C. tarsalis Reference Genome Phylogenetic Inferences & Protein Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <span style=\"color:lightseagreen\">Culex tarsalis Reference Genome Phylogenetic Inferences & Protein Prediction:<br>Linking Orthogroup IDs to Functional Descriptions</span>\n",
    "***\n",
    "#### 2021 - 2022 Academic Year\n",
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <span style=\"color:lightseagreen\">Orthogroups & Phylogenetic Inferences With OrthoFinder</span>\n",
    "In order to calculate comparative genomics, OrthoFinder [[1]](https://doi.org/10.1186/s13059-019-1832-y) was used to find orthogroups, orthologs, rooted gene/species trees, and gene duplication events. For the purposes of this project, information on which protein accessions were in which orthogroup was collected, species trees were examined using Dendroscope [[2]](https://academic.oup.com/sysbio/article/61/6/1061/1666897), and gene duplications events were analized. OrthoFinder V2.4.0 and Dendroscope V3.8.3 were used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%script bash --bg\n",
    "\n",
    "module load orthofinder\n",
    "\n",
    "orthofinder -f ./MosProteinFASTAsFolder"
   ]
  },
  {
   "attachments": {
    "SpeciesTree.png": {
     "image/png": 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9ZeWP9KsuJ+z2cu/ppHIqksqpbT3e30/3x1x8p+ny0JdphyEfYHz8o3z3x0c6pcvKH0qb5sV0fbnzdD7tSUXrzWUF6linbVncpr65uy1r/Zyv+5t55XwnLx4vHz2RteNU1lepPT9Ybrafj9TOG34K2f1qvMmPXA7Yz9vkOzfzvfOD6RLpP77oE0nlVNRNr0/vXm/K783rzSbfbiwtv9qya5rD8fyj+H7dbEtRn1La5hK6mzZpaFcpR+RSplM65Af3ebnPRfOndkpj3ne2ym8CxdWpeXWfl5shl/K7XIm385F25enN9LGWH/Ihts3+Ph8w35sOQ7pZ54fu8/OnlymVZH183bTH7tOLPpVPe1LT/tmz07O//Vhui7xiafnVltdN+zEDZ9tDrr/jfl8q8CF9/8swHNa79GMuqpv1u1x6T2m3PuRa3qVxtZ7GS3VOn9Pw+1zFm1djLtjbpj9cjjS8z28Bn16kux3X3Ye02Z/SQ3nfOK3X+aj7ccz/L3i9f1U2PD7Lf6v2lDZvT3O9fyLDiMA3q08f0/XcFlnlOpxL9avmNif0LuVqPeyaw5jD8fpdMxfWQ8qF9lXTvEnreadm/PxesCqlfJMPkfe+HGmV6/h6+6j38S4//rrscsgRfsjl91T+Bu2HZlPOh97f5veGd/kV+t38olfzPk+iwQJ8s/qPFTnbbptNGsaXQy7ApdnSpR9ytV017ZCGbXup+vuUH89VNgfndr1ed/9Syq9yrZ6P9HIcy5Hy2uMi+2sp8U23G475jSEfPMf3NE7zX2J9O6T383vDdWr7Ib28+9RifwINFuCb1ae355XVvjRYVuNmc7X5sS0tknMqv8/V9mazLU3zueq/Lak8P55vSjd7aIZLcj5tzqW8xO6899Xx3dVmc8pb7ksr5ZMS2m+26W5zd3c+eN5zV/rn/ZQOm/x/gLlXnt81bja35975E/kWIeDbtXo5R98+nT41WJqum1P5em6wrMrdnJ2HMiXYNB9KKp9Ledf3b9o+V+pzi+a4albltGfe8NGRrkuT5adnZf2shPbD3c2c3OdU3ub3kj5n/amMpt+XUn7KB/9tftHdfJCn0WABvl39fa7JL9rjNBfX9uXQttuh+5zKc7U9pHXfDttmlU79Jn3/qZRfDrBN+/5FztSllbLvVzmolyO9Gca23475TWH6XUVefdff7I5d3uvSYNmnTZ9jerPN208lhs+pvH1I/3hRXvTJzJUD37D+cLyM/d3lwnk9pFRmU8o44TmVv893yrhg3qB0VHIyn0t597GUN81uzI9vy4d6DintSgelJO725XykD6WxPpb5xrP1mLbNXX7B3dQ2L0vrpRz12DV9fuX8YF9Oe5aDlxcdPu32n0nlwDetK2cvszZX6KZfr8tiXi+98W5eWa/nD/HkZb69eV4q7HxzVs5/ntfyss/HenSk9fO82v0yPztry4uV7fOz88Gb5+eXvJmf6Juf84HLy3180Sdy2hMgPJfTAvjvWh3HYzaWD4v+l/gWIYD/rm7zbvP63bt5OPG/xLcIAYTng/sA4ZlgAQjPaU+A8KRygPB82hMgPKkcIDyf9gQIzzAiQHgaLADhabAAhOdbhADC02ABCM9cOUB4UjlAeE57AoTncloA4fkWIYDwfIsQQHg+uA8QngkWgPCc9gQITyoHCM+nPQHCk8oBwvNpT4DwDCMChKfBAhCeBgtAeL5FCCA8DRaA8MyVA4QnlQOE57QnQHgupwUQnm8RAgjPtwgBhOeD+wDhmWABCM9pT4DwpHKA8HzaEyA8qRwgPJ/2BAjPMCJAeBosAOFpsACE51uEAMLTYAEIz1w5QHhSOUB4TnsChOdyWgDh+RYhgPB8ixBAeD64DxCeCRaA8Jz2BAhPKgcIz6c9AcKTygHC82lPgPAMIwKEp8ECEJ4GC0B4vkUIIDwNFoDwzJUDhCeVA4TntCdAeC6nBRCebxECCM+3CAGE54P7AOGZYAEIz2lPgPCkcoDwfNoTIDypHCA8n/YECM8wIkB4GiwA4WmwAITnW4QAwtNgAQjPXDlAeFI5QHhOewKE53JaAOH5FiGA8HyLEEB4PrgPEJ4JFoDwnPYECE8qBwjPpz0BwpPKAcLzaU+A8AwjAoSnwQIQngYLQHi+RQggPA0WgFDWQ1cW++GmaU7pOLT5jgYLQCjrlEr13qe+eZt2p/ux98F9gGDWaSif7Tyl5mbaNU3/8sr1ygGC+WXcp1NJ5c1v6UW+/zo1rlcOEMs/UnM19KWUt3On5Wp02hMgmF/STZO251JeToC+KqVcKgeI5G3qmy51n1P5y6a5lsoBIimjK80hfSrl745SOUAw63STb++Gl02/PeQqPm70ygGCmVN5mS7vm006bIYh35XKAUJZl495Ns1pyhX8NBynUtj1ygHCk8oBwpPKAcKTygHCM8ECEJ6L3AKE51uEAMKTygHC63z1BEB0TnsChKfBAhCeBgtAeBosAOFpsACEJ5UDhOcaLADhdVI5QHRSOUB4rlcOEJ5UDhBeZxgRILrWRW4BojPBAhCeXjlAeCZYAMKTygHCk8oBwpPKAcIzVw4QnrlygPDMlQOEp1cOEJ4JFoDwpHKA8KRygPCkcoDwzJUDhGeuHCA8c+UA4emVA4RnggUgPKkcIDypHCA8qRwgPHPlAOGZKwcIz1w5QHh65QDhmWABCE8qBwhPKgcITyoHCM9cOUB45soBwjNXDhCeXjlAeCZYAMKTygHCk8oBwpPKAcIzVw4QnrlygPDMlQOEp1cOEJ4JFoDwpHKA8KRygPCkcoDwzJUDhGeuHCA8c+UA4emVA4RnggUgPKkcIDypHCA8qRwgPHPlAOGZKwcIz1w5QHh65QDhmWABCE8qBwhPKgcITyoHCM9cOUB45soBwjNXDhCeXjlAeCZYAMKTygHCk8oBwpPKAcIzVw4QnrlygPDMlQOEp1cOEJ4JFoDwpHKA8KRygPCkcoDwzJUDhGeuHCA8c+UA4emVA4RnggUgPKkcIDypHCA8qRz4pq33+/Vl9WzdXVaeYt9eVv5Uv/7D7fp9f1nL60862L9lrhz4hrXbMaV0eFy9xy8Z0R43l5U/tU3p928Xn7Xp82vv/nqXxFw58O1qp5/avm/H4XK/GL6koN5cln8unS4r/8ajI0yHy8qXM1dORX338/Nu7ZdfdX61TfOQ5vbGD9M/mg+l27zKN0NZ2Q3Tqem3pbaeHhXY/TB1p1w1b0sY3+Wbw9tmd7oepn15djVsb3Zlt+f5h3ubc3h/GKZ10w1pmNq87/22vNpqmKaSxE9TedN4sW2bNr/aJu9xHKf9ddmmm/LNYRryc0+kV05F7d0Kqnne9OljmL1p7qa8OOR4Xkr5Ib3f5ii9TuvmbXp93iRbp+37abrP25TyPt3lvL1ppmnabVOu5au0290dH/JRS2HPu+fi/H5K636XtrtuO77fjblE7/JW98d18yw/mLalwZKPujvkA63GYbdelzeXdWqb2+P73cvhqX17EyxUtH51WYEqXjxqVM8J/LDNZfpVsytlfZPr+G3q7w+fWiBdyts8P+YKPpXKWfYY3zXbYw7h07Y55Wrc/Jp+PZfym/TsfMjd8U0z7pt2+Dmn9PS8md89tvsuvW+afwzNm9Ru8os2uzE/mp/al1L+PPUvytH6nOmfRiqnos6PH1X1j85GbktBvc1lenjIdXWX5Vx9s70r5fhinUpVf8h1/q7U4/LUcXNez+8Bu7nhnve+Oafyfc7r+SiH/HZx7pXfPJT1VTrs8qs+S+WhXIPnd5PnuykftbxBzKn853xzyOn9qZlcKqeqtVJOVT98TOXr7nep/HC8u5vuylzLJv1y3qKYy+wc2e9L5ZxT+etPCX11LuWryxtEKeVjPsr20Dc5oTf98NM0ldfbTClN/