03-22-2019_Number_of_Unique_Species.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "suppressPackageStartupMessages({\n",
    "    library(tidyverse)\n",
    "    library(reshape2)\n",
    "    library(ggpubr)\n",
    "    library(matrixStats)\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = read.csv(\"all_samples_species.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>taxa</th><th scope=col>V1V2_HNO17_S8_R1</th><th scope=col>V1V2_HNO19_S9_R1</th><th scope=col>V1V2_HNO209_S14_R1</th><th scope=col>V1V2_HNO223_S15_R1</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>Actinomyces graevenitzii F0530</td><td> 1                            </td><td> 1                            </td><td> 1                            </td><td> 1                            </td></tr>\n",
       "\t<tr><td>Aerococcus urinaeequi         </td><td> 0                            </td><td> 0                            </td><td> 0                            </td><td> 0                            </td></tr>\n",
       "\t<tr><td>Alistipes obesi               </td><td> 0                            </td><td> 0                            </td><td> 0                            </td><td> 1                            </td></tr>\n",
       "\t<tr><td>Ambiguous_taxa                </td><td>49                            </td><td>34                            </td><td>23                            </td><td>17                            </td></tr>\n",
       "\t<tr><td>Anaerococcus sp. SJ-2013      </td><td> 0                            </td><td> 0                            </td><td> 0                            </td><td> 0                            </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       " taxa & V1V2\\_HNO17\\_S8\\_R1 & V1V2\\_HNO19\\_S9\\_R1 & V1V2\\_HNO209\\_S14\\_R1 & V1V2\\_HNO223\\_S15\\_R1\\\\\n",
       "\\hline\n",
       "\t Actinomyces graevenitzii F0530 &  1                             &  1                             &  1                             &  1                            \\\\\n",
       "\t Aerococcus urinaeequi          &  0                             &  0                             &  0                             &  0                            \\\\\n",
       "\t Alistipes obesi                &  0                             &  0                             &  0                             &  1                            \\\\\n",
       "\t Ambiguous\\_taxa                 & 49                               & 34                               & 23                               & 17                              \\\\\n",
       "\t Anaerococcus sp. SJ-2013       &  0                             &  0                             &  0                             &  0                            \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| taxa | V1V2_HNO17_S8_R1 | V1V2_HNO19_S9_R1 | V1V2_HNO209_S14_R1 | V1V2_HNO223_S15_R1 |\n",
       "|---|---|---|---|---|\n",
       "| Actinomyces graevenitzii F0530 |  1                             |  1                             |  1                             |  1                             |\n",
       "| Aerococcus urinaeequi          |  0                             |  0                             |  0                             |  0                             |\n",
       "| Alistipes obesi                |  0                             |  0                             |  0                             |  1                             |\n",
       "| Ambiguous_taxa                 | 49                             | 34                             | 23                             | 17                             |\n",
       "| Anaerococcus sp. SJ-2013       |  0                             |  0                             |  0                             |  0                             |\n",
       "\n"
      ],
      "text/plain": [
       "  taxa                           V1V2_HNO17_S8_R1 V1V2_HNO19_S9_R1\n",
       "1 Actinomyces graevenitzii F0530  1                1              \n",
       "2 Aerococcus urinaeequi           0                0              \n",
       "3 Alistipes obesi                 0                0              \n",
       "4 Ambiguous_taxa                 49               34              \n",
       "5 Anaerococcus sp. SJ-2013        0                0              \n",
       "  V1V2_HNO209_S14_R1 V1V2_HNO223_S15_R1\n",
