Survival_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6c7c9913",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy.stats import gaussian_kde\n",
    "from matplotlib.colors import LogNorm\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import seaborn as sns\n",
    "from scipy.stats import pearsonr\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.metrics import r2_score\n",
    "\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from sksurv.nonparametric import kaplan_meier_estimator\n",
    "from sksurv.preprocessing import OneHotEncoder\n",
    "from sksurv.linear_model import CoxPHSurvivalAnalysis\n",
    "from sksurv.metrics import concordance_index_censored\n",
    "from sksurv.compare import compare_survival\n",
    "from sksurv.datasets import get_x_y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "86880ffc",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tcga_clinical = pd.read_csv(\"/home/cke/TCGA_HNSCC_clinical_data.tsv\",sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d28c117e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Study ID</th>\n",
       "      <th>Patient ID</th>\n",
       "      <th>Sample ID</th>\n",
       "      <th>Diagnosis Age</th>\n",
       "      <th>American Joint Committee on Cancer Metastasis Stage Code</th>\n",
       "      <th>Neoplasm Disease Lymph Node Stage American Joint Committee on Cancer Code</th>\n",
       "      <th>Neoplasm Disease Stage American Joint Committee on Cancer Code</th>\n",
       "      <th>American Joint Committee on Cancer Publication Version Type</th>\n",
       "      <th>American Joint Committee on Cancer Tumor Stage Code</th>\n",
       "      <th>Alcohol Consumption Frequency</th>\n",
       "      <th>...</th>\n",
       "      <th>Specimen Second Longest Dimension</th>\n",
       "      <th>Stage Other</th>\n",
       "      <th>Time between clamping and freezing</th>\n",
       "      <th>Time between excision and freezing</th>\n",
       "      <th>Tissue Source Site</th>\n",
       "      <th>Patient Smoking History Category</th>\n",
       "      <th>Primary Therapy Outcome Success Type</th>\n",
       "      <th>Person Neoplasm Status</th>\n",
       "      <th>Vial number</th>\n",
       "      <th>Patient's Vital Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>hnsc_tcga</td>\n",
       "      <td>TCGA-4P-AA8J</td>\n",
       "      <td>TCGA-4P-AA8J-01</td>\n",
       "      <td>66.0</td>\n",
       "      <td>MX</td>\n",
       "      <td>N2c</td>\n",
       "      <td>Stage IVA</td>\n",
       "      <td>7th</td>\n",
       "      <td>T2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4P</td>\n",
       "      <td>[Unknown]</td>\n",
       "      <td>Complete Remission/Response</td>\n",
       "      <td>TUMOR FREE</td>\n",
       "      <td>A</td>\n",
       "      <td>Alive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>hnsc_tcga</td>\n",
       "      <td>TCGA-BA-4074</td>\n",
       "      <td>TCGA-BA-4074-01</td>\n",
       "      <td>69.0</td>\n",
       "      <td>M0</td>\n",
       "      <td>N2c</td>\n",
       "      <td>Stage IVA</td>\n",
       "      <td>6th</td>\n",
       "      <td>T2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BA</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WITH TUMOR</td>\n",
       "      <td>A</td>\n",
       "      <td>Dead</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>hnsc_tcga</td>\n",
       "      <td>TCGA-BA-4075</td>\n",
       "      <td>TCGA-BA-4075-01</td>\n",
       "      <td>49.0</td>\n",
       "      <td>M0</td>\n",
       "      <td>N0</td>\n",
       "      <td>Stage III</td>\n",
       "      <td>6th</td>\n",
       "      <td>T3</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BA</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WITH TUMOR</td>\n",
       "      <td>A</td>\n",
       "      <td>Dead</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>hnsc_tcga</td>\n",
       "      <td>TCGA-BA-4076</td>\n",
       "      <td>TCGA-BA-4076-01</td>\n",
       "      <td>39.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NX</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6th</td>\n",
       "      <td>TX</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BA</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WITH TUMOR</td>\n",
       "      <td>A</td>\n",
       "      <td>Dead</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>hnsc_tcga</td>\n",
       "      <td>TCGA-BA-4077</td>\n",
       "      <td>TCGA-BA-4077-01</td>\n",
       "      <td>45.0</td>\n",
       "      <td>M0</td>\n",
       "      <td>N0</td>\n",
       "      <td>Stage IVA</td>\n",
       "      <td>6th</td>\n",
       "      <td>T4a</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BA</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WITH TUMOR</td>\n",
       "      <td>B</td>\n",
       "      <td>Dead</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>525</th>\n",
       "      <td>hnsc_tcga</td>\n",
       "      <td>TCGA-UF-A7JT</td>\n",
       "      <td>TCGA-UF-A7JT-01</td>\n",
       "      <td>72.0</td>\n",
       "      <td>M0</td>\n",
       "      <td>N0</td>\n",
       "      <td>Stage IVA</td>\n",
       "      <td>6th</td>\n",
       "      <td>T4a</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UF</td>\n",
       "      <td>1</td>\n",
       "      <td>Complete Remission/Response</td>\n",
       "      <td>WITH TUMOR</td>\n",
       "      <td>A</td>\n",
       "      <td>Dead</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526</th>\n",
       "      <td>hnsc_tcga</td>\n",
       "      <td>TCGA-UF-A7JV</td>\n",
       "      <td>TCGA-UF-A7JV-01</td>\n",
       "      <td>62.0</td>\n",
       "      <td>M0</td>\n",
       "      <td>N2b</td>\n",
       "      <td>Stage IVA</td>\n",
       "      <td>7th</td>\n",
       "      <td>T4a</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UF</td>\n",
       "      <td>1</td>\n",
       "      <td>Complete Remission/Response</td>\n",
       "      <td>WITH TUMOR</td>\n",
       "      <td>A</td>\n",
       "      <td>Dead</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527</th>\n",
       "      <td>hnsc_tcga</td>\n",
       "      <td>TCGA-UP-A6WW</td>\n",
       "      <td>TCGA-UP-A6WW-01</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7th</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UP</td>\n",
       "      <td>1</td>\n",
       "      <td>Complete Remission/Response</td>\n",
       "      <td>TUMOR FREE</td>\n",
       "      <td>A</td>\n",
       "      <td>Alive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528</th>\n",
       "      <td>hnsc_tcga</td>\n",
       "      <td>TCGA-WA-A7GZ</td>\n",
       "      <td>TCGA-WA-A7GZ-01</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7th</td>\n",
       "      <td>T2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WA</td>\n",
       "      <td>2</td>\n",
       "      <td>Complete Remission/Response</td>\n",
       "      <td>TUMOR FREE</td>\n",
       "      <td>A</td>\n",
       "      <td>Dead</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>529</th>\n",
       "      <td>hnsc_tcga</td>\n",
       "      <td>TCGA-WA-A7H4</td>\n",
       "      <td>TCGA-WA-A7H4-01</td>\n",
       "      <td>69.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N0</td>\n",
       "      <td>Stage II</td>\n",
       "      <td>7th</td>\n",
       "      <td>T2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WA</td>\n",
       "      <td>2</td>\n",
       "      <td>Complete Remission/Response</td>\n",
       "      <td>TUMOR FREE</td>\n",
       "      <td>A</td>\n",
       "      <td>Alive</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>530 rows × 94 columns</p>\n",
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      ],
      "text/plain": [
       "      Study ID    Patient ID        Sample ID  Diagnosis Age  \\\n",
       "0    hnsc_tcga  TCGA-4P-AA8J  TCGA-4P-AA8J-01           66.0   \n",
       "1    hnsc_tcga  TCGA-BA-4074  TCGA-BA-4074-01           69.0   \n",
       "2    hnsc_tcga  TCGA-BA-4075  TCGA-BA-4075-01           49.0   \n",
       "3    hnsc_tcga  TCGA-BA-4076  TCGA-BA-4076-01           39.0   \n",
       "4    hnsc_tcga  TCGA-BA-4077  TCGA-BA-4077-01           45.0   \n",
       "..         ...           ...              ...            ...   \n",
       "525  hnsc_tcga  TCGA-UF-A7JT  TCGA-UF-A7JT-01           72.0   \n",
       "526  hnsc_tcga  TCGA-UF-A7JV  TCGA-UF-A7JV-01           62.0   \n",
       "527  hnsc_tcga  TCGA-UP-A6WW  TCGA-UP-A6WW-01           58.0   \n",
       "528  hnsc_tcga  TCGA-WA-A7GZ  TCGA-WA-A7GZ-01           58.0   \n",
       "529  hnsc_tcga  TCGA-WA-A7H4  TCGA-WA-A7H4-01           69.0   \n",
       "\n",
       "    American Joint Committee on Cancer Metastasis Stage Code  \\\n",
       "0                                                   MX         \n",
       "1                                                   M0         \n",
       "2                                                   M0         \n",
       "3                                                  NaN         \n",
       "4                                                   M0         \n",
       "..                                                 ...         \n",
       "525                                                 M0         \n",
       "526                                                 M0         \n",
       "527                                                NaN         \n",
       "528                                                NaN         \n",
       "529                                                NaN         \n",
       "\n",
       "    Neoplasm Disease Lymph Node Stage American Joint Committee on Cancer Code  \\\n",
       "0                                                  N2c                          \n",
       "1                                                  N2c                          \n",
       "2                                                   N0                          \n",
       "3                                                   NX                          \n",
       "4                                                   N0                          \n",
       "..                                                 ...                          \n",
       "525                                                 N0                          \n",
       "526                                                N2b                          \n",
       "527                                                NaN                          \n",
       "528                                                 N0                          \n",
       "529                                                 N0                          \n",
       "\n",
       "    Neoplasm Disease Stage American Joint Committee on Cancer Code  \\\n",
       "0                                            Stage IVA               \n",
       "1                                            Stage IVA               \n",
       "2                                            Stage III               \n",
       "3                                                  NaN               \n",
       "4                                            Stage IVA               \n",
       "..                                                 ...               \n",
       "525                                          Stage IVA               \n",
       "526                                          Stage IVA               \n",
       "527                                                NaN               \n",
       "528                                                NaN               \n",
       "529                                           Stage II               \n",
       "\n",
       "    American Joint Committee on Cancer Publication Version Type  \\\n",
       "0                                                  7th            \n",
       "1                                                  6th            \n",
       "2                                                  6th            \n",
       "3                                                  6th            \n",
       "4                                                  6th            \n",
       "..                                                 ...            \n",
       "525                                                6th            \n",
       "526                                                7th            \n",
       "527                                                7th            \n",
       "528                                                7th            \n",
       "529                                                7th            \n",
       "\n",
       "    American Joint Committee on Cancer Tumor Stage Code  \\\n",
