{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "e4ff106e-c6b4-4da3-88d0-143641816deb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "from scipy import stats\n",
    "from statsmodels.stats.multicomp import pairwise_tukeyhsd\n",
    "plt.rcParams['pdf.fonttype'] = 42"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "9613bdaf-456e-46eb-af14-c40a2d7849a8",
   "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>Intensity</th>\n",
       "      <th>Length</th>\n",
       "      <th>strain</th>\n",
       "      <th>genotype</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>23.188</td>\n",
       "      <td>11.437</td>\n",
       "      <td>L972</td>\n",
       "      <td>WT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12.775</td>\n",
       "      <td>13.391</td>\n",
       "      <td>L972</td>\n",
       "      <td>WT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18.562</td>\n",
       "      <td>12.226</td>\n",
       "      <td>L972</td>\n",
       "      <td>WT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>17.600</td>\n",
       "      <td>11.902</td>\n",
       "      <td>L972</td>\n",
       "      <td>WT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14.675</td>\n",
       "      <td>12.087</td>\n",
       "      <td>L972</td>\n",
       "      <td>WT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>329</th>\n",
       "      <td>27.087</td>\n",
       "      <td>13.433</td>\n",
       "      <td>HS754</td>\n",
       "      <td>Padh11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330</th>\n",
       "      <td>36.650</td>\n",
       "      <td>12.299</td>\n",
       "      <td>HS754</td>\n",
       "      <td>Padh11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>331</th>\n",
       "      <td>42.462</td>\n",
       "      <td>12.892</td>\n",
       "      <td>HS754</td>\n",
       "      <td>Padh11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332</th>\n",
       "      <td>37.038</td>\n",
       "      <td>12.888</td>\n",
       "      <td>HS754</td>\n",
       "      <td>Padh11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>333</th>\n",
       "      <td>34.962</td>\n",
       "      <td>14.796</td>\n",
       "      <td>HS754</td>\n",
       "      <td>Padh11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>334 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Intensity  Length strain genotype\n",
       "0       23.188  11.437   L972       WT\n",
       "1       12.775  13.391   L972       WT\n",
       "2       18.562  12.226   L972       WT\n",
       "3       17.600  11.902   L972       WT\n",
       "4       14.675  12.087   L972       WT\n",
       "..         ...     ...    ...      ...\n",
       "329     27.087  13.433  HS754   Padh11\n",
       "330     36.650  12.299  HS754   Padh11\n",
       "331     42.462  12.892  HS754   Padh11\n",
       "332     37.038  12.888  HS754   Padh11\n",
       "333     34.962  14.796  HS754   Padh11\n",
       "\n",
       "[334 rows x 4 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('quantification.csv')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "1c677cfb-7e01-4bc8-9e96-256224bc2445",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "genotype\n",
       "Padh1     55\n",
       "Padh11    56\n",
       "Ptdh1     60\n",
       "Ptdh11    46\n",
       "Ptdh13    20\n",
       "Ptdh15    57\n",
       "WT        20\n",
       "empty     20\n",
       "dtype: int64"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('genotype').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "5f91e90e-2247-46c3-80e8-ab872833499e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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LsNmnrdLB6O1r/m8rx7Pebx2HK7hrOUiAEwBjrIOwXgzG3pk5/4B6AICqvh4ntm2S5v8PhwneMEAAcLSiCv/dtq1NcXh7e7cl9DZx10ygACcAxlgnVgugy7X/joYe3SEiGkZoYK79JwAhcO0TfVu5ayZQgBMAY6yD0Gqvr9o1efJku6aDrsvNhG9RAbRe3uhuNEKrN5cISBAgEMHk5QPv+OGY1iuyxeMYjUZ89dVXjeJwBXctBwlwAmCMdRDW6/BabsatmY06BMMIL4MBBPMTvwhAIEIDAGNDA45kHEEejjkUR0fHvYAYY51WNjQwwXzjt1T5GADoIEADwAgoYklIuXAJgDHWIWi1WqSmprb9gyePA9//B6ipQrneiFPQYOSAGKggILj4PIKHDEXqbVPbFEdbEZFNI7Y182RwjX9v7tzOLIFwAmCMOVVeXh527tyJqVOnIjY21mnHFQQBXg7MlS9qNDAZDaAuAajXVyAEBFVCCoSf9gImA3D+LLQunoPfYDBg1apVNttiYZB6JZkXqQTS0tJaPE5qaqpD16A5XAXEGHMavV6PHTt2oLKyEjt27Gj1idYdxOwMQKMFrj2BS4uvA5CzA5BlIXg5q6C4BMAYc5r9+/ejuroaAFBdXY39+/djwoQJssakSkiBSVcJEKGwuh4hIPQckgy1RuO27pZNVl+dPA7kZCIsbiiejYmV3tdSFY+zeyBxAmCMOUVZWRn2798vjZQlIuzfvx9JSUno1q2bbHGp4hIhZmeAKsoRAsJm+CJ1UDxUXl5u627ZZPVV4