analysis/CAYA_vs_NonTCGA-ExAc/Freq_Plot_of_CAYA_vs_NonTCGA-ExAc.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# AIM to summarize the nonTCGA Exac and ALL\n",
    "***\n",
    "## Make a sumamry table of genes and their frequency in \n",
    "\n",
    "\n",
    "|summary |CAYA |nonTCGA| Known/Candidate |  |\n",
    "|---|---|---|---|---|\n",
    "|g1| # of variants for g1 in ALL / 1507 *2 | # of variants for g1 in nonExac / 53105 *2 | |\n",
    "|g2|# of variants for g1 in ALL / 1507 *2| # of variants for g1 in nonExac / 53105 *2| |\n",
    "|...|||\n",
    "\n",
    "***\n",
    "\n",
    "- Use nonTCGA_ExAC_All_040819_GeneticAnalysis_062019.xls\n",
    "- Use Mutation_data_cleaned_051019.xls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import pandas_profiling as pp\n",
    "import pandas_flavor as pf\n",
    "import numpy as np\n",
    "import datetime\n",
    "\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from IPython.core.display import display, HTML"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load nonTCGA ExAC Data file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "mut_fp = \"data/nonTCGA_ExAC_All_040819_GeneticAnalysis_062019.xlsx\"\n",
    "df = pd.read_excel(mut_fp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(35425, 78)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2124"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Hugo_Symbol.unique().size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "collector = []\n",
    "for e,i in enumerate( df.Hugo_Symbol.tolist() ):\n",
    "    lnx = df.loc[e].to_dict()\n",
    "    nX =i.split('; ')\n",
    "    if len(nX) >1 :\n",
    "        for x in nX :\n",
    "            lnx = df.loc[e].to_dict()\n",
    "            #print( '>>', e,lnx.get('Hugo_Symbol'), x )\n",
    "            lnx.update({'Hugo_Symbol': x })\n",
    "            #print( '>>>',e, lnx.get('Hugo_Symbol'), x )\n",
    "            collector.append(lnx)\n",
    "    else :\n",
    "        collector.append(lnx)\n",
    "        #print( '>',e, lnx.get('Hugo_Symbol') )\n",
    "\n",
    "dfX = pd.DataFrame( collector )\n",
    "dfX = dfX[df.columns.tolist()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(44506, 78)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfX.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_mut_freq =dfX.Hugo_Symbol.value_counts() / (53105 * 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2375"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_mut_freq.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_mut_freq.name = \"nonTCGAExAC\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load CCF Mutation Data file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "mut_fp2 = \"data/Mutation_data_cleaned_051019.xls\"\n",
    "ccfdf = pd.read_excel(mut_fp2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3016, 84)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ccfdf.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1258"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ccfdf.Hugo_Symbol.unique().size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "ccfdf_mut_freq =ccfdf.Hugo_Symbol.value_counts() / (1507 *2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1258"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ccfdf_mut_freq.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "ccfdf_mut_freq.name = \"CAYA\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Combine the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_df = pd.concat([ ccfdf_mut_freq, df_mut_freq ], axis=1,sort=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "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>CAYA</th>\n",
       "      <th>nonTCGAExAC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RB1</th>\n",
       "      <td>0.010617</td>\n",
       "      <td>0.000264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRKN</th>\n",
       "      <td>0.007631</td>\n",
       "      <td>0.000377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NF1</th>\n",
       "      <td>0.007299</td>\n",
       "      <td>0.000932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHEK2</th>\n",
       "      <td>0.006304</td>\n",
       "      <td>0.000452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAH</th>\n",
       "      <td>0.005972</td>\n",
       "      <td>0.001007</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           CAYA  nonTCGAExAC\n",
       "RB1    0.010617     0.000264\n",
       "PRKN   0.007631     0.000377\n",
       "NF1    0.007299     0.000932\n",
       "CHEK2  0.006304     0.000452\n",
       "PAH    0.005972     0.001007"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_df.fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    1230\n",
       "True     1181\n",
       "dtype: int64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "( joined_df.CAYA > joined_df.nonTCGAExAC ).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "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>CAYA</th>\n",
       "      <th>nonTCGAExAC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RB1</th>\n",
       "      <td>0.010617</td>\n",
       "      <td>0.000264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRKN</th>\n",
       "      <td>0.007631</td>\n",
       "      <td>0.000377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NF1</th>\n",
       "      <td>0.007299</td>\n",
       "      <td>0.000932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHEK2</th>\n",
       "      <td>0.006304</td>\n",
