step2_metagenome_profiling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>BDS^3</b> Ukrainian Biological Data Science School\n",
    "\n",
    "2024-06, Uzhzhorod \n",
    "\n",
    "<p>\n",
    "<div class=\"alert-info\" style=\"padding: 20px; border-radius: 10px\">\n",
    "<b> 🦠 Курс \"Аналіз мікробіому. Пошук ассоціацій з хворобами\"</b> \n",
    "\n",
    "<i> by Kateryna Pantiukh </i> \n",
    "https://github.com/Chartiza \n",
    "</div>\n",
    "\n",
    "**Практичний блок 2. Metagenome profiling**\n",
    "\n",
    "Приклади результатів найпоширеніших програм для профілювання метагеному. Аналіз продуктивності програм за допомогою штучних даних. Вивчення barplot, swarmplot, scatterplot. \n"
   ]
  },
  {
   "attachments": {
    "general_pipeline-01.png": {
     "image/png": 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12Pq17sqL+/kqmnzsRQ2v7OM4oJX64QoMioLdK/6cwXGqW9YPlr+7NuTnsLHrxdlv2JRB49+nGPdvy2/pnq/mg+Xvdn9NFfCRBUyg1aP3F8gCbH9bfkuwfbYAf9fXLz0+sPUSPQpgaW1dXFSUeOEax7XVZfsUrOdt/8WhbV6YQC969Ovxx6Yb1AwQFX7wxsUrHKf/eP2JlK3+HWbrfbN6h3g9AHADWlnGB0n77Emn7yp2ywWa3CopVXsvK7gHWp91b73muGS59zdaFhA/SqmlGPyMw0TQcZIfcKcbTf6uD3h3/uOGgr+ujt24qtnXF/MKDdnHTW1WaP5loLbdQvuZEvdCFS/MvzMuV/j9wnDNu9NSGLWFFywsuCDFP+C1XDZacmrrSGJtTh9NiXmPxhzKrMqm+PhROYPG7nu0nPLQrKUeYsa1F4XhGtZ7ciH9qyoeZK4ynR+vZ0+P6StwT3EEQ/eo1Y5aiMUd3FKH+aTmFan9+tiRKF/buwv/M2fXQA/2OitQxg8ehd8vXPt8VsrLmVjEY7FMd2yqew9fw7G1qEefEnoM3Fdbf0+P1p8+eKKmzyOoRR8X2fe23y2+qZcaYk0yQYcyk/Ie6avWq9h/k/SROJzJyOFPETfX0fsxK1DGT49Dd6GU74Imhnh2EPTSEOO/tem7W8vYS/x3fb/Tl2N9e7AUgrPd27PbgHITQrayasQ2NfpScqydjY2FOfuwGn0p+UADczYOUyUOc7l3J00FuDrQ66erqWx5uo/iDy7Kwtza72SWKbL4O+X3WiBejnasDLQXlorkWRlOZ7HqeuV/Z/jPKfJpOkb+Aa7Putck9hrLmfPK/85Md2xKT+5SynUWUC632BXSR38fvEyNfMNqQt+8izQ/aPLHDQX/Cekf3dq6O9oJluGPUiZoWeE47h/tW3k52rFv9qsDvVLzi3TvyU4lPC6/yx6GZg059LXOfxyWf65vlZQuj70mKNt8r46CkvPfejSIV0XrUI9mdHn2vOyyi/e2Jxfoa8NzTr14Ryzyth/ZxroajoX1ZKdO5YJZ3x2doH11a1v19w/FBUXiiTaNLdQtyymLynnk+vBvObtW7uYH3MPe/rP4unAXmravI37Dw/gQQ2Xqz9RrZwvDQbweAJ45Nao1/cR1D5dXc59TMB6O+6LZKII18rSjvjrmGKKPWzUrelR630QGBqi2y6ag5Ikeg/WMQfOlUnYLPfTbrBsePqnnJgk1K7lyJet3/R5w0KFMfQXr+Wrws4Xfj7WJhfm5vELKN8Vfhp7aIaoATXLadMemvRztEvMKlymyHPdFt7Uw52+N5t5WPliQksG2T7G2uRJH6sjJQm+L27RsZdUo8naWKl7G2y9/pzXi9f36eRaHz6C9O90koQ/0cW0W5eQO6uommOji0n7LgcMWVjXQW9DQHJq+3bzxtb/v7NTXfhbE5OgxWM9U8enVU4psVQppXqSYH92jvPbszy52NqvsbPir70iUV314VR23kKV8wHJ5s2g7e8BOy3BHiS93JM9SPkhU17Wcqehh7krWGEd2sGoobsNg3ZPZByONFsAfGlSAHi/YcPnm5tvqW0SibmdXqAzxWXmalleLWnA3X0s7r1QzHJEqxno+iR+NJeUWu0Iql1tVfOdvPJlwxD1d1D4VzT1v/xA06ohzaYpbVgRdu/itR+Uml9Oltw3/T+3HImi8EXyzl7t6TTl6u1iPwXpG9+SZVRe9v0DQ8ZyZ1mtDcVFRxAYFP5X8tF4bxswZnXU7n7LNqLocPZ07dGI3yofz6Yjf+wb4nNx/Ju9OBd7Xk8Pczkb+RdsfPilQ1f60ZZ/aJaP3F7jLmuz67m9K4KO2VUBsfEjbqHCO5fPJSS+g7VN2Hf7e3/3ireL8R9Q20NKlzcLtr+u3wvcsVH3m7OFGRERE6HfLeod4PQC8QH3Tgg5lUp9TdLSvm/ijg1Y/Q/SO5PdxM9qRrMTaRN4xAAAgAElEQVRMK79q9Vw2rP9sRYl/DVZPq6RgxMgqOrZzh9oNWNvaevsHVGjbJcri6H17vQcNsbbXmL3x2M4dgi2LC+DeR9bM2Vm0alWVWXTxaO0Sl/61HrcZPtipEmuJrxyj6utHtKS+EUevVL/AecsLFhDM5ROHkzS95Wt8BHJ9xYyq5/vCvVVYaZk+W5JOK4SNmhvDQvPz8j7+bpUe92IkntTv0MXxTX0179HAThVdS22XfD225M1KThvh0kowZCXDD9ZT+mlBcio/K8uqvyUrsQXWHZ5FMLX0068Q/R6mPF/5o1tbQVyVeqbPlThSO6jqg/HpaAFzJY5qB3qdK3Hk5wLSSxmGt5fsSNS1C4u4bv1avZSDJXWYz5LzSY77og94d7YyN2dJ2KtSbH054C8ZGqkwoftzMCqUJ6CiJdqbUhQakyOYWKHe9BEREVtiZ+qlJtp1abxw53S1Y6uu+HNGYR5NLxs+pX3/0dNVIew2ZdH7C6zzG376wxT+cK8u3epTvpqEM3fsW9t+HfFmQV49tjrHcQt3PludrSKYQg0GF/96IE/Ilbo1++Hs+xkpZqpbXzszjnsyaLz9oPHPtn/2f48mh7mNmf1qJbafkWIW8+dtOjpbuxf3P/y5Vo0bCubWTYjXA4AQBTXcw+Xu4XKjGuoH6gI9Jqxg8LwIjGhjHZFSVJ2dZVS9ohxG6DFYz3Hc/I/mnLh+q3L9ZHtLnPhRvEfFxYf375v/0RxxaI8tv/2P/f/9+Sd+vF7t8ju/Wf7Hnv9uPaHnH/wPnjTsKZ1/Tr5Ev5utqPggKb4K64iVfRznnMqq5piRZ6sZxXoN1qvl6tbl8P4XveRKlMX9XNq6uLTv3sNjd3i4i0t7/vu3t8Tp8OWEQV3dXFzav9KmzZHDRyZNnTp14SL+AqcVmb0lqntF+kTSvkFDe/oxq+fHcSokfLCTe7jcxqLe7sFOBnrahp6bodGDspUPU/OLOjs0sTKvf1x+lz94kufxC6tcnamfdXJeYR+Jg7SxFT8ae1x+l+buScnU1DIX69tD2thqR6LcxsJ8eHvJ1ez8ysVzv0nJyAqUyfOVpxTZLa0a+Uqbb7isn+RFejlM/tYWt2nJtjZI2sLBqiFtbZkii9UGJSYS7IhZpsga49qaEo+objlcWqXm6dThVHBEx+V3M5QPaEf8pIJigmOky+Bqdv6l7Dyq7dAzCbPd29N6/Gj+0JirbS3MaUoVi60vLOFhXaD93WQkQ4LVBSPbWFO83hhG71MbqSe2dk9s7dS8lgXYcpyt2lVcutV36SYRr6J2R2p33f21Rt1fk7y8wIvFqr79lm3Knj8uoOb+R/vcusasrAxDngGAetuSC76+qLrN3TXYqZNdA8PVErVOD+swu6WtazWfi01Xbs2/WdUH59mQoUbyYKB+HfDunJxXaIixBKuSIlNMEOjXMTJbPadMMLJZze6rOgtTRbG+3aWNqyNrpCZV7Dij96Eje0ucyo3XbwwL3bJxoyr/ZkjI2H+FUKf4O7fTVy5fPidE9We7Tp29/QMob8aJ67f6ubRV2xu3z8BBljY2//35J36fXEHQv9zpVVf26NLV7Ao/rNpLMqJLyyGGKE+FRKVnjVGNwQUGod9vkEq7knHwrKLyz1Pr91NCbT4cVc7ZywnsSZr9m37gOC5gyjT+Avy3sNq3s2CB/0Qdk3TspOMGq4GNeWkl2vYmea6uthJqUivvG6EuqPFPYHzD1k1L2kmmdNF1YFVD01f/eqhmlA+HHpKo+p4NGshC/3oA0GiCq+0EV1v3cDkljEZ6HLX09XgvVNGpUa3XXblfnb2ndVeh/jKUi9ZwFxU671SP3q98cb9E/10iDv661dq2sWBi/7Hj6AXFyFhP2AXvvD1pzr9o7srlyyl8z2dhZbnk25UrZs/iB+VvxsXm5+V16ecbE7lfXICd3yynF/n376feunnk8JHRQUGGC8yZNejGccaeXBKgclyb+Rmi5tRG21lT3+IvvmD/8xXl5GrJjkW98lljIQvWl7vBnd8sX7l8OZu4/Y/97Tw8q3iAYoWl+EkLADWg6oNDAABogpsbAChHfJA0Me/RmEOZ7uHyT7s3neCq/tkrKJeflSUbwEot8QLlrqKdltX9nv7q1rLxqqxbU4wzWK9FRWuyotdDhZbXUhijPePGzBDBeo7jhrw1UUv/+u83be4tcRodFPTGu++18/Bc/Mv2cjfYf+y4zWtWXTlxvEs/X5ry9vAALfF3QdB/8dOoXDX3pYUKqU3P3NQyDS2aV8/D3nNCQn5fv4a9efnd7XWn5ZNHywbH/itE3FIIAFA7nBvayxS7bdHjEVpKrmUB7etSr6Ns5cPv4m8kFT3oaN2IxmoOPZNQbnIqABAwosGyAMBodbJrEB8klViZf33xnnhANuDLCpRlBcr8eD9r2Z8U7qQsmWxurG+P1GE+/AVoC20tzPlTtNSx2j3SC1r9RO+usb49BHOjlMU0N3WYz+I2LTWV1s/K0tOpmaZ1jSQdgfGL9e0xV+LIikmnTPea1H4JiX3QrT1/+emOTQWXnO6FwRk3Ld7+qlD7x9+toh6sE/vJ1PaRF9h6InrKuLE0rRKRd2v7ZpOmTtU0Fm7VGagPMjCexy8gWF93nFZkDurqRklsSG+Jk+CDorfEqeR5A60iKVH7x4IuGwQAqJVM9xlr/tAXAlcHeo05Eqd2VlagrOeBs6FnElKH+aidO7C5neO+6M5Hzq/PukdjNXsev+C4L7qXo53aVcDQIjYoIjYoCvJ0DfxO67VhWq8N1y89rvQCxm9UmHRUmFQvyXAMDfF6ANDVgQAJpcRxD5cHHUJXSo0c90Wznsh0W8PvmLwgJUNwl7P1aip/gdjM3A2Xb/IfrozNzF3l6qz7HgX3jv1OX5Y2tmIBfcHctZduDHvFSVNpo5TFsZm5/OUPeHfm77cyFQSiqtNyinW5hATWXrrBX3591r0Nl29eHeilaXnthcEZNxUUVuMXtp/fgLuK2+zPEs1PSNDokZQ0o6KHe2znji0bN7KcPGCcUof5qAYn9O3BmugYfhterG8PPytLWvjqQC/xwlmBstRhPid6dxXPghpnbd9MbWBd0Mn9tCKTn27+tCKTP6w0TeGnvhFsU7yLcjcIAFBT5kocWUco+prj3xLT6LvsS/BHt7b0DcgWyAqUsbtiQQ8YQUeWWN8e1KWGfnMFNbHJCpQFNbERr0s75feXEsgKlP3o1pZfsFjfHqz3FW2KbZmWvzrQi5WT1i23vkPPJIgXU9VAfpHaZ2p3d3M9Lr97q6R0fda91LyiH91eyiO/ytU5W/lwQUqG2n39M+EWjZvNCswOX8fSGpsRI0bsWShnmdCN1h9b9v2xZd+d1BKTq+E6j0M+HACosPgg6YKYnIiUIvdwefSo1rYWaPYrhzit4Z95BYvM67M/Cx4JFxBPqSIWZv3Rre2AV1rwb5gExKUt5BWGH6790a3t8PaSngfOIm+joZV7CQmcyysUTEkvekBDIlcUzrhRoWC62rC7hZUlhdVKlMUXjx0tKijwHjSEJbKnCFpRTm5aYgJ1vbe2byYIzYtjcN7+Ad37D+BPOXH9lmDvFlaW/ceOO41gvXEb49pa8LGfOsxn69VUtb+rf/LtJliYNQOnDvMZcySO/zN+lauzIUYjB6gj0OgFYGjLFFn8Z8g8j1/gv+8ECW3+mXCLS7jFX4A/d33WvSax12J9e2gaC8rL0Y4tH36/MPxpH/bwp1Nmu7f/44aCZt0qKS23BwyVhF5nBcr4+WTWZ91bz9sy6XzkvPgotOylrYX5+qx7U/OVu7u5jr6UTBP9rCw1/U5sa2HuK23ONtjv9GVVK0hyGvtR0EficCYjh7+K+PONXx52B8I/UtCj35bfigo/SNv7etomjuMW7pzesk3ZpyN+z7ujekfYtXCkF2wW2zktz/fD2ffVFo3txdLaurioSO3WoNIQrweAClvsbb/Y2949XC7bk25jUe/UqNaoQ02Wx14T3y2dG9qr54GzBtrjjkT51YFe/Js2frSF4q38WR90a5+tfKhlXV9p8x2JcupVwXEcu6X7Z8KtxcoHu/t0xfileqcsffGMYSUuIfFwtYt83CrRNR5n3NhoyR/NWFhZaurZam3frB0vx7SOW9PyJ5iKkJhEQUnfO35p10APtfH6tZduaDqsV/53JqiJTeowH6un7YWhZxIQrK99MBYFANQmJ3p37ezQeMPlm5tvCzO/rXJ1lucrtR+r6tG0zNzN19LOKx+UWytRt7M1zWI/r6j7C8dxFeoB08XOZpWdDX/KjkR51Ue7pdYLv+R0aokX/4Jgzg3t9ccNBb9P/R83FPzWjlOK7HGdpPzIO39TlNdeMGu6Y1PKbn81O7/f6ctVORAQGx/SdnzI+9N6beA47tMfprh0q89xqhj61xFv8pcNe/vPjOsp6z8/sHD762ziu1+8JQt4NmYhReSn9dogDtkf/i2HgvX8WdN6bQgbu15TfB8qBPF6AKik+CBpTNaDycfuuofLV/ZxHNAKcRw1qE/HAe/OLAv8jkS5QZOKqKInyWmxvj2kja1oyvLYa2yPjvuid3dz9ZU2Z4Xpf/j8sUFemtYNPZPAOoOMvpTc1sKcRWpoLkK3ehelLE7NK2KjOVX0ErIyrz/mSJzgLFfuksMZB6gd3mzlEPVyYH1ulzbH5XcrcXCqDoMvP9KONFkAAGCc5kocOzs01vQ9NSs5LauTVDBRMMiTYF2/Vg6VO1D2OBrrTq77Fyg1KggayP2sLPXywCslsmf/q10mdZiP2gFjp2flsbVmJaeNcGl1ondXtZF3frB+rsTxXF4hZbdff/weTdHy1ALoUUFevY9fX8dxXPvuXV6f4GXT2KK4oEi8+XZdGlNwX/W47WBpVLj6EiTGptKLiA0KNnH4pECcMX1BvB4AKs/bsVF8kLTPnvQ5p7Iogl8HK1NwZ6P2RmdozFVNq4tvTcQLa1ld0x613PGouks/7zFNBI89Ctbl35zdKinVkksHNBFUqfiUCU6x+E5X+zXAR/13okRnmalQYXDGAWqBbg52Jxzs2AeLKjG98qHunyrMid5dX7GzZp8JWnLvQh1RoizGYzcAYLSWKbLGuLbOCpTRs8IjXFql5r0UnXTcF00d8PlTQjw7sNeq1PDZ+Zey81paNfKVNg89kzDbvX0lDveblIysQJk8X3lKkU2b2nD5po7reh6/sMrVmXr6J+cV9pE4SBtbCUef8u3hYNUw4vptGwvz4e0lV7PzdW9N/+DEpaxA2QcnLqmdS4npxcF6+pH4Vnb+Ae/OdEdBtwfU0Sdb+TA1v6izQxMr8/rH5Xf5w9suU2RR5zA6KWoPB/TrTrrSpZuqv/zPi5895zF3Q196QSlxBFF71kG+IK/e19NUPfR7+b8mLtHM5R7TesWouos1bjhovD3HcatD4uL/Uk0Z8T761+uBWVkZ8goBQFUVlDyR7UlXfTS3sV7sbV/RrW2Jnclx3LAOs1vaulbzudh05db8mwodFgT9M4a0rbg7NGaxvt2lja1rsID00VQ5bpJQo65c01Hy4GRyblSFittLMqJLyyE1foRR6VljLlyr8WLUVkaS+PtKxsGziojKrftqi7FP6nfQd4kqZsXsWR9/t0rHVYpycn/9/lv+wBgbw0ID3npb0rFTzR4Fx3EJikU6LPWSSZ6rDVumKkjOiUvOjTPa4kEd0cyyZbcW/SwtbI3wcPX1Dctizcx0x6az3dsLsoMaubrzrNuSdpIpXdrqsKDBjRgxgnYxKsyoOyyyDvUsa831S49Zevr23btIXVvxc9pQ/pyFO6eHjV1Py9i1cOSn0Hk5wY5K9P6Cn7/8lV5bWlsv/v0dW7sn1XuUFcNGCY6IqOT9G59BA1noXw8AemBrUS8+SDrp2J2IlKKIlKK62dEeAMDQinJyB3V1W/Ltyv6ah3jtLXEaHRQkjsHdjIt9e3jA4csJ1rws9gIT+8muX38pfbn25QHApO0OD9c9Xq/6XbpxIz9ez38NVVFcUvDJocHW5tbzX/vNzrK5q72Hq70HahSMxKX0gxvjv3Bt1mO2z7padk5mXEym1t/YzFxHq0bU6du0gvUAWtjaPRGkknfpVl8wZXzIiz+fzyrTlIBePF0WYCsL4E806mC9aUG8HgD0Zkv/FhzHuYfL3cPlpjIObc/mTXc1sdFhQaiddvWo4b6NoIVNAwtUj1rzP5pzeNAQtWH03hKn7X/s/+/PP4lnvT084LQis7fESe14kr0lTocvJ2w9IeyflZuWNqirG4agBKhBvSVOm3bs7NLPl+O4Yzt3zP9oDntLliiL+7m0/U/UMerkvmL2rN3h4Wzuitmzhv5j9JRxY6nhLTctLaCX9/6zMc2cnRVJiQ+KiqglT9WBzrF5M2dnatU7cf0WZblZMXvWvXu5i3/ZTovlZGa6uLSn5dt5eNICb7z7XjsPz53fLG/RqrWgHZF92mgvpJajqwvS868tPfnO8iFHVvsj+xwYqW6th6xurXpq7T+X/h11O6I2Xau3SkprQc90PC5c/SIiIqryGC6ALhCvBwA9iw+S7k0pCo3JcQ+X7xrs1Mmugabtb0sumOBaw49Yujva1WwBoGb5tXbEGQCToyns3lvidOL6rbTEBPEB0SzqLy9el4L1ahsAmjk7ixd2cWnfz2/Alo0bqTC4ggAMjcLZHMf1HzvuNC8s3s+lLf89+PF3q/4Z8unEfjLW9vb3+Ri2AL2d6ROAJbGhyDt7Ldhab4nT4uezWuTkXr9+g788M/ZfIarN8go2sZ/s8OUEHQup6ehqvSUnJ3aw7YxIPZiKf3T77B/dPpsZ6bPQ77/2lhjCBADAgBCvBwD9G9nGemQba/dw+ZhDmZrGoR26X6FQltZ4vB4AwBTtPxsjCLtvDAv9ftNmCyvLnExhAH1jWOiSb1dSh1lr+2YLvvxy5zfLx/4rhL+MIFh/bOcO/p+ywJG0OsXgaGFKhRETud/bPwAXkZhfa8cstAiCPtA7XZGU+NvaNbvDwydNncrefaODgmIi9wv28eG8z9hr7/5+updgY1jolo0bN+3Y2cGrZ0XLzW9HjIncP3zUG/RBUW4hNR1drbc74dsOtp3/0e2zmjrQC2mRypJ8ev1r4qq3Os2i11YWjXs4+9eFU6Av8w8OzS8tWONfTh9nwWLfn5yUlJ9U7lpGaLX/mZmRPjXbzoRvWACo9erhFAOAgcQHSQ/4SyhDzror9/k7cQ+XK5SlqHgAgMpp5uw8JyRkY9izUW1vxsXm5+WpjZsX5eRu2bhx/kdzekuc6N/iL75YuXx5blqalj33HzuO/Zv/0ZxHxcU0feuJ6IfKoon9ZLQpRVIigvUABnUzLrYoJ5fjOEnHTh9/t+q0InPgyFErZqtCq97+AbvDw739A/j/uvcf4NardyVKdDMudsvGjacVmV36+VpYWdK/Cm1h046d9KH04ZTJrEVQeyG1HF2tdyxlZw0G6zmO6+HsL2s3jv6p2mWfv+7h7H8waWNwpCw4UhZ981nbbXFJYXCk7GrmX2x1Njcz//rmcx8FR8o2n/uouKSQv4BqKMKbO4IjZV9FBfFnqfKQ5Fz8/uSk4EjZ3ssr+NNprb2XVwRHyn67EEYT6U+2JO1OsNb3JycJDlBtwajYxSWFtPeDSRvFe69QmYMjZfmlBfSClUpcgeLFkvKTBAWmw5x/cOiFtEhBPWsqcE2Z4BbyQ+ynxlASAFMx2WuNjiXlL6n7Wkao3MJX5ejO//Iw60wT060cXaB/PQAYkMTaPD5IGnQoc13C/XUJ96mjvXu4nO1xb0rRyDbWOAUAABVFCSgC3npb0rET5aZXuwFN2ef53fOXfLtSU157sWbOzvw097qvCACV0M7DkxK+f79pM8dxJ/48wE/+Tr3aXVzafzjvs7uK24u/+GLBl18GTJmm434WfPllb4nTnJCQ1wKGt/PwHB0U1FviRDv6fum/+/kN4C9M/eUpIq+2C3yXfr5LF3xGQX/+dC2F1H50UFOGdJw6pONUilAHR8rW+EdbWtis8Y8OjpRJLCWTPZcsOvku6xju1Nhlcs9vJz99HRwpe6vTLGoAoMA3aw8IjpR5OPSc3PPbWzkXl58NXj74zw/7bqHFvooKUhQr2AYvpEWO7PrxyK4fX838KzhSNqXr5/TnhbRIKszknt/GPY2nf+4XTmFuVSvR860xmgr2a+IqWbtxtDzbJluromWmauE4jr8RcQWqXYyhiv3cL3xk14+55wUO6bWmrX33cgtcIySNO5zNPII3KIAu6j9q+F6fbzafD0ZtGYNRYaqQ1CTP1cZfVPSvBwCDCx/sxCL1/GA9x3HLLt5D/QMAVM5pReY//PpriZj3ljjtPxujdhYlsqfXqpzRTwNqC955u0T5rCt9UU7uxH4y1oWfbAwLndjvRa/GKyeO49QBGBp1PKee6fSav8PTisytJ6K9/QMCpkw7rcjkB+s//m6VON08f3VaZey/QiidPX9HW09ET124SLyvqQsXsWC9ePtbT0Sr/TjSXkgtRwfVj3p5U59uihcza/yjFcWKRSffXT74TzaRuqLfyrlIfyZmn2WzWOCexGWf4zhu+VlV0MrSwoZNp7A7w7LxdHZ6jf8nP0sPlYT6oR9M+11TEFxTwcT7qmKZ+bRUoBbiDdJOyy0wABg5tcH68788nOy1ZrLXmi2zY+s/ali5I6if03Thm/toO/Ijwkfiolbn0KzzvzzUfVZBfDNNBaOFWcmfpNsLdvTwuoO4kPIjljQ3anVOuUfENiU+nCfp9jRr4Zv72K5rN/SvBwBDKSh5suBcTpSiWMv2C0ueoP4BAHRkbd9MHD4TrEphL01zmXI3ZW3fjPrR8zvS8kN11J0WwTUAgNrkYNrvrGc3P8lMXvGdz6PeXD74T0sLm+BIWd+Wg8b3WPhVVBCLNQuyx2hCPc33Xl5BfcmLSwpDDr3et+Wgilbhsx7rl7/6yu938dxKFKzSZe7YuCM/uY2mChQsxufh0DM4UkZ1y9YyxdT2AHXEiBEj6ECps7YWD687THjvpVZA80Lb0Hd+Dfs9cPM7z4L4t47UUxbU6zSqYoGRyV5rfjr1r7DfA59PKJ7stYY1DNBrv5nP/twyO/btWa83dMnWMqt+TtMvpv6iKhhrXXjE8be57vtNa/uEeb2TTSWvn/PkPa81G/d84TeTo62ZFz58l7c8Hb50YDabknWmydqvt/HKLDwcv5n2zwtWvPDNffO+/mdDl2zzQtt3+y/dfD6Yt+Wcdd9vWrq6JnPKVQPE6wFAz47eLl6XcD8p75GOm92bUoRTAAAAAABQI/ihYf5rfpIZO8sWbBZ7we8VTjlz1G5Hyy50X0ttCPutTrPsLFuI60xTwcRbqHqZBal4NM3SshjL2yNeUnuBAcDI3UktetWrHce9GMyv1KYg7PfAJ+n2cUcVirQMjuOy7+Y4NLfvNKpNhQ5l8/ngx5wqh/vf528W3C8QzF26+rPJXv8e+UbA62O9GrpkT/rOk+Oytc967/XFS1d/lvXySNJSqdS80LbU5tn2KeJPHturMiXUa/2i1zxbjOEvz3Gco899uVzOiTxJt5dKpZlxjTiuEZv3wacTPhi3cPP5YArWC9YJWxZi7Oe+yhCvBwA9G9DKckCrlx5fKih5MunYXU0R/NCYnDntcBIAAAAAAKB88w8OzS8tYB3SAQCMU1NHy/Mnkv18XuRvYd3Gvd5pyHFtnnZC9/pz5/mKFp96vjv63H+6cdX29/73xVxHn/vPY9zZtNMPPp3g6HO/3FmCvYT9HljKCaPwhuDsLBHvXUvS/xtX0582hNRmiNcDgMHZWtQLH+zE9hKT9WDysbv8neY+qNesERLjAAAAAABAOZYMOYAqAr6c4oywqDdogk+L/q0ad0L1mKJcpeLcnSNFparn72f3Wutq72HqR2Trnrtt0g6WfIY8Uj7hJ4b/YNzCkW8EVHFH/ITvT9Ltp476kh/s7jegT05mgaPWWT+d+td7Xi+l2n+Sbr/ow5/Upq/RUdTqHL+ZL7VVrNwSynG5grXrtc5JS1Mk7vHmJwWiDDmPGzwUF6x+TtNtP61Z6lXL8+GYlZWVGUExAKCOOnq7eM6pLB/Lb3xalg7rMLulrSuuBAAwEltiZ1a6IG6SUB2W0o8SZbGF1bN7dP5rA+2impU8OJmcG1WhffaSjOjSckiNlBbqmisZB88qIip30K+2GPukfgdDVFhvidPooKA33n1PPNgsW0DT+Ba9JU7fb9q8d8evi3/ZLp5Lw03TyBbMgnfePnL4SM0OZZGgWKTDUi+Z5LnasGUqz8xIn9X+Z6q2DYCaIc+N/++1dbN91tV4/ReXFHxyaPAEtxCfNqNrvDCgd0l3Tq2K/de8vr+0bmyQr8tK0z1/PQWXKS88f+LD6w53Uotad7SifDL1HzV83ODZ0K+aXqvZ8qOGT3PIcE4eDx43eChYmOYWFz1q18tckKlGyywacvZeVnHb7o0o4w1/LUFhtE+h16yQ4u7z4tXNC21vni1t6mhp6y6M6VPBHigfO7nWExSsEvR1D0C/Fg0UyEL/egCoSQNaWcYHSbfElhrPWdgav+hs+n6O49ybebja9zSCEpme5Jxz8blxHMf5u07xd51icuUvLilYcnJibrEq9ODXakQzK4kRFKp2YpdKr9YBE92rL8Bdy/RzacsiZfzXVbFi9qyPv1vFNvDTsn8HvPW2pCN6qwGYho+/W9Vb4qQpIn9akUkhe4FjO3dMmjrV2z9g745fr5w43qWfr3hF8VqLf9k+PydXPLcoJ5dGrsY1A9qZmZlxHGcS/QhnTJ++bv163Zc36KHFxcWF79q1ZOlSQ2zcJMyM9Al97Ve0e9ViHVv0We1/5kFpkUk3cD62v7fol7fe9XopCXtDl2ypi+p357NleGFrTa/VbLnBQ0cf1QKPRSvy54pDLVpm0TMBtqptFovXqu14kIQAACAASURBVNAUes32pbb8gimlNgXSgS+qRUPBqmTPQlUC/T3ciIiISva3qDaI1wMAcCxMv3zIkYnuoYgbVpGf63tsAw9Ki0IODpzgHurTuqpP+VWDmZE+7s08pvms/dJvj/GXthbgXypU/60au87vu7Wu14sR2B0ezo/XT11Y4b6roNbuhG+PpexE3VRI/zZjR7t9ZEIFNgYlymIKygti6BP7yf4TdUxtAUuUxfM/mkPLL/5lu2Ddnd8snzR1qqYjs7Zvxl+Y1mWRek2Bfqh+GRkZEolk8OBBBw8eYjtPTk52dX2pY6CZ2UtP4YuDzkuXLpk//7MlS/49b9588QLjxo7duWuXliC1YPtVMWTIYHYsrq4u16/fEGy5sLDQxuZZjvv58+YtXbZMvOu4uDhPT8+CggIbG5vCwkJbW9tt27a+/fYE/jJUdXopdmFh4bGoqOGBgVT5HTp02BcRQX8WFhb26NH9woWLtra24n1t377t559/PnToMM3y8PCwtbXVY2WaFjyhUnc0Mrde7X/GqM54REREhR7DLbUp0JKKHUAtxOsBoK6j5yhX+59BmN4Q6AbL+O+qZ0b6THALwX1/zaL6n3tw4KtO/eva+3HF7FkXL8RtOXDYwsoyNy0toJf3f6KOsf7slKHC21/V6LV/0w+Lv/hCl+BXibK4n0tbtp0Vs2ftDg9nK2raoyIp8UGRKm3ozbhYjuPsHJs3c3ZeMXsWP7fGxrDQE1FHad2inNxBXd0WfPllwJRpbMtD/zF6yrixhy8nWNs3o43vPxvTzNnZYPVn7Fhb4Gi3jxB6rpwfznwQnxuHT+kK2bRj58R+Mpa+5tjOHcNHvaHpQRnB0zmCcH96aqpnHxl/+WM7d7DXRQX5gs+lnd8sH/uvELapGjl8EPhj377AESPEsV1BsF4X8+bNnzdvPoXpKWTP17Rp00rXvaury9Mo9nX+RDMzM9Y2wHHcunVrP/ggmA7k5YaH61QkPhas5zhOJpNx6nh6esbGxtKSNjY2sbGxnp6egni9IFhvZmZ27dq1Dh06sIYK/q61B9BtbGwoOs8qf9u2bTTFxsZGcOz8PW7btvXgwUP8HdHq27dvE5S21vvk4KDQ13413aOka5g/xdCNLtu3b5swYeK8uXMFD2TQ5RQbG+vhYeyZ4o0tZA9gaPVQwwBQl7FgPa4CQ6N7LOMsG938IfGlkVg25Ih7s16fHBxUdw55wTtvv/Hue1tPRFOO+GbOzqcVmU0cmtNcCplRsJ7juIAp0zTlshCg6BuLzX383ar9Z2Mo/bSWPUo6dqK4fDsPz3YenuIg+8R+soEjR7F1Wb/ajWEvmlj+Ph/DetfSxgN6eRui6ozfJwcHRSasWu1/ZprP2rpZA/oyzWftav8zUck/hdSlD4cq6tLP95U2bSiwXpSTu3nNKhZDF5jYT7Zph/DJDwr30+t/hnw6/6M5/Ln9x45j/zq/nCj/tCKT7ejYzh29JU4lSvXPtkN1CnyecJnExcWZPVfpUsyf/2K4v7inxo0du37Dhn0VzzOwbt1aMzOz5OTr4oB1WVkZf0csWM9XWFhoZmYWGxsr3jI70sARI9QuQH3V1b7WIikxsewp2n4Zj+5VOm7sWI7jduzU9twVHVpZWZnaoPy2bVsnTJio4+5qjeLSwha27UzxaOg6nzHjg7KXGXq/J/86Of3995cuW5aRkcEvzODBqq/Uq1cTDF0AAKgoxOsBoE5DsL46GWfIfmakz2K/GsteFxwpC46U3cq5eCvn4sGkjcGRsvkHh9Ks709OCo5U3xGs1uvWekg3e6+oWzvqyPEeOXxEPCwkBbtjIvePDgpSuxblhtaEVoyJ3M//d+Ny/IfzPtO+x3Jdv35DvO6QtyZu2biR/end369KNVJbzIz0+fy1X/3dZtX1itAfP9f3Frz2q9G2/hohVXL5j+aUKIsHdXUTjBPLXDlx/JU2bQTZ6gXh/mbOzt9v2qy2pbBEWfz28Bcp7/Zv+mH/ph/Yn/3Hjtu0Y+f38z+tzbVsIo5FvTR2t4eHB8ULK1d6ivoVFLwYqNDjqR07d5aVlQnaBnQxY8YHlGlH7bL7IiIoCG5mZiY4EJo4ZfLksrIytaF2dqRlZWWenp5qg+nbt29T+1oL1kd+4w8/CJbSpVb/2LfPzMxs0+bN5S5sa2tLx0jYa5qblpY2/f33dSkwGAO1rU2MmZkZ/y2giuxPn06pnPjXLVts+/ZtguksHE8XSWFhIf25fsOGvq/1PRYVJZE8G5ersLDwgw+C6QmVk3+dxNVh5CZ7rTHaAkZ8lfLwuoOOCz+87sA/FmM+rhqHeD0AQF1HIWNNlVAXQsZ2ls1rtgBt7bu3te8+pOPUr/x+zy999tM3KT+JLRAcKYu+uaO4pJCC+AeTNuoyi+y9vCI4UvbbhTDBKnnFd1jbAMdxv10IEyxWsyZ4Lv3P1ZVGUhhDGx0UxM8sQVbMVgV5vf0DdoeHq92/9vA6rejtH8D/173/ALdevbXvsVyTpk7d+c1ywVI/Lfv395s2G1Ol1rz0/GvW5tY1/vFS+9hZNneybJmcE2fqR/aw5G717Oi0IlP7SNRTxo1d/Mt2tbNYuJ8+VU4rMkuUxQveebu3xIn+7fxmuYWVJX/jAVOmDXlr4sR+MrZM0xYt+ONhALE0t7lTcLM6K8O3f3/q+k3BPuoOr2NsmnWf/2PfviFDBpuZmb377jtlZWX8bDO0wIzp083MzNaurUwIpqys7OKFi2rj6cMDAwcPHmRmZjb9/fd9+/dn0+lwtm3bGjgicPv2bdu3b4uLi6PpQ4YMpgT3dLDHjx2jZDssWsqWKSsrmzBh4pAhg+n5gAkTJoojqi4u7TXV1br1611c2puZmdHe/9i3T22rA9sdRerT0tO2bdu6d+8eKrb2auFjU2ju/PmfVWgIXL1Yc/6jfyC3W2XRJSomTjBVVla2fsMGjuMoic38efNYmxYtRo9W8NtyWDieVue/Qzt3dvPt33/w4EF0Hdra2ioUCo7jpr//Pu0F6ibzQtsqBs1HfN6moUt25dbdfD4YIXtNkL8eAKAcFLDu23LQ+B4L2ZLBkbI1/s/6qeUV3/k86k2JpeRzvxdhtcz8606NVb8Kom/u+DVxFVsYQIw1igxxflPTpfJr4ipZu3Ef9t3CcdyFtEj+Fahp1ldRQU7WrSf3/HZk149pL291miVrN45WWdNu3JIhB/jXM/8Kh+r08Xerrpw43lviNCckpF2nznt3/Hrk8BEW/zqtyJzYT3b9+o3vN20uKiiY/9Gc0UFBuuSDprQ5Li7tP5z32V3F7cVffMGyzGvfoyphzpdf0tzXAoYLsl1PXbhIkZTYW+I0aerU7r18Tvx5YHd4+Inrtyg9DjDFJYVD29a5HAXVQ9Z6ZHJunKu9sSfb1S45N8pN0tcQWxZ/Pmifov3zRDDXwspy8S/bF2tdzMLKUlNffkOwMS+ttn3p0f8NOVwjuZgFkWgPDw9xlhXBMvw/PTw8WL9ytQusW7++3PCxlu3v2LlTU3IYfqp6TZsSTxckuNe0LnutqQCUHH/kyFEUABXsl79lfhWp3cXwwMBy+9RrWYA/y9XVRVOGH8OJSv5J0rhD68Ydqnm/tQONjiAe0JjN4o+QTIF1Qo1tS5YunT//M/41wB/aQTt6+oSGQFi6dMmSJf9u2bKl6kfua30RrzcJT9Ltp476UiZTPWIYHX1mxodTvN5pyAqedabJvJn/HvmG6nG3vf/dL5VKw35/6bOawuIj3wjgz2WxcnrBBsWNWp2z7acdI98IuBB7WS6Xb9zzRb3WOWxJFmT/6dS/Hjd4GPFVyutjvVjInmZNeG/ctp9UfYN++nPBY/t7rBjWTg8Flf3zsXmhb/4qKK3hjAqTqrofea42/nOOeD0AQPnW+EfPPzj0JC9CylxIi9x0+SvxdArWcxyXXXS73O3z+7Dz4/57L684mPY7vV4++E9LCxvBwmy/miaG9v150cl36c8pXT9XpaO9/BX9GdJrTVv77myt709OYh26p3T9vIezf7lFVbsjtExUAqu04pLCYHWXmYDq7Dw/j1pmKYoVimJFHO+UUWRfvNYa/+iDSRv33vgJZ1BfGtWv/+DxY9031qWfL4t2efsHCGJh/MjX6bHCM6gl7ibo9Kr7HgOmTOMvL+gbK+nYib+uYK7ajrSVHnAyOVeY9wBqli6fURVliG2aBEuz7OIyXR8hB03OydVnUDF+lCdwglsIRtAxCdWQZLyiNA1OazgzI338XafM9llXswduukOPUnYm6iZPozJMf//9gICA4YGBNOv4sWNf/furQ4cOr127RtBGpVAoaCQDNoVez583b+myZRzHrV27hvJKaXft2rVvVqxg7WqdO7tVZw1U2sxIn4V+/zWSwox4nvKLgr/Vo17rHBZPn8R5stA59ZFv7GDB5o74PPjhdYeo1Ul+M+05jkvcUy8jPYs/l627+XyweaHtu/2Xsrlslt9M1ZQRXBuO4+RHlDf25NDWqOWAln/MCYPvWWeasE3RFt7zWszfuFipTYFcLq+2ajQhiNcDAOhkyZADlF5cEFPY9HLY9FbOxeVnn30h0ZIju348suvHbHrHxh2pHzQff5vBkbLN5z6a3PNbVQ+ItN8FUfWvooIEy9OWBVtgfzaxdOJH1df4R695GogvLikMOfQ6fy1+qYIjZX2zzwp6W2vfUcb9a4jzVt2XUfr8xe7h0DMu+5yO52VIx6lDOk6ljDpDOk410AHWHTl5+6xt1Td6ge4szSr5dK2JonbTtzrNkjTplJwdY21hq7aBrSqCI2UzPZZ2dnoNl6ExiL29zk0SavzlNGb1Hl8z6fJTwHFmpI+Lreuc17YaQYkA1HhQWhRycKB7i37GEyL/v8GHTDRkT+bNm6+2X7xv//78jE98LVu2VNtotGTpUkqYw6flKRZXV1f+QzCsCcGYzYz0mdf3F3vLlkZezupX/1HDxw0eltoU5GfXmzfupcQyT/vaqyLs/7d4lThirimGXhDfTFNaeYq/U8uBpgN19Lm/ZXZsdLTGN2ZZg0f0EEANcrJ1NZbzpxXi9QAAuhrScepr7cYHR8q+8vudrTLTY+nquHnsz7b23Sk8Kkj7zp8uCPpTD33WfZ6PFqMFKMLCut7PPzg0v7RgjX/00Rs/q12LiLepfTqTVZQmmKJ9R5r644N2gmA6S1AjmCWOubMpWmZN7vntZHV71xLBR6OLvqQWxPZsOqSwFDdaVRJ7u4Z78FWzpPykr/x+t7NsQd8abOf0rUHZ1SSWkmCf1bQMQw9jCfK2sYRsqt9s7d9j7XD8YP2tnIu/xqtand9y/5y/x98uhJ3MOCzeoJh4C4Imgcz864tOvss+WzQVtc5KUCxCyL7SGpZlXLijPneKaWExx63xi86m768FRwS1yTTPZe4tfI0tMm5pYbva/8ySkxNv5yebbtQeyjX34EA7K4nRnmLLAkmxraIGC/C4wUN+Z3k2PetMk9NHLrE/6+c05Sel0cKuU5GWaL529XOavve6qjc9df8ngtD/4wYPR3zeRk9HX0m9Wv+jZgugI/yMBACoAEsLmzX+0fxYfGen19iUIc5vuksGqh5XvJ/IFgiOlLHpP8TOE4dElSX5qqGH0v6QNOn0Q+w8ieWLYYJ+uxDmI32DFmjZpAOF6cd0/tDO6sUyk3t+e/3gUEpNLmnSKU+pkOddpXzluuvbclBwpCyk15o8pWLT5a8am9uKHwLQy44A6o5z8iXe0gVFpWrGzQNdJCgW1bV6WuMfvfncR3HZ58R5yejBF+puT8toH6YiOFLW2Nx2yZADWnroUzMANQPnFd9hbcm6D2ihdgvUjM2+6RadfDek1xrtI2rUcQmKRfisqITcvP9kKhNMrtjaTXQPneiO9hsAXc3v++yplE8ODiouLfRp0X9wh2ktbNuhAk1XXvHdI9c2Rd2OaGRus8jvv8uGHDHCQ5kyZcqmTZtUv9a/OVNtKXEme62hfPEslz2LqoctC1n45i6WAl5+xPLimRfB+s3ng9/zWszPdz/Zaw1LSV9qU8Dfy+MGD9fuCJvstZDt6+F1hw/GLdQlgk9NAk/S7fnJ7gXLiNPvZJ1pMuPDKZWtlcqwt2pdnburNDPjf/IFAGq9LbEzOY4b1mF2y2p/NMmkn6M0RUZY4bgGjFaNnxr6aKoiz1YzkJ+6ohrVrx+X9v8qvXovyYguLYfUVOGZ5Jy49Nx4P9f3Krc6f3AUcSo2fmxdvC61Iqt9XIZNZw0DghXphZYBLXTZAiX2oaFf3B17UehfU1Erkb8+KvmnYq7U37Vaf92pdSXj4FlFhF42ZWPRVOqoh8+cuqBhvSf/n717j4ui3v84PpOXIkFBLQU1byymeQH0JCc0sYTKvJUJpnbEywkVSz1ZQlZqZWBZWscLeCr1F+YtU9E4J7DAo3bUBPFSKuAtDdREQTBNrf098GvTNLssC+yys/B6Pvxjd3Z25jvfXUZ4z3c+372nzU/iYj2nmGsOAKBPSgn7Kq5iX82Yxvf2Ztv//e0aZDG+HgAAwF5ERRfqXVivWo6ZtdKV68VKsbJtJz9Tv0mdaEcmBfo3vl88Lm2ainb120UmBZqttCaMuX9eRukj3K2Z0MLCFp7v8bF476UbRco4/XLNqFEDFV+/+H3uG6T2lt1x2y8Zp9/WcwsBADVBYmKiEtlvmPUDkX0FHN5wW9Z3B6omrD+/1Wt7Wsk4sG/uvnVvhP6R1wMA4DRkmRvjnJIo7UJqb1lNTuoFdbauKUpW2oQWpU1TYVrTzPJ2yly5vFsQL6mz/tKayswZaiK1lySpY5Ow32r56KdhjlVbvu3YuQ+Kr1tVexcAgCogIvs777wz5EVupa2Iewf9du+gqqhlv2HWD5L0Q8k9uN27T58+vQr2aBPk9QAA2IAsl5QeLioqcnX9I3HbvGlT/5sjL8oM2Q0G75yco3bK4ktL+WVZDg7uM3LkyIMHDsbOmRMWGrpqtXbivry8PC8vr+DgPikpWzQbkWU5atq0jp06iqft23fw9/e3R/urDWI4s+rV+vnbU+/qsGGAAx1UTaN6311P3n5H56u//lqjPhDX2jdO/LT63JVjOmhLlWLKWeiES23XwR2mBDR/nA8EKE1i4q2aeP898UlO/i76SW9O/7vxnt0ZolErV66sV6+eEzWevB4AANvIyspyc3NTh9r9BwwoKipyc3NTbz82NiY6+uWoadNiYmPFEpH1Kw+MRmN2dvZ7774bFx8/LiLinblz1dcAlMsAwcF9li//P09PT2X54sWLJkwouaMwIeGT4cNHSJK0YkXCiBHPqLes3o76aUxsrCzLpnm9p6enWE1ppJpyCLCeOobz8xz7i+xZAzvPtfaN7/PiGC1rJYaf13Df/fS5JH1e03uhWtt5+ouE/W/8vfPrXZqHMOUs9ObN1CfOXMljtifAggdbPfNgq2dI7fXj5ph6SQyrnzRp0sMPP+x0h0BeDwDmjR83TpKkuPh40zHFJTWp09PFUGKzMaggRkxvSkzs179/aXuJjopKz0hPSdmSm5urDl7NDohWLzRdoQKVUoqLi/38fPfuzdSkzGohIcHJySnqIzLbMOUwRRhd02q2ZGRk3Owfg7d3W6XHZFnOyspSR+0hIcFt27RdHBcXFRUtVhDButFo1HyRDAbD4ri4xXFx6tXES7GxMVFR0WLNoWFhq9esUd41fvyE8eMniPaI78Pw4SOGDx9hzXdDluWw0NDyHrgS4qsvP8B6e/Oco34iAMAeRFK/oO9ORjFDt17pvV6SpLNFx97YNozUHrBApPbXfr2SkPki/eQoLkVeK9+7daaaP39+mzZtnPRAbtNBGwBAj+Li43v07BEc3GdoWJjSPJHASpJ06FAZRZZlWR4zZozRaLQQ1hcXF8fOmZOcnJKWmurl5WWnTlixIkEzMlqW5c2bNpUMcXV1zc7O0Yzd1lDCekmSsrNzTFcQG1cOUyTR6k6rCZTvQ3Z2TkrKluzs7OioqKhp0wyGP80Un5KyJS4+Xv6dJEli8LvZXg0JCRaXASRJ2r5tu/KS6GFBPRw+NjZGluUVKxKKi4vLVZdm86ZNsiwXFRWZDq63zKgSO2eO2QH4AOwtMikwMimQbgaczovJfaQbVwhA4RSauLVZ0HfnxKSA/Ct5fGKABXVruYzuukD82zDrB/W/bxZf/e2IweViS5ciL5cie/35X2N1bzF4dNcFTwe9nPg75w3rGV8PAJY0b9Y8OTlFluU33nzTYDBER0WFhYaKMdTbt21Xxjsrw6sFJSpV56rqKFMZ6ezm5paWmipJUq+gIPW4bGHFigSbfDrDh49Yvny5weAt0vaQkODg4D4WriKUpri42M3NLT09XfO6GBseEhL8+eclo2/8/HwlSfLw8LBJ452FOk/Pysry8fHR3HWRkZHh7+8/LiLC9I4NISw0dPWaNeJxSEiwcqWkuLhYs6bmNotxERHicXT0y8ptH6bXS7KzszUXD5S6OkVFRZomieWWh+Tn5eUpd4SIyz9FRUVO/BECNZII+itQb2fHsVWBbYbypQEq7LPv5wU0eSig1VPWbGDHsVVpJ9flXskt+T2z8f1j7p9n746v8MnB4T7YPvrIpSPD7n2uzHNU1feqlfaeSsrIS7Fhe2anDvlHj6XqKc0rTET2XGQCrJSYmDh//vyvv/5arH7u3LnEVV+ZvnVW/LgytzcjIs6afTrvpqw8xlnx41zrNnSt28jTTfu3bTVT7uIJAGBzH6dPlCTpMZ9JVX/OtfAbpyzLokZNdna2j4+PqEIuzpnjx41TUtfS6uGImTzV+bvmjZpKJuItaampvYKC7FEPR5SscXNzC+rd2/KWS3u72clITWVkZHTt2rW0renwV3z+6tAth3804tQEp9Pda8B9niEOb3V2fsbpC/t7G8Jtu9nkI//aeHSZ8nRh3x3qWM00YotMClSeqofhK29UL5EkaeOBd5NP3SqVPrBteEi7v4s3Drv3uc05yy7dKFJ2pN7sqz2Wv7F9pHhav7ZbTMh/xOOCK2enpz6p7GLYvc99eviflU8AU7OXXZFu9DWMreR2Ku+7vORduYkObwYqYHTXBY7tNmv+j7tyvXhqyiMhLZ4c2OmFqmrXLVbm9epTgcPtOLZKOcOoH2vYo1d11Q/2bo9+zsAA4Fh2DbIYXw8ApRLDhw0GQ3BwH3WF9x49e8TFx6vfpR4L3759B39//5IKITfrk3h7t5333jyvZs0kSdry1RaxTl5eniaslyRpU2Ki2TDdJkwrpFsQEhKckrJFfUEiIeET5TDFAarXycjIOHToe1HaZdGihVwJBgB7ELl5xVKY2alDNOmbJusX25/oH6tkWLNTh5wq/F6M8bScs99Rx029kdmpQ6b3XisuLWguHvC9AKw3NeWRif6x7Zv2NH2HCJ29XLyGdZ5e8HPuhwdmK5fKIpMC29Vvl/dz7rNdY78+ujzj/O6xnaYn5Swd1nn6pkMfHLl0ZG7wl2KotVjzyKUjE/1LZqBZkBFVWkYvTj6BbYau3Dtje96WhX13FFw5e/Hnkroox/MzJUlq3chXueA3u/fnV68XvbF9pDLIPTIp0MvFq2m95vc27i6u/CltMLtxJXAXDcv6abc4L0UmBfo3vv+htiP3535lmrYHthn66eF/ijfWr+1W2imrwr3q3/j+jPO7h9373PnLPyaf+tzLxWt677Vm+yE6+dHQ9s+73+kl+l99eqxf262fd3jDO5styIiqX9vt0o2isZ2m31HHTTxV9qW+Cmt2v6KLzl/+sbPXw6Kp7eq3e77Hx2bbo8T3FThA015q28h/fdZiibweAOyJvB4AzFOHzpph8mIOT/HYQjYdFRWtLomjrv/u6elp+sZ+/fsrC81uVr3QdIUyU3ILK2heUh9vae9Sr+N/k7pAEADAHu7z7F2xrSqxS3Tyo8oweVPqDMtsUmOWu0sT9WJRX+LwT//jKwBUktlYWYTOs3t/futHr5HvwhZ9I5MCP9g++vkeH0uSdOTSEfEzPqaRb0ZS4IcHZounz/f4ODIpcGrKI8oZQFlTuYanbEQRmRSoxOtP+836+fql6ORHY0L+I/YuEmERHyef+vzW1lyaiK0pRWmU80lgm6HqNpS28YZ3lox0yczb8rTfLHUnZJzf/cA9ZobGiyT61R7LxdPXen8mHpgdaV6xXlUn7wM7vSBSdXeXJpp+kCQpJuQ/h85sE2G9JEkf7Z6iFLdRbj8S/aPpfLOtMrtf0ZPipqtvc5PFR1laeypzgAAAh2C+WQAAAMAJvNpj+fTUJ6OTHz2en3k8P/OD7aM1bZ4b/KVI5HccW/XB9tFiTL0Qnfzo3lNJYsSlIqRFSbGaQ2e2ieWze38ushux/eQj/6pMn4gAKDIpcO+ppENnthH9AOXl5eJl4Qfn+HntlEItG9xX+T6+966/mi4svHJGeTzm/nlK6GyZlTcDmd14+6Y9F/bd8bTfrOP5mUonLOy7Y2HfHe2b9oxMCly5d4Z6I2LYeNP63k3rey/su+Pwmf+Kubindl+o2Z29e/Wj3VMikwLbN+055v55di2SE5kUeOV6cUi7v0/vvdb6HdnpawMAsC3G1wMAoF/WVzECUO2JHEo5ShGIq5e41HFVnmrmWlTyNXXQNrDTC+phqu43h8QqT5XhmaZJkKaujjUvidGjw+59ju8pYCUxJn126hBxz4pCxNYf7Z7y4YHZykJ1hZlyEffciHe82mN50/remncv7LtDTOKqXiIe1K/tphRvCWwztG3jbuooXD2bRWlK27h6O2M7TRdXFkXFHuFpv1maRoqgXFkyu/fnc7aNnLsrUnOOskevqvthmN8bGSmPiKf1a7v5N76/nB+ItdrVbzc15RGxsigcZLY9mmO01dcGAGBXzDcLwPEcON9s/pW8GalPMN1o1ZiYFPBOcIpLHTe9tcpWX4Dx40omvlemFFaIzD09Pd3faHLfyQAAIABJREFU37+827Sc169YkVCuMkTFxcVpqan9+ve/WZ2pZCLlTYmJ4qkiJCRYKXZkMHjn5By1/KtCcXGxenYHG2K+WVRM9Z5v1rkcz88UFSG8XLz6eo/ya9HXJs1nvllUnlPMN2tvVk4qC6j9cGH/+qzFkwIW0ysAaji7BlnUwwFQozVy8ZzVe/3EpICa3hH2p8+w3rbi4uN79OwRHNxnaFiYsmFZlrOyskrGhR36XlmiCAkJFguzs7NlWS4uLlbWEem/MDQsTHnL5k2blOVijl+x/ooVCSEhwcpq2dnZpgfn6uqqpPMGg+HmTMIJmnXUMxMoMy5YYKewHkA10LqRr6gIMb33WluF9QBsRYwopzsBANAb8noANV0jF88FfXfGbH+G1N5OJiYFfLL/jQV9d1bvsF5o3qx5cnLK6jVrRFweHRUVFhpqMBi8vdtu37ZdrGNUSUnZInJ5g8FgNBrd3NxWrEiQZbmoqGhxXJyy2VWrVyvv6T9gQHRUlOmuR4x4Jjk5RayTm5vr4+NjuaniosKq1atLW6G4uFiW5fR0bZ1TNdHUcnQQAAAAAAAoHfXrAaBEdI9PxIP3d47PvrC3Xu16j7Z+pm2jclcvgSRJR/Mz1mWXZM2Ghn6TAhbXqHJDPu3aSZKUlZXl4+NTVFQUO2eOGHve5+E+cfHxi+PiNm/a1H/AgKKiIldXM9VCvb3bzpw5UwyEt7CX48ePW26Gp6enhVeVNlgI62VZDgsNtTxwXtw6YLmpAGxIlv8oZTl+3Li4+HjxeNGihePHT7B3T69YkTBz5sycnKMxMW9FRUWXtlpsbEx09MvjIiLUFx3VMjIyoqKmpaRsMa3HBQAAAIC8HgD+hGqMlXdPw841tmSzCMoNBkNwcB91oZgePXuIZK3wUqEkSRs3bmjfvkNYWGhwcB/lvWIwu7+/vxjYnpaa2isoSJKkqGnTxEu5P/7Yf8AAb++2FnJ2y0RSv2jRwoSETzZu3CDWHT58REhIcErKFtFaUTE/IeETEc9JktS+fQd/f3/1OmK1TYmJoqgOgKqnmSpDlmULEblNDB8+QkyYkZeXp75yoBCXEIxGo0jzZVn29m6rKaslzmai7lZp2wEAzRXKSiptU6XNEqRZnpeXN2Xy5NVr1kRNmxYTG1vJxgAAUCbyegAAbEP99566Crw651IemFaHV97u6uqqPBYPxB+H/v7+mj8pNauZfUmtX//+ZperW1va38aaIyJiA+wtLy/Py8trXETE3599Njn5y48++qi0HYqpL/7+7LPiqRjhnpubW1xc7OPjk5DwiTjtiPtmWrduPSQ09F9LlsTFxyvXBRWakD0kJPj48eOak9WDD/b09m5r2oy4+Pjc3FzlaVFRkZvbn8qgifJfyszb4gLn+HHj7HqZwdnt+KIo+dNvrhRdvsen1chXurm5/2b5gBZMzfgh60TJZ/d0rz5PN1K/lBifa7r+gAivvBPyt1/+aHZrAyK8NEt+O93o74NelyRp2Tf/+LXuL5pXx3RbWPINXPDyXQGFmpcSZ5/YuP6L0t5Yu9htZNCtGHTgE4+7NXBLWLZKkqSP9kRWj88RujUuIkJzFpJlOSHhE2WKIHGyWrV6tRgtIcsyqT0AwN7I6wEAAKpCYnzu9i9KykO163rvmBkdSttjzr5fv9951mxSplaBVK4C+xLpm9nU7ONJ6Tt27DT7EsGcTXh5eeXm5opQ29/fPyoqWgz5VGRkZEiStGvXzgkTIhMSPhE5+IoVCdHRL6sv5smyrFwmVO7OWRwX987cuabzRYv1t6al9QoKys7OVt9VI4id5uQcNXuI6mJcpsWytny1xfQtZhdC/Izv3/atJEmzVo/zbGWcE7H9hUdKbgFcsivCbPc8273kLq7OPf/yduKTeSfkGWFxa+ZLbX3vmxbfQ5KkzG1XN39cMl15v9Fl1yBK/++BvJwTLvXqDYgYoXkp//QNSZJefOW58Afe0/zMjum2cMacqbOmzT2451jvgD+dlGoXu21c/8Wyb/4R/sB7Zt9oegboPZETQg0yNCxs9Zo1ixYt7N494NCh7wcOHCROIOIiX4+ePUQxLnU5QZGqDx8+IjoqSik/qFx0XL16jSRJ/1qyRHM50GDwzsk5qj6tLY6Lk2X5Hy+8IG4ZjI2NCQ7uM3z4CHVer9HAvUFN/8AAAHZGXg8AAGBfIkdzqVfv/a9Lwq85EdvFEtPcbdJDCVcuXxaPB0TYN5WzZl9iqGzUxLd+2tlAPWC2aH/DHTt2ipc06xPM2VDWkSNKAi4G0auJgN7f33/8+AmyLN9/f3ezJarUyVRxcbGSdqWlppptqRgXbzQafXx8TO+k8ff3z87OkWXZYPDWjLvXDJYXQZtaUtK/TafCTkr6dxX2qDOZONdfksS9CCWfwrT4Hs92/05cZvPuUsv0QNTnE89Wxs49/7J/27dHM7+TpJIzw6fvJCmnhUMZxxp7NVSuGnq2Mqqv2IkzTPe+Pc1eVvzfV/skSbp30G/SmyVX5gZMbyWWJ84uuXx4z8NXSiqqLVul+aEeGRQbGBjwa91fPtoTOabbwj3/90u3v90uXjJ7TjD1084GURPfWvblK782uiiemg7hh5MaP27c6jVrlLONcguOCNPFg+HDR8iyrFxiFNPdi7NZTGxsQUGBOCPJsqxc5lS/XSkJqD6niauP4mQoTnd5eXnq652mZFmumvlCAAA13G01vQMAAACqxMNhD4ndiGBdo6jgtme7x1+5fLm0wbOKJbsiluyKuJnl3UrlSuZ5LknlJNNU7qczBQMivDTD563flyRJjZrXNs3lJ49+Y9GqGY2amxn5oQ7mJEna839/jK+3Ppgb021hrXwP5WmZjayWjEbj2L+PlX+Xl5dn4SjDQkNFFD58+IisrCxZxWDwVlYTJeOFD/75gdlYytXVddGihWKOCmWhweCt3uaiRQuVsF6W5ZCQYNFgd3d3ZR13d3f1iNeQkGCDwVBUVKTeTlFREdNgWOOlAZ+LGH3C3JFmw3q1zG1Xn+0eL8bmKz/jBWd/kiTpq9VfdwhoMnjCX/dvzXi2e7zYpppY0m90/9LuARK3zpTcPfPlKxvXf1G7uKTkUa18j43rvyjtR1tE+aPf7yqexi54efEHH9a6dntp7RdnAOWfWJh/pqjkbpIvzoinhPXVSctWLStwNOpT4uK4OOWMlL5nj9n1+/XvL84/W9PSxJJdu3aKB72CgoKD+4wfN87Ly6uoqEh5S3Z2tvJYnEuNRiNhPQCgCjC+HgAA2xN3dpudwUx9N3fFlDY9mqkVKxLELeQxMW+JGSDNEtWuS5usUlOCQ8xGq5TXgDWW7Ip4acDnmz/etPnjP9Z+aclY5fGM4V/m5ZwobUBraTK3XV00dbl40TSVe27e0x0Cmvxzyspnu29Tr2D9vkQSd1vz/LuaSyJtF3ncmG4L77nnntu9z4vVfjvd6Lbm+eKxaTBXMiR2qJmqOIIYM6s8FdtXgjkxArcmB3OlzXJhegZQaiuLKa9LOz9YeElt/PgJmkzKdCi92ZbExMaaLetsdn4OlKmo4DZRA8dCGRw18dMtSVLo5Kc0ZbI0b3//6xEimt/xRVHg47emGZj0UMkc457erSwX4xoRPlSSpF8bXQwMDBgZFPvRnsjwR96MXfCyJBWKV0WFK0HccDPwicdTF+T/vqzkgXLzzcAnHleuAQh3BRQqpxpl4b2DfvtoUMnCwxtue+fNf1JBqzqJiooePPgp9S8bmxIT+/W3dIuY0WgUv2iplyjL+w8YoFkuiPOP8kvU+vXrx/1+b1lycoq4Eqn+DW337l0Gg0FpWE7OUeVxTT6PHc3PMDTqqoOGAEB1Rl4PAIDtrVq9evWaNYsXL1JnXrIsx8S8VcmwvlyU6W3FoFrTPy/HjxsXFx9vNBpFmq+ZalJQv2vFioQRI54hrC+XHV8ULX/9U01e9mz3+Lef/bBzz79MnOuvRGy7krbtStqmXkepcqNR4VSuXPvKO/jHjZiiisUvOY0vnb9e0oDP/0hS8k/fEIE+wZzOEZQ7l49mfS9+SC0XrO83ur+I1zVPza6snDFWzj0ulith/ZaV+aJA1qwVj1jup47d2ohofvT7XXd02/nxpHT1dbW27ZurVxaTVShlc4TeE/+oinPzpcfHdFsYGBigXOqz4N5Bv8U2NVOJy+kEtQpbt++twV1edvYDsQmzlxJLm2NfUF+kLHO52YudlifStzClfw23LjtuQd+dNb0XAMDOyOsBALCLrKwsHx8fJa+PjooSg8hEZYl5783zatbsX0uWiLhcrCPi8pkzZzZv1jyod29v77Y5OUc3JSa6ubmJp+okXZZlUX46qHfvMv+efPDBnt7ebU2Xx8XH5+b+MTepqFtd2kY2b9o0YsQz/OFaXp0Db5Vz2bIyXyRlRQW3cnC/3gaz6Zimur0m8a9MKlfmvtQO7jmmfjpjztQJQ2dJkrQ8LeqG9EfFAGVuSYI5wIaUK2qaqjXiOl/eiVvjfMV5QJllWnMfj/LTvWRXhDiTrJl/a/lLS8aqS+usmf+ZKFtf5hGoC2EtWjVjwtBZ6itqHne5KI/FDTdmr7e9+Mpz77z5T3HzzYDprQZMjxQ33Bzccyxh2aqBTzzu1cLzXxteU+7dqZXvsWVlTsKyVYGBAUPGBFeDa3hPdZjy2tdPNMxe1tsQroPmAFaZmBQwq/d6+goA7M3MUDsAqGIfp0+UJOkxn0mebhSxRVWbmBRgv1FCISHBKSlbjEZjcXGxMkmasDUtbdWqVXHxJSmMUohGMwS+tKem9XBkWQ4O7qMZKabIyMgICwvNyTlqtj6PZqHZYfhiI127dq3KXxvs+tFYQ5yabGXLynwRhwmlpe2CJkNXR/CJ8bliOllTpvm+oEnlLO9LzbTc/JhuC1985bmSqSZVS8Q6ibNPlFbAWgyTX/bNn6riaII5/4e8Sgvm3DpfKNeH0N1rwH2eIeV6iz1k52ecvrCfJM4eUrOXXZFu9DWMrfpda3yXl7wrN7Fcb7EVCz+5sMborgv00E87T3+RsP8NRitD//adTv7X/tf4rgKAwq5BFnk9AMcjr4cD2TsUlmVZDLRPS03tFRSkLkGjrGCTvH7RooWW50AzW+tGvXfTtimys7N9fHyq+HeGapbXV9jKucdT1yab1r1Baap9Xm/2MpvpTTaan27Ne62fBsOC6Kio2DlzzO5F/bRkhsZx43r07GGrUlrk9ag8neT1gkjtBxvGcYUPOjQt+eHLNy6T1AOAhl2DLOrhAABgR2mpqT4+PsHBfURYL0nSO3PnxsXHizzL27utMtdZuSQkfGIweOfkHBVvysrKMhi0vyWoVyipWqAK9JXx+EajMToqSgnXoqZNE/mdcmeAqH1f9WE9FE9Pbf30VIbQ4hazYf2iRQsnTIhcsSJBE4i3bNWytDtmKkmW5ahp05TZZdVnjIyMDNMrAYvj4oaGhV26dMnyZUWgZgpo/nhA88fFoX/2/by0E2bKsgNVrKFL06c6TOncpNeckK/oewCoYuT1AADYUa+gIE1u5erqWlp8ZnlqNc3UZ2WOVNUMpS9ty0ripqYurePp6UlYD+jB4sWLNFf4Nm8qKY40fvyE8eMnyLKsOS1ERUW3aNGivJG9mFY6JuYtMd9Gaaa/8orySnJyinLZ719LlkRNm5aRkeHv769+66rVq2VZJq8HLHuqw5SnOkyhkwAAqMlu49MHAAAA9G/ChMgePXuom9l/wID09PSMm8ZFRGgK0YgLe0VFRbIsr1iRYOXxDR8+wmg0irB+xYoEWZazs7M16+Tm5rq5ucm/U298cVxcTGysCOsNBm/TJgEAAACwgPH1AAAAgBOImjZt+7btyiB6WZbDQkOVYeyL4+Li4uNjY2M04+LFPT2yLJ86dcrKYywuLvbz883JOZqbm2t2bL76thsxn3ZWVpbpav/97zYvr1LnVQYAAABgivH1AAAAgBOIiY2Ni48X7RRD2let/lOd66Kioujol80eiNFozNybWeYxyrKckZHh6uqanZ1jNBo9PT0trClkZWUZjUYxhUZeXp6sMnLk35RYf/y4cTExb/E1AwAAACxjfD0AABUXGxtz8sRJkaB5e7d9avBTz0+aZCHhqnoWSleLIbR9Hu6zOC6utHZZs45S8Joy94C9iZHyRqNx+PA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    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![general_pipeline-01.png](attachment:general_pipeline-01.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p><div class=\"alert-success\" style=\"padding: 20px; border-radius: 10px\">\n",
    "<b> PACKAGES </b> </div>\n",
    "\n",
    "\n",
    "- Перед початком роботи треба \"включити\" пакети, які ми будемо використовувати. \n",
    "- Якщо це перший раз використання, спочатку требя їх встановити на компьютер за допомогою команді **% pip install package-name**, як наприклад:\n",
    "\n",
    "<i> % pip install pandas </i>\n",
    "\n",
    "- Після того як пакети встановленні кожен наступни раз пакет можно зразу \"підключити\" за допомогою команди **import package-name**\n",
    "\n",
    "- Для виконання команди треба буде писати назву пакету, тому для зручності ми можемо скоротити назву за допомогою команди **as short_name**, наприклад:\n",
    "\n",
    "<i> import pandas as pd </i>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%pip install pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import packages\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read mock community data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b> Mock Community Data:</b> \n",
    "Це штучно створені дані, що імітують характеристики реальної спільноти. Вони використовуються для тестування та валідації систем, алгоритмів або програмного забезпечення в умовах, що наближаються до реальних. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>ZymoBIOMICS® Gut Microbiome Standard</b> is a mixture of 18 bacterial strains, 2 fungal strains, and 1 archaeal strain in staggered abundances to mimic a true gut microbiome. The standard presents multiple challenges for NGS pipelines, such as tough-to-lyse Gram-positive bacteria (e.g. Roseburia hominis) to test lysis efficiency, genomes with a wide range of GC content to test sequencing coverage bias, low-abundance pathogenic organisms for detection limit assessment and 5 different strains of E. coli to test taxonomic resolution. These challenge points can be used to expose artifacts, errors, and bias in microbiomics or metagenomics workflows. Serving as a defined input, this standard can be used to guide construction and optimization of entire workflows or as a quality control tool for inter-lab studies."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The microbial standard is accurately characterized and contains negligible impurity (< 0.01%). It was constructed by pooling cells from pure cultures of 21 microbial strains. The cells from each pure culture were quantified before pooling. After mixing, the microbial composition was confirmed using NGS-based sequencing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Species</th>\n",
       "      <th>std_abundance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Faecalibacterium prausnitzii</td>\n",
       "      <td>14.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Veillonella rogosae</td>\n",
       "      <td>19.94</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Species  std_abundance\n",
       "0  Faecalibacterium prausnitzii          14.77\n",
       "1           Veillonella rogosae          19.94"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# зчитуємо дані\n",
    "std = pd.read_excel('input/mock_standard.xlsx')\n",
    "# remove space at the end of species names\n",
    "std['Species'] = std['Species'].str.strip()\n",
    "std.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Завдання:</b> \n",
    "Проаналізуйте отриманий датафрейм. \n",
    "- Які стовбці ми маємо, скільки видів бактерій? \n",
    "- чи всі вони унікальні? \n",
    "- яка мінімальна, максимальна та середня відносна відносна чисельність бактерій?\n",
    "- які ще якості буде корисно подивитись?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "  <summary> Підказка </summary>\n",
    "  \n",
    "  std.head(2)\n",
    "  \n",
    "  std.tail(2)\n",
    "  \n",
    "  len(std['Species'])\n",
    "  \n",
    "  len(std['Species'].unique())\n",
    "  \n",
    "  std['std_abundance'].min()\n",
    "  \n",
    "  std['std_abundance'].max()\n",
    "  \n",
    "  std['std_abundance'].mean()\n",
    "\n",
    "  std.isnull().values.any()\n",
    "\n",
    "</details>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bar plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='std_abundance', ylabel='Species'>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Візуалізація даних\n",
    "plt.figure(figsize=(10, 5))\n",
    "sns.barplot(x='std_abundance', y='Species', data=std)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Завдання:</b> \n",
    "- Відсортуйте види за спаданням їх відносної кількості. \n",
    "- Намалюйте новий графік з відносною кількістю видів бактерій. \n",
    "- Для візуалізації використайте ваш улюблений колір.\n",
    "- додайте курсив до назв видів бактерій\n",
    "- Подумайте чи можна ще якось вдосконалити графік?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "  <summary> Підказка </summary>\n",
    "  \n",
    "  std = std.sort_values('std_abundance', ascending=False)\n",
    "  \n",
    "  plt.yticks(fontstyle='italic')  \n",
    "\n",
    "</details>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p><div class=\"alert-success\" style=\"padding: 20px; border-radius: 10px\">\n",
    "<b> KRAKEN </b> </div>\n",
    "\n",
    "Metagenome profiling program \n",
    "https://github.com/DerrickWood/kraken"
   ]
  },
  {
   "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>name</th>\n",
       "      <th>taxonomy_id</th>\n",
       "      <th>taxonomy_lvl</th>\n",
       "      <th>kraken_assigned_reads</th>\n",
       "      <th>added_reads</th>\n",
       "      <th>new_est_reads</th>\n",
       "      <th>fraction_total_reads</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Faecalibacterium prausnitzii_E</td>\n",
       "      <td>50115</td>\n",
       "      <td>S</td>\n",
       "      <td>2732871</td>\n",
       "      <td>218706</td>\n",
       "      <td>2951577</td>\n",
       "      <td>0.16067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Faecalibacterium prausnitzii_D</td>\n",
       "      <td>50114</td>\n",
       "      <td>S</td>\n",
       "      <td>48882</td>\n",
       "      <td>7395</td>\n",
       "      <td>56277</td>\n",
       "      <td>0.00306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Faecalibacterium sp934513205</td>\n",
       "      <td>50142</td>\n",
       "      <td>S</td>\n",
       "      <td>42512</td>\n",
       "      <td>2357</td>\n",
       "      <td>44869</td>\n",
       "      <td>0.00244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Faecalibacterium hattorii</td>\n",
       "      <td>50108</td>\n",
       "      <td>S</td>\n",
       "      <td>32761</td>\n",