       "0                                                   T2    \n",
       "1                                                   T2    \n",
       "2                                                   T3    \n",
       "3                                                   TX    \n",
       "4                                                  T4a    \n",
       "..                                                 ...    \n",
       "525                                                T4a    \n",
       "526                                                T4a    \n",
       "527                                                NaN    \n",
       "528                                                 T2    \n",
       "529                                                 T2    \n",
       "\n",
       "     Alcohol Consumption Frequency  ... Specimen Second Longest Dimension  \\\n",
       "0                              NaN  ...                               NaN   \n",
       "1                              NaN  ...                               0.7   \n",
       "2                              7.0  ...                               0.7   \n",
       "3                              NaN  ...                               0.6   \n",
       "4                              0.0  ...                               0.5   \n",
       "..                             ...  ...                               ...   \n",
       "525                            NaN  ...                               NaN   \n",
       "526                            NaN  ...                               NaN   \n",
       "527                            7.0  ...                               NaN   \n",
       "528                            NaN  ...                               NaN   \n",
       "529                            NaN  ...                               NaN   \n",
       "\n",
       "    Stage Other Time between clamping and freezing  \\\n",
       "0           NaN                                NaN   \n",
       "1           NaN                                NaN   \n",
       "2           NaN                                NaN   \n",
       "3           NaN                                NaN   \n",
       "4           NaN                                NaN   \n",
       "..          ...                                ...   \n",
       "525         NaN                                NaN   \n",
       "526         NaN                                NaN   \n",
       "527         NaN                                NaN   \n",
       "528         NaN                                NaN   \n",
       "529         NaN                                NaN   \n",
       "\n",
       "    Time between excision and freezing Tissue Source Site  \\\n",
       "0                                  NaN                 4P   \n",
       "1                                  NaN                 BA   \n",
       "2                                  NaN                 BA   \n",
       "3                                  NaN                 BA   \n",
       "4                                  NaN                 BA   \n",
       "..                                 ...                ...   \n",
       "525                                NaN                 UF   \n",
       "526                                NaN                 UF   \n",
       "527                                NaN                 UP   \n",
       "528                                NaN                 WA   \n",
       "529                                NaN                 WA   \n",
       "\n",
       "    Patient Smoking History Category Primary Therapy Outcome Success Type  \\\n",
       "0                          [Unknown]          Complete Remission/Response   \n",
       "1                                  2                                  NaN   \n",
       "2                                  2                                  NaN   \n",
       "3                                  2                                  NaN   \n",
       "4                                  4                                  NaN   \n",
       "..                               ...                                  ...   \n",
       "525                                1          Complete Remission/Response   \n",
       "526                                1          Complete Remission/Response   \n",
       "527                                1          Complete Remission/Response   \n",
       "528                                2          Complete Remission/Response   \n",
       "529                                2          Complete Remission/Response   \n",
       "\n",
       "    Person Neoplasm Status Vial number  Patient's Vital Status  \n",
       "0               TUMOR FREE           A                   Alive  \n",
       "1               WITH TUMOR           A                    Dead  \n",
       "2               WITH TUMOR           A                    Dead  \n",
       "3               WITH TUMOR           A                    Dead  \n",
       "4               WITH TUMOR           B                    Dead  \n",
       "..                     ...         ...                     ...  \n",
       "525             WITH TUMOR           A                    Dead  \n",
       "526             WITH TUMOR           A                    Dead  \n",
       "527             TUMOR FREE           A                   Alive  \n",
       "528             TUMOR FREE           A                    Dead  \n",
       "529             TUMOR FREE           A                   Alive  \n",
       "\n",
       "[530 rows x 94 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tcga_clinical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c67c1aa2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tcga_survival = df_tcga_clinical.loc[:,['Patient ID','Overall Survival (Months)','Overall Survival Status']]\n",
    "# df_tcga_survival"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "aff19067",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Patient ID</th>\n",
       "      <th>Overall Survival (Months)</th>\n",
       "      <th>Overall Survival Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>TCGA-4P-AA8J</td>\n",
       "      <td>3.35</td>\n",
       "      <td>LIVING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TCGA-BA-4074</td>\n",
       "      <td>15.18</td>\n",
       "      <td>DECEASED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TCGA-BA-4075</td>\n",
       "      <td>9.30</td>\n",
       "      <td>DECEASED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TCGA-BA-4076</td>\n",
       "      <td>13.63</td>\n",
       "      <td>DECEASED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TCGA-BA-4077</td>\n",
       "      <td>37.25</td>\n",
       "      <td>DECEASED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>525</th>\n",
       "      <td>TCGA-UF-A7JT</td>\n",
       "      <td>32.62</td>\n",
       "      <td>DECEASED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526</th>\n",
       "      <td>TCGA-UF-A7JV</td>\n",
       "      <td>2.96</td>\n",
       "      <td>DECEASED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527</th>\n",
       "      <td>TCGA-UP-A6WW</td>\n",
       "      <td>17.02</td>\n",
       "      <td>LIVING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528</th>\n",
       "      <td>TCGA-WA-A7GZ</td>\n",
       "      <td>20.53</td>\n",
       "      <td>DECEASED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>529</th>\n",
       "      <td>TCGA-WA-A7H4</td>\n",
       "      <td>14.55</td>\n",
       "      <td>LIVING</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>528 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Patient ID  Overall Survival (Months) Overall Survival Status\n",
       "0    TCGA-4P-AA8J                       3.35                  LIVING\n",
       "1    TCGA-BA-4074                      15.18                DECEASED\n",
       "2    TCGA-BA-4075                       9.30                DECEASED\n",
       "3    TCGA-BA-4076                      13.63                DECEASED\n",
       "4    TCGA-BA-4077                      37.25                DECEASED\n",
       "..            ...                        ...                     ...\n",
       "525  TCGA-UF-A7JT                      32.62                DECEASED\n",
       "526  TCGA-UF-A7JV                       2.96                DECEASED\n",
       "527  TCGA-UP-A6WW                      17.02                  LIVING\n",
       "528  TCGA-WA-A7GZ                      20.53                DECEASED\n",
       "529  TCGA-WA-A7H4                      14.55                  LIVING\n",
       "\n",
       "[528 rows x 3 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tcga_survival.dropna(inplace=True)\n",
    "df_tcga_survival"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "444608c9",
   "metadata": {},
   "source": [
    "## Prepare df_merged as in pipeline_downstream_analysis-show\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c1da25cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# read in best decon cell type frac results file\n",
    "# BayesPrism top100DEGs\n",
    "res_prevail = pd.read_csv(\"/home/cke/Real/TCGAResults/BayesPrism/celltypefrac_BP_fullpipeline_real_Jul28_real_top100DEGs.csv\",index_col=0)\n",
    "res_prevail['sample'] = res_prevail.index.tolist()\n",
    "res_prevail['sample'] = res_prevail['sample'].str.rstrip('A')\n",
    "# res_prevail\n",
    "# read in best decon cell type frac results file\n",
    "# BayesPrism top100DEGs\n",
    "res_prevail_subtypes = pd.read_csv(\"/home/cke/Real/TCGAResults/BayesPrism/celltypefrac_BP_ImmuneSubtypes_real_top100DEGs_Aug8.csv\",index_col=0)\n",
    "res_prevail_subtypes['sample'] = res_prevail_subtypes.index.tolist()\n",
    "res_prevail_subtypes['sample'] = res_prevail_subtypes['sample'].str.rstrip('A')\n",
    "# res_prevail_subtypes\n",
    "# read in fga data table from Kari's plots\n",
    "fga_Kari = pd.read_csv(\"/home/cke/KariPDF/fga_table.csv\",header=None)\n",
    "fga_Kari.columns = ['sample','fga']\n",
    "# using cellularity extracted from Kari's plots pdf \n",
    "cellularity_Kari = pd.read_csv(\"/home/cke/KariPDF/cellularity_table.csv\",header=None)\n",
    "cellularity_Kari.columns = ['sample','cellularity']\n",
    "cellularity_Kari = cellularity_Kari[cellularity_Kari['cellularity']<1.0]\n",
    "# cellularity_Kari\n",
    "# fga_Kari\n",
    "df_merged = pd.merge(res_prevail,pd.merge(cellularity_Kari,fga_Kari,on='sample'))\n",
    "df_merged_subtypes = pd.merge(res_prevail_subtypes,pd.merge(cellularity_Kari,fga_Kari,on='sample'))\n",
    "# Merging fga + cell type fractions "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b77c3d65",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/cke/miniconda3/envs/BLADE/lib/python3.10/site-packages/openpyxl/worksheet/_reader.py:312: UserWarning: Unknown extension is not supported and will be removed\n",
      "  warn(msg)\n"
     ]
    }
   ],
   "source": [
    "def define_FGA(fga):\n",
    "    if fga > 0.2:\n",
    "        return 'High'\n",
    "    else:\n",
    "        return 'Silent'\n",
    "df_merged['FGA_status'] = df_merged['fga'].apply(define_FGA)\n",
    "df_merged_subtypes['FGA_status'] = df_merged_subtypes['fga'].apply(define_FGA)\n",
    "\n",
    "Nulton = pd.read_excel(\"/home/cke/Nulton 2017 - supplementary.xlsx\",sheet_name=1)\n",
    "# Nulton\n",
    "TCGA_pheno = pd.read_csv(\"/home/cke/TCGA-HNSC.GDC_phenotype.tsv\",sep='\\t')\n",
    "TCGA_pheno['hpv_status']=''\n",
    "TCGA_pheno.loc[(TCGA_pheno['hpv_status_by_ish_testing']=='Positive') | (TCGA_pheno['hpv_status_by_p16_testing']=='Positive'),'hpv_status']='Positive'\n",
    "TCGA_pheno.loc[(TCGA_pheno['hpv_status_by_ish_testing']=='Negative') & (TCGA_pheno['hpv_status_by_p16_testing']=='Negative'),'hpv_status']='Negative'\n",
    "# TCGA_pheno['hpv_status'].value_counts()\n",
    "TCGA_pheno['sample'] = TCGA_pheno['submitter_id.samples'].str.rsplit(\"-\",n=1,expand=True)[0]\n",
    "list_pos_tcgaPheno = TCGA_pheno[TCGA_pheno['hpv_status']=='Positive']['sample'].tolist()\n",
    "list_pos_Nulton = Nulton['HNSCC Barcode'].tolist()\n",
    "# remove conflict samples between TCGA annotation and Nulton et al.\n",
    "list_remove = []\n",
    "for i in list_pos_tcgaPheno:\n",
    "    if i not in list_pos_Nulton:\n",
    "        list_remove.append(i)\n",
    "# list_remove"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "adb74a7b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We gathered 72 Positive samples from two source\n",
      "We removed 10 conflicting samples\n"
     ]
    }
   ],
   "source": [
    "set_pos = list_pos_Nulton\n",
    "print(\"We gathered\",len(list_pos_Nulton),\"Positive samples from two source\") \n",