       "      <td>0.000452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAH</th>\n",
       "      <td>0.005972</td>\n",
       "      <td>0.001007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTN</th>\n",
       "      <td>0.005972</td>\n",
       "      <td>0.002872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TYR</th>\n",
       "      <td>0.005640</td>\n",
       "      <td>0.000772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TMPRSS3</th>\n",
       "      <td>0.005309</td>\n",
       "      <td>0.000301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EYS</th>\n",
       "      <td>0.005309</td>\n",
       "      <td>0.000593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABCA3</th>\n",
       "      <td>0.004977</td>\n",
       "      <td>0.001158</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             CAYA  nonTCGAExAC\n",
       "RB1      0.010617     0.000264\n",
       "PRKN     0.007631     0.000377\n",
       "NF1      0.007299     0.000932\n",
       "CHEK2    0.006304     0.000452\n",
       "PAH      0.005972     0.001007\n",
       "TTN      0.005972     0.002872\n",
       "TYR      0.005640     0.000772\n",
       "TMPRSS3  0.005309     0.000301\n",
       "EYS      0.005309     0.000593\n",
       "ABCA3    0.004977     0.001158"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_df[(joined_df.CAYA > joined_df.nonTCGAExAC)].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sanity Check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
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/6KbrBAAAACRJjtx/dK465ZA0lJL3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\n/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74LK7+TC6hijY3dtq+/tBRMnQWmdJWyryqe3Q7zeksAT9tRkL2k2SOS4MeM+SSINSba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/BHtPQXKjQc659ceALnu+h4xWJiBg9k3b1x/wrd0yzwY+6/JtxPO7ptx3JtLFcs01mvNxyNHl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\n",
      "text/plain": [
       "<Figure size 2210.4x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfx=joined_df.head(100)\n",
    "a4_dims = (30.7, 8.27)\n",
    "fig, ax = plt.subplots(figsize=a4_dims)\n",
    "ax1 = plt.plot(dfx.CAYA *100, label=\"CAYA\", marker='.');\n",
    "ax2 = plt.plot(dfx.nonTCGAExAC *100 , label=\"nonTCGAExAC\", marker='+');\n",
    "plt.tight_layout();\n",
    "labels=['CAYA','nonTCGAExAC']\n",
    "locs, labs = plt.xticks();\n",
    "plt.legend(loc='upper left')\n",
    "plt.setp(labs, rotation=45);\n",
    "plt.xlabel(\"Genes\");\n",
    "plt.ylabel(\"Frequency\");\n",
    "ax.set_yscale('linear')\n",
    "ax.set(title=\"Mutation Freqies Genes Top 100 genes\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "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>CAYA</th>\n",
       "      <th>nonTCGAExAC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AC067969.1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RP11-589N15.2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RN7SL861P</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LLGL2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RP11-452H21.1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000009</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               CAYA  nonTCGAExAC\n",
       "AC067969.1      0.0     0.000009\n",
       "RP11-589N15.2   0.0     0.000009\n",
       "RN7SL861P       0.0     0.000009\n",
       "LLGL2           0.0     0.000009\n",
       "RP11-452H21.1   0.0     0.000009"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_df_only_in_caya = joined_df[ joined_df.index.isin( ccfdf.Hugo_Symbol.unique() ) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1258, 2)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_df_only_in_caya.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True     1181\n",
       "False      77\n",
       "dtype: int64"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "( joined_df_only_in_caya.CAYA > joined_df_only_in_caya.nonTCGAExAC ).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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6OdnziPpyAQAAfe7og3ZL273tOXvR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djY1tvaYhw/UrZGSdioI8WqaM04LSnnb3IJBiZ2TIXIR4wJ8QYJMGhI9AQPdClHkdrr8DUlyJ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\n",
      "text/plain": [
       "<Figure size 2160x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfx=joined_df_only_in_caya.head(100)\n",
    "a4_dims = (30, 8.27)\n",
    "fig, ax = plt.subplots(figsize=a4_dims)\n",
    "ax1 = plt.plot(dfx.CAYA , label=\"CAYA\", marker='.');\n",
    "ax2 = plt.plot(dfx.nonTCGAExAC  , label=\"nonTCGAExAC\", marker='+');\n",
    "plt.tight_layout();\n",
    "labels=['CAYA','nonTCGAExAC']\n",
    "locs, labs = plt.xticks();\n",
    "plt.legend(loc='upper left')\n",
    "plt.setp(labs, rotation=45);\n",
    "plt.xlabel(\"Genes\");\n",
    "plt.ylabel(\"Frequency\");\n",
    "ax.set_yscale('linear')\n",