       "      <td>2974</td>\n",
       "      <td>35735</td>\n",
       "      <td>0.00195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Faecalibacterium prausnitzii_I</td>\n",
       "      <td>50117</td>\n",
       "      <td>S</td>\n",
       "      <td>30704</td>\n",
       "      <td>1834</td>\n",
       "      <td>32538</td>\n",
       "      <td>0.00177</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             name  taxonomy_id taxonomy_lvl  \\\n",
       "0  Faecalibacterium prausnitzii_E        50115            S   \n",
       "1  Faecalibacterium prausnitzii_D        50114            S   \n",
       "2    Faecalibacterium sp934513205        50142            S   \n",
       "3       Faecalibacterium hattorii        50108            S   \n",
       "4  Faecalibacterium prausnitzii_I        50117            S   \n",
       "\n",
       "   kraken_assigned_reads  added_reads  new_est_reads  fraction_total_reads  \n",
       "0                2732871       218706        2951577               0.16067  \n",
       "1                  48882         7395          56277               0.00306  \n",
       "2                  42512         2357          44869               0.00244  \n",
       "3                  32761         2974          35735               0.00195  \n",
       "4                  30704         1834          32538               0.00177  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show original file\n",
    "# Karaken + Braken results\n",
    "bra = pd.read_csv('input/mock.bracken', sep='\\t')\n",
    "bra.head(5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Species</th>\n",
       "      <th>taxonomy_id</th>\n",
       "      <th>taxonomy_lvl</th>\n",
       "      <th>kraken_assigned_reads</th>\n",
       "      <th>added_reads</th>\n",
       "      <th>new_est_reads</th>\n",
       "      <th>fraction_total_reads</th>\n",
       "      <th>std_abundance</th>\n",
       "      <th>status</th>\n",
       "      <th>abundance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3049</th>\n",
       "      <td>Clostridium perfringens</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00009</td>\n",
       "      <td>not detected</td>\n",
       "      <td>0.00009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2655</th>\n",
       "      <td>Enterococcus faecalis</td>\n",
       "      <td>48771.0</td>\n",
       "      <td>S</td>\n",
       "      <td>139.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>0.00110</td>\n",
       "      <td>detected</td>\n",
       "      <td>0.00110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1892</th>\n",
       "      <td>Salmonella enterica</td>\n",
       "      <td>94937.0</td>\n",
       "      <td>S</td>\n",
       "      <td>3524.0</td>\n",
       "      <td>276.0</td>\n",
       "      <td>3800.0</td>\n",
       "      <td>0.00021</td>\n",
       "      <td>0.00700</td>\n",
       "      <td>detected</td>\n",
       "      <td>0.00700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3048</th>\n",
       "      <td>Methanobrevibacter smithii</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.17000</td>\n",
       "      <td>not detected</td>\n",
       "      <td>0.17000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3050</th>\n",
       "      <td>Candida albicans</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.31000</td>\n",
       "      <td>not detected</td>\n",
       "      <td>0.31000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Species  taxonomy_id taxonomy_lvl  \\\n",
       "3049     Clostridium perfringens          NaN          NaN   \n",
       "2655       Enterococcus faecalis      48771.0            S   \n",
       "1892         Salmonella enterica      94937.0            S   \n",
       "3048  Methanobrevibacter smithii          NaN          NaN   \n",
       "3050            Candida albicans          NaN          NaN   \n",
       "\n",
       "      kraken_assigned_reads  added_reads  new_est_reads  fraction_total_reads  \\\n",
       "3049                    NaN          NaN            NaN                   NaN   \n",
       "2655                  139.0          5.0          144.0               0.00001   \n",
       "1892                 3524.0        276.0         3800.0               0.00021   \n",
       "3048                    NaN          NaN            NaN                   NaN   \n",
       "3050                    NaN          NaN            NaN                   NaN   \n",
       "\n",
       "      std_abundance        status  abundance  \n",
       "3049        0.00009  not detected    0.00009  \n",
       "2655        0.00110      detected    0.00110  \n",
       "1892        0.00700      detected    0.00700  \n",
       "3048        0.17000  not detected    0.17000  \n",
       "3050        0.31000  not detected    0.31000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Karaken + Braken results\n",
    "bra = pd.read_csv('input/mock.bracken', sep='\\t')\n",
    "# change column name 'name' to 'Species'\n",
    "bra = bra.rename(columns={'name':'Species'})\n",
    "\n",
    "mrg_bra = pd.merge(bra, std, on='Species', how='outer').sort_values(by='std_abundance')\n",
    "\n",
    "# if metaplane_abundance & std_abundance not null add value present in new column 'status'\n",
    "mrg_bra['status'] = mrg_bra.apply(lambda x: 'detected' if pd.notnull(x['fraction_total_reads']) and pd.notnull(x['std_abundance']) else '', axis=1)\n",
    "mrg_bra['status'] = mrg_bra.apply(lambda x: 'false positive' if pd.notnull(x['fraction_total_reads']) and pd.isnull(x['std_abundance']) else x['status'], axis=1)\n",
    "mrg_bra['status'] = mrg_bra.apply(lambda x: 'not detected' if pd.isnull(x['fraction_total_reads']) and pd.notnull(x['std_abundance']) else x['status'], axis=1)\n",
    "\n",
    "# add new column abundane. if metaplane_abundance & std_abundance not null fill it with std_abundance value\n",
    "mrg_bra['abundance'] = mrg_bra.apply(lambda x: x['std_abundance'] if pd.notnull(x['std_abundance']) else x['fraction_total_reads'], axis=1)\n",
    "\n",
    "mrg_bra.to_excel('results/mock_braken.xlsx', index=False)\n",
    "mrg_bra.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "    <summary> Пояснення. lambda функція </summary>\n",
    "  \n",
    "    Метод apply:\n",
    "\n",
    "    Метод apply використовується для застосування функції вздовж осі DataFrame.\n",
    "    Аргумент axis=1 означає, що функція застосовується до кожного рядка. Якщо б використовувався axis=0, функція застосовувалась би до кожного стовпця.\n",
    "    \n",
    "    Lambda Функція:\n",
    "\n",
    "    lambda функція - це анонімна функція, визначена за допомогою ключового слова lambda.\n",
    "    У цьому контексті вона використовується для створення простої функції, що приймає рядок (x) як вхідний параметр.\n",
    "    \n",
    "    Логіка Функції:\n",
    "\n",
    "    pd.notnull(x['fraction_total_reads']): Це перевіряє, чи значення у стовпці fraction_total_reads поточного рядка (x) не є null.\n",
    "    pd.notnull(x['std_abundance']): Це перевіряє, чи значення у стовпці std_abundance поточного рядка (x) не є null.\n",
    "    якщо ... і ... інакше ...: Це умовний (тернарний) оператор, що повертає 'виявлено', якщо обидві умови True, інакше повертає порожній рядок ''.\n",
    "    \n",
    "    Повернуте Значення:\n",
    "\n",
    "    Для кожного рядка у DataFrame mrg_bra, метод apply застосовує lambda функцію. Якщо fraction_total_reads і std_abundance не є null, повертає 'виявлено'; інакше повертає порожній рядок.\n",
    "    \n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Завдання:</b> \n",
    "- Проаналізуйте результат. Що ми можемо сказати про программу Kraken? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "  <summary> Підказка </summary>\n",
    "  \n",
    "  - Щоб зробити висновок перевірте скільки видів бактерій, які присутні в зразку були коректно знайдені програмою. \n",
    "  - Чи є види, які не були знайдені (false negative)? \n",
    "  - Чи є види які були знайдені хоча вони не присутні у зразку (false positives)?\n",
    "\n",
    "</details>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p><div class=\"alert-success\" style=\"padding: 20px; border-radius: 10px\">\n",
    "<b> MetaPhlAn </b> </div>\n",
    "\n",
    "Metagenome profiling program \n",
    "https://github.com/biobakery/MetaPhlAn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>clade_name</th>\n",
       "      <th>NCBI_tax_id</th>\n",
       "      <th>metaplane_abundance</th>\n",
       "      <th>additional_species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>k__Bacteria</td>\n",
       "      <td>2</td>\n",
       "      <td>99.70188</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>k__Archaea</td>\n",
       "      <td>2157</td>\n",
       "      <td>0.15262</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>k__Eukaryota</td>\n",
       "      <td>2759</td>\n",
       "      <td>0.14549</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>k__Bacteria|p__Bacteroidetes</td>\n",
       "      <td>2|976</td>\n",
       "      <td>32.51553</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>k__Bacteria|p__Firmicutes</td>\n",
       "      <td>2|1239</td>\n",
       "      <td>32.34157</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     clade_name NCBI_tax_id  metaplane_abundance  \\\n",
