notebooks/11-sequence-counts.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from __future__ import division\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from biom import load_table\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download the open reference OTU table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/yovazquezbaeza/.bashrc: line 34: module: command not found\n",
      "discarding /home/yovazquezbaeza/miniconda/bin from PATH\n",
      "prepending /home/yovazquezbaeza/miniconda/envs/qiime/bin to PATH\n",
      "otu_table_mc2_w_tax.biom                      100% 9160KB   2.2MB/s   00:04    \n"
     ]
    }
   ],
   "source": [
    "!scp barnacle:/home/yovazquezbaeza/research/suchodolski-dogs/open-ref-otus/otu_table_mc2_w_tax.biom  counts/open-ref-table.biom"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "!biom summarize-table -i counts/open-ref-table.biom -o counts/open-ref-table-summary.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the summaries from split libraries and the OTU table to get a proportion of the sequences assigned to an OTU. Note that the original output formats are not Pandas friendly, therefore I used vim to trimmed out the lines that were not needed at all."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sl = pd.read_csv('counts/split_library_log.txt', sep='\\t', index_col='#SampleID')\n",
    "ot = pd.read_csv('counts/table-summary.txt', sep='\\t', index_col='#SampleID')\n",
    "ot_open = pd.read_csv('counts/open-ref-table-summary.txt', sep='\\t', index_col='#SampleID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "tot = pd.DataFrame(index=sl.index, columns=['Sequences', 'OTU_Counts', 'OTU_Counts_open'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tot['Sequences'] = sl.Count\n",
    "tot['OTU_Counts'] = ot.Count\n",
    "tot['OTU_Counts_open'] = ot_open.Count\n",
    "\n",
    "tot['Percent'] = np.divide(tot.OTU_Counts, tot.Sequences *1.0) * 100\n",
    "tot['Percent_open'] = np.divide(tot.OTU_Counts_open, tot.Sequences *1.0) * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Examine the percents of sequences assigned to an OTU, both for open and closed reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1103e2590>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Juj4PXwacTjqF/2dJH8vTZ5DeMEH6Z9auf7IbpSPTiHhM6ZLMLweukgTpQ3BV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\nMzMDnBDMzCxzQjAzMwD+P2mTBunbcxgnAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fd37e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tot['Percent'].hist(bins=200)\n",
