Figure2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina' # on mac\n",
    "import pandas as pd\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from glob import glob\n",
    "import os,sys\n",
    "import seaborn as sns\n",
    "\n",
    "import ete3\n",
    "\n",
    "from helper_scripts import *\n",
    "sys.path.append('/Users/silas/Documents/GitHub/atlas/')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "\n",
    "plot_params=dict(SAVEPLOT=False,figurefolder='Figures',formats=['.svg'] )\n",
    "\n",
    "figheight=4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "working_dir='AL'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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eW1pfmUySz5WOJ4pGoxw4cIAjR47Q1NRE8nySCxcuzO8QX7RTvbmZYrHIxZGL7N27l9tvv51cLnfNJp10On3Nmjav10tXVxf+Jj+TU5Pz75tOpxkYGODWW25l7969pSl2B9fDNTU10dfXR1tbGxcvXmRsfGx+aqsSjvfs3cO3v/3tFddnVihI7Dy1joy3tLSwb98+rd8VkR1LQbNBFItFOjo6uPXWW3nyySfnd5TbYnna10BLawuxWIzWllayuSwXRi7QHGzm0MFDHDhwAFu0pR3gxkNLa2nnemV3bS6Xo72jnbZQG7lc7pqzN7O5LKnRFD09PbSHr634WW1Nm9frveZ9KyOu3d3dK752ObVOYzc1NXHgwAG6o91Vd7Dv3bOXkZGVdxYrSOxctYyMV5aNiIjsVAqaDcLj8fD4449jjOGDH/wgQ0NDnD59mottF2luaebwocP07O9hbm6Op59+mle/+tXM5meZnJzk8kuXCfhLgXFubg6P18OxVx/D3+S/ZiTS6/XS0tKy7DOsNJq42pq2he/bFmpbtKGnnuvh/E3+qqOfChL10wiVlmoZGdeB/iKy0yloNohsNks8HufRRx/lxhtv5OjRo7zyla/kqdxTGGMozBZ48cUXufDiBY70HmFubm6+go+1dv4w9qXhyanRxI2saduq9XAKEtWtNyg2WsnGWkbGRUR2MgXNBlEoFPB6vVhrefzxx3nkkUdoa2tjqmeKucIcM9kZmpqaCAQCBAIB/AE/Bw8dZHR0dMXw5NRo4kbWtG3lejgFicU2EhQbuWTjSiPjIiI7mYJmg5ibm6Orq4vrrruOJ554gitXrnD58mVmKe3mtlhaW1vp2ddDS0sLgUCAV77ylRw8cHDF8OTkaOJGpqK3ehpbQWLjQVElG0VEdh4FzQbR2dlJV1cXs7OzvOIVr2B8fJzLly8z0TKBz+ejPdxOa1srhbkCoVCIlpaWmsKTk6OJG5mK1jT21ttIUFTJRhGRnUlBs0F4vV66u7vnq1B0dXURiURItaeA0q70yclJvF4vHR0da9ows3A0cXJy8ppd56FQqObRxI1MRVdeu3vPbsbGxpgrzOH1lY5Iag421/z1yNptNCiqZKOIyM6koNkgpqamsNbyrne9iwcffJAzZ84QDAaZ3j9NsVgkP5uns7OT48ePY61lJjtDW1tbTe/d1NTEkd4jeDwezp49y/kXz5PL5ggEA/OlJw8dPrSm0cT1TEUvXB84fXWaoi3OH8W0HTeSbCcbDYoq2SgisjMpaDaIYrHId77zHdrb23n/+9/P888/z5kzZzjffJ5gIMj+6/YT7S6NOI6MjBCLxWp+79nZWRKJBC9dfondu3cT2RVZdObm5cuXsVhivbGagt56diyvtD4QWHF9YCMcpbPVNhoUVbJRRGRnUtBsED6fj1AoxLe//W1aW1s5dOgQ119/PaezpzEYZmdnGU2Nkp3JcvDQwTX9IE9dSnH+/Hmmr06TzWUXnblZqWmeHkvT2tK64iaO5XYsBwIBenp62LtnL1DatLRcGFzP+sBGO0pnK200KKpko4jIzqSg2SAikQj79+8nlUoxNjbGo48+isfj4WLoIsViEWstba1thNvD7IrsqvkH+Ux2hkwmQ3u4nY6ODjweDxNXJhgbG6Mw9/II12qbOJYbkfT7/US7o1wZv8LQc0PMzMzQ0lraEb8wDFqurZNujCEYCOLxeCgWi2Rz2UXPYDANe5TOVthoUFTJRhGRnUlBs0EEg0H6+/tJJBKlndhdXUxPTzPpnVxUKrLWH+SV0cBEIsGZM2eYnJosBcNolH3RfRw+fJhz58+Rz+fnX7PSJo6lI5I+r4+DBw4yfmWcU6dOMTExQVNTE9HuKO0d7YvCYM/+nvna7T5v6Wtr72gvBejKFH45AE9kJpjMlOqm1/sonZ00Je9EUNzqI6pERGTzKWg2kFgsxvj4OCdOnCCTyRAOh2mldf5+rT/IF44+Xr58meRocj5Qjo6OcvbsWY4dO8bBAwdJJBLzI5vVNnEst2O5q6uLXC43HzIr/U5OTdIWasPr9c6HwaamJlpbW5mcnOTggYPkcjkSiQTJZOm5FgbgUChEYa5A6tLKgQjWf5TOTp2S32hQ1BFVspxsNjt/WobP5yMSiRAMBrf6sUTEIQqaDSQQCDA4OEhnZyfDw8OlMHR1ZM0/yBeOPhpTGi1caGJiglOnTvHa17yWrq4uLl2+BFTfxLF0x7IxhvaOdhKJxHzIrJiZmSGXy83XPZ+enuZi8iK7du0i4A8sGgFdqBKAb7vtttII6ESmpv9maz1Kp5Gr26zGiaCoSktSkcvliMfjDA0NMTo6Ov9LY3d3N/39/cRiMQKBwFY/pohskIJmgwkEAgwMDNDb20s6ncaf8K/pB/nS0cdAIEBzsJlsNruo3cTEBMnRJIcOHuLyS5ex1lbdxLF0x3IwEKRYLJJMJq9pW1lPutDk5CT79u1jcnJy2ZC58Jm+c+Y7XHfddTT5awt5az1KZ6dXt3EqKKrS0s6Wy+U4efLk/OzLQqlUikQiwfj4OIODgwqbItucZ/Umsl15PB48Hg/GY2p+zdLRR6/XSygUqlpSsGiLBPyBFdfmLd2x7PF4sEW7aH3nwnvGLH7eYrHUx5XxK1VDJjD/jMmLSdrD7de8z3LWcpTOWg8tz89e+/U1ikpQ3LN7D5FIRKORsibxeHzZkFmRyWQ4ceIE8Xh8k59MRJymEc0Gs3Q66tTVU2taP7jceYltoTYisxHS6TSzs7Pz1/O5PLZoaW1r5br911Vdm7d0x3KxWMR4DH7/teGkubn5mhEMn8+Hx+th6uoUTU1Ni56hoqmpiUgkQluojYnMBJFdEQL+ANlc9pq2C63lKB1VtxHZuGw2y9DQUNWQWZHJZBgeHqa3t1drNkW2MQXNBrLcdNQUU0Dt6weXOy/R6y2VefQ3+ZmcKu3oLhaLtIVKxyXt37+fvXv3Vn3PpTuWs7ksHo+HaDTK6OjofLumpiZCbSG83sUjjF2dXbS2tOL1eol2Rxc9g8fjobm5mVBbaH4TUbFYJBgM0trWumLQXOtROqpuI7Jx6XR60f/uV5JMJkmn0/T09NT5qUSkXhQ0G8hq01G1rB+sdl6i1+ulvaOdtlDbfK3z/v5+Dh8+XFOd8aU7lieuTLAvuo+zZ8/OH21UGZFcqBIGPV4PgUDgmmdYeHRThc/nI9QW4tChQ8zMzDh2lI6q24hsXKFQWHbZzHLy+XzNv9yJiDspaDaIWqejVjvSZ7XzEitncba0tHD4UG0hE67dsTyRmSAUCnHbbbfxnTPfAZgfkaxYGAYtdj4AV56hmq7O0jmbHR0dNAebHTtKR9VtRDbO5/Mtu2xmOX6/v+Zf7kTEnfS/4Aaxlumo1dYP1utg7YU7lqemprDWcvjwYQ4dOkRqNLVqGFzPgeFOHqWj6jYiGxeJROju7iaVSq3aNhqNap2zyDanoNkg1jIdtdr6wc04WNsW7fwz7O/ZT09Pz6phcL0B2MmjdFTdRmRjFlYxW2kGJhwO09fXp41AItucgmaDWDodZYyhtbWV1mJraad2YZbiXKkmeLX1g4tKKnq9RKNRRw/W3mhFHTdUlnHDM2zUTiqdKe60tIrZUuFwmOPHjxOLxbbg6UTESQqaDaIyHTU2Nsa+ffvo7u4mFArhy/jIz5aOISrMFZidnSUYDC5aP+hEScXVwotTFXXcUFnGDc+wHm4qnamwu7MtV8VsYTnZvr4+VQYSaRAKmg0iGAxyww03EAqFmJqawhhDPB7n68NfZzQ5iq/JR0dHBz37ejh0+BCG0mHmGw2AtYYXpyvquKGyjBueoVZuKZ3pprArW2tpFTPVOhdpTAqaDeS6667j+eefZ2Jigueee44HH3yQs01n5+83NzczNjbG1NQUxbkifX19JEfXHwBrDS9Heo+QHE3WXFGn2o54WT83lM50S9gVdwkGgzonU6SBqQRlA3nhhReYmJjA4/HwpS99iXQ6jdfrxef10Rxsxt/kJ5PJcPnyZYaGh7gwcoFMJrPukoq1hpcXX3wRW7TLtlmqsiNenOOW0pm1/ntJJpN16V9ERDafgmaDqJyj2d7ezosvvsjs7Cy7du0iHA4TDodpC7URCAYoFApMTk0yOTnJ+fPnsUVbU03wpQFwTeFl5CLNzc019aOKOs5bT+lMp7kl7IqIyOZS0GwQ6XSaiYkJ5ubmiMfjeDylSjpNTU34mnyLQt7MzAyz+VleeuklZguzBPyrL7hfGgDXFF7GxijaYk39qKKO89xQOtMNYVdERDafgmaDKBQKFItFisUiMzMzK7attJsrlALF0triy1kaANcSXozH0NTUVFM/qqjjPDeUznRD2BURkc2noNkgfD4fHo8Hj8dDc/PKZSE9Hg8YaGltIRgMMje3+g/1pQFwLeHF7/cTagvhD6y8wUcVdeqjUjqzFvUK+m4IuyIisvkUNBtEJBKhvb0dr9e76iHHzc3NBAIBdkV2sWvXLjzelf8ZLBcA1xpe9uzdw8EDB6vWKFdFnfqplM5cqT481DfouyHsiojI5lPQbBCVsm5TU1PEYjF27969bLumpiZCbSFCoRD79u2js7OT/r7+NQfAtYaX5mAzfX19HHv1MY4cPkJHRwdtbW10dHRw5PARjr36mI61qaNoNLqu/z87xQ1hV0RENp/O0WwgsViMiYkJrl69yp133slDDz3ES8WX5u83NTURiUTYs3fPfKho8q2/pOJa635v14o6jcANpTNVJ15EZOdR0GwggUCAW265hUQiQSQSYffu3Xzu2c+RupTC4/HQ0d7B/v372b9//6JQsd4AuN7wsp0q6jSSrQ76bgi7IiKyuRQ0G0wgEODo0aNks1muu+46ruy5wvTMNF6PtzRtvkKoWE8ArGd4UT3s+tjKoL/VYVdERDaXgmaDCgaDBINBOsc6a96EsRFOhhfVw258GtUWEdkZFDTFVVQPW7Yjjb6LiCxPQVNcpdZ62G1tbRw4cGCTn05kMY2+i4isTEFTXGOt9bC7o90aNZIto9F3EZHVKWjKmtRzinA99bC1zk+2ikbfZTvLZrOk0+n5UfhIJEIwGNzqx5IGpKApNdmMKULVw5btQqPvsl3lcjni8ThDQ0OMjo6Sz+fx+/10d3fT399PLBYjEAhs9WNKA1HQlFVt1hSh6mHLdqHRd9mOcrkcJ0+e5MSJE2QymUX3UqkUiUSC8fFxBgcHFTbFMSpBKauqdYowmUxuqB/Vw5btQqPvsh3F4/FlQ2ZFJpPhxIkTxOPxTX4yaWQKmrKitU4R5mfz6+5L9bBlu9Dou2w32WyWoaGhqiGzIpPJMDw8TDab3aQnk0anoCkrqmWK0Of1sWf3Htra2rh8+TKXLl8inU6vK3RGo1H6+/qrhk3VwxY30Oi7bDfpdJrR0dGa2iaTSdLpdJ2fSHYKrdGUFa02Rej3+zl44CC5XI6hoSGKtojf71/3RiHVw5btoDL6nkqlVhzt1+i7uEWhUCCfr+2X/3w+X/PSEJHVKGjKilaaIvR5fRw8cJDxK+OcOnWKXC5HT8/LU9/r3SiketiyHUSjUfqn+quuX9bou7iJz+fD76/t+2dlsEDECfqXJCuqTBFeuXLlmntdXV3kcjlOnTrFxMQEnZ2d1+xU3MhZgqqHLW6m0XfZTiKRCN3d3aRSqVXbRqNRfe8VxyhoyoqqTREaY2jvaCeRSDAxMUFTUxOhthBe77WbHnSWoDQqjb7LdhEMBunv7yeRSKy4ISgcDtPX16fD28Ux2gwkq1pug04wEKRYLJJMJmlqaiISidAWaqv6HpWzBEUaUWX0fc/uPUQiEYVMcaVYLMbx48cJh8PL3g+Hwxw/fpxYLLbJTyaNTCOasqrlpgibmppoamqiOdhMtDtKW6ht2dHMCp0lKCKytQKBAIODg3R2djI8PEwymZyvDBSNRunr61NlIHGcgqbUZOkUYdEWyefzRPdFmZxcfaRSZwmKiGy9QCDAwMAAvb29qnUum0JBU9Zk4Qad/GyeXbt21RQ0dZagiIh7BINBenp6tvoxZAfQGk1ZN1XyERERkZUoaMqGqJKPiIiIVKOpc9kQnSUoIiIi1ShoyprkZ/PLnheoswRFRERkKQVNqW8AX6cAACAASURBVMns7CzJZJKRiyOMj4/Pj1ourGeuSj4iIiKykIKmrGp2dpbh4eFlazqvt565iIiIND5tBpJVJZPJZUNmRaWeeTKZ3OQnExERETfbEUHTlPyYMeYxY8ykMWbaGPOkMebnjDHLniJujLnDGPMFY8xYuf1TxphfqNa+UeVn84xcHKkaMisq9czzs/lNejIRERFxux0RNIFPAX8BHAbuB/4c8AN/CtxvjDELGxtj3g08ArweeBD4L+X2fwzct3mPvfUmM5OMj4/X1Fb1zEVERGShhl+jaYz5HuD9QAI4bq19qXy9Cfgb4L3AB4BPlq+HKQXROeCN1tpvlq//OvBV4C5jzN3W2h0ROOeKcxQKhZraqp65iIiILLQTRjTfU/74R5WQCWCtnQV+vfzpv1/Q/i5gN3BfJWSW22eBD5U//WD9HtddvB4vPl9tv4+onrmIiIgstBOCZnf549ll7lWuHTPGdJT//ubyx4eWaf8IMA3cYYwJOPeI7hUKh+js7KypreqZi4iIyEINP3UOVEYxDy9z78iCvx8FHgOuL38+tLSxtbZgjEkAA+XXnlmpY2PME1VuHV3pdU7IZrOk02kuXb60ocPTK/XMU6nUihuCVM9cREREltoJQfMfgO8H7jHG3GetHQMwxviA31zQrjJs117+OFHl/SrXO6rc31K5XI54PM7Q0BCjo6Pk83n8fj/t3e0c6T9CLBYjEFjbYGzuUI6TzSc5ceIEmUzmmvvhcJjjx48zODi45vcWERGRxrUTguZ9wA8BbwWeNcb8T0rT398N9ALDQB+lzT+1qOxQt6s1tNbesuwblEY6j9XYX81yuRwnTy4fCFOpFIlEgvHx8TUHwkAgwODgIJ2dnQwPD5NMJucDbDQapa+vb10BVkRERBpbwwdNa23RGPMu4Ocp7T5/PzALfIPSbvOPUwqal8ovqYxYtrO88JJ2rhGPx6uOOgJkMhlOnDhBZ2cnAwMDK75XZeq9UmoyEokwMDBAb2/vNdeDwWA9vhwRERHZ5ho+aEJpbSXwR+U/84wxzcDNwAzwTPnyc8CtQD/wxJL2PkprPQssv7loy2SzWYaGhqqGzIpMJsPw8DC9vb3LBsRqU+/d3d309/cTi8Xo6emp15chUnfL/RKlX5ZEROpjRwTNFbwfCAKfKh93BKWzMn8QuBP4zJL2rwdagEestblNe8oapNNpRkdHa2qbTCZJp9PXBMZ6Tb2LuEEtv0Tp37WIiLN2RNA0xoSttZkl1waB3wOmgI8suPUA8PvA3caYexcc2B4Efqvc5hP1f+q1KRQK5PO1lX/M5/PLHsLu5NS7iJvolygRka2xI4Im8GVjzAzwNDBJ6XiitwE54D3W2vlpcGttxhjzk5QC58PGmPuAMeBdlI4+eoBSGUtX8fl8+P21HS3k9/uvOYR9tal3Ywytra0YYzh//nzVqXcRN9IvUSIiW2OnBM0HgLsp7T5vBi4C/x34PWvtC0sbW2s/Z4x5A/BrlEpUBoE4cA/wMWvtqjvON1skEqG7u5tUKrVq22g0SiQSWXSt2tR7U1MT+/btY8+ePczNzVEsFvH5fGQyGQVN2RacWr8sIiJrtyOCprX2D4E/XONr/oXSqOe2EAwG6e/vJ5FIrPgDNRwO09fXd80P0uWm3pubmxkYGGB6eprTp08Tj8eZmZmho6ODS5cucfPNN2tdm7ieE+uXRURkfXZE0NwpYrEY4+Pjqx6sHovFrrm3dOq9qamJgYEBUqkUDz30EJcvX56/l8lkeOKJJ0ilUlrXJq7nxPplERFZHwXNBrKRg9WXTr3v27eP6enpa0ImQCgUoqWlRevaZFvY6PplERFZP31HbTCBQGBdB6svnHqfnJxkz549nD59+pqQGQgE6Orqmv9hrHVt4nYbXb8sIiLrp6DZoILB4JrXmVWm3p9++mnm5uaIx+OL7gcCAXp6eujq6lp0XevaxM02un5ZRETWT0FT5lWm3vfs2cPo6CjGGILBIF6vl1AoRFdX16LRzAqtaxO328j6ZRERWT8FTVkkEAjQ399PMBjk6NGjhEIhPB4PLS0tVdeuaV2buN1G1i+LiMj6KR3Isvbs2UMsFuPq1aurttW6NtkO1rt+WURE1k9BU5aldW3SqNazfllExG2y2ey2+KVZQVOq0ro2ERERd8nlcsTjcYaGhhgdHZ1fBtTd3U1/f7/rlgEpaEpVWtcmIiLiHrlcjpMnTy47AJRKpUgkEq4rpKKgKSvSujYRERF3iMfjVWcZAVcWUlHQlJpoXZuIiMjWyWazDA0NrbhvAtxXSMWz1Q8gIiIiIitLp9OMjo7W1LZSSMUNFDRFREREXK5QKJDP52tq66ZCKgqaIiIiIi7n8/nw+/01tXVTIRUFTRERERGXi0QidHd319TWTYVUFDRFREREXK5SSCUcDq/Yzm2FVBQ0RURERLaBWCzG8ePHq4ZNNxZScccEvoiIiIisaDsWUlHQFBGRqrZLPWWRnWK7FVJR0BQRkWtst3rKIjvNdimkoqApIiKLbMd6yiLiTgqaIqLpUVlkO9ZTFhF3UtAU2cE0PSpLbdd6yiLiTgqaIjuUpkdlOeupp7wd1omJyNbQOZoiO1St06PxeHyTn0y20natpywi7qSgKbIDrXV6NJvNbtKTyVbbrvWURcSdFDRFdqD1TI/KzrBd6ymLiDspaIrsQJoelWq2az1lEXEnzXnItqDjd5yl6VFZSSwWY3x8vOoaXjfWUxYRd9JPD3E1Hb9TH5Xp0VQqtWpbTY/uPNuxnrKIuJOCpriWjt+pn8r0aCKRWHFDkKZHd67tVk9ZRNxJQVNcS9VJ6kvTo1KL7VJPWUTcSUFTXKly/M7k5CRtbW14vV7m5ua4evUq1tr5dqpOsn6aHhURkXpT0BRXGhsbwxjDrbfeytzcHMViEY/Hg9fr5dKlS1y8eJHZ2VlA1Uk2QtOjIiJSTwqa4koeT+nkrdOnTxOPx5mZmaG5uZlYLEYsFuNVr3oVzzzzDDMzMzp+xwGaHhURkXpQ0BTXyeVyPP300/zd3/0d58+fX3Tv7NmzPPnkk9x5550MDAxw+vRpHb8jIiLiUjqwXVwnHo9z6tQpcrncsvcvX77MQw89xPT0NPv27dPxOyIiIi6loCmuUtkEND09TSQSqboR5fLlyzz//PPs379fx++IiIi4lIKmuMrCGtxdXV309PRUDZvnz5+nq6vL8eN3stksIyMjnDt3jpGREbLZrKPvLyIislNoYZu4ysIa3D6fj3379hEMBhkbG2NycpK5uTm8Xi+hUIjdu3fT2dnp2PE7qkIkIiLiLEeDpjHGCwSstdNLrr8ZeDcwDfyZtTbhZL/SOJbW4Pb5fOzZs4euri6mp6fnjzlqaWkhGo06GjJVhUhERMRZTk+dfxQYM8a0Vy4YY+4Gvgz8e+BXgBPGmOsc7lcaRKUG91I+n49wOExHRwfhcBifz+foJqBaqxDF43FH+hMREdkJnA6arwe+Zq2dWHDtN4ArwA8Dvwx0APc43K80iEoN7nA4vGI7J2twVzYgrVTzG16uQqQ1myIiIrVxOmheB8wP+RhjjgDXA/daaz9trf0o8EXgTof7lQYSi8U4fvx41bDpdA3uhRuQVlOpQiQiIiKrc3ozUBhYOCz0GsACDy249gzwJof7lQay2TW4F25AWo2qEImIiNTO6aCZBA4v+Py7gRngiQXX2gD9pJYVbWYN7qUbkFaiKkQiIiK1c/on5mPAu4wx7wCywF3AV6y1swvaHAFGHO5XGtRm1OCubEBKpVKrtlUVIhERkdo5vUbzd8rv+XngHwE/8NuVm8aYMPBG4HGH+xVZt63YgCQiIrITODqiaa39tjHmNuAD5Uv3W2tPLmhyE/Al4DNO9iuyUbFYjPHx8apHHDm9AUlERGQncHyxmbX228AvVbn3deDrTvcpslGbvQFJRERkJ9iUXQ3GmCbglcC0tfa5zehTZK02cwOSiIjITuB0CcrvpbQB6KettWPla72Uzs7sLX/+eeB7rbXaeS6utBkbkERERHYCpzcD/RhwtBIyy/4IiAFfA56iVPP8Rx3uV0RERERcxump81dQqmsOzO8yfxvwN9bau8tT6N+iFDT/3OG+ZQOy2aymi0VERMRRTgfN3ZQOba/4rnIf9wFYa2eNMV8Gvt/hfmWdcrkc8XicoaEhRkdH5zfAdHd309/frw0wIiIism5OB81JoH3B52+gVIJy4U7zLBByuF9Zh1wux8mTJ5c90ieVSpFIJBgfH2dwcFBhU0RERNbM6TWaw8BbjTEBY4wfeB/wlLX2pQVtDgKXHO5X1iEej1c9NxIgk8lw4sQJ4vH4Jj+ZiIiINAKng+afUSoxOQycKf/9L5e0uQ14xuF+ZY2y2SxDQ0NVQ2ZFJpNheHiYbDa7SU8mIiIijcLRoGmt/RTwe0ALpSn0j5f/AGCMeTNwiNIOdNlC6XSa0dHRmtomk0nS6XSdn0hEREQaTT0qA/0q8KtVbn8d6ASuOt2vrE2hUCCfz9fUNp/PUyjo2FMRERFZm02pDFRhrc0DtaUbqSufz4ff76+prd/vx+fb1H8qIiIi0gCcXqMJgDHmJmPM7xljPm+M+acF1w8ZY77XGNNZj36ldpFIhO7u7praRqNRIpFInZ9IREREGo3jQdMY8xHgFPDLwDuBNy3p7zPADzndr6xNMBikv7+fcDi8YrtwOExfX58ObxcREZE1czRoGmPuBj5EqTrQzcDvLrxvrT0LfBN4l5P9yvrEYjGOHz9eNWyGw2GOHz9OLBbb5CcTERGRRuD0wrufA+LAu621eWPMv12mzRngjQ73uypjzNuBn6dUJjNCqYLRE8B/ttY+ukz7OyiF5tuBIKWv6y+Be621c5v13PUUCAQYHByks7OT4eFhksnkfGWgaDRKX1+fKgOJbBGVhRWRRuB00LwR+GR50081F4G9Dve7ImPM71Oayk8DnwNeAmLAu4H3GmN+2Fr76QXt3w18llIVo/uBMUrLAP4YeA2lg+gbQiAQYGBggN7eXv1QE3EBlYUVkUbidNA0QHGVNnspBbhNYYzpBn4JSAE3WWsvLbj3JuCrwEeAT5evhYE/B+aAN1prv1m+/uvltncZY+621t63WV/DZggGg/T09Gz1Y4jsaCoLKyKNph4lKO+odtMY4wVey+ZWBjpI6et8fGHIBLDWfo1SffbdCy7fVf78vkrILLfNUppKB/hgXZ9YRHYklYUVkUbjdND8G+CYMeYXq9z/vyhNWf//Dve7kmFKZ3ceN8bsWnjDGPN6IAT804LLby5/fGiZ93oEmAbuMMZoOEFEHKOysCLSiJyeOv8TSusX/8AY872ABTDGfBR4HXAr8Bilmuibwlo7Zoz5FeA/A88aYz5Haa1mL6Xd718G/t2Cl1xf/ji0zHsVjDEJYIBSHfczK/VtjHmiyq2ja/oiRKThracsrJa7iIjbORo0rbUz5XWPfwr8IOAt37qH0trNTwM/a63d1HqG1to/Mca8QGnX+E8uuBWntHlp4ZR6e/njRJW3q1zvcPQhRVxEO543n8rCikgjqket8wngR4wx9wCDlI4SmgBOWGsvO91fLYwxvwz8DvAx4OPAKKVRxd8F/ocx5mZr7S/X+nblj3a1htbaW6o8zxPAsRr7E9k02vG8dVQWVkQaUd2+U1lrx4B/rNf718oY80bg94EHrbX3LLh1qnzO5xDwi8aY/1o+UL4yYtnO8iqnm1cb8RTZlrTjeWtVysKmUqlV26osrIhsF3Wpde4y7yh//NrSG9baaeAEpf8Ory5ffq78sX9pe2OMDzgMFICzjj+pyBbSjuetpbKwItKIHB/RNMZ0AT8GHAc6eXmd5kLWWvsWp/uuojL0srvK/cr1yuKor1JaX3onpbrsC70eaAEesdbmnHxIka201h3Pvb29Cjp1EIvFGB8frxr4VRZWRLYbR4OmMeYo8DCl8GZWaLrq+kYH/TPws8BPGWP+m7V2pHLDGPNWSpV+ssA3ypcfoDTVfrcx5t4FB7YHgd8qt/nEZj28yGbQjmd3UFlYEWk0To9ofhTYA/wepSOMXnRBXfAHKJ2T+d3AGWPMg5Q2A91AaVrdAP/JWpsGsNZmjDE/WX7dw8aY+yiVoHwXpaOPHqBUllKkYWjHs3uoLKyINBKng+brgP9lrf1Vh9933ay1RWPM24CfAe4G/i2l6e8x4AvAx6y1X1ryms8ZY94A/BrwXiBI6Sike8rtN3NEVqTutOPZfVQWVkQaQT1qnT/r8HtumLV2ltJh8n+yhtf8C/C2uj2UiItox7OIiNSD07vOn+Dlyjoisk1ox7OIiNSD00HzI8DbymdXisg2EovFOH78eNWwqR3PIiKyVk5PnV8HfB74kjHmM5RGOK8s19Ba+9cO9y0iG6AdzyIi4jSng+YnKR1dZID3l/8s3ThjytcUNEVcRjueRUTESU4HzR91+P1EZAtox7OIiDjB0aBprf2Uk+8nIiIiItvXTqh1LiIiIiJboC6nLhtjdlM66PwGoNVa+xMLrh8Gvm2tnalH3yIiIiLiDo4HTWPMjwMfo1RNp7Lx5yfKt/cCjwI/BfyF032LiIiIiHs4OnVujPlXlGqcD1Eq9fiJhfettU8DzwDf42S/IiIiIuI+To9o/gqQBN5grc0YY169TJungO9yuF8RERERcRmnNwPdCvyDtTazQpsLQLfD/YqIiIiIyzgdNP3A1VXadABzDvcrIiIiIi7jdNB8AbhllTa3Ac853K+IiIiIuIzTQfPzwOuMMe9b7qYx5keBm4DPOtyviIiIiLiM05uB/gC4G/iMMeYuoB3AGPOzwOuA9wDDwL0O9ysiIiIiLuN0CcpxY8wbgL8GFo5qfqz88Z+BH7DWrraOU0RERES2OccPbLfWngfeaIy5idIxRhFgAnjMWvuE0/2JiIiIiDvVpQQlgLX2KUpnZoqIiIjIDuR0ZaCzxpifW6XNzxhjzjrZr4iIiIi4j9O7zg9ROidzJR3AQYf7FRERERGXcTpo1qINyG9BvyIiIiKyiTa8RtMYc2DJpY5lrgF4gQPAXYCmzkVEREQanBObgV4A7ILPf778pxoD3ONAvyIiIiLiYk4Ezb+mFDQN8MOUdpp/a5l2c0Aa+Iq19ksO9CsiIiIiLrbhoGmt/ZHK340xPww8aK39yEbfV0RERES2N6crA23F5iIRERERcaG6HdhujDkK3AC0WWv/v3r1IyIiIiLu5PgIpDHmZmPMN4FngAeATy649wZjzLQx5p1O9ysiIiIi7uJ0ZaB+4GHgeuBPgS8uafIIMEbpiCMRERERaWBOj2j+BuAHjltr7wFOLrxprbXAo8Cgw/2KiIiIiMs4HTTfAvydtfbMCm3OA/sc7ldEREREXMbpoNkBXKihT7/D/YqIiIiIyzgdNC8BsVXaDAAvOtyviIiIiLiM00Hzq8A7jTHXL3fTGDNIaXr9Hx3uV0RERERcxumg+btAAXjEGPNBymsxjTED5c//HpgEPupwvyIiIiLiMk5XBnrOGPNe4DPAx8uXDaX65wa4ArzHWnveyX5FRERExH0crwxkrX3IGHMY+ABwOxABJoDHgL+y1o453aeIiIiIuE9dSlBaa69QOrD9T+vx/iIiIiLifo6XoBQRERERgQ2OaBpjXr/e11prH9lI3yIiIiLibhudOn8YsOt8rXeDfcsOkM1mSafTFAoFfD4fkUiEYDC41Y8lIiIiNdho0PwI6w+aIlXlcjni8ThDQ0OMjo6Sz+fx+/10d3fT399PLBYjEAhs9WOKiIjICjYUNK21H3boOUTm5XI5Tp48yYkTJ8hkMovupVIpEokE4+PjDA4OKmyKiIi4mDYDievE4/FlQ2ZFJpPhxIkTxOPxTX4yERERWYu6HG8EYIx5HfBqoJ3SOZpPWmv/uV79SWPIZrMMDQ1VDZkVmUyG4eFhent7tWZTRETEpRwPmsaY1wB/CcQqlyiv4zTGDAM/bq39F6f7lcaQTqcZHR2tqW0ymSSdTtPT01PnpxIREZH1cDRoGmNuAb4MBIH/TWlX+ijQDbwJeD3wJWPM66y1p5zsWxpDoVAgn8/X1Dafz1MoFOr8RCIiIrJeTo9o/nb5Pd9trf37Jfd+0xjzbuCBcru3Oty3NACfz4ff76+prd/vx+er2+oPERER2SCnNwPdAfzdMiETAGvt54EHy+1ErhGJROju7q6pbTQaJRKJ1PmJREREZL2cDppFYLWtwMPo7E2pIhgM0t/fTzgcXrFdOBymr69PG4FERERczOmg+U3gVau0eRVwwuF+pYHEYjGOHz9eNWyGw2GOHz9OLBZb9r6IiIi4g9ML3D4EPGyM+aC19hNLbxpjfgZ4C/BGh/uVJbZz6cZAIMDg4CCdnZ0MDw+TTCbnKwNFo1H6+vpUGUhERGQbcDpo/mvgq8DHjTG/APwzkAL2Aq8F+oCHgH9jjPk3C15nrbX/j8PPsiM1SunGQCDAwMAAvb292zYwi4iI7HROB80PL/h7X/nPUm/l2h3nFlDQ3KBGLN0YDAZ1TqaIiMg25XTQfJPD7ydrUGvpxs7OTgYGBjb56URERGSncTRoWmv/t5PvJ7VT6UYREXfazmvmRTZKp103CJVuFBFxl0ZZMy+yEXULmsYYQ6n0ZNNy96215+vV906k0o0iIu7RiGvmRdbD8aBpjHkf8J+AGwFvlWa2Hn3vZCrdKCLiHlozL1LiaNoon5P5MaAAfB0YKf9d6qxSujGVSq3aVqUbRUTqR2vmRV7m9LDWfwAuAXdYaxMOv7esoFK6MZFIrPjNTaUbRUTqS2vmRV7mdAnKHuBvFTK3hko3iohsPa2ZF3mZ0yOaLwJa1bxFVLpRRGTrac28yMuc/tf9SeCnjTEha+2kw+8tNVDpRhGRraU18yIvc3rq/PeBk8A/GWPeYIwJOfz+a2aM+RFjjF3lz9wyr7vDGPMFY8yYMWbaGPOUMeYXjDHVdtK7SqV048GDB+np6dkxITObzTIyMsK5c+cYGRkhm81u9SOJyA5TWTNfbRlThdbMy07gdGWgOWPMfwH+FvgqQOk4zeWa2s2aK/gW8JtV7r0OeDPwxYUXjTHvBj4LZIH7gTHgncAfA68B3levh5X10cHIIuImsViM8fHxqkccac287BROH2/0buABSudnJoCLbPHxRtbab1EKm9cwxjxa/uufLbgWBv4cmAPeaK39Zvn6r1MKz3cZY+621t5X1weXmulgZBFxG62ZFylxelTxw8A08HZr7dcdfm9HGWNeCdxO6azP/7Xg1l3AbuCvKyETwFqbNcZ8CPgK8EFAQdMldDCyiLiR1syLOB80r6cU0FwdMsv+XfnjX1hrF67RfHP540PLvOYRSkH6DmNMwFqbq+cDyup0MLKIuF1lzbzITuR00HwJqO3wsC1kjGkGfggoAv99ye3ryx+Hlr7OWlswxiSAAeAIcGaVfp6ocuvomh5YqtLByCIiIu7l9K7zzwL/yhjT5PD7Ou17gQ7gi9baF5fcay9/nKjy2sr1jno8mKyNDkYWERFxL6dHND8E3Ab8rTHmF6y1Lzj8/k75qfLH/7aO11a20dvVGlprb1n2DUojncfW0bcsoYORRURE3Mvpn7rfBpoohc13GmOusPzIoLXW9jrcd02MMa8A7gAuAF9YpknleduXuQcQXtJOtpAORhYREXEvp6fOPZSOMzpf/pOhNAK49I/T/a5FtU1AFc+VP/YvvWGM8QGHKX2NZ+vzeLIWOhhZRETEvZw+sP2Qk+/nNGNMEHg/pU1Af1Gl2VeBHwTuBD6z5N7rgRbgEe04dw8djCwiIuJOO23B2vuATuAfltkEVPEApVKadxtj7l1wYHsQ+K1ym0/U/UmlZjoYWURExJ3qGjTLVXbagQlr7coHHW6OyiagP6vWwFqbMcb8JKXA+bAx5j5KJSjfRenoowcolaUUF9HByCIiIu7jeNA0xniB/wj8BKX1jJXrCUpnVn7UWrvpZ8wYY24AXkv1TUDzrLWfM8a8Afg14L1AEIgD9wAfs9auuuNctoYORhYREXEPp2ud+ylV1HkDpeN/XgSSQBQ4BPw2cKcx5l9bazf1YHdr7RlePpqolvb/Arytfk8kIiIi0tic3v19D/BGSrXDb7DWHrLWfld5k9D1wN8Dryu3ExEREZEG5nTQ/AHgaeB7rLXDC29Ya58H3gM8Q2lXt4iIiIg0MKeDZoxSWcficjfL178IbMlh7SIiIiKyeZwOmnmgbZU2rcCsw/2KiIiIiMs4HTSfAu4yxuxe7qYxZhdwF3Da4X5FRERExGWcDpofB3YDJ4wxP26MOWKMaTbGHDbG/CjwePn+xx3uV0RERERcxukSlH9jjLkZ+E8sfyi6Af7AWvs3TvYrIiIiIu7j+IHt1tpfNcb8T+DHgVdTrgwEPAn8pbX2Uaf7FBERERH3qUsJSmvtY8Bj9XhvEREREdkeNrxG0xgTMMacMMZ8xRjTtEI7f7nNYyu1ExEREZHG4MRmoB8EbgH+yFpb9diicsnJPwSOowPbRURERBqeE0HzPcBZa+0XVmtorX0IGAbe50C/IiIiIuJiTgTNVwMPr6H9I8DNDvQrIiIiIi7mRNDcBaTW0D4FRBzoV0RERERczImgOcPqZScXagOyDvQrIiIiIi7mRNB8ERhcQ/tbgfMO9CsiIiIiLuZE0HwYuN0Yc+tqDY0xtwB3AF9zoF8RERERcTEngubHAQv8rTHmhmqNjDFHgb8F5oD/14F+RURERMTFNlwZyFr7nDHmI8CHgSeNMQ8AXwUuUAqg+4G3AO8FAsD/ba19bqP9ioiIiIi7OVKC0lr7EWNMAfgN4AeA71/SxACzwK9Za3/XiT5FRERExN0cq3Vurf0dY8z/AH4MeA0QpRQwLwJfB/7KWnvOqf5ERERExN0cC5oA5SD5G06+p4iIiIhsT05sBhIRERERuYaCpoiIiIjUgaF2vwAAG2pJREFUhYKmiIiIiNSFgqaIiIiI1IWCpoiIiIjUhYKmiIiIiNSFgqaIiIiI1IWCpoiIiIjUhYKmiIiIiNSFgqaIiIiI1IWCpoiIiIjUhYKmiIiIiNSFb6sfQEREnJPNZkmn0xQKBXw+H5FIhGAwuNWPJSI7lIKmiEgDyOVyxONxhoaGGB0dJZ/P4/f76e7upr+/n1gsRiAQ2OrHFJEdRkFTRGSby+VynDx5khMnTpDJZBbdS6VSJBIJxsfHGRwcVNgUkU2lNZoiIttcPB5fNmRWZDIZTpw4QTwe3+QnE5GdTkFTRGQby2azDA0NVQ2ZFZlMhuHhYbLZ7CY9mYiIgqaIyLaWTqcZHR2tqW0ymSSdTtf5iUREXqagKSKyjf2f9u49vLK6vvf4+wshCaAZhqhNzngBJ4nS0Z7jJVGwIOAdrYpCi/aoxyO0WD3UYo94QYXqY7GtFS+tPUdr8fqgQqVaqKICotKSEW9F0SSSOd4yo2SGiVySEPieP9YKbjY7QzIzK3t29vv1PPv5zV6/31r7u/eeZD7zW7eFhQXm5+eXNXZ+fp6FhYWKK5Kk3zBoSlIL6+jooLOzc1ljOzs76ejwHFBJq8egKUktrLe3l76+vmWN7e/vp7e3t+KKJOk3DJqS1MK6u7sZGhqip6dnl+N6enoYHBz04u2SVpVBU5Ja3MDAACMjI0uGzZ6eHkZGRhgYGFjlyiS1Ow/WkaQW19XVxfDwMOvXr2d8fJypqam77wzU39/P4OCgdwaS1BQGTUlaA7q6uti0aRMbN270XueS9hkGTUlaQ7q7u9mwYUOzy5AkwGM0JUmSVBGDpiRJkiph0JQkSVIlDJqSJEmqhEFTkiRJlTBoSpIkqRIGTUmSJFXCoClJkqRKGDQlSZJUCYOmJEmSKuEtKKV91OzsrPesliS1NIOmtI+Zm5tjYmKCsbExtm7dyvz8PJ2dnfT19TE0NMTAwABdXV3NLlOSpPtk0JT2IXNzc2zevJnR0VFmZmbu0bdt2zYmJyfZsWMHw8PDhk1J0j7PYzSlfcjExETDkLloZmaG0dFRJiYmVrkySZJWzqAp7SNmZ2cZGxtbMmQumpmZYXx8nNnZ2VWqTJKk3WPQlPYR09PTbN26dVljp6ammJ6errgiSZL2jEFT2kcsLCwwPz+/rLHz8/MsLCxUXJEkSXumrYJmRBwdERdHxFREzJXt5RFxQoOxR0XEZRGxPSJui4jvRcRrImL/ZtSuta+jo4POzs5lje3s7KSjw3P5JEn7trYJmhFxNnA1cAzwBeBdwOeB9cCxdWOfVzP2s8DfAZ3Au4ELV61otZXe3l76+vqWNba/v5/e3t6KK5Ikac+0xZRIRJwMvA34MvCCzPx1Xf8BNX/uAT4I3Akcm5nfLJe/GbgCOCkiTslMA6f2qu7uboaGhpicnNzlCUE9PT0MDg568XZJ0j5vzc9oRsR+wDuB24AX14dMgMy8o+bpScADgQsXQ2Y5ZhY4u3z6yuoqVjsbGBhgZGSEnp6ehv09PT2MjIwwMDCwypVJkrRy7TCjeRRwOHARsCMing08CpgFRjPz3+vGH1+2X2iwraspAutREdGVmXO7euGIuG6Jrkcut3i1l66uLoaHh1m/fj3j4+NMTU3dfWeg/v5+BgcHvTOQJKlltEPQHC7bbcC3gEfXdkbE1cBJmfmrctEjynasfkOZuRARk8Am4OHADZVUrLbW1dXFpk2b2Lhxo/c6lyS1tHYImg8q29OBSeCpwLXAwyhOCHoG8Bl+c0LQurLducT2Fpcfcl8vnJmPa7S8nOl87H2tr/bW3d3Nhg0bml2GJEm7bc0fowksXo4oKGYuv5KZt2Tm94ETgZ8BT46II5e5vSjb3Mt1SpIkrSntEDR3lO2Nmfnd2o7MvB34Yvl0pGwXZyzX0VhP3ThJkiQ10A5B80dle/MS/YtB9MC68UP1AyOig+LEogXgxr1VoCRJ0lrUDkHzaopgOBgRjW678qiy3VK2V5TtMxuMPQY4CLjmvs44lyRJandrPmhm5k3Apyh2hb+lti8inkZxMtBOfnM5o4uAm4BTIuLxNWO7gbeXTz9QcdmSJEktrx3OOgc4E3gC8KaIOAYYpTjr/ESKOwCdlpk3A2TmTEScRhE4r4qIC4HtwHMpLn10EUVwlSRJ0i6s+RlNgMz8JUXQfDfwEOAMiguzXwocnZmfqRt/CfBkit3uLwT+F3AHRWA9JTM941ySJOk+tMuMJpm5nSIonrnM8d8ATqi0KEmSpDWsLWY0JUmStPoMmpIkSaqEQVOSJEmVMGhKkiSpEgZNSZIkVcKgKUmSpEoYNCVJklQJg6YkSZIqYdCUJElSJQyakiRJqoRBU5IkSZUwaEqSJKkSBk1JkiRVwqApSZKkShg0JUmSVAmDpiRJkiph0JQkSVIlDJqSJEmqREezC5D2NbOzs0xPT7OwsEBHRwe9vb10d3c3uyxJklqOQVMqzc3NMTExwdjYGFu3bmV+fp7Ozk76+voYGhpiYGCArq6uZpcpSVLLMGhKFCFz8+bNjI6OMjMzc4++bdu2MTk5yY4dOxgeHjZsSpK0TB6jKQETExMNQ+aimZkZRkdHmZiYWOXKJElqXQZNtb3Z2VnGxsaWDJmLZmZmGB8fZ3Z2dpUqkySptRk01famp6fZunXrssZOTU0xPT1dcUWSJK0NBk21vYWFBebn55c1dn5+noWFhYorkiRpbTBoqu11dHTQ2dm5rLGdnZ10dHgOnSRJy2HQVNvr7e2lr69vWWP7+/vp7e2tuCJJktYGg6baXnd3N0NDQ/T09OxyXE9PD4ODg168XZKkZTJoSsDAwAAjIyNLhs2enh5GRkYYGBhY5cokSWpdHmwmAV1dXQwPD7N+/XrGx8eZmpq6+85A/f39DA4OemcgSZJWyKAplbq6uti0aRMbN270XueSJO0FBk2pTnd3Nxs2bGh2GZIktTyP0ZQkSVIlDJqSJEmqhEFTkiRJlTBoSpIkqRIGTUmSJFXCoClJkqRKGDQlSZJUCYOmJEmSKmHQlCRJUiUMmpIkSaqEQVOSJEmVMGhKkiSpEgZNSZIkVcKgKUmSpEoYNCVJklQJg6YkSZIqYdCUJElSJQyakiRJqoRBU5IkSZUwaEqSJKkSBk1JkiRVwqApSZKkShg0JUmSVAmDpiRJkiph0JQkSVIlDJqSJEmqhEFTkiRJlTBoSpIkqRIdzS5AklbD7Ows09PTLCws0NHRQW9vL93d3c0uS5LWNIOmpDVtbm6OiYkJxsbG2Lp1K/Pz83R2dtLX18fQ0BADAwN0dXU1u0xJWpMMmpLWrLm5OTZv3szo6CgzMzP36Nu2bRuTk5Ps2LGD4eFhw6YkVcBjNCWtWRMTEw1D5qKZmRlGR0eZmJhY5cokqT0YNCWtSbOzs4yNjS0ZMhfNzMwwPj7O7OzsKlUmSe2jLYJmRGyJiFzisXWJdY6KiMsiYntE3BYR34uI10TE/qtdv6SVm56eZuvWhj/e9zI1NcX09HTFFUlS+2mnYzR3Auc3WH5L/YKIeB5wMTALfArYDvwe8G7gScDJ1ZUpaW9YWFhgfn5+WWPn5+dZWFiouCJJaj/tFDRvzsxz7mtQRPQAHwTuBI7NzG+Wy98MXAGcFBGnZOaFVRYrac90dHTQ2dm5rLGdnZ10dLTTr0NJWh1tset8hU4CHghcuBgyATJzFji7fPrKZhQmafl6e3vp6+tb1tj+/n56e3srrkiS2k87/Re+KyL+O/BQ4Fbge8DVmXln3bjjy/YLDbZxNXAbcFREdGXm3K5eMCKuW6LrkcsvW9Lu6O7uZmhoiMnJyV2eENTT08Pg4KAXb5ekCrRT0OwDPla3bDIiXp6ZX61Z9oiyHavfQGYuRMQksAl4OHBDJZVK2isGBgbYsWPHkpc46unpYWRkhIGBgSZUJ0lrX7sEzX8CvgZ8H/g1RUh8NfBHwL9FxJGZ+d1y7Lqy3bnEthaXH3JfL5qZj2u0vJzpfOzySpe0u7q6uhgeHmb9+vWMj48zNTV1952B+vv7GRwc9M5AklShtgiamXlu3aLrgdMj4hbgtcA5wInL3FwsbnbvVCepSl1dXWzatImNGzd6r3NJWmVtETR34R8oguYxNcsWZyzX3Xs4AD114yS1gO7ubjZs2NDsMiSprbT7Wee/LNuDa5b9qGyH6gdHRAdwOLAA3FhtaZIkSa2t3YPmkWVbGxqvKNtnNhh/DHAQcM19nXEuSZLU7tZ80IyITRFxaIPlDwPeXz79eE3XRcBNwCkR8fia8d3A28unH6ioXEmSpDWjHY7RPBl4fURcCUxSnHW+EXg20A1cBvzN4uDMnImI0ygC51URcSHFLSifS3Hpo4sobkspSZKkXWiHoHklRUB8DMWu8oOBm4GvU1xX82OZeY8zyDPzkoh4MvAm4IUUgXQCOBN4b/14SZIk3duaD5rlxdi/ep8D773eN4AT9n5FkiRJ7WHNH6MpSZKk5jBoSpIkqRIGTUmSJFXCoClJkqRKGDQlSZJUifBKPasvIqYPPPDAQ4844ohmlyJJkrRLN9xwA7fffvv2zOxd6boGzSaIiEmgB9hS8Us9smx/WPHraPX4na5Nfq9rj9/p2tPO3+lhwExmHr7SFQ2aa1hEXAeQmY9rdi3aO/xO1ya/17XH73Tt8TvdPR6jKUmSpEoYNCVJklQJg6YkSZIqYdCUJElSJQyakiRJqoRnnUuSJKkSzmhKkiSpEgZNSZIkVcKgKUmSpEoYNCVJklQJg6YkSZIqYdCUJElSJQyakiRJqoRBcw2KiAdHxIcj4hcRMRcRWyLi/IhY3+zatDIR0RsRp0bEZyNiIiJuj4idEfH1iHhFRPgzvEZExEsiIsvHqc2uR7svIo6OiIsjYqr8HTwVEZdHxAnNrk0rFxHPLr+/n5W/g2+MiM9ExJHNrq0VeMH2NSYiNgLXAA8C/gX4ITACHAf8CHhSZk43r0KtREScDnwAmAKuBH4C/BbwAmAdcDFwcvqD3NIi4iHAfwL7A/cDTsvMDzW3Ku2OiDgbeBtwE/CvFD+7DwAeA1yZma9rYnlaoYh4J/A6YBq4hOJ7HQCeC3QAL83Mjzevwn2fQXONiYgvAk8HzsjM99Us/1vgz4D/k5mnN6s+rUxEHA8cDFyamXfVLO8DRoGHACdl5sVNKlF7KCIC+BJwOPDPwJ9j0GxJEXEy8Gngy8ALMvPXdf0HZOYdTSlOK1b+nv058CvgdzLzlzV9xwFXAJOZ+fAmldgS3O22hkTEwylC5hbg7+q63wrcCrwkIg5e5dK0mzLzisz8fG3ILJdvBf6hfHrsqhemvekM4Hjg5RQ/o2pB5WEs7wRuA15cHzIBDJkt52EUOena2pAJkJlXAr8GHtiMwlqJQXNtOb5sL28QTH4NfAM4CHjiahemSiz+o7XQ1Cq02yLiCOA84D2ZeXWz69EeOYpiVvoyYEd5XN9ZEfGnHsvXssaBeWAkIh5Q2xERxwD3p5i91i50NLsA7VWPKNuxJfrHKWY8h4CvrEpFqkREdAAvLZ9+oZm1aPeU3+HHKI67fWOTy9GeGy7bbcC3gEfXdkbE1RSHufxqtQvT7snM7RFxFvC3wA8i4hKKYzU3Uhyj+SXgj5tYYkswaK4t68p25xL9i8sPWYVaVK3zgEcBl2XmF5tdjHbLWyhOEPndzLy92cVojz2obE8HJoGnAtdS7H59F/AM4DN4qEtLyczzI2IL8GHgtJquCeCC+l3qujd3nbeXKFvPAGthEXEG8FqKKwq8pMnlaDdExAjFLOa7MvPfm12P9or9yzYoZi6/kpm3ZOb3gROBnwFPdjd6a4mI1wEXARdQzGQeDDwOuBH4RET8VfOqaw0GzbVlccZy3RL9PXXj1GIi4lXAe4AfAMdl5vYml6QVqtllPga8ucnlaO/ZUbY3ZuZ3azvKGevFPQ8jq1qVdltEHEtxgtfnMvPMzLwxM2/LzG9R/Ofh58BryxNxtQSD5tryo7IdWqJ/sGyXOoZT+7CIeA3wfuB6ipC5tcklaffcj+Jn9AhgtuYi7UlxdQiAD5bLzm9alVqpxd+/Ny/RvxhED1yFWrR3PKdsr6zvyMzbKC4xtx/FITBagsdori2LPwxPj4j96q67eH/gScDtwH80ozjtvvKA9POA7wBPy8ybmlySdt8c8I9L9D2W4h+tr1MEF3ert46rKa4AMRgRnZk5X9f/qLLdsqpVaU90le1SlzBaXF7/XauGM5prSGb+GLgcOAx4VV33uRTHlnw0M71WXwuJiDdThMzrgKcYMltbZt6emac2egCfK4d9pFz2qWbWquUrfy4/RXHo0ltq+yLiaRQnA+3Eq0S0kq+V7R9FxIbajoh4FsXkzSzF3fi0BGc0154/ofhL/96IeApwA/AEiltQjgFvamJtWqGIeBnwF8CdFL/0zihuJHMPWzLzglUuTdK9nUnx+/ZN5XUWRynOOj+R4mf4tMxcate69j0XUVwn86nADRHxWWArxWEvz6E48ev13tZ51wyaa0xm/jgiHk8RTp4JnEBxr933Aud68kjLObxs9wdes8SYr1KcESmpiTLzlxHxBOBsinD5RIq7x1wK/GVmethSC8nMuyLiBIo9hKdQfKcHAdspLsz/3sy8vIkltgTvdS5JkqRKeIymJEmSKmHQlCRJUiUMmpIkSaqEQVOSJEmVMGhKkiSpEgZNSZIkVcKgKUmSpEoYNCVJklQJg6YkSZIqYdCUJElSJQyakiRJqoRBU5LWuIg4NiIyIs5pdi31IuKqiMhm1yGpGgZNSS0pIh4ZEe+LiOsjYmdEzEfELyLi0oh4RUR0r2Ith5VB7oLVes1WEREXlJ/NYc2uRdLq62h2AZK0UhHxFuCtFP9Z/g/gI8AtwG8BxwIfAl4JPL5JJe5rRoEjgJuaXUgDLwUOanYRkqph0JTUUiLijcC5wE+BkzPz2gZjngO8drVr21dl5m3AD5tdRyOZ+ZNm1yCpOu46l9Qyyt2v5wB3ACc0CpkAmfmvwDPr1v39iLi63M1+e0T8Z0S8ISK6GrzOlvJxUET8dUT8JCLmImIiIs6KiKgZew4wWT59WbmbePHxP8oxnRHx6oi4LCL+X7mt7RHx5Yh41hLvdbGG+0XEuyPip2Xd34mI55djOiLijRExHhGzEfHjiHh1g201PEZz8fjIuu3Mla/1zojobLCt50fExyNiLCJujYhbIuK6iDgjIvarG5vAy8qnkzWfy5b6Ghq8zn4RcXpEbC5f49byz6+sf53F1yq39YCI+L8RMVW+l+9HxMsbfcaSqueMpqRW8nLgAODCzLx+VwMzc27xzxHxDuANFLuOP0mxm/1ZwDuAZ0TE0zLzjrpNHABcDvwX4N+ABeD5wHlAN8WsKsBVwCHAnwLfBS6p2cZ3yvZQ4D3ANcCXgF8B/cDvAZdFxGmZ+aEGb+OAcvyhwL8AncCLgIsj4unAnwBPKOubA04G3hcRv8rMT+3q86nzSeDocjszwAnA64AHUXzmtc4D7gKuBX4OrAOOL9/fMPCSmrHnUnxm/7Xsv7lcfjP37WPAiylmrj8EJHAi8PfA7wJ/2GCdQ4BvAPPARRTf00nAhyPirsz8yDJeV9LelJk+fPjw0RIP4CsUgePUFaxzZLnOT4C+muUdwOfLvjfWrbOlXH4ZcGDN8gdRhKSbgQNqlh9Wjr9giRq6gAc3WL4OuB7YXvs6dTV8HuiqWX50uXw7sBk4pKbv4RQh69t12zq2XOecuuVXlcuvAw6tWX4wMAHcWfuZlX0bG7yP/SiOk03gCXV9F5TLD1vis7mq+KfoHsteVK7zLeB+dXV9s+x7cd06WT4+BOxfs/y3Kf6T8INm//314aMdH+46l9RK+sv2ZytY53+W7dszc+viwsxcoDiO8y7g1CXWPSMzb69Z55cUM4vrgEcst4DMnMvMe9WcmTuBDwPrKWYDG3lN1szOZubXKHbVrwfOysyba/pupJjRe3RE7L/c+srtbK/Zzq3AJygC5D1OqMrMHzd4H3dRzFgCPGMFr7uUxe/s9Zl5S11dZ5VPG31ntwFnZuadNev8gOIzOSIi7r8XapO0AgZNSa1k8djIlVx38bFle0V9R2aOUYTWwyPikLrunZk50WB7Py3b9SuogYjYVF7q58byWMssj018VzlkQ4PVbm4U7IBflO11Dfp+DuwP9K2gvG82WNbwfUZEb0ScFxHfK4+dXHwfi7U0eh8r9ViK/wBc1aDvqxQzrY9p0DeemTMNli++l/rvWFLFPEZTUiv5BfBI4MErWGdd2U4t0T8FPLQcV3vs4FLHES6U7bJnDCPiiRRBt4Ni9//nKI6FvAv4b8DzKHav19u5qxrKGdGl6jtgufXVzoo22M7d77MM45uBwykumfRRil34C/zmONVG72Ol1gHbM3O+Qa0LEXETxWEM9fbadyZp7zBoSmolX6c48eQpwD8uc53FMNYHNJod7K8bV4WzgQOB4zLzqtqOiHgDRdBsBadShMxzM/Oc2o6IOJIiaO4NO4FDI+KArDtJKyI6gAdQBHVJ+zh3nUtqJf9EcWmjF0bEb+9qYM1li75dtsc2GDNAMTs6ucSs3nItHhO41IzZAMUM3VUN+p68B6+72gbK9uIGfUu9j/v6bBr5NsW/T8c06Dum3Na3VrA9SU1i0JTUMjJzC8V1NDuBSyOi4Z1/IuKZFJfqgeJkG4CzI+KBNWP2B/6G4vfgcmdHl7KD4rjRhy7Rv4Vihu536up8BXvn5JnVsqVsj61dGBGPobh8VCPTZbvUZ9PI4nf2lxFx912Dyj+fVz7d0+9M0ipw17mklpKZ7yh3n74V2BwR11CczLJ4C8pjgMFyGZl5TUT8FcV1Ia+PiIuAWymuo/koit3xf72HNd0SEdcCR0fEJ4Axipm8z2Xm94DzKQLl1yPi0xS7hh9PcT3Iiyiu9dgKPgr8b+D8iDgOGKf4rJ8D/DPwBw3W+Uq5zgfLz/4WipOc3r/Ui2TmJyPiecDvA9+PiEsogvzzKXbdfzozP7H33pakqjijKanlZOZfUITE91OcOPJyijDzbIrjME+lCHGL48+iuDbjOMW9tc+g+P13NvC0Ried7IaXAJdS3JHorcDbKM94z8wvUFyc/QcUYewVFBdYP65cpyVk5i8oruN5KcXn+2rgYRQXjn/9Eut8keIyUncAf0bxufz5Ml7uRcCrKGZE/xg4nWLm+NVln6QWEJkruUqIJEmStDzOaEqSJKkSBk1JkiRVwqApSZKkShg0JUmSVAmDpiRJkiph0JQkSVIlDJqSJEmqhEFTkiRJlTBoSpIkqRIGTUmSJFXCoClJkqRKGDQlSZJUCYOmJEmSKmHQlCRJUiUMmpIkSaqEQVOSJEmVMGhKkiSpEv8f68718QfgyMsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 261,