    "print(\"We removed\",len(list_remove),\"conflicting samples\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b4c2c377",
   "metadata": {},
   "outputs": [],
   "source": [
    "dict_primary_site = {'Alveolar Ridge': 'Oral Cavity',\n",
    " 'Floor of mouth': 'Oral Cavity',\n",
    " 'Palate': 'Oral Cavity',\n",
    " 'Lip': 'Oral Cavity',\n",
    " 'Oral Tongue': 'Oral Cavity',\n",
    " 'Oral Cavity': 'Oral Cavity',\n",
    " 'Other and unspecified parts of tongue': 'Oral Cavity',\n",
    " 'Other and unspecified parts of mouth': 'Oral Cavity',\n",
    " 'Base of tongue': 'Oropharynx',\n",
    " 'Tonsil': 'Oropharynx',\n",
    " 'Oropharynx': 'Oropharynx',\n",
    "    'Larynx': 'Larynx',    \n",
    "    'Floor of mouth':'Oral Cavity',\n",
    "    'Gum':'Oral Cavity',\n",
    "    'Oropharynx':'Oropharynx',\n",
    "    'Hypopharynx':'Hypopharynx',}\n",
    "TCGA_pheno_new = TCGA_pheno.copy()\n",
    "TCGA_pheno_new['primary_site'] = TCGA_pheno_new['primary_site'].map(dict_primary_site)\n",
    "TCGA_pheno_new.dropna(subset='primary_site',inplace=True)\n",
    "\n",
    "#Selecting only primary tumor!\n",
    "TCGA_pheno_new = TCGA_pheno_new[TCGA_pheno_new['sample_type.samples']=='Primary Tumor']\n",
    "TCGA_pheno_new['primary_site'].value_counts()\n",
    "\n",
    "df_merged['sample_match'] = df_merged['sample'].str.rsplit(\"-\",n=1,expand=True)[0]\n",
    "df_merged_sites = pd.merge(df_merged,TCGA_pheno_new[['sample','primary_site']],left_on='sample_match',right_on='sample')\n",
    "# df_merged_sites\n",
    "\n",
    "df_merged_subtypes['sample_match'] = df_merged_subtypes['sample'].str.rsplit(\"-\",n=1,expand=True)[0]\n",
    "df_merged_subtypes_sites = pd.merge(df_merged_subtypes,TCGA_pheno_new[['sample','primary_site']],left_on='sample_match',right_on='sample')\n",
    "# df_merged_subtypes_sites"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8aec00e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_merged_sites = pd.merge(df_merged_sites,df_tcga_survival,left_on='sample_match',right_on='Patient ID',how='left')\n",
    "df_merged_subtypes_sites = pd.merge(df_merged_subtypes_sites,df_tcga_survival,left_on='sample_match',right_on='Patient ID',how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "892d429f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "60\n",
      "354\n",
      "60\n",
      "354\n"
     ]
    }
   ],
   "source": [
    "df_merged_HPVpos = df_merged_sites.copy()\n",
    "df_merged_HPVpos = df_merged_HPVpos[df_merged_HPVpos['sample_match'].isin(set_pos)]\n",
    "df_merged_HPVpos['hpv_status'] = \"Positive\"\n",
    "# df_merged_HPVpos\n",
    "print(df_merged_HPVpos.shape[0])\n",
    "df_merged_HPVneg = df_merged_sites.copy()\n",
    "df_merged_HPVneg = df_merged_HPVneg[~df_merged_HPVneg['sample_match'].isin(set_pos) & ~df_merged_HPVneg['sample_match'].isin(list_remove)]\n",
    "df_merged_HPVneg['hpv_status'] = \"Negative\"\n",
    "# df_merged_HPVneg\n",
    "print(df_merged_HPVneg.shape[0])\n",
    "df_merged_HPVpos_subtypes = df_merged_subtypes_sites.copy()\n",
    "df_merged_HPVpos_subtypes = df_merged_HPVpos_subtypes[df_merged_HPVpos_subtypes['sample_match'].isin(set_pos)]\n",
    "df_merged_HPVpos_subtypes['hpv_status'] = \"Positive\"\n",
    "# df_merged_HPVpos\n",
    "print(df_merged_HPVpos_subtypes.shape[0])\n",
    "df_merged_HPVneg_subtypes = df_merged_subtypes_sites.copy()\n",
    "df_merged_HPVneg_subtypes = df_merged_HPVneg_subtypes[~df_merged_HPVneg_subtypes['sample_match'].isin(set_pos) & ~df_merged_HPVneg_subtypes['sample_match'].isin(list_remove)]\n",
    "df_merged_HPVneg_subtypes['hpv_status'] = \"Negative\"\n",
    "# df_merged_HPVneg\n",
    "print(df_merged_HPVneg_subtypes.shape[0])\n",
    "# Ultimate dataframe containing all information\n",
    "df_merged_nonrelative = pd.concat([df_merged_HPVpos,df_merged_HPVneg])\n",
    "df_merged_subtypes_nonrelative = pd.concat([df_merged_HPVpos_subtypes,df_merged_HPVneg_subtypes])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "25d8eeea",
   "metadata": {
    "scrolled": true
   },
   "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>B-cell</th>\n",
       "      <th>Dendritic</th>\n",
       "      <th>Endothelial</th>\n",
       "      <th>Fibroblast</th>\n",
       "      <th>Macrophage</th>\n",
       "      <th>Mast</th>\n",
       "      <th>myocyte</th>\n",
       "      <th>other</th>\n",
       "      <th>T-cell</th>\n",
       "      <th>tumor</th>\n",
       "      <th>...</th>\n",
       "      <th>cellularity</th>\n",
       "      <th>fga</th>\n",
       "      <th>FGA_status</th>\n",
       "      <th>sample_match</th>\n",
       "      <th>sample_y</th>\n",
       "      <th>primary_site</th>\n",
       "      <th>Patient ID</th>\n",
       "      <th>Overall Survival (Months)</th>\n",
       "      <th>Overall Survival Status</th>\n",
       "      <th>hpv_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.709435e-03</td>\n",
       "      <td>0.003259</td>\n",
       "      <td>0.037323</td>\n",
       "      <td>0.027008</td>\n",
       "      <td>0.052619</td>\n",
       "      <td>0.000677</td>\n",
       "      <td>1.216315e-02</td>\n",
       "      <td>2.098187e-06</td>\n",
       "      <td>0.028711</td>\n",
       "      <td>0.832527</td>\n",
       "      <td>...</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.572</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CN-5374</td>\n",
       "      <td>TCGA-CN-5374</td>\n",
       "      <td>Oropharynx</td>\n",
       "      <td>TCGA-CN-5374</td>\n",
       "      <td>56.90</td>\n",
       "      <td>DECEASED</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8.058788e-03</td>\n",
       "      <td>0.004823</td>\n",
       "      <td>0.053060</td>\n",
       "      <td>0.050577</td>\n",
       "      <td>0.088309</td>\n",
       "      <td>0.001369</td>\n",
       "      <td>9.219069e-07</td>\n",
       "      <td>1.354588e-06</td>\n",
       "      <td>0.031462</td>\n",
       "      <td>0.762338</td>\n",
       "      <td>...</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.098</td>\n",
       "      <td>Silent</td>\n",
       "      <td>TCGA-CR-5249</td>\n",
       "      <td>TCGA-CR-5249</td>\n",
       "      <td>Oropharynx</td>\n",
       "      <td>TCGA-CR-5249</td>\n",
       "      <td>37.84</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>3.396785e-03</td>\n",
       "      <td>0.041641</td>\n",
       "      <td>0.040713</td>\n",
       "      <td>0.013894</td>\n",
       "      <td>0.158393</td>\n",
       "      <td>0.000163</td>\n",
       "      <td>6.779418e-04</td>\n",
       "      <td>1.593186e-06</td>\n",
       "      <td>0.041585</td>\n",
       "      <td>0.699535</td>\n",
       "      <td>...</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.245</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CV-6433</td>\n",
       "      <td>TCGA-CV-6433</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-CV-6433</td>\n",
       "      <td>21.06</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>9.403402e-03</td>\n",
       "      <td>0.003327</td>\n",
       "      <td>0.024324</td>\n",
       "      <td>0.302406</td>\n",
       "      <td>0.185639</td>\n",
       "      <td>0.000672</td>\n",
       "      <td>9.655291e-07</td>\n",
       "      <td>1.128296e-06</td>\n",
       "      <td>0.020712</td>\n",
       "      <td>0.453513</td>\n",
       "      <td>...</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.436</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-H7-A76A</td>\n",
       "      <td>TCGA-H7-A76A</td>\n",
       "      <td>Oropharynx</td>\n",
       "      <td>TCGA-H7-A76A</td>\n",
       "      <td>20.93</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1.096958e-02</td>\n",
       "      <td>0.048059</td>\n",
       "      <td>0.060456</td>\n",
       "      <td>0.054257</td>\n",
       "      <td>0.097379</td>\n",
       "      <td>0.000084</td>\n",
       "      <td>5.340647e-03</td>\n",
       "      <td>1.951452e-06</td>\n",
       "      <td>0.038107</td>\n",
       "      <td>0.685345</td>\n",
       "      <td>...</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.542</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-BB-4225</td>\n",
       "      <td>TCGA-BB-4225</td>\n",
       "      <td>Oropharynx</td>\n",
       "      <td>TCGA-BB-4225</td>\n",
       "      <td>4.80</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>412</th>\n",
       "      <td>4.269644e-05</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>0.018005</td>\n",
       "      <td>0.019971</td>\n",
       "      <td>0.009111</td>\n",
       "      <td>0.000082</td>\n",
       "      <td>7.632417e-03</td>\n",
       "      <td>3.212852e-04</td>\n",
       "      <td>0.002373</td>\n",
       "      <td>0.942446</td>\n",
       "      <td>...</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.562</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-C9-A47Z</td>\n",
       "      <td>TCGA-C9-A47Z</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-C9-A47Z</td>\n",
       "      <td>6.27</td>\n",
       "      <td>DECEASED</td>\n",
       "      <td>Negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>413</th>\n",
       "      <td>6.054611e-03</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>0.062586</td>\n",
       "      <td>0.095856</td>\n",
       "      <td>0.043977</td>\n",
       "      <td>0.000638</td>\n",
       "      <td>5.265638e-04</td>\n",
       "      <td>1.956283e-01</td>\n",
       "      <td>0.000798</td>\n",
       "      <td>0.593934</td>\n",
       "      <td>...</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.736</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CN-6010</td>\n",
       "      <td>TCGA-CN-6010</td>\n",
       "      <td>Larynx</td>\n",
       "      <td>TCGA-CN-6010</td>\n",
       "      <td>50.03</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>2.447322e-07</td>\n",
       "      <td>0.000006</td>\n",
       "      <td>0.046802</td>\n",
       "      <td>0.340756</td>\n",
       "      <td>0.052835</td>\n",
       "      <td>0.000410</td>\n",
       "      <td>2.725393e-07</td>\n",
       "      <td>5.001734e-07</td>\n",
       "      <td>0.007906</td>\n",
       "      <td>0.551284</td>\n",
       "      <td>...</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.778</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CV-7235</td>\n",
       "      <td>TCGA-CV-7235</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-CV-7235</td>\n",
       "      <td>77.10</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>1.076841e-03</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.031584</td>\n",
       "      <td>0.020308</td>\n",
       "      <td>0.012922</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>3.760127e-04</td>\n",
       "      <td>3.780077e-04</td>\n",
       "      <td>0.006510</td>\n",
       "      <td>0.926642</td>\n",
       "      <td>...</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.642</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CX-7086</td>\n",
       "      <td>TCGA-CX-7086</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-CX-7086</td>\n",
       "      <td>18.82</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>7.891968e-03</td>\n",
       "      <td>0.006893</td>\n",
       "      <td>0.060843</td>\n",
       "      <td>0.114456</td>\n",
       "      <td>0.074855</td>\n",
       "      <td>0.000914</td>\n",
       "      <td>5.875009e-02</td>\n",
       "      <td>4.273614e-06</td>\n",
       "      <td>0.012290</td>\n",
       "      <td>0.663102</td>\n",
       "      <td>...</td>\n",
       "      <td>0.31</td>\n",
       "      <td>0.603</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-HD-A6HZ</td>\n",
       "      <td>TCGA-HD-A6HZ</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-HD-A6HZ</td>\n",
       "      <td>3.65</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>414 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           B-cell  Dendritic  Endothelial  Fibroblast  Macrophage      Mast  \\\n",
       "2    5.709435e-03   0.003259     0.037323    0.027008    0.052619  0.000677   \n",
       "6    8.058788e-03   0.004823     0.053060    0.050577    0.088309  0.001369   \n",
       "24   3.396785e-03   0.041641     0.040713    0.013894    0.158393  0.000163   \n",
       "33   9.403402e-03   0.003327     0.024324    0.302406    0.185639  0.000672   \n",
       "41   1.096958e-02   0.048059     0.060456    0.054257    0.097379  0.000084   \n",
       "..            ...        ...          ...         ...         ...       ...   \n",
       "412  4.269644e-05   0.000016     0.018005    0.019971    0.009111  0.000082   \n",
       "413  6.054611e-03   0.000002     0.062586    0.095856    0.043977  0.000638   \n",