f5RKd+kYRouWX9f3i6ep9LHn44p7/s0UjkVSeVUdiidlOynq0spP6fyOaHn6tu0w2H6fOqxKxV2LuVT+dEtqfy7Syrf3jabj6X85lzKT+cTqPkozfHUvBg2OavnZ/Ldbp1O57eF/Arp+jTsc1jPe5cjrUuJX6c3Zbv1fs73T2GunIqeK+XU1aW5aG9Lo3q6aa5KMzyn8lPKP5qboWum4fpYSvzZzXboc4TOu5R2yC49zL3ycyrPD455y3L6ss9791N626zKqc/VNKfyNlfldsjvBWWrPr1ux+1N8yHlx9vSJj+Vo5asv8/VvhvTTZ9+LX+9p5Zyc+VUJJVTWze+HIZhzBXzejwOhzLGMuaCekrDOPe1++Y6vbts2zRvhp+GbUnlXRrvd0Ouvrly35d3gynf7NOQHyxvAmkYShnP+w9pzEm+HCKvD0Pe/FlepumHm/ancRhXpcHSD+Wpl2W4ZTjdHPKdh1zyy/ZPb7CYK6civXLq2zyszp/YbFerZv0sl/Hn+c6z1arLibqcrtx8Pz89K9u8L02Zrmyc3wA2XXN6m+/vS3xef7hqhhymm79/ODWb67xyWq1KMf61tORPD39vuvxS+1WZXs+H+LC6yQH9Vd+8uVq9KEfqN+/zhler5zf5wbLv+S/2FHrlVCSVE9DD/WXl3xoeLitflwkWKlLKieDVdnvYlj/nbkf5GNEfG+ucf5TKqUgpJ4KrXMeLu/Msy/5Pf2zf/+2y8nVJ5VSkVw7LkMqpSCqHZZgrpyKpHJZhrpyKpHJYhrlyKlLKYRl65VSklMMyTLBQkV45LEMqpyKpHJYhlVORVA7LkMqpSCqHZZgrpyKlHJZhrpyKlHJYhrlyKtIrh2XolVORVA7LMMFCRVI5LEMqpyKpHJYhlVORUg7LkMqpSCmHZZgrpyK9cliGuXIqksphGebKqUgqh2XolVORVA7LMMFCRUo5LEMqpyKlHJYhlVORXjksQyqnIqkclmGunIqkcliGuXIqksphGebKqUgph2XolVORUg7LMMFCRXrlsAypnIqkcliGVE5FUjksQyqnIqkclmGunIqUcliGuXIqUsphGebKqUivHJahV05FUjkswwQLFUnlsAypnIqkcliGVE5FSjksQyqnIqUclmGunIr0ymEZ5sqpSCqHZZgrpyKpHJahV05FUjkswwQLFSnlsAypnIqUcliGVE5FeuWwDKmciqRyWIa5ciqSymEZ5sqpSCqHZZgrpyKlHJahV05FSjkswwQLFemVwzKkciqSymEZUjkVSeWwDKmciqRyWIa5cipSymEZ5sqpSCmHZZgrpyK9cliGXjkVSeWwDBMsVCSVwzKkciqSymEZUjkVKeWwDKmcipRyWIa5cirSK4dlmCunIqkclmGunIqkcliGXjkVSeWwDBMsVKSUwzKkcipSymEZUjkV6ZXDMqRyKpLKYRnmyqlIKodlmCunIqkclmGunIqUcliGXjkVKeWwDBMsVKRXDsuQyqlIKodlSOVUJJXDMqRyKpLKYRnmyqlIKYdlmCunIqUclmGunIr0ymEZeuVUJJXDMkywUJFUDsuQyqlIKodlSOVUpJTDMqRyKlLKYRnmyqlIrxyWYa6ciqRyWIa5ciqSymEZeuVUJJXDMkywUJFSDsuQyqlIKYdlSOVUpFcOy5DKqUgqh2WYK6ciqRyWYa6ciqRyWIa5cipSymEZeuVUpJTDMkywUJFeOSxDKqeiksq7w3m1LNbb7aGf7wJfQiqnopLK92lbqvcmNc1Dut3eHdvzc8DTSeVUVH789int8+opNb/NK9vb+SngC7TT5vtXV6vNKv+2sPjKi91VLuXjJnW5lB+bdv4v4q/H+ScT+BLd+vfeWlh8tcVpTuX9dts0z9LlJ7LcASCMctpzn5o+XZVUPtup5AChnEv5TbMZ+7fnVP7+zgQLQCiXVN404/acyh9K2xyAQM6lPOfwdtiO+f5qKjMsAARynisva6s0NM1u7F60nblygEg+pfKmOXzXXKfZND8FQAyllPeXFJ4XbZsz+bVUDhBJKeUAhObKiADhSeUA4UnlAOFJ5QDhKeUA4SnlAOHplQOEJ5UDhCeVA4QnlQOEp5QDhKeUA4SnVw4QnlQOEN5zpRwgOqkcIDy9coDwpHKA8JRygPCUcoDw9MoBwpPKAcL7+fvLCgBRSeUA4emVA4QnlQOE5xosAOFJ5QDh6ZUDhCeVA4SnlAOEp5QDhKdXDhCeVA4QnmuwAIQnlQOEp1cOEJ5UDhCea7AAhCeVA4SnVw4QnlQOEJ5SDhCeUg4Qnl45QHhSOUB4rsECEJ5UDhCeXjlAeFI5QHiuwQIQnlQOEJ5eOUB4UjlAeEo5QHhKOUB4euUA4UnlAOG5BgtAeFI5QHh65QDhSeUA4bkGC0B4UjlAeHrlAOFJ5QDhKeUA4SnlAOHplQOEJ5UDhOcaLADhSeUA4emVA4QnlQOE5xosAOFJ5QDh6ZUDhCeVA4SnlAOEp5QDhKdXDhCeVA4QnmuwAIQnlQOEp1cOEJ5UDhCea7AAhCeVA4SnVw4QnlQOEJ5SDhCeUg4Qnl45QHhSOUB4rsECEJ5UDhCeXjlAeFI5QHiuwQIQnlQOEJ5eOUB4UjlAeEo5QHhKOUB4euVU1x+220N/uTPb7S8rf2L3+uayltc3l5Uvsbl62gtBAFI5te3Tdru9S4+r8bi7rPyJ9+8uK9nDXynl2+FpLwQBrP/KvwFYzjrN5XSX+qZt80q5GUrC6NuuaW668liT1y7y0+Xx/EzZ4rI+R/rreffy2LySF+d9L9q+udzPBy47HLaPX+jxBtfnByCO62mzOv+6elVu/PHna/5ZNzfb8fyjuFk321xcm910rrDtmNL2prkrTx/yysVhu09pyqV42j1aP5T3gpTWTfO3YzemIZfi7pgfeNQ/2R5O8wGb/ZTSkGv2714oH2RYbVK6zVs+5B3LUSGQ7u36o3mt3Pjjz1f60zZ9enb5UczVtpTy27u5wnbDtvslHfqb8UOzStfnDbLdcere5seb+928vi5lOJf1h+F0vU3Pm2dp3HfDy6ZNh+vukD7H69t01+3ToXmdVtfdy1zGD79/oWabtt0pbfKrna7XKW8AwNP0ufx+tM3h+mNYnsv6Op2ad2k9fK72za4E6i4/fpfL93hZn9636UV+chqafYnm65SPW3on784dk+Iw5KC9TvvulO/8mPKRcim/f/RCU6ne97fN6pjfONqyFQBP8qaU3ottaW/MYflV6Zccj2OJ7KvfnREtTzdNqbylwVLWx00zPbzIm6cxZ+l9LtK5MvfNKR3Hq0dtkrvyPtGUlst+dUzDp1T+6YVyWZ/bNv02HYfPfykA/pObj/3s3el3vfLDtN//+Ld1rsWr9Pq8xexcvo+vSyovm+b1TV7v0+nZ/vS2+1zKm/Wzl2n83GCZI3+TS/YuTc8+jP/6QsNDfj4fNdf63Xg+FwvAk2zS3AS5Tm/nattPuVaXBstcpvdtTteb9EtZP9uVPkk3rpvh/ef10mB5m59s93nzvNynm750SPrHkX+6yeV9bDfHfGeXS/kl/t/mgD6/0MdUvi77rMpWADzRlNZd15XzjLu0b7fHXM9zKW/H4Xo9TW0z7vpztT3Lmbpbp7xNLrqrNP22Trn05/VdOrW34ylX8RLIcylPd9ft7lEpv80P7HPYPqXX+fGXl1T+0Pz28YXuSxDPqXyVj9SNc/gH4Gn61ZhSWuUKnMttej1PsLzKMT0/movtPIz4qN1xuP37/PhcvudhxPN66XmXwv3snMr75nkZRnzU8t7uyjBiXrnKi6v7tx975fMwYjlIWf90JMOIAF+m7c4f6ilrTZ+LaFsKad+WEcTuzfnhj3KWnh9vXvS/Wy8f7ClDLH050nzzTx8R2t5eNp4/CJRfsLzQm7LjD+fH5/UX5Rg+IgTw39BfXCZYzso44X/Q38y73fTnc6oAVHNIKf2Uf6X+PLVydnjUQ/8D28t+SSkHqKzb7/e/5D/7pnvU+7j+z32Q52Wn/S//+P2OAAAAAAAAAAAAAAAAAAAAAAAA8A1qmv8HWnyuHM9cV7AAAAAASUVORK5CYII="
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    "SpeciesTree_Gene_Duplications_0.5_Support.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Gene Duplication Events Species Tree:\n",
    "A summation of identified orthogroup node gene duplication events with at least 50% support over the branches of the species tree.\n",
    "![SpeciesTree_Gene_Duplications_0.5_Support.png](attachment:SpeciesTree_Gene_Duplications_0.5_Support.png)\n",
    "***\n",
    "#### Species Tree:\n",
    "A STAG (Species Tree inference from All Genes) species tree conclded from all orthogroups.\n",
    "![SpeciesTree.png](attachment:SpeciesTree.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>Orthogroup</th>\n",
       "      <th>Clemson_tarsalis</th>\n",
       "      <th>Culex_quinquefasciatus</th>\n",
       "      <th>Davis_tarsalis</th>\n",
       "      <th>Culex_pipiens</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OG0000000</td>\n",
       "      <td>Clemson_tarsalis_Ct.00g000390.m01, Clemson_tar...</td>\n",
       "      <td>Culex_quinquefasciatus_CPIJ003782-PA, Culex_qu...</td>\n",
       "      <td>Davis_tarsalis_mRNA6969, Davis_tarsalis_mRNA8820</td>\n",