       "width": 333
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 368,
       "width": 388
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Completeness= pd.read_table(f'{working_dir}/genomes/checkm/completeness.tsv',index_col=0)\n",
    "\n",
    "f = plt.figure(figsize=(5,figheight))\n",
    "ax=sns.scatterplot(y=Completeness.Completeness, x= Completeness.Contamination,alpha=0.5,color='k')\n",
    "\n",
    "from matplotlib.patches import Rectangle\n",
    "from matplotlib.collections import PatchCollection\n",
    "ax.add_collection(PatchCollection([Rectangle((0,90),5,10)], facecolor='green',alpha=0.3))\n",
    "\n",
    "saveplot('completness_contamination',**plot_params)\n",
    "\n",
    "\n",
    "plt.show()\n",
    "\n",
    "\n",
    "ax=sns.swarmplot(y=Completeness.Completeness -5*Completeness.Contamination,color='k',alpha=0.5,\n",
    "                 x=Completeness['Marker lineage'].map(lambda s: s.split()[0]))\n",
    "_ =ax.set_xticklabels(ax.get_xticklabels(),rotation=90)\n",
    "_ =ax.set_ylabel('Quality score')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(45, 13)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Completeness.loc[(Completeness.Completeness>90) & (Completeness.Contamination<5)].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Taxonomy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "checkmTax= pd.read_table(f'{working_dir}/genomes/checkm/taxonomy.tsv',index_col=0)\n",
    "\n",
    "\n",
    "checkmTax = pd.DataFrame(list(checkmTax['Taxonomy (contained)'].apply(lambda s: s.split(';'))),\n",
    "                       index=checkmTax.index)\n",
    "checkmTax.columns=['kindom','phylum','class','order','family','genus','species']\n",
    "\n",
    "checkmTax=checkmTax.fillna(method='ffill',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "Tax= pd.read_table(f'{working_dir}/genomes/taxonomy/taxonomy.tsv',index_col=0)\n",
    "\n",
    "Tax=Tax.replace('NoStdName',np.nan).fillna(method='ffill',axis=1)\n",
    "\n",
    "Labels=Tax.species+' '+Tax.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "phylum= checkmTax.phylum.map(lambda s: s.split('__')[1])"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Tax.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(69, 13)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Completeness.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "from atlas.scripts.utils import tree\n",
    "\n",
    "T = tree.load_tree(f'{working_dir}/genomes/tree/tree.nwk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from ete3 import TreeStyle\n",
    "\n",
    "ts = TreeStyle()\n",
    "ts.show_leaf_name= False\n",
    "ts.mode = \"c\"\n",
    "ts.scale=200\n",
    "ts.show_scale=False\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "T.render(\"%%inline\",tree_style=ts,layout=tree.layout_black_circles)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Stats based on raw Counts\n",
    "\n",
    "There are good reasons to use rawcounts and use centric log ratios, see more in \n",
    "\n",
    "Gloor, Gregory B., Jean M. Macklaim, Vera Pawlowsky-Glahn, and Juan J. Egozcue. 2017. “Microbiome Datasets Are Compositional: And This Is Not Optional.” Frontiers in Microbiology 8 (November). Frontiers: 2224. doi:10.3389/fmicb.2017.02224."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Raw counts samples x MAGs "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>Sample</th>\n",
       "      <th>MAG01</th>\n",
       "      <th>MAG02</th>\n",
       "      <th>MAG03</th>\n",
       "      <th>MAG04</th>\n",
       "      <th>MAG05</th>\n",
       "      <th>MAG06</th>\n",
       "      <th>MAG07</th>\n",
       "      <th>MAG08</th>\n",
       "      <th>MAG09</th>\n",
       "      <th>MAG10</th>\n",
       "      <th>...</th>\n",
       "      <th>MAG60</th>\n",
       "      <th>MAG61</th>\n",
       "      <th>MAG62</th>\n",
       "      <th>MAG63</th>\n",
       "      <th>MAG64</th>\n",
       "      <th>MAG65</th>\n",
       "      <th>MAG66</th>\n",
       "      <th>MAG67</th>\n",
       "      <th>MAG68</th>\n",
       "      <th>MAG69</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>C1</td>\n",
       "      <td>532</td>\n",
       "      <td>8913</td>\n",
       "      <td>85558</td>\n",
       "      <td>100611</td>\n",
       "      <td>41563</td>\n",
       "      <td>318511</td>\n",
       "      <td>37088</td>\n",
       "      <td>100752</td>\n",
       "      <td>21448</td>\n",
       "      <td>34777</td>\n",
       "      <td>...</td>\n",
       "      <td>50299</td>\n",
       "      <td>26880</td>\n",
       "      <td>37834</td>\n",
       "      <td>30967</td>\n",
       "      <td>157089</td>\n",
       "      <td>7619</td>\n",
       "      <td>3560</td>\n",
       "      <td>17679</td>\n",
       "      <td>4312</td>\n",
       "      <td>60867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>C13</td>\n",
       "      <td>197</td>\n",
       "      <td>18007</td>\n",
       "      <td>8882</td>\n",
       "      <td>784486</td>\n",
       "      <td>70002</td>\n",
       "      <td>128642</td>\n",
       "      <td>517</td>\n",
       "      <td>58088</td>\n",
       "      <td>12426</td>\n",
       "      <td>62115</td>\n",
       "      <td>...</td>\n",
       "      <td>46477</td>\n",
       "      <td>113983</td>\n",
       "      <td>124091</td>\n",
       "      <td>58688</td>\n",
       "      <td>180897</td>\n",
       "      <td>17130</td>\n",
       "      <td>26087</td>\n",
       "      <td>19440</td>\n",
       "      <td>14994</td>\n",
       "      <td>161443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>C14</td>\n",
       "      <td>226</td>\n",
       "      <td>19770</td>\n",
       "      <td>3757</td>\n",
       "      <td>797582</td>\n",
       "      <td>24518</td>\n",
       "      <td>45427</td>\n",
       "      <td>193</td>\n",
       "      <td>22513</td>\n",
       "      <td>8094</td>\n",
       "      <td>55139</td>\n",
       "      <td>...</td>\n",
       "      <td>15815</td>\n",
       "      <td>155273</td>\n",
       "      <td>32631</td>\n",
       "      <td>50482</td>\n",
       "      <td>149742</td>\n",
       "      <td>12026</td>\n",
       "      <td>8118</td>\n",
       "      <td>20728</td>\n",
       "      <td>14400</td>\n",
       "      <td>139391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>C2</td>\n",
       "      <td>369</td>\n",
       "      <td>11054</td>\n",
       "      <td>25992</td>\n",
       "      <td>481991</td>\n",
       "      <td>69543</td>\n",
       "      <td>205274</td>\n",
       "      <td>1660</td>\n",
       "      <td>116274</td>\n",
       "      <td>11955</td>\n",
       "      <td>46803</td>\n",
       "      <td>...</td>\n",
       "      <td>67664</td>\n",
       "      <td>82717</td>\n",
       "      <td>104162</td>\n",
       "      <td>46949</td>\n",
       "      <td>121092</td>\n",
       "      <td>13395</td>\n",
       "      <td>130743</td>\n",
       "      <td>13904</td>\n",
       "      <td>9585</td>\n",
       "      <td>90133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>C3</td>\n",
       "      <td>203</td>\n",
       "      <td>12220</td>\n",
       "      <td>2828</td>\n",
       "      <td>354181</td>\n",
       "      <td>37773</td>\n",
       "      <td>94925</td>\n",
       "      <td>423</td>\n",
       "      <td>4250</td>\n",
       "      <td>13431</td>\n",
       "      <td>36248</td>\n",
       "      <td>...</td>\n",
       "      <td>76710</td>\n",
       "      <td>28826</td>\n",
       "      <td>10630</td>\n",
       "      <td>34009</td>\n",
       "      <td>164772</td>\n",
       "      <td>12688</td>\n",
       "      <td>7256</td>\n",
       "      <td>13466</td>\n",
       "      <td>58348</td>\n",
       "      <td>59935</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 69 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Sample  MAG01  MAG02  MAG03   MAG04  MAG05   MAG06  MAG07   MAG08  MAG09  \\\n",
       "C1        532   8913  85558  100611  41563  318511  37088  100752  21448   \n",
       "C13       197  18007   8882  784486  70002  128642    517   58088  12426   \n",
       "C14       226  19770   3757  797582  24518   45427    193   22513   8094   \n",
       "C2        369  11054  25992  481991  69543  205274   1660  116274  11955   \n",
       "C3        203  12220   2828  354181  37773   94925    423    4250  13431   \n",
       "\n",
       "Sample  MAG10  ...  MAG60   MAG61   MAG62  MAG63   MAG64  MAG65   MAG66  \\\n",
       "C1      34777  ...  50299   26880   37834  30967  157089   7619    3560   \n",
       "C13     62115  ...  46477  113983  124091  58688  180897  17130   26087   \n",
       "C14     55139  ...  15815  155273   32631  50482  149742  12026    8118   \n",
       "C2      46803  ...  67664   82717  104162  46949  121092  13395  130743   \n",
       "C3      36248  ...  76710   28826   10630  34009  164772  12688    7256   \n",
       "\n",
       "Sample  MAG67  MAG68   MAG69  \n",
       "C1      17679   4312   60867  \n",
       "C13     19440  14994  161443  \n",
       "C14     20728  14400  139391  \n",
       "C2      13904   9585   90133  \n",
       "C3      13466  58348   59935  \n",
       "\n",
       "[5 rows x 69 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Counts= pd.read_csv(f'{working_dir}/genomes/counts/raw_counts_genomes.tsv',index_col=0,sep='\\t')\n",
    "Counts=Counts.T\n",
    "Counts.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# transforme counts\n",
    "\n",
    "centrig log ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "data= Counts.copy()\n",
    "\n",
    "min_nz_value = data[data>0].min().min()\n",
    "data=data.replace(0,min_nz_value*0.65).applymap(np.log2)\n",
    "# normalize by geometrical mean\n",
    "data= (data.T-data.mean(1)).T\n",
    "\n",
    "\n",
    "data.index.name='Samples'\n",
    "data.columns.name='Genomes'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd, seaborn as sns\n",
    "import scipy.spatial as sp, scipy.cluster.hierarchy as hc\n",
    "\n",
    "mags= Tax.index\n",
    "\n",
    "\n",
    "from itertools import combinations\n",
    "\n",
    "dist=np.array([T.get_distance(*pair) for pair in combinations(mags,2)])\n",
    "\n",
    "linkage = hc.linkage(dist, method='complete')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 6 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 470,
       "width": 474
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "color_map= dict(zip(phylum.unique() ,\n",
    "               sns.color_palette('deep',n_colors=len(phylum.unique()))\n",
    "              ))\n",
    "\n",
    "metadata= pd.DataFrame(index=data.index)\n",
    "metadata['Source']=metadata.index.str[0].map({'C':'Cecum','F':'Feces'})\n",
    "\n",
    "cg=sns.clustermap(data.T,figsize=(7.5,7.5),\n",
    "            row_cluster=True,cmap='RdBu_r', center=0,\n",
    "             yticklabels= [],#Labels,\n",
    "            row_linkage=linkage,\n",
    "               row_colors=phylum.map(color_map),\n",
    "               col_colors= metadata.Source.map({'Cecum':'orange','Feces':'brown'}),\n",
    "           \n",
    "              )\n",
    "\n",
    "saveplot('heatmap',**plot_params)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fraction of mapped reads"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "read_stats= pd.read_table(f\"{working_dir}/stats/read_counts.tsv\")\n",
    "read_stats= read_stats.loc[read_stats.Step=='QC']\n",
    "read_stats.index=read_stats.Sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 115.2x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 265,
       "width": 140
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mapped_reads= Counts.sum(1)/ (read_stats.Reads_pe*2+read_stats.Reads_se)\n",
    "mapped_reads=mapped_reads.dropna()\n",
    "\n",
    "f= plt.figure(figsize=(figheight/2.5,figheight))\n",
    "ax= plt.subplot(111)\n",
    "ax.set_ylim([0,1])\n",
    "sns.swarmplot(y=mapped_reads,x=metadata.Source,palette='Greys',ax=ax)\n",
    "ax.set_ylabel('Fraction of mapped reads')\n",
    "\n",