       "414  2.447322e-07   0.000006     0.046802    0.340756    0.052835  0.000410   \n",
       "415  1.076841e-03   0.000132     0.031584    0.020308    0.012922  0.000071   \n",
       "417  7.891968e-03   0.006893     0.060843    0.114456    0.074855  0.000914   \n",
       "\n",
       "          myocyte         other    T-cell     tumor  ... cellularity    fga  \\\n",
       "2    1.216315e-02  2.098187e-06  0.028711  0.832527  ...        0.36  0.572   \n",
       "6    9.219069e-07  1.354588e-06  0.031462  0.762338  ...        0.48  0.098   \n",
       "24   6.779418e-04  1.593186e-06  0.041585  0.699535  ...        0.66  0.245   \n",
       "33   9.655291e-07  1.128296e-06  0.020712  0.453513  ...        0.27  0.436   \n",
       "41   5.340647e-03  1.951452e-06  0.038107  0.685345  ...        0.56  0.542   \n",
       "..            ...           ...       ...       ...  ...         ...    ...   \n",
       "412  7.632417e-03  3.212852e-04  0.002373  0.942446  ...        0.63  0.562   \n",
       "413  5.265638e-04  1.956283e-01  0.000798  0.593934  ...        0.36  0.736   \n",
       "414  2.725393e-07  5.001734e-07  0.007906  0.551284  ...        0.40  0.778   \n",
       "415  3.760127e-04  3.780077e-04  0.006510  0.926642  ...        0.61  0.642   \n",
       "417  5.875009e-02  4.273614e-06  0.012290  0.663102  ...        0.31  0.603   \n",
       "\n",
       "     FGA_status  sample_match      sample_y primary_site    Patient ID  \\\n",
       "2          High  TCGA-CN-5374  TCGA-CN-5374   Oropharynx  TCGA-CN-5374   \n",
       "6        Silent  TCGA-CR-5249  TCGA-CR-5249   Oropharynx  TCGA-CR-5249   \n",
       "24         High  TCGA-CV-6433  TCGA-CV-6433  Oral Cavity  TCGA-CV-6433   \n",
       "33         High  TCGA-H7-A76A  TCGA-H7-A76A   Oropharynx  TCGA-H7-A76A   \n",
       "41         High  TCGA-BB-4225  TCGA-BB-4225   Oropharynx  TCGA-BB-4225   \n",
       "..          ...           ...           ...          ...           ...   \n",
       "412        High  TCGA-C9-A47Z  TCGA-C9-A47Z  Oral Cavity  TCGA-C9-A47Z   \n",
       "413        High  TCGA-CN-6010  TCGA-CN-6010       Larynx  TCGA-CN-6010   \n",
       "414        High  TCGA-CV-7235  TCGA-CV-7235  Oral Cavity  TCGA-CV-7235   \n",
       "415        High  TCGA-CX-7086  TCGA-CX-7086  Oral Cavity  TCGA-CX-7086   \n",
       "417        High  TCGA-HD-A6HZ  TCGA-HD-A6HZ  Oral Cavity  TCGA-HD-A6HZ   \n",
       "\n",
       "    Overall Survival (Months)  Overall Survival Status hpv_status  \n",
       "2                       56.90                 DECEASED   Positive  \n",
       "6                       37.84                   LIVING   Positive  \n",
       "24                      21.06                   LIVING   Positive  \n",
       "33                      20.93                   LIVING   Positive  \n",
       "41                       4.80                   LIVING   Positive  \n",
       "..                        ...                      ...        ...  \n",
       "412                      6.27                 DECEASED   Negative  \n",
       "413                     50.03                   LIVING   Negative  \n",
       "414                     77.10                   LIVING   Negative  \n",
       "415                     18.82                   LIVING   Negative  \n",
       "417                      3.65                   LIVING   Negative  \n",
       "\n",
       "[414 rows x 21 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged_nonrelative"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7008e32b",
   "metadata": {
    "scrolled": true
   },
   "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>B-cells</th>\n",
       "      <th>CD14-cells</th>\n",
       "      <th>CD8-cells</th>\n",
       "      <th>Endothelial</th>\n",
       "      <th>Fibroblast</th>\n",
       "      <th>Macrophage</th>\n",
       "      <th>Mast</th>\n",
       "      <th>NK-cells</th>\n",
       "      <th>pDC-cells</th>\n",
       "      <th>Tconv-cell</th>\n",
       "      <th>...</th>\n",
       "      <th>cellularity</th>\n",
       "      <th>fga</th>\n",
       "      <th>FGA_status</th>\n",
       "      <th>sample_match</th>\n",
       "      <th>sample_y</th>\n",
       "      <th>primary_site</th>\n",
       "      <th>Patient ID</th>\n",
       "      <th>Overall Survival (Months)</th>\n",
       "      <th>Overall Survival Status</th>\n",
       "      <th>hpv_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.620612e-03</td>\n",
       "      <td>0.002204</td>\n",
       "      <td>0.014791</td>\n",
       "      <td>0.037763</td>\n",
       "      <td>0.022564</td>\n",
       "      <td>0.042804</td>\n",
       "      <td>0.000541</td>\n",
       "      <td>0.003753</td>\n",
       "      <td>0.006411</td>\n",
       "      <td>1.306061e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.572</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CN-5374</td>\n",
       "      <td>TCGA-CN-5374</td>\n",
       "      <td>Oropharynx</td>\n",
       "      <td>TCGA-CN-5374</td>\n",
       "      <td>56.90</td>\n",
       "      <td>DECEASED</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8.501797e-03</td>\n",
       "      <td>0.004056</td>\n",
       "      <td>0.013711</td>\n",
       "      <td>0.054489</td>\n",
       "      <td>0.044358</td>\n",
       "      <td>0.066875</td>\n",
       "      <td>0.001113</td>\n",
       "      <td>0.012184</td>\n",
       "      <td>0.013605</td>\n",
       "      <td>4.213912e-07</td>\n",
       "      <td>...</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.098</td>\n",
       "      <td>Silent</td>\n",
       "      <td>TCGA-CR-5249</td>\n",
       "      <td>TCGA-CR-5249</td>\n",
       "      <td>Oropharynx</td>\n",
       "      <td>TCGA-CR-5249</td>\n",
       "      <td>37.84</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2.015392e-03</td>\n",
       "      <td>0.051412</td>\n",
       "      <td>0.035599</td>\n",
       "      <td>0.047367</td>\n",
       "      <td>0.009128</td>\n",
       "      <td>0.139650</td>\n",
       "      <td>0.000177</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.042890</td>\n",
       "      <td>7.530978e-07</td>\n",
       "      <td>...</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.245</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CV-6433</td>\n",
       "      <td>TCGA-CV-6433</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-CV-6433</td>\n",
       "      <td>21.06</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>9.055811e-03</td>\n",
       "      <td>0.003418</td>\n",
       "      <td>0.021548</td>\n",
       "      <td>0.025543</td>\n",
       "      <td>0.296215</td>\n",
       "      <td>0.174300</td>\n",
       "      <td>0.000691</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.018348</td>\n",
       "      <td>3.856858e-07</td>\n",
       "      <td>...</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.436</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-H7-A76A</td>\n",
       "      <td>TCGA-H7-A76A</td>\n",
       "      <td>Oropharynx</td>\n",
       "      <td>TCGA-H7-A76A</td>\n",
       "      <td>20.93</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1.100306e-02</td>\n",
       "      <td>0.055995</td>\n",
       "      <td>0.034966</td>\n",
       "      <td>0.063223</td>\n",
       "      <td>0.048292</td>\n",
       "      <td>0.068426</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.000053</td>\n",
       "      <td>0.054114</td>\n",
       "      <td>4.731678e-07</td>\n",
       "      <td>...</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.542</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-BB-4225</td>\n",
       "      <td>TCGA-BB-4225</td>\n",
       "      <td>Oropharynx</td>\n",
       "      <td>TCGA-BB-4225</td>\n",
       "      <td>4.80</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>412</th>\n",
       "      <td>1.794621e-05</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>0.001660</td>\n",
       "      <td>0.012728</td>\n",
       "      <td>0.012865</td>\n",
       "      <td>0.002925</td>\n",
       "      <td>0.000026</td>\n",
       "      <td>0.001184</td>\n",
       "      <td>0.000126</td>\n",
       "      <td>6.463346e-03</td>\n",
       "      <td>...</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.562</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-C9-A47Z</td>\n",
       "      <td>TCGA-C9-A47Z</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-C9-A47Z</td>\n",
       "      <td>6.27</td>\n",
       "      <td>DECEASED</td>\n",
       "      <td>Negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>413</th>\n",
       "      <td>6.985689e-03</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>0.068687</td>\n",
       "      <td>0.092435</td>\n",
       "      <td>0.102898</td>\n",
       "      <td>0.000816</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>1.907857e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.736</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CN-6010</td>\n",
       "      <td>TCGA-CN-6010</td>\n",
       "      <td>Larynx</td>\n",
       "      <td>TCGA-CN-6010</td>\n",
       "      <td>50.03</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>3.909553e-07</td>\n",
       "      <td>0.000652</td>\n",
       "      <td>0.011922</td>\n",
       "      <td>0.051758</td>\n",
       "      <td>0.331036</td>\n",
       "      <td>0.043414</td>\n",
       "      <td>0.000374</td>\n",
       "      <td>0.001721</td>\n",
       "      <td>0.000740</td>\n",
       "      <td>2.944636e-07</td>\n",
       "      <td>...</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.778</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CV-7235</td>\n",
       "      <td>TCGA-CV-7235</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-CV-7235</td>\n",
       "      <td>77.10</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>1.092963e-03</td>\n",
       "      <td>0.000544</td>\n",
       "      <td>0.005968</td>\n",
       "      <td>0.032534</td>\n",
       "      <td>0.013663</td>\n",
       "      <td>0.005613</td>\n",
       "      <td>0.000060</td>\n",
       "      <td>0.002352</td>\n",
       "      <td>0.002253</td>\n",
       "      <td>1.266288e-06</td>\n",
       "      <td>...</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.642</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CX-7086</td>\n",
       "      <td>TCGA-CX-7086</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-CX-7086</td>\n",
       "      <td>18.82</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>8.469815e-03</td>\n",
       "      <td>0.010019</td>\n",
       "      <td>0.004468</td>\n",
       "      <td>0.061878</td>\n",
       "      <td>0.117164</td>\n",
       "      <td>0.050565</td>\n",
       "      <td>0.000399</td>\n",
       "      <td>0.006222</td>\n",
       "      <td>0.002939</td>\n",
       "      <td>6.468833e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.31</td>\n",
       "      <td>0.603</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-HD-A6HZ</td>\n",
       "      <td>TCGA-HD-A6HZ</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-HD-A6HZ</td>\n",
       "      <td>3.65</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>414 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          B-cells  CD14-cells  CD8-cells  Endothelial  Fibroblast  Macrophage  \\\n",
       "2    5.620612e-03    0.002204   0.014791     0.037763    0.022564    0.042804   \n",
       "6    8.501797e-03    0.004056   0.013711     0.054489    0.044358    0.066875   \n",
       "24   2.015392e-03    0.051412   0.035599     0.047367    0.009128    0.139650   \n",
       "33   9.055811e-03    0.003418   0.021548     0.025543    0.296215    0.174300   \n",
       "41   1.100306e-02    0.055995   0.034966     0.063223    0.048292    0.068426   \n",
       "..            ...         ...        ...          ...         ...         ...   \n",
       "412  1.794621e-05    0.000022   0.001660     0.012728    0.012865    0.002925   \n",
       "413  6.985689e-03    0.000002   0.000021     0.068687    0.092435    0.102898   \n",
       "414  3.909553e-07    0.000652   0.011922     0.051758    0.331036    0.043414   \n",
       "415  1.092963e-03    0.000544   0.005968     0.032534    0.013663    0.005613   \n",
       "417  8.469815e-03    0.010019   0.004468     0.061878    0.117164    0.050565   \n",
       "\n",
       "         Mast  NK-cells  pDC-cells    Tconv-cell  ...  cellularity    fga  \\\n",
       "2    0.000541  0.003753   0.006411  1.306061e-02  ...         0.36  0.572   \n",
       "6    0.001113  0.012184   0.013605  4.213912e-07  ...         0.48  0.098   \n",
