{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(limma)\n",
    "library(edgeR)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read the count table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 14</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>X</th><th scope=col>Geneid</th><th scope=col>sorted_reads.mfc_cnt_2.bam</th><th scope=col>sorted_reads.mfc_dac_2.bam</th><th scope=col>sorted_reads.mfc_dac_1.bam</th><th scope=col>sorted_reads.mfc_dac_3.bam</th><th scope=col>sorted_reads.yb5_dac_3.bam</th><th scope=col>sorted_reads.yb5_cnt_1.bam</th><th scope=col>sorted_reads.mfc_cnt_1.bam</th><th scope=col>sorted_reads.yb5_cnt_3.bam</th><th scope=col>sorted_reads.yb5_dac_1.bam</th><th scope=col>sorted_reads.yb5_dac_2.bam</th><th scope=col>sorted_reads.yb5_cnt_2.bam</th><th scope=col>sorted_reads.mfc_cnt_3.bam</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>0</td><td>ENSG00000223972</td><td>  18</td><td>  57</td><td>  46</td><td>  56</td><td> 215</td><td>  59</td><td>  11</td><td>  32</td><td> 278</td><td> 203</td><td>  35</td><td>  55</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>1</td><td>ENSG00000227232</td><td>2441</td><td>4172</td><td>3644</td><td>4329</td><td>5629</td><td>4055</td><td>2089</td><td>2568</td><td>6803</td><td>4957</td><td>2568</td><td>7559</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>2</td><td>ENSG00000278267</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>3</td><td>ENSG00000243485</td><td>   3</td><td>  11</td><td>   8</td><td>  13</td><td>  23</td><td>  12</td><td>   2</td><td>   9</td><td>  33</td><td>  26</td><td>   7</td><td>   8</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>4</td><td>ENSG00000237613</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   1</td><td>   0</td><td>   0</td><td>   2</td><td>   1</td><td>   0</td><td>   0</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>5</td><td>ENSG00000268020</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   1</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 14\n",
       "\\begin{tabular}{r|llllllllllllll}\n",
       "  & X & Geneid & sorted\\_reads.mfc\\_cnt\\_2.bam & sorted\\_reads.mfc\\_dac\\_2.bam & sorted\\_reads.mfc\\_dac\\_1.bam & sorted\\_reads.mfc\\_dac\\_3.bam & sorted\\_reads.yb5\\_dac\\_3.bam & sorted\\_reads.yb5\\_cnt\\_1.bam & sorted\\_reads.mfc\\_cnt\\_1.bam & sorted\\_reads.yb5\\_cnt\\_3.bam & sorted\\_reads.yb5\\_dac\\_1.bam & sorted\\_reads.yb5\\_dac\\_2.bam & sorted\\_reads.yb5\\_cnt\\_2.bam & sorted\\_reads.mfc\\_cnt\\_3.bam\\\\\n",
       "  & <int> & <chr> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int>\\\\\n",
       "\\hline\n",
       "\t1 & 0 & ENSG00000223972 &   18 &   57 &   46 &   56 &  215 &   59 &   11 &   32 &  278 &  203 &   35 &   55\\\\\n",
       "\t2 & 1 & ENSG00000227232 & 2441 & 4172 & 3644 & 4329 & 5629 & 4055 & 2089 & 2568 & 6803 & 4957 & 2568 & 7559\\\\\n",
       "\t3 & 2 & ENSG00000278267 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    0\\\\\n",
       "\t4 & 3 & ENSG00000243485 &    3 &   11 &    8 &   13 &   23 &   12 &    2 &    9 &   33 &   26 &    7 &    8\\\\\n",
       "\t5 & 4 & ENSG00000237613 &    0 &    0 &    0 &    0 &    0 &    1 &    0 &    0 &    2 &    1 &    0 &    0\\\\\n",
       "\t6 & 5 & ENSG00000268020 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    1 &    0 &    0 &    0 &    0\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 14\n",
       "\n",
       "| <!--/--> | X &lt;int&gt; | Geneid &lt;chr&gt; | sorted_reads.mfc_cnt_2.bam &lt;int&gt; | sorted_reads.mfc_dac_2.bam &lt;int&gt; | sorted_reads.mfc_dac_1.bam &lt;int&gt; | sorted_reads.mfc_dac_3.bam &lt;int&gt; | sorted_reads.yb5_dac_3.bam &lt;int&gt; | sorted_reads.yb5_cnt_1.bam &lt;int&gt; | sorted_reads.mfc_cnt_1.bam &lt;int&gt; | sorted_reads.yb5_cnt_3.bam &lt;int&gt; | sorted_reads.yb5_dac_1.bam &lt;int&gt; | sorted_reads.yb5_dac_2.bam &lt;int&gt; | sorted_reads.yb5_cnt_2.bam &lt;int&gt; | sorted_reads.mfc_cnt_3.bam &lt;int&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 1 | 0 | ENSG00000223972 |   18 |   57 |   46 |   56 |  215 |   59 |   11 |   32 |  278 |  203 |   35 |   55 |\n",
       "| 2 | 1 | ENSG00000227232 | 2441 | 4172 | 3644 | 4329 | 5629 | 4055 | 2089 | 2568 | 6803 | 4957 | 2568 | 7559 |\n",
       "| 3 | 2 | ENSG00000278267 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |\n",
       "| 4 | 3 | ENSG00000243485 |    3 |   11 |    8 |   13 |   23 |   12 |    2 |    9 |   33 |   26 |    7 |    8 |\n",
       "| 5 | 4 | ENSG00000237613 |    0 |    0 |    0 |    0 |    0 |    1 |    0 |    0 |    2 |    1 |    0 |    0 |\n",
       "| 6 | 5 | ENSG00000268020 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    1 |    0 |    0 |    0 |    0 |\n",
       "\n"
      ],
      "text/plain": [
       "  X Geneid          sorted_reads.mfc_cnt_2.bam sorted_reads.mfc_dac_2.bam\n",
       "1 0 ENSG00000223972   18                         57                      \n",
       "2 1 ENSG00000227232 2441                       4172                      \n",
       "3 2 ENSG00000278267    0                          0                      \n",
       "4 3 ENSG00000243485    3                         11                      \n",
       "5 4 ENSG00000237613    0                          0                      \n",
       "6 5 ENSG00000268020    0                          0                      \n",
       "  sorted_reads.mfc_dac_1.bam sorted_reads.mfc_dac_3.bam\n",
       "1   46                         56                      \n",
       "2 3644                       4329                      \n",
       "3    0                          0                      \n",
       "4    8                         13                      \n",
       "5    0                          0                      \n",
       "6    0                          0                      \n",
       "  sorted_reads.yb5_dac_3.bam sorted_reads.yb5_cnt_1.bam\n",
       "1  215                         59                      \n",
       "2 5629                       4055                      \n",
       "3    0                          0                      \n",
       "4   23                         12                      \n",
       "5    0                          1                      \n",
       "6    0                          0                      \n",
       "  sorted_reads.mfc_cnt_1.bam sorted_reads.yb5_cnt_3.bam\n",
       "1   11                         32                      \n",
       "2 2089                       2568                      \n",
       "3    0                          0                      \n",
       "4    2                          9                      \n",
       "5    0                          0                      \n",
       "6    0                          1                      \n",
       "  sorted_reads.yb5_dac_1.bam sorted_reads.yb5_dac_2.bam\n",
       "1  278                        203                      \n",
       "2 6803                       4957                      \n",
       "3    0                          0                      \n",
       "4   33                         26                      \n",
       "5    2                          1                      \n",
       "6    0                          0                      \n",
       "  sorted_reads.yb5_cnt_2.bam sorted_reads.mfc_cnt_3.bam\n",
       "1   35                         55                      \n",
       "2 2568                       7559                      \n",
       "3    0                          0                      \n",
       "4    7                          8                      \n",
       "5    0                          0                      \n",
       "6    0                          0                      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cc <- read.csv(\"counts.csv\")\n",
    "head(cc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Do the table formatting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "rownames(cc) <- cc[,2]\n",
    "cc <- cc[, -c(1,2)]\n",
    "o <- order(colnames(cc))\n",
    "cc <- cc[, o]\n",
    "ccl <- apply(cc, c(1,2), function(x) log2(x+1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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U8Unro5+o6S/mZJP1FSuupz+/eV9IUl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\nAAEIQGB8Cfw/WoFdkTZ0ugYAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "smoothScatter(ccl[,1], ccl[,2])\n",