jDzDwDXDStrGVcBMcbajYiwc+dO6XUsDJiNOsSSATt37nT59AmWGPR6fZM/4uAkiP4B1+rb0ez79Hq9W2JVCi4BMMbarbS0FAUF1xdWsdRvDyE9NhcUoLS0FN27d3dpDE01tN4oFuaxAdvTVpsXYW+CsxtalYxLAIyxdgsNDUVMTIxUf50NDXRQIUfwQkxMDEJDQ2WO0EwJDa9KIpAnlXeaoNPpEBQUhMrKSgQGBsodDmMdVllZGdLT0yGKorRNpVLhySefREhIiMvP31Jfe8t+U84xqE4cgxA/DMLghCbf5+y+9nKw977GVUCMMafo1q0bxo4di3379oGIIAgCxo4d65abP2DnOIFhI80/DABXATHGnGjs2LHw9/cHAAQEBGDs2LEyR8RawiUAxpjd7Klmuf322/Hdd99h4sSJAJqf3qAzVLV0dJwAGGN2s6enjcXmzZttpju4sdeNJ/W2UaoOXwVUVVWFESNGYOjQoUhISMB7770nd0iMsWu4142ydfheQCaTCQ0NDfDz80NtbS3i4+Nx+PBhu0ceci8gxuzXWhWQXq+XJjR79tln4fXLKfO8O0OSgUHxNu/lKiDX8ZheQGq1Gn5+fgCA+vp6mEwmjxrJx5g7tWVGTi8vL3hZTXfAlEf2KqC9e/di+vTp6N27NwRBwLYmFmd+55130LdvX/j4+CAlJQX79u2z2V9RUYGkpCRERETgueeeU8ygE8YYUzLZE0BNTQ2SkpKwdu3aJvdv3LgRixYtwgsvvIDMzEyMGzcOU6ZMQWFhofSe4OBgHDt2DGfOnMG///1vXL582V3hM8ZYhyV7ApgyZQpeeeUV3H333U3uf+ONN/Dwww9j/vz5GDx4MN566y1ERkbi3XffbfTesLAwJCYmYu/evc2er6GhATqdzuaHMcY8kewJoCV6vR4ZGRlSf2KLiRMn4sCBAwCAy5cvSzdxnU6HvXv3trgK0erVqxEUFCT9REZGuu4fwJgHEXOzgC0fIxbXGolPHofhvbdgeO8t8z6mOIpOAKWlpTCZTAgLC7PZHhYWhkuXLgEAzp8/j1/96ldISkrC2LFj8eSTTyIxsfk5vpctW4bKykrpp6ioyKX/BsY8hZidAegqr3f5zMkErl4Byq6Y9zHF6RC9gG7sKmaZZwQAUlJScPToUbuP5e3tDW9vuZZfYKzzUiWkQDx2GNnFZeYNQ5KB6ippH1MeRSeA0NBQqNVq6WnfoqSkpFGpgDEmL1VcItB/EPIsI4UHxUPLXUAVTdFVQF5eXkhJScGuXbtstu/atQtjxoxp17HT09MRFxeHESNGtOs4jHk6MTcLxo3rber5Y2EAtnzMdf8KJ3sJoLq6GqdPn5ZenzlzBkePHkVISAiioqKwZMkSzJkzB8OHD8fo0aOxbt06FBYW4rHHHmvXeRcuXIiFCxdKI+YYY44RszNAl4thOvsZ4OOLeagx79BVmhddd9O6u6ztZE8AR44cwa233iq9XrJkCQBg7ty52LBhA+677z6UlZVh5cqVKC4uRnx8PHbu3Ik+ffrIFTJjzIoqIcV882+oBxrq0Q2EMqiAwCCu+1e4Dj8XUHvxXECMXdfaXD/N2pAOlF4GCLhoMKEQaowcEGNOADfMAWQPnieofTxmLiBHpaenIz09HSaTSe5QGFOMtkz3bC0WBoyGCT4gAAIGwghD/kmU5Z/CQXg1OyV0c3iqaPdQdCOwKy1cuBC5ubk4fPiw3KEw1qGZb/56hEBEAAjdIaIrCFoAPiCeElrBPLYEwBhr2bRp06DRtH6LiPxpN7qUXgJIAAlqAASIJqiI4BsUAt8BQ9Cl6AwMkX0xs3fzbXdGoxE7duxw4r+AtYYTAGOsSRqNxq4EUBXdH9qGOgDA1dgEAED37CNQ6Rtg8vFD1wtnoYvuj7rwaL7hKAz//2CMSaz7hBiN9lXZVIRFoCIsAgAQcPEcgovOwKj1gpoI/peKAEGAV+VV6T3NsT6fh/dNcRtOAIwxiXUPoLZWx8TCgElogACCTf8dIojV1U2u9dFSHDxli+t5bCMwjwRmzHmu3/wBbwB1ECACMAEQARy1s/cPcy+PLQHwSGDGGtNqr9+o7W0EBoC+e3bCu8oAEtQo7xMD75pq6EmE9moJjFpvhA8Z1mIDMGDbCGwdB3Mdj00AjLHGrAdf2dsILH1OpYbBPxBXh46C/4Wz6HH0R6hEgmBoQNcLZ1EXFeNQHMx1PLYKiDHmPFdjE1DbvafUCyiwsACkUoNUKuj9g6Brw82fuQ+XABhj7VYdHo3q8GgAgP+Fs9DU1cLk7YMriSOk7Ux5uATAGHOqwMICCNe6cQYWFsD/wll5A2LN8tgEwL2AGHMNXVQMDH5dAADa2hoEFhbIHBFrjsdWAXEvIKZUrc3Iab2/tVkz2zOrpr0DwSwsg8DqfbtANInQe3nDr+Iqqrr1sOtYbT0faz+PTQCMKVVzM3LGwmAzq+aNr5vSnlk17R0IZolDDRE1AIIhQgBAAEqhgu50PradPu9QDMy1PLYKiLGO5sZZNZUyy6YlDsA86EsN842l9tpgMH+I5iUimeI4tCDMvHnz8Lvf/Q6/+tWvXBGTW/GCMExpmq0COnkcyMmEMTYBX3z5BUZDj169ekEYPb7ZRVfaWgXk0IIw1+LCkGSI2Rmoy8+DNwjC8DFQXywErpYCIaHAvIV2H5IXhGkfly4IU1VVhYkTJyIyMhIPPfQQ5s6di/DwcIeDZczTOLzy1jUJMEIFgEAQcjLNG5tIAq2d48YbrSAIba8yShwGUaOBmJ0BhHQHIQ/VEBBcVWE+tgBAEKDlBV4Ux6EEsGXLFpSVleFf//oXNmzYgOXLl+P222/Hww8/jBkzZvAwbsZa4cjKW7NRh0CI0OWdQjY0SIAR3sXF8Cu+iLK8k9iALm2Ow1krb4nZGUBlBSCK+BreSIARwUOSob6WGHhtYGVyuA2gW7dueOaZZ5CZmYlDhw6hf//+mDNnDnr37o3FixcjPz/fmXE6HXcDZR1NNjTQQSU1+m6GL+qgjGoSVUIKEBQMDEmWYsOgeKjiEqG57yGo4hLlDpE1od29gIqLi/HNN9/gm2++gVqtxtSpU5GTk4O4uDisWbMGixcvdkacTsfdQJlStGXSNSOAQUQYfv4sul44C71/BPQ11TC1stqWzTFcsPKWKi4RqrhE6PV6AF869djMdRxKAAaDAV9++SXWr1+Pb775BomJiVi8eDEeeOABBAQEAAD+93//F48//rhiEwBjStGWSdcsul0qhE9FKQKuXER5zGDURcVwn27WZg59Z3r16gVRFHH//ffj0KFDGDp0aKP3TJo0CcHBwe0MjzHWFF1UDLpcMvetDyz6BaWJI2WNR8zNMrcDDE6SNQ7WNg4lgDfffBP33nsvfHx8mn1P165dcebMGYcDY6wzc2TpRWsVYRHw6huLrucKIKrV8C0sQFUbqoCaiqM9pEbgaz2SYmEAtnwMMWkE1/8rmEMJ4Pvvv8fMmTMbJYCamho89dRT+OCDD5wSHGOdVXuWXrQ2GyICDbWoO3QA25DpUBzOWHpRlZByvQSQV2QenKarNPcA4gSgWA71Avrwww9RV1fXaHtdXR0++uijdgfFGLOPdc8gOVl6+1jGImRDAwgCSFcJMTdL1thY89r0rdHpdCAiEBGqqqpsSgAmkwk7d+5Ejx49nB4kY52No0sv3ijg4jmE5ucgEsDIAUPsqgZyx9KLedACAYHAlcsw/edzAOCSgAK16VsXHBwMQRAgCAIGDhzYaL8gCFixYoXTgmOss3J06cUbdb1wFt41OgBCm5ddvDEOpxuSDOz6EtBouSpIodr0rfv+++9BRJgwYQK2bNmCkJAQaZ+Xlxf69OmD3r17Oz1IV0hPT0d6ejpMJpPcoTBmN/8LZxFYWABdVAyqw6Ohi4qBpq4WABS17GIsDEBOJlQJKaDyUh4JrFBtSgC33HILAODMmTOIiorq0JM18UAwphRt6QUUcPY0NHU18D+Tj9JuPWHoEY6KsAjrgzn1fI6yNAKTSmVuG2CKZHcCyMrKQnx8PFQqFSorK5Gdnd3sexMTuajHmL3a0gtoNmrRDyYUotLpo3mdKRsaDAwM4id/hbM7AQwdOhSXLl1Cjx49MHToUAiC0GQfYkEQuFqFMRfpDREEIAomzEZdi4vBuFOTA8GqdDD98F8A3ACsVHYngDNnzqB79+7S74wxx2m1WqSmprb9g9/tBHIyUVVdg0CImDUg2vyUfW0+/ubWBWgpDme4cSBYAozmdQCu7eMEoEx2J4A+ffo0+TtjrO0cmncfAKbMhP62qfh+1QokwIieCSlQnTgGVOmAE8egSRzm/GCtNLuOweAkabEa5BUhGxoM6NrNPBZgcNK1SeJs8aIv8nOo79mHH36I0NBQ3HnnnQCA5557DuvWrUNcXBw+/fRTThCMuVgetMiDFqmD4qFy45z7ra5jkFckrRH8eXGZuXrq8y/R1AyhzlqLgDnOoZHAq1atgq+vLwDg4MGDWLt2LdasWYPQ0FCe/ZMxN1PanPtKWauYtc6hEkBRURH69+8PANi2bRtmz56NRx55BDfffDPGjx/vzPgYYwrSWtsFEcGUcwyqE8cQFj8MqYMTWjwWk5dDCcDf3x9lZWWIiorCN998Iz31+/j4NDlHEGOsfSy9bFQJKUD/QbLFYVfbxbCR5h+meA4lgDvuuAPz589HcnIyTp06JbUF5OTkIDo62pnxMeZxmmxoPXbYPLvm/u8gZv6EWBiQB22TjavWuKGVtcShBJCeno4XX3wRRUVF2LJlC7p16wYAyMjIwP333+/UAF2Fp4JgStVUQ6ulYdUfIlQAEqBCHrRIS0uT9jU1JoAbWllLBHLWihAdlGUqiMrKSgQGBsodDmPQ6/XN9rRp6mY/G3UIhAgdVObF2K1wAvBM9t7XHE4AFRUVOHToEEpKSiCK4vUDCgLmzJnjyCFlwQnAczXbp/2Gfa1Vozi7mqWluJqMLS+n2YFgXAXkmVyaALZv344HHngANTU1CAgIsPmCCYKAq1evOha1DDgBeC57nrSvQkAIqMUpF/gpmymNvfc1h8YB/P73v8fvfvc7VFVVoaKiAuXl5dJPR7r5M9YcS1/2eO7Tzjoxh0oAXbp0QXZ2Nvr16+eKmNyKSwCeq6WqFuPxo/jlyy24CgEjB8SYu182M88OV7MwpbH3vuZQL6BJkybhyJEjnSIBMM/VYp/2+KHY/OVOAMCoe+dyFQ/rlBxKAHfeeSeWLl2K3NxcJCQkNBrRd9dddzklOMYYY67jUAJYsGABAGDlypWN9vF6AKyjE3OzgGOHpcFWjHVWDiUA626fjHU2YnYGoKtEAoycAFin5lAvIGv19fXOiIMxxVAlpACBQci+4flIzM2CceN6cwmBsU7AoQRgMpnwpz/9CeHh4fD398cvv/wCAHjppZfwz3/+06kBMuZuqrhE4J45Nk//Ym4WTP/5HHS52FxCYKwTcCgBvPrqq9iwYQPWrFlj0zsiISEB77//vtOCY0wpxOwMQKMFDHpe6Jx1Gg4lgI8++gjr1q3DAw88ALVaLW1PTEzEyZMnnRYcY3IQc7OALR8jFtfGCJw8DtJVAn5doJ5yt2IWXmGsvRxqBL5w4YK0IIw1URRbnMOEsY5AzM4ASi5hEhrMG3IygbpaoK4Wph/+CwCcBFin4FAJYMiQIdi3b1+j7Zs2bUJycnK7g2JMTqqEFMBggBHmKSEQ3A2oLAfq64CSS9wGwDoNh0oAy5cvx5w5c3DhwgWIoojPP/8ceXl5+Oijj7Bjxw5nx+gSvB5A59farJpNOnkcyMmEaVACSo4cQjY06H/1ClRqNUAEqNWgwUmtLsRijaeKYErl8HTQX3/9NVatWoWMjAyIoohhw4bh5ZdfxsSJE50do0vxXECdV0uzfTbHMre+9UiXQqgRBfODwkF4tXlsAM8WytzNpXMBAeb5gCZNmuToxxlTpGxokAAjQmFCMAgqAGEQcRhaXIBamhWUB4ixzsChBNCvXz8cPnxYWgrSoqKiAsOGDZPGBTCmFNOmTYNGY9/X3Qgg8D+boNKbBzmqAdykMqE+MBACEXr5dsHgm8a3fAyjscNUhzLP5VACOHv2bJN15w0NDbhw4UK7g2LM2TQaTasJwP/CWQQWFkAXFQMV2U53QhDgVVMFg38gqqL7251MGFOyNn2Lv/zyS+n3r7/+GkFBQdJrk8mE7777DtHR0U4LjrH2sG7eMhpbX9Al4OxpeOnK0aPsCqpDusOv4irEa+NctPW1MGq9YPD2RUVYBNDK8azP5+HLbjMFa1MCmDlzJgDzjJ9z58612afVahEdHY3XX3/dacEx1h7WPYDsqY6JhQGT0AAjgJJLl7EZvoiFAaOhhw8IQk0N6mpqcWLbpja1ARgMBnh7ezvyT2DMpdqUACyzgPbt2xeHDx9GaGioS4JiTA6Wm3oCjNJEcHnQIgFGqCDCH4SGa/u5EZh1Bg5VZJ45c8bZcTDmdNYLFbW1EXjwtR8A8L14DkH5OVAbGhCk9YZhwBDM7N2n5WNYNQLfuGASY0rhcEvWd999h++++w4lJSWN1gf44IMP2h0YY+1lPfjKnkZga6FZhxBY9Avqg0MBlQBBEEBab5j8uqAuKqZNfzg8CIwplUNTQaxYsQITJ07Ed999h9LSUpSXl9v8MNbRBRb9ArVBjy4lF6CtrQEAkCBAU1cL/wtn5Q2OMSdxqATw97//HRs2bMCcOXOcHQ9jiqCL7GdTAtB3CUBg0S8gtQaBhQWoDo+WO0TG2s2hBKDX6zFmzBhnx8KYYpQmjkRp4kjpde+D34FUaggmI3RRMTJGxpjzOJQA5s+fj3//+9946aWXnB0PY4pgGRQGkeBTUQqjjx8E0QRdZD9++medhkMJoL6+HuvWrcO3336LxMTERr0c3njjDacEx5hcAgsLoK2tgXflVQCApqEeDUEh8KqpkjkyxpzHoQSQlZWFoUOHAgCOHz/uzHgYUwRdVAwCCwugrquBRt8Ao5c3DH5duPqHdSoOJYDvv//e2XEwpijV4dGoDo+2mR+Iq35YZ9OmBHD33Xe3+h5BELBlyxaHA2LMFeyaC+jiOYTm5wAASvsPQXlYOOq79UR5j3BzX347jtGW8zEmtzYlAOvJ3xjrSOyZC2g26qC6Nt9/3eED2GE1FxDg2GIwjClZmxLA+vXrXRUHY7LLhgb+19YCs8wFlAAjukGECpAWieckwDoLh5eE7Cx4ScjOy6E1ga/R6/VIS0tDLAy4u6sfBF0F4OMHREQB97RtACSvCczczeVLQjKmdIIgtHst3jxoIfToCQEAjAaok0ZAxev7sk7CobmAlKSoqAjjx49HXFwcEhMTsWnTJrlDYp3NkGQIPXtDPeVuqOIS5Y6GMafp8CUAjUaDt956C0OHDkVJSQmGDRuGqVOnokuXLnKHxjqLQfHQJA6TOwrGnK7DJ4BevXqhV69eAIAePXogJCQEV69e5QTAHCLmZkHMzgAGJ8kdCmMuJ3sV0N69ezF9+nT07t0bgiBg27Ztjd7zzjvvoG/fvvDx8UFKSgr27dvX5LGOHDkCURQRGRnp4qhZZyVmZwCVFUBOptyhMOZysieAmpoaJCUlYe3atU3u37hxIxYtWoQXXngBmZmZGDduHKZMmYLCwkKb95WVleHBBx/EunXr3BE266RUCSlAUDAwJBmxMGA26oCT5ulOxNwsGDeuh5ibJW+QjDmJorqBCoKArVu3SovPA8BNN92EYcOG4d1335W2DR48GDNnzsTq1asBAA0NDbjjjjuwYMGCVtcoaGhoQENDg/Rap9MhMjKSu4EyG3q9HhdXvYBuEOHdOwJejyyGceN6c+kgKBia+x6SO0TGmmVvN1DZSwAt0ev1yMjIwMSJE222T5w4EQcOHABg7us9b948TJgwwa4FalavXo2goCDph6uLWHN8QeYhX/V1AK6XDlQJKbLGxZizKDoBlJaWwmQyISwszGZ7WFgYLl26BAD44YcfsHHjRmzbtg1Dhw7F0KFDkZ2d3ewxly1bhsrKSumnqKjIpf8G1kGdPA5fEEwA4OMLAFDFJUJz30PcFZR1Gh2iF9CNoyiJSNo2duzYRovSt8Tb2xve3t5OjY91QjmZqIMglQLE3Cy+8bNOR9ElgNDQUKjVaulp36KkpKRRqYAxpxqSjCtQ4ypUAJG5dxBjnYyiE4CXlxdSUlKwa9cum+27du1q95rE6enpiIuLw4gRI9p1HNZJDYrHZvjiILyAwCCu92edkuwJoLq6GkePHsXRo0cBAGfOnMHRo0elbp5LlizB+++/jw8++AAnTpzA4sWLUVhYiMcee6xd5124cCFyc3Nx+PDh9v4TWCeWB600+Rt3AWWdjextAEeOHMGtt94qvV6yZAkAYO7cudiwYQPuu+8+lJWVYeXKlSguLkZ8fDx27tyJPn36yBUy80CWAWJidga3BbBOQ/YEMH78eLQ2FOGJJ57AE0884aaIGGtMlZBivvlzVRDrRGRPAIwpjZibBRw7jFgYpMVfVHGJ/OTPOh2PTQDp6elIT0+HyWSSOxQmk2YXjDl2GFRZgQQYkQct9HrzkpA4edw8R9CQZGBQvPR2XvCFdVSKmgpCDrwimOfS6/VYtWpVo+2xMCABRmRDY7P84zzUoBtElEGFDbg+22xqamq7F55hzJl4RTDGHJQHLa/7yzwClwC4BOCxWloz2HqfVMXDVUCsg+ASAGOtaG3N4EZThiQOM/8w1knIPhBMLjwSmDHm6bgKiKuAGGOdTKdYD4AxxpjrcAJgjDEPxY3AzKVa6mlz4/6WetNwTxvGnI8TAHMpg8HQ5GCrGzU3+MqCB1sx5nweWwXEvYCUIxYGTEIDusOEBBjlDocxj8G9gLgXkEu1VgWk1+txNu1P6AETgv27ABNn2AyysuAqIMbsxwPBmCK0NtgKALKhQQKA4CHJUJ04BpVGwzNvMuYGHlsFxBTi5HGp7h8VZdKiK4wx1+MEwGQj5mYBO7egL4wYDb15jp2gYF50hTE34Sog5nZibhbE7AyQrhIQTdAACIEI4PrKWwC4GogxF+MEwNzOsr4uBAEIDUPDxfOogwCfnEyYqquAq1dg0lVyAmDMxTy2Coi7gcpHlZACBAVDffMEYNQtuAoV6iCYq4AAwKP7pTHmPtwNlLuBykq/7k00XDyPMqjQ++77Ify0FwCgvnkClwAYcxB3A2Vu0Vo//9aIJF7/PTsDqtoawGCA0WgELGvx2oHHCTDWdpwAWLvYO9VDc8xTQGjM3UDzz+JO1EMN4Mrnn9qsu9saniqCsbbjBMBkdeP6u6OhRzeILXyCMeYsnACY00ybNg0ajf1fqR7Hj6DruQKYvLxQPGgoqiOiYSouhL7oDEyRfTGzd58WP280GrFjx472hs2Yx+IEwJxGo9HYlQD8L5xFYGEB/C5fhMpkhMqoR2T2IRjzjkEAYPLyhlqtblMyYYy1Hf+FsXax7kRmNNo3k2fA2dPw0pVDZTK/XwBAogletdUgAOqGegScPY2KsIgWj2N9Pg/vzMaYQzgBsHax7gFkb3XMBNRjOAwwAFAD0ANQG02oBWCAgDrRhIPFV5C3bVub4vD29m5L6Ix5PI9NAOnp6UhPT4fJZJI7FI8TAkI1BPiDYALgBcAA4CI02AxfmaNjzHN4bAJYuHAhFi5cKA2YYI7Raq/34LG3Edj34jmoi86goos/upSVQFWtg5fJiJ49wjBz1AS7z23dCGwdB2PMPh6bAJhzWA++srcRuC4qBmq1GoGFBSgflIiwjB8gEMG/9DKiDu+BLioG1eHRDsfBGLMPJwAmi8DCAnhXXEWPq1dAKjVIECCQCL8rl6Cpq21zAmCMtZ3HTgbH5KWLioHKoIfaYICo0aAhuBtIUEEQuU2GMXfhBMBkUR0eDYO/eZIqjb4BAGDy8YVJ64WrsQlyhsaYx+AEwGRzNTYBpFIBogkqfQMagrqiZOgorv5hzE24DYC5nWUksC4qBnr/QHhV6yB6eePi6NvkDo0xj8IlAOZ2gYUF0NbWILCwAFdjE1DbvSdX+zAmAy4BMKexdyqI8vBoBBedQUV4NHQ9wlHarScAQG0wtKk7p73nY4w1jRMAcxp7p4IwrwFgxNXiSwjBAZyERpoS2rIv22obY8w1OAEwt0uAEYEQEQURagBRMD/J50Er7UuAkRMAYy7msWsCW88FdOrUKV4T2EEOLQl58jiQkwmUXAJ0FTCYRJyBBv3uugeaIz+Y3zPqFmBQvN2H5CUhGbvO3jWBPTYBWPCi8PIRc7Ng3P8dLl68iEKoMcrfBwIRoBKgnnI3LwrPmIPsva9xLyAmG1VcIjBvITagC0JAgFYLNNQDWi+I2Rlyh8dYp8cJgClCNjRAj54QYmIBgx5C11C5Q2Ks0+MEwOR18jhmo878+z1zAJUAISAIVF4qb1yMeQBOAExeOZlSrx8AUCWkAEHB5v8yxlyKu4HaqbXeLtb7W+uRwj1WrAxJhi7vFLKhwUCY2wW48Zcx9+AEYCeDwYBVq1a1+j57BjKlpqbCy8vL2SF2TIPisRlfyh0FYx6JE4CTyTGQqTOUTmJhALZ8DDFpBJcAGHMTTgB20mq1SE1NbXrnyeMQszOwNf8ssqHBrAHR6JmQgtRmBjI5e/3alkonbZ1aQa7SSQKMgK4SYnYGJwDG3IQTgJ0EQWj2xmg8cQyorkICjNgMX6junauYKp4EGNEdJkyCeaUtxU2vcK0X0FUIgCCAdJUQc7M4CTDmBpwAnECVkALx2GFkF5eZN5w8DuOJY1AlpLjlRtZs6eTkceDHPcDVUlTUNyABRkx/dlmLycnZpZNWXesFBKiAgEAIVTouBTDmJtwN1AlUcYnAPXOuP13nZAKVFW4bzWopndz4ozpxzPw/2NcPGgBX0fT7rH/cXv8/JBk6qMwDwYYkcxdQxtyISwCuMCQZuFYCkJMqIUVKQtXlFebpFpTGuhfQoHhoEofJGw9jHoQTgCs4+Ubm0IybANB/ENB/EIzHj0L35RZkQ4Novd7hOBzpIdRa7HqrePQtxMZjJxhzPk4AznKtMTPbBZfU3jEIN7LuAQRokAAjtqetdrgh2JEeQm2JfXvaaoyGOQkchJdNnDx2gjHn89gEYL0egIXDT9onjwPffIEeMCEBLT/J2sNZT7vWYxIAKH6hlQQY0Q2i9LtS42Sss+D1AKzmzfbx8XHoSXs26tAdJmgBfA3vdt+4bnza1ev1UlzTpk2DRmNf3g64eM689m5EX4iiiK4XzqIysh+qwvvYHYvRaJSWenTkKbxNg9QK8iD8tNe844YFYbgKiDH72bsegMeWAJwpGxokwNzLZjT0GA19oyoMZ9FoNHYngLqoGNRFxUivL/UdYD6G06NqXkvjJyy8vb3NvySlmH8YY27BCaAZbXnSBgADEeJ+2o0uZZchAJgY2h2Dbxpv9+etn7QZY8wdOAFYcbQ2zFLV0uAfAG2DeW77isi+bo+DMcbaghOAFeu66rY8jc9DDXwgwhtAKVTm6p9DmQAyHY5DqhZxkP+FswgsLIAuKgbV4dGNXjPGGI8EdhI1AC2Abla9buQUWFgAbW0NAgsLmnzNGGNcArBiPQ9OW9oATBfPoSE/B2p9A0Qvb/gOGIKZve3vaQPYtgE4Yz4eXVSM9MTf1GvGGOMEYMW6m2Fbe9uUq9XSDbYuPLpdF9YZ3R2rw6NtqnpufM0YY5wAnKSpKhc569u5zp8x1hpOAM0wGu2vxw+4eA7q2hqYiFDWMwohZ09DU1eDgLOnUREW0e7zWfcKsjeuAAdiaC0u7p3EWOfCCaAZbekFNBt1qIRontY44whuRQN8QKitKMeJbZvaPSDMkd5J0jxAFbXI27bNdpudq4M1FUd7eycxxpSDewE5QTY00pz2CTCiCwhqAF1AsvUIyoMWm+ELwJygYmHAaOjRB0ZpwjXGmGfjEoCVFtf9bYVer8fmtDQAQP9ePaBqaIC3jy8Gjrql2bWBW4qjuddtHaEc+dNuaOtqECkI8KoxQRAFdA0Ixsxbptr1eWf3TmKMKQcnACv2zFvTmjxooXroKadOXexo7yQAqIruj8DCAmjqaiFqvSGIJpQPSmzTMZqKgzHW8XEC6GDa0jgNABVhESjvEQ7/82fRvSAXgiDAZDLZfZy2no8x1nFwAnAhMTfLvMC5ExeHb8+EcbNRh0CIUB/aDw0OONwYzBjrHLgR2IXE7Ay3Lg5/o1gYpAZg4HpjNQCbhWIYY56JSwAuZFmUvb2LwzvcOL3lY0BXif7+Afhz/gXkQYvpzy6D1y+ngJxM9ByS3KYGam4EZqxz4QTgIs6s/nG0cVpMGmEufQxOAvIvIBYGeG3fCE3SCKjuf7hdMTHGOj6uAnIRuat/AEAVlwjNfQ9JSysmwAjoKmWNiTGmHJwAXESVkAIEBbe7+seZsqEBAoMUFRNjTD6dIgHMmjULXbt2xezZs+UORWJ5+nZW7x9nyIMWuGcOAMC4cT3E3CyZI2KMyalTJICnn34aH330kdxhdBhKqJ5ijMmvUzQC33rrrdi9e7dLz0FENpOy3Uiv1zf5e1O0Wq2so2qd1TuJMdaxyZ4A9u7di9deew0ZGRkoLi7G1q1bMXPmTJv3vPPOO3jttddQXFyMIUOG4K233sK4cePcGqfBYMCqVaua3W/uc2+eaTPt2pxAzUlNTXXqVBFtpYpLVFTVFGNMHrJXAdXU1CApKQlr165tcv/GjRuxaNEivPDCC8jMzMS4ceMwZcoUFBYWOnS+hoYG6HQ6mx9nSICRB1cxxjoU2UsAU6ZMwZQpU5rd/8Ybb+Dhhx/G/PnzAQBvvfUWvv76a7z77rtYvXp1m8+3evVqrFixos2fa20wFp3IBh3/GaGDk7BsSFKLVTxyDKiyrAWAk8eBxGFuPz9jTHlkLwG0RK/XIyMjAxMnTrTZPnHiRBw4cMChYy5btgyVlZXST1FRkV2fswzGau7HOykFPg8sgN+wkfD29m7xvXLU/1tKKMjJdPu5GWPKJHsJoCWlpaUwmUwICwuz2R4WFoZLly5JrydNmoSff/4ZNTU1iIiIwNatWzFixIgmj+nt7e2Rq1pZFqvpOSRZ7lAYYwqh6ARgceMTMxHZbPv666/dHVKHkwct8qBt8+I0jLHOS9FVQKGhoVCr1TZP+wBQUlLSqFTQVunp6YiLi2u2pMAYY52dohOAl5cXUlJSsGvXLpvtu3btwpgxY9p17IULFyI3NxeHDx9u13EYY6yjkr0KqLq6GqdPn5ZenzlzBkePHkVISAiioqKwZMkSzJkzB8OHD8fo0aOxbt06FBYW4rHHHpMxamXpTIPUGGPuIxARyRnA7t27ceuttzbaPnfuXGzYsAGAeSDYmjVrUFxcjPj4eLz55pv41a9+5ZTz63Q6BAUFobKyEoGBgU45prvp9foWB6kB17uBtrYKmNyD1Bhj7WfvfU32EsD48ePRWg564okn8MQTT7gpos7JeqAaLwPJGAMUUAKQS3p6OtLT02EymXDq1KkOXQJorQqIiGDKOQbViWMQ4odBGJzQ7Hu5Coixjs/eEoDHJgCLzlAFxBhj1uy9rym6FxBjjDHX4QTAGGMeihMAY4x5KI9NADwSmDHm6bgRmBuBGWOdDDcCM8YYaxEnAMYY81CcABhjzENxAmCMMQ/lsQmAewExxjydx/cCqqysRHBwMIqKirgXEGOsU9DpdIiMjERFRQWCgoKafZ/ss4HKraqqCgAQGRkpcySMMeZcVVVVLSYAjy8BiKKIixcvIiAgoN2zYFqyrhJLExxb2yk1LoBjc5RSY3N2XESEqqoq9O7dGypV8zX9Hl8CUKlUiIiIcOoxAwMDFfXlssaxtZ1S4wI4NkcpNTZnxtXSk7+FxzYCM8aYp+MEwBhjHooTgBN5e3tj+fLl8Pb2ljuURji2tlNqXADH5iilxiZXXB7fCMwYY56KSwCMMeahOAEwxpiH4gTAGGMeihMAY4x5KE4ALqLX6+UOgTHGWsQJwAWOHTuG1NRUlJWVyR0KY4w1ixOAkx07dgzJycnw9vZGt27d5A6HuYEoigCUWeprqpc39/xmFpwAnCg3NxejR4/Gn/70J7z66qtyh9Mur776Kt599125w5BYbrJKI4oiVCqVVOorLS2VOySJKIoQBAHl5eW4cOECTpw4AQAQBEG2JKD05HPj98xkMskUiZl1PK6IhROAk+Tk5GDcuHGIiorCsmXLAMj/5XGUKIq4cuUKvvzyS1RUVMgdjnSTvXDhAjIzMxVzE7G++VtKfaGhoXKHBeB6bMePH8ddd92FiRMn4s4778RLL70EAO2e+dbRmCwJSYnVo5ZrdurUKbzyyisAALVaLdvfsSWec+fOoaSkxDWxEGu3zMxM8vX1pREjRtAtt9xCCxcupMrKSiIiMplMMkfnmG3btlFERARlZGQQkXz/DlEUiYjoxIkT5OvrS0OHDpVikpPlemRlZZGvry8tW7bMZn9dXZ0cYRHR9Wt2/PhxCg4Opueee462b99Of/nLX6h///5UWFjo9pgs1ysnJ4fi4+PplVdeoStXrrg9juZYrll+fj6FhYWRl5cXLVq0SNpvNBpliefkyZOk1WqpZ8+edP78eafHwgmgnY4ePUpdunShl19+mYiIXn31VRo1ahQtXLiQdDodESk7CVi+aDf+TkQ0Y8YMmjx5stu//De6cuUKTZgwge677z6KjY1VTBI4c+YMCYJA8+bNk7a9+OKLNG3aNJo0aRItX75c2n7jtXW14uJiSkxMpOeff17advz4cbrtttvo+PHjdOTIEbfGQ0RUWFhIycnJ1Lt3bxowYAC9/vrrikoC5eXlNHv2bJo1axYtX76c4uPj6amnnpL2u/vv4PLly3T77bfTHXfcQePHj6f+/ftTUVGRU2PhKqB2uHz5MoYNG4ZHH30UK1asAAA8++yzmD59OjIyMrBs2TJUVVVBpVIpsg7bUiQHgLS0NLz77rs4fvy4tP+hhx7C5cuXkZeXB0C++tvz588jJiYGS5YswdGjR1FfX4+HH34YP//8syzxWAQHByMoKAglJSXIysrC2LFjsW/fPkRERGDgwIF488038Zvf/AaA+6tcjEYj7rjjDjzwwAPSts2bN+PQoUOYNWsW7rrrLtx5551ua7gmIuzbtw89e/bEnj17MGvWLLz99tv46KOPFNNu4uvri969e+OBBx7AokWL8NBDD+H777/H008/DcD91UEnTpxA165d8Yc//AFr1qxBVFQUbr31Vpw/fx5qtRpGo7H9J3FKGvFQ586do4SEBLr//vtJr9dL2/V6veJLAtZVFNXV1bRkyRK6+eabqXv37rRy5Uo6dOgQERElJCTQM888I1OUZrW1tXTs2DHp+tXU1NCgQYNo6NChNk+y7nxCs5zrypUrFBERQYIg0K9//Wu6dOmS9J5du3aRn58fbdiwwW1xWauoqJB+X79+PYWEhNDGjRspOzubsrKyqFu3bvTiiy+6LZ6zZ8/Sf/7zH+n10qVLqU+fPvT6669TSUlJo/e78+/FUkKrr6+XtpWWllJaWlqjkkB9fb3N37sr7d+/X/r9xx9/pAkTJthU41m+h45eK04ADhJFkYxGI73xxhuUmJhIX3zxBRFd/x9iMBikJPD0009LbQJKsGPHDlq7di0RES1YsIBSUlKIyFxEX79+PaWkpFB8fDw9+OCD9Pzzz1P//v0pOzvbLbHdWFVy4+uGhgYiMicF6+qg+vp6evXVV+ndd991SVzWf2DW/4+JzElg2rRptG3bNpvPlJeXU79+/Wj16tUuiaml2G60fft2+vHHH222TZ06lX73u9+5NLbWPPfcc1ISsFQHrVu3ji5evOjS8zZ1zay/a5ZtV69epddee80mCTzyyCP0+OOPu7Rar7kb+k8//SQlAUt10MqVK+n777936DycANqorKzM5nVFRQUlJyfTpEmTpG2WpwODwUB//vOfadCgQbR06VK31wM3Z/78+RQREUG33347hYaG0rFjx4jo+h/AxYsX6cCBAzRhwgSKiYkhQRDovffeIyLXPpVZjn316lUqLS1t9n2WG29tbS0NGjSIUlJSaNasWaTVaiknJ8dlcZ09e5YuX75MRI2TQH19faOG3/Lycho3bhz9+9//JiLXtAO0FFtL9Ho9zZgxg15//XWXxdYcy8OThSUJpKWl0bx58yg4OJh++eUXl53f3mtmuSZXr16ltLQ0SkpKov79+5O3tzf99NNPLourtX2WJDBo0CCaO3cuCYJAubm5Dp2TE0AbFBQUUEhICE2fPp2Ki4upurqaiIgyMjLI19eX/vznP0vvtXyh9Ho9vf7663TmzBk5Qm7WiBEjSBAEeuGFF6QvlyiKjW4Ehw8fpscff5wiIyOlPxZXaGsvEcuNt6KiggRBoJCQEMrMzHR6XPb0xmju5vnCCy9Qv379XNbrpj09RV588UWKjIykgoICl8RmNBqlGPLz8yk/P9/mXDcmgaVLl5IgCBQQEEA///yzS2KynJeo7dfs0qVLlJycTCEhIU4vDVtX1RGZ7ycff/wx7dmzh2pqaqTt1vH98MMPFBgY2O7vPSeANjh16hQFBweTIAg0ceJESktLk56ely5dSsnJyXTgwAHp/Uqq87eor68nnU5Hv/3tb+nee++lAQMG0Nq1a6UvoeVLZv1ly83NpaSkJNq9e7dLY2trL5Ha2lpauHAh+fn5ueTJ36KtvTH27dtH8+bNc1lSak9sP/zwAy1YsIBCQ0NdcqNNS0ujTz/9VHr92WefUa9evahPnz40ePBg+vDDD6V91klg8eLFFBIS4tL/jxZtvWZ6vZ7+8Ic/kLe3t/T37ixvv/02Pfroo3T69GkiMne/9vHxofj4eBIEgZ544gmb/0+W+BYuXEje3t50/Pjxdp2fE0ArLE8MlifOv/71r7R48WJ68cUX6bHHHqPk5GTavn07/fTTTzRkyBCpO6iSbv4txTJ//nyKiYmh9PR0Ki8vl7bfWNUVHR0tVQO5giiK9Mknn9CUKVMoPz+/ybrhG507d45uu+02lxTHre3evZvuvfde+u677+jQoUON6mAt3w0ic3XB+++/TzNnznRLu0lbY/voo4/o/vvvb/eNoynl5eX04IMPkq+vL33xxRdkMpmoT58+9P7779O2bdvo+eefJ5VKZdNOI4oiffHFFyQIgtu6prblmhGZH5oee+wxlyTzv/71r9SjRw/6/e9/T4cOHaKpU6fSunXrqL6+nrZs2SJV81hfmx9//JFGjx7tlK7QnABaUVVVZfN69+7dNHnyZNq5cyfV1dXR2rVrKTg4mF577TWaNGkSBQcH09GjR2WKtjHr6ol169bRY489RsuXL7d5SluwYAENHDiQ3njjDcrPz6cJEybQ+PHjpf2ff/45BQQE0MmTJ10aa1t7iej1eqqtrXVpTBb29MawXOvq6upG3xulxFZXVydVXbpCfn4+PfXUUxQUFER/+ctfaPHixdK+8vJyWrFiBQmCYJMEDAaDyxt9b2Rv7xpLMnB2G4l1SeK9996jiIgIWrJkCd1zzz023/Uvv/yS4uLi6MEHH7S54V+9etUpcXACaEFxcTFFRkZSamoqnTt3Ttr+pz/9iUJDQ6W6w/3799OCBQvozjvvJEEQaOrUqTZ/dHKxPv+LL75I/v7+NHPmTBo9ejSFhobSk08+Ke1fuHAhDRgwgPr160cjRoyQetsQER04cMBldcWtaa6XyIULF9xy/rb0xlixYoXDvTE6cmxvvvmmzQPD6dOn6amnniJ/f38aN26czXstSUCr1dIbb7zhknha4mjvGmf+LW/atImSkpLo/fffl7b9/e9/p65du1JwcHCjktD27dspKSmJZs2a5fRSEieAFli+rMHBwXTbbbfRm2++Ke2bO3cuzZ07V6o7v3z5Mu3Zs4emTZvm9HrC9jp06BDNmDGD9u7dS0Tm6p0PP/yQ/Pz86Nlnn5Xet3fvXvrmm2+kpx/rJOBOSukl0to+Z/bG6MixffXVV9S1a1e6++67pW15eXn0zDPPkCAItGXLFpv3l5eX0/PPP0/BwcFUXl7u8gclpV2zc+fO0bRp02j8+PE2SeCTTz6h7t270xNPPCG1CVhs2bKFRo0a5fQHH04AdsjJyaHZs2dT//79afz48XTy5En67LPPaO7cubRr1y6b98r91