       "24   0.000177  0.000005   0.042890  7.530978e-07  ...         0.66  0.245   \n",
       "33   0.000691  0.000004   0.018348  3.856858e-07  ...         0.27  0.436   \n",
       "41   0.000095  0.000053   0.054114  4.731678e-07  ...         0.56  0.542   \n",
       "..        ...       ...        ...           ...  ...          ...    ...   \n",
       "412  0.000026  0.001184   0.000126  6.463346e-03  ...         0.63  0.562   \n",
       "413  0.000816  0.000008   0.000001  1.907857e-02  ...         0.36  0.736   \n",
       "414  0.000374  0.001721   0.000740  2.944636e-07  ...         0.40  0.778   \n",
       "415  0.000060  0.002352   0.002253  1.266288e-06  ...         0.61  0.642   \n",
       "417  0.000399  0.006222   0.002939  6.468833e-02  ...         0.31  0.603   \n",
       "\n",
       "    FGA_status  sample_match      sample_y primary_site    Patient ID  \\\n",
       "2         High  TCGA-CN-5374  TCGA-CN-5374   Oropharynx  TCGA-CN-5374   \n",
       "6       Silent  TCGA-CR-5249  TCGA-CR-5249   Oropharynx  TCGA-CR-5249   \n",
       "24        High  TCGA-CV-6433  TCGA-CV-6433  Oral Cavity  TCGA-CV-6433   \n",
       "33        High  TCGA-H7-A76A  TCGA-H7-A76A   Oropharynx  TCGA-H7-A76A   \n",
       "41        High  TCGA-BB-4225  TCGA-BB-4225   Oropharynx  TCGA-BB-4225   \n",
       "..         ...           ...           ...          ...           ...   \n",
       "412       High  TCGA-C9-A47Z  TCGA-C9-A47Z  Oral Cavity  TCGA-C9-A47Z   \n",
       "413       High  TCGA-CN-6010  TCGA-CN-6010       Larynx  TCGA-CN-6010   \n",
       "414       High  TCGA-CV-7235  TCGA-CV-7235  Oral Cavity  TCGA-CV-7235   \n",
       "415       High  TCGA-CX-7086  TCGA-CX-7086  Oral Cavity  TCGA-CX-7086   \n",
       "417       High  TCGA-HD-A6HZ  TCGA-HD-A6HZ  Oral Cavity  TCGA-HD-A6HZ   \n",
       "\n",
       "    Overall Survival (Months) Overall Survival Status hpv_status  \n",
       "2                       56.90                DECEASED   Positive  \n",
       "6                       37.84                  LIVING   Positive  \n",
       "24                      21.06                  LIVING   Positive  \n",
       "33                      20.93                  LIVING   Positive  \n",
       "41                       4.80                  LIVING   Positive  \n",
       "..                        ...                     ...        ...  \n",
       "412                      6.27                DECEASED   Negative  \n",
       "413                     50.03                  LIVING   Negative  \n",
       "414                     77.10                  LIVING   Negative  \n",
       "415                     18.82                  LIVING   Negative  \n",
       "417                      3.65                  LIVING   Negative  \n",
       "\n",
       "[414 rows x 23 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged_subtypes_nonrelative"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55d90003",
   "metadata": {},
   "source": [
    "# replicating Puram decon paper\n",
    "## TME defined subclasses\n",
    "Association between cell proportions and overall survival in patients with HNSCC profiled by TCGA. Estimated cell proportions were stratified by a half–half split, and the separation between survival curves was evaluated using a log-rank test."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "9a6403bd",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_32099/3956061433.py:3: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted['B-cell group'][:int(len(df_merged_nonrelative)/2)]='Low'\n",
      "/tmp/ipykernel_32099/3956061433.py:4: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted['B-cell group'][int(len(df_merged_nonrelative)/2):]='High'\n"
     ]
    }
   ],
   "source": [
    "df_merged_nonrelative_sorted = df_merged_HPVneg.sort_values('B-cell')\n",
    "df_merged_nonrelative_sorted['B-cell group']=''\n",
    "df_merged_nonrelative_sorted['B-cell group'][:int(len(df_merged_nonrelative)/2)]='Low'\n",
    "df_merged_nonrelative_sorted['B-cell group'][int(len(df_merged_nonrelative)/2):]='High'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "2af3db07",
   "metadata": {
    "collapsed": true
   },
   "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>B-cell</th>\n",
       "      <th>Dendritic</th>\n",
       "      <th>Endothelial</th>\n",
       "      <th>Fibroblast</th>\n",
       "      <th>Macrophage</th>\n",
       "      <th>Mast</th>\n",
       "      <th>myocyte</th>\n",
       "      <th>other</th>\n",
       "      <th>T-cell</th>\n",
       "      <th>tumor</th>\n",
       "      <th>...</th>\n",
       "      <th>fga</th>\n",
       "      <th>FGA_status</th>\n",
       "      <th>sample_match</th>\n",
       "      <th>sample_y</th>\n",
       "      <th>primary_site</th>\n",
       "      <th>Patient ID</th>\n",
       "      <th>Overall Survival (Months)</th>\n",
       "      <th>Overall Survival Status</th>\n",
       "      <th>hpv_status</th>\n",
       "      <th>B-cell group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>1.190561e-07</td>\n",
       "      <td>2.474051e-07</td>\n",
       "      <td>0.021832</td>\n",
       "      <td>0.860649</td>\n",
       "      <td>0.024076</td>\n",
       "      <td>1.715053e-07</td>\n",
       "      <td>1.068588e-07</td>\n",
       "      <td>1.382516e-07</td>\n",
       "      <td>2.788593e-07</td>\n",
       "      <td>0.093441</td>\n",
       "      <td>...</td>\n",
       "      <td>0.396</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CQ-6221</td>\n",
       "      <td>TCGA-CQ-6221</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-CQ-6221</td>\n",
       "      <td>32.85</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>384</th>\n",
       "      <td>1.438484e-07</td>\n",
       "      <td>2.689546e-07</td>\n",
       "      <td>0.009661</td>\n",
       "      <td>0.802536</td>\n",
       "      <td>0.036985</td>\n",
       "      <td>2.172633e-05</td>\n",
       "      <td>5.139043e-05</td>\n",
       "      <td>1.466198e-07</td>\n",
       "      <td>3.105177e-07</td>\n",
       "      <td>0.150743</td>\n",
       "      <td>...</td>\n",
       "      <td>0.541</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-IQ-A61O</td>\n",
       "      <td>TCGA-IQ-A61O</td>\n",
       "      <td>Oropharynx</td>\n",
       "      <td>TCGA-IQ-A61O</td>\n",
       "      <td>13.83</td>\n",
       "      <td>DECEASED</td>\n",
       "      <td>Negative</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>307</th>\n",
       "      <td>1.633674e-07</td>\n",
       "      <td>4.511910e-07</td>\n",
       "      <td>0.024422</td>\n",
       "      <td>0.489952</td>\n",
       "      <td>0.050825</td>\n",
       "      <td>2.763190e-07</td>\n",
       "      <td>8.484362e-02</td>\n",
       "      <td>2.013747e-07</td>\n",
       "      <td>7.161861e-04</td>\n",
       "      <td>0.349240</td>\n",
       "      <td>...</td>\n",
       "      <td>0.745</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CQ-6224</td>\n",
       "      <td>TCGA-CQ-6224</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-CQ-6224</td>\n",
       "      <td>56.54</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>2.390008e-07</td>\n",
       "      <td>4.310074e-07</td>\n",
       "      <td>0.014317</td>\n",
       "      <td>0.576152</td>\n",
       "      <td>0.040460</td>\n",
       "      <td>2.195232e-04</td>\n",
       "      <td>1.236877e-01</td>\n",
       "      <td>2.881325e-07</td>\n",
       "      <td>3.712601e-06</td>\n",
       "      <td>0.245159</td>\n",
       "      <td>...</td>\n",
       "      <td>0.235</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CN-6016</td>\n",
       "      <td>TCGA-CN-6016</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-CN-6016</td>\n",
       "      <td>47.40</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>2.447322e-07</td>\n",
       "      <td>5.819924e-06</td>\n",
       "      <td>0.046802</td>\n",
       "      <td>0.340756</td>\n",
       "      <td>0.052835</td>\n",
       "      <td>4.104470e-04</td>\n",
       "      <td>2.725393e-07</td>\n",
       "      <td>5.001734e-07</td>\n",
       "      <td>7.906435e-03</td>\n",
       "      <td>0.551284</td>\n",
       "      <td>...</td>\n",
       "      <td>0.778</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CV-7235</td>\n",
       "      <td>TCGA-CV-7235</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-CV-7235</td>\n",
       "      <td>77.10</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>1.464691e-02</td>\n",
       "      <td>1.829896e-03</td>\n",
       "      <td>0.048516</td>\n",
       "      <td>0.024198</td>\n",
       "      <td>0.055318</td>\n",
       "      <td>1.797958e-03</td>\n",
       "      <td>3.428617e-04</td>\n",
       "      <td>6.407169e-02</td>\n",
       "      <td>2.589854e-02</td>\n",
       "      <td>0.763380</td>\n",
       "      <td>...</td>\n",
       "      <td>0.706</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CV-7242</td>\n",
       "      <td>TCGA-CV-7242</td>\n",
       "      <td>Larynx</td>\n",
       "      <td>TCGA-CV-7242</td>\n",
       "      <td>35.97</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>1.472977e-02</td>\n",
       "      <td>1.758920e-06</td>\n",
       "      <td>0.097364</td>\n",
       "      <td>0.136325</td>\n",
       "      <td>0.050838</td>\n",
       "      <td>1.533377e-04</td>\n",
       "      <td>2.917146e-03</td>\n",
       "      <td>3.170684e-02</td>\n",
       "      <td>1.080287e-02</td>\n",
       "      <td>0.655161</td>\n",
       "      <td>...</td>\n",
       "      <td>0.806</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CV-7248</td>\n",
       "      <td>TCGA-CV-7248</td>\n",
       "      <td>Larynx</td>\n",
       "      <td>TCGA-CV-7248</td>\n",
       "      <td>17.12</td>\n",
       "      <td>DECEASED</td>\n",
       "      <td>Negative</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393</th>\n",
       "      <td>1.518479e-02</td>\n",
       "      <td>5.355360e-05</td>\n",
       "      <td>0.095030</td>\n",
       "      <td>0.061323</td>\n",
       "      <td>0.084360</td>\n",
       "      <td>9.033053e-04</td>\n",
       "      <td>3.420620e-05</td>\n",
       "      <td>6.854778e-06</td>\n",
       "      <td>7.721582e-02</td>\n",
       "      <td>0.665888</td>\n",
       "      <td>...</td>\n",
       "      <td>0.487</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-BB-4217</td>\n",
       "      <td>TCGA-BB-4217</td>\n",
       "      <td>Larynx</td>\n",
       "      <td>TCGA-BB-4217</td>\n",
       "      <td>6.14</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>1.593262e-02</td>\n",
       "      <td>3.396562e-04</td>\n",
       "      <td>0.090168</td>\n",
       "      <td>0.281000</td>\n",
       "      <td>0.196304</td>\n",
       "      <td>1.955797e-03</td>\n",
       "      <td>2.049138e-02</td>\n",
       "      <td>1.125537e-06</td>\n",
       "      <td>3.191061e-02</td>\n",
       "      <td>0.361898</td>\n",
       "      <td>...</td>\n",
       "      <td>0.613</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CN-4733</td>\n",
       "      <td>TCGA-CN-4733</td>\n",
       "      <td>Oral Cavity</td>\n",
       "      <td>TCGA-CN-4733</td>\n",
       "      <td>52.10</td>\n",
       "      <td>LIVING</td>\n",
       "      <td>Negative</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>4.661268e-02</td>\n",
       "      <td>1.316282e-04</td>\n",
       "      <td>0.079778</td>\n",
       "      <td>0.102721</td>\n",
       "      <td>0.109197</td>\n",
       "      <td>8.093525e-04</td>\n",
       "      <td>2.694748e-05</td>\n",
       "      <td>1.112117e-03</td>\n",
       "      <td>1.723978e-02</td>\n",
       "      <td>0.642372</td>\n",
       "      <td>...</td>\n",
       "      <td>0.751</td>\n",
       "      <td>High</td>\n",
       "      <td>TCGA-CV-A45W</td>\n",
       "      <td>TCGA-CV-A45W</td>\n",
       "      <td>Larynx</td>\n",
       "      <td>TCGA-CV-A45W</td>\n",
       "      <td>45.93</td>\n",
       "      <td>DECEASED</td>\n",
       "      <td>Negative</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>354 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           B-cell     Dendritic  Endothelial  Fibroblast  Macrophage  \\\n",
       "154  1.190561e-07  2.474051e-07     0.021832    0.860649    0.024076   \n",
       "384  1.438484e-07  2.689546e-07     0.009661    0.802536    0.036985   \n",
       "307  1.633674e-07  4.511910e-07     0.024422    0.489952    0.050825   \n",
       "124  2.390008e-07  4.310074e-07     0.014317    0.576152    0.040460   \n",
       "414  2.447322e-07  5.819924e-06     0.046802    0.340756    0.052835   \n",
       "..            ...           ...          ...         ...         ...   \n",