       "1  1                  1                \n",
       "2  0                  0                \n",
       "3  0                  1                \n",
       "4 23                 17                \n",
       "5  0                  0                "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[1:5,1:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2_mat = as.matrix( df[-1])\n",
    "rownames(df2_mat) = df$taxa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'V1V2'</li>\n",
       "\t<li>'V2V3'</li>\n",
       "\t<li>'V3V4'</li>\n",
       "\t<li>'V4V5'</li>\n",
       "\t<li>'V5V7'</li>\n",
       "\t<li>'V7V9'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'V1V2'\n",
       "\\item 'V2V3'\n",
       "\\item 'V3V4'\n",
       "\\item 'V4V5'\n",
       "\\item 'V5V7'\n",
       "\\item 'V7V9'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'V1V2'\n",
       "2. 'V2V3'\n",
       "3. 'V3V4'\n",
       "4. 'V4V5'\n",
       "5. 'V5V7'\n",
       "6. 'V7V9'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] \"V1V2\" \"V2V3\" \"V3V4\" \"V4V5\" \"V5V7\" \"V7V9\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sets\n",
    "primer_sets = unique( sapply(strsplit(colnames(df2_mat),'_'),'[[',1) )\n",
    "primer_sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"V1V2\"\n",
      "[1] \"V2V3\"\n",
      "[1] \"V3V4\"\n",
      "[1] \"V4V5\"\n",
      "[1] \"V5V7\"\n",
      "[1] \"V7V9\"\n"
     ]
    }
   ],
   "source": [
    "new_df = list();\n",
    "for( i in 1:length(primer_sets) ){\n",
    "    primer= primer_sets[i]\n",
    "    print(primer)\n",
    "    new_df[[primer]] = rowMeans(df2_mat[ , grep( primer, colnames(df2_mat))])\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df = as.data.frame( new_df )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>V1V2</th><th scope=col>V2V3</th><th scope=col>V3V4</th><th scope=col>V4V5</th><th scope=col>V5V7</th><th scope=col>V7V9</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Actinomyces graevenitzii F0530</th><td> 0.826087  </td><td> 1.00000000</td><td> 0.86956522</td><td> 0.73913043</td><td> 0.6956522 </td><td> 0.26086957</td></tr>\n",
       "\t<tr><th scope=row>Aerococcus urinaeequi</th><td> 0.000000  </td><td> 0.00000000</td><td> 0.00000000</td><td> 0.00000000</td><td> 0.6956522 </td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Alistipes obesi</th><td> 0.173913  </td><td> 0.04347826</td><td> 0.04347826</td><td> 0.04347826</td><td> 0.0000000 </td><td> 0.04347826</td></tr>\n",
       "\t<tr><th scope=row>Ambiguous_taxa</th><td>33.130435  </td><td>28.08695652</td><td>21.73913043</td><td>27.47826087</td><td>22.0000000 </td><td>21.91304348</td></tr>\n",
       "\t<tr><th scope=row>Anaerococcus sp. SJ-2013</th><td> 0.000000  </td><td> 0.00000000</td><td> 0.00000000</td><td> 0.04347826</td><td> 0.0000000 </td><td> 0.00000000</td></tr>\n",
       "\t<tr><th scope=row>Bacteroides thetaiotaomicron</th><td> 0.000000  </td><td> 0.00000000</td><td> 0.00000000</td><td> 0.04347826</td><td> 0.0000000 </td><td> 0.04347826</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllll}\n",
       "  & V1V2 & V2V3 & V3V4 & V4V5 & V5V7 & V7V9\\\\\n",
       "\\hline\n",
       "\tActinomyces graevenitzii F0530 &  0.826087   &  1.00000000 &  0.86956522 &  0.73913043 &  0.6956522  &  0.26086957\\\\\n",
       "\tAerococcus urinaeequi &  0.000000   &  0.00000000 &  0.00000000 &  0.00000000 &  0.6956522  &  0.00000000\\\\\n",
       "\tAlistipes obesi &  0.173913   &  0.04347826 &  0.04347826 &  0.04347826 &  0.0000000  &  0.04347826\\\\\n",
       "\tAmbiguous\\_taxa & 33.130435   & 28.08695652 & 21.73913043 & 27.47826087 & 22.0000000  & 21.91304348\\\\\n",
       "\tAnaerococcus sp. SJ-2013 &  0.000000   &  0.00000000 &  0.00000000 &  0.04347826 &  0.0000000  &  0.00000000\\\\\n",
       "\tBacteroides thetaiotaomicron &  0.000000   &  0.00000000 &  0.00000000 &  0.04347826 &  0.0000000  &  0.04347826\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | V1V2 | V2V3 | V3V4 | V4V5 | V5V7 | V7V9 |\n",
       "|---|---|---|---|---|---|---|\n",
       "| Actinomyces graevenitzii F0530 |  0.826087   |  1.00000000 |  0.86956522 |  0.73913043 |  0.6956522  |  0.26086957 |\n",
       "| Aerococcus urinaeequi |  0.000000   |  0.00000000 |  0.00000000 |  0.00000000 |  0.6956522  |  0.00000000 |\n",