    "idx <- which(ccl[,1]<2 & ccl[,2]<5)\n",
    "points(ccl[idx,1], ccl[idx,2], col=\"blue\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Adjust the column names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "34983"
      ],
      "text/latex": [
       "34983"
      ],
      "text/markdown": [
       "34983"
      ],
      "text/plain": [
       "[1] 34983"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>57992</li><li>12</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 57992\n",
       "\\item 12\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 57992\n",
       "2. 12\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 57992    12"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "length(idx)\n",
    "dim(cc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "tmp <- colnames(cc)\n",
    "colnames(cc) <- sapply(tmp, function(x) substr(x, 14, 22))\n",
    "colnames(ccl) <- sapply(tmp, function(x) substr(x, 14, 22))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 12</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>mfc_cnt_1</th><th scope=col>mfc_cnt_2</th><th scope=col>mfc_cnt_3</th><th scope=col>mfc_dac_1</th><th scope=col>mfc_dac_2</th><th scope=col>mfc_dac_3</th><th scope=col>yb5_cnt_1</th><th scope=col>yb5_cnt_2</th><th scope=col>yb5_cnt_3</th><th scope=col>yb5_dac_1</th><th scope=col>yb5_dac_2</th><th scope=col>yb5_dac_3</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>ENSG00000223972</th><td>  11</td><td>  18</td><td>  55</td><td>  46</td><td>  57</td><td>  56</td><td>  59</td><td>  35</td><td>  32</td><td> 278</td><td> 203</td><td> 215</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000227232</th><td>2089</td><td>2441</td><td>7559</td><td>3644</td><td>4172</td><td>4329</td><td>4055</td><td>2568</td><td>2568</td><td>6803</td><td>4957</td><td>5629</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000278267</th><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000243485</th><td>   2</td><td>   3</td><td>   8</td><td>   8</td><td>  11</td><td>  13</td><td>  12</td><td>   7</td><td>   9</td><td>  33</td><td>  26</td><td>  23</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000237613</th><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   1</td><td>   0</td><td>   0</td><td>   2</td><td>   1</td><td>   0</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000268020</th><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   0</td><td>   1</td><td>   0</td><td>   0</td><td>   0</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 12\n",
       "\\begin{tabular}{r|llllllllllll}\n",
       "  & mfc\\_cnt\\_1 & mfc\\_cnt\\_2 & mfc\\_cnt\\_3 & mfc\\_dac\\_1 & mfc\\_dac\\_2 & mfc\\_dac\\_3 & yb5\\_cnt\\_1 & yb5\\_cnt\\_2 & yb5\\_cnt\\_3 & yb5\\_dac\\_1 & yb5\\_dac\\_2 & yb5\\_dac\\_3\\\\\n",
       "  & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int>\\\\\n",
       "\\hline\n",
       "\tENSG00000223972 &   11 &   18 &   55 &   46 &   57 &   56 &   59 &   35 &   32 &  278 &  203 &  215\\\\\n",
       "\tENSG00000227232 & 2089 & 2441 & 7559 & 3644 & 4172 & 4329 & 4055 & 2568 & 2568 & 6803 & 4957 & 5629\\\\\n",
       "\tENSG00000278267 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    0\\\\\n",
       "\tENSG00000243485 &    2 &    3 &    8 &    8 &   11 &   13 &   12 &    7 &    9 &   33 &   26 &   23\\\\\n",
       "\tENSG00000237613 &    0 &    0 &    0 &    0 &    0 &    0 &    1 &    0 &    0 &    2 &    1 &    0\\\\\n",
       "\tENSG00000268020 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    0 &    1 &    0 &    0 &    0\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 12\n",
       "\n",
       "| <!--/--> | mfc_cnt_1 &lt;int&gt; | mfc_cnt_2 &lt;int&gt; | mfc_cnt_3 &lt;int&gt; | mfc_dac_1 &lt;int&gt; | mfc_dac_2 &lt;int&gt; | mfc_dac_3 &lt;int&gt; | yb5_cnt_1 &lt;int&gt; | yb5_cnt_2 &lt;int&gt; | yb5_cnt_3 &lt;int&gt; | yb5_dac_1 &lt;int&gt; | yb5_dac_2 &lt;int&gt; | yb5_dac_3 &lt;int&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| ENSG00000223972 |   11 |   18 |   55 |   46 |   57 |   56 |   59 |   35 |   32 |  278 |  203 |  215 |\n",
       "| ENSG00000227232 | 2089 | 2441 | 7559 | 3644 | 4172 | 4329 | 4055 | 2568 | 2568 | 6803 | 4957 | 5629 |\n",
       "| ENSG00000278267 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |\n",
       "| ENSG00000243485 |    2 |    3 |    8 |    8 |   11 |   13 |   12 |    7 |    9 |   33 |   26 |   23 |\n",
       "| ENSG00000237613 |    0 |    0 |    0 |    0 |    0 |    0 |    1 |    0 |    0 |    2 |    1 |    0 |\n",
       "| ENSG00000268020 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    0 |    1 |    0 |    0 |    0 |\n",
       "\n"
      ],
      "text/plain": [
       "                mfc_cnt_1 mfc_cnt_2 mfc_cnt_3 mfc_dac_1 mfc_dac_2 mfc_dac_3\n",
       "ENSG00000223972   11        18        55        46        57        56     \n",
       "ENSG00000227232 2089      2441      7559      3644      4172      4329     \n",
       "ENSG00000278267    0         0         0         0         0         0     \n",
       "ENSG00000243485    2         3         8         8        11        13     \n",
       "ENSG00000237613    0         0         0         0         0         0     \n",
       "ENSG00000268020    0         0         0         0         0         0     \n",
       "                yb5_cnt_1 yb5_cnt_2 yb5_cnt_3 yb5_dac_1 yb5_dac_2 yb5_dac_3\n",
       "ENSG00000223972   59        35        32       278       203       215     \n",
       "ENSG00000227232 4055      2568      2568      6803      4957      5629     \n",
       "ENSG00000278267    0         0         0         0         0         0     \n",
       "ENSG00000243485   12         7         9        33        26        23     \n",
       "ENSG00000237613    1         0         0         2         1         0     \n",
       "ENSG00000268020    0         0         1         0         0         0     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(cc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 6 × 12 of type dbl</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>mfc_cnt_1</th><th scope=col>mfc_cnt_2</th><th scope=col>mfc_cnt_3</th><th scope=col>mfc_dac_1</th><th scope=col>mfc_dac_2</th><th scope=col>mfc_dac_3</th><th scope=col>yb5_cnt_1</th><th scope=col>yb5_cnt_2</th><th scope=col>yb5_cnt_3</th><th scope=col>yb5_dac_1</th><th scope=col>yb5_dac_2</th><th scope=col>yb5_dac_3</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>ENSG00000223972</th><td> 3.584963</td><td> 4.247928</td><td> 5.807355</td><td> 5.554589</td><td> 5.857981</td><td> 5.832890</td><td> 5.906891</td><td> 5.169925</td><td> 5.044394</td><td> 8.124121</td><td> 7.672425</td><td> 7.754888</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000227232</th><td>11.029287</td><td>11.253847</td><td>12.884171</td><td>11.831703</td><td>12.026869</td><td>12.080151</td><td>11.985842</td><td>11.326991</td><td>11.326991</td><td>12.732167</td><td>12.275543</td><td>12.458919</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000278267</th><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000243485</th><td> 1.584963</td><td> 2.000000</td><td> 3.169925</td><td> 3.169925</td><td> 3.584963</td><td> 3.807355</td><td> 3.700440</td><td> 3.000000</td><td> 3.321928</td><td> 5.087463</td><td> 4.754888</td><td> 4.584963</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000237613</th><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 1.000000</td><td> 0.000000</td><td> 0.000000</td><td> 1.584963</td><td> 1.000000</td><td> 0.000000</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000268020</th><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td><td> 1.000000</td><td> 0.000000</td><td> 0.000000</td><td> 0.000000</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 6 × 12 of type dbl\n",
       "\\begin{tabular}{r|llllllllllll}\n",
       "  & mfc\\_cnt\\_1 & mfc\\_cnt\\_2 & mfc\\_cnt\\_3 & mfc\\_dac\\_1 & mfc\\_dac\\_2 & mfc\\_dac\\_3 & yb5\\_cnt\\_1 & yb5\\_cnt\\_2 & yb5\\_cnt\\_3 & yb5\\_dac\\_1 & yb5\\_dac\\_2 & yb5\\_dac\\_3\\\\\n",
       "\\hline\n",
       "\tENSG00000223972 &  3.584963 &  4.247928 &  5.807355 &  5.554589 &  5.857981 &  5.832890 &  5.906891 &  5.169925 &  5.044394 &  8.124121 &  7.672425 &  7.754888\\\\\n",