    "\n",
    "plt.xlabel('Percent of Sequences Assigned to an OTU (closed reference)')\n",
    "plt.ylabel('Counts')\n",
    "plt.xlim([0, 100])\n",
    "\n",
    "plt.title('Entire Cohort')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10fc62290>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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h/PCaNYAXAhdHxMfbWjC3IZiZNdTpvoxG82AATwD3RMS9U9nYZDghmJk11tEb0yJiIXAn\nsDGwCfCXqWzIps71owXHouBYFByL1miYECQdBFwPvIX0XOUb8mM1G5K0Ve4M7zZJt0o6Kk+fnjvL\nWyLpCklDq7ITZma26pqpMroZ2DciHszjmwNXRsSODVcubQlsGRHjkjYk3eH8BuBw4HcRcZqkjwOb\nRMSxVcu6ysjMrIFO92Uk4Lel8Yconp42oYh4ICLG8/BjwB3As4ADgDl5tjmkJGFmZl3UTEL4IXC5\npDFJhwPfB34w2Q1JGgZ2IlU/bVF6jvJyYIvJrm+QuH604FgUHIuCY9EaEz1T+XmkA/dHJb0J2D2/\n9RPg65PZSK4uugQ4OiIerVziAERESHLdkJlZl03UdcVs4DiAiLiEdEBH0o7AmcDrmtmApLXyshdG\nxNw8ebmkLSPiAUkzgAdrLTs2Nsbw8DAAQ0NDjIyMMDo6ChRnBIMwPjo62lPl8XjvjFf0Snm6NV6Z\n1ivl6cb+S+LEE09kVdRtVJZ0Y0TsUue9WyNi+4YrT5cCc4CHIuKDpemn5WmnSjoWGHKjspnZ5FXV\nuLStUXmin4Ku2+T6dwfeAewtaXF+7Q98BnilpCWkzvI+0+T6BlL12eAgcywKjkXBsWiNiaqMbpT0\nzxHx5fJESe+lyQfkRMS11E86+zZXRDMz64SJqoy2BL4D/JUiAbwYWAc4MCLub2vBXGVkZtZQK6uM\nJrwxLbcB7A1sT+rL6LaIuGoqG5p0wZwQzMwa6lQbApFcFRFnRcTnOpUMbGWuHy04FgXHouBYtMZU\nnodgZmaroYZ9GXWLq4zMzBrrWJWRmZkNDieEPuD60YJjUXAsCo5FazghmJkZ4DYEM7O+5jYEMzNr\nOSeEPuD60YJjUXAsCo5FazghmJkZ4DYEM7O+5jYEMzNrOSeEPuD60YJjUXAsCo5FazghmJkZ0OY2\nBEnnAa8BHoyIHfK0mcB7gN/m2Y6LiB/WWNZtCGZmDfRTG8L5wP5V0wKYFRE75dfTkoGZmXVeWxNC\nRFwDPFLjrSllr0Hl+tGCY1FwLAqORWt0qw3hSEk3STpX0lCXymBmZiVrdmGbZwOfzMOfAs4A3l1r\nxrGxMYaHhwEYGhpiZGSE0dFRoDgjGITx0dHRniqPx3tnvKJXytOt8cq0XilPN/YfYObMmayKtt+Y\nJmkYmFdpVJ7Ee25UNjNroJ8alZ9G0ozS6IHALZ0uQ7+pPhscZI5FwbEoOBat0dYqI0kXAXsBm0m6\nFzgRGJU0Qvq10VLgiHaWwczMmuO+jMzM+lhfVxmZmVlvckLoA64fLTgWBcei4Fi0hhOCmZkBbkMw\nM+trbkMwM7OWc0LoA64fLTgWBcei4Fi0hhOCmZkBbkMwM+trbkMwM7OWc0LoA64fLTgWBcei4Fi0\nhhOCmZkBbkMwM+trbkMwM7OWc0LoA64fLTgWBcei4Fi0hhOCmZkBbkMwM+tb5faDsp5sQ5B0nqTl\nkm4pTZsuab6kJZKukDTUzjKYmVlz2l1ldD6wf9W0Y4H5EbEdcGUetwm4frTgWBQci4Jj0RptTQgR\ncQ3wSNXkA4A5eXgO8IZ2lsHMzJrT9jYEScPAvIjYIY8/EhGb5GEBD1fGq5ZzG4KZ2QRa3Yaw5iqV\nZhVFREiqe9QfGxtjeHgYgKGhIUZGRhgdHQWKS0SPe9zjHh/U8VbrxhXCncBoRDwgaQawICKeX2M5\nXyFkCxcufOqDMOgci4JjURjUWPTVr4zquAw4LA8fBsztQhnMzKxKW68QJF0E7AVsBiwH/hX4LnAx\nsDWwDDgoIlbUWNZXCGZmE2j1FYJvTDMz61OrQ5WRTVK7GpD6kWNRcCwKjkVrOCGYmRngKiMzs77l\nKiMzM2sLJ4Q+4PrRgmNRcCwKjkVrOCGYmRngNgQzs77lNgQzM2sLJ4Q+4PrRgmNRcCwKjkVrOCGY\nmRngNgQzs77lNgQzM2sLJ4Q+4PrRgmNRcCwKjkVrOCGYmRngNgQzs77lNgQzM2uLriUEScsk3Sxp\nsaQbulWOfuD60YJjUXAsCo5Fa6zZxW0HMBoRD3exDGZmlnWtDUHSUmCXiHiozvtuQzAzm8Dq1IYQ\nwI8k3SjpvV0sh5mZ0d0qo90j4n5JmwPzJd0ZEdeUZxgbG2N4eBiAoaEhRkZGGB0dBYo6w0EYL9eP\n9kJ5ujlemdYr5enm+Pj4OMccc0zPlKeb47Nnzx7I40Or9cTPTiWdCDwWEWeUprnKKFu4cOFTH4RB\n51gUHIvCoMai1VVGXUkIktYHpkXEo5I2AK4AToqIK0rzOCGYmU2g1QmhW1VGWwDfyTuzJvAf5WRg\nZmad15VG5YhYGhEj+bV9RJzSjXL0i3bVF/Yjx6LgWBQci9bwncpmZgb0SKNyLW5DMDOb2Op0H4KZ\nmfUQJ4Q+4PrRgmNRcCwKjkVrOCGYmRngNgQzs75SaTeICLchmJlZezgh9AHXjxYci4JjUXAsWsMJ\nwczMALchmJn1FbchmJlNYObMmd0uQsfVSwarwgmhD7h+tOBYFByLwkknndTtIqwWnBDMzAxwG4KZ\nrQYkMSjHi2aqityGYGZ9Z9asz/LhDx/b7WJY1rWEIGl/SXdK+pWkj3erHP3AdcUFx6KwOsRi9uyz\nmDXr1Ekt044GZEkrvTplou3VKlO7y9aVhCBpGvB5YH/ghcAhkl7QjbL0g/Hx8W4XoWc4FoXVIRZr\nrDH5Q5AbkNunW1cIuwL/FRHLIuJvwDeA13epLD1vxYoV3S5Cz3AsCo6FtVq3EsKzgHtL4/flaWZm\n1iXdSgiD8XOAFlm2bFm3i9AzHIvC6hCLjTfeuNtFsJKu/OxU0m7AzIjYP48fBzwZEaeW5nHSMDOb\ngqn+7LRbCWFN4JfAK4D/Bm4ADomIOzpeGDMzA2DNbmw0Ip6Q9AHgcmAacK6TgZlZd/XsncpmZtZZ\nPXen8iDfsCZpK0kLJN0m6VZJR+Xp0yXNl7RE0hWShrpd1k6RNE3SYknz8vhAxkLSkKRvS7pD0u2S\nXjrAsTguf0dukfR1SesMSiwknSdpuaRbStPq7nuO1a/yMXW/RuvvqYTgG9b4G/DBiPgnYDfg/Xn/\njwXmR8R2wJV5fFAcDdxO8cu0QY3FZ4HvR8QLgB2BOxnAWEgaBt4L7BwRO5CqnA9mcGJxPun4WFZz\n3yW9EHgr6Vi6P/AFSRMe83sqITDgN6xFxAMRMZ6HHwPuIN2fcQAwJ882B3hDd0rYWZKeDbwaOAeo\n/Gpi4GIh6RnAnhFxHqQ2uIj4PQMYC+APpBOn9fOPU9Yn/TBlIGIREdcAj1RNrrfvrwcuioi/RcQy\n4L9Ix9i6ei0h+Ia1LJ8J7QRcD2wREcvzW8uBLbpUrE47E/go8GRp2iDGYhvgt5LOl7RI0lckbcAA\nxiIiHgbOAO4hJYIVETGfAYxFSb19fybpGFrR8HjaawnBLdyApA2BS4CjI+LR8nu5T/DVPk6SXgs8\nGBGLKa4OVjIosSD9GnBn4AsRsTPwR6qqRAYlFpK2BY4BhkkHvA0lvaM8z6DEopYm9n3CuPRaQvgN\nsFVpfCtWznCrPUlrkZLBhRExN09eLmnL/P4M4MFula+DXg4cIGkpcBGwj6QLGcxY3AfcFxE/z+Pf\nJiWIBwYwFrsAP4mIhyLiCeBS4GUMZiwq6n0nqo+nz87T6uq1hHAj8DxJw5LWJjWIXNblMnWMUt+2\n5wK3R8Ts0luXAYfl4cOAudXLrm4i4viI2CoitiE1Gl4VEYcymLF4ALhX0nZ50r7AbcA8BiwWpMb0\n3SStl78v+5J+dDCIsaio9524DDhY0tqStgGeR7oJuK6euw9B0v8BZlPcsHZKl4vUMZL2AK4Gbqa4\ntDuO9E+8GNgaWAYcFBED09WlpL2AD0fEAZKmM4CxkPQiUuP62sCvgcNJ35FBjMXHSAe+J4FFwHuA\njRiAWEi6CNgL2IzUXvCvwHeps++SjgfeBTxBqoK+fML191pCMDOz7ui1KiMzM+sSJwQzMwOcEMzM\nLHNCMDMzwAnBzMwyJwQzMwMGLCFI+nvuSvkWSRdLWq8LZdhL0ssmuczakn6Uy/6Wqvd2k/Sz/N7t\nkk5sbYl7h6Q3SHpS0j9OcfmTJL2i1eWq2saYpM/VmD7p/3sLyrK2pNm5++MlkuZKelbuLnlxft0v\n6b48vEjS88pdK+f1zJT04Trb+ICksY7s0BRJ2jN3l71I0rrdLg9A7rL76ka9j3ZaTxWmAx6PiJ1y\nt7l/Bf6lmYVyr4qtsjepW4bJ2JnUTclOEfGtqvfmAO+NiJ2AfyLdoLK6OgT4z/x30iLixIi4srVF\natpU/u+r6mRgA2C73DXyXODSiHg4f5Z2Ar4IzMrjO5N6Eq1W82alfKfwu4Gvtaf4zWtwYH07cHJE\n7BwRf25iXcr71jYR8RfgGnqtV9aIGJgX8Ghp+F+Afyd1n3seqVfRRcAB+f0x0q3fVwILSF+s80l3\nEd8EvDHPtx/wE+AXpIPxBnn6MmBmnn4z8I+kDrnuJ/VNsxjYo6p800lf2puAnwI7AJuTuq1dkZd5\nbtUyDwOb19jXDers13qkbsVvJ/UD8zNS3/IAj5WWfzNwfh7enNR/zg359fI8fWbexgLS3bNHlpZ/\nZ96PceCCBuvZK+/b4lzWDWvsz4Y5plsDd5SmzyDd3b0YuAXYnXSi89U8fjPpDk3ytDfl4VeTuhe/\nETgLmNfEPr0jx3Mx6UC6Rp5+OOkZ4dcDXwY+V1X26v/77nnaVTlGPwK2qrHPu5I+W4uA60gHdkif\nzUuBHwBLgFNrLLs+8LvqWOZY7VMaP5F0F3i5rLdULbPSPKXpe5C6V66Mj5A+Tzfl8g3l6QtJvQ9U\n/kcvafAZbbh/pe/YZ0jfsbdS47tIuov5IeAuUv9gkHrQvSGXc2Zpv39JOsG6lfQ5qzffHfn/fCvp\nMcDr5vf+If8vx3MZtqm3vTz9pcC3un1cXCmm3S5AR3c2JwRS75FzgSNIZ1Fvz9OH8odi/fyhvLf0\noT6VdCZFad7NgB8D6+VpHwdOyMNLgffn4fcBXyl9uT5Up3yfKy2/N7A4D+9FPmDVWOYEUlK4FPhn\nYJ08vd5+fQg4J0/fgXRGuHM5Pnn4TRQJ4evA7nl4a1JfS5AOntcCawGbkg5A00hXKr8Eple232A9\nlwEvy8PrA9Nq7OfbgS/m4atLZf4wcHweFilxvBi4orTsxvnv+cAbgXVJ3Sc/p1Suyxrs0wtyOafl\n+b4AHEpKSHfnedfKy55Vo/wr/d9Jfe8cmocPB75TY5mNStvbF/h2Hh4jJauNgHVIB8ZnVS27I7Co\nxjpnsXKSW5WEcGzVsjeTntsAcBJwZh5eAHwpD+9ZWT8Tf/cm3L/Sd+wjeXii7+L5rHwCVynLGvn/\nsGfe778DuzYx39+AHfN73yztw/XA6/Pw2qSTr5rryePrAL9p93FvMq9WVoX0g/UkLc7DV5POTn4K\nvE7SR/L0dUgHqyA9hajSH8orSGchAETEitxF8wuBn+QrzLVJZygVl+a/i0gHoop6l6O7V+aLiAWS\nNs1dYde9fI2IT0n6D9IH722k6pS983it/dqT9PQtIuIWSTfXW3fJvsALSlfRG+X++AP4XqSHGT0k\n6UFgS2Af4OJIfddTimG99VwHnJn349KIqNUj4yGk5yMAfCuPLyKdeZ2Xe4mdGxE3Sfo18FxJZwHf\nA64orUfA84G7IuLuPO0iUjJlgn16BSnR3JjLvy7wAOksfmFEPAQg6ZtApRO6auX/424U1QVfA06r\nMf8QcIGkf8jlKn9fr4zcNbqk20kHqgl7smxSTGL61qQEWHmIzzMiPcAF0pl2uXrzIkgPeJG0cZ6/\n3mc0aH7/vpn/7sbE38VK7PcD9isdBzYgndnfC9wdETc0Md/SiKh8b34BDOfv6TMj4rt5P/+ay15v\nPddExF8krSFp3WiiKqsTBi0h/ClSvelT8ofnjRHxq6rpLyX1O7/S5BrrnB8Rb6uzvb/kv3+n+VhP\nuu4yIu4CvijpK6QHqUzPb9Xar4m2Uf7SlxvcBby08iGvWld5WmU/o842aq4HOFXSfwKvAa6T9KqI\n+GVpO9NJSW57SUE6Yw/go/kAsyfwWuCrkmZFxIW5M7hXkaoGDyLVddfaz0q5ymrtE8CciDi+KgbV\nT/SbzP+YvnuHAAADr0lEQVSv0byfIh0YD5T0HFLVS8VfSsN/J8Wk7NfA1pI2jPT0vYoXk85S63kI\n2KRq2qakKpda6u1Do32r/A/qffca7V9F+Ts60Xex/D8/JSK+XLXNYZ7+fa83X3XZGjVUP2095VXS\n4BkFnTRojcq1XA4cVRmRVEkY1R/o+cD7S/MNkepLd1d6aAeSNpD0vAbbe5R0KVzLNaSqESSNAr+t\n+jI/jaTXlEa3I/VquIL6+3U16UoCSduTqhYqlkt6fm6gO5Dig3pF1bpeNEGRglQ3/pZKYpJUOcBU\nr2ck/902Im6LiNOAn5PaW8reTGqHGI6IbSJia2Bp/vXI1qQ4nUPqDXRnSZuSqlouJVWplU8CglQ1\n8dx8kIV05VfZ11oHsiC1Jb1Z0ua5zNPztq8H9srjawFvqbE8PP3//hNSt96Q/udX11hmY9JTwSBV\nK01kpXJHxB9JZ+mzKg2ukt5JqlJZUG8l+fN2v6S98zLTSYn12hqz3026eiLSIz0fUeqxF1J12sJS\n2d6a17cH6Slnf6D57169aWXXM/F3sbL85cC78pUp+VdXm9dYX7PzQeok9DHgvsoJQv4V0XoTrUfS\nOsDfIzUw94RBSwi1MvGngLUk3SzpVlLdZ2Xe8vz/Bmyi9JPVcWA0In5Hqu+8SNJNpC95rZ9Eltc1\nDzhQ6Wd+u1fNNxN4cV7XyRR9nFeXpewdkn6ZL0kvINVnPjnBfp1NesrU7XnaL0rrOpb0K57rKA5E\nkL60u0i6SdJtpLaX8r6tvLMRtwOfBn6cY3VGnfVUqmmOznG9iXR2/oOqVR4MfKdq2iWkaqNRYFzS\nItKVwGzSYwIX5JhcSOpCvFy+PwP/F/ihpBtJz+n9fWl/au3THcAngCtyOa8Atoz0rIKZpKrHa0nP\nKaj1v6r+vx8JHJ7X9Xbg6BrLnAackvetclVUr4y1tnkc8GdgiaQlpHahA2vMV73sO4ETcvyuJDWE\nLq2x3LWkB9ZUHAacnvdpR+CTpfX/Oe/HFyiu1pr97tXbv6emRcRvmfi7GHm++aQ2o58qVZdeTGp3\nql5fU/NVjR8KHJW3fx3p0ZYTrWcn0uemZ7j76wEnaQGpYXBRt8vSSZI2yGfRSPp3YElEfLbLxeor\nSnWGi6hdDViebyA/Y41IOhn4eURUn+x0zaBdIZhVvDefrd9Gqpr5UrcL1G8inU1+hVzNac3L1UV7\n0GNPdvMVgpmZAb5CMDOzzAnBzMwAJwQzM8ucEMzMDHBCMDOzzAnBzMwA+B/5uPNuz2i12QAAAABJ\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fb86fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tot['Percent_open'].hist(bins=200)\n",
    "\n",
    "plt.xlabel('Percent of Sequences Assigned to an OTU (open reference)')\n",
    "plt.ylabel('Counts')\n",
    "plt.xlim([0, 100])\n",
    "\n",
    "plt.title('Entire Cohort')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Look only at the samples that were used for analysis\n",
    "\n",
    "Note that during our entire analysis we excluded the samples from the dogs that had accute hemorragic diarrhea. Also note that a few samples are dropped since they don't accrue the minimum of 15,000 sequences. All this can be summarized by looking at the core OTU table we used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bt = load_table('otu_table.15000.no-diarrhea.biom')\n",
    "\n",
    "sub = tot.loc[bt.ids('sample')].copy()\n",