       "      <td>Culex_pipiens_00000508-RA, Culex_pipiens_00014...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OG0000001</td>\n",
       "      <td>Clemson_tarsalis_Ct.00g000420.m01, Clemson_tar...</td>\n",
       "      <td>Culex_quinquefasciatus_CPIJ005359-PA, Culex_qu...</td>\n",
       "      <td>Davis_tarsalis_mRNA14890</td>\n",
       "      <td>Culex_pipiens_00001767-RA, Culex_pipiens_00002...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OG0000002</td>\n",
       "      <td>Clemson_tarsalis_Ct.00g000220.m01, Clemson_tar...</td>\n",
       "      <td>Culex_quinquefasciatus_CPIJ014099-PA</td>\n",
       "      <td>Davis_tarsalis_mRNA8910, Davis_tarsalis_mRNA9390</td>\n",
       "      <td>Culex_pipiens_00004994-RA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OG0000003</td>\n",
       "      <td>Clemson_tarsalis_Ct.00g000010.m01, Clemson_tar...</td>\n",
       "      <td>Culex_quinquefasciatus_CPIJ010419-PA, Culex_qu...</td>\n",
       "      <td></td>\n",
       "      <td>Culex_pipiens_00007914-RA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OG0000004</td>\n",
       "      <td>Clemson_tarsalis_Ct.00g003100.m01, Clemson_tar...</td>\n",
       "      <td>Culex_quinquefasciatus_CPIJ001417-PA, Culex_qu...</td>\n",
       "      <td></td>\n",
       "      <td>Culex_pipiens_00002767-RA, Culex_pipiens_00006...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Orthogroup                                   Clemson_tarsalis  \\\n",
       "0  OG0000000  Clemson_tarsalis_Ct.00g000390.m01, Clemson_tar...   \n",
       "1  OG0000001  Clemson_tarsalis_Ct.00g000420.m01, Clemson_tar...   \n",
       "2  OG0000002  Clemson_tarsalis_Ct.00g000220.m01, Clemson_tar...   \n",
       "3  OG0000003  Clemson_tarsalis_Ct.00g000010.m01, Clemson_tar...   \n",
       "4  OG0000004  Clemson_tarsalis_Ct.00g003100.m01, Clemson_tar...   \n",
       "\n",
       "                              Culex_quinquefasciatus  \\\n",
       "0  Culex_quinquefasciatus_CPIJ003782-PA, Culex_qu...   \n",
       "1  Culex_quinquefasciatus_CPIJ005359-PA, Culex_qu...   \n",
       "2               Culex_quinquefasciatus_CPIJ014099-PA   \n",
       "3  Culex_quinquefasciatus_CPIJ010419-PA, Culex_qu...   \n",
       "4  Culex_quinquefasciatus_CPIJ001417-PA, Culex_qu...   \n",
       "\n",
       "                                     Davis_tarsalis  \\\n",
       "0  Davis_tarsalis_mRNA6969, Davis_tarsalis_mRNA8820   \n",
       "1                          Davis_tarsalis_mRNA14890   \n",
       "2  Davis_tarsalis_mRNA8910, Davis_tarsalis_mRNA9390   \n",
       "3                                                     \n",
       "4                                                     \n",
       "\n",
       "                                       Culex_pipiens  \n",
       "0  Culex_pipiens_00000508-RA, Culex_pipiens_00014...  \n",
       "1  Culex_pipiens_00001767-RA, Culex_pipiens_00002...  \n",
       "2                          Culex_pipiens_00004994-RA  \n",
       "3                          Culex_pipiens_00007914-RA  \n",
       "4  Culex_pipiens_00002767-RA, Culex_pipiens_00006...  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Orthogroups = pd.read_csv(\"Orthogroups.tsv\",sep='\\t')\n",
    "Orthogroups = Orthogroups.fillna('')\n",
    "Orthogroups.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "### <span style=\"color:lightseagreen\">Getting Protein Function Predictive Information With InterProScan</span>\n",
    "In order to match protein accessions with functional descriptions, InterProScan [[3]](https://doi.org/10.1093/nar/gki442) was used to collect protein functional and predictive information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%script bash --bg\n",
    "module load interproscan\n",
    "\n",
    "interproscan.sh -cpu 16 -goterms -i Quinquefasciatus.proteins.fasta -dp -b ./Culex_quinquefasciatus__GOInterProOutput\n",
    "interproscan.sh -cpu 16 -goterms -i Pipiens.proteins.fasta -dp -b ./Culex_pipiens_pallens__GOInterProOutput\n",
    "interproscan.sh -cpu 16 -goterms -i Davis_tarsalis.proteins.fasta -dp -b ./Davis-Culex_tarsalis__GOInterProOutput\n",
    "interproscan.sh -cpu 16 -goterms -i Clemson_tarsalis.proteins.fasta -dp -b ./Clemson-Culex_tarsalis__GOInterProOutput\n",
    "\n",
    "cat *__GOInterProOutput.tsv > AllGOInterProOutput.tsv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Protein accession</th>\n",
       "      <th>Sequence MD5 digest</th>\n",
       "      <th>Sequence length</th>\n",
       "      <th>Analysis</th>\n",
       "      <th>Signature accession</th>\n",
       "      <th>Signature description</th>\n",
       "      <th>Start location</th>\n",
       "      <th>Stop location</th>\n",
       "      <th>Score</th>\n",
       "      <th>Status</th>\n",
       "      <th>Date</th>\n",
       "      <th>InterPro annotations - accession</th>\n",
       "      <th>InterPro annotations - description</th>\n",
       "      <th>GO_Term</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Clemson_tarsalis_Ct.00g268710.m01.polypeptide</td>\n",
       "      <td>a2898e6bb199d565e512004fa664eab7</td>\n",
       "      <td>1463</td>\n",