    "saveplot('Mapping_ratio',**plot_params)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "arguments did not match any overloaded call:\n  QColor(Qt.GlobalColor): argument 1 has unexpected type 'tuple'\n  QColor(int): too many arguments\n  QColor(QRgba64): argument 1 has unexpected type 'tuple'\n  QColor(Any): argument 1 has unexpected type 'tuple'\n  QColor(): argument 1 has unexpected type 'tuple'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-40-99f14d504cef>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     38\u001b[0m \u001b[0mts\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow_scale\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     39\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 40\u001b[0;31m \u001b[0m_\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mT\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrender\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Figures/tree.svg\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtree_style\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mts\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlayout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheatmap\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     41\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     42\u001b[0m \u001b[0mT\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrender\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"%%inline\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtree_style\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mts\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlayout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheatmap\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/lib/python3.6/site-packages/ete3/coretype/tree.py\u001b[0m in \u001b[0;36mrender\u001b[0;34m(self, file_name, layout, w, h, tree_style, units, dpi)\u001b[0m\n\u001b[1;32m   1363\u001b[0m             return drawer.render_tree(self, file_name, w=w, h=h,\n\u001b[1;32m   1364\u001b[0m                                     \u001b[0mlayout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlayout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtree_style\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtree_style\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1365\u001b[0;31m                                       units=units, dpi=dpi)\n\u001b[0m\u001b[1;32m   1366\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1367\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"cpickle\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/lib/python3.6/site-packages/ete3/treeview/drawer.py\u001b[0m in \u001b[0;36mrender_tree\u001b[0;34m(t, imgName, w, h, layout, tree_style, header, units, dpi)\u001b[0m\n\u001b[1;32m    102\u001b[0m         \u001b[0mn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_feature\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"_nid\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnid\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    103\u001b[0m     \u001b[0mscene\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minit_scene\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlayout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtree_style\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 104\u001b[0;31m     \u001b[0mtree_item\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn2i\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn2f\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrender\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    105\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    106\u001b[0m     \u001b[0mscene\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minit_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn2i\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn2f\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/lib/python3.6/site-packages/ete3/treeview/qt4_render.py\u001b[0m in \u001b[0;36mrender\u001b[0;34m(root_node, img, hide_root)\u001b[0m\n\u001b[1;32m    299\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mnode\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mroot_node\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtraverse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mis_leaf_fn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0m_leaf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    300\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mnode\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mroot_node\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mhide_root\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 301\u001b[0;31m             \u001b[0mrender_node_content\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn2i\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn2f\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    302\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    303\u001b[0m     \u001b[0;31m# Adjust content to rect or circular layout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/lib/python3.6/site-packages/ete3/treeview/qt4_render.py\u001b[0m in \u001b[0;36mrender_node_content\u001b[0;34m(node, n2i, n2f, img)\u001b[0m\n\u001b[1;32m    633\u001b[0m             \u001b[0mnode_ball\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_SphereItem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    634\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mnode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimg_style\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"shape\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"circle\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 635\u001b[0;31m             \u001b[0mnode_ball\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_CircleItem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    636\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mnode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimg_style\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"shape\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"square\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    637\u001b[0m             \u001b[0mnode_ball\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_RectItem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/lib/python3.6/site-packages/ete3/treeview/qt4_render.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, node)\u001b[0m\n\u001b[1;32m     81\u001b[0m         \u001b[0m_ActionDelegator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     82\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 83\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetBrush\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mQBrush\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mQColor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimg_style\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"fgcolor\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     84\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetPen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mQPen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mQColor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimg_style\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"fgcolor\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     85\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: arguments did not match any overloaded call:\n  QColor(Qt.GlobalColor): argument 1 has unexpected type 'tuple'\n  QColor(int): too many arguments\n  QColor(QRgba64): argument 1 has unexpected type 'tuple'\n  QColor(Any): argument 1 has unexpected type 'tuple'\n  QColor(): argument 1 has unexpected type 'tuple'"
     ]
    }
   ],
   "source": [
    "T= ete3.ClusterTree(T.write())\n",
    "\n",
    "d= data.groupby(metadata.Source).mean().T\n",
    "\n",
    "#d.columns=d.columns.droplevel(0)\n",
    "\n",
    "d.index.name='#Names'\n",
    "T.link_to_arraytable( d.to_csv(sep='\\t'))\n",
    "\n",
    "\n",
    "\n",
    "# nodes are linked to the array table\n",
    "#array =  t.arraytable\n",
    "\n",
    "\n",
    "v= d.abs().max().max()\n",
    "\n",
    "from ete3 import ClusterTree, TreeStyle, AttrFace, ProfileFace, TextFace\n",
    "from ete3.treeview.faces import add_face_to_node\n",
    "def heatmap(node):\n",
    "    #node.img_style[\"size\"]=0\n",
    "    \n",
    "    # If node is a leaf\n",
    "    if node.is_leaf():\n",
    "        # And a line profile\n",
    "        size=20\n",
    "        profileFace  = ProfileFace(d.max().max(), d.min().min(), 0,width=size*d.shape[1],height=size ,style= \"heatmap\")\n",
    "        add_face_to_node(profileFace, node, 0, aligned=True)\n",
    "        \n",
    "        #node.img_style[\"fgcolor\"]=color_map[phylum[node.name]]\n",
    "\n",
    "\n",
    "        \n",
    "ts = TreeStyle()\n",
    "ts.show_leaf_name= False\n",
    "ts.mode = \"c\"\n",
    "#ts.scale=200\n",
    "ts.show_scale=False\n",
    "\n",
    "_= T.render(\"Figures/tree.svg\",tree_style=ts,layout=heatmap)\n",
    "\n",
    "T.render(\"%%inline\",tree_style=ts,layout=heatmap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bin Id\n",
       "MAG01         Bacteria\n",
       "MAG02    Bacteroidetes\n",
       "MAG03       Firmicutes\n",
       "MAG04    Bacteroidetes\n",
       "MAG05       Firmicutes\n",
       "             ...      \n",
       "MAG65    Bacteroidetes\n",
       "MAG66       Firmicutes\n",
       "MAG67    Bacteroidetes\n",
       "MAG68    Bacteroidetes\n",
       "MAG69    Bacteroidetes\n",
       "Name: phylum, Length: 69, dtype: object"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "phylum"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "\n",
    "pca= PCA()\n",
    "transformed_data= pca.fit_transform(data)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a3918e7f0>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ZufTKNrZ+yL7p+muesPRmf87+sMK+HX0BAEbXSMzhZ3UtDtrDDN6D7ugr7AMArA+Bn4tmR18AgNEn8HPRLnRHX6P8AABrT+DnktjRFwBgtAn8XBI7+gIAjDaBn4tmR18AgNEn8HPR7OgLADD6BH4uSX9H3+VC/7k7+gIAsPZGYuMtNq613NEXAIALJ/BzydZiR18AAC6OKT0MzWru6AsAwMUR+AEAoMMEfgAA6DCBHwAAOkzgBwCADhP4AQCgwwR+AABWxeKNN23EuT6sww8AwFD1N92876ET2XfgWI6fPpPJqyayd/f2TE9N2pRzjQn8AAAMzdx8y6kzj2Vm9v4cOnLyCdfufuBYdu7YmtmZPdkysUnoXyOm9AAAMDTjY7Vk2O87dORkZmbvF/bXkMAPAMBQzM237D98fNmw33foyMnsP3zCnP41IvADADAU42OVfQeODdT2zoNHjfKvEYEfAIChOX76zGDtTp1d5UroE/gBABiayasmBmu3ZfMqV0KfwA8AwFDMzbfs3b19oLa37brWHP41IvADADAU42OV6anJ7NyxdcV2O3dszfTUNnP414jADwDA0MzNt8zO7Fk29PfX4Te6v3ZsvAUAwNCMj1W2TGzKXbffnP2HT+TOg0dz/NTZTG7ZnNt2XZvpqW122l1jAj8AAEPVD/M3XX9Npqe2PX6+P6ov7K8tU3oAAFgVi4O9oL8+BH4AAOgwgR8AADpM4AcAgA4T+AEAoMMEfgAA6DCBHwCADWPxhl028Do/6/ADADDy+pt13ffQiew7cCzHT5/J5FUT2bt7e6anJm3mtQKBHwCAkTY333LqzGOZmb0/h46cfMK1ux84lp07tmZ2Zk+2TGwS+pcwElN6quqaqvqhqrqrqv60qr5aVV+qqv1V9Q+qauA6q+qRqmrLvP3lan4cAAAM3/hYLRn2+w4dOZmZ2fuF/WWMygj/q5P8RpK/SHJPkj9P8j8l+V+TvDPJ91TVq1trg07S+lKStyxx/vQQagUAYI3Mzbfc99CJZcN+36EjJ7P/8IncdP01gv8ioxL4P5PklUn+U2ttvn+yqv5lkv+a5LYshP87B+zvZGvtjmEXCQDA2hofq+w7cGygtncePJrpqW2rXNHGMxJTelprH26t/cdzw37v/F8meXvv5UvXvDAAgHNYIWZ9HD99ZrB2p86uciUb06iM8K/ksd7xaxdwz+aqem2Sb0vy5SSfTPLR1trcsIsDALrPCjHra/KqicHabdm8ypVsTCMd+KvqiiR/v/fyDy7g1qcnec+icw9X1Uxr7SNDKQ4AuCxYIWZ9zc237N29PXc/cP5pPbftutYvX0sYiSk9K/jXSf5Wkg+01v7zgPfMJrk1C6H/yiTfnuQdSa5L8sGqev4gnVTVgaXektxwoR8EALBxWSFmfY2PVaanJrNzx9YV2+3csTXTU9v8f1jCyAb+qvqxJD+V5E+SvG7Q+1prb+o9E/D51tpXWmufaq39aJJfTfLkJHesSsEAQOfMzbfsP3x84BVizOlfHXPzLbMze5YN/f2/svjvv7SRnNJTVbcn+bUk/z3Jra21R4fQ7duz8AvEiwdp3FrbvUxtB5LsGkI9AMCIs0LMaBgfq2yZ2JS7br85+w+fyJ0Hj+b4qbOZ3LI5t+26NtNT20zlWcHIBf6q+vEkb07yqSyE/S8Mqet+P1cOqT8A4DJghZjR0A/zN11/zRN+seqP6gv7yxupKT1V9S+yEPYfSPKyIYb9JLmpd/zsEPsEADrOCjGjZXGwF/TPb2QCf1W9MQsP6R7Iwsj+iRXabqqqG6rq+kXnn1dVT1ui/TOSvK338r1DLBsA6LD+CjGD6K8QA6NmJKb0VNXrk/xCkrkkH0vyY1Xf8NvaI621d/f+vT3Jg0n+LAur7/S9OslPV9U9SR5OcirJ9Um+L8lEkg8k+ZVV+SAAgM45d4WYlR7c7a8QA6NoJAJ/kmf2juNJfnyZNh9J8u7z9HNPkuck2ZmFKTxXJjmZZH8W1uV/T2vNr94AwMD6K8QstzTnuSvEmF7CKBqJwN9auyMXsFxma+2RJN/wFdXbVMvGWgDA0Fghho1uJAI/AMAos0IMG9nIPLQLADDqrBDDRiTwAwBAhwn8AADQYQI/AAB0mMAPAAAdJvADAECHCfwAANBhAj8AAHSYwA8AAB0m8AMAQIcJ/AAA0GECPwAAdJjADwAAHSbwAwBAhwn8AADQYQI/AAB0mMAPAAAdJvADAECHCfwAANBhAj8AAHSYwA8AAB0m8AMAQIcJ/AAA0GECPwAAdJjADwAAHSbwwwibm28rvgYAOJ8r1rsA4BvNzbeMj1Xue+hE9h04luOnz2Tyqons3b0901OTj18HADgfgR9GzNx8y6kzj2Vm9v4cOnLyCdfufuBYdu7YmtmZPdkysUnoBwDOy5QeGDHjY7Vk2O87dORkZmbvF/YBgIEI/DBC5uZb9h8+vmzY7zt05GT2Hz5hTj8AcF4CP4yQ8bHKvgPHBmp758GjRvkBgPMS+GHEHD99ZrB2p86uciUAQBcI/DBiJq+aGKzdls2rXAkA0AUCP4yQufmWvbu3D9T2tl3XmsMPAJyXwA8jZHysMj01mZ07tq7YbueOrZme2mYOPwBwXgI/jJi5+ZbZmT3Lhv7+OvxG9wGAQdh4C0bM+Fhly8Sm3HX7zdl/+ETuPHg0x0+dzeSWzblt17WZntpmp10AYGACP4ygfpi/6fprMj217fHz/VF9YR8AGNTITOmpqmur6req6nNVdbaqHqmqt1TVUy+wn6f17nuk18/nev1eu1q1w2pZHOwFfQDgQo3ECH9VXZ/kE0m+OcnvJ/mTJN+V5A1JXlFVN7fWvjhAP9f0+nl2kg8neV+SG5LMJPm+qrqptfbZ1fkoAABg9IzKCP+/y0LY/7HW2g+01n66tXZLkjcneU6SfzVgP/9HFsL+m1trt/b6+YEs/OLwzb33AwAAl411D/xV9awkL0/ySJJ/u+jyzyf5cpLXVdWV5+nnyiSv67X/+UWX39br/2/33h8AAFwW1j3wJ7mld/zD1tr8uRdaa6eSfDzJNyV54Xn6uSnJk5N8vHffuf3MJ/nD3suXXXLFAACwQYzCHP7n9I6fWeb64Sz8BeDZST50if2k1895VdWBZS7dMMj9AAAwCkZhhP/q3vFLy1zvn19569Hh9QMAAJ0xCiP859Nfh/BStxW9oH5aa7uX7GRh5H/XJdYCAABrYhRG+Psj71cvc/0pi9qtdj8AANAZoxD4P907Lje3fqp3XG5u/rD7AQCAzhiFwH9P7/jyqnpCPVW1JcnNSb6a5I/O088f9drd3Lvv3H7GsvDg77nvDwAAOm/dA39r7aEsLJl5XZLbF11+U5Irk/xOa+3L/ZNVdUNVPWG1nNba6STv6bW/Y1E//6TX/3+20y4AAJeTUXlo9x8n+USSt1bVrUkeTHJjFtbM/0ySn1nU/sHesRad/5dJXprkJ6vqO5P81yTPTfL9Sb6Qb/yFAgAAOm3dR/iTx0f5X5Dk3VkI+j+V5Pokb01yU2vtiwP288UsbMD11iR/o9fPjUlmk+zuvR8AALhsjMoIf1prR5LMDNh28cj+udceTfKG3hsAAFzWRmKEHwAAWB0CPwAAdJjADwAAHSbwAwBAhwn8AADQYQI/AAB0mMAPAABLmJtvK77eKEZmHX4AABgFc/Mt42OV+x46kX0HjuX46TOZvGoie3dvz/TU5OPXNwqBHwAAeubmW06deSwzs/fn0JGTT7h29wPHsnPH1szO7MmWiU0bJvSb0gMAAD3jY7Vk2O87dORkZmbv3zBhPxH4AQAgycLo/v7Dx5cN+32HjpzM/sMnNsycfoEfAACyMLq/78CxgdreefDohhnlF/gBAKDn+Okzg7U7dXaVKxkegR8AAHomr5oYrN2WzatcyfAI/AAAkIU5/Ht3bx+o7W27rjWHHwAANpLxscr01GR27ti6YrudO7ZmemqbOfwAALDRzM23zM7sWTb099fh3yij+4mNtwAA4HHjY5UtE5ty1+03Z//hE7nz4NEcP3U2k1s257Zd12Z6apuddgEAYCPrh/mbrr8m01PbHj/fH9XfSGE/MaUHAACWtDjYb7Sg3yfwAwBAhwn8AADQYQI/AAB0mMAPAAAdJvADAECHCfwAANBhAj8AAHSYwA8AAB0m8AMAQIcJ/AAA0GECPwAAdJjADwAAHSbwAwBAhwn8AADQYQI/AAB0mMAPAAAdJvADAECHCfwAANBhAj8AAHTYugf+qpqqqn9RVR+uqiNV9ddV9fmq+v2qetkF9nVdVbUV3t63Wh8HAACMoivWu4Akv5jk7yX570k+kOTRJM9J8sokr6yqN7TW3nqBff5xkruXOP+pSykUAAA2mlEI/H+Q5Jdba4fOPVlVL0ny/yX5N1X1f7XW/uIC+nygtXbHEGsEAIANad2n9LTW3r047PfOfyTJvUmelORFa10XAAB0wSiM8K/ksd7xaxd437dW1Y8kuSbJF5Pc11r75FArAwCADWBkA39VPSPJrUm+kuSjF3j7d/fezu3v3iSvb639+YDv/8Ayl264wFoAAGDdrPuUnqVU1eYkv5tkc5I7Wmv/Y8Bbv5KFh4B3J3lq7+0lSe5J8tIkH6qqK4de8Cqbm28rvgYAgOUMZYS/qh5J8owLuOV3W2uvXaav8STvSXJzkvcn+ZVBO22tfSHJzy06/dGqenmS/UluTPJDSX5tgL52L1PfgSS7Bq3pUszNt4yPVe576ET2HTiW46fPZPKqiezdvT3TU5OPXwcAgOUMa0rPQ0nOXED7zy11shf235vk1Ul+L8lrW2uXPJzdWvtaVb0zC4H/xRkg8K+3ufmWU2cey8zs/Tl05OQTrt39wLHs3LE1szN7smVik9APAMCyhhL4W2u3XmofVXVFkv+QhbD/H5L8/dba3KX2e47jveOGmNIzPlZLhv2+Q0dOZmb2/tx1+81rXBkAABvJSMzhr6onJdmXhbD/O0leN+SwnyQv7B0/O+R+h25uvmX/4ePLhv2+Q0dOZv/hE+b0AwCwrHUP/L0HdO9K8v1J3pVkprU2f557rq6qG6rqWxadv7H3y8Pi9rck+Yney/cOp/LVMz5W2Xfg2EBt7zx41JQeAACWNQrLcr49yfcmOZHkWJKfq/qGAHtva+3ec16/Kslskt9O8oPnnP/lJM/rLcF5tHfuO5Lc0vv3G1trnxhi7avm+OnBHok4fursKlcCAMBGNgqB/5m947Z84wo757p3gL7ek4VfBvYk+Z4km5J8PgsPAL+ttfaxiy9zbU1eNTFYuy2bV7mS4Vq8spCVhgAAVte6B/7W2ksv4p53J3n3EufflYVpQRva3HzL3t3bc/cD55/Wc9uuazdEaLbEKADA+lj3wM83Gh+rTE9NZueOrSs+uLtzx9ZMT21bw8oujiVGAQDWz7o/tMvS5uZbZmf2ZOeOrUte74fkjbBCz6BLjAr7AADDZ4R/RI2PVbZMbMpdt9+c/YdP5M6DR3P81NlMbtmc23Zdm+mpbRtiGszcfMt9D50YeInRm66/ZuQ/JgCAjUTgH2H94HvT9dc8YepOf1R/IwTjC11idCNMUQIA2EhM6dkAFgf7jRD0z2WJUQCA9SPws+q6usQoAMBGIPCzqvpLjA6iv8QoAADDI/BfBhaH6LUM1ecuMbqS/hKjG226EgCrZz1/fkGXeGi3w0Zls6v+EqPLLc157hKjAj8Ao/LzC7pC4O+oUdrsqitLjAKw+kbp5xd0hcDfUYNudnXX7TevWT3Jxl5iFIDVN2o/v6ALzOHvoLn5lv2Hjw+82dVaz+lf6TUAl69R/vkFG5nA30EXutmV0A3AKPDzC1aHwN9RNrsCYCPy8wuGT+DvKJtdAbAR+fkFwyfwd5DNrgDYiPz8gtUh8HeQza4A2Ij8/ILVIfB3VH+zq+W+aZ672RUAjAo/v2D4rMPfUTa7AmAj8vMLhk/g7zCbXQGwEfn5BcNlSs9lwGZXAGxEfn7BcAj8AADQYQI/AAB0mMAPAAAdJvADAECHCfwAANBhAj8AAHSYwA8AAB0m8AMAQIcJ/AAA0GECPwAAdJjADwAAHSbwAwBAhwn8AADQYQI/AAB0mMAPAAAdJvADAEDvxKnXAAARDklEQVSHCfwAANBh6x74q+q6qmorvL3vIvp8UVV9oKoeraqvVNUnq+rHq2p8NT4GAAAYVVesdwHn+OMkdy9x/lMX0klVfX+SO5OcSfL+JI8m+TtJ3pzk5iSvvrQyAQBg4xilwP9Aa+2OS+mgqp6S5DeTzCV5aWvtv/XOvzHJh5PsrarXtNYu+K8GAACwEa37lJ4h25tkMsn7+mE/SVprZ5L8bO/lP1qPwgAAYD2M0gj/t1bVjyS5JskXk9zXWvvkBfZxS+/4B0tc+2iSryR5UVVtbq2dvfhSAQBgYxilwP/dvbfHVdW9SV7fWvvzAft4Tu/4mcUXWmtfq6qHkzwvybOSPHjxpQIAwMYwCoH/K0l+MQsP7H62d+47ktyR5GVJPlRV39la+/IAfV3dO35pmev981vP11FVHVjm0g0D1AEAACNhKHP4q+qR8yytufjtvf17W2tfaK39XGvtYGvtZO/to0lenuS/JPkbSX5oGHUmqf67HVJ/AAAw0oY1wv9QFpbBHNTnztegNwXnnUluTPLiJL82QL/9Efyrl7n+lEXtVnr/u5c63xv53zVALQAAsO6GEvhba7cOo58lHO8drxyw/aeTvCDJs5M8YUpOVV2R5JlJvpavTx0CAIBOG/VlOV/YOw4a0D/cO75iiWsvTvJNST5hhR4AAC4X6x74q+rGqnrSEudvSfITvZfvXXTt6qq6oaq+ZdFt+5KcSPKaqnrBOe0nkvxS7+VvDK14AAAYcaOwSs8vJ3lebwnOo71z35Gvr6n/xtbaJxbd86oks0l+O8kP9k+21v6qqn44C8H/3qp6X5JHk7wyC0t27kvy/tX5MAAAYPSMQuB/TxYC/J4k35NkU5LPJ/m9JG9rrX3sQjprrd1dVS9J8jNJbksykeRPk/xkkre21qzQAwDAZWPdA39r7V1J3nWB97w7ybtXuP7xJN97SYUBAEAHrPscfgAAYPUI/AAA0GECPwAAdJjADwAAHSbwAwBAhwn8AADQYQI/AMA6mJtvK76GYVn3dfgBAC4nc/Mt42OV+x46kX0HjuX46TOZvGoie3dvz/TU5OPXYVgEfgCANTI333LqzGOZmb0/h46cfMK1ux84lp07tmZ2Zk+2TGwS+hkaU3oAANbI+FgtGfb7Dh05mZnZ+4V9hkrgBwBYA3PzLfsPH1827PcdOnIy+w+fMKefoRH4AQDWwPhYZd+BYwO1vfPgUaP8DI3ADwCwRo6fPjNYu1NnV7kSLicCPwDAGpm8amKwdls2r3IlXE4EfgCANTA337J39/aB2t6261pz+BkagR8AYA2Mj1Wmpyazc8fWFdvt3LE101PbzOFnaAR+AIA1MjffMjuzZ9nQ31+H3+g+w2TjLQCANTI+VtkysSl33X5z9h8+kTsPHs3xU2czuWVzbtt1baanttlpl6ET+AEA1lA/zN90/TWZntr2+Pn+qL6wz7CZ0gMAsA4WB3tBn9Ui8AMAQIcJ/AAA0GECPwAAdJjADwAAHSbwAwBAhwn8AADQYQI/AAB0mMAPDGzxVu+2fgeA0WenXeC8+tu83/fQiew7cCzHT5/J5FUT2bt7e6anJm0DDwAjTOAHVjQ333LqzGOZmb0/h46cfMK1ux84lp07tmZ2Zk+2TGwS+gFgBJnSA6xofKyWDPt9h46czMzs/cI+AIwogR9Y1tx8y/7Dx5cN+32HjpzM/sMnzOkHgBEk8APLGh+r7DtwbKC2dx48apQfAEaQwA+s6PjpM4O1O3V2lSsBAC6GwA+saPKqicHabdm8ypUAABdD4AeWNTffsnf39oHa3rbrWnP4AWAECfzAssbHKtNTk9m5Y+uK7Xbu2JrpqW3m8APACBL4gRXNzbfMzuxZNvT31+E3ug8Ao8nGW8CKxscqWyY25a7bb87+wydy58GjOX7qbCa3bM5tu67N9NQ2O+0CwAhb98BfVe9O8vrzNPtwa+3WAfq6LsnDKzR5f2vtNQMXByTJ42H+puuvyfTUtsfP90f1hX0AGF3rHviT3J3kkWWuvS7Js5J88AL7/ONev4t96gL7Ac6xONgL+gAw+tY98LfW7s4S4byqtib550n+Osm7L7DbB1prd1xycQAAsMGN8kO7r0vy5CT/d2vtxHoXAwAAG9G6j/Cv4Id7x39/Efd+a1X9SJJrknwxyX2ttU8OrTIAANggRjLwV9VNSb49yWdaa/dcRBff3Xs7t897k7y+tfbnA9ZwYJlLN1xEPQAAsC5GdUrPP+wdf/MC7/tKkl9MsjvJU3tvL0lyT5KXJvlQVV05pBoBAGDkDWWEv6oeSfKMC7jld1trr12mr6uT/N1cxMO6rbUvJPm5Rac/WlUvT7I/yY1JfijJrw3Q1+5l6juQZNeF1AUAAOtlWFN6Hkpy5gLaf26Fa69N8k1J3jesh3Vba1+rqndmIfC/OAMEfgAA6IKhBP5BNsW6AP2Hdd8xxD6T5HjvaEoPAACXjZGaw19VNyZ5fhYe1r13yN2/sHf87JD7BQCAkTVSgT9ff1h3xaU4q+rqqrqhqr5l0fkbq+pJS7S/JclP9F6+dyiVAgDABjAyy3JW1VOS/L0sPKz72+dp/qoks712P3jO+V9O8rzeEpxHe+e+I8ktvX+/sbX2iSGVDAAAI29kAn+S/z0L8+sv5WHd92Thl4E9Sb4nyaYkn0/ye0ne1lr72DAKBQCAjWJkAn9r7TeS/MaAbd+dJZbsbK29K8m7hloYAABsYKM2hx8AABgigR8AADpM4AcAgA4T+AEAoMMEfgAA6DCBHwBYVXPzbcXXwOoamWU5AYBumZtvGR+r3PfQiew7cCzHT5/J5FUT2bt7e6anJh+/DqwugR8AGLq5+ZZTZx7LzOz9OXTk5BOu3f3AsezcsTWzM3uyZWKT0A+rzJQeAGDoxsdqybDfd+jIyczM3i/swxoQ+AGAoZqbb9l/+PiyYb/v0JGT2X/4hDn9sMoEfgBgqMbHKvsOHBuo7Z0Hjxrlh1Um8AMAQ3f89JnB2p06u8qVAAI/ADB0k1dNDNZuy+ZVrgQQ+AGAoZqbb9m7e/tAbW/bda05/LDKBH4AYKjGxyrTU5PZuWPriu127tia6alt5vDDKhP4AYChm5tvmZ3Zs2zo76/Db3QfVp+NtwCAoRsfq2yZ2JS7br85+w+fyJ0Hj+b4qbOZ3LI5t+26NtNT2+y0C2tE4AcAVkU/zN90/TWZntr2+Pn+qL6wD2vDlB4AYFUtDvaCPqwtgR8AADpM4AcAgA4T+AEAoMMEfgAA6DCBHwAAOkzgBwCADhP4AQCgwwR+AADoMIEfAAA6TOAHAIAOE/gBAKDDqrW23jVsKFX1xSc/+clPe+5zn7vepQAA0GEPPvhgvvrVrz7aWrvmUvoR+C9QVT2c5ClJHlnnUtbTDb3jn6xrFYwCnwv0+Vygz+cC5/L5cGmuS/JXrbVnXkonAj8XrKoOJElrbfd618L68rlAn88F+nwucC6fD6PBHH4AAOgwgR8AADpM4AcAgA4T+AEAoMMEfgAA6DCr9AAAQIcZ4QcAgA4T+AEAoMMEfgAA6DCBHwAAOkzgBwCADhP4AQCgwwR+AADoMIGfgVTVpqp6Q1XNVtUDVfXXVdWq6ocGuPf1VfVfq+p0VX2pqu6tqv9lLepmbVXVdb3Pi+Xe3rfeNTJcVXVtVf1WVX2uqs5W1SNV9Zaqeup618ba6v2/X+5r/y/Xuz6Gq6r2VtWvV9XHquqvev+f33uee15UVR+oqker6itV9cmq+vGqGl+rui9XV6x3AWwYVyZ5S+/fn0/yl0l2nO+mqvqVJD+V5GiS30zypCSvSfIfq+qfttbetjrlss7+OMndS5z/1FoXwuqpquuTfCLJNyf5/SR/kuS7krwhySuq6ubW2hfXsUTW3pfy9Z8V5zq91oWw6n42yfOz8P/2aJIbVmpcVd+f5M4kZ5K8P8mjSf5OkjcnuTnJq1ez2MudnXYZSFU9KcmtSR5orf1FVd2R5OeT/HBr7Z3L3POiJB9P8lCSPa21/9E7f12SA1n4JeKG1tojq10/a6P3//bhJL/dWvvBdS2GVVdV/znJy5P8WGvt1885/6tJfiLJO1prP7pe9bG2quqRJGmtXbe+lbAWquplWQj6f5rkJUnuSfK7rbXXLtH2Kb12Vye5ubX233rnJ5J8OMlNSf631pq/Aq8SU3oYSGvtr1trH2yt/cUF3Nb/Qf+v+mG/19cjSf5tks1JZoZXJbBWqupZWQj7j2Th6/lcP5/ky0leV1VXrnFpwBpord3TWjvcBhs53ptkMsn7+mG/18eZLPylIEn+0SqUSY/Az2q6pXf8gyWufXBRG7rlW6vqR6rqX/aO37HeBTF0/a/dP2ytzZ97obV2Kgt/3fumJC9c68JYV5ur6rW9r/03VNXLzM8mK+eBjyb5SpIXVdXmtSvp8mIOP6uiN6q3PcnpZf4qcLh3fPbaVcUa+u7e2+Oq6t4kr2+t/fm6VMSwPad3/Mwy1w9n4S8Az07yoTWpiFHw9CTvWXTu4aqaaa19ZD0KYiQs+/2itfa1qno4yfOSPCvJg2tZ2OXCCD+r5ere8UvLXO+f37oGtbB2vpLkF5PsTvLU3lt/budLk3zIFI/O8DXOYrNZeNbr6Vl4Ruvbk7wjyXVJPlhVz1+/0lhnvl+sM4H/MnKeJdOWeltxea0h8dT4iLmUz5PW2hdaaz/XWjvYWjvZe/toFkZ6/0uSv5HkvEu50gnVO/oav0y01t7UWvtwa+3zrbWvtNY+1Xto+1eTPDnJHetbISPM94tVZkrP5eWhLCyHNajPXcL76v+2fvUy18/32z7rZ+ifJ70/2b4zyY1JXpzk1y6yNkbH+b7Gn7KoHZevt2dheeYXr3chrBvfL9aZwH8Zaa3duobv68tVdSzJ9qr6liXm8U/1jsvN/2WdrOLnyfHe0ZSebvh077jcczi+xun7Qu/oa//y9ekkL8jC94sD516oqiuSPDPJ15J8du1LuzyY0sNq+nDv+Iolrn3PojZ0X3+1Ft/Qu+Ge3vHlVfWEnyVVtSULG+l8NckfrXVhjJybekdf+5evlfLAi7OwotcnWmtn166ky4vAz2p6e+/4M1X11P7J3uZMtyc5m4WHvOiIqrqxt0nb4vO3ZGEjpiRZi2dDWGWttYeS/GEWHsi8fdHlN2VhNPd3WmtfXuPSWAdV9byqetoS55+RpL+juq/9y9e+JCeSvKaqXtA/2dt465d6L39jPQq7XNhpl4FV1U/n61tnf2cWttT+RL6+xOb+xbvuVtX/meQns7Ab374kT0ry95Jck+SfttbeFjqjt/Tm85Lcm4X/50nyHfn6GsxvbK390jfeyUZUVddn4XvANyf5/Swsp3djkpdlYSrPi1prX1y/Clkrvd3XfzoLf/l5OMmpJNcn+b4kE0k+kORVrbW/Xq8aGa6q+oEkP9B7+fQkfzsLf8X5WO/cidbaP1vUfl8WnhF7X5JHk7wyC0t27kvydwfcxIuLIPAzsF6Ye8kKTX67tfaDS9z3+iT/JMnfTDKf5GCSf9Na+39XoUzWUVX9gySvSvK3kmxLsinJ55Pcl+RtrbWPrXA7G1BV7UjyC1n4U/01Sf4iyd1J3tRae3Q9a2PtVNVLsrC7+s58fVnOk0keyMK6/O8R5rql90vez6/Q5M9aa9ctuufmJD+ThWleE0n+NMlvJXlra21udSolEfgBAKDTzOEHAIAOE/gBAKDDBH4AAOgwgR8AADpM4AcAgA4T+AEAoMMEfgAA6DCBHwAAOkzgBwCADhP4AQCgwwR+AADoMIEfAAA6TOAHAIAOE/gBAKDDBH4AAOgwgR8AADpM4AcAgA77/wE0SD0sccW+AAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 250,
       "width": 382
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(transformed_data[:,0],\n",
    "                transformed_data[:,1])\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MA plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a38a59a90>"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 263,
       "width": 386
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Means= data.groupby(metadata.Source).mean().T\n",
    "\n",
    "\n",
    "def MA_plot(Abundance,Effect,ax=None,xlabel='Average abundance [clog2]',ylabel='FC [log2]'):\n",
    "    \n",
    "    if ax is None:\n",
    "        ax = plt.subplot(111)\n",
    "\n",
    "    sns.scatterplot(Abundance,Effect,color='grey',ax=ax)\n",
    "\n",
    "\n",
    "    ax.set_xlabel(xlabel)\n",
    "    ax.set_ylabel(ylabel)\n",
    "    \n",
    "    ax.hlines(0,*ax.get_xlim())\n",
    "    \n",
    "    return ax\n",
    "    \n",
    "    \n",
    "MA_plot(Means.mean(1), Means['Feces']-Means['Cecum'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "EggNOG= pd.read_table('AL/Genomecatalog/annotations/eggNog.tsv',index_col=0)\n",
    "\n",
    "bactNOG= EggNOG['Matching_OGs'].str.contains('bactNOG')\n",
    "bactNOG= EggNOG.loc[bactNOG,'Matching_OGs'].apply(lambda s: [nog for nog in s.split(',') if 'bactNOG' in nog][0])\n",
    "\n",
    "bactNOG.name='bactNOG'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "#EggNOG= pd.read_table('AL/Genomecatalog/annotations/eggNog.tsv',index_col=0)\n",
    "\n",
    "Kegg= EggNOG['KEGG_KO'].dropna()\n",
    "#bactNOG= EggNOG.loc[bactNOG,'Matching_OGs'].apply(lambda s: [nog for nog in s.split(',') if 'bactNOG' in nog][0])\n",
    "\n",
    "#bactNOG.name='bactNOG'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "K= pd.DataFrame(0,index=Kegg.index,columns=np.unique(np.sum(list(Kegg.str.split(',')))))\n",
    "\n",
    "for g,l in Kegg.str.split(',').iteritems():\n",
    "    K.loc[g,l]+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "Clusters= pd.read_table('AL/Genomecatalog/clustering/orf2gene.tsv',sep='\\t',index_col=0)\n",
    "Clusters['Genome']=Clusters.index.map(lambda s: s.split('_')[0])\n",
    "\n",
    "#Clusters= Clusters.join(bactNOG,on='Gene')\n",
    "C=Clusters.groupby(['Gene','Genome']).size().unstack().T.fillna(0)\n",
    "#I=Clusters.groupby(['bactNOG','Genome']).size().unstack().T.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(69, 41827)"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "C.loc[:,K.index].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(41827, 4486)"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "K.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "assert K.max().max()==1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "I=C.loc[:,K.index]@K"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a9c22e6d8>"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 250,
       "width": 377
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "I.sum().hist(bins=[0,1,2,3,5,10,20,30,50,70,100])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 263,
       "width": 408
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "DR =DimensionalReduction((I.T/I.sum(1)).T) #((I.T-I.mean(1))/I.std(1)).T)\n",
    "\n",
    "pl=DR.plot_Components_2D(hue = Completeness.Completeness,palette='Greens')\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/silas/anaconda3/lib/python3.6/site-packages/matplotlib/figure.py:98: MatplotlibDeprecationWarning: \n",
      "Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
      "  \"Adding an axes using the same arguments as a previous axes \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 317,
       "width": 477
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f= plt.figure(figsize=(5,5))\n",
    "plt.axis('equal')\n",
    "ax= DR.plot_Components_2D(hue=phylum,palette='deep')\n",
    "ax.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "\n",
    "ax.set_yticks([-0.01,0,0.01,0.02])\n",
    "ax.set_xticks([-0.02,-0.01,0,0.01,0.02])\n",
    "\n",
    "saveplot('PCA_functions',**plot_params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a9b3660f0>"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 263,
       "width": 399
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "DR.plot_Loadings_2D()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "(-DR.components.loc[2]+DR.components.loc[1]).sort_values()\n",
    "foi='05DRM@bactNOG'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "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>seed_eggNOG_ortholog</th>\n",
       "      <th>seed_ortholog_evalue</th>\n",
       "      <th>seed_ortholog_score</th>\n",
       "      <th>predicted_gene_name</th>\n",
       "      <th>GO_terms</th>\n",
       "      <th>KEGG_KO</th>\n",
       "      <th>BiGG_Reactions</th>\n",
       "      <th>Annotation_tax_scope</th>\n",
       "      <th>Matching_OGs</th>\n",
       "      <th>best_OG|evalue|score</th>\n",
       "      <th>categories</th>\n",
       "      <th>eggNOG_HMM_model_annotation</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>query_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Gene007721</th>\n",
       "      <td>573061.Clocel_0148</td>\n",
       "      <td>3.000000e-19</td>\n",
       "      <td>103.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene021640</th>\n",
       "      <td>575590.HMPREF0156_00701</td>\n",
       "      <td>9.100000e-17</td>\n",
       "      <td>93.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,09DNZ@bctoNOG,0XQ7Y@NOG</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>surface antigen BspA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene071451</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>6.100000e-41</td>\n",
       "      <td>174.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene029525</th>\n",
       "      <td>213810.RUM_08710</td>\n",
       "      <td>9.900000e-21</td>\n",
       "      <td>107.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene021758</th>\n",
       "      <td>575593.HMPREF0491_02893</td>\n",
       "      <td>3.400000e-23</td>\n",