    "\n",
    "sub['Percent'] = np.divide(sub.OTU_Counts, sub.Sequences *1.0) * 100\n",
    "sub['Percent_open'] = np.divide(sub.OTU_Counts_open, sub.Sequences *1.0) * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now visualize this data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x111515850>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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gM4Pe93PgqZLWU7q5xSX5k9FrYdUnvDMlnQcskbS+pBMlXZmvzPiGvNzLJV0k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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e2ad890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub['Percent'].hist(bins=200)\n",
    "\n",
    "plt.xlabel('Percent of Sequences Assigned to an OTU')\n",
    "plt.ylabel('Counts')\n",
    "plt.xlim([70, 100])\n",
    "plt.title('Samples used for Analysis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10f1a43d0>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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6uuzhE0y/L3BlROwWEZdMZgVKj53vtm8BH+7BeiYWEbX+Iz23vNH9XuC/SI8i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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111550ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub['Percent_open'].hist(bins=200)\n",
    "\n",
    "plt.xlabel('Percent of Sequences Assigned to an OTU (Open Reference)')\n",
    "plt.ylabel('Counts')\n",
    "plt.xlim([70, 100])\n",
    "plt.title('Samples used for Analysis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "94.247970426585781"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub.Percent.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "99.143186791879018"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub.Percent_open.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This last bit is particularly revealing of the minor gains that we get from using the open reference OTU picking protocol. The mean percent of reads mapped to an OTU went from 94.2 % (in closed reference) to 99.14 % (in open reference). Furthermore in the original analysis performed in Gevers et al 2014, a closed reference OTU picking approach was used, therefore to directly compare co-occurrence networks between analyses would be incorrect."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}