H+jDz/8kG6//XYaMWKETV16XV0d/e1vf6PY2NgmGwNdPahKib1E5OyN0ZFjM5lMtHv3burVqxfNmDFD2l5QUECPP/44BQQE0Oeff27zmYqKCpdPA6HEa2apUiotLaW7776bJk6cSB988IG0/7333qPw8HBasmRJo1K3K6ruOAHYqaysjLZv307JycnUr18/+sMf/kApKSn0yCOPyB1ai/73f/+X4uLiyNvb26Z+nYjo559/puDgYPr222/dFo9Se4nI3RujI8YmiqL0BJ2bm0v//Oc/SRAEmjt3rvSegoICWrhwIQUGBtLWrVtdEkdTlHrNLNeroKCA/vznP1OvXr0oISGBPv74Y+k969ato/DwcFq6dCmdOnVK2u6Kh0tOAA5YtGgRTZ48mcLDw20GScmtuaLuf/7zH0pKSqLp06dL1UBE5mqr/v37u+0PU8m9ROTujdFRYyMi2rx5M0VFRdGjjz5KCQkJpNFoaObMmdL+06dP09NPP02CIND27dtdHg+Rsq/Z1q1bycfHh55//nlauHAh9enTh0aMGGFTEnj//ffJx8eHXnjhBZdOO8EJoA2sM/D3339Pzz//PAUEBNCJEydkjMrMOratW7fSv//9b5t++59//jmNGDGCbrrpJvrb3/5GmzZtomnTplFcXJxb59BRWi8RpfTG6GixWZw5c4a6d+9Of/3rX4nI/P9w8+bNFBoaapME8vLyaOnSpS7vSabkayaKIl25coWGDRtGK1eulLYXFRXR5MmTadiwYTYlgQ8//NCmBOAKnADa6MZimJLm+CEyN5iGhoZSz549aejQoTaTWG3bto3i4+NJpVLR9OnT6cUXX2xy4JezKbWXiJJ6Y3Sk2KxlZmZSeHi4TWNpQ0MDbdy4kQRBoPnz50vbXT2BmhKvmXU1GZH5YSYxMZH+8pe/ENH1v7vz589TREQEDR8+nN555x2XxNIUTgAdnPU0DhcvXqTbb7+dsrOz6ezZs7RmzRoaOnQoPfTQQ9L7/+///o+GDx9OjzzyCB08eNDmGK6i1F4iSuqN0ZFis3blyhUKCQlpdNO6fPkyDRgwgARBoN/85jduiUUp18zyfbVuhN69ezd9++23VF9fT2PHjqWHH36YiMx/e5Yk8D//8z8UEhJC99xzj82gTFfiBNCBWd+4S0tL6cSJE3TnnXdKXzydTkdvv/02JSUl2cz6+Nlnn9HIkSPpgQcesGkTcGWcSuslorTeGB0lthvV1NTQI488Qrfddhv93//9n7S9vr6eHnroIdq8eTPl5+e7PA6lXbOSkhIKDQ2lzZs3044dO8jLy0vqhPHVV1+RIAiUlpZm85knn3yS3nnnHWl8kTtwAugEXnzxRYqJiaFRo0ZRfHy8zT6dTkd/+9vfaNiwYTZ1stu3b6cBAwbQ/PnzXbZ8oZJ7iSitN4bSY7McNyMjgz799FN67733pNHOP/30E02cOJFuueUWSktLo4MHD9LixYspJibGZn0EV1LCNbuxqmfNmjXk7e1NGo2GPvvsMyK6XuWzdu1aEgSB/ud//odSU1Pp0UcfpYCAALcv18kJoAOy/qJ98sknFBYWRu+++y49+eSTFBISQnfddZfN+6uqqmj16tU0d+5cm3lOdu7c6dIBVRZK7CVCpKzeGEqOzXKD3LJlC4WHh1NSUhIlJCRQeHi41JXyyJEj9PTTT1O3bt2ob9++1LdvX5fO6tkUOa+Z5W+ysLCQ3nvvPXrrrbdo+fLlJAgCqVQq2rhxIxHZJptvv/2WJk+eTGPGjKFbb73V5RMHNoUTQAe2efNmWr9+PX300UdEZJ4dc9OmTRQdHW1T327Zd+PEdu6gtF4iRMrsjaGk2JpqE9q9ezcFBQVJdes5OTkkCAL16dPHphqxvLyc8vPzW1zPwdnkvmaW63Xs2DGKjo6mpKQk6tq1K0VFRdHs2bPp/fffJ0EQpDEu1vX+ls+6u+rOghNAB1VUVET+/v4kCAK99dZb0nZLEujbty/Nnj270efcPVJZKb1ElNwbQ0mxNfUku23bNvrHP/4h3VwLCwspKiqKFixYQNOmTaNevXrZTIPuDkq5ZtY3fz8/P3r++efp6tWrtH//fpo3bx6FhobSnj176KWXXiJBEOhf//qX9NmPP/6Y/vvf/0r/HjlwAuggmnoq27NnD6WkpNDNN99s042zrq6OtmzZQj4+PpSamurOMBuRs5eIkntjKDG2G59kk5OTpWkR7r33Xjp//jxVVlbSqFGjpBHwBw8eJEEQKCgoSOpV5ipKvGZE5oQYGhpK9957r832rVu3UkBAAB06dIj0ej299NJLpFKp6IUXXqAnn3yS/P393VaybA4ngA7A+ua/fv16eu6552jRokX02Wef0Z49eyg2NpYmT55s85na2lr6/vvv3TrIqyly9xJRcm8MJcXW3JPswYMH6aGHHqJevXrR8ePH6eDBgzR8+HBprYMjR47QfffdR3PmzHFL9Z2SrpnFmTNnaMSIEXTXXXfRvn37pO0//PADBQUF0aFDh4jI/GD29ttv0+DBg+mWW25xextJUzgBdCBLly6lsLAwWrx4Mc2ePZsGDhxITz/9NO3du5d69epFU6dObfJz7kgCSuolouTeGEqOraUnWX9/f/rpp59o69at5OXlRWfPniVRFOmll16i2bNnu7T6TsnXzOLUqVM0efJkmjhxIuXm5pJOp6MePXrYzLZrUVpaqpgBpBqwDuGbb77Bli1b8OWXX2LkyJHYtGkTtm/fjlGjRmHcuHH47LPPMHfuXIwYMQKHDx+2+axarXZpbEQEQRDw+eef4+mnn0ZoaChEUcQf//hHbN++HSNHjsSqVavw0UcfYfXq1QgMDAQAbNmyBWFhYU6NRRRFqFQqFBUV4euvv0ZNTQ1qamqg1+shCAKICACgUqkAAAsXLsSgQYOQlpaGX375Bd7e3ti7dy8iIyOdGpfSYwMAk8mEvn37oqGhAfv378fYsWMBAD169IBarYZWq8WMGTMwfPhwDB48GAkJCThx4gT27t0LrVbrkpiUfs0sBgwYgLfffhvPPPMMHn/8cWRlZWHu3Ll47bXXbP4dANCtWzeXxtIm8uYfZq/169dL0yls2rSJAgICpPly6urqpLrQmTNnunxkr1J7iSi5N4aSY7Nmz5OsTqejNWvW0BtvvEF5eXkui6WjXDNrp06dogkTJlCfPn1oz5490nalTRNvwQlA4SxfnL///e/0m9/8hnbu3En+/v42k6Vt27aNUlNT6fLly9I2VyUBpfYSUXJvDCXH1pRTp07RlClT6JZbbqGuXbvSokWLpH3ualPqaNfMWn5+Pk2ePJkmTZpks/SkEnEC6CBycnJIq9WSIAi0fv16aXttbS1NmjSJfve737lthKpSe4kouTeGkmNrihKeZDvaNbN26tQpmjZtGo0aNcrl3/v2UMldBcXsExcXh3/+85/w8fHBiRMnsHv3bnz//feYMWMGiouL8Y9//MOmTtTZLHWYWVlZGD16NO677z589913+PrrrzFjxgzs378fFRUVyM3NhdFoxFNPPQUA0Gq1+PWvf4277roLXbt2dUlsFjfWYVv06NFDqn/VarVITU3FW2+9hc8//xzZ2dnYu3cvBgwY4LGxNWXAgAH4xz/+gcGDB2PVqlX44YcfAACCILgtho52zawNGDAAr732GiIiItC7d29ZY2mR3BmI2c9gMNCnn35K4eHhFB4eTikpKTR9+nSpB4ari+dK7SViTcm9MZQcW3PkfpLtiNfMmlzratuLE0AHVFJSQqdOnaLCwkK3Tu/QWn/nn3/+mURRpDFjxpCvry+NHDmSAgIC3D7HSUt12K5uIG+NkmNrzokTJ2j27Nl07tw5Wc7fEa9ZR8EJoBNw5x+BknqJtBan3HXYzVFybM2R+0m2I16zjkAgclGlMeu08vPz8cwzz6C2tlbq7/zmm28CMNfbunrcgb1Onz6Np556CkSEl156CTfffLPcIUmUHJtS8TVzPm4EZm02YMAA/PWvf4VarUZgYCBmzZol7bM0zilB//798fbbb0Or1eLZZ5/Fjz/+KHdIEiXHplR8zZxPOX+trENRQi8Reyi5N4aSY1MqvmbOxVVArF3y8/OxZMkSlJaW4s0338SoUaPkDqlJer0eXl5ecofRJCXHplR8zZyDSwCsXTrKE5mSbxZKjk2p+Jo5B5cAmFPwExljHQ8nAMYY81BcBcQYYx6KEwBjjHkoTgCMMeahOAEwxpiH4gTAGGMeihMAY4x5KE4AjDHmoTgBMCaDs2fPQhAEHD16VO5QmAfjBMAYYx6KEwDzOFVVVXjggQfQpUsX9OrVC2+++SbGjx+PRYsWATBPa/Hcc88hPDwcXbp0wU033YTdu3dLn9+wYQOCg4Px9ddfY/DgwfD398fkyZNRXFwsvUcURaxcuRIRERHw9vbG0KFD8dVXX0n7+/btCwBITk6GIAgYP3489u7dC61Wi0uXLtnE+/vf/x6/+tWvbM69bds2DBw4ED4+PrjjjjtQVFRk85nt27cjJSUFPj4+6NevH1asWAGj0ejMy8g6A5kWomFMNvPnz6c+ffrQt99+S9nZ2TRr1iwKCAigZ555hoiIfvvb39KYMWNo7969dPr0aXrttdfI29ubTp06RURE69evJ61WS7fffjsdPnyYMjIyaPDgwfTb3/5WOscbb7xBgYGB9Omnn9LJkyfpueeeI61WKx3j0KFDBIC+/fZbKi4uprKyMiIiGjhwIK1Zs0Y6jsFgoB49etAHH3xgc+7hw4fTgQMH6MiRIzRy5EgaM2aM9JmvvvqKAgMDacOGDVRQUEDffPMNRUdH0x//+EeXXlfW8XACYB5Fp9ORVqulTZs2SdsqKirIz8+PnnnmGTp9+jQJgkAXLlyw+dxtt91Gy5YtIyLzTRgAnT59Wtqfnp5OYWFh0uvevXvTq6++anOMESNG0BNPPEFE5vWVATRaL/kvf/kLDR48WHq9bds28vf3p+rqaptz//jjj9J7Tpw4QQDop59+IiKicePG0apVq2yO+/HHH1OvXr3su0jMY3AVEPMov/zyCwwGA0aOHCltCwoKQmxsLADg559/BhFh4MCB8Pf3l3727NmDgoIC6TN+fn6IiYmRXvfq1QslJSUAAJ1Oh4sXLzZasvDmm2/GiRMnWoxv3rx5OH36tLTa1QcffIBf//rX6NKli/QejUaD4cOHS68HDRqE4OBg6dgZGRlYuXKlTfwLFixAcXExamtr23S9WOemkTsAxtyJrk1+e+PKZZbtoihCrVYjIyOj0drG/v7+0u9ardZmnyAI0jGst914jtZWTOvRowemT5+O9evXo1+/fti5c6dN+0Nzx7beJooiVqxYgbvvvrvRe3x8fFo8P/MsnACYR4mJiYFWq8WhQ4cQGRkJwPzEnp+fj1tuuQXJyckwmUwoKSnBuHHjHDpHYGAgevfujf3790uNtwBw4MABqeRhWTvBZDI1+vz8+fPxm9/8BhEREYiJiWlUkjAajThy5Ih0rLy8PFRUVGDQoEEAgGHDhiEvLw/9+/d3KH7mOTgBMI8SEBCAuXPnYunSpQgJCUGPHj2wfPlyqFQqCIKAgQMH4oEHHsCDDz6I119/HcnJySgtLcV///tfJCQkYOrUqXadZ+nSpVi+fDliYmIwdOhQrF+/HkePHsUnn3wCwPyk7+vri6+++goRERHw8fFBUFAQAGDSpEkICgrCK6+8gpUrVzY6tlarxVNPPSUtkP7kk09i1KhRUkJ4+eWXMW3aNERGRuLee++FSqVCVlYWsrOz8corrzjpSrJOQdYWCMZkoNPp6Le//S35+flRz5496Y033qCRI0fSH/7wByIi0uv19PLLL1N0dDRptVrq2bMnzZo1i7KysojI3BAbFBRkc8ytW7eS9Z+TyWSiFStWUHh4OGm1WkpKSqL//Oc/Np957733KDIyklQqFd1yyy02+1566SVSq9V08eJFm+2Wc2/ZsoX69etHXl5eNGHCBDp79qzN+7766isaM2YM+fr6UmBgII0cOZLWrVvXnsvGOiFeEYx5vJqaGoSHh+P111/Hww8/LHc4AIAFCxbg8uXL+PLLL222b9iwAYsWLUJFRYU8gbFOhauAmMfJzMzEyZMnMXLkSFRWVkrVLDNmzJA5MqCyshKHDx/GJ598gi+++ELucFgnxwmAeaS0tDTk5eXBy8sLKSkp2LdvH0JDQ+UOCzNmzMChQ4fw6KOP4o477pA7HNbJcRUQY4x5KB4IxhhjHooTAGOMeShOAIwx5qE4ATDGmIfiBMAYYx6KEwBjjHkoTgCMMeahOAEwxpiH+n88IsvVLNnT7AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4,4))\n",
    "sns.boxplot(data=data, x='genotype',y='Length', color='lightgray',order=[\n",
    "    'WT','empty','Padh11','Ptdh15','Ptdh13','Padh1','Ptdh11','Ptdh1'\n",
    "])\n",
    "sns.stripplot(data=data, x='genotype',y='Length',color='salmon',alpha=0.8,size=2,order=[\n",
    "    'WT','empty','Padh11','Ptdh15','Ptdh13','Padh1','Ptdh11','Ptdh1'\n",
    "])\n",
    "plt.xticks(rotation=45)\n",
    "plt.ylim(0,25)\n",
    "plt.savefig('Length.pdf')\n",
    "plt.savefig('Length.jpg', bbox_inches='tight',dpi=300)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(4,4))\n",
    "sns.boxplot(data=data, x='genotype',y='Intensity', color='lightgray',order=[\n",
    "    'WT','empty','Padh11','Ptdh15','Ptdh13','Padh1','Ptdh11','Ptdh1'\n",
    "])\n",
    "sns.stripplot(data=data, x='genotype',y='Intensity',color='salmon',alpha=0.8,size=2,order=[\n",
    "    'WT','empty','Padh11','Ptdh15','Ptdh13','Padh1','Ptdh11','Ptdh1'\n",
    "])\n",
    "plt.xticks(rotation=45)\n",
    "plt.yscale('log')\n",
    "plt.savefig('Intensity.pdf')\n",
    "plt.savefig('Intensity.jpg', bbox_inches='tight',dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "24682e75-036c-4066-8e1b-2daf8498e3ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4,4))\n",
    "sns.scatterplot(data=data,x='Intensity',y='Length',hue='genotype', size=2, alpha=0.8)\n",
    "plt.xscale('log')\n",
    "plt.legend(fontsize=\"8\", frameon=False, ncol=2,loc='lower right')\n",
    "plt.ylim(0,25)\n",
    "plt.savefig('Intensity_vs_Length.pdf')\n",
    "plt.savefig('Intensity_vs_length.jpg', bbox_inches='tight',dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "4c2eccc5-3164-40cd-b95b-7a7ee924466b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "91.744589482624\n",
      "2.894152934065373e-62\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Multiple Comparison of Means - Tukey HSD, FWER=0.05</caption>\n",
       "<tr>\n",
       "  <th>group1</th> <th>group2</th> <th>meandiff</th>  <th>p-adj</th>  <th>lower</th>   <th>upper</th>  <th>reject</th>\n",
       "</tr>\n",
       "<tr>\n",