       "0                   k__Bacteria           2             99.70188   \n",
       "1                    k__Archaea        2157              0.15262   \n",
       "2                  k__Eukaryota        2759              0.14549   \n",
       "3  k__Bacteria|p__Bacteroidetes       2|976             32.51553   \n",
       "4     k__Bacteria|p__Firmicutes      2|1239             32.34157   \n",
       "\n",
       "  additional_species  \n",
       "0                NaN  \n",
       "1                NaN  \n",
       "2                NaN  \n",
       "3                NaN  \n",
       "4                NaN  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read data. Metaplan\n",
    "tax = pd.read_csv('input/mock_Metaplan.txt', sep='\\t', names=[\"clade_name\", \"NCBI_tax_id\",\n",
    "                   \"metaplane_abundance\", \"additional_species\"], skiprows=4)\n",
    "\n",
    "tax.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/fr/j_4kmkcj6zs6nglntg64jfgr0000gn/T/ipykernel_62925/2695482579.py:11: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  data['Species'] = data['Species'].str.replace('_', ' ')\n",
      "/var/folders/fr/j_4kmkcj6zs6nglntg64jfgr0000gn/T/ipykernel_62925/2695482579.py:13: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  data['Species'] = data['Species'].str.rstrip()\n"
     ]
    },
    {
     "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>Species</th>\n",
       "      <th>metaplane_abundance</th>\n",
       "      <th>std_abundance</th>\n",
       "      <th>status</th>\n",
       "      <th>abundance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bacteroides fragilis</td>\n",
       "      <td>20.46364</td>\n",
       "      <td>8.33</td>\n",
       "      <td>detected</td>\n",
       "      <td>8.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Escherichia coli</td>\n",
       "      <td>18.90745</td>\n",
       "      <td>8.71</td>\n",
       "      <td>detected</td>\n",
       "      <td>8.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Species  metaplane_abundance  std_abundance    status  \\\n",
       "0  Bacteroides fragilis             20.46364           8.33  detected   \n",
       "1      Escherichia coli             18.90745           8.71  detected   \n",
       "\n",
       "   abundance  \n",
       "0       8.33  \n",
       "1       8.71  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read data and compare with standard. Metaplan\n",
    "tax = pd.read_csv('input/mock_Metaplan.txt', sep='\\t', names=[\"clade_name\", \"NCBI_tax_id\",\n",
    "                   \"metaplane_abundance\", \"additional_species\"], skiprows=4)\n",
    "# select only species information\n",
    "taxU = tax[tax['clade_name'].str.contains(\"s__\")].copy()  \n",
    "newR = taxU['clade_name'].str.split(pat='s__', expand=True)\n",
    "taxU.loc[:, 'Species'] = newR[1].values  \n",
    "\n",
    "data = taxU[['Species', 'metaplane_abundance']]\n",
    "# change '_' to ' ' in species names\n",
    "data['Species'] = data['Species'].str.replace('_', ' ')\n",
    "# remove space at the end of species names\n",
    "data['Species'] = data['Species'].str.rstrip()\n",
    "\n",
    "# merge with standard data\n",
    "mrg_met = pd.merge(data, std, on='Species', how='outer')\n",
    "\n",
    "# if metaplane_abundance & std_abundance not null add value present in new column 'status'\n",
    "mrg_met['status'] = mrg_met.apply(lambda x: 'detected' if pd.notnull(x['metaplane_abundance']) and pd.notnull(x['std_abundance']) else '', axis=1)\n",
    "mrg_met['status'] = mrg_met.apply(lambda x: 'false positive' if pd.notnull(x['metaplane_abundance']) and pd.isnull(x['std_abundance']) else x['status'], axis=1)\n",
    "mrg_met['status'] = mrg_met.apply(lambda x: 'not detected' if pd.isnull(x['metaplane_abundance']) and pd.notnull(x['std_abundance']) else x['status'], axis=1)\n",
    "\n",
    "# add new column abundane. if metaplane_abundance & std_abundance not null fill it with std_abundance value\n",
    "mrg_met['abundance'] = mrg_met.apply(lambda x: x['std_abundance'] if pd.notnull(x['std_abundance']) else x['metaplane_abundance'], axis=1)\n",
    "\n",
    "# save result table to file\n",
    "mrg_met.to_excel('results/mock_metaphlan.xlsx', index=False)\n",
    "mrg_met.head(2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Завдання:</b> \n",
    "- Проаналізуйте результат. Що ми можемо сказати про программу MetaPhlAn? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p><div class=\"alert-success\" style=\"padding: 20px; border-radius: 10px\">\n",
    "<b> mOTUs </b> </div>\n",
    "\n",
    "Metagenome profiling program \n",
    "https://github.com/motu-tool/mOTUs\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>consensus_taxonomy</th>\n",
       "      <th>unnamed sample</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Leptospira alexanderi [ref_mOTU_v3_00001]</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Leptospira weilii [ref_mOTU_v3_00002]</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          consensus_taxonomy  unnamed sample\n",
       "0  Leptospira alexanderi [ref_mOTU_v3_00001]             0.0\n",
       "1      Leptospira weilii [ref_mOTU_v3_00002]             0.0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mOTUs\n",
    "motus = pd.read_csv('input/mock.motus', sep='\\t')\n",
    "motus.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Species</th>\n",
       "      <th>motus_abundance</th>\n",
       "      <th>std_abundance</th>\n",
       "      <th>status</th>\n",
       "      <th>abundance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Clostridium perfringens</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00009</td>\n",
       "      <td>not detected</td>\n",
       "      <td>0.00009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Enterococcus faecalis</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00110</td>\n",
       "      <td>not detected</td>\n",
       "      <td>0.00110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Salmonella enterica</td>\n",
       "      <td>0.000466</td>\n",
       "      <td>0.00700</td>\n",
       "      <td>detected</td>\n",
       "      <td>0.00700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Species  motus_abundance  std_abundance        status  \\\n",
       "18  Clostridium perfringens              NaN        0.00009  not detected   \n",
       "17    Enterococcus faecalis              NaN        0.00110  not detected   \n",
       "1       Salmonella enterica         0.000466        0.00700      detected   \n",
       "\n",
       "    abundance  \n",
       "18    0.00009  \n",
       "17    0.00110  \n",
       "1     0.00700  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mOTUs\n",
    "motus = pd.read_csv('input/mock.motus', sep='\\t')\n",
    "motus = motus[motus['unnamed sample'] > 0]\n",
    "# slpit column by [\n",
    "motus['Species'] = motus['consensus_taxonomy'].str.split('[').str[0]\n",
    "motus = motus[['Species', 'unnamed sample']]\n",
    "# change column name\n",
    "motus = motus.rename(columns={'unnamed sample':'motus_abundance'})\n",
    "# drop space at the end of Species name\n",
    "motus['Species'] = motus['Species'].str.rstrip()\n",
    "\n",
    "mrg_motus = pd.merge(motus, std, on='Species', how='outer').sort_values(by='std_abundance')\n",
    "\n",
    "# if metaplane_abundance & std_abundance not null add value present in new column 'status'\n",
    "mrg_motus['status'] = mrg_motus.apply(lambda x: 'detected' if pd.notnull(x['motus_abundance']) and pd.notnull(x['std_abundance']) else '', axis=1)\n",
    "mrg_motus['status'] = mrg_motus.apply(lambda x: 'false positive' if pd.notnull(x['motus_abundance']) and pd.isnull(x['std_abundance']) else x['status'], axis=1)\n",
    "mrg_motus['status'] = mrg_motus.apply(lambda x: 'not detected' if pd.isnull(x['motus_abundance']) and pd.notnull(x['std_abundance']) else x['status'], axis=1)\n",
    "\n",
    "# add new column abundane. if metaplane_abundance & std_abundance not null fill it with std_abundance value\n",
    "mrg_motus['abundance'] = mrg_motus.apply(lambda x: x['std_abundance'] if pd.notnull(x['std_abundance']) else x['motus_abundance'], axis=1)\n",
    "\n",
    "mrg_motus.to_excel('results/mock_motus.xlsx', index=False)\n",
    "mrg_motus.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Завдання:</b> \n",
    "- Проаналізуйте результат. Що ми можемо сказати про программу mOTUs? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p><div class=\"alert-success\" style=\"padding: 20px; border-radius: 10px\">\n",
    "<b> Visualisation and Comparison the results </b> </div>\n",
    "\n",
    "Візуалізація коректно виявлених видів, false negative & false positives для оцінки роботи програм."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Swarmplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/fr/j_4kmkcj6zs6nglntg64jfgr0000gn/T/ipykernel_62925/3645169111.py:5: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.swarmplot(data=mrg_met, y='abundance', x='status', palette=['#70bb03','#f26b58','grey'])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 25.722222222222214, '')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fig size\n",
    "plt.figure(figsize=(5, 5))\n",
    "\n",
    "plt.yscale(\"log\")\n",
    "sns.swarmplot(data=mrg_met, y='abundance', x='status', palette=['#70bb03','#f26b58','grey'])\n",
