data/HA/Lee2019/build_data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Wrangling for [Lee *et al.*, (2019)](https://elifesciences.org/articles/49324)\n",
    "\n",
    "Mutational Antigenic Profiling of H3 influenza escape from human sera."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## notebook setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## mutational antigenic profiling data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mut_positive mutdiffsel</th>\n",
       "      <th>site_positive diffsel</th>\n",
       "      <th>condition</th>\n",
       "      <th>label_site</th>\n",
       "      <th>wildtype</th>\n",
       "      <th>mutation</th>\n",
       "      <th>mut_mutdiffsel</th>\n",
       "      <th>site_abs diffsel</th>\n",
       "      <th>site_negative diffsel</th>\n",
       "      <th>site_max diffsel</th>\n",
       "      <th>site_min diffsel</th>\n",
       "      <th>site</th>\n",
       "      <th>protein_chain</th>\n",
       "      <th>protein_site</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>90560</th>\n",
       "      <td>3.6671</td>\n",
       "      <td>15.837</td>\n",
       "      <td>2010-age-21</td>\n",
       "      <td>193</td>\n",
       "      <td>F</td>\n",
       "      <td>D</td>\n",
       "      <td>3.6671</td>\n",
       "      <td>17.384</td>\n",
       "      <td>-1.5467</td>\n",
       "      <td>3.6671</td>\n",
       "      <td>-0.52377</td>\n",
       "      <td>208</td>\n",
       "      <td>A</td>\n",
       "      <td>193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90561</th>\n",
       "      <td>3.1793</td>\n",
       "      <td>15.837</td>\n",
       "      <td>2010-age-21</td>\n",
       "      <td>193</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>3.1793</td>\n",
       "      <td>17.384</td>\n",
       "      <td>-1.5467</td>\n",
       "      <td>3.6671</td>\n",
       "      <td>-0.52377</td>\n",
       "      <td>208</td>\n",
       "      <td>A</td>\n",
       "      <td>193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90562</th>\n",
       "      <td>2.0820</td>\n",
       "      <td>15.837</td>\n",
       "      <td>2010-age-21</td>\n",
       "      <td>193</td>\n",
       "      <td>F</td>\n",
       "      <td>Q</td>\n",
       "      <td>2.0820</td>\n",
       "      <td>17.384</td>\n",
       "      <td>-1.5467</td>\n",
       "      <td>3.6671</td>\n",
       "      <td>-0.52377</td>\n",
       "      <td>208</td>\n",
       "      <td>A</td>\n",
       "      <td>193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90563</th>\n",
       "      <td>2.0098</td>\n",
       "      <td>15.837</td>\n",
       "      <td>2010-age-21</td>\n",
       "      <td>193</td>\n",
       "      <td>F</td>\n",
       "      <td>E</td>\n",
       "      <td>2.0098</td>\n",
       "      <td>17.384</td>\n",
       "      <td>-1.5467</td>\n",
       "      <td>3.6671</td>\n",
       "      <td>-0.52377</td>\n",
       "      <td>208</td>\n",
       "      <td>A</td>\n",
       "      <td>193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90564</th>\n",
       "      <td>1.0960</td>\n",
       "      <td>15.837</td>\n",
       "      <td>2010-age-21</td>\n",
       "      <td>193</td>\n",
       "      <td>F</td>\n",
       "      <td>L</td>\n",
       "      <td>1.0960</td>\n",
       "      <td>17.384</td>\n",
       "      <td>-1.5467</td>\n",
       "      <td>3.6671</td>\n",
       "      <td>-0.52377</td>\n",
       "      <td>208</td>\n",
       "      <td>A</td>\n",
       "      <td>193</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       mut_positive mutdiffsel  site_positive diffsel    condition label_site  \\\n",
       "90560                   3.6671                 15.837  2010-age-21        193   \n",
       "90561                   3.1793                 15.837  2010-age-21        193   \n",
       "90562                   2.0820                 15.837  2010-age-21        193   \n",
       "90563                   2.0098                 15.837  2010-age-21        193   \n",
       "90564                   1.0960                 15.837  2010-age-21        193   \n",
       "\n",
       "      wildtype mutation  mut_mutdiffsel  site_abs diffsel  \\\n",
       "90560        F        D          3.6671            17.384   \n",
       "90561        F        N          3.1793            17.384   \n",
       "90562        F        Q          2.0820            17.384   \n",
       "90563        F        E          2.0098            17.384   \n",
       "90564        F        L          1.0960            17.384   \n",
       "\n",
       "       site_negative diffsel  site_max diffsel  site_min diffsel  site  \\\n",
       "90560                -1.5467            3.6671          -0.52377   208   \n",
       "90561                -1.5467            3.6671          -0.52377   208   \n",
       "90562                -1.5467            3.6671          -0.52377   208   \n",
       "90563                -1.5467            3.6671          -0.52377   208   \n",
       "90564                -1.5467            3.6671          -0.52377   208   \n",
       "\n",
       "      protein_chain  protein_site  \n",
       "90560             A           193  \n",
       "90561             A           193  \n",
       "90562             A           193  \n",
       "90563             A           193  \n",
       "90564             A           193  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# target columns\n",
    "target_sera = ['2010-age-21', '2009-age-53', '2009-age-64', '2009-age-65', 'ferret-Pitt-1-postinf', \n",
    "               'ferret-Pitt-2-postinf', 'ferret-Pitt-3-postinf', 'ferret-WHO-Perth2009', 'ferret-WHO-Victoria2011']\n",
    "site_metrics = ['abs_diffsel', 'positive_diffsel', 'negative_diffsel', 'max_diffsel', 'min_diffsel']\n",
    "mut_metrics = ['mutdiffsel']\n",
    "\n",
    "# process the data\n",
    "df = pd.read_csv('https://raw.githubusercontent.com/jbloomlab/map_flu_serum_Perth2009_H3_HA/master/'\n",
    "                 'results/avgdiffsel/avg_sel_tidy.csv', low_memory=False)\n",
    "df = (df[df['serum_name_formatted'].isin(target_sera)]\n",
    "      .drop(columns=['serum', 'serum_group', 'serum_vaccination', 'zoom_site'])  # unneeded columns\n",
    "      .rename(columns={'serum_name_formatted': 'condition',\n",
    "                       'site': 'label_site', \n",
    "                      'isite': 'site', \n",
    "                      'pdb_site': 'protein_site',\n",
    "                      'pdb_chain': 'protein_chain'})  # rename some columns \n",
    "     .rename(columns={key: f\"site_{' '.join(key.split('_'))}\"\n",
    "                      for key in site_metrics})  # rename and format site metrics\n",
    "      .rename(columns={key: f\"mut_{' '.join(key.split('_'))}\" \n",
    "                      for key in mut_metrics})  # rename and format mut metrics\n",
    "     )\n",
    "\n",
    "# positive mut_diffsel\n",
    "df['mut_positive mutdiffsel'] = df['mut_mutdiffsel'].clip(lower=0)\n",
    "\n",
    "# change the order of the columns \n",
    "firstmut = 'mut_positive mutdiffsel'\n",
    "firstsite = 'site_positive diffsel'\n",
    "cols = list(df.columns.values) \n",
    "cols.remove(firstmut) \n",
    "cols.remove(firstsite) \n",
    "df = df[[firstmut, firstsite] + cols]\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('Lee2019.csv', index=False)"
   ]
  }
 ],
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