       "      <td>CDD</td>\n",
       "      <td>cd01479</td>\n",
       "      <td>Sec24-like</td>\n",
       "      <td>690</td>\n",
       "      <td>938</td>\n",
       "      <td>3.45499E-116</td>\n",
       "      <td>T</td>\n",
       "      <td>14-06-2022</td>\n",
       "      <td>IPR041742</td>\n",
       "      <td>Sec24-like, trunk domain</td>\n",
       "      <td>GO:0006886|GO:0006888|GO:0030127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Clemson_tarsalis_Ct.00g380650.m01.polypeptide</td>\n",
       "      <td>0a4dfc668b760d2e62d7f5c53f875d31</td>\n",
       "      <td>116</td>\n",
       "      <td>MobiDBLite</td>\n",
       "      <td>mobidb-lite</td>\n",
       "      <td>consensus disorder prediction</td>\n",
       "      <td>101</td>\n",
       "      <td>116</td>\n",
       "      <td>-</td>\n",
       "      <td>T</td>\n",
       "      <td>14-06-2022</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Clemson_tarsalis_Ct.00g380650.m01.polypeptide</td>\n",
       "      <td>0a4dfc668b760d2e62d7f5c53f875d31</td>\n",
       "      <td>116</td>\n",
       "      <td>MobiDBLite</td>\n",
       "      <td>mobidb-lite</td>\n",
       "      <td>consensus disorder prediction</td>\n",
       "      <td>90</td>\n",
       "      <td>116</td>\n",
       "      <td>-</td>\n",
       "      <td>T</td>\n",
       "      <td>14-06-2022</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Clemson_tarsalis_Ct.00g389150.m01.polypeptide</td>\n",
       "      <td>a9e36bff72224f086de97d827976074d</td>\n",
       "      <td>1038</td>\n",
       "      <td>MobiDBLite</td>\n",
       "      <td>mobidb-lite</td>\n",
       "      <td>consensus disorder prediction</td>\n",
       "      <td>970</td>\n",
       "      <td>1000</td>\n",
       "      <td>-</td>\n",
       "      <td>T</td>\n",
       "      <td>14-06-2022</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Clemson_tarsalis_Ct.00g389150.m01.polypeptide</td>\n",
       "      <td>a9e36bff72224f086de97d827976074d</td>\n",
       "      <td>1038</td>\n",
       "      <td>MobiDBLite</td>\n",
       "      <td>mobidb-lite</td>\n",
       "      <td>consensus disorder prediction</td>\n",
       "      <td>859</td>\n",
       "      <td>874</td>\n",
       "      <td>-</td>\n",
       "      <td>T</td>\n",
       "      <td>14-06-2022</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               Protein accession  \\\n",
       "0  Clemson_tarsalis_Ct.00g268710.m01.polypeptide   \n",
       "1  Clemson_tarsalis_Ct.00g380650.m01.polypeptide   \n",
       "2  Clemson_tarsalis_Ct.00g380650.m01.polypeptide   \n",
       "3  Clemson_tarsalis_Ct.00g389150.m01.polypeptide   \n",
       "4  Clemson_tarsalis_Ct.00g389150.m01.polypeptide   \n",
       "\n",
       "                Sequence MD5 digest  Sequence length    Analysis  \\\n",
       "0  a2898e6bb199d565e512004fa664eab7             1463         CDD   \n",
       "1  0a4dfc668b760d2e62d7f5c53f875d31              116  MobiDBLite   \n",
       "2  0a4dfc668b760d2e62d7f5c53f875d31              116  MobiDBLite   \n",
       "3  a9e36bff72224f086de97d827976074d             1038  MobiDBLite   \n",
       "4  a9e36bff72224f086de97d827976074d             1038  MobiDBLite   \n",
       "\n",
       "  Signature accession          Signature description  Start location  \\\n",
       "0             cd01479                     Sec24-like             690   \n",
       "1         mobidb-lite  consensus disorder prediction             101   \n",
       "2         mobidb-lite  consensus disorder prediction              90   \n",
       "3         mobidb-lite  consensus disorder prediction             970   \n",
       "4         mobidb-lite  consensus disorder prediction             859   \n",
       "\n",
       "   Stop location         Score Status        Date  \\\n",
       "0            938  3.45499E-116      T  14-06-2022   \n",
       "1            116             -      T  14-06-2022   \n",
       "2            116             -      T  14-06-2022   \n",
       "3           1000             -      T  14-06-2022   \n",
       "4            874             -      T  14-06-2022   \n",
       "\n",
       "  InterPro annotations - accession InterPro annotations - description  \\\n",
       "0                        IPR041742           Sec24-like, trunk domain   \n",
       "1                                -                                  -   \n",
       "2                                -                                  -   \n",
       "3                                -                                  -   \n",
       "4                                -                                  -   \n",
       "\n",
       "                            GO_Term  \n",
       "0  GO:0006886|GO:0006888|GO:0030127  \n",
       "1                                    \n",
       "2                                    \n",
       "3                                    \n",
       "4                                    "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AllGOInterProOutput = pd.read_csv(\"AllGOInterProOutput.tsv\",sep='\\t')\n",
    "AllGOInterProOutput = AllGOInterProOutput.fillna('')\n",