       "\tENSG00000227232 & 11.029287 & 11.253847 & 12.884171 & 11.831703 & 12.026869 & 12.080151 & 11.985842 & 11.326991 & 11.326991 & 12.732167 & 12.275543 & 12.458919\\\\\n",
       "\tENSG00000278267 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000\\\\\n",
       "\tENSG00000243485 &  1.584963 &  2.000000 &  3.169925 &  3.169925 &  3.584963 &  3.807355 &  3.700440 &  3.000000 &  3.321928 &  5.087463 &  4.754888 &  4.584963\\\\\n",
       "\tENSG00000237613 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  1.000000 &  0.000000 &  0.000000 &  1.584963 &  1.000000 &  0.000000\\\\\n",
       "\tENSG00000268020 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  0.000000 &  1.000000 &  0.000000 &  0.000000 &  0.000000\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 6 × 12 of type dbl\n",
       "\n",
       "| <!--/--> | mfc_cnt_1 | mfc_cnt_2 | mfc_cnt_3 | mfc_dac_1 | mfc_dac_2 | mfc_dac_3 | yb5_cnt_1 | yb5_cnt_2 | yb5_cnt_3 | yb5_dac_1 | yb5_dac_2 | yb5_dac_3 |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| ENSG00000223972 |  3.584963 |  4.247928 |  5.807355 |  5.554589 |  5.857981 |  5.832890 |  5.906891 |  5.169925 |  5.044394 |  8.124121 |  7.672425 |  7.754888 |\n",
       "| ENSG00000227232 | 11.029287 | 11.253847 | 12.884171 | 11.831703 | 12.026869 | 12.080151 | 11.985842 | 11.326991 | 11.326991 | 12.732167 | 12.275543 | 12.458919 |\n",
       "| ENSG00000278267 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |\n",
       "| ENSG00000243485 |  1.584963 |  2.000000 |  3.169925 |  3.169925 |  3.584963 |  3.807355 |  3.700440 |  3.000000 |  3.321928 |  5.087463 |  4.754888 |  4.584963 |\n",
       "| ENSG00000237613 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  1.000000 |  0.000000 |  0.000000 |  1.584963 |  1.000000 |  0.000000 |\n",
       "| ENSG00000268020 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  0.000000 |  1.000000 |  0.000000 |  0.000000 |  0.000000 |\n",
       "\n"
      ],
      "text/plain": [
       "                mfc_cnt_1 mfc_cnt_2 mfc_cnt_3 mfc_dac_1 mfc_dac_2 mfc_dac_3\n",
       "ENSG00000223972  3.584963  4.247928  5.807355  5.554589  5.857981  5.832890\n",
       "ENSG00000227232 11.029287 11.253847 12.884171 11.831703 12.026869 12.080151\n",
       "ENSG00000278267  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000\n",
       "ENSG00000243485  1.584963  2.000000  3.169925  3.169925  3.584963  3.807355\n",
       "ENSG00000237613  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000\n",
       "ENSG00000268020  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000\n",
       "                yb5_cnt_1 yb5_cnt_2 yb5_cnt_3 yb5_dac_1 yb5_dac_2 yb5_dac_3\n",
       "ENSG00000223972  5.906891  5.169925  5.044394  8.124121  7.672425  7.754888\n",
       "ENSG00000227232 11.985842 11.326991 11.326991 12.732167 12.275543 12.458919\n",
       "ENSG00000278267  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000\n",
       "ENSG00000243485  3.700440  3.000000  3.321928  5.087463  4.754888  4.584963\n",
       "ENSG00000237613  1.000000  0.000000  0.000000  1.584963  1.000000  0.000000\n",
       "ENSG00000268020  0.000000  0.000000  1.000000  0.000000  0.000000  0.000000"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(ccl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IEoEAWiQBQYSgokQBpKvZ22RoEoEAWi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BEUu6BOam61ptnvmHS4/oteZ7wrH6CfTvjIvPOe+g+68glWMpz5tmf9n6CTfXov8/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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "boxplot(ccl)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read the design metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 12 × 3</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>FileName</th><th scope=col>celline</th><th scope=col>treatment</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>mfc_cnt_1</th><td>mfc_cnt_1</td><td>mfc</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>mfc_cnt_2</th><td>mfc_cnt_2</td><td>mfc</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>mfc_cnt_3</th><td>mfc_cnt_3</td><td>mfc</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>mfc_dac_1</th><td>mfc_dac_1</td><td>mfc</td><td>dac</td></tr>\n",
       "\t<tr><th scope=row>mfc_dac_2</th><td>mfc_dac_2</td><td>mfc</td><td>dac</td></tr>\n",
       "\t<tr><th scope=row>mfc_dac_3</th><td>mfc_dac_3</td><td>mfc</td><td>dac</td></tr>\n",
       "\t<tr><th scope=row>yb5_cnt_1</th><td>yb5_cnt_1</td><td>yb5</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>yb5_cnt_2</th><td>yb5_cnt_2</td><td>yb5</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>yb5_cnt_3</th><td>yb5_cnt_3</td><td>yb5</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>yb5_dac_1</th><td>yb5_dac_1</td><td>yb5</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>yb5_dac_2</th><td>yb5_dac_2</td><td>yb5</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>yb5_dac_3</th><td>yb5_dac_3</td><td>yb5</td><td>cnt</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 12 × 3\n",
       "\\begin{tabular}{r|lll}\n",
       "  & FileName & celline & treatment\\\\\n",
       "  & <chr> & <chr> & <chr>\\\\\n",
       "\\hline\n",
       "\tmfc\\_cnt\\_1 & mfc\\_cnt\\_1 & mfc & cnt\\\\\n",
       "\tmfc\\_cnt\\_2 & mfc\\_cnt\\_2 & mfc & cnt\\\\\n",
       "\tmfc\\_cnt\\_3 & mfc\\_cnt\\_3 & mfc & cnt\\\\\n",
       "\tmfc\\_dac\\_1 & mfc\\_dac\\_1 & mfc & dac\\\\\n",
       "\tmfc\\_dac\\_2 & mfc\\_dac\\_2 & mfc & dac\\\\\n",
       "\tmfc\\_dac\\_3 & mfc\\_dac\\_3 & mfc & dac\\\\\n",
       "\tyb5\\_cnt\\_1 & yb5\\_cnt\\_1 & yb5 & cnt\\\\\n",
       "\tyb5\\_cnt\\_2 & yb5\\_cnt\\_2 & yb5 & cnt\\\\\n",
       "\tyb5\\_cnt\\_3 & yb5\\_cnt\\_3 & yb5 & cnt\\\\\n",
       "\tyb5\\_dac\\_1 & yb5\\_dac\\_1 & yb5 & cnt\\\\\n",
       "\tyb5\\_dac\\_2 & yb5\\_dac\\_2 & yb5 & cnt\\\\\n",
       "\tyb5\\_dac\\_3 & yb5\\_dac\\_3 & yb5 & cnt\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 12 × 3\n",
       "\n",
       "| <!--/--> | FileName &lt;chr&gt; | celline &lt;chr&gt; | treatment &lt;chr&gt; |\n",
       "|---|---|---|---|\n",
       "| mfc_cnt_1 | mfc_cnt_1 | mfc | cnt |\n",
       "| mfc_cnt_2 | mfc_cnt_2 | mfc | cnt |\n",
       "| mfc_cnt_3 | mfc_cnt_3 | mfc | cnt |\n",
       "| mfc_dac_1 | mfc_dac_1 | mfc | dac |\n",
       "| mfc_dac_2 | mfc_dac_2 | mfc | dac |\n",
       "| mfc_dac_3 | mfc_dac_3 | mfc | dac |\n",
       "| yb5_cnt_1 | yb5_cnt_1 | yb5 | cnt |\n",
       "| yb5_cnt_2 | yb5_cnt_2 | yb5 | cnt |\n",
       "| yb5_cnt_3 | yb5_cnt_3 | yb5 | cnt |\n",
       "| yb5_dac_1 | yb5_dac_1 | yb5 | cnt |\n",
       "| yb5_dac_2 | yb5_dac_2 | yb5 | cnt |\n",
       "| yb5_dac_3 | yb5_dac_3 | yb5 | cnt |\n",
       "\n"
      ],
      "text/plain": [
       "          FileName  celline treatment\n",
       "mfc_cnt_1 mfc_cnt_1 mfc     cnt      \n",
       "mfc_cnt_2 mfc_cnt_2 mfc     cnt      \n",
       "mfc_cnt_3 mfc_cnt_3 mfc     cnt      \n",
       "mfc_dac_1 mfc_dac_1 mfc     dac      \n",
       "mfc_dac_2 mfc_dac_2 mfc     dac      \n",
       "mfc_dac_3 mfc_dac_3 mfc     dac      \n",
       "yb5_cnt_1 yb5_cnt_1 yb5     cnt      \n",
       "yb5_cnt_2 yb5_cnt_2 yb5     cnt      \n",
       "yb5_cnt_3 yb5_cnt_3 yb5     cnt      \n",
       "yb5_dac_1 yb5_dac_1 yb5     cnt      \n",
       "yb5_dac_2 yb5_dac_2 yb5     cnt      \n",
       "yb5_dac_3 yb5_dac_3 yb5     cnt      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "meta <- read.table(\"metadata.txt\", sep=\"\\t\", header=T)\n",
    "rownames(meta) <- as.character(meta[,1])\n",
    "o <- order(rownames(meta))\n",
    "meta <- meta[o, ]\n",
    "meta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "targets <- meta[, c(\"celline\", \"treatment\")]\n",
    "targets <- as.data.frame(targets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 12 × 2</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>celline</th><th scope=col>treatment</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>mfc_cnt_1</th><td>mfc</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>mfc_cnt_2</th><td>mfc</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>mfc_cnt_3</th><td>mfc</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>mfc_dac_1</th><td>mfc</td><td>dac</td></tr>\n",
       "\t<tr><th scope=row>mfc_dac_2</th><td>mfc</td><td>dac</td></tr>\n",
       "\t<tr><th scope=row>mfc_dac_3</th><td>mfc</td><td>dac</td></tr>\n",