       "      <td>115.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0XQ7Y@NOG</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Cell surface protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene062319</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>1.900000e-64</td>\n",
       "      <td>253.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene062367</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>1.100000e-118</td>\n",
       "      <td>433.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene029608</th>\n",
       "      <td>573061.Clocel_1425</td>\n",
       "      <td>1.600000e-23</td>\n",
       "      <td>116.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene000192</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>3.600000e-54</td>\n",
       "      <td>218.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene051425</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>3.800000e-80</td>\n",
       "      <td>305.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene056183</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>7.700000e-76</td>\n",
       "      <td>290.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene056196</th>\n",
       "      <td>545696.HOLDEFILI_02215</td>\n",
       "      <td>8.400000e-11</td>\n",
       "      <td>73.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0I9JW@eryNOG,0P4K6@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bactNOG: Cell surface protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene029675</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>7.500000e-79</td>\n",
       "      <td>300.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene029680</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>4.600000e-49</td>\n",
       "      <td>201.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene029728</th>\n",
       "      <td>573061.Clocel_0148</td>\n",
       "      <td>4.700000e-25</td>\n",
       "      <td>120.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene071764</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>3.600000e-42</td>\n",
       "      <td>178.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene000261</th>\n",
       "      <td>553174.HMPREF0659_A7250</td>\n",
       "      <td>3.200000e-35</td>\n",
       "      <td>154.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bctoNOG: surface antigen BspA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene071801</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>2.300000e-32</td>\n",
       "      <td>145.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene051508</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>3.700000e-106</td>\n",
       "      <td>391.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene013720</th>\n",
       "      <td>213810.RUM_08710</td>\n",
       "      <td>1.900000e-31</td>\n",
       "      <td>142.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene039148</th>\n",
       "      <td>536227.CcarbDRAFT_1853</td>\n",
       "      <td>7.900000e-304</td>\n",
       "      <td>1048.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene008037</th>\n",
       "      <td>697329.Rumal_0746</td>\n",
       "      <td>1.000000e-12</td>\n",
       "      <td>80.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0NDYS@firmNOG,0XQ7Y@NOG</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>surface protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene008040</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>9.900000e-19</td>\n",
       "      <td>100.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene062647</th>\n",
       "      <td>1042156.CXIVA_21200</td>\n",
       "      <td>2.900000e-06</td>\n",
       "      <td>60.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene051760</th>\n",
       "      <td>706436.HMPREF9074_03810</td>\n",
       "      <td>2.700000e-11</td>\n",
       "      <td>75.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,09GDD@bctoNOG,0PAZW@flaNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>M</td>\n",
       "      <td>cell surface protein (Leucine-rich repeat prot...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene072597</th>\n",
       "      <td>382464.VDG1235_4694</td>\n",
       "      <td>7.100000e-19</td>\n",
       "      <td>100.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0XQ7Y@NOG,1DI1G@verNOG,1DNV5@ver...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>M</td>\n",
       "      <td>Inherit from bactNOG: Cell surface protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene013972</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>1.800000e-64</td>\n",
       "      <td>252.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene014016</th>\n",
       "      <td>575590.HMPREF0156_00701</td>\n",
       "      <td>1.500000e-80</td>\n",
       "      <td>305.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,09DNZ@bctoNOG,0XQ7Y@NOG</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>surface antigen BspA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene014018</th>\n",
       "      <td>203275.BFO_2000</td>\n",
       "      <td>6.500000e-38</td>\n",
       "      <td>165.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bctoNOG: surface antigen BspA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene062733</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>1.700000e-82</td>\n",
       "      <td>312.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene086592</th>\n",
       "      <td>138119.DSY3856</td>\n",
       "      <td>4.900000e-09</td>\n",
       "      <td>67.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene007019</th>\n",
       "      <td>626522.GCWU000325_01274</td>\n",
       "      <td>2.600000e-40</td>\n",
       "      <td>171.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bctoNOG: surface antigen BspA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene028817</th>\n",
       "      <td>553174.HMPREF0659_A7250</td>\n",
       "      <td>7.700000e-27</td>\n",
       "      <td>126.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bctoNOG: surface antigen BspA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene070428</th>\n",
       "      <td>553174.HMPREF0659_A7250</td>\n",
       "      <td>2.800000e-43</td>\n",
       "      <td>181.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bctoNOG: surface antigen BspA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene070429</th>\n",
       "      <td>203275.BFO_2000</td>\n",
       "      <td>2.700000e-42</td>\n",
       "      <td>178.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bctoNOG: surface antigen BspA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene061732</th>\n",
       "      <td>573061.Clocel_0148</td>\n",
       "      <td>5.700000e-17</td>\n",
       "      <td>94.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene100970</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>1.300000e-20</td>\n",
       "      <td>105.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene100989</th>\n",
       "      <td>626522.GCWU000325_02665</td>\n",
       "      <td>1.700000e-30</td>\n",
       "      <td>139.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,09JEJ@bctoNOG,0XQ7Y@NOG</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bactNOG: Cell surface protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene061773</th>\n",
       "      <td>402612.FP0166</td>\n",
       "      <td>2.700000e-19</td>\n",
       "      <td>102.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,09GDD@bctoNOG,0PAZW@flaNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>M</td>\n",
       "      <td>cell surface protein (Leucine-rich repeat prot...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene061829</th>\n",
       "      <td>347256.MHO_2260</td>\n",
       "      <td>6.500000e-45</td>\n",
       "      <td>188.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0XQ7Y@NOG,1CAVF@tenNOG</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bactNOG: Cell surface protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene021035</th>\n",
       "      <td>479437.Elen_1195</td>\n",
       "      <td>2.700000e-10</td>\n",
       "      <td>72.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>00TM8@actNOG,05DRM@bactNOG,0XQ7Y@NOG</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bactNOG: Cell surface protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene021036</th>\n",
       "      <td>553973.CLOHYLEM_07755</td>\n",
       "      <td>3.900000e-09</td>\n",
       "      <td>68.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene061884</th>\n",
       "      <td>573061.Clocel_3323</td>\n",
       "      <td>3.500000e-29</td>\n",
       "      <td>134.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene038441</th>\n",
       "      <td>553174.HMPREF0659_A7250</td>\n",
       "      <td>2.500000e-22</td>\n",
       "      <td>112.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bctoNOG: surface antigen BspA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene021151</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>1.700000e-80</td>\n",
       "      <td>306.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene044699</th>\n",
       "      <td>428126.CLOSPI_02317</td>\n",
       "      <td>3.900000e-62</td>\n",
       "      <td>245.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0I7T5@eryNOG,0NDYS@firmNOG,COG54...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>M</td>\n",
       "      <td>Cell surface protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene089655</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>1.000000e-74</td>\n",
       "      <td>288.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene101367</th>\n",
       "      <td>264731.PRU_1403</td>\n",
       "      <td>2.700000e-08</td>\n",
       "      <td>65.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,09GDD@bctoNOG,0XQ7Y@NOG</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>M</td>\n",
       "      <td>cell surface protein (Leucine-rich repeat prot...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene044864</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>7.900000e-41</td>\n",
       "      <td>173.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene038658</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>4.000000e-53</td>\n",
       "      <td>215.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene051141</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>2.500000e-31</td>\n",
       "      <td>142.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene071056</th>\n",
       "      <td>545695.TREAZ_3516</td>\n",
       "      <td>5.400000e-57</td>\n",
       "      <td>228.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0XQ7Y@NOG</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Cell surface protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene068237</th>\n",
       "      <td>402612.FP0174</td>\n",
       "      <td>3.200000e-22</td>\n",
       "      <td>111.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,09GDD@bctoNOG,0PAZW@flaNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>M</td>\n",
       "      <td>cell surface protein (Leucine-rich repeat prot...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene068256</th>\n",
       "      <td>203275.BFO_2000</td>\n",
       "      <td>1.200000e-38</td>\n",
       "      <td>166.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bctoNOG: surface antigen BspA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene101507</th>\n",
       "      <td>428126.CLOSPI_02317</td>\n",
       "      <td>1.800000e-22</td>\n",
       "      <td>112.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0I7T5@eryNOG,0NDYS@firmNOG,COG54...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>M</td>\n",
       "      <td>Cell surface protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene068285</th>\n",
       "      <td>553174.HMPREF0659_A7250</td>\n",
       "      <td>7.300000e-33</td>\n",
       "      <td>147.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bctoNOG: surface antigen BspA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene038726</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>3.100000e-186</td>\n",
       "      <td>658.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene038767</th>\n",
       "      <td>203275.BFO_2000</td>\n",
       "      <td>3.500000e-63</td>\n",
       "      <td>248.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bctoNOG: surface antigen BspA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene089944</th>\n",
       "      <td>768706.Desor_3179</td>\n",
       "      <td>3.700000e-124</td>\n",
       "      <td>451.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>N</td>\n",
       "      <td>Domain protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene101701</th>\n",
       "      <td>626522.GCWU000325_02665</td>\n",
       "      <td>4.100000e-69</td>\n",
       "      <td>267.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bactNOG[38]</td>\n",
       "      <td>05DRM@bactNOG,09JEJ@bctoNOG,0XQ7Y@NOG</td>\n",
       "      <td>NA|NA|NA</td>\n",
       "      <td>S</td>\n",
       "      <td>Inherit from bactNOG: Cell surface protein</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>226 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               seed_eggNOG_ortholog  seed_ortholog_evalue  \\\n",