    "AllGOInterProOutput.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "### <span style=\"color:lightseagreen\">Assigning Orthogroups IDs To Functional Descriptions With SQLite</span>\n",
    "In order to link orthogroups to functional descriptions, SQLite was used to combine Genmap orthogroup and protein accession information with InterProScan protein accession and functional description information, due to file sizes. SQLiteStudio V3.3.3 was used.\n",
    "\n",
    "To begin, GenMap's Orthogroups.tsv output file, table 'Orthogroups', was compared against each individual mosquito species' adjusted InterProScan's output tsv file, table 'Mosquito'. Using SQLite, orthogroups were combined with protein accessions and descriptions for each mosquito species, and a new table was created for each Culex species, labled 'OGMosquito'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%script sqlite3 --bg\n",
    "SELECT Orthogroups.Orthogroup, Mosquito.\"Protein accession\", Mosquito.Score, \n",
    "Mosquito.\"Signature description\", Mosquito.\"InterPro annotations - description”\n",
    "FROM Orthogroups, Mosquito\n",
    "WHERE Orthogroups.Mosquito LIKE Mosquito.\"Protein accession\"\n",
    "# export as OGMosquito.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, the 'OGMosquito' table created previously was analyzed, and was removed of duplicates. A new table was created for each mosquito species, 'OutOGMosquito'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%script sqlite3 --bg\n",
    "DELETE FROM OGMosquito\n",
    "WHERE EXISTS (\n",
    "SELECT 1 FROM OGMosquito p2\n",
    "WHERE OGMosquito.Column1 = p2.Column1\n",
    "AND OGMosquito.Column2 = p2.Column2\n",
    "AND OGMosquito.Column4 = p2.Column4\n",
    "AND OGMosquito.rowid > p2.rowid\n",
    ");  \n",
    "SELECT * FROM OGMosquito\n",
    "# export as OutOGMosquito.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, each of the 4 Culex species tables were combined into 1, table 'OutOGAll.txt'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%script bash --bg\n",
    "cat OutOGMosquito1.txt OutOGMosquito2.txt OutOGMosquito3.txt OutOGMosquito4.txt >> OutOGAll.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>Orthogroup</th>\n",
       "      <th>ProteinAccession</th>\n",
       "      <th>Score</th>\n",
       "      <th>SignatureDescription</th>\n",
       "      <th>InterProAnnotationsDescription</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>171359</th>\n",
       "      <td>OG0016681</td>\n",
       "      <td>Culex_quinquefasciatus_CPIJ020271-PA</td>\n",
       "      <td>1.1e-30</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171360</th>\n",
       "      <td>OG0016681</td>\n",
       "      <td>Culex_quinquefasciatus_CPIJ020271-PA</td>\n",
       "      <td>5e-27</td>\n",
       "      <td>Ligated ion channel L-glutamate- and glycine-b...</td>\n",
       "      <td>Ionotropic glutamate receptor, L-glutamate and...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171361</th>\n",
       "      <td>OG0016681</td>\n",
       "      <td>Culex_quinquefasciatus_CPIJ020271-PA</td>\n",
       "      <td>4.5e-26</td>\n",
       "      <td>GLUTAMATE RECEPTOR 1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171362</th>\n",
       "      <td>OG0016681</td>\n",
       "      <td>Culex_quinquefasciatus_CPIJ020271-PA</td>\n",
       "      <td>4.5e-26</td>\n",
       "      <td>IONOTROPIC GLUTAMATE RECEPTOR</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171363</th>\n",
       "      <td>OG0016681</td>\n",
       "      <td>Culex_quinquefasciatus_CPIJ020271-PA</td>\n",
       "      <td>4.13e-19</td>\n",
       "      <td>Periplasmic binding protein-like II</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Orthogroup                      ProteinAccession     Score  \\\n",
       "171359  OG0016681  Culex_quinquefasciatus_CPIJ020271-PA   1.1e-30   \n",
       "171360  OG0016681  Culex_quinquefasciatus_CPIJ020271-PA     5e-27   \n",
       "171361  OG0016681  Culex_quinquefasciatus_CPIJ020271-PA   4.5e-26   \n",
       "171362  OG0016681  Culex_quinquefasciatus_CPIJ020271-PA   4.5e-26   \n",
       "171363  OG0016681  Culex_quinquefasciatus_CPIJ020271-PA  4.13e-19   \n",
       "\n",
       "                                     SignatureDescription  \\\n",
       "171359                                                      \n",
       "171360  Ligated ion channel L-glutamate- and glycine-b...   \n",
       "171361                               GLUTAMATE RECEPTOR 1   \n",
       "171362                      IONOTROPIC GLUTAMATE RECEPTOR   \n",
       "171363                Periplasmic binding protein-like II   \n",
       "\n",
       "                           InterProAnnotationsDescription  \n",
       "171359                                                     \n",
       "171360  Ionotropic glutamate receptor, L-glutamate and...  \n",
       "171361                                                     \n",
       "171362                                                     \n",
       "171363                                                     "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "OutOGAll = pd.read_csv(\"OutOGAll.txt\",sep='\\t')\n",