       "113  1.464691e-02  1.829896e-03     0.048516    0.024198    0.055318   \n",
       "67   1.472977e-02  1.758920e-06     0.097364    0.136325    0.050838   \n",
       "393  1.518479e-02  5.355360e-05     0.095030    0.061323    0.084360   \n",
       "407  1.593262e-02  3.396562e-04     0.090168    0.281000    0.196304   \n",
       "8    4.661268e-02  1.316282e-04     0.079778    0.102721    0.109197   \n",
       "\n",
       "             Mast       myocyte         other        T-cell     tumor  ...  \\\n",
       "154  1.715053e-07  1.068588e-07  1.382516e-07  2.788593e-07  0.093441  ...   \n",
       "384  2.172633e-05  5.139043e-05  1.466198e-07  3.105177e-07  0.150743  ...   \n",
       "307  2.763190e-07  8.484362e-02  2.013747e-07  7.161861e-04  0.349240  ...   \n",
       "124  2.195232e-04  1.236877e-01  2.881325e-07  3.712601e-06  0.245159  ...   \n",
       "414  4.104470e-04  2.725393e-07  5.001734e-07  7.906435e-03  0.551284  ...   \n",
       "..            ...           ...           ...           ...       ...  ...   \n",
       "113  1.797958e-03  3.428617e-04  6.407169e-02  2.589854e-02  0.763380  ...   \n",
       "67   1.533377e-04  2.917146e-03  3.170684e-02  1.080287e-02  0.655161  ...   \n",
       "393  9.033053e-04  3.420620e-05  6.854778e-06  7.721582e-02  0.665888  ...   \n",
       "407  1.955797e-03  2.049138e-02  1.125537e-06  3.191061e-02  0.361898  ...   \n",
       "8    8.093525e-04  2.694748e-05  1.112117e-03  1.723978e-02  0.642372  ...   \n",
       "\n",
       "       fga  FGA_status  sample_match      sample_y primary_site    Patient ID  \\\n",
       "154  0.396        High  TCGA-CQ-6221  TCGA-CQ-6221  Oral Cavity  TCGA-CQ-6221   \n",
       "384  0.541        High  TCGA-IQ-A61O  TCGA-IQ-A61O   Oropharynx  TCGA-IQ-A61O   \n",
       "307  0.745        High  TCGA-CQ-6224  TCGA-CQ-6224  Oral Cavity  TCGA-CQ-6224   \n",
       "124  0.235        High  TCGA-CN-6016  TCGA-CN-6016  Oral Cavity  TCGA-CN-6016   \n",
       "414  0.778        High  TCGA-CV-7235  TCGA-CV-7235  Oral Cavity  TCGA-CV-7235   \n",
       "..     ...         ...           ...           ...          ...           ...   \n",
       "113  0.706        High  TCGA-CV-7242  TCGA-CV-7242       Larynx  TCGA-CV-7242   \n",
       "67   0.806        High  TCGA-CV-7248  TCGA-CV-7248       Larynx  TCGA-CV-7248   \n",
       "393  0.487        High  TCGA-BB-4217  TCGA-BB-4217       Larynx  TCGA-BB-4217   \n",
       "407  0.613        High  TCGA-CN-4733  TCGA-CN-4733  Oral Cavity  TCGA-CN-4733   \n",
       "8    0.751        High  TCGA-CV-A45W  TCGA-CV-A45W       Larynx  TCGA-CV-A45W   \n",
       "\n",
       "    Overall Survival (Months) Overall Survival Status  hpv_status B-cell group  \n",
       "154                     32.85                  LIVING    Negative          Low  \n",
       "384                     13.83                DECEASED    Negative          Low  \n",
       "307                     56.54                  LIVING    Negative          Low  \n",
       "124                     47.40                  LIVING    Negative          Low  \n",
       "414                     77.10                  LIVING    Negative          Low  \n",
       "..                        ...                     ...         ...          ...  \n",
       "113                     35.97                  LIVING    Negative         High  \n",
       "67                      17.12                DECEASED    Negative         High  \n",
       "393                      6.14                  LIVING    Negative         High  \n",
       "407                     52.10                  LIVING    Negative         High  \n",
       "8                       45.93                DECEASED    Negative         High  \n",
       "\n",
       "[354 rows x 22 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged_nonrelative_sorted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "670f2121",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_32099/3591332845.py:5: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][:int(len(df_merged_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/3591332845.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][int(len(df_merged_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/3591332845.py:5: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][:int(len(df_merged_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/3591332845.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][int(len(df_merged_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/3591332845.py:5: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][:int(len(df_merged_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/3591332845.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][int(len(df_merged_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/3591332845.py:5: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][:int(len(df_merged_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/3591332845.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][int(len(df_merged_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/3591332845.py:5: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][:int(len(df_merged_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/3591332845.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][int(len(df_merged_nonrelative_sorted)/2):]=i+' High'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "B-cell group=B-cell Low    0.114637\n",
      "dtype: float64\n",
      "0.2816480100594824 0.5956230815455432\n",
      "Dendritic group=Dendritic Low   -0.06833\n",
      "dtype: float64\n",
      "0.1070557326075567 0.7435213678944668\n",
      "Endothelial group=Endothelial Low    0.44299\n",
      "dtype: float64\n",
      "4.087358868470572 0.04320510473294793\n",
      "Fibroblast group=Fibroblast Low    0.12405\n",
      "dtype: float64\n",
      "0.3525584981013277 0.5526683873472039\n",
      "Macrophage group=Macrophage Low   -0.058648\n",
      "dtype: float64\n",
      "0.07847071237783679 0.7793806508884729\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_32099/3591332845.py:5: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][:int(len(df_merged_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/3591332845.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][int(len(df_merged_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/3591332845.py:5: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][:int(len(df_merged_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/3591332845.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][int(len(df_merged_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/3591332845.py:5: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][:int(len(df_merged_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/3591332845.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][int(len(df_merged_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/3591332845.py:5: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][:int(len(df_merged_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/3591332845.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][int(len(df_merged_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/3591332845.py:5: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][:int(len(df_merged_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/3591332845.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_nonrelative_sorted[i+' group'][int(len(df_merged_nonrelative_sorted)/2):]=i+' High'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mast group=Mast Low    0.472511\n",
      "dtype: float64\n",
      "4.916799636193591 0.02659674153708515\n",
      "myocyte group=myocyte Low   -0.098381\n",
      "dtype: float64\n",
      "0.20663071253470647 0.6494211324477651\n",
      "other group=other Low    0.147954\n",
      "dtype: float64\n",
      "0.4890542642703662 0.48434947903002024\n",
      "T-cell group=T-cell Low    0.45984\n",
      "dtype: float64\n",
      "4.708196650309593 0.030019125698906423\n",
      "tumor group=tumor Low   -0.034378\n",
      "dtype: float64\n",
      "0.02695319243478559 0.8695939522136991\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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55JCNrrNo0SKy+zy//vWvs9VWW9GjRw/ee++9Gt9/8uTJdS5jbWpaUE4Skhg/fjznn38+q1ev5phjjmHrrb/4Gu/UqRMLFxa/db6hNz2VzJTWRySJYuZ9ThTWZLz99ts0a9aMTp06ERHccMMNHHvssRucM2nSJFq2bFm93axZs+oO1Vxj9Lfddtu8YqmP1TcPOeQQJk+ezLx58xgyZAhXXnklkmrsdG/dujXLly/fYF9muWuLrxg1ioqKiupaFyR38R9++OEADBgwoDoZPfHEE7zxxhvV561atSqvZFxXDb0zu2QmbnMCz6/fh/dWeB4eaxqWLFnCqFGjOOecc5DEsccey0033cSaNWuApM3+008/rfX1e++9N//617946623ALjnnnvq9L5t27at8Yu1Xbt2VFRU8OCDDwKwevXqOnXUtm/fnu233776y/SOO+6orl0ceuih3HnnnXTv3p2tttqKDh06MGHCBA4++OCNrrPPPvswZ86cOpUh0+TJk5kxY8ZGj7omCYBjjz2WJ554gg8//JAPP/yQJ554ojphv//++0DyeVx55ZWMGjWq+nVvvPEG++67b94xb4oTRS2G9Elu19hp2bSk+cmsDH322WfVw2MHDRrEMcccUz3E8swzz6RHjx7VQzHPOuus6ppDTVq1asW4ceMYPHgwAwcOZNddd61TDCeeeCIPPPAAffr02ajZ5o477uD666+nV69eHHTQQSxevHij169cuZKKiorqxzXXXMPtt9/OBRdcQK9evZgxYwaXXnop8EXn8aGHHgrAwIED2W677dh+++03uu6hhx7KSy+9VC81mypTp06loqKCP//5z5x11ln07Jk0QXbo0IGf/OQn9O3bl759+3LppZdWd2z/8pe/ZJ999qFXr16ceOKJHHnkkdXXe+qppxg8eHDR41R9fgilUFlZGcVa4W7ctT9h5PLrYdeBMOLRolzTrMprr73GPvvsU+owLIfzzjuPE088Ma/aQKm89957DB8+fIPBALWp6XdP0vSIqKzpfNcocpi4zQnMarEfLJ4Jtw1OHq5dmDUZP/7xj+vlvoT68M477/CrX/2qXq7tzuxNmNL6CHpu92KysXhm8tOd22ZNwk477cTXvva1UodRJ3379q23a7tGsQkTtzkhaXYa8Sh8aT+Y94xrFWbWpDhR5CO9GY+Z9+U+z8ysjDhRbMLsRR8z7ObnkgkCK0ckHdtmZk2IE0UOQ/p0psfO7TztuJWtcpw99g9/+APnnHNOna+Vef6mDB06lLfffrvOseXrkksuoUuXLhuVafXq1QwbNow999yTfv36MXfu3OpjF110Efvuuy/77rsv9957b/X+U045hTfffLMocbkzO4fh/boyvF9Xht38XPW048M3/TKzRqNq9lhIbuQaPnw4y5cvr9cZZKtmj62sTEZiTpo0iTZt2nDQQQcBbHAD2eYq5rVmzZrFunXr2H333Yt2zWwnnngi55xzTvU0KFVuvfVWtt9+e+bMmcP48eO56KKLuPfee3n00Ud58cUXmTFjBqtXr+awww7j+OOPp127dpx99tlcddVV/O53v9vsuFyjqIOqm+9cq7ByVjV77I033khEsG7dOi644AL69u1Lr169uPnmm4Hki/3www9n6NCh7L333nzrW9+qvintscceY++992bgwIHcf//91dcePXo0I0eO5JhjjuHUU0+trm3MnTuXsWPHcu2111bfcDd69GiuvvpqAObMmcOgQYPo3bs3+++/f/Vd33WVea2pU6fSq1cvBgwYwAUXXLDBHcwLFy7kuOOOo3v37lx44YU1Xuuuu+5iyJAh1dtt2rThkksuoXfv3vTv37/WuZ/y0b9/f3beeeeN9j/00EOcdtppQFKrmThxIhHB7NmzOeyww9h6663Zdttt6d27N4899hiQTCXyt7/9LedNknXlGkUdDO/XdcMkUTXyycNkrVj+evEXw6+L5Uv7JVPn56Exzh5bdXd5lWXLltU4pHXEiBGMGzeOgw46iIsvvniDYzNmzOCll16iZcuW7LXXXvzgBz/YYPZWSGaT/eY3v5jH9NNPP6V///78/Oc/58ILL+R3v/sd//3f/73Ba5566inOP//8jWLZZpttNmhu25TM2WS33npr2rdvz9KlS+nduzdjxozhhz/8IStXruSpp56iR48eQDJ1+Z577snLL7/MAQccUOf3qokTRb72G5okCk8WaGWqsc0em9l8BkmfQ/bsDB999BErVqyobt4aPnw4jzzySPXxo446ivbt2wPQo0cP5s2bt1GiyJ5NtkWLFtV9MAcccABPPvnkRrEdccQRG8RWqNpmkz3mmGOYOnUqBx10EDvuuCMDBgyocTZZJ4otaPaijxk2fW8ubbEfLFrOyy+8w/B+XUsdlpWDPP/yry/lOnvspq5VW3kytW7dmlWrvpgktHnz5tXlre01xapRVFRU8O6771JRUcHatWtZvnx59dxPl1xyCZdccgmQJMDM/o1izSbrPoo6qhoBVWXl5+vcZ2FlpVxmj63J9ttvT9u2bXn++ecBGD9+fN7XKGQ22aoaRfYjnyQBSW2sasnT++67jyOPPBJJrFu3jqVLlwLwyiuv8Morr1Q3D0Lyb1Y10eDmcKKoo+H9unLvWQO496wB9Ny5Pdu0aLbhPRZmjVA5zB5bV7feeisjR45kwIABRER1U1NdDR48eIM1IurDhRdeSEVFRfWMuKNHjwbgjDPOYOnSpey5555cc801XHFFUgNds2YNhxxyCD169GDkyJHceeed1U1P7733Hq1bt66xczxfnj22ELcN5r0Vqzi35f8we9HH9Ni5Hfee5bW1LT+ePXbL+uSTT6rvT7jiiitYtGgRv/71r+v8+s8++4wjjjiCKVOm0KxZs/oKs2iuvfZa2rVrxxlnnLHRMc8eu4Xs1LYV9541YIPmKDNruB599FH69OnDvvvuy+TJkzcaobQprVu3ZsyYMSxY0DianLfbbrvqIbWba7M6syVtC6yKiHVFiaYxqZ4ccO9SR2JmdTBs2LCNhuzmK7tjvyEbMaJ4ozLzqlFI2krScEmPSnofeB1YJGmWpF9K6r6pa5SFrMkBq+7aNstXuTX9WsNXyO9cvk1PTwF7AP8FfCkiukREJ+AQ4HngCknfzjuKxiZjcsCqu7Z//MBMJwvLS6tWrVi6dKmThW0xEcHSpUtrvSelNvk2PQ2KiDWSdo2I6lskI2IZ8BfgL5Ka53nNRq3qPoofPzCTh2Ys8H0VVmcVFRXMnz+fJUuWlDoUa0JatWpVfbNkXeWVKCJiTfr0AWD/zGOS+kfE8xnnNBkbTfFhVgfNmzenW7dupQ7DbJPy7aM4WdIVQFtJ+0jKHCM2rrbXmZlZ45Vv09MUoBVwJnANsJekj4CFwGfFDa0RWDwTbhsMwKVLl3Pf5wMYdnPSb+EmKDMrF/k2PS0A/ijprYiYAiCpA9CNZARU01E18inVff1chraAUxYNAnCiMLOykVeikKRITKnal3ZkL8s+p4gxNkyVIzaYPbbFbYPpCfT4vN0Xixw5WZhZGch7eKykH0ja4BtQUgtJR0q6HSjOrYCNlBc5MrNyk28fxXHAfwD3SOoGfAS0Jkk4TwDXRsSMYgbYqCyeyXDO5pOd9mciJ5Q6GjOzosi3j2IV8Fvgt+n9Eh2BzyLio3qIrXGp6rNYPJODYzkTt3GiMLPykLPpSVIPSXdmbE+U1BOq76noC5wj6cBC3lzScZL+KWmOpItrON5e0v9KejmdJqThLilXOQJGPJosP2lmVkY21UcxEcicYrEiImYBSDoIuAPoCvxB0kn5vHF6D8ZvgOOBHsA3JfXIOu37wOyI6A0cDvxKUot83qcUdlvzNpcuvSCdNNDMrHHbVKI4Bvh5xvbHGc9PBcZGxEiSL/GL8nzvA4E5EfF2RHwOjAeGZJ0TJDf3CWhDMrqq9pVTGoL9hjK3+e50Wf0W7z1756bPNzNr4HImioiYGRHfytg1R9JQSZ2ArwMPpee9D7Ss4RK5dAbezdien+7LdCOwD8kNfTOB8zLnmKoiaaSkaZKmlXzenMoRvHzU3cyOXdlp2TTXKsys0ct3eOz5wFnAAuDFiHgWIO3YbpPntWpahT37/otjgRnALkAf4EZJG60UFBHjIqIyIip33HHHPMMovuH9uvLK9kcnG+lU5GZmjVVeiSIiFkfE0UDLiMgc1nMEyRTk+ZgPdMnYriCpOWQaAdyf3uQ3B/gXjWSloInbnMCsFu7YNrPGr6ClULObfyLiibSvIh9Tge6SuqUd1KcAD2ed8w5wFICknYC9gLcLidnMzAqzWUuhbo6IWCvpHOBxoBnw+4iYJWlUenws8DOSEVUzSZqqLoqID0oVs5lZU1SyRAEQEROACVn7xmY8X0gy8qpRWrFq7Rdra1c23FtAzMxyKajpyTZtSJ/OPLTuoGTDHdpm1ojlu3DRCkkf1/BYIenjTV+h6Rjerytvd/2GO7TNrNHLd66ntvUViJmZNUwF91FI2h7oTrLiHQAR8XQxgionK1at5b0Vq9ip1IGYmRWooEQh6UzgPJJ7H2YA/YHngCOLFlkZGNKnMyyADz5Z7URhZo1WoZ3Z55HMHDsvIo4AvgKUeO6Mhmd4v660bbU1K1at5e4X3il1OGZmBSk0UaxK16ZAUsuIeJ3kZjjL0rFNMgWWV7wzs8aq0EQxX9J2wIPAk5IeYuPpNwzYqW0r+m/1Gru/82fXKsysUSp0Co+TIuKjiBgN/AS4lWQ2WcuWrnw3pNmzrlWYWaNUUKKQdL6kCoCI+L+IeDhdU8KyVY6AXQeyX7N3+NGiHzLrFwN54c+/KnVUZmZ1VmjTUzvgcUmTJX0/nbDParPfUD7Zfh+2adGMLp+/RZs3Hyh1RGZmdaaI7CUg8nix1AsYBvw7MD8iBhUrsEJVVlbGtGnTSh1GrWb9YiA9P5/JuPbn0uag7zK8X9dSh2RmhqTpEVFZ07HNnevpfWAxsBTotJnXahI+6Z4sLf6V5X9zn4WZNQqF9lGcLWkSMBHoCHw3InoVM7By1e8b/w92Hcg2LZrxwr+WeSSUmTV4hU7hsSvwnxExo4ixNCnd189lfIuf0Xbi1tDsDE9DbmYNVqHDYy92ktgM+w2lRefetG21NV0+f4tZT9zqmoWZNVj5TjP+TPoze7pxTzOej8oRMOJRXj7qbt5tsQcrP1/n/goza7DyShQRMTD92TYi2mU82kZEu/oJsXwN79eVnju3d3+FmTVom3PDXediB9NUeT4oM2vICu3Mbgc8IWkZMB64LyLeK15YTctOn77Jo+0uZ+WidYy7dhATtzkBSKYp930WZlZqhXZmj4mInsD3gV2A/5P0t6JG1lTsNxS+tB8d27Skh+Zx8GdPATB70ceuYZhZg+Ab7kot7dje6dyJbNv1K/TUO9zb4n/4QftnmL3oY4bd/Jz7LsyspHzDXUOS1i5YPJMhzZ6lx87tXLMws5LLO1FIElBJcsNdz4i4LCJmFz+0JiitXfCl/dipbSvuPWsAPXb2YDIzK628O7MjIiR9xTfcbTlVTVA1cYe3mdW3Qkc9PSepb0RMLWo0tpEhfWofhTx7UXKPoxOFmdWnQhPFEcAoSXOBTwGRVDbcT1Es856BabcxvN+IWhNBbbUMM7NiKnTU0/HA7sCRwInAV9OfVgzp8qnMvG+Tp3pklJnVt0JrFKfVsv+nhQZiGSpH1ClJVDVLuQnKzOpToYni04znrUhqFK9tfji2gcUz4bbBG+7bb2j1lOTD+3VleL+uDLv5uY06vN3JbWbFUlCiiIhfZW5Luhp4ON/rSDoO+DXQDLglIq6o4ZzDgeuA5sAHEXFY/hE3QlXNT5kWz0x+Zq1dkd3h7RqGmRVToTWKbNuQ9FnUmaRmwG+Ao4H5wFRJD2fekyFpO+C3wHER8Y6kpnP3d+WIjRczyq5dpKpqFlXcyW1mxVRQopA0E4h0sxmwI/n3TxwIzImIt9NrjgeGAJk37w0H7o+IdwAi4v1C4jUzs8IVWqP4asbztcB7EbE2z2t0Bt7N2J4P9Ms658tA83S6kLbAryPij9kXkjQSGAnQtaubWyD3TXqFcr+HWdNU6PDYA4FlETEPGAH8SdL+eV5DNeyLrO2tgQOAwcCxwE8kfXmjF0WMi4jKiKjccccd8wyj/Azp07noU394zimzpqvQGsVPIuLPkgaSfIFfDdzExjWCXOYDXTK2K4CFNZzzQUR8Cnwq6WmgN/BGgXE3flUjoTJGP2XL7rMoBvd7mDVdhdYo1qU/BwM3RcRDQIs8rzEV6C6pm6QWwClsPHLqIeAQSVtL2oYkETXdYbgZs8vW5T4LM7NiKDRRLJB0M3AyMEFSy3yvlfZpnAM8TvLl/6eImCVplKRR6TmvAY8BrwD/IBlC+2qBMTd+GbPLmpltKYrI7haow4uSv+6PA2ZGxJuSdgb2i4gnih1gviorK2PatGmlDqN+3TY4qVXUlDByNEltjqqb+vLp+3Dnt1njIWl6RFTWdKzQG+5WAvdnbC8CFhUWnuWtppvxoNYb8ooh1yy2NfFNf2blo1g33NmWVNPNeFDrDXnFkG8HuTu/zcrH5q6ZbWZmZS6vGoWkOyLiO5LOi4hf11dQthlqmkgQ6q3vwszKX75NTwdI2hX4D0l/JOumuYhYVrTILH8l6Lsws/KXb6IYSzJcdXdgOhsmiiDPiQGtyErQd5FLTdOIeCSUWeOTV6KIiOuB6yXdFBFn11NMVgZqGiXlkVBmjVOhw2PPltQbOCTd9XREvFK8sKzoNrEIUrHVNErKI6HMGqeCRj1JOhe4C+iUPu6S9INiBmZFVDX1RyZPA2JmdVTofRRnAv3SyfqQdCXwHHBDsQKzIspjESQzs2yF3kchvpgYkPR5TdOGm5lZI1dojeI24AVJD6TbXwduLUpEZmbWoBRUo4iIa0gWLFoGfAiMiIjrihiXlamqIbN3v/BOqUMxszoqeK6niHgReLGIsViZqxoy62GyZo2L53qyLWZ4v67ce9aAoi/Tamb1y4nCzMxyKvQ+inMkbV/sYGwLq7oJ77bBMO22UkdjZg1UoTWKLwFTJf1J0nGSPDS2scm8Cc8335lZDoWOevpvoDvJkNjTgTcl/ULSHkWMzepT1frbXoPbzDah4D6KSBbbXpw+1gLbA/dJuqpIsZmZWQNQ0PDYdK6n04APgFuACyJijaStgDeBC4sXopWjmqYg3xyevtys/hR6H0VH4N8iYl7mzohYL+mrmx+WbXG1rYxXD65fvYoPWqyGpcW53srP17HN0mYwu31xLmiWjyawemShiaJldpKQdGVEXBQRrxUhLtuSalsZr57s1LYVO7VtVbTrzVq0vGjXMstLE1k9stBEcTRwUda+42vYZ41BbSvjNRI/TZuw7h0xoMSRWJPTRGZhzitRSDob+B6wu6TMhYraAlOKGZiZmTUM+dYo7gb+ClwOXJyxf0VELCtaVGZm1mDku2b2cmA58M36CcfMzBqafJuenomIgZJWAJF5iOTWCs/2ZmZWZvKtUQxMf7atn3DMzKyh8eyxZmaWU75NT1VNTjVNAuimJzOzMpRv01NRm5wkHQf8GmgG3BIRV9RyXl/geWBYRHiaU9tIsacEqS+easQao2J1ZgOQT41CUjPgNyQ3780nmbb84YiYXcN5VwKP5xOrNR1VS6w2dF4C1hqrUnZmHwjMiYi3ASSNB4YAs7PO+wHwF6BvEd7TytDwfl0bxZdvY6jxmNWklJ3ZnYF3M7bnp/uqSeoMnASMzXUhSSMlTZM0bcmSJUUP1MysKSt0KdRWkn4o6X5Jf5F0vqR8Z3mrsUM8a/s64KKIWJfrQhExLiIqI6Jyxx13zDMMMzPLpdBJAf8IrABuSLe/CdwBfCOPa8wHumRsVwALs86pBManK612BE6QtDYiHiwgZjMzK0ChiWKviOidsf2UpJfzvMZUoLukbsAC4BRgeOYJEdGt6rmkPwCPOEmYmW1ZhfZRvCSpf9WGpH7kOXtsRKwFziEZzfQa8KeImCVplKRRBcZlZmZFlu/w2Jkk/QjNgVMlvZMe6srGo5U2KSImABOy9tXYcR0Rp+d7fTMz23z5Nj15mVMzsyYm3/soqpc/lbQ90B3IHO00b6MXmZlZo1ZQZ7akM4HzSEYqzQD6A88BRxYtMjMzaxAK7cw+j+RO6XkRcQTwFcB3upmZlaFCE8WqiFgFIKllRLwO7FW8sMzMrKEo9D6K+ZK2Ax4EnpT0IRvfLGdmZmWgoEQRESelT0dLegpoDzxWtKjMzKzBKLQzuxXwPWAgyX0Vz+DV8szMylIp53oyM7NGoJRzPZmZWSNQsrmezMyscSjpXE9mZtbwea4nMzPLaXPmeuoNHJJuTo4I91GYmZWhQpdCPQ+4C+iUPu6U9INiBmZmZg1DoaOezgD6RcSnAJKuJJkU8IacrzIzs0an0FFPAtZlbK9L95mZWZkptEZxG/CCpAfS7a8DtxYlIjMza1AKnevpGkmTSKbwEDAiIl4qZmBmZtYw5J0oJAmoiIgXgReLH5KZmTUkefdRRESQTC9uZmZNQKGd2c9L6lvUSMzMrEEqtDP7CGCUpLnApyT9FBERvYoVmJmZNQyFJorjixqFmZk1WIUmivfYeOGim4oVlJmZNRxeuMjMzHLywkVmZptj8Uy4bXCpo0h8aT84/oqiX7bQRPGSpP4R8Tx44SIza6L2G1rqCLaIQhNFPzZeuOi1qoWNPPrJzJqEyhHJo8wVmiiOK2oUZmbWYBU619O8TZ+1aZKOA34NNANuiYgrso5/C7go3fwEONsLJJmZbVmF3pm92SQ1A35Dck9GD+CbknpknfYv4LC0KetnwLgtG6WZmRXa9FQMBwJzIuJtAEnjgSHA7KoTIuLZjPOfByq2aIRmRTZ70ccMu/m5UodhDcyQPp0Z3q9rqcOoVdFqFJK+lOdLOgPvZmzPT/fV5gzgr7W890hJ0yRNW7JkSZ5hmG0ZQ/p0psfO7UodhjUwsxd9zEMzFpQ6jJyKWaO4FchnMHFNK+JFjSdKR5AkioE1HY+IcaTNUpWVlTVew6zUhvfr2qD/arTSaAw1zKIliojI946T+UCXjO0KYGH2SZJ6AbcAx0fE0sIjNDOzQhTU9CTpyrrs24SpQHdJ3SS1AE4BHs66ZlfgfuA7EfFGIbGamdnmKbSP4uga9uU1o2xErAXOAR4HXgP+FBGzJI2SNCo97VJgB+C3kmZImlZgvGZmVqC8mp4knU0ya+wekl7JONQWeLbmV9UuIiYAE7L2jc14fiZwZr7XNTOz4sm3j+JukpFHlwMXZ+xfERHLihaVmZk1GHk1PUXE8oiYS9JvsCy9Q/s7wC2SvlIP8ZmZWYkV2kfxk4hYIWkgcCxwOzB2E68xM7NGqNBEsS79ORi4KSIeAloUJyQzM2tICk0UCyTdDAwDJkhquRnXMjOzBqzQL/eTSYa1HhsRHwEdgAuKFZSZmTUchSaKz4BtSdbKBmgOfFSMgMzMrGEpNFH8FujPF4liBcmU4WZmVmYKXgo1IvaX9BJARHyYTsNhZmZlptAaxZp04aEAkLQjsL5oUZmZWYNRaKK4HngA6CTp58AzwC+KFpWZmTUYha6ZfZek6cBRJOtKfD0iXitqZGZm1iAUvB5FRLwOvF7EWMzMrAHyTXJmZpaTE4WZmeXkRGFmZjk5UZiZWU5OFGZmlpMThZmZ5eREYWZmOTlRmJlZTk4UZmaWkxOFmZnl5ERhZmY5OVGYmVlOThRmZpaTE4WZmeXkRGFmZjk5UZiZWU5OFGZmlpMThZmZ5VTSRCHpOEn/lDRH0sU1HJek69Pjr0javxRxmpk1ZSVLFJKaAb8Bjgd6AN+U1CPrtOOB7uljJHDTFg3SzMxKWqM4EJgTEW9HxOfAeGBI1jlDgD9G4nlgO0k7b+lAzcyasq1L+N6dgXcztucD/epwTmdgUeZJkkaS1Djo2rVr0QM1M6svPXZpV+oQNqmUiUI17IsCziEixgHjACorKzc6bmbWUF12Ys9Sh7BJpWx6mg90ydiuABYWcI6ZmdWjUiaKqUB3Sd0ktQBOAR7OOudh4NR09FN/YHlELMq+kJmZ1Z+SNT1FxFpJ5wCPA82A30fELEmj0uNjgQnACcAcYCUwolTxmpk1VaXsoyAiJpAkg8x9YzOeB/D9LR2XmZl9wXdmm5lZTk4UZmaWkxOFmZnl5ERhZmY5KekvLh+SlgDzCnx5R+CDIobTEJV7GV2+xq/cy9hQy7drROxY04GySxSbQ9K0iKgsdRz1qdzL6PI1fuVexsZYPjc9mZlZTk4UZmaWkxPFhsaVOoAtoNzL6PI1fuVexkZXPvdRmJlZTq5RmJlZTk4UZmaWkxMFIOk4Sf+UNEfSxaWOJx+Sfi/pfUmvZuzrIOlJSW+mP7fPOPZfaTn/KenYjP0HSJqZHrteUk2LRm1xkrpIekrSa5JmSTov3V8WZZTUStI/JL2clm9Mur8sypdJUjNJL0l6JN0umzJKmpvGNUPStHRf2ZSPiGjSD5Ipzt8CdgdaAC8DPUodVx7xHwrsD7yase8q4OL0+cXAlenzHmn5WgLd0nI3S4/9AxhAsqrgX4HjS122NK6dgf3T522BN9JylEUZ01japM+bAy8A/culfFll/SFwN/BIGf6ezgU6Zu0rm/K5RgEHAnMi4u2I+BwYDwwpcUx1FhFPA8uydg8Bbk+f3w58PWP/+IhYHRH/Ilnn40BJOwPtIuK5SH5b/5jxmpKKiEUR8WL6fAXwGsm66WVRxkh8km42Tx9BmZSviqQKYDBwS8busipjDcqmfE4UyZfOuxnb89N9jdlOka4EmP7slO6vrayd0+fZ+xsUSbsBXyH5q7tsypg2ycwA3geejIiyKl/qOuBCYH3GvnIqYwBPSJouaWS6r2zKV9KFixqImtoAy3XMcG1lbfCfgaQ2wF+A/4yIj3M03Ta6MkbEOqCPpO2AByTtm+P0Rlc+SV8F3o+I6ZIOr8tLatjXoMsIHBwRCyV1Ap6U9HqOcxtd+VyjSLJ2l4ztCmBhiWIplvfSaizpz/fT/bWVdX76PHt/gyCpOUmSuCsi7k93l1UZASLiI2AScBzlVb6Dga9JmkvStHukpDspozJGxML05/vAAyRN2mVTPicKmAp0l9RNUgvgFODhEse0uR4GTkufnwY8lLH/FEktJXUDugP/SKvFKyT1T0dZnJrxmpJK47kVeC0irsk4VBZllLRjWpNAUmtgEPA6ZVI+gIj4r4ioiIjdSP5//T0ivk2ZlFHStpLaVj0HjgFepUzKB3jUU9JnxAkko2neAi4pdTx5xn4PsAhYQ/IXyRnADsBE4M30Z4eM8y9Jy/lPMkZUAJUkv9xvATeS3rVf6gcwkKT6/QowI32cUC5lBHoBL6XlexW4NN1fFuWrobyH88Wop7IoI8mIyZfTx6yq75ByKV9EeAoPMzPLzU1PZmaWkxOFmZnl5ERhZmY5OVGYmVlOThRmZpaTE4WZmeXkRGFmZjk5UViTJWk7Sd/L2H52C7znaEk/qsfrV0gaVl/Xt6bJicKasu2A6kQREQeVLpSiOYpkfRKzonGisKbsCmCPdFWyX0r6BJLpzCW9LukWSa9KukvSIElT0tXKDqy6gKRvK1mhboakmyU1y34TSZekK5n9Ddgr69iD6dTUs6qmp5b0M6Ur+aXbP5d0bjqn0KNKVsN7NbvmIGkgcA0wNI2nWzE/LGvCSj2HiB9+lOoB7MaGKwN+krF/LbAfyR9T04Hfk0wDPQR4MD1vH+B/gebp9m+BU9PnE4BdgAOAmcA2QDuSRWp+lPGeHdKfrUnm+Nkhff8X0/1bkcz7swPw78DvMl7bvoYyPQbsW+rP1o/yeng9CrOa/SsiZgJImgVMjIiQNJPkixySZp4DgKnp+hitSaeSjogT0teeDDwQESvT7eyZic+VdFL6vAvQPSKel7RU0leAnYCXImJp+t5XS7qSZGK9yTXEvRfJRHNmReNEYVaz1RnP12dsr+eL/zcCbo+I/9rEtWqceTNdxGcQMCAiVkqaBLRKD98CnA58iaQ2Q0S8IekAktlzL5f0RET8NON6OwDLI2JNHcpnVmfuo7CmbAXQdjNeP5GkP6ATgKQOknbNOudp4CRJrdM1C07MONYe+DBNEnsD/TOOPUCygFFf4PH0+rsAKyPiTuBqNu607kYDWejGyotrFNZkpc05UyS9Cvy1gNfPlvTfJGslb0WyJsj3gXmSJgBnRsSLku4lWUdjHpDZXPQYMErSKyTNRc9nXPtzSU8BH0WyVCokfSa/lLQ+fa+zs0J6HeiYlmdkRNT7cF9rGrwehVkDlCaeF4FvRMSbpY7HmjY3PZk1MJJ6kIyOmugkYQ2BaxRmZpaTaxRmZpaTE4WZmeXkRGFmZjk5UZiZWU5OFGZmlpMThZmZ5eREYWZmOf1/3KgWldnQBgQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# major cell types\n",
    "for i in df_merged_HPVneg.columns[:10]:\n",
    "    df_merged_nonrelative_sorted = df_merged_HPVneg.sort_values(i)\n",
    "    df_merged_nonrelative_sorted[i+' group']=''\n",
    "    df_merged_nonrelative_sorted[i+' group'][:int(len(df_merged_nonrelative_sorted)/2)]=i+' Low'\n",
    "    df_merged_nonrelative_sorted[i+' group'][int(len(df_merged_nonrelative_sorted)/2):]=i+' High'\n",
    "    fig = plt.subplots()\n",
    "    chisq,pval = Survival_kmCurve(df_merged_nonrelative_sorted[df_merged_nonrelative_sorted['primary_site']=='Oral Cavity'],i+' group',)\n",
    "    print(chisq,pval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "12144184",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "5d20f301",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_32099/2797385280.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/2797385280.py:7: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/2797385280.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/2797385280.py:7: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/2797385280.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/2797385280.py:7: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/2797385280.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/2797385280.py:7: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "B-cells group=B-cells Low    0.152087\n",
      "dtype: float64\n",
      "0.47873506633943597 0.48899583891300247\n",
      "CD14-cells group=CD14-cells Low   -0.111455\n",
      "dtype: float64\n",
      "0.2774025698748818 0.5984087401404127\n",
      "CD8-cells group=CD8-cells Low    0.379064\n",
      "dtype: float64\n",
      "3.2943598466623962 0.06951820097742013\n",
      "Endothelial group=Endothelial Low    0.437747\n",
      "dtype: float64\n",
      "3.922379621085421 0.04764739116842942\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_32099/2797385280.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/2797385280.py:7: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/2797385280.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/2797385280.py:7: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/2797385280.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/2797385280.py:7: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/2797385280.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/2797385280.py:7: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/2797385280.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/2797385280.py:7: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fibroblast group=Fibroblast Low    0.068725\n",
      "dtype: float64\n",
      "0.10803653241589842 0.7423906847770922\n",
      "Macrophage group=Macrophage Low   -0.193787\n",
      "dtype: float64\n",
      "0.8600345322686481 0.35372902815126883\n",
      "Mast group=Mast Low    0.562014\n",
      "dtype: float64\n",
      "6.630241101549326 0.010026169267820975\n",
      "NK-cells group=NK-cells Low    0.018848\n",
      "dtype: float64\n",
      "0.00757598388253821 0.9306396155925917\n",
      "pDC-cells group=pDC-cells Low    0.46484\n",
      "dtype: float64\n",
      "4.696437143201383 0.030225211976216703\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_32099/2797385280.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/2797385280.py:7: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/2797385280.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/2797385280.py:7: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n",
      "/tmp/ipykernel_32099/2797385280.py:6: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
      "/tmp/ipykernel_32099/2797385280.py:7: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tconv-cell group=Tconv-cell Low   -0.014604\n",
      "dtype: float64\n",
      "0.0046939165279374275 0.9453779378687015\n",
      "Treg-cells group=Treg-cells Low    0.022568\n",
      "dtype: float64\n",
      "0.011646075038708365 0.9140615459782842\n",
      "tumor group=tumor Low   -0.189979\n",
      "dtype: float64\n",
      "0.8228096767246813 0.36435996108518987\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# immune subtypes\n",
    "# major cell types\n",
    "for i in df_merged_HPVneg_subtypes.columns[:12]:\n",
    "    df_merged_subtypes_nonrelative_sorted = df_merged_HPVneg_subtypes.sort_values(i)\n",
    "    df_merged_subtypes_nonrelative_sorted[i+' group']=''\n",
    "    df_merged_subtypes_nonrelative_sorted[i+' group'][:int(len(df_merged_subtypes_nonrelative_sorted)/2)]=i+' Low'\n",
    "    df_merged_subtypes_nonrelative_sorted[i+' group'][int(len(df_merged_subtypes_nonrelative_sorted)/2):]=i+' High'\n",
    "    fig = plt.subplots()\n",
    "    chisq,pval = Survival_kmCurve(df_merged_subtypes_nonrelative_sorted[df_merged_subtypes_nonrelative_sorted['primary_site']=='Oral Cavity'],i+' group',)\n",
    "    print(chisq,pval)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9950395",