       "\t<tr><th scope=row>yb5_cnt_1</th><td>yb5</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>yb5_cnt_2</th><td>yb5</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>yb5_cnt_3</th><td>yb5</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>yb5_dac_1</th><td>yb5</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>yb5_dac_2</th><td>yb5</td><td>cnt</td></tr>\n",
       "\t<tr><th scope=row>yb5_dac_3</th><td>yb5</td><td>cnt</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 12 × 2\n",
       "\\begin{tabular}{r|ll}\n",
       "  & celline & treatment\\\\\n",
       "  & <chr> & <chr>\\\\\n",
       "\\hline\n",
       "\tmfc\\_cnt\\_1 & mfc & cnt\\\\\n",
       "\tmfc\\_cnt\\_2 & mfc & cnt\\\\\n",
       "\tmfc\\_cnt\\_3 & mfc & cnt\\\\\n",
       "\tmfc\\_dac\\_1 & mfc & dac\\\\\n",
       "\tmfc\\_dac\\_2 & mfc & dac\\\\\n",
       "\tmfc\\_dac\\_3 & mfc & dac\\\\\n",
       "\tyb5\\_cnt\\_1 & yb5 & cnt\\\\\n",
       "\tyb5\\_cnt\\_2 & yb5 & cnt\\\\\n",
       "\tyb5\\_cnt\\_3 & yb5 & cnt\\\\\n",
       "\tyb5\\_dac\\_1 & yb5 & cnt\\\\\n",
       "\tyb5\\_dac\\_2 & yb5 & cnt\\\\\n",
       "\tyb5\\_dac\\_3 & yb5 & cnt\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 12 × 2\n",
       "\n",
       "| <!--/--> | celline &lt;chr&gt; | treatment &lt;chr&gt; |\n",
       "|---|---|---|\n",
       "| mfc_cnt_1 | mfc | cnt |\n",
       "| mfc_cnt_2 | mfc | cnt |\n",
       "| mfc_cnt_3 | mfc | cnt |\n",
       "| mfc_dac_1 | mfc | dac |\n",
       "| mfc_dac_2 | mfc | dac |\n",
       "| mfc_dac_3 | mfc | dac |\n",
       "| yb5_cnt_1 | yb5 | cnt |\n",
       "| yb5_cnt_2 | yb5 | cnt |\n",
       "| yb5_cnt_3 | yb5 | cnt |\n",
       "| yb5_dac_1 | yb5 | cnt |\n",
       "| yb5_dac_2 | yb5 | cnt |\n",
       "| yb5_dac_3 | yb5 | cnt |\n",
       "\n"
      ],
      "text/plain": [
       "          celline treatment\n",
       "mfc_cnt_1 mfc     cnt      \n",
       "mfc_cnt_2 mfc     cnt      \n",
       "mfc_cnt_3 mfc     cnt      \n",
       "mfc_dac_1 mfc     dac      \n",
       "mfc_dac_2 mfc     dac      \n",
       "mfc_dac_3 mfc     dac      \n",
       "yb5_cnt_1 yb5     cnt      \n",
       "yb5_cnt_2 yb5     cnt      \n",
       "yb5_cnt_3 yb5     cnt      \n",
       "yb5_dac_1 yb5     cnt      \n",
       "yb5_dac_2 yb5     cnt      \n",
       "yb5_dac_3 yb5     cnt      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "targets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create design object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "Treat <- factor(paste(targets$celline,targets$treatment,sep=\".\"))\n",
    "design <- model.matrix(~0+Treat)\n",
    "colnames(design) <- levels(Treat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 12 × 3 of type dbl</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>mfc.cnt</th><th scope=col>mfc.dac</th><th scope=col>yb5.cnt</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>1</td><td>0</td><td>0</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>1</td><td>0</td><td>0</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>1</td><td>0</td><td>0</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>0</td><td>1</td><td>0</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>0</td><td>1</td><td>0</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>0</td><td>1</td><td>0</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>0</td><td>0</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>0</td><td>0</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>0</td><td>0</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>10</th><td>0</td><td>0</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>11</th><td>0</td><td>0</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>12</th><td>0</td><td>0</td><td>1</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 12 × 3 of type dbl\n",
       "\\begin{tabular}{r|lll}\n",
       "  & mfc.cnt & mfc.dac & yb5.cnt\\\\\n",
       "\\hline\n",
       "\t1 & 1 & 0 & 0\\\\\n",
       "\t2 & 1 & 0 & 0\\\\\n",
       "\t3 & 1 & 0 & 0\\\\\n",
       "\t4 & 0 & 1 & 0\\\\\n",
       "\t5 & 0 & 1 & 0\\\\\n",
       "\t6 & 0 & 1 & 0\\\\\n",
       "\t7 & 0 & 0 & 1\\\\\n",
       "\t8 & 0 & 0 & 1\\\\\n",
       "\t9 & 0 & 0 & 1\\\\\n",
       "\t10 & 0 & 0 & 1\\\\\n",
       "\t11 & 0 & 0 & 1\\\\\n",
       "\t12 & 0 & 0 & 1\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 12 × 3 of type dbl\n",
       "\n",
       "| <!--/--> | mfc.cnt | mfc.dac | yb5.cnt |\n",
       "|---|---|---|---|\n",
       "| 1 | 1 | 0 | 0 |\n",
       "| 2 | 1 | 0 | 0 |\n",
       "| 3 | 1 | 0 | 0 |\n",
       "| 4 | 0 | 1 | 0 |\n",
       "| 5 | 0 | 1 | 0 |\n",
       "| 6 | 0 | 1 | 0 |\n",
       "| 7 | 0 | 0 | 1 |\n",
       "| 8 | 0 | 0 | 1 |\n",
       "| 9 | 0 | 0 | 1 |\n",
       "| 10 | 0 | 0 | 1 |\n",
       "| 11 | 0 | 0 | 1 |\n",
       "| 12 | 0 | 0 | 1 |\n",
       "\n"
      ],
      "text/plain": [
       "   mfc.cnt mfc.dac yb5.cnt\n",
       "1  1       0       0      \n",
       "2  1       0       0      \n",
       "3  1       0       0      \n",
       "4  0       1       0      \n",
       "5  0       1       0      \n",
       "6  0       1       0      \n",
       "7  0       0       1      \n",
       "8  0       0       1      \n",
       "9  0       0       1      \n",
       "10 0       0       1      \n",
       "11 0       0       1      \n",
       "12 0       0       1      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "design"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Do the dispersion estimate and model fitting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "y <- DGEList(counts=cc)\n",
    "y <- estimateDisp(y, design)\n",
    "fit <- glmFit(y, design)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the biological question with a contrast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 3 × 1 of type dbl</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>mfc.cnt - mfc.dac</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>mfc.cnt</th><td> 1</td></tr>\n",
       "\t<tr><th scope=row>mfc.dac</th><td>-1</td></tr>\n",
       "\t<tr><th scope=row>yb5.cnt</th><td> 0</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 3 × 1 of type dbl\n",
       "\\begin{tabular}{r|l}\n",
       "  & mfc.cnt - mfc.dac\\\\\n",
       "\\hline\n",
       "\tmfc.cnt &  1\\\\\n",
       "\tmfc.dac & -1\\\\\n",
       "\tyb5.cnt &  0\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 3 × 1 of type dbl\n",
       "\n",
       "| <!--/--> | mfc.cnt - mfc.dac |\n",
       "|---|---|\n",
       "| mfc.cnt |  1 |\n",
       "| mfc.dac | -1 |\n",
       "| yb5.cnt |  0 |\n",
       "\n"
      ],
      "text/plain": [
       "         Contrasts\n",
       "Levels    mfc.cnt - mfc.dac\n",
       "  mfc.cnt  1               \n",
       "  mfc.dac -1               \n",
       "  yb5.cnt  0               "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cm <- makeContrasts( mfc.cnt-mfc.dac, levels=design)\n",
    "cm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Do the model fit and get top genes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "lrt <- glmLRT(fit, contrast=cm)\n",
    "topOnes <- topTags(lrt, n=dim(cc)[1])$table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 50 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>logFC</th><th scope=col>logCPM</th><th scope=col>LR</th><th scope=col>PValue</th><th scope=col>FDR</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>ENSG00000233276</th><td>-5.703099</td><td> 5.9162987</td><td>243.92073</td><td>5.493388e-55</td><td>3.185726e-50</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000141756</th><td>-2.501588</td><td> 6.0074403</td><td>193.90297</td><td>4.471368e-44</td><td>1.296518e-39</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000226383</th><td>-5.534574</td><td> 3.5313765</td><td>173.87071</td><td>1.056378e-39</td><td>2.042050e-35</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000164850</th><td>-2.078655</td><td> 5.0686256</td><td>173.16300</td><td>1.507899e-39</td><td>2.186152e-35</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000084207</th><td>-4.253757</td><td> 8.2322890</td><td>170.89071</td><td>4.727468e-39</td><td>5.483106e-35</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000163362</th><td>-2.521056</td><td> 5.2121847</td><td>151.69374</td><td>7.392005e-35</td><td>7.144619e-31</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000135926</th><td>-2.922313</td><td> 