    "plt.title('Metaphlan')\n",
    "plt.ylabel('Relative abundance')\n",
    "plt.xlabel('')\n",
    "\n",
    "#plt.savefig('results/Metaphlan.png', dpi=300, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/fr/j_4kmkcj6zs6nglntg64jfgr0000gn/T/ipykernel_36206/4135553602.py:11: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.swarmplot(data=mrg_met, y='abundance', x='status', palette=['green','red','grey'], ax=axes[0])\n",
      "/var/folders/fr/j_4kmkcj6zs6nglntg64jfgr0000gn/T/ipykernel_36206/4135553602.py:18: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.swarmplot(data=mrg_bra, y='abundance', x='status', palette=['green','red','grey'], ax=axes[1])\n",
      "/Users/ketpantuh/Library/Python/3.8/lib/python/site-packages/seaborn/categorical.py:3399: UserWarning: 7.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ketpantuh/Library/Python/3.8/lib/python/site-packages/seaborn/categorical.py:3399: UserWarning: 98.9% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/var/folders/fr/j_4kmkcj6zs6nglntg64jfgr0000gn/T/ipykernel_36206/4135553602.py:25: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.swarmplot(data=mrg_motus, y='abundance', x='status', palette=['green','red','grey'], ax=axes[2])\n",
      "/Users/ketpantuh/Library/Python/3.8/lib/python/site-packages/seaborn/categorical.py:3399: UserWarning: 91.3% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ketpantuh/Library/Python/3.8/lib/python/site-packages/seaborn/categorical.py:3399: UserWarning: 89.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Увага! Цей код потребує трошки часу на виконання! \n",
    "\n",
    "# Create a figure with 3 subplots (1 row, 3 columns)\n",
    "fig, axes = plt.subplots(1, 3, figsize=(15, 5), sharey=True)\n",
    "\n",
    "# First subplot\n",
    "axes[0].set_yscale(\"log\")\n",
    "sns.swarmplot(data=mrg_met, y='abundance', x='status', palette=['#70bb03','#f26b58','grey'], ax=axes[0])\n",
    "axes[0].set_title('Metaphlan')\n",
    "axes[0].set_ylabel('Relative abundance')\n",
    "axes[0].set_xlabel('')\n",
    "\n",
    "# Second subplot\n",
    "axes[1].set_yscale(\"log\")\n",
    "sns.swarmplot(data=mrg_bra, y='abundance', x='status', palette=['green','red','grey'], ax=axes[1])\n",
    "axes[1].set_title('Kraken with GTDB')\n",
    "axes[1].set_ylabel('')\n",
    "axes[1].set_xlabel('')\n",
    "\n",
    "# Third subplot\n",
    "axes[2].set_yscale(\"log\")\n",
    "sns.swarmplot(data=mrg_motus, y='abundance', x='status', palette=['green','red','grey'], ax=axes[2])\n",
    "axes[2].set_title('mOTUs')\n",
    "axes[2].set_ylabel('')\n",
    "axes[2].set_xlabel('')\n",
    "\n",
    "# Adjust layout\n",
    "plt.tight_layout()\n",
    "\n",
    "# Save the figure\n",
    "#plt.savefig('results/mOTUs.png', dpi=300, bbox_inches='tight')\n",
    "#plt.savefig('results/mOTUs.svg', bbox_inches='tight')\n",
    "\n",
    "# Show plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Завдання:</b> \n",
    "- Проаналізуйте результат. Який висновок ми можемо зробити щодо перформанса кожної програми?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scatterplot\n",
    "Проаналізувати корекність виявлення відносної кількості бактерій."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Species</th>\n",
       "      <th>metaplane_abundance</th>\n",
       "      <th>std_abundance</th>\n",
       "      <th>status</th>\n",
       "      <th>abundance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bacteroides fragilis</td>\n",
       "      <td>20.46364</td>\n",
       "      <td>8.33</td>\n",
       "      <td>detected</td>\n",
       "      <td>8.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Escherichia coli</td>\n",
       "      <td>18.90745</td>\n",
       "      <td>8.71</td>\n",
       "      <td>detected</td>\n",
       "      <td>8.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Species  metaplane_abundance  std_abundance    status  \\\n",
       "0  Bacteroides fragilis             20.46364           8.33  detected   \n",
       "1      Escherichia coli             18.90745           8.71  detected   \n",
       "\n",
       "   abundance  \n",
       "0       8.33  \n",
       "1       8.71  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mrg_met.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.0, 20.0)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5, 5))\n",
    "sns.scatterplot(data=mrg_met, x='metaplane_abundance', y='std_abundance', color='#00b1c4')\n",
    "plt.xlabel('Metaphlan, relative abundance (%)')\n",
    "plt.ylabel('Standard, abundance (%)')\n",
    "plt.title('Metaphlan vs Standard')\n",
    "plt.xlim(-1, 20)\n",
    "plt.ylim(-1, 20)\n",
    "\n",
    "#plt.savefig('results/metaphlan_vs_standard.png', dpi=300, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nan"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# calculate r2 value\n",
    "from scipy.stats import linregress\n",
    "\n",
    "# Extract the columns from the DataFrame\n",
    "x = mrg_met['metaplane_abundance']\n",
    "y = mrg_met['std_abundance']\n",
    "\n",
    "# Perform linear regression\n",
    "slope, intercept, r_value, p_value, std_err = linregress(x, y)\n",
    "\n",
    "# Calculate the R-squared value\n",
    "r_squared = r_value**2\n",
    "r_squared\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Чому не працює?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Species                 object\n",
       "metaplane_abundance    float64\n",
       "std_abundance          float64\n",
       "status                  object\n",
       "abundance              float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check column datatype\n",
    "mrg_met.dtypes"
   ]
  },
  {
   "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>Species</th>\n",
       "      <th>metaplane_abundance</th>\n",
       "      <th>std_abundance</th>\n",
       "      <th>status</th>\n",
       "      <th>abundance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bacteroides fragilis</td>\n",
       "      <td>20.46364</td>\n",
       "      <td>8.33000</td>\n",
       "      <td>detected</td>\n",
       "      <td>8.33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Escherichia coli</td>\n",
       "      <td>18.90745</td>\n",
       "      <td>8.71000</td>\n",
       "      <td>detected</td>\n",
       "      <td>8.71000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Faecalibacterium prausnitzii</td>\n",
       "      <td>12.54292</td>\n",
       "      <td>14.77000</td>\n",
       "      <td>detected</td>\n",
       "      <td>14.77000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Prevotella corporis</td>\n",
       "      <td>12.05189</td>\n",
       "      <td>6.26000</td>\n",
       "      <td>detected</td>\n",
       "      <td>6.26000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Roseburia hominis</td>\n",
       "      <td>8.67727</td>\n",
       "      <td>12.43000</td>\n",
       "      <td>detected</td>\n",
       "      <td>12.43000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Fusobacterium nucleatum</td>\n",
       "      <td>8.53479</td>\n",
       "      <td>7.53000</td>\n",
       "      <td>detected</td>\n",
       "      <td>7.53000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Bifidobacterium adolescentis</td>\n",
       "      <td>4.59147</td>\n",
       "      <td>8.83000</td>\n",
       "      <td>detected</td>\n",
       "      <td>8.83000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Clostridioides difficile</td>\n",
       "      <td>3.60509</td>\n",
       "      <td>1.10000</td>\n",
       "      <td>detected</td>\n",
       "      <td>1.10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Veillonella dispar</td>\n",
       "      <td>3.34746</td>\n",
       "      <td>NaN</td>\n",
       "      <td>false positive</td>\n",
       "      <td>3.34746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Lactobacillus fermentum</td>\n",
       "      <td>2.88391</td>\n",
       "      <td>9.68000</td>\n",
       "      <td>detected</td>\n",
       "      <td>9.68000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Akkermansia muciniphila</td>\n",
       "      <td>2.80919</td>\n",
       "      <td>1.62000</td>\n",
       "      <td>detected</td>\n",
       "      <td>1.62000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Veillonella infantium</td>\n",
       "      <td>1.28491</td>\n",
       "      <td>NaN</td>\n",
       "      <td>false positive</td>\n",
       "      <td>1.28491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Methanobrevibacter smithii</td>\n",
       "      <td>0.15262</td>\n",
       "      <td>0.17000</td>\n",
       "      <td>detected</td>\n",
       "      <td>0.17000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Saccharomyces cerevisiae</td>\n",
       "      <td>0.07433</td>\n",
       "      <td>0.32000</td>\n",
       "      <td>detected</td>\n",
       "      <td>0.32000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Candida albicans</td>\n",
       "      <td>0.07116</td>\n",
       "      <td>0.31000</td>\n",
       "      <td>detected</td>\n",
       "      <td>0.31000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Salmonella enterica</td>\n",
       "      <td>0.00187</td>\n",
       "      <td>0.00700</td>\n",
       "      <td>detected</td>\n",