       "   <td>Padh1</td> <td>Padh11</td>  <td>-0.5049</td>  <td>0.379</td> <td>-1.218</td>  <td>0.2082</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "   <td>Padh1</td>  <td>Ptdh1</td>  <td>3.5888</td>    <td>0.0</td>  <td>2.8876</td>   <td>4.29</td>    <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "   <td>Padh1</td> <td>Ptdh11</td>  <td>2.4379</td>    <td>0.0</td>  <td>1.6874</td>  <td>3.1884</td>   <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "   <td>Padh1</td> <td>Ptdh13</td>  <td>-0.2318</td> <td>0.9963</td> <td>-1.2126</td>  <td>0.749</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "   <td>Padh1</td> <td>Ptdh15</td>  <td>-0.0203</td>   <td>1.0</td>  <td>-0.7303</td> <td>0.6896</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "   <td>Padh1</td>   <td>WT</td>    <td>-0.6863</td> <td>0.3949</td> <td>-1.6671</td> <td>0.2945</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "   <td>Padh1</td>  <td>empty</td>  <td>-0.3518</td> <td>0.9577</td> <td>-1.3326</td>  <td>0.629</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Padh11</td>  <td>Ptdh1</td>  <td>4.0937</td>    <td>0.0</td>  <td>3.3957</td>  <td>4.7916</td>   <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Padh11</td> <td>Ptdh11</td>  <td>2.9428</td>    <td>0.0</td>  <td>2.1953</td>  <td>3.6902</td>   <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Padh11</td> <td>Ptdh13</td>  <td>0.2731</td>  <td>0.9899</td> <td>-0.7054</td> <td>1.2515</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Padh11</td> <td>Ptdh15</td>  <td>0.4845</td>  <td>0.4226</td> <td>-0.2222</td> <td>1.1913</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Padh11</td>   <td>WT</td>    <td>-0.1814</td> <td>0.9992</td> <td>-1.1599</td>  <td>0.797</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Padh11</td>  <td>empty</td>  <td>0.1531</td>  <td>0.9997</td> <td>-0.8254</td> <td>1.1315</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "   <td>Ptdh1</td> <td>Ptdh11</td>  <td>-1.1509</td> <td>0.0001</td> <td>-1.887</td>  <td>-0.4148</td>  <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "   <td>Ptdh1</td> <td>Ptdh13</td>  <td>-3.8206</td>   <td>0.0</td>  <td>-4.7905</td> <td>-2.8507</td>  <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "   <td>Ptdh1</td> <td>Ptdh15</td>  <td>-3.6091</td>   <td>0.0</td>  <td>-4.3039</td> <td>-2.9144</td>  <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "   <td>Ptdh1</td>   <td>WT</td>    <td>-4.2751</td>   <td>0.0</td>  <td>-5.245</td>  <td>-3.3052</td>  <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "   <td>Ptdh1</td>  <td>empty</td>  <td>-3.9406</td>   <td>0.0</td>  <td>-4.9105</td> <td>-2.9707</td>  <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Ptdh11</td> <td>Ptdh13</td>  <td>-2.6697</td>   <td>0.0</td>  <td>-3.6758</td> <td>-1.6636</td>  <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Ptdh11</td> <td>Ptdh15</td>  <td>-2.4582</td>   <td>0.0</td>  <td>-3.2027</td> <td>-1.7137</td>  <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Ptdh11</td>   <td>WT</td>    <td>-3.1242</td>   <td>0.0</td>  <td>-4.1303</td> <td>-2.1181</td>  <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Ptdh11</td>  <td>empty</td>  <td>-2.7897</td>   <td>0.0</td>  <td>-3.7958</td> <td>-1.7836</td>  <td>True</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Ptdh13</td> <td>Ptdh15</td>  <td>0.2115</td>  <td>0.9979</td> <td>-0.7647</td> <td>1.1877</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Ptdh13</td>   <td>WT</td>    <td>-0.4545</td> <td>0.9406</td> <td>-1.6423</td> <td>0.7333</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Ptdh13</td>  <td>empty</td>   <td>-0.12</td>    <td>1.0</td>  <td>-1.3078</td> <td>1.0678</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Ptdh15</td>   <td>WT</td>    <td>-0.666</td>  <td>0.4293</td> <td>-1.6422</td> <td>0.3102</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Ptdh15</td>  <td>empty</td>  <td>-0.3315</td> <td>0.9686</td> <td>-1.3077</td> <td>0.6447</td>   <td>False</td>\n",
       "</tr>\n",
       "<tr>\n",
       "    <td>WT</td>    <td>empty</td>  <td>0.3345</td>  <td>0.9893</td> <td>-0.8533</td> <td>1.5223</td>   <td>False</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.table.SimpleTable'>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fvalue, pvalue = stats.f_oneway(data.loc[data['genotype']=='WT','Length'],\n",
    "                                data.loc[data['genotype']=='empty','Length'],\n",
    "                                data.loc[data['genotype']=='Padh11','Length'],\n",
    "                                data.loc[data['genotype']=='Ptdh13','Length'],\n",
    "                                data.loc[data['genotype']=='Padh1','Length'],\n",
    "                                data.loc[data['genotype']=='Ptdh11','Length'],\n",
    "                                data.loc[data['genotype']=='Ptdh1','Length'])\n",
    "print(fvalue)\n",
    "print(pvalue)\n",
    "\n",
    "tukey = pairwise_tukeyhsd(data['Length'],data['genotype'])\n",
    "tukey.summary()"
   ]
  }
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