analyses/cas9-electroporation/Cas9  and CD4 sgRNA RNP Electroporation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Attaching package: ‘dplyr’\n",
      "\n",
      "The following objects are masked from ‘package:stats’:\n",
      "\n",
      "    filter, lag\n",
      "\n",
      "The following objects are masked from ‘package:base’:\n",
      "\n",
      "    intersect, setdiff, setequal, union\n",
      "\n",
      "\n",
      "Attaching package: ‘tidyr’\n",
      "\n",
      "The following object is masked from ‘package:magrittr’:\n",
      "\n",
      "    extract\n",
      "\n"
     ]
    }
   ],
   "source": [
    "library('readr')\n",
    "library('magrittr')\n",
    "library('dplyr')\n",
    "library('tidyr')\n",
    "library('ggplot2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>Donor</th><th scope=col>sgRNA</th><th scope=col>avg_cd4</th><th scope=col>sd_cd4</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>Donor 14 </td><td>None     </td><td>78.566667</td><td> 6.726316</td></tr>\n",
       "\t<tr><td>Donor 14 </td><td>CD4      </td><td> 9.806667</td><td> 1.035197</td></tr>\n",
       "\t<tr><td>Donor 15 </td><td>None     </td><td>83.200000</td><td>11.171840</td></tr>\n",
       "\t<tr><td>Donor 15 </td><td>CD4      </td><td>11.666667</td><td> 1.607275</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       " Donor & sgRNA & avg\\_cd4 & sd\\_cd4\\\\\n",
       "\\hline\n",
       "\t Donor 14  & None      & 78.566667 &  6.726316\\\\\n",
       "\t Donor 14  & CD4       &  9.806667 &  1.035197\\\\\n",
       "\t Donor 15  & None      & 83.200000 & 11.171840\\\\\n",
       "\t Donor 15  & CD4       & 11.666667 &  1.607275\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "Donor | sgRNA | avg_cd4 | sd_cd4 | \n",
       "|---|---|---|---|\n",
       "| Donor 14  | None      | 78.566667 |  6.726316 | \n",
       "| Donor 14  | CD4       |  9.806667 |  1.035197 | \n",
       "| Donor 15  | None      | 83.200000 | 11.171840 | \n",
       "| Donor 15  | CD4       | 11.666667 |  1.607275 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  Donor    sgRNA avg_cd4   sd_cd4   \n",
       "1 Donor 14 None  78.566667  6.726316\n",
       "2 Donor 14 CD4    9.806667  1.035197\n",
       "3 Donor 15 None  83.200000 11.171840\n",
       "4 Donor 15 CD4   11.666667  1.607275"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ko_summary <-\n",
    "    read_tsv(\n",
    "        'flow-data.tsv',\n",
    "        col_types=cols(\n",
    "            `Donor`=col_factor(levels=c('D14', 'D15')),\n",
    "            `Replicate`=col_factor(levels=c('R1', 'R2', 'R3')),\n",
    "            `sgRNA`=col_factor(levels=c('N/A', 'CD4')),\n",
    "            .default=col_double()\n",
    "        )\n",
    "    ) %>%\n",
    "    mutate(\n",
    "        `Donor`=factor(`Donor`, labels=c('Donor 14', 'Donor 15')),\n",
    "        `sgRNA`=factor(`sgRNA`, labels=c('None', 'CD4'))\n",
    "    ) %>%\n",
    "    group_by(`Donor`, `sgRNA`) %>%\n",
    "    summarize(\n",
    "        `avg_cd4`=mean(`Live/CD4+ CD8- | Freq. of Parent`),\n",
    "        `sd_cd4`=sd(`Live/CD4+ CD8- | Freq. of Parent`)\n",
    "    )\n",
    "\n",
    "ko_summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "0.875180310245311"
      ],
      "text/latex": [
       "0.875180310245311"
      ],
      "text/markdown": [
       "0.875180310245311"
      ],
      "text/plain": [
       "[1] 0.8751803"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "1.0 - (9.806667 / 78.566667)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "0.859775637019231"
      ],
      "text/latex": [
       "0.859775637019231"
      ],
      "text/markdown": [
       "0.859775637019231"
      ],
      "text/plain": [
       "[1] 0.8597756"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "1.0 - (11.666667 / 83.200000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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w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\ngg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ko_summary %>%\n",
    "ggplot(aes(x=`sgRNA`, y=`avg_cd4`, fill=`sgRNA`)) +\n",
    "    geom_col() +\n",
    "    geom_errorbar(aes(\n",
    "        ymin=`avg_cd4`-`sd_cd4`,\n",
    "        ymax=`avg_cd4`+`sd_cd4`\n",
    "    ), width=.2) +\n",
    "    facet_wrap(~Donor, ncol=2) +\n",
    "    ylab('Percent CD4+ Population (%)\\n(n=3)') +\n",
    "    ylim(0, 100)"
   ]
  }
 ],
 "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": "3.4.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}