5.4675657</td><td>149.71721</td><td>1.998809e-34</td><td>1.540543e-30</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000104870</th><td>-3.433664</td><td> 3.5342194</td><td>149.59540</td><td>2.125180e-34</td><td>1.540543e-30</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000180964</th><td>-4.335465</td><td> 3.5329774</td><td>141.26409</td><td>1.408627e-32</td><td>9.076565e-29</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000104518</th><td>-5.387493</td><td> 3.1888639</td><td>123.85316</td><td>9.071447e-29</td><td>5.260713e-25</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000197582</th><td>-5.278091</td><td> 4.5133934</td><td>116.55376</td><td>3.595004e-27</td><td>1.895286e-23</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000204019</th><td>-9.918227</td><td>-0.6362576</td><td>101.07093</td><td>8.874789e-24</td><td>4.288889e-20</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000182704</th><td>-1.798445</td><td> 5.1259700</td><td> 95.06534</td><td>1.842038e-22</td><td>8.217189e-19</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000105219</th><td>-4.317743</td><td> 0.5699180</td><td> 94.51764</td><td>2.429186e-22</td><td>1.006238e-18</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000102024</th><td>-2.757694</td><td> 4.2441337</td><td> 83.43320</td><td>6.590574e-20</td><td>2.548004e-16</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000172139</th><td>-1.993189</td><td> 4.0623091</td><td> 79.84664</td><td>4.046272e-19</td><td>1.466571e-15</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000160447</th><td>-2.468747</td><td> 3.9630904</td><td> 77.24381</td><td>1.511047e-18</td><td>5.154625e-15</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000206557</th><td>-3.233202</td><td> 0.8473956</td><td> 73.38309</td><td>1.067772e-17</td><td>3.440123e-14</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000142273</th><td>-3.679722</td><td> 2.0576244</td><td> 73.07182</td><td>1.250169e-17</td><td>3.815780e-14</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000185269</th><td>-2.818678</td><td> 7.0564054</td><td> 71.85205</td><td>2.319519e-17</td><td>6.725676e-14</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000100504</th><td>-1.225585</td><td> 6.3600612</td><td> 69.98786</td><td>5.967063e-17</td><td>1.647819e-13</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000141574</th><td>-2.059939</td><td> 2.7079635</td><td> 65.11322</td><td>7.071611e-16</td><td>1.864077e-12</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000180667</th><td>-3.019311</td><td> 3.8312463</td><td> 64.82469</td><td>8.186680e-16</td><td>2.064182e-12</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000229131</th><td>-8.653637</td><td>-1.7872946</td><td> 59.55112</td><td>1.191584e-14</td><td>2.879263e-11</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000105974</th><td> 2.641631</td><td> 6.6239356</td><td> 58.33806</td><td>2.207323e-14</td><td>5.120284e-11</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000166342</th><td>-5.481015</td><td>-1.3646599</td><td> 57.79505</td><td>2.909009e-14</td><td>6.263842e-11</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000182534</th><td>-1.824629</td><td> 5.2405685</td><td> 57.79011</td><td>2.916329e-14</td><td>6.263842e-11</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000074416</th><td>-1.734053</td><td> 3.9329130</td><td> 57.64903</td><td>3.133174e-14</td><td>6.489250e-11</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000173267</th><td>-3.525948</td><td> 1.1458353</td><td> 55.80017</td><td>8.022465e-14</td><td>1.604272e-10</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000136425</th><td>-3.066962</td><td> 2.9669399</td><td> 54.00445</td><td>2.000356e-13</td><td>3.866822e-10</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000100373</th><td>-4.828312</td><td> 0.6886064</td><td> 53.83824</td><td>2.176943e-13</td><td>4.072428e-10</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000157600</th><td> 1.326333</td><td> 5.9063247</td><td> 53.36695</td><td>2.767130e-13</td><td>5.006024e-10</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000211897</th><td>-7.418733</td><td>-2.7777059</td><td> 53.30992</td><td>2.848648e-13</td><td>5.006024e-10</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000006555</th><td>-4.293480</td><td> 3.8714568</td><td> 52.87900</td><td>3.547430e-13</td><td>6.050663e-10</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000162433</th><td> 1.328405</td><td> 4.3254864</td><td> 52.58738</td><td>4.115262e-13</td><td>6.818636e-10</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000251026</th><td>-4.412753</td><td> 0.5830247</td><td> 52.28839</td><td>4.791981e-13</td><td>7.719348e-10</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000114638</th><td>-5.507392</td><td>-1.8435934</td><td> 52.07641</td><td>5.338234e-13</td><td>8.366888e-10</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000126838</th><td>-3.191187</td><td>-1.0053643</td><td> 50.66550</td><td>1.095278e-12</td><td>1.671509e-09</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000269842</th><td>-7.331674</td><td>-2.8392675</td><td> 50.53497</td><td>1.170602e-12</td><td>1.740655e-09</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000156711</th><td>-1.204530</td><td> 4.7882501</td><td> 49.93310</td><td>1.590781e-12</td><td>2.306314e-09</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000211892</th><td>-7.458537</td><td>-1.1134785</td><td> 49.14284</td><td>2.379853e-12</td><td>3.366157e-09</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000095321</th><td>-2.193409</td><td> 4.1892771</td><td> 49.03405</td><td>2.515581e-12</td><td>3.473418e-09</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000230159</th><td>-7.250118</td><td>-2.8993756</td><td> 48.23830</td><td>3.774439e-12</td><td>5.090401e-09</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000107742</th><td>-3.278429</td><td> 1.2324994</td><td> 47.83923</td><td>4.626414e-12</td><td>6.097613e-09</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000129038</th><td>-1.426747</td><td> 4.4651952</td><td> 47.08209</td><td>6.807482e-12</td><td>8.772877e-09</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000237523</th><td>-3.369142</td><td> 1.5944370</td><td> 46.82920</td><td>7.745071e-12</td><td>9.764177e-09</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000137642</th><td>-1.455876</td><td> 6.8786362</td><td> 46.72793</td><td>8.155828e-12</td><td>1.006325e-08</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000261578</th><td>-2.321949</td><td> 1.9443346</td><td> 46.47956</td><td>9.257932e-12</td><td>1.118512e-08</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000249917</th><td>-2.607830</td><td> 1.3151994</td><td> 46.34441</td><td>9.919007e-12</td><td>1.173925e-08</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000134759</th><td> 0.969678</td><td> 7.6116472</td><td> 45.99307</td><td>1.186723e-11</td><td>1.376409e-08</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 50 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & logFC & logCPM & LR & PValue & FDR\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tENSG00000233276 & -5.703099 &  5.9162987 & 243.92073 & 5.493388e-55 & 3.185726e-50\\\\\n",
       "\tENSG00000141756 & -2.501588 &  6.0074403 & 193.90297 & 4.471368e-44 & 1.296518e-39\\\\\n",
       "\tENSG00000226383 & -5.534574 &  3.5313765 & 173.87071 & 1.056378e-39 & 2.042050e-35\\\\\n",
       "\tENSG00000164850 & -2.078655 &  5.0686256 & 173.16300 & 1.507899e-39 & 2.186152e-35\\\\\n",
       "\tENSG00000084207 & -4.253757 &  8.2322890 & 170.89071 & 4.727468e-39 & 5.483106e-35\\\\\n",
       "\tENSG00000163362 & -2.521056 &  5.2121847 & 151.69374 & 7.392005e-35 & 7.144619e-31\\\\\n",
       "\tENSG00000135926 & -2.922313 &  5.4675657 & 149.71721 & 1.998809e-34 & 1.540543e-30\\\\\n",
       "\tENSG00000104870 & -3.433664 &  3.5342194 & 149.59540 & 2.125180e-34 & 1.540543e-30\\\\\n",
       "\tENSG00000180964 & -4.335465 &  3.5329774 & 141.26409 & 1.408627e-32 & 9.076565e-29\\\\\n",
       "\tENSG00000104518 & -5.387493 &  3.1888639 & 123.85316 & 9.071447e-29 & 5.260713e-25\\\\\n",
       "\tENSG00000197582 & -5.278091 &  4.5133934 & 116.55376 & 3.595004e-27 & 1.895286e-23\\\\\n",
       "\tENSG00000204019 & -9.918227 & -0.6362576 & 101.07093 & 8.874789e-24 & 4.288889e-20\\\\\n",
       "\tENSG00000182704 & -1.798445 &  5.1259700 &  95.06534 & 1.842038e-22 & 8.217189e-19\\\\\n",