       "      <td>0.00700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Veillonella rogosae</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.94000</td>\n",
       "      <td>not detected</td>\n",
       "      <td>19.94000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Enterococcus faecalis</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00110</td>\n",
       "      <td>not detected</td>\n",
       "      <td>0.00110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Clostridium perfringens</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00009</td>\n",
       "      <td>not detected</td>\n",
       "      <td>0.00009</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Species  metaplane_abundance  std_abundance  \\\n",
       "0           Bacteroides fragilis             20.46364        8.33000   \n",
       "1               Escherichia coli             18.90745        8.71000   \n",
       "2   Faecalibacterium prausnitzii             12.54292       14.77000   \n",
       "3            Prevotella corporis             12.05189        6.26000   \n",
       "4              Roseburia hominis              8.67727       12.43000   \n",
       "5        Fusobacterium nucleatum              8.53479        7.53000   \n",
       "6   Bifidobacterium adolescentis              4.59147        8.83000   \n",
       "7       Clostridioides difficile              3.60509        1.10000   \n",
       "8             Veillonella dispar              3.34746            NaN   \n",
       "9        Lactobacillus fermentum              2.88391        9.68000   \n",
       "10       Akkermansia muciniphila              2.80919        1.62000   \n",
       "11         Veillonella infantium              1.28491            NaN   \n",
       "12    Methanobrevibacter smithii              0.15262        0.17000   \n",
       "13      Saccharomyces cerevisiae              0.07433        0.32000   \n",
       "14              Candida albicans              0.07116        0.31000   \n",
       "15           Salmonella enterica              0.00187        0.00700   \n",
       "16           Veillonella rogosae                  NaN       19.94000   \n",
       "17         Enterococcus faecalis                  NaN        0.00110   \n",
       "18       Clostridium perfringens                  NaN        0.00009   \n",
       "\n",
       "            status  abundance  \n",
       "0         detected    8.33000  \n",
       "1         detected    8.71000  \n",
       "2         detected   14.77000  \n",
       "3         detected    6.26000  \n",
       "4         detected   12.43000  \n",
       "5         detected    7.53000  \n",
       "6         detected    8.83000  \n",
       "7         detected    1.10000  \n",
       "8   false positive    3.34746  \n",
       "9         detected    9.68000  \n",
       "10        detected    1.62000  \n",
       "11  false positive    1.28491  \n",
       "12        detected    0.17000  \n",
       "13        detected    0.32000  \n",
       "14        detected    0.31000  \n",
       "15        detected    0.00700  \n",
       "16    not detected   19.94000  \n",
       "17    not detected    0.00110  \n",
       "18    not detected    0.00009  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# visual check df\n",
    "mrg_met"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>Species</th>\n",
       "      <th>metaplane_abundance</th>\n",
       "      <th>std_abundance</th>\n",
       "      <th>status</th>\n",
       "      <th>abundance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bacteroides fragilis</td>\n",
       "      <td>20.46364</td>\n",
       "      <td>8.330</td>\n",
       "      <td>detected</td>\n",
       "      <td>8.330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Escherichia coli</td>\n",
       "      <td>18.90745</td>\n",
       "      <td>8.710</td>\n",
       "      <td>detected</td>\n",
       "      <td>8.710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Faecalibacterium prausnitzii</td>\n",
       "      <td>12.54292</td>\n",
       "      <td>14.770</td>\n",
       "      <td>detected</td>\n",
       "      <td>14.770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Prevotella corporis</td>\n",
       "      <td>12.05189</td>\n",
       "      <td>6.260</td>\n",
       "      <td>detected</td>\n",
       "      <td>6.260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Roseburia hominis</td>\n",
       "      <td>8.67727</td>\n",
       "      <td>12.430</td>\n",
       "      <td>detected</td>\n",
       "      <td>12.430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Fusobacterium nucleatum</td>\n",
       "      <td>8.53479</td>\n",
       "      <td>7.530</td>\n",
       "      <td>detected</td>\n",
       "      <td>7.530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Bifidobacterium adolescentis</td>\n",
       "      <td>4.59147</td>\n",
       "      <td>8.830</td>\n",
       "      <td>detected</td>\n",
       "      <td>8.830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Clostridioides difficile</td>\n",
       "      <td>3.60509</td>\n",
       "      <td>1.100</td>\n",
       "      <td>detected</td>\n",
       "      <td>1.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Lactobacillus fermentum</td>\n",
       "      <td>2.88391</td>\n",
       "      <td>9.680</td>\n",
       "      <td>detected</td>\n",
       "      <td>9.680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Akkermansia muciniphila</td>\n",
       "      <td>2.80919</td>\n",
       "      <td>1.620</td>\n",
       "      <td>detected</td>\n",
       "      <td>1.620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Methanobrevibacter smithii</td>\n",
       "      <td>0.15262</td>\n",
       "      <td>0.170</td>\n",
       "      <td>detected</td>\n",
       "      <td>0.170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Saccharomyces cerevisiae</td>\n",
       "      <td>0.07433</td>\n",
       "      <td>0.320</td>\n",
       "      <td>detected</td>\n",
       "      <td>0.320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Candida albicans</td>\n",
       "      <td>0.07116</td>\n",
       "      <td>0.310</td>\n",
       "      <td>detected</td>\n",
       "      <td>0.310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Salmonella enterica</td>\n",
       "      <td>0.00187</td>\n",
       "      <td>0.007</td>\n",
       "      <td>detected</td>\n",
       "      <td>0.007</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Species  metaplane_abundance  std_abundance  \\\n",
       "0           Bacteroides fragilis             20.46364          8.330   \n",
       "1               Escherichia coli             18.90745          8.710   \n",
       "2   Faecalibacterium prausnitzii             12.54292         14.770   \n",
       "3            Prevotella corporis             12.05189          6.260   \n",
       "4              Roseburia hominis              8.67727         12.430   \n",
       "5        Fusobacterium nucleatum              8.53479          7.530   \n",
       "6   Bifidobacterium adolescentis              4.59147          8.830   \n",
       "7       Clostridioides difficile              3.60509          1.100   \n",
       "9        Lactobacillus fermentum              2.88391          9.680   \n",
       "10       Akkermansia muciniphila              2.80919          1.620   \n",
       "12    Methanobrevibacter smithii              0.15262          0.170   \n",
       "13      Saccharomyces cerevisiae              0.07433          0.320   \n",
       "14              Candida albicans              0.07116          0.310   \n",
       "15           Salmonella enterica              0.00187          0.007   \n",
       "\n",
       "      status  abundance  \n",
       "0   detected      8.330  \n",
       "1   detected      8.710  \n",
       "2   detected     14.770  \n",
       "3   detected      6.260  \n",
       "4   detected     12.430  \n",
       "5   detected      7.530  \n",
       "6   detected      8.830  \n",
       "7   detected      1.100  \n",
       "9   detected      9.680  \n",
       "10  detected      1.620  \n",
       "12  detected      0.170  \n",
       "13  detected      0.320  \n",
       "14  detected      0.310  \n",
       "15  detected      0.007  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# drop NA raws\n",
    "mrg_met = mrg_met.dropna(subset=['metaplane_abundance', 'std_abundance'])\n",
    "mrg_met"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.431271042079431"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# calculate r2 value\n",
    "from scipy.stats import linregress\n",
    "\n",
    "# Extract the columns from the DataFrame\n",
    "x = mrg_met['metaplane_abundance']\n",
    "y = mrg_met['std_abundance']\n",
    "\n",
    "# Perform linear regression\n",
    "slope, intercept, r_value, p_value, std_err = linregress(x, y)\n",
    "\n",
    "# Calculate the R-squared value\n",
    "r_squared = r_value**2\n",
    "r_squared"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Завдання:</b> \n",
    "- Порахуйте R2 для інших програм. Зробіть висновки."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Завдання:</b> \n",
    "- Які загальні висновки ми можемо зробити?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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