       "| Alistipes obesi |  0.173913   |  0.04347826 |  0.04347826 |  0.04347826 |  0.0000000  |  0.04347826 |\n",
       "| Ambiguous_taxa | 33.130435   | 28.08695652 | 21.73913043 | 27.47826087 | 22.0000000  | 21.91304348 |\n",
       "| Anaerococcus sp. SJ-2013 |  0.000000   |  0.00000000 |  0.00000000 |  0.04347826 |  0.0000000  |  0.00000000 |\n",
       "| Bacteroides thetaiotaomicron |  0.000000   |  0.00000000 |  0.00000000 |  0.04347826 |  0.0000000  |  0.04347826 |\n",
       "\n"
      ],
      "text/plain": [
       "                               V1V2      V2V3        V3V4        V4V5       \n",
       "Actinomyces graevenitzii F0530  0.826087  1.00000000  0.86956522  0.73913043\n",
       "Aerococcus urinaeequi           0.000000  0.00000000  0.00000000  0.00000000\n",
       "Alistipes obesi                 0.173913  0.04347826  0.04347826  0.04347826\n",
       "Ambiguous_taxa                 33.130435 28.08695652 21.73913043 27.47826087\n",
       "Anaerococcus sp. SJ-2013        0.000000  0.00000000  0.00000000  0.04347826\n",
       "Bacteroides thetaiotaomicron    0.000000  0.00000000  0.00000000  0.04347826\n",
       "                               V5V7       V7V9       \n",
       "Actinomyces graevenitzii F0530  0.6956522  0.26086957\n",
       "Aerococcus urinaeequi           0.6956522  0.00000000\n",
       "Alistipes obesi                 0.0000000  0.04347826\n",
       "Ambiguous_taxa                 22.0000000 21.91304348\n",
       "Anaerococcus sp. SJ-2013        0.0000000  0.00000000\n",
       "Bacteroides thetaiotaomicron    0.0000000  0.04347826"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_df %>% head"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "64"
      ],
      "text/latex": [
       "64"
      ],
      "text/markdown": [
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      ],
      "text/plain": [
       "[1] 64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "length( unique((rownames(new_df[ new_df$V1V2 !=0,][\"V1V2\"]))) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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      "text/latex": [
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      "text/markdown": [
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      ],
      "text/plain": [
       "[1] 54"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "length( unique((rownames(new_df[ new_df$V2V3 !=0,][\"V1V2\"]))) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "54"
      ],
      "text/latex": [
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      "text/markdown": [
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      ],
      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "length( unique((rownames(new_df[ new_df$V4V5 !=0,][\"V1V2\"]))) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "40"
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      "text/latex": [
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      ],
      "text/markdown": [
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      ],
      "text/plain": [
       "[1] 40"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "length( unique((rownames(new_df[ new_df$V3V4 !=0,][\"V1V2\"]))) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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      ],
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "length( unique((rownames(new_df[ new_df$V3V4 !=0,][\"V1V2\"]))) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "v1v2 = length( unique((rownames(new_df[ new_df$V1V2 !=0,][\"V1V2\"]))) )\n",
    "v2v3 = length( unique((rownames(new_df[ new_df$V2V3 !=0,][\"V2V3\"]))) )\n",
    "v3v4 = length( unique((rownames(new_df[ new_df$V3V4 !=0,][\"V3V4\"]))) )\n",
    "v4v5 = length( unique((rownames(new_df[ new_df$V4V5 !=0,][\"V4V5\"]))) )\n",
    "v5v7 = length( unique((rownames(new_df[ new_df$V5V7 !=0,][\"V5V7\"]))) )\n",
    "v7v9 = length( unique((rownames(new_df[ new_df$V5V7 !=0,][\"V7V9\"]))) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uj+itBkMjkcjvz8/OTk5PDw8MTExLy8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\n/BOJoe87ZwAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.height=4, repr.plot.width=5)\n",
    "barplot( cbind( v1v2, v2v3, v3v4, v4v5, v5v7, v7v9 ) , las=1)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R 3.5",
   "language": "R",
   "name": "ir35"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}