       "query_name                                                  \n",
       "Gene007721       573061.Clocel_0148          3.000000e-19   \n",
       "Gene021640  575590.HMPREF0156_00701          9.100000e-17   \n",
       "Gene071451        768706.Desor_3179          6.100000e-41   \n",
       "Gene029525         213810.RUM_08710          9.900000e-21   \n",
       "Gene021758  575593.HMPREF0491_02893          3.400000e-23   \n",
       "Gene062319        768706.Desor_3179          1.900000e-64   \n",
       "Gene062367        768706.Desor_3179         1.100000e-118   \n",
       "Gene029608       573061.Clocel_1425          1.600000e-23   \n",
       "Gene000192        768706.Desor_3179          3.600000e-54   \n",
       "Gene051425        768706.Desor_3179          3.800000e-80   \n",
       "Gene056183        768706.Desor_3179          7.700000e-76   \n",
       "Gene056196   545696.HOLDEFILI_02215          8.400000e-11   \n",
       "Gene029675        768706.Desor_3179          7.500000e-79   \n",
       "Gene029680        768706.Desor_3179          4.600000e-49   \n",
       "Gene029728       573061.Clocel_0148          4.700000e-25   \n",
       "Gene071764        768706.Desor_3179          3.600000e-42   \n",
       "Gene000261  553174.HMPREF0659_A7250          3.200000e-35   \n",
       "Gene071801        768706.Desor_3179          2.300000e-32   \n",
       "Gene051508        768706.Desor_3179         3.700000e-106   \n",
       "Gene013720         213810.RUM_08710          1.900000e-31   \n",
       "Gene039148   536227.CcarbDRAFT_1853         7.900000e-304   \n",
       "Gene008037        697329.Rumal_0746          1.000000e-12   \n",
       "Gene008040        768706.Desor_3179          9.900000e-19   \n",
       "Gene062647      1042156.CXIVA_21200          2.900000e-06   \n",
       "Gene051760  706436.HMPREF9074_03810          2.700000e-11   \n",
       "Gene072597      382464.VDG1235_4694          7.100000e-19   \n",
       "Gene013972        768706.Desor_3179          1.800000e-64   \n",
       "Gene014016  575590.HMPREF0156_00701          1.500000e-80   \n",
       "Gene014018          203275.BFO_2000          6.500000e-38   \n",
       "Gene062733        768706.Desor_3179          1.700000e-82   \n",
       "...                             ...                   ...   \n",
       "Gene086592           138119.DSY3856          4.900000e-09   \n",
       "Gene007019  626522.GCWU000325_01274          2.600000e-40   \n",
       "Gene028817  553174.HMPREF0659_A7250          7.700000e-27   \n",
       "Gene070428  553174.HMPREF0659_A7250          2.800000e-43   \n",
       "Gene070429          203275.BFO_2000          2.700000e-42   \n",
       "Gene061732       573061.Clocel_0148          5.700000e-17   \n",
       "Gene100970        768706.Desor_3179          1.300000e-20   \n",
       "Gene100989  626522.GCWU000325_02665          1.700000e-30   \n",
       "Gene061773            402612.FP0166          2.700000e-19   \n",
       "Gene061829          347256.MHO_2260          6.500000e-45   \n",
       "Gene021035         479437.Elen_1195          2.700000e-10   \n",
       "Gene021036    553973.CLOHYLEM_07755          3.900000e-09   \n",
       "Gene061884       573061.Clocel_3323          3.500000e-29   \n",
       "Gene038441  553174.HMPREF0659_A7250          2.500000e-22   \n",
       "Gene021151        768706.Desor_3179          1.700000e-80   \n",
       "Gene044699      428126.CLOSPI_02317          3.900000e-62   \n",
       "Gene089655        768706.Desor_3179          1.000000e-74   \n",
       "Gene101367          264731.PRU_1403          2.700000e-08   \n",
       "Gene044864        768706.Desor_3179          7.900000e-41   \n",
       "Gene038658        768706.Desor_3179          4.000000e-53   \n",
       "Gene051141        768706.Desor_3179          2.500000e-31   \n",
       "Gene071056        545695.TREAZ_3516          5.400000e-57   \n",
       "Gene068237            402612.FP0174          3.200000e-22   \n",
       "Gene068256          203275.BFO_2000          1.200000e-38   \n",
       "Gene101507      428126.CLOSPI_02317          1.800000e-22   \n",
       "Gene068285  553174.HMPREF0659_A7250          7.300000e-33   \n",
       "Gene038726        768706.Desor_3179         3.100000e-186   \n",
       "Gene038767          203275.BFO_2000          3.500000e-63   \n",
       "Gene089944        768706.Desor_3179         3.700000e-124   \n",
       "Gene101701  626522.GCWU000325_02665          4.100000e-69   \n",
       "\n",
       "            seed_ortholog_score predicted_gene_name GO_terms KEGG_KO  \\\n",
       "query_name                                                             \n",
       "Gene007721                103.2                 NaN      NaN     NaN   \n",
       "Gene021640                 93.2                 NaN      NaN     NaN   \n",
       "Gene071451                174.1                 NaN      NaN     NaN   \n",
       "Gene029525                107.1                 NaN      NaN     NaN   \n",
       "Gene021758                115.5                 NaN      NaN     NaN   \n",
       "Gene062319                253.1                 NaN      NaN     NaN   \n",
       "Gene062367                433.3                 NaN      NaN     NaN   \n",
       "Gene029608                116.7                 NaN      NaN     NaN   \n",
       "Gene000192                218.8                 NaN      NaN     NaN   \n",
       "Gene051425                305.4                 NaN      NaN     NaN   \n",
       "Gene056183                290.4                 NaN      NaN     NaN   \n",
       "Gene056196                 73.9                 NaN      NaN     NaN   \n",
       "Gene029675                300.8                 NaN      NaN     NaN   \n",
       "Gene029680                201.8                 NaN      NaN     NaN   \n",
       "Gene029728                120.2                 NaN      NaN     NaN   \n",
       "Gene071764                178.3                 NaN      NaN     NaN   \n",
       "Gene000261                154.8                 NaN      NaN     NaN   \n",
       "Gene071801                145.6                 NaN      NaN     NaN   \n",
       "Gene051508                391.7                 NaN      NaN     NaN   \n",
       "Gene013720                142.9                 NaN      NaN     NaN   \n",
       "Gene039148               1048.9                 NaN      NaN     NaN   \n",
       "Gene008037                 80.5                 NaN      NaN     NaN   \n",
       "Gene008040                100.5                 NaN      NaN     NaN   \n",
       "Gene062647                 60.8                 NaN      NaN     NaN   \n",
       "Gene051760                 75.1                 NaN      NaN     NaN   \n",
       "Gene072597                100.9                 NaN      NaN     NaN   \n",
       "Gene013972                252.7                 NaN      NaN     NaN   \n",
       "Gene014016                305.8                 NaN      NaN     NaN   \n",
       "Gene014018                165.2                 NaN      NaN     NaN   \n",
       "Gene062733                312.8                 NaN      NaN     NaN   \n",
       "...                         ...                 ...      ...     ...   \n",
       "Gene086592                 67.4                 NaN      NaN     NaN   \n",
       "Gene007019                171.8                 NaN      NaN     NaN   \n",
       "Gene028817                126.3                 NaN      NaN     NaN   \n",
       "Gene070428                181.8                 NaN      NaN     NaN   \n",
       "Gene070429                178.3                 NaN      NaN     NaN   \n",
       "Gene061732                 94.0                 NaN      NaN     NaN   \n",
       "Gene100970                105.9                 NaN      NaN     NaN   \n",
       "Gene100989                139.0                 NaN      NaN     NaN   \n",
       "Gene061773                102.1                 NaN      NaN     NaN   \n",
       "Gene061829                188.3                 NaN      NaN     NaN   \n",
       "Gene021035                 72.4                 NaN      NaN     NaN   \n",
       "Gene021036                 68.6                 NaN      NaN     NaN   \n",
       "Gene061884                134.4                 NaN      NaN     NaN   \n",
       "Gene038441                112.1                 NaN      NaN     NaN   \n",
       "Gene021151                306.2                 NaN      NaN     NaN   \n",
       "Gene044699                245.0                 NaN      NaN     NaN   \n",
       "Gene089655                288.1                 NaN      NaN     NaN   \n",
       "Gene101367                 65.9                 NaN      NaN     NaN   \n",
       "Gene044864                173.3                 NaN      NaN     NaN   \n",
       "Gene038658                215.7                 NaN      NaN     NaN   \n",
       "Gene051141                142.1                 NaN      NaN     NaN   \n",
       "Gene071056                228.0                 NaN      NaN     NaN   \n",
       "Gene068237                111.3                 NaN      NaN     NaN   \n",
       "Gene068256                166.4                 NaN      NaN     NaN   \n",
       "Gene101507                112.8                 NaN      NaN     NaN   \n",
       "Gene068285                147.1                 NaN      NaN     NaN   \n",
       "Gene038726                658.3                 NaN      NaN     NaN   \n",
       "Gene038767                248.1                 NaN      NaN     NaN   \n",
       "Gene089944                451.8                 NaN      NaN     NaN   \n",
       "Gene101701                267.7                 NaN      NaN     NaN   \n",
       "\n",
       "           BiGG_Reactions Annotation_tax_scope  \\\n",
       "query_name                                       \n",
       "Gene007721            NaN          bactNOG[38]   \n",
       "Gene021640            NaN          bactNOG[38]   \n",
       "Gene071451            NaN          bactNOG[38]   \n",
       "Gene029525            NaN          bactNOG[38]   \n",
       "Gene021758            NaN          bactNOG[38]   \n",
       "Gene062319            NaN          bactNOG[38]   \n",
       "Gene062367            NaN          bactNOG[38]   \n",
       "Gene029608            NaN          bactNOG[38]   \n",
       "Gene000192            NaN          bactNOG[38]   \n",
       "Gene051425            NaN          bactNOG[38]   \n",
       "Gene056183            NaN          bactNOG[38]   \n",
       "Gene056196            NaN          bactNOG[38]   \n",
       "Gene029675            NaN          bactNOG[38]   \n",
       "Gene029680            NaN          bactNOG[38]   \n",
       "Gene029728            NaN          bactNOG[38]   \n",
       "Gene071764            NaN          bactNOG[38]   \n",
       "Gene000261            NaN          bactNOG[38]   \n",
       "Gene071801            NaN          bactNOG[38]   \n",
       "Gene051508            NaN          bactNOG[38]   \n",
       "Gene013720            NaN          bactNOG[38]   \n",
       "Gene039148            NaN          bactNOG[38]   \n",
       "Gene008037            NaN          bactNOG[38]   \n",
       "Gene008040            NaN          bactNOG[38]   \n",
       "Gene062647            NaN          bactNOG[38]   \n",
       "Gene051760            NaN          bactNOG[38]   \n",
       "Gene072597            NaN          bactNOG[38]   \n",
       "Gene013972            NaN          bactNOG[38]   \n",
       "Gene014016            NaN          bactNOG[38]   \n",
       "Gene014018            NaN          bactNOG[38]   \n",
       "Gene062733            NaN          bactNOG[38]   \n",
       "...                   ...                  ...   \n",
       "Gene086592            NaN          bactNOG[38]   \n",
       "Gene007019            NaN          bactNOG[38]   \n",
       "Gene028817            NaN          bactNOG[38]   \n",
       "Gene070428            NaN          bactNOG[38]   \n",
       "Gene070429            NaN          bactNOG[38]   \n",
       "Gene061732            NaN          bactNOG[38]   \n",
       "Gene100970            NaN          bactNOG[38]   \n",
       "Gene100989            NaN          bactNOG[38]   \n",
       "Gene061773            NaN          bactNOG[38]   \n",
       "Gene061829            NaN          bactNOG[38]   \n",
       "Gene021035            NaN          bactNOG[38]   \n",
       "Gene021036            NaN          bactNOG[38]   \n",
       "Gene061884            NaN          bactNOG[38]   \n",
       "Gene038441            NaN          bactNOG[38]   \n",
       "Gene021151            NaN          bactNOG[38]   \n",
       "Gene044699            NaN          bactNOG[38]   \n",
       "Gene089655            NaN          bactNOG[38]   \n",
       "Gene101367            NaN          bactNOG[38]   \n",
       "Gene044864            NaN          bactNOG[38]   \n",
       "Gene038658            NaN          bactNOG[38]   \n",
       "Gene051141            NaN          bactNOG[38]   \n",
       "Gene071056            NaN          bactNOG[38]   \n",
       "Gene068237            NaN          bactNOG[38]   \n",
       "Gene068256            NaN          bactNOG[38]   \n",
       "Gene101507            NaN          bactNOG[38]   \n",
       "Gene068285            NaN          bactNOG[38]   \n",