       "\tENSG00000105219 & -4.317743 &  0.5699180 &  94.51764 & 2.429186e-22 & 1.006238e-18\\\\\n",
       "\tENSG00000102024 & -2.757694 &  4.2441337 &  83.43320 & 6.590574e-20 & 2.548004e-16\\\\\n",
       "\tENSG00000172139 & -1.993189 &  4.0623091 &  79.84664 & 4.046272e-19 & 1.466571e-15\\\\\n",
       "\tENSG00000160447 & -2.468747 &  3.9630904 &  77.24381 & 1.511047e-18 & 5.154625e-15\\\\\n",
       "\tENSG00000206557 & -3.233202 &  0.8473956 &  73.38309 & 1.067772e-17 & 3.440123e-14\\\\\n",
       "\tENSG00000142273 & -3.679722 &  2.0576244 &  73.07182 & 1.250169e-17 & 3.815780e-14\\\\\n",
       "\tENSG00000185269 & -2.818678 &  7.0564054 &  71.85205 & 2.319519e-17 & 6.725676e-14\\\\\n",
       "\tENSG00000100504 & -1.225585 &  6.3600612 &  69.98786 & 5.967063e-17 & 1.647819e-13\\\\\n",
       "\tENSG00000141574 & -2.059939 &  2.7079635 &  65.11322 & 7.071611e-16 & 1.864077e-12\\\\\n",
       "\tENSG00000180667 & -3.019311 &  3.8312463 &  64.82469 & 8.186680e-16 & 2.064182e-12\\\\\n",
       "\tENSG00000229131 & -8.653637 & -1.7872946 &  59.55112 & 1.191584e-14 & 2.879263e-11\\\\\n",
       "\tENSG00000105974 &  2.641631 &  6.6239356 &  58.33806 & 2.207323e-14 & 5.120284e-11\\\\\n",
       "\tENSG00000166342 & -5.481015 & -1.3646599 &  57.79505 & 2.909009e-14 & 6.263842e-11\\\\\n",
       "\tENSG00000182534 & -1.824629 &  5.2405685 &  57.79011 & 2.916329e-14 & 6.263842e-11\\\\\n",
       "\tENSG00000074416 & -1.734053 &  3.9329130 &  57.64903 & 3.133174e-14 & 6.489250e-11\\\\\n",
       "\tENSG00000173267 & -3.525948 &  1.1458353 &  55.80017 & 8.022465e-14 & 1.604272e-10\\\\\n",
       "\tENSG00000136425 & -3.066962 &  2.9669399 &  54.00445 & 2.000356e-13 & 3.866822e-10\\\\\n",
       "\tENSG00000100373 & -4.828312 &  0.6886064 &  53.83824 & 2.176943e-13 & 4.072428e-10\\\\\n",
       "\tENSG00000157600 &  1.326333 &  5.9063247 &  53.36695 & 2.767130e-13 & 5.006024e-10\\\\\n",
       "\tENSG00000211897 & -7.418733 & -2.7777059 &  53.30992 & 2.848648e-13 & 5.006024e-10\\\\\n",
       "\tENSG00000006555 & -4.293480 &  3.8714568 &  52.87900 & 3.547430e-13 & 6.050663e-10\\\\\n",
       "\tENSG00000162433 &  1.328405 &  4.3254864 &  52.58738 & 4.115262e-13 & 6.818636e-10\\\\\n",
       "\tENSG00000251026 & -4.412753 &  0.5830247 &  52.28839 & 4.791981e-13 & 7.719348e-10\\\\\n",
       "\tENSG00000114638 & -5.507392 & -1.8435934 &  52.07641 & 5.338234e-13 & 8.366888e-10\\\\\n",
       "\tENSG00000126838 & -3.191187 & -1.0053643 &  50.66550 & 1.095278e-12 & 1.671509e-09\\\\\n",
       "\tENSG00000269842 & -7.331674 & -2.8392675 &  50.53497 & 1.170602e-12 & 1.740655e-09\\\\\n",
       "\tENSG00000156711 & -1.204530 &  4.7882501 &  49.93310 & 1.590781e-12 & 2.306314e-09\\\\\n",
       "\tENSG00000211892 & -7.458537 & -1.1134785 &  49.14284 & 2.379853e-12 & 3.366157e-09\\\\\n",
       "\tENSG00000095321 & -2.193409 &  4.1892771 &  49.03405 & 2.515581e-12 & 3.473418e-09\\\\\n",
       "\tENSG00000230159 & -7.250118 & -2.8993756 &  48.23830 & 3.774439e-12 & 5.090401e-09\\\\\n",
       "\tENSG00000107742 & -3.278429 &  1.2324994 &  47.83923 & 4.626414e-12 & 6.097613e-09\\\\\n",
       "\tENSG00000129038 & -1.426747 &  4.4651952 &  47.08209 & 6.807482e-12 & 8.772877e-09\\\\\n",
       "\tENSG00000237523 & -3.369142 &  1.5944370 &  46.82920 & 7.745071e-12 & 9.764177e-09\\\\\n",
       "\tENSG00000137642 & -1.455876 &  6.8786362 &  46.72793 & 8.155828e-12 & 1.006325e-08\\\\\n",
       "\tENSG00000261578 & -2.321949 &  1.9443346 &  46.47956 & 9.257932e-12 & 1.118512e-08\\\\\n",
       "\tENSG00000249917 & -2.607830 &  1.3151994 &  46.34441 & 9.919007e-12 & 1.173925e-08\\\\\n",
       "\tENSG00000134759 &  0.969678 &  7.6116472 &  45.99307 & 1.186723e-11 & 1.376409e-08\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 50 × 5\n",
       "\n",
       "| <!--/--> | logFC &lt;dbl&gt; | logCPM &lt;dbl&gt; | LR &lt;dbl&gt; | PValue &lt;dbl&gt; | FDR &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| ENSG00000233276 | -5.703099 |  5.9162987 | 243.92073 | 5.493388e-55 | 3.185726e-50 |\n",
       "| ENSG00000141756 | -2.501588 |  6.0074403 | 193.90297 | 4.471368e-44 | 1.296518e-39 |\n",
       "| ENSG00000226383 | -5.534574 |  3.5313765 | 173.87071 | 1.056378e-39 | 2.042050e-35 |\n",
       "| ENSG00000164850 | -2.078655 |  5.0686256 | 173.16300 | 1.507899e-39 | 2.186152e-35 |\n",
       "| ENSG00000084207 | -4.253757 |  8.2322890 | 170.89071 | 4.727468e-39 | 5.483106e-35 |\n",
       "| ENSG00000163362 | -2.521056 |  5.2121847 | 151.69374 | 7.392005e-35 | 7.144619e-31 |\n",
       "| ENSG00000135926 | -2.922313 |  5.4675657 | 149.71721 | 1.998809e-34 | 1.540543e-30 |\n",
       "| ENSG00000104870 | -3.433664 |  3.5342194 | 149.59540 | 2.125180e-34 | 1.540543e-30 |\n",
       "| ENSG00000180964 | -4.335465 |  3.5329774 | 141.26409 | 1.408627e-32 | 9.076565e-29 |\n",
       "| ENSG00000104518 | -5.387493 |  3.1888639 | 123.85316 | 9.071447e-29 | 5.260713e-25 |\n",
       "| ENSG00000197582 | -5.278091 |  4.5133934 | 116.55376 | 3.595004e-27 | 1.895286e-23 |\n",
       "| ENSG00000204019 | -9.918227 | -0.6362576 | 101.07093 | 8.874789e-24 | 4.288889e-20 |\n",
       "| ENSG00000182704 | -1.798445 |  5.1259700 |  95.06534 | 1.842038e-22 | 8.217189e-19 |\n",
       "| ENSG00000105219 | -4.317743 |  0.5699180 |  94.51764 | 2.429186e-22 | 1.006238e-18 |\n",
       "| ENSG00000102024 | -2.757694 |  4.2441337 |  83.43320 | 6.590574e-20 | 2.548004e-16 |\n",
       "| ENSG00000172139 | -1.993189 |  4.0623091 |  79.84664 | 4.046272e-19 | 1.466571e-15 |\n",
       "| ENSG00000160447 | -2.468747 |  3.9630904 |  77.24381 | 1.511047e-18 | 5.154625e-15 |\n",
       "| ENSG00000206557 | -3.233202 |  0.8473956 |  73.38309 | 1.067772e-17 | 3.440123e-14 |\n",
       "| ENSG00000142273 | -3.679722 |  2.0576244 |  73.07182 | 1.250169e-17 | 3.815780e-14 |\n",
       "| ENSG00000185269 | -2.818678 |  7.0564054 |  71.85205 | 2.319519e-17 | 6.725676e-14 |\n",
       "| ENSG00000100504 | -1.225585 |  6.3600612 |  69.98786 | 5.967063e-17 | 1.647819e-13 |\n",
       "| ENSG00000141574 | -2.059939 |  2.7079635 |  65.11322 | 7.071611e-16 | 1.864077e-12 |\n",
       "| ENSG00000180667 | -3.019311 |  3.8312463 |  64.82469 | 8.186680e-16 | 2.064182e-12 |\n",
       "| ENSG00000229131 | -8.653637 | -1.7872946 |  59.55112 | 1.191584e-14 | 2.879263e-11 |\n",
       "| ENSG00000105974 |  2.641631 |  6.6239356 |  58.33806 | 2.207323e-14 | 5.120284e-11 |\n",
       "| ENSG00000166342 | -5.481015 | -1.3646599 |  57.79505 | 2.909009e-14 | 6.263842e-11 |\n",
       "| ENSG00000182534 | -1.824629 |  5.2405685 |  57.79011 | 2.916329e-14 | 6.263842e-11 |\n",
       "| ENSG00000074416 | -1.734053 |  3.9329130 |  57.64903 | 3.133174e-14 | 6.489250e-11 |\n",
       "| ENSG00000173267 | -3.525948 |  1.1458353 |  55.80017 | 8.022465e-14 | 1.604272e-10 |\n",
       "| ENSG00000136425 | -3.066962 |  2.9669399 |  54.00445 | 2.000356e-13 | 3.866822e-10 |\n",
       "| ENSG00000100373 | -4.828312 |  0.6886064 |  53.83824 | 2.176943e-13 | 4.072428e-10 |\n",
       "| ENSG00000157600 |  1.326333 |  5.9063247 |  53.36695 | 2.767130e-13 | 5.006024e-10 |\n",
       "| ENSG00000211897 | -7.418733 | -2.7777059 |  53.30992 | 2.848648e-13 | 5.006024e-10 |\n",
       "| ENSG00000006555 | -4.293480 |  3.8714568 |  52.87900 | 3.547430e-13 | 6.050663e-10 |\n",
       "| ENSG00000162433 |  1.328405 |  4.3254864 |  52.58738 | 4.115262e-13 | 6.818636e-10 |\n",
       "| ENSG00000251026 | -4.412753 |  0.5830247 |  52.28839 | 4.791981e-13 | 7.719348e-10 |\n",
       "| ENSG00000114638 | -5.507392 | -1.8435934 |  52.07641 | 5.338234e-13 | 8.366888e-10 |\n",
       "| ENSG00000126838 | -3.191187 | -1.0053643 |  50.66550 | 1.095278e-12 | 1.671509e-09 |\n",
       "| ENSG00000269842 | -7.331674 | -2.8392675 |  50.53497 | 1.170602e-12 | 1.740655e-09 |\n",
       "| ENSG00000156711 | -1.204530 |  4.7882501 |  49.93310 | 1.590781e-12 | 2.306314e-09 |\n",
       "| ENSG00000211892 | -7.458537 | -1.1134785 |  49.14284 | 2.379853e-12 | 3.366157e-09 |\n",
       "| ENSG00000095321 | -2.193409 |  4.1892771 |  49.03405 | 2.515581e-12 | 3.473418e-09 |\n",
       "| ENSG00000230159 | -7.250118 | -2.8993756 |  48.23830 | 3.774439e-12 | 5.090401e-09 |\n",
       "| ENSG00000107742 | -3.278429 |  1.2324994 |  47.83923 | 4.626414e-12 | 6.097613e-09 |\n",
       "| ENSG00000129038 | -1.426747 |  4.4651952 |  47.08209 | 6.807482e-12 | 8.772877e-09 |\n",
