant relationships according to the independence test of $\\chi^2$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Significance relations obtained with the tabu algorithm:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>from</th><th scope=col>to</th><th scope=col>strength</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>rs1799865   </td><td>rs3918358   </td><td>3.312751e-20</td></tr>\n",
       "\t<tr><td>rs4410790   </td><td>rs6968554   </td><td>1.785994e-18</td></tr>\n",
       "\t<tr><td>rs492602    </td><td>rs602662    </td><td>1.695393e-16</td></tr>\n",
       "\t<tr><td>rs659366    </td><td>rs660339    </td><td>7.434565e-16</td></tr>\n",
       "\t<tr><td>rs2228059   </td><td>rs2296135   </td><td>2.959759e-09</td></tr>\n",
       "\t<tr><td>rs1799865   </td><td>rs768539    </td><td>1.000000e+00</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       " from & to & strength\\\\\n",
       "\\hline\n",
       "\t rs1799865    & rs3918358    & 3.312751e-20\\\\\n",
       "\t rs4410790    & rs6968554    & 1.785994e-18\\\\\n",
       "\t rs492602     & rs602662     & 1.695393e-16\\\\\n",
       "\t rs659366     & rs660339     & 7.434565e-16\\\\\n",
       "\t rs2228059    & rs2296135    & 2.959759e-09\\\\\n",
       "\t rs1799865    & rs768539     & 1.000000e+00\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| from | to | strength |\n",
       "|---|---|---|\n",
       "| rs1799865    | rs3918358    | 3.312751e-20 |\n",
       "| rs4410790    | rs6968554    | 1.785994e-18 |\n",
       "| rs492602     | rs602662     | 1.695393e-16 |\n",
       "| rs659366     | rs660339     | 7.434565e-16 |\n",
       "| rs2228059    | rs2296135    | 2.959759e-09 |\n",
       "| rs1799865    | rs768539     | 1.000000e+00 |\n",
       "\n"
      ],
      "text/plain": [
       "  from      to        strength    \n",
       "1 rs1799865 rs3918358 3.312751e-20\n",
       "2 rs4410790 rs6968554 1.785994e-18\n",
       "3 rs492602  rs602662  1.695393e-16\n",
       "4 rs659366  rs660339  7.434565e-16\n",
       "5 rs2228059 rs2296135 2.959759e-09\n",
       "6 rs1799865 rs768539  1.000000e+00"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sig_tabu <- arc.strength(tabu, data = ind_med, criterion = \"x2\") \n",
    "head(sig_tabu)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To select the significant relationships, we assume that we are interested in those that contain the target variable: W1.2MedDifWRelFFM1. Let's select with this condition."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>from</th><th scope=col>to</th><th scope=col>strength</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>178</th><td>W1.2MedDifWRelFFM1Bin</td><td>rs11144134           </td><td>0.9989072            </td></tr>\n",
       "\t<tr><th scope=row>272</th><td>W1.2MedDifWRelFFM1Bin</td><td>rs7191721            </td><td>0.9877784            </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       "  & from & to & strength\\\\\n",
       "\\hline\n",
       "\t178 & W1.2MedDifWRelFFM1Bin & rs11144134            & 0.9989072            \\\\\n",
       "\t272 & W1.2MedDifWRelFFM1Bin & rs7191721             & 0.9877784            \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | from | to | strength |\n",
       "|---|---|---|---|\n",
       "| 178 | W1.2MedDifWRelFFM1Bin | rs11144134            | 0.9989072             |\n",
       "| 272 | W1.2MedDifWRelFFM1Bin | rs7191721             | 0.9877784             |\n",
       "\n"
      ],
      "text/plain": [
       "    from                  to         strength \n",
       "178 W1.2MedDifWRelFFM1Bin rs11144134 0.9989072\n",
       "272 W1.2MedDifWRelFFM1Bin rs7191721  0.9877784"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sig_tabu[sig_tabu$from  == 'W1.2MedDifWRelFFM1Bin',]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>from</th><th scope=col>to</th><th scope=col>strength</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>77</th><td>rs6968554            </td><td>W1.2MedDifWRelFFM1Bin</td><td>0.0637851            </td></tr>\n",
       "\t<tr><th scope=row>334</th><td>rs1800497            </td><td>W1.2MedDifWRelFFM1Bin</td><td>0.5435754            </td></tr>\n",
       "\t<tr><th scope=row>335</th><td>rs1572312            </td><td>W1.2MedDifWRelFFM1Bin</td><td>0.6633979            </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       "  & from & to & strength\\\\\n",
       "\\hline\n",
       "\t77 & rs6968554             & W1.2MedDifWRelFFM1Bin & 0.0637851            \\\\\n",
       "\t334 & rs1800497             & W1.2MedDifWRelFFM1Bin & 0.5435754            \\\\\n",
       "\t335 & rs1572312             & W1.2MedDifWRelFFM1Bin & 0.6633979            \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | from | to | strength |\n",
       "|---|---|---|---|\n",
       "| 77 | rs6968554             | W1.2MedDifWRelFFM1Bin | 0.0637851             |\n",
       "| 334 | rs1800497             | W1.2MedDifWRelFFM1Bin | 0.5435754             |\n",
       "| 335 | rs1572312             | W1.2MedDifWRelFFM1Bin | 0.6633979             |\n",
       "\n"
      ],
      "text/plain": [
       "    from      to                    strength \n",
       "77  rs6968554 W1.2MedDifWRelFFM1Bin 0.0637851\n",
       "334 rs1800497 W1.2MedDifWRelFFM1Bin 0.5435754\n",
       "335 rs1572312 W1.2MedDifWRelFFM1Bin 0.6633979"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sig_tabu[sig_tabu$to  == 'W1.2MedDifWRelFFM1Bin',]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The relationships given between the genetic predictors and the target variable are not significant, but it may be that in the presence of the physical variables these relationships make more sense. That is why we collect these predictors to be analyzed later along with the physical predictors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "snp_tabu <- c(sig_tabu[sig_tabu$from  == 'W1.2MedDifWRelFFM1Bin',]$to, sig_tabu[sig_tabu$to  == 'W1.2MedDifWRelFFM1Bin',]$from)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'rs11144134'</li>\n",
       "\t<li>'rs7191721'</li>\n",
       "\t<li>'rs6968554'</li>\n",
       "\t<li>'rs1800497'</li>\n",
       "\t<li>'rs1572312'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'rs11144134'\n",
       "\\item 'rs7191721'\n",
       "\\item 'rs6968554'\n",
       "\\item 'rs1800497'\n",
       "\\item 'rs1572312'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'rs11144134'\n",
       "2. 'rs7191721'\n",
       "3. 'rs6968554'\n",
       "4. 'rs1800497'\n",
       "5. 'rs1572312'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] \"rs11144134\" \"rs7191721\"  \"rs6968554\"  \"rs1800497\"  \"rs1572312\" "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snp_tabu"
   ]
  }
 ],
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   "display_name": "R",
   "language": "R",
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  },
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