    "OutOGAll = OutOGAll.fillna('')\n",
    "OutOGAll.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "### <span style=\"color:lightseagreen\">Using Natural Language Processing (UniFunc) To Simplify Functional Descriptions</span>\n",
    "In order to link orthogroups to functional descriptions, Python's Pandas was used to get the dataframe ready for natural language processing programs.\n",
    "\n",
    "To prepare for the first UniFunc run, GeneIDs were the actual protein accessions, numbered, and the Groups were the non-adjusted protein accessions due to UniFunc accepting only input tsv files containing the columns such as Gene ID, Group, and Description."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>GeneID</th>\n",
       "      <th>Group</th>\n",
       "      <th>Descriptions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Davis_tarsalis_mRNA14890_0</td>\n",
       "      <td>Davis_tarsalis_mRNA14890</td>\n",
       "      <td>consensus disorder prediction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Culex_pipiens_00004994-RA_1</td>\n",
       "      <td>Culex_pipiens_00004994-RA</td>\n",
       "      <td>Tetrahydrofolate dehydrogenase/cyclohydrolase ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Culex_pipiens_00004994-RA_2</td>\n",
       "      <td>Culex_pipiens_00004994-RA</td>\n",
       "      <td>FTHFS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Culex_pipiens_00004994-RA_3</td>\n",
       "      <td>Culex_pipiens_00004994-RA</td>\n",
       "      <td>Formate--tetrahydrofolate ligase signature 1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Culex_pipiens_00004994-RA_4</td>\n",
       "      <td>Culex_pipiens_00004994-RA</td>\n",
       "      <td>NAD_bind_m-THF_DH_Cyclohyd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334087</th>\n",
       "      <td>Davis_tarsalis_mRNA14403_334087</td>\n",
       "      <td>Davis_tarsalis_mRNA14403</td>\n",
       "      <td>Zinc finger</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334088</th>\n",
       "      <td>Davis_tarsalis_mRNA14403_334088</td>\n",
       "      <td>Davis_tarsalis_mRNA14403</td>\n",
       "      <td>CCCH-type</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334089</th>\n",
       "      <td>Culex_pipiens_00017909-RA_334089</td>\n",
       "      <td>Culex_pipiens_00017909-RA</td>\n",
       "      <td>Cadherin_repeat</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334090</th>\n",
       "      <td>Culex_pipiens_00017909-RA_334090</td>\n",
       "      <td>Culex_pipiens_00017909-RA</td>\n",
       "      <td>Cadherins domain profile</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334091</th>\n",
       "      <td>Culex_pipiens_00017909-RA_334091</td>\n",
       "      <td>Culex_pipiens_00017909-RA</td>\n",
       "      <td>Cadherin-like</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>334092 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  GeneID                      Group  \\\n",
       "0             Davis_tarsalis_mRNA14890_0   Davis_tarsalis_mRNA14890   \n",
       "1            Culex_pipiens_00004994-RA_1  Culex_pipiens_00004994-RA   \n",
       "2            Culex_pipiens_00004994-RA_2  Culex_pipiens_00004994-RA   \n",
       "3            Culex_pipiens_00004994-RA_3  Culex_pipiens_00004994-RA   \n",
       "4            Culex_pipiens_00004994-RA_4  Culex_pipiens_00004994-RA   \n",
       "...                                  ...                        ...   \n",
       "334087   Davis_tarsalis_mRNA14403_334087   Davis_tarsalis_mRNA14403   \n",
       "334088   Davis_tarsalis_mRNA14403_334088   Davis_tarsalis_mRNA14403   \n",
       "334089  Culex_pipiens_00017909-RA_334089  Culex_pipiens_00017909-RA   \n",
       "334090  Culex_pipiens_00017909-RA_334090  Culex_pipiens_00017909-RA   \n",
       "334091  Culex_pipiens_00017909-RA_334091  Culex_pipiens_00017909-RA   \n",
       "\n",
       "                                             Descriptions  \n",
       "0                           consensus disorder prediction  \n",
       "1       Tetrahydrofolate dehydrogenase/cyclohydrolase ...  \n",
       "2                                                   FTHFS  \n",
       "3            Formate--tetrahydrofolate ligase signature 1  \n",
       "4                              NAD_bind_m-THF_DH_Cyclohyd  \n",
       "...                                                   ...  \n",
       "334087                                        Zinc finger  \n",
       "334088                                          CCCH-type  \n",
       "334089                                    Cadherin_repeat  \n",
       "334090                           Cadherins domain profile  \n",
       "334091                                      Cadherin-like  \n",
       "\n",
       "[334092 rows x 3 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nOutOGAll = OutOGAll.groupby(['Orthogroup','ProteinAccession']).agg({'SignatureDescription': ', '.join, 'InterProAnnotationsDescription': ', '.join})\n",
    "nOutOGAll = nOutOGAll.reset_index(drop=False)\n",
    "nOutOGAll['Descriptions'] = nOutOGAll[['SignatureDescription', 'InterProAnnotationsDescription']].apply(lambda x: ', '.join(x), axis = 1)\n",