       "| ENSG00000237523 | -3.369142 |  1.5944370 |  46.82920 | 7.745071e-12 | 9.764177e-09 |\n",
       "| ENSG00000137642 | -1.455876 |  6.8786362 |  46.72793 | 8.155828e-12 | 1.006325e-08 |\n",
       "| ENSG00000261578 | -2.321949 |  1.9443346 |  46.47956 | 9.257932e-12 | 1.118512e-08 |\n",
       "| ENSG00000249917 | -2.607830 |  1.3151994 |  46.34441 | 9.919007e-12 | 1.173925e-08 |\n",
       "| ENSG00000134759 |  0.969678 |  7.6116472 |  45.99307 | 1.186723e-11 | 1.376409e-08 |\n",
       "\n"
      ],
      "text/plain": [
       "                logFC     logCPM     LR        PValue       FDR         \n",
       "ENSG00000233276 -5.703099  5.9162987 243.92073 5.493388e-55 3.185726e-50\n",
       "ENSG00000141756 -2.501588  6.0074403 193.90297 4.471368e-44 1.296518e-39\n",
       "ENSG00000226383 -5.534574  3.5313765 173.87071 1.056378e-39 2.042050e-35\n",
       "ENSG00000164850 -2.078655  5.0686256 173.16300 1.507899e-39 2.186152e-35\n",
       "ENSG00000084207 -4.253757  8.2322890 170.89071 4.727468e-39 5.483106e-35\n",
       "ENSG00000163362 -2.521056  5.2121847 151.69374 7.392005e-35 7.144619e-31\n",
       "ENSG00000135926 -2.922313  5.4675657 149.71721 1.998809e-34 1.540543e-30\n",
       "ENSG00000104870 -3.433664  3.5342194 149.59540 2.125180e-34 1.540543e-30\n",
       "ENSG00000180964 -4.335465  3.5329774 141.26409 1.408627e-32 9.076565e-29\n",
       "ENSG00000104518 -5.387493  3.1888639 123.85316 9.071447e-29 5.260713e-25\n",
       "ENSG00000197582 -5.278091  4.5133934 116.55376 3.595004e-27 1.895286e-23\n",
       "ENSG00000204019 -9.918227 -0.6362576 101.07093 8.874789e-24 4.288889e-20\n",
       "ENSG00000182704 -1.798445  5.1259700  95.06534 1.842038e-22 8.217189e-19\n",
       "ENSG00000105219 -4.317743  0.5699180  94.51764 2.429186e-22 1.006238e-18\n",
       "ENSG00000102024 -2.757694  4.2441337  83.43320 6.590574e-20 2.548004e-16\n",
       "ENSG00000172139 -1.993189  4.0623091  79.84664 4.046272e-19 1.466571e-15\n",
       "ENSG00000160447 -2.468747  3.9630904  77.24381 1.511047e-18 5.154625e-15\n",
       "ENSG00000206557 -3.233202  0.8473956  73.38309 1.067772e-17 3.440123e-14\n",
       "ENSG00000142273 -3.679722  2.0576244  73.07182 1.250169e-17 3.815780e-14\n",
       "ENSG00000185269 -2.818678  7.0564054  71.85205 2.319519e-17 6.725676e-14\n",
       "ENSG00000100504 -1.225585  6.3600612  69.98786 5.967063e-17 1.647819e-13\n",
       "ENSG00000141574 -2.059939  2.7079635  65.11322 7.071611e-16 1.864077e-12\n",
       "ENSG00000180667 -3.019311  3.8312463  64.82469 8.186680e-16 2.064182e-12\n",
       "ENSG00000229131 -8.653637 -1.7872946  59.55112 1.191584e-14 2.879263e-11\n",
       "ENSG00000105974  2.641631  6.6239356  58.33806 2.207323e-14 5.120284e-11\n",
       "ENSG00000166342 -5.481015 -1.3646599  57.79505 2.909009e-14 6.263842e-11\n",
       "ENSG00000182534 -1.824629  5.2405685  57.79011 2.916329e-14 6.263842e-11\n",
       "ENSG00000074416 -1.734053  3.9329130  57.64903 3.133174e-14 6.489250e-11\n",
       "ENSG00000173267 -3.525948  1.1458353  55.80017 8.022465e-14 1.604272e-10\n",
       "ENSG00000136425 -3.066962  2.9669399  54.00445 2.000356e-13 3.866822e-10\n",
       "ENSG00000100373 -4.828312  0.6886064  53.83824 2.176943e-13 4.072428e-10\n",
       "ENSG00000157600  1.326333  5.9063247  53.36695 2.767130e-13 5.006024e-10\n",
       "ENSG00000211897 -7.418733 -2.7777059  53.30992 2.848648e-13 5.006024e-10\n",
       "ENSG00000006555 -4.293480  3.8714568  52.87900 3.547430e-13 6.050663e-10\n",
       "ENSG00000162433  1.328405  4.3254864  52.58738 4.115262e-13 6.818636e-10\n",
       "ENSG00000251026 -4.412753  0.5830247  52.28839 4.791981e-13 7.719348e-10\n",
       "ENSG00000114638 -5.507392 -1.8435934  52.07641 5.338234e-13 8.366888e-10\n",
       "ENSG00000126838 -3.191187 -1.0053643  50.66550 1.095278e-12 1.671509e-09\n",
       "ENSG00000269842 -7.331674 -2.8392675  50.53497 1.170602e-12 1.740655e-09\n",
       "ENSG00000156711 -1.204530  4.7882501  49.93310 1.590781e-12 2.306314e-09\n",
       "ENSG00000211892 -7.458537 -1.1134785  49.14284 2.379853e-12 3.366157e-09\n",
       "ENSG00000095321 -2.193409  4.1892771  49.03405 2.515581e-12 3.473418e-09\n",
       "ENSG00000230159 -7.250118 -2.8993756  48.23830 3.774439e-12 5.090401e-09\n",
       "ENSG00000107742 -3.278429  1.2324994  47.83923 4.626414e-12 6.097613e-09\n",
       "ENSG00000129038 -1.426747  4.4651952  47.08209 6.807482e-12 8.772877e-09\n",
       "ENSG00000237523 -3.369142  1.5944370  46.82920 7.745071e-12 9.764177e-09\n",
       "ENSG00000137642 -1.455876  6.8786362  46.72793 8.155828e-12 1.006325e-08\n",
       "ENSG00000261578 -2.321949  1.9443346  46.47956 9.257932e-12 1.118512e-08\n",
       "ENSG00000249917 -2.607830  1.3151994  46.34441 9.919007e-12 1.173925e-08\n",
       "ENSG00000134759  0.969678  7.6116472  45.99307 1.186723e-11 1.376409e-08"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(topOnes, n=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple pairwise comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "cc2 <- cc[,1:6]\n",
    "group <- factor(c(1,1,1,2,2,2))\n",
    "y <- DGEList(counts=cc2,group=group)\n",
    "y <- calcNormFactors(y)\n",
    "design <- model.matrix(~group)\n",
    "y <- estimateDisp(y,design)\n",
    "\n",
    "fit <- glmFit(y,design)\n",
    "lrt <- glmLRT(fit)\n",
    "topOnes_pairwise <- topTags(lrt, n=dim(cc2)[1])$table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>logFC</th><th scope=col>logCPM</th><th scope=col>LR</th><th scope=col>PValue</th><th scope=col>FDR</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>ENSG00000130600</th><td> 5.505566</td><td>9.008124</td><td>1041.4478</td><td>1.758697e-228</td><td>1.019903e-223</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000135480</th><td> 4.606337</td><td>5.098251</td><td> 792.1216</td><td>2.786028e-174</td><td>8.078366e-170</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000070985</th><td> 6.610261</td><td>2.469754</td><td> 625.4816</td><td>4.803161e-138</td><td>9.284831e-134</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000147174</th><td> 3.857756</td><td>3.692567</td><td> 606.1356</td><td>7.749302e-134</td><td>1.123494e-129</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000105974</th><td>-2.766143</td><td>5.721369</td><td> 605.2399</td><td>1.213603e-133</td><td>1.407585e-129</td></tr>\n",
       "\t<tr><th scope=row>ENSG00000198883</th><td> 7.718994</td><td>2.154230</td><td> 589.9396</td><td>2.582475e-130</td><td>2.496048e-126</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & logFC & logCPM & LR & PValue & FDR\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tENSG00000130600 &  5.505566 & 9.008124 & 1041.4478 & 1.758697e-228 & 1.019903e-223\\\\\n",
       "\tENSG00000135480 &  4.606337 & 5.098251 &  792.1216 & 2.786028e-174 & 8.078366e-170\\\\\n",
       "\tENSG00000070985 &  6.610261 & 2.469754 &  625.4816 & 4.803161e-138 & 9.284831e-134\\\\\n",
       "\tENSG00000147174 &  3.857756 & 3.692567 &  606.1356 & 7.749302e-134 & 1.123494e-129\\\\\n",
       "\tENSG00000105974 & -2.766143 & 5.721369 &  605.2399 & 1.213603e-133 & 1.407585e-129\\\\\n",
       "\tENSG00000198883 &  7.718994 & 2.154230 &  589.9396 & 2.582475e-130 & 2.496048e-126\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 5\n",
       "\n",
       "| <!--/--> | logFC &lt;dbl&gt; | logCPM &lt;dbl&gt; | LR &lt;dbl&gt; | PValue &lt;dbl&gt; | FDR &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| ENSG00000130600 |  5.505566 | 9.008124 | 1041.4478 | 1.758697e-228 | 1.019903e-223 |\n",
       "| ENSG00000135480 |  4.606337 | 5.098251 |  792.1216 | 2.786028e-174 | 8.078366e-170 |\n",
       "| ENSG00000070985 |  6.610261 | 2.469754 |  625.4816 | 4.803161e-138 | 9.284831e-134 |\n",
       "| ENSG00000147174 |  3.857756 | 3.692567 |  606.1356 | 7.749302e-134 | 1.123494e-129 |\n",
       "| ENSG00000105974 | -2.766143 | 5.721369 |  605.2399 | 1.213603e-133 | 1.407585e-129 |\n",
       "| ENSG00000198883 |  7.718994 | 2.154230 |  589.9396 | 2.582475e-130 | 2.496048e-126 |\n",
       "\n"
      ],
      "text/plain": [
       "                logFC     logCPM   LR        PValue        FDR          \n",
       "ENSG00000130600  5.505566 9.008124 1041.4478 1.758697e-228 1.019903e-223\n",
       "ENSG00000135480  4.606337 5.098251  792.1216 2.786028e-174 8.078366e-170\n",
       "ENSG00000070985  6.610261 2.469754  625.4816 4.803161e-138 9.284831e-134\n",