    "ax.set(title=\"Mutation Freqies Genes Top 100 genes\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "ccfdf_ss = ccfdf[[\"Hugo_Symbol\",  \"Known_Cancer_Predisposition_Genes\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/padmanr/.virtualenvs/p3/lib/python3.5/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "ccfdf_ss.drop_duplicates(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "ccfdf_ss.set_index(\"Hugo_Symbol\", inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/padmanr/.virtualenvs/p3/lib/python3.5/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "ccfdf_ss.sort_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1258, 1)"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ccfdf_ss.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_df_only_in_caya.sort_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_df_only_in_caya_02 = pd.concat([joined_df_only_in_caya, ccfdf_ss], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1258, 3)"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_df_only_in_caya_02.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_df_only_in_caya_02.sort_values('CAYA', ascending=False, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "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>CAYA</th>\n",
       "      <th>nonTCGAExAC</th>\n",
       "      <th>Known_Cancer_Predisposition_Genes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hugo_Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RB1</th>\n",
       "      <td>0.010617</td>\n",
       "      <td>0.000264</td>\n",
       "      <td>known</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRKN</th>\n",
       "      <td>0.007631</td>\n",
       "      <td>0.000377</td>\n",
       "      <td>suggesting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NF1</th>\n",
       "      <td>0.007299</td>\n",
       "      <td>0.000932</td>\n",
       "      <td>known</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHEK2</th>\n",
       "      <td>0.006304</td>\n",
       "      <td>0.000452</td>\n",
       "      <td>known</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAH</th>\n",
       "      <td>0.005972</td>\n",
       "      <td>0.001007</td>\n",
       "      <td>suggesting</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 CAYA  nonTCGAExAC Known_Cancer_Predisposition_Genes\n",
       "Hugo_Symbol                                                         \n",
       "RB1          0.010617     0.000264                             known\n",
       "PRKN         0.007631     0.000377                        suggesting\n",
       "NF1          0.007299     0.000932                             known\n",
       "CHEK2        0.006304     0.000452                             known\n",
       "PAH          0.005972     0.001007                        suggesting"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_df_only_in_caya_02.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_df_only_in_caya_02[\"freq_more\"] = [ 0 if i == True else 1 for i in joined_df_only_in_caya_02.CAYA > joined_df_only_in_caya_02.nonTCGAExAC ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "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>CAYA</th>\n",
       "      <th>nonTCGAExAC</th>\n",
       "      <th>Known_Cancer_Predisposition_Genes</th>\n",
       "      <th>freq_more</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hugo_Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>HLCS</th>\n",
       "      <td>0.000332</td>\n",
       "      <td>0.000348</td>\n",
       "      <td>suggesting</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HMCN1</th>\n",
       "      <td>0.000332</td>\n",
       "      <td>0.000471</td>\n",
       "      <td>suggesting</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HMGCL</th>\n",
       "      <td>0.000332</td>\n",
       "      <td>0.000160</td>\n",
       "      <td>suggesting</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HMGCS2</th>\n",
       "      <td>0.000332</td>\n",
       "      <td>0.000207</td>\n",
       "      <td>suggesting</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZP3</th>\n",
       "      <td>0.000332</td>\n",
       "      <td>0.000094</td>\n",
       "      <td>suggesting</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 CAYA  nonTCGAExAC Known_Cancer_Predisposition_Genes  \\\n",
       "Hugo_Symbol                                                            \n",
       "HLCS         0.000332     0.000348                        suggesting   \n",
       "HMCN1        0.000332     0.000471                        suggesting   \n",
       "HMGCL        0.000332     0.000160                        suggesting   \n",
       "HMGCS2       0.000332     0.000207                        suggesting   \n",
       "ZP3          0.000332     0.000094                        suggesting   \n",
       "\n",
       "             freq_more  \n",
       "Hugo_Symbol             \n",
       "HLCS                 1  \n",
       "HMCN1                1  \n",
       "HMGCL                0  \n",
       "HMGCS2               0  \n",
       "ZP3                  0  "
      ]
     },
     "execution_count": 214,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_df_only_in_caya_02.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "0.000332 > 0.000471"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "0.000332 > 0.000160"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "known    32\n",
       "Name: Known_Cancer_Predisposition_Genes, dtype: int64"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ccfdf[ ccfdf.Hugo_Symbol == 'RB1'].Known_Cancer_Predisposition_Genes.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pathogenic           29\n",
       "Likely Pathogenic     3\n",
       "Name: IVA_Prediction, dtype: int64"
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ccfdf[ ccfdf.Hugo_Symbol == 'RB1'].IVA_Prediction.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save the joined file 02"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_df_only_in_caya_02.to_csv(\"data/joined_freq_02.csv\", index_label=\"Genes\")"
   ]
  }
 ],
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