       "Gene038726            NaN          bactNOG[38]   \n",
       "Gene038767            NaN          bactNOG[38]   \n",
       "Gene089944            NaN          bactNOG[38]   \n",
       "Gene101701            NaN          bactNOG[38]   \n",
       "\n",
       "                                                 Matching_OGs  \\\n",
       "query_name                                                      \n",
       "Gene007721  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene021640              05DRM@bactNOG,09DNZ@bctoNOG,0XQ7Y@NOG   \n",
       "Gene071451  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene029525  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene021758                            05DRM@bactNOG,0XQ7Y@NOG   \n",
       "Gene062319  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene062367  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene029608  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene000192  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene051425  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene056183  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene056196  05DRM@bactNOG,0I9JW@eryNOG,0P4K6@firmNOG,0XQ7Y...   \n",
       "Gene029675  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene029680  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene029728  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene071764  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene000261  057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...   \n",
       "Gene071801  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene051508  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene013720  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene039148  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene008037              05DRM@bactNOG,0NDYS@firmNOG,0XQ7Y@NOG   \n",
       "Gene008040  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene062647  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene051760  05DRM@bactNOG,09GDD@bctoNOG,0PAZW@flaNOG,0XQ7Y...   \n",
       "Gene072597  05DRM@bactNOG,0XQ7Y@NOG,1DI1G@verNOG,1DNV5@ver...   \n",
       "Gene013972  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene014016              05DRM@bactNOG,09DNZ@bctoNOG,0XQ7Y@NOG   \n",
       "Gene014018  057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...   \n",
       "Gene062733  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "...                                                       ...   \n",
       "Gene086592  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene007019  057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...   \n",
       "Gene028817  057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...   \n",
       "Gene070428  057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...   \n",
       "Gene070429  057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...   \n",
       "Gene061732  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene100970  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene100989              05DRM@bactNOG,09JEJ@bctoNOG,0XQ7Y@NOG   \n",
       "Gene061773  05DRM@bactNOG,09GDD@bctoNOG,0PAZW@flaNOG,0XQ7Y...   \n",
       "Gene061829               05DRM@bactNOG,0XQ7Y@NOG,1CAVF@tenNOG   \n",
       "Gene021035               00TM8@actNOG,05DRM@bactNOG,0XQ7Y@NOG   \n",
       "Gene021036  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene061884  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene038441  057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...   \n",
       "Gene021151  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene044699  05DRM@bactNOG,0I7T5@eryNOG,0NDYS@firmNOG,COG54...   \n",
       "Gene089655  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene101367              05DRM@bactNOG,09GDD@bctoNOG,0XQ7Y@NOG   \n",
       "Gene044864  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene038658  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene051141  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene071056                            05DRM@bactNOG,0XQ7Y@NOG   \n",
       "Gene068237  05DRM@bactNOG,09GDD@bctoNOG,0PAZW@flaNOG,0XQ7Y...   \n",
       "Gene068256  057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...   \n",
       "Gene101507  05DRM@bactNOG,0I7T5@eryNOG,0NDYS@firmNOG,COG54...   \n",
       "Gene068285  057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...   \n",
       "Gene038726  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene038767  057AU@bacteNOG,05DRM@bactNOG,09DNZ@bctoNOG,0XQ...   \n",
       "Gene089944  05DRM@bactNOG,0EP2V@cloNOG,0NDYS@firmNOG,0XQ7Y...   \n",
       "Gene101701              05DRM@bactNOG,09JEJ@bctoNOG,0XQ7Y@NOG   \n",
       "\n",
       "           best_OG|evalue|score categories  \\\n",
       "query_name                                   \n",
       "Gene007721             NA|NA|NA          N   \n",
       "Gene021640             NA|NA|NA          S   \n",
       "Gene071451             NA|NA|NA          N   \n",
       "Gene029525             NA|NA|NA          N   \n",
       "Gene021758             NA|NA|NA          N   \n",
       "Gene062319             NA|NA|NA          N   \n",
       "Gene062367             NA|NA|NA          N   \n",
       "Gene029608             NA|NA|NA          N   \n",
       "Gene000192             NA|NA|NA          N   \n",
       "Gene051425             NA|NA|NA          N   \n",
       "Gene056183             NA|NA|NA          N   \n",
       "Gene056196             NA|NA|NA          S   \n",
       "Gene029675             NA|NA|NA          N   \n",
       "Gene029680             NA|NA|NA          N   \n",
       "Gene029728             NA|NA|NA          N   \n",
       "Gene071764             NA|NA|NA          N   \n",
       "Gene000261             NA|NA|NA          S   \n",
       "Gene071801             NA|NA|NA          N   \n",
       "Gene051508             NA|NA|NA          N   \n",
       "Gene013720             NA|NA|NA          N   \n",
       "Gene039148             NA|NA|NA          N   \n",
       "Gene008037             NA|NA|NA          N   \n",
       "Gene008040             NA|NA|NA          N   \n",
       "Gene062647             NA|NA|NA          N   \n",
       "Gene051760             NA|NA|NA          M   \n",
       "Gene072597             NA|NA|NA          M   \n",
       "Gene013972             NA|NA|NA          N   \n",
       "Gene014016             NA|NA|NA          S   \n",
       "Gene014018             NA|NA|NA          S   \n",
       "Gene062733             NA|NA|NA          N   \n",
       "...                         ...        ...   \n",
       "Gene086592             NA|NA|NA          N   \n",
       "Gene007019             NA|NA|NA          S   \n",
       "Gene028817             NA|NA|NA          S   \n",
       "Gene070428             NA|NA|NA          S   \n",
       "Gene070429             NA|NA|NA          S   \n",
       "Gene061732             NA|NA|NA          N   \n",
       "Gene100970             NA|NA|NA          N   \n",
       "Gene100989             NA|NA|NA          S   \n",
       "Gene061773             NA|NA|NA          M   \n",
       "Gene061829             NA|NA|NA          S   \n",
       "Gene021035             NA|NA|NA          S   \n",
       "Gene021036             NA|NA|NA          N   \n",
       "Gene061884             NA|NA|NA          N   \n",
       "Gene038441             NA|NA|NA          S   \n",
       "Gene021151             NA|NA|NA          N   \n",
       "Gene044699             NA|NA|NA          M   \n",
       "Gene089655             NA|NA|NA          N   \n",
       "Gene101367             NA|NA|NA          M   \n",
       "Gene044864             NA|NA|NA          N   \n",
       "Gene038658             NA|NA|NA          N   \n",
       "Gene051141             NA|NA|NA          N   \n",
       "Gene071056             NA|NA|NA          N   \n",
       "Gene068237             NA|NA|NA          M   \n",
       "Gene068256             NA|NA|NA          S   \n",
       "Gene101507             NA|NA|NA          M   \n",
       "Gene068285             NA|NA|NA          S   \n",
       "Gene038726             NA|NA|NA          N   \n",
       "Gene038767             NA|NA|NA          S   \n",
       "Gene089944             NA|NA|NA          N   \n",
       "Gene101701             NA|NA|NA          S   \n",
       "\n",
       "                                  eggNOG_HMM_model_annotation  \n",
       "query_name                                                     \n",
       "Gene007721                                     Domain protein  \n",
       "Gene021640                               surface antigen BspA  \n",
       "Gene071451                                     Domain protein  \n",
       "Gene029525                                     Domain protein  \n",
       "Gene021758                               Cell surface protein  \n",
       "Gene062319                                     Domain protein  \n",
       "Gene062367                                     Domain protein  \n",
       "Gene029608                                     Domain protein  \n",
       "Gene000192                                     Domain protein  \n",
       "Gene051425                                     Domain protein  \n",
       "Gene056183                                     Domain protein  \n",
       "Gene056196         Inherit from bactNOG: Cell surface protein  \n",
       "Gene029675                                     Domain protein  \n",
       "Gene029680                                     Domain protein  \n",
       "Gene029728                                     Domain protein  \n",
       "Gene071764                                     Domain protein  \n",
       "Gene000261         Inherit from bctoNOG: surface antigen BspA  \n",
       "Gene071801                                     Domain protein  \n",
       "Gene051508                                     Domain protein  \n",
       "Gene013720                                     Domain protein  \n",
       "Gene039148                                     Domain protein  \n",
       "Gene008037                                    surface protein  \n",
       "Gene008040                                     Domain protein  \n",
       "Gene062647                                     Domain protein  \n",
       "Gene051760  cell surface protein (Leucine-rich repeat prot...  \n",
       "Gene072597         Inherit from bactNOG: Cell surface protein  \n",
       "Gene013972                                     Domain protein  \n",
       "Gene014016                               surface antigen BspA  \n",
       "Gene014018         Inherit from bctoNOG: surface antigen BspA  \n",
       "Gene062733                                     Domain protein  \n",
       "...                                                       ...  \n",
       "Gene086592                                     Domain protein  \n",
       "Gene007019         Inherit from bctoNOG: surface antigen BspA  \n",
       "Gene028817         Inherit from bctoNOG: surface antigen BspA  \n",
       "Gene070428         Inherit from bctoNOG: surface antigen BspA  \n",
       "Gene070429         Inherit from bctoNOG: surface antigen BspA  \n",
       "Gene061732                                     Domain protein  \n",
       "Gene100970                                     Domain protein  \n",
       "Gene100989         Inherit from bactNOG: Cell surface protein  \n",
       "Gene061773  cell surface protein (Leucine-rich repeat prot...  \n",
       "Gene061829         Inherit from bactNOG: Cell surface protein  \n",
       "Gene021035         Inherit from bactNOG: Cell surface protein  \n",
       "Gene021036                                     Domain protein  \n",
       "Gene061884                                     Domain protein  \n",
       "Gene038441         Inherit from bctoNOG: surface antigen BspA  \n",
       "Gene021151                                     Domain protein  \n",
       "Gene044699                               Cell surface protein  \n",
       "Gene089655                                     Domain protein  \n",
       "Gene101367  cell surface protein (Leucine-rich repeat prot...  \n",
       "Gene044864                                     Domain protein  \n",
       "Gene038658                                     Domain protein  \n",
       "Gene051141                                     Domain protein  \n",
       "Gene071056                               Cell surface protein  \n",
       "Gene068237  cell surface protein (Leucine-rich repeat prot...  \n",
       "Gene068256         Inherit from bctoNOG: surface antigen BspA  \n",
       "Gene101507                               Cell surface protein  \n",
       "Gene068285         Inherit from bctoNOG: surface antigen BspA  \n",
       "Gene038726                                     Domain protein  \n",
       "Gene038767         Inherit from bctoNOG: surface antigen BspA  \n",
       "Gene089944                                     Domain protein  \n",
       "Gene101701         Inherit from bactNOG: Cell surface protein  \n",
       "\n",
       "[226 rows x 12 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EggNOG.loc[bactNOG.index[bactNOG==foi]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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