       "ENSG00000147174  3.857756 3.692567  606.1356 7.749302e-134 1.123494e-129\n",
       "ENSG00000105974 -2.766143 5.721369  605.2399 1.213603e-133 1.407585e-129\n",
       "ENSG00000198883  7.718994 2.154230  589.9396 2.582475e-130 2.496048e-126"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(topOnes_pairwise)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "207"
      ],
      "text/latex": [
       "207"
      ],
      "text/markdown": [
       "207"
      ],
      "text/plain": [
       "[1] 207"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "length(intersect(rownames(topOnes)[1:500], rownames(topOnes_pairwise)[1:500]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Deseq2 pairwise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: S4Vectors\n",
      "\n",
      "Loading required package: stats4\n",
      "\n",
      "Loading required package: BiocGenerics\n",
      "\n",
      "Loading required package: parallel\n",
      "\n",
      "\n",
      "Attaching package: ‘BiocGenerics’\n",
      "\n",
      "\n",
      "The following objects are masked from ‘package:parallel’:\n",
      "\n",
      "    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,\n",
      "    clusterExport, clusterMap, parApply, parCapply, parLapply,\n",
      "    parLapplyLB, parRapply, parSapply, parSapplyLB\n",
      "\n",
      "\n",
      "The following object is masked from ‘package:limma’:\n",
      "\n",
      "    plotMA\n",
      "\n",
      "\n",
      "The following objects are masked from ‘package:stats’:\n",
      "\n",
      "    IQR, mad, sd, var, xtabs\n",
      "\n",
      "\n",
      "The following objects are masked from ‘package:base’:\n",
      "\n",
      "    Filter, Find, Map, Position, Reduce, anyDuplicated, append,\n",
      "    as.data.frame, basename, cbind, colnames, dirname, do.call,\n",
      "    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,\n",
      "    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,\n",
      "    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,\n",
      "    tapply, union, unique, unsplit, which.max, which.min\n",
      "\n",
      "\n",
      "\n",
      "Attaching package: ‘S4Vectors’\n",
      "\n",
      "\n",
      "The following object is masked from ‘package:base’:\n",
      "\n",
      "    expand.grid\n",
      "\n",
      "\n",
      "Loading required package: IRanges\n",
      "\n",
      "Loading required package: GenomicRanges\n",
      "\n",
      "Loading required package: GenomeInfoDb\n",
      "\n",
      "Loading required package: SummarizedExperiment\n",
      "\n",
      "Loading required package: MatrixGenerics\n",
      "\n",
      "Loading required package: matrixStats\n",
      "\n",
      "\n",
      "Attaching package: ‘MatrixGenerics’\n",
      "\n",
      "\n",
      "The following objects are masked from ‘package:matrixStats’:\n",
      "\n",
      "    colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,\n",
      "    colCounts, colCummaxs, colCummins, colCumprods, colCumsums,\n",
      "    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,\n",
      "    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,\n",
      "    colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,\n",
      "    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,\n",
      "    colWeightedMeans, colWeightedMedians, colWeightedSds,\n",
      "    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,\n",
      "    rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,\n",
      "    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,\n",
      "    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,\n",
      "    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,\n",
      "    rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,\n",
      "    rowWeightedMads, rowWeightedMeans, rowWeightedMedians,\n",
      "    rowWeightedSds, rowWeightedVars\n",
      "\n",
      "\n",
      "Loading required package: Biobase\n",
      "\n",
      "Welcome to Bioconductor\n",
      "\n",
      "    Vignettes contain introductory material; view with\n",
      "    'browseVignettes()'. To cite Bioconductor, see\n",
      "    'citation(\"Biobase\")', and for packages 'citation(\"pkgname\")'.\n",
      "\n",
      "\n",
      "\n",
      "Attaching package: ‘Biobase’\n",
      "\n",
      "\n",
      "The following object is masked from ‘package:MatrixGenerics’:\n",
      "\n",
      "    rowMedians\n",
      "\n",
      "\n",
      "The following objects are masked from ‘package:matrixStats’:\n",
      "\n",
      "    anyMissing, rowMedians\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "library(DESeq2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "estimating size factors\n",
      "\n",
      "estimating dispersions\n",
      "\n",
      "gene-wise dispersion estimates\n",
      "\n",
      "mean-dispersion relationship\n",
      "\n",
      "final dispersion estimates\n",
      "\n",
      "fitting model and testing\n",
      "\n"
     ]
    }
   ],
   "source": [
    "cc2 <- cc[,1:6]\n",
    "conds <- c(\"cnt\",\"cnt\",\"cnt\",  \"dac\", \"dac\", \"dac\")\n",
    "colData<-data.frame(condition=as.factor(conds))\n",
    "dds <- DESeqDataSetFromMatrix(countData = cc2,colData = colData,design = formula(colData) ) \n",
    "dds <- DESeq(dds)\n",
    "res <- results(dds)\n",
    "o <- order(res[,\"pvalue\"])\n",
    "res <- res[o, ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "log2 fold change (MLE): condition dac vs cnt \n",
       "Wald test p-value: condition dac vs cnt \n",
       "DataFrame with 57992 rows and 6 columns\n",
       "                 baseMean log2FoldChange     lfcSE      stat       pvalue\n",
       "                <numeric>      <numeric> <numeric> <numeric>    <numeric>\n",
       "ENSG00000130600 21561.070        5.50280  0.133035   41.3636  0.00000e+00\n",
       "ENSG00000135480  1420.357        4.60734  0.155206   29.6854 1.18459e-193\n",
       "ENSG00000105974  2226.621       -2.76973  0.102993  -26.8924 2.69261e-159\n",
       "ENSG00000147174   529.979        3.86159  0.159577   24.1989 2.28414e-129\n",
       "ENSG00000086548  2890.536        2.69275  0.115384   23.3373 1.85514e-120\n",
       "...                   ...            ...       ...       ...          ...\n",
       "ENSG00000239415         0             NA        NA        NA           NA\n",
       "ENSG00000223692         0             NA        NA        NA           NA\n",
       "ENSG00000202239         0             NA        NA        NA           NA\n",
       "ENSG00000160307         0             NA        NA        NA           NA\n",
       "ENSG00000210174         0             NA        NA        NA           NA\n",
       "                        padj\n",
       "                   <numeric>\n",
       "ENSG00000130600  0.00000e+00\n",
       "ENSG00000135480 1.56348e-189\n",
       "ENSG00000105974 2.36922e-155\n",
       "ENSG00000147174 1.50736e-125\n",
       "ENSG00000086548 9.79402e-117\n",
       "...                      ...\n",
       "ENSG00000239415           NA\n",
       "ENSG00000223692           NA\n",
       "ENSG00000202239           NA\n",
       "ENSG00000160307           NA\n",
       "ENSG00000210174           NA"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "DESeq2 and edgeR agree quite a lot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "385"
      ],
      "text/latex": [
       "385"
      ],
      "text/markdown": [
       "385"
      ],
      "text/plain": [
       "[1] 385"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "length(intersect(rownames(res)[1:500], rownames(topOnes_pairwise)[1:500]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(Vennerable)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IH9IFOBy259LBSgAAUo0LAAA6SGfbiVAhSgAAWaQUAGQ+Ydu2HatA3mLdth3voP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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "i1 <- rownames(res)[1:500]\n",
    "i2 <- rownames(topOnes_pairwise)[1:500]\n",
    "i3 <- rownames(topOnes)[1:500]\n",
    "\n",
    "vennD <- Venn ( list(i1, i2, i3), SetNames = c(\"DESeq2\", \"edgeR_pairwise\",\"edgeR_glm\"))\n",
    "plot(vennD, doWeights = T, type = \"circles\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.0.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}