    "nOutOGAll.drop(['SignatureDescription', 'InterProAnnotationsDescription'], axis=1, inplace=True)\n",
    "\n",
    "nOutOGAll['Descriptions']= nOutOGAll['Descriptions'].astype(str)\n",
    "nOutOGAll['Descriptions']= nOutOGAll['Descriptions'].str.replace(', ,', ',')\n",
    "nOutOGAll['Descriptions']= nOutOGAll['Descriptions'].str.strip(' ')\n",
    "nOutOGAll['Descriptions']= nOutOGAll['Descriptions'].str.strip(\"'\")\n",
    "nOutOGAll['Descriptions']= nOutOGAll['Descriptions'].str.rstrip(\",\")\n",
    "nOutOGAll['Descriptions']= nOutOGAll['Descriptions'].str.lstrip(\",\")\n",
    "nOutOGAll['Descriptions']= nOutOGAll['Descriptions'].str.replace(\".\",\"\")\n",
    "\n",
    "df_explode = nOutOGAll.assign(Descriptions=nOutOGAll.Descriptions.str.split(\",\")).explode('Descriptions').reset_index(level=0, drop=True)\n",
    "df_explode['Descriptions'] = df_explode['Descriptions'].str.strip()\n",
    "\n",
    "# how many lines of the file you want for testing: \n",
    "    # ex = df_explode.iloc[:1011] for first 1010 lines\n",
    "df = df_explode.iloc[:]\n",
    "\n",
    "df['GeneID'] = df['ProteinAccession'] + '_' + df['ProteinAccession'].index.astype(str)\n",
    "df2 = df[['GeneID', 'ProteinAccession', 'Descriptions']].copy()\n",
    "df2.rename(columns={\"ProteinAccession\": \"Group\", \"Description\": \"Annotations\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2.to_csv('For_UniFunc_Part1.tsv',index=False, sep='\\t')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "UniFunc [[4]](https://doi.org/10.1515/hsz-2021-01250) is a text mining tool/language proccessor that analyses similarities between pairs of protein function annotations. Because of the large amount of data still present after duplicates having been removed, UniFunc was ran 2 seperate times. UniFunc V.1.4.5 was used.\n",
    "\n",
    "The file created previously using Pandas was run by UniFunc with the cluster function as a bash script."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%script bash --bg\n",
    "unifunc cluster_function -i For_UniFunc_Part1.tsv -o OutputUniFunc_Part1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To prepare for the second UniFunc run, the OUTPUT_FUNC_CLUSTER results file in cluster_id, score, annotations format, table 'rep_func_cluster', was combined with the Orthogroups.tsv table from the InterProScan output to create a new input file for UniFunc. This time, the file is in the GeneID, Orthogroup, Description format using the the 'Group' from the previous input as the 'GeneID' and the orthogroup as the 'Group'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%script sqlite3 --bg\n",
    "SELECT rep_func_cluster.ProteinAccession, Orthogroups.Orthogroup, rep_func_cluster.Descriptions\n",
    "FROM rep_func_cluster, Orthogroups\n",
    "WHERE rep_func_cluster.ProteinAccession = Orthogroups.GeneID\n",
    "# export as OG_UniFunc_Part2.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>GeneID</th>\n",
       "      <th>Orthogroup</th>\n",
       "      <th>Descriptions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Davis_tarsalis_mRNA14890_0</td>\n",
       "      <td>OG0000001</td>\n",
       "      <td>consensus disorder prediction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Culex_pipiens_00004994-RA_1</td>\n",
       "      <td>OG0000002</td>\n",
       "      <td>Tetrahydrofolate dehydrogenase/cyclohydrolase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Culex_quinquefasciatus_CPIJ014099-PA_2</td>\n",
       "      <td>OG0000002</td>\n",
       "      <td>Tetrahydrofolate dehydrogenase/cyclohydrolase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Culex_pipiens_00010304-RA_3</td>\n",
       "      <td>OG0000007</td>\n",
       "      <td>consensus disorder prediction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Culex_pipiens_00010304-RA_4</td>\n",
       "      <td>OG0000007</td>\n",
       "      <td>Coil</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   GeneID Orthogroup  \\\n",
       "0              Davis_tarsalis_mRNA14890_0  OG0000001   \n",
       "1             Culex_pipiens_00004994-RA_1  OG0000002   \n",
       "2  Culex_quinquefasciatus_CPIJ014099-PA_2  OG0000002   \n",
       "3             Culex_pipiens_00010304-RA_3  OG0000007   \n",
       "4             Culex_pipiens_00010304-RA_4  OG0000007   \n",
       "\n",
       "                                    Descriptions  \n",
       "0                  consensus disorder prediction  \n",
       "1  Tetrahydrofolate dehydrogenase/cyclohydrolase  \n",
       "2  Tetrahydrofolate dehydrogenase/cyclohydrolase  \n",
       "3                  consensus disorder prediction  \n",
       "4                                           Coil  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "OG_rep_func_cluster = pd.read_csv(\"OG_UniFunc_Part2.csv\",sep='\\t', index_col=False, header=None, names=['GeneID', 'Orthogroup', 'Descriptions'])\n",
    "OG_rep_func_cluster['GeneID'] = OG_rep_func_cluster['GeneID'] + '_' + OG_rep_func_cluster['GeneID'].index.astype(str)\n",
    "OG_rep_func_cluster.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "OG_rep_func_cluster.to_csv('For_UniFunc_Part3.tsv',index=False, sep='\\t')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The file created previously using Pandas was run by UniFunc with the cluster function as a bash script."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%script bash --bg\n",
    "unifunc cluster_function -i For_UniFunc_Part3.tsv -o OutputUniFunc_Part3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To analyze the UniFunc results, the OUTPUT_FUNC_CLUSTER results file in cluster_id, score, annotations format, table 'OG_rep_func_cluster', was then combined with the AllAdj_GeneID_Orthogroup_Annotations.tsv table created earlier, table 'OG', to create a new input file for analysis using Pandas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%script sqlite3 --bg\n",
    "SELECT OG_rep_func_cluster.Orthogroup, OG.GeneID, OG_rep_func_cluster.Descriptions\n",
    "FROM OG_rep_func_cluster, OG\n",
    "WHERE OG_rep_func_cluster.Orthogroup = OG.Orthogroup\n",
    "# export as Final_UniFunc_Part4.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>Orthogroup</th>\n",
       "      <th>Descriptions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OG0000001</td>\n",
       "      <td>consensus disorder prediction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OG0000002</td>\n",
       "      <td>Tetrahydrofolate dehydrogenase/cyclohydrolase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OG0000007</td>\n",
       "      <td>consensus disorder prediction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OG0000012</td>\n",
       "      <td>consensus disorder prediction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OG0000014</td>\n",
       "      <td>consensus disorder prediction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11258</th>\n",
       "      <td>OG0016745</td>\n",
       "      <td>phbp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11259</th>\n",
       "      <td>OG0016746</td>\n",
       "      <td>consensus disorder prediction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11260</th>\n",
       "      <td>OG0016747</td>\n",
       "      <td>trypsin domain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11261</th>\n",
       "      <td>OG0016754</td>\n",
       "      <td>Zinc finger</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11262</th>\n",
       "      <td>OG0016755</td>\n",
       "      <td>Cadherins domain profile</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11263 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Orthogroup                                   Descriptions\n",
       "0      OG0000001                  consensus disorder prediction\n",
       "1      OG0000002  Tetrahydrofolate dehydrogenase/cyclohydrolase\n",
       "2      OG0000007                  consensus disorder prediction\n",
       "3      OG0000012                  consensus disorder prediction\n",
       "4      OG0000014                  consensus disorder prediction\n",
       "...          ...                                            ...\n",
       "11258  OG0016745                                           phbp\n",
       "11259  OG0016746                  consensus disorder prediction\n",
       "11260  OG0016747                                 trypsin domain\n",
       "11261  OG0016754                                    Zinc finger\n",
       "11262  OG0016755                       Cadherins domain profile\n",
       "\n",
       "[11263 rows x 2 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comb_rep_func_cluster = pd.read_csv(\"Final_UniFunc_Part4.csv\",sep='\\t', index_col=False)\n",
    "comb_rep_func_cluster2 = comb_rep_func_cluster.drop_duplicates(['Orthogroup','Descriptions'],keep= 'first')\n",
    "max_comb_rep_func_cluster = comb_rep_func_cluster2.assign(count=(comb_rep_func_cluster2[\"Descriptions\"].str.len())).groupby('Orthogroup').max()\\\n",
    "               .drop('count',axis=1)\n",
    "max_comb_rep_func_cluster.drop(['GeneID'], axis=1, inplace=True)\n",
    "max_comb_rep_func_cluster = max_comb_rep_func_cluster.reset_index(drop=False)\n",
    "max_comb_rep_func_cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "max_comb_rep_func_cluster.to_csv('OG+Descriptions.tsv',index=False, sep='\\t')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "### <span style=\"color:lightseagreen\">References</span>\n",
    "[1] Emms, D.M., Kelly, S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol 20, 238 (2019). https://doi.org/10.1186/s13059-019-1832-y\n",
    "<br>[2] Daniel H. Huson, Celine Scornavacca, Dendroscope 3: An Interactive Tool for Rooted Phylogenetic Trees and Networks, Systematic Biology, Volume 61, Issue 6, December 2012, Pages 1061–1067, https://doi.org/10.1093/sysbio/sys062\n",
    "<br>[3] Quevillon, E., Silventoinen, V., Pillai, S., Harte, N., Mulder, N., Apweiler, R., & Lopez, R. (2005). InterProScan: protein domains identifier. Nucleic acids research, 33(Web Server issue), W116–W120. https://doi.org/10.1093/nar/gki442\n",
    "<br>[4] Queirós, P., Novikova, P., Wilmes, P. & May, P. (2021). Unification of functional annotation descriptions using text mining. Biological Chemistry, 402(8), 983-990. https://doi.org/10.1515/hsz-2021-0125"
   ]
  }
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