   "metadata": {},
   "source": [
    "### 3 by 2-setups: Decon results from major cell types and immune subtypes\n",
    "-\tHPV- negative oral cavity CNA-silent vs nonsilent\n",
    "-\tHPV-negative oropharynx vs HPV-positive oropharynx\n",
    "-\tOral cavity vs larynx vs oropharynx vs hypopharynx (all HPV-negative)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "9c2a3b88",
   "metadata": {},
   "outputs": [],
   "source": [
    "def Survival_kmCurve(df,condition,):\n",
    "    df = df.dropna()\n",
    "    list_col = ['Overall Survival Status','Overall Survival (Months)']\n",
    "    list_col.append(condition)\n",
    "    df = df.loc[:,list_col]\n",
    "    df.loc[:,'Overall Survival Status'] = df.loc[:,'Overall Survival Status'].map({'DECEASED':True,'LIVING':False})\n",
    "    df.loc[:,'Overall Survival (Days)'] = df.loc[:,'Overall Survival (Months)']*30\n",
    "\n",
    "    data_x,data_y = get_x_y(df,['Overall Survival Status','Overall Survival (Days)'],True)\n",
    "#     fig = plt.subplots()\n",
    "    \n",
    "    for value in data_x[condition].unique():\n",
    "        mask = data_x[condition] == value\n",
    "        time_cell, survival_prob_cell = kaplan_meier_estimator(data_y[\"Overall Survival Status\"][mask],\n",
    "                                                               data_y[\"Overall Survival (Days)\"][mask])\n",
    "        plt.step(time_cell, survival_prob_cell, where=\"post\",\n",
    "                 label=\"%s (n = %d)\" % (value, mask.sum()))\n",
    "\n",
    "    plt.ylabel(\"est. probability of survival $\\hat{S}(t)$\")\n",
    "    plt.xlabel(\"time:days $t$\")\n",
    "    plt.legend(loc=\"best\")\n",
    "    \n",
    "    chisq,pval = compare_survival(data_y,data_x[condition])\n",
    "    \n",
    "    data_x_numeric = OneHotEncoder().fit_transform(data_x.drop('Overall Survival (Months)',axis=1).astype('category'))\n",
    "    # print(data_x_numeric.head())\n",
    "\n",
    "    estimator = CoxPHSurvivalAnalysis()\n",
    "    estimator.fit(data_x_numeric, data_y)\n",
    "    plt.title(\"K-sample log-rank P-val: \"+str(f'{pval:.2e}'))\n",
    "\n",
    "    print(pd.Series(estimator.coef_, index=data_x_numeric.columns))\n",
    "    return chisq,pval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "90186a84",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FGA_status=Silent   -0.009801\n",
      "dtype: float64\n",
      "0.001191602292239555 0.9724628188033086\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "chisq,pval = Survival_kmCurve(df_merged_HPVneg[df_merged_HPVneg['primary_site']=='Oral Cavity'],'FGA_status',)\n",
    "print(chisq,pval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7d9263f1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "primary_site=Larynx        -0.470099\n",
      "primary_site=Oral Cavity   -0.367958\n",
      "primary_site=Oropharynx    -0.074700\n",
      "dtype: float64\n",
      "1.814748554645367 0.6117307563218148\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "chisq,pval = Survival_kmCurve(df_merged_HPVneg,'primary_site')\n",
    "print(chisq,pval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "926d7c8d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hpv_status=Positive   -2.040584\n",
      "dtype: float64\n",
      "15.754687360300702 7.210904804581319e-05\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "chisq,pval = Survival_kmCurve(df_merged_nonrelative[df_merged_nonrelative['primary_site']=='Oropharynx'],'hpv_status')\n",
    "print(chisq,pval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8e11b075",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b16f2be2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "1c5f5f6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_x = df_merged_HPVneg[df_merged_HPVneg['primary_site']=='Oral Cavity'].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "c6b693a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_y = df_merged_HPVneg[df_merged_HPVneg['primary_site']=='Oral Cavity'].dropna().loc[:,df_tcga_survival.columns[1:]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "b5ddd3b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_y.loc[:,'Overall Survival Status'] = data_y['Overall Survival Status'].map({'DECEASED':True,'LIVING':False})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "4c3c6205",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_y['Overall Survival (Days)'] = data_y['Overall Survival (Months)']*30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "3d9714c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fbae7844640>"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ugtgyUuV6FQvf28QDWgVPRLJAwjcKM+tjZvfHbT9rZsdA1ZiK44BLzez4KA83sxFm9paZrTKzSbUcP8DM/tfMlgbThGTEaLbO7WPz0eutQkSyQX1VT88Cv4zbznf3UgAzOwH4C9ADmGFmZ4Z5cDCZ4J+BkUAf4Gwzqz4Z+w+BFe7eHxgC/NbMWod5TiocnJdLca+DUh2GiEhS1JcohgNT4ra3xv0+F5jq7hOJ/SH+s5DPPh5Y5e7vuvsuYDYwpto5TmxwnwHtgU1A/ctOiYhI0iRMFO6+3N3/I27XKjM7y8y6At8CHgvO+wRoE/LZ3YAP4rbLgn3x/gQcDawDlgOXxc8xVcnMJprZYjNbrDlnRESSK2yvp58APwA+BF5z95cBgobt9iHvVdt4i+rz354GlACHAoXAn8ysQ42L3Ke5e5G7F3Xp0iVkGE2nskFbRCSThUoU7v6Ru58KtHH30+MODSU2BXkYZUD3uO18Ym8O8SYAf/OYVcB7wNdCPiclxhTGXo7UoC0imS7SCnfVq3/c/amgrSKMRUBvM+sVNFCPA+ZUO2ctMAzAzA4GjgLejRJzcxtf3EMN2iKSFVI2k5277zazS4F/AjnAPe5eamYXBcenAr8m1qNqObGqqp+5+4ZUxSwi0hKldMpTd38CeKLavqlxv9cR63mVWda8BIvvBb6mgXcikvEiVT1JAv3Oin0vf1jtFCKSFcIuXFRBzZ5JEKsWcnev0SOpxSmaAMsfBmLtFEoSIpLpws71lNdUgYiISHqKXPVkZh3N7HgzO7nyk8zAsonGU4hIJouUKMzsQuAFYj2WJgff1yQvrCzw0XK4dxSXH/QyoHYKEclcUd8oLiM2c+wadx8KHAto7oxK/c6Cr/aDj5ZTvO1fFPc6SG8VIpKxoiaKHcHaFJhZG3d/k9hgOIFYg/aEx2PJgr2jtH/x6HLG3rlACUNEMkrUcRRlZnYg8HfgaTP7lJrTb0igcgzFYyUfsqJ86z77RETSXdQpPM50983ufg1wNTCd2GyyUofxxT148AeD6XNIB1VDiUhGidqY/RMzywdw9+fdfU6wpoTUQ4PwRCTTRG2j6AD808xeNLMfBhP2SQNUThaotwoRyRRRq54mu/sxxJYqPRR43syeSWpk2aJq3qe94hu3lSxEJN01dq6nT4CPgI1A18aHk2Xi5n2KN764B785M9YjSslCRNJd1DaKi83sOeBZoDPwfXcvSGZgWaFoAhx2Yq2H4pOF2itEJJ1F7R57GPBjdy9JYiwtjiYNFJFMELWNYpKSRPKoYVtE0lmoRGFmLwXfFWa2Ne5TYWZbmybE7KaGbRFJd6EShbufGHznuXuHuE+e1qJIoJaeT5XUViEi6a4xA+66JTuYrFRHz6d4GlshIumsMQPuntKAuwZI0PMpniYOFJF0FanXk7tPBiabWQEwltiAuzJ3PyWp0bUgmjhQRNKVBtylkfiJA0VE0oUG3KUptVeISLoIXfVkZgYUoQF34QRLozbEbTt38F7r7Sx7+VQo/nUTByYikljoNwp3d+BYJYkQKpdGbaCD83Lpl7OWY7c8o4ZtEUm5qFN4LDCz49x9UVKjyVZFE2KfELbdNox223ay8L1NLHxvU9UYizGF3dTILSLNKmqiGApcZGbvA9sBI/ayoXaKJDk4L5eD83L5zbB+VUlCvaFEJBWiJoqRSY1C6jS+uEdVYhh754IURyMiLVHURHFeHfuvjRqINMyK8q2MvXOBqqBEpNlETRTb437nAmcAKxsfjiRSOXpbVVAi0pyiTjP+27jPFGAIEHruJzMbYWZvmdkqM5tUxzlDzKzEzErN7Pko8WaL+AF5lW8W6hElIk0t6htFde2Aw8NcYGY5wJ+BU4EyYJGZzXH3FXHnHAjcDoxw97Vm1rJGf9cx9uK2nTvY0Honn5Xvod3GHFhxQP336ndW6J5XIiIQMVGY2XLAg80coAvh2yeOB1a5+7vBPWcDY4AVceeMB/7m7msB3P2TKPFmpMpZZ2tR2SOqtHwLn+3aQ2n5Fjq3b8PBebm1X/DR8ti3EoWIRBD1jeKMuN+7gY/dfXfIe3QDPojbLgOKq51zJNAqmC4kD/iDu8+sfiMzmwhMBOjRI0vq7Rsw9mLpwrVVkwj2adOBBycMrv3EBo4IFxGpTdRJAY8HNrn7GmAC8JCZDQh5D6tln1fb3h8YCIwCTgOuNrMja1zkPs3di9y9qEuXLiHDyFxqsxCR5hA1UVzt7hVmdiKxP8DvA+4IeY8yoHvcdj6wrpZznnT37e6+AXgB6B8x5qw1prBbVbLQKnkikmxRE8We4HsUcIe7Pwa0DnmPRUBvM+tlZq2BccCcauc8BpxkZvubWTtiVVPqhluN3ixEpClFbaP40MzuBE4BbjSzNoRff3u3mV0K/JNYg/g97l5qZhcFx6e6+0ozexJYBnwJ3O3ub0SMOetpnIWINAWLTQYb8qLY3+5HAMvd/R0zOwTo5+5PJTvAsIqKinzx4sWpDiOlxt65INbAHSyA9KuNVwBwbaeb9zlPo7tFpJKZLXH3otqORV0K9TPgb3Hb5UB5tPAk2SrfLBLRW4eINFSyBtxJGomfSBCAe2MD8uK7z2qCQRFpqMaumS0iIlkuVKIws78E35c1TTgiIpJuwlY9DTSzw4D/b2YzqTZozt03JS0yaXKVXWlBDdsiUrewiWIq8CSxCQCXsG+icEJODCjNqNoEg5UTC7IRPtsVYnJBEUm+NJ+0M1SicPfbgNvM7A53v7iJYpJkq2WCwcqJBYF9JhdMJOHEgyISTQZM2hm1e+zFZtYfOCnY9YK7L0teWJJU9UwwWDm5YCL1TjwoItFkwKSdUacZ/09is7VWjqWYZWbT3P2PSYtMmk2N7rS1UHdakZYr6jiKC4Fid98OYGY3AgsAJQoRkSwTNVEYeycGJPhd27ThkkXie0k1hHpSiWSHqIniXmChmT0abH8LmJ6UiCQtNWRakHiaIkQke0RtzP5dsOrcicTeJCa4++vJDEzSS0PaMeKpTUMke0Se68ndXwNeS2IskmVqq6pSdZRI5tGkgNIkaquqUnWUSGZSopAmUVtVlaqjRDJTpNljzexSM+uY7GBERCT9RJ1m/KvAIjN7yMxGmJm6xoqIZKlIicLdfwn0JtYl9nzgHTP7jZkdkcTYJAtVNnA/sHBtqkMRkQaKvHCRxxbb/ij47AY6Ag+b2U1Jik2yzJjCbvQ5pAMryrfWO7eUiKSPqG0U/2lmS4CbgPlAv2A22YHA/0tifJJFxhf34MEfDKbPIR1SHYqIhBC111Nn4NvuviZ+p7t/aWZnND4sERFJF1ETRZvqScLMbnT3n7n7yiTEJVku7LxR9dFAPpGmE7WN4tRa9o1sTCDSclS2VSSL2jxEmlaoNwozuxi4BDjczOIXKsoj1lYhUq+w80bVRwP5RJpW2KqnB4B/ANcDk+L2V7j7pqRFJSIiaSPsmtlbgC3A2U0TjoiIpJuwVU8vufuJZlYBePwhYkMr1O9RRCTLhH2jODH4zmuacEREJN1EHpktIiItQ9iqp8oqp9omAVTVk6RMssdlNBWN95BMFOqNwt3z3L1D8F39EzpJBDPPvmVmq8xsUoLzjjOzPWZ2VthnSPZL9riMpqLxHpKpktWYDUCYZGFmOcCfiQ3eKyM2bfkcd19Ry3k3Av8ME6u0HMkel9FUMuGNR6Q2qWzMPh5Y5e7vApjZbGAMsKLaeT8CHgGOS8IzRUQkpFQ2ZncDPojbLgv2VTGzbsCZwNRENzKziWa22MwWr1+/PumBioi0ZFGnGc81s8vN7G9m9oiZ/cTMcsPeppZ91auzbgV+5u57Et3I3ae5e5G7F3Xp0iVkGCIikkjU2WNnAhXAH4Pts4G/AN8JcY8yoHvcdj6wrto5RcDsYKXVzsDpZrbb3f8eIWYREYkgaqI4yt37x23PM7OlIe+xCOhtZr2AD4FxwPj4E9y9V+VvM5sBzFWSEBFpXlHbKF43s0GVG2ZWTMjZY919N3Apsd5MK4GH3L3UzC4ys4sixiUiIkkWtnvscmLtCK2Ac81sbXCoBzV7K9XL3Z8Anqi2r9aGa3c/P+z9RUSk8cJWPWmZUxGRFibsOIqq5U/NrCPQG4jv7bSmxkUiIpLRIjVmm9mFwGXEeiqVAIOABcA3khaZiIikhaiN2ZcRGym9xt2HAscCGukmIpKFoiaKHe6+A8DM2rj7m8BRyQtLRETSRdRxFGVmdiDwd+BpM/uUmoPlREQkC0RKFO5+ZvDzGjObBxwAPJm0qEREJG1EbczOBS4BTiQ2ruIltFqeiEhWSuVcTyIikgFSOdeTiIhkgJTN9SQiIpkhpXM9iYhI+tNcTyIiklBj5nrqD5wUbL7o7mqjEBHJQlGXQr0MmAV0DT73m9mPkhmYiIikh6i9ni4Ait19O4CZ3UhsUsA/JrxKREQyTtReTwbsidveE+wTEZEsE/WN4l5goZk9Gmx/C5ielIhEstiK8q2MvXNBqsOQJBpT2I3xxT1SHUaTijrX0+/M7DliU3gYMMHdX09mYCLZZkxht1SHIEm2onwrgBJFdWZmQL67vwa8lvyQRLLT+OIeWf8HSkvTUt4OQ7dRuLsTm15cRERagKiN2a+Y2XFJjURERNJS1MbsocBFZvY+sJ1YO4W7e0GyAhMRkfQQNVGMTGoUIiKStqImio+puXDRHckKSkRE0ocWLhIRkYS0cJGIiCSkhYtERCShqG8UxdRcuGhl5cJG6v0kIpI9oiaKEUmNQkRE0lbUuZ7W1H9W/cxsBPAHIAe4291vqHb8P4CfBZvbgIu1QJKISPOK2kbRaGaWA/yZ2JiMPsDZZtan2mnvAV8PqrJ+DUxr3ihFRCRliQI4Hljl7u+6+y5gNjAm/gR3f9ndPw02XwHymzlGEZEWL2mJwsy+GvKSbsAHcdtlwb66XAD8o45nTzSzxWa2eP369SHDEBGRRJL5RhF24aLaVsTzWk80G0osUfystuPuPs3di9y9qEuXLiHDEBGRRKL2eqrB3UeFvKQM6B63nQ+sq36SmRUAdwMj3X1j9AhFRCSKSG8UZnZjQ/bVYxHQ28x6mVlrYBwwp9o9ewB/A85x97ejxCoiIo0Tterp1Fr2hZpR1t13A5cC/wRWAg+5e6mZXWRmFwWn/QroBNxuZiVmtjhivCIiElGoqiczu5jYrLFHmNmyuEN5wMthH+7uTwBPVNs3Ne73hcCFYe8rIiLJE7aN4gFiPY+uBybF7a9w901Ji0pERNJGqKond9/i7u8TazfYFIzQPge428yObYL4REQkxaK2UVzt7hVmdiJwGnAfMLWea0REJANFTRR7gu9RwB3u/hjQOjkhiYhIOomaKD40szuBscATZtamEfcSEZE0FvUP9+8S69Z6mrtvBg4CrkhWUCIikj6ijsz+HPgKsbWyrwVaAZuTFJOISMZYUb6VsXcuiHz9rzZuAeDaRtyjUp9DO/Df3zym0fepLmqiuB34EvgGsURRATwCHJekuERE0t6YwkTzmGaPyEuhuvsAM3sdwN0/DabhEBFpMcYX92B8cY/G3eTeAwB4cMLgJETUNKK2UXwRLDzkAGbWhdgbhoiIZJmoieI24FGgq5lNAV4CfpO0qEREJG1EXTN7lpktAYYRW1fiW+6+MqmRiYhIWoi8HoW7vwm8mcRYREQkDWmQnIiIJKREISIiCSlRiIhIQkoUIiKSkBKFiIgkpEQhIiIJKVGIiEhCShQiIpKQEoWIiCSkRCEiIgkpUYiISEJKFCIikpAShYiIJKREISIiCSlRiIhIQkoUIiKSkBKFiIgkpEQhIiIJpTRRmNkIM3vLzFaZ2aRajpuZ3RYcX2ZmA1IRp4hIS5ayRGFmOcCfgZFAH+BsM+tT7bSRQO/gMxG4o1mDFBGRlL5RHA+scvd33X0XMBsYU+2cMcBMj3kFONDMDmnuQEVEWrJUJopuwAdx22XBvrDnYGYTzWyxmS1ev3590gMVEWkyX+0X+6Sx/VP4bKtln0c4B3efBkwDKCoqqnFcRCRtjbwh1RHUK5VvFGVA97jtfGBdhHNERKQJpTJRLAJ6m1kvM2sNjAPmVDtnDnBu0PtpELDF3cubO1ARkZYsZVVP7r7bzC4F/gnkAPe4e6mZXRQcnwo8AZwOrAI+AyakKl4RkZYqlW0UuPsTxJJB/L6pcb8d+GFzxyUiIntpZLaIiCSkRCEiIgkpUYiISEJKFCIikpDF2ouzh5mtB9ZEvLwzsCGJ4aSjbC+jypf5sr2M6Vq+w9y9S20Hsi5RNIaZLXb3olTH0ZSyvYwqX+bL9jJmYvlU9SQiIgkpUYiISEJKFPualuoAmkG2l1Hly3zZXsaMK5/aKEREJCG9UYiISEJKFCIikpASBWBmI8zsLTNbZWaTUh1PGGZ2j5l9YmZvxO07yMyeNrN3gu+Occd+HpTzLTM7LW7/QDNbHhy7zcxqWzSq2ZlZdzObZ2YrzazUzC4L9mdFGc0s18xeNbOlQfkmB/uzonzxzCzHzF43s7nBdtaU0czeD+IqMbPFwb6sKR/u3qI/xKY4Xw0cDrQGlgJ9Uh1XiPhPBgYAb8TtuwmYFPyeBNwY/O4TlK8N0Csod05w7FVgMLFVBf8BjEx12YK4DgEGBL/zgLeDcmRFGYNY2ge/WwELgUHZUr5qZb0ceACYm4X/nb4PdK62L2vKpzcKOB5Y5e7vuvsuYDYwJsUxNZi7vwBsqrZ7DHBf8Ps+4Ftx+2e7+053f4/YOh/Hm9khQAd3X+Cx/1pnxl2TUu5e7u6vBb8rgJXE1k3PijJ6zLZgs1XwcbKkfJXMLB8YBdwdtzuryliLrCmfEkXsD50P4rbLgn2Z7GAPVgIMvrsG++sqa7fgd/X9acXMegLHEvtbd9aUMaiSKQE+AZ5296wqX+BW4Ergy7h92VRGB54ysyVmNjHYlzXlS+nCRWmitjrAbO0zXFdZ0/6fgZm1Bx4BfuzuWxNU3WZcGd19D1BoZgcCj5pZ3wSnZ1z5zOwM4BN3X2JmQxpySS370rqMwL+7+zoz6wo8bWZvJjg348qnN4pY1u4et50PrEtRLMnycfAaS/D9SbC/rrKWBb+r708LZtaKWJKY5e5/C3ZnVRkB3H0z8Bwwguwq378Do83sfWJVu98ws/vJojK6+7rg+xPgUWJV2llTPiUKWAT0NrNeZtYaGAfMSXFMjTUHOC/4fR7wWNz+cWbWxsx6Ab2BV4PX4gozGxT0sjg37pqUCuKZDqx099/FHcqKMppZl+BNAjNrC5wCvEmWlA/A3X/u7vnu3pPY/1//cvfvkSVlNLOvmFle5W9gOPAGWVI+QL2eYm1GnE6sN81q4KpUxxMy9r8C5cAXxP5GcgHQCXgWeCf4Piju/KuCcr5FXI8KoIjYf9yrgT8RjNpP9Qc4kdjr9zKgJPicni1lBAqA14PyvQH8KtifFeWrpbxD2NvrKSvKSKzH5NLgU1r5Z0i2lM/dNYWHiIgkpqonERFJSIlCREQSUqIQEZGElChERCQhJQoREUlIiUJERBJSohARkYSUKERCMrMDzeySuO2Xm+g5+WY2tinuLRKGEoVIeAcCVYnC3U9ooucMI7bWiEhKKVGIhHcDcESwmtnNZrYNYtOgm9mbZna3mb1hZrPM7BQzmx+scnZ85Q3M7HsWW9muxMzuNLOc+AeY2YnA74CzgnN6NWsJReJoCg+RkIJ1Mea6e99ge5u7tw/2ryK2ZkYpsQknlxKbf2s0MMHdv2VmRxNb/ezb7v6Fmd0OvOLuM6s950ngv9z9DURSSOtRiCTXe+6+HMDMSoFn3d3NbDnQMzhnGDAQWBSsq9GWvVNQxzuK2KRxIimlRCGSXDvjfn8Zt/0le/9/M+A+d/95XTcxs07AFnf/okmiFAlBbRQi4VUAeY24/llibQ9dAczsIDM7rNo5vUiTRWtElChEQnL3jcD8oMH65gjXrwB+SWyN5WXA08Ah1U57E+gcPKOpelWJNIgas0VEJCG9UYiISEJKFCIikpAShYiIJKREISIiCSlRiIhIQkoUIiKSkBKFiIgk9H+4MayMxAJXhwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for value in data_x[\"FGA_status\"].unique():\n",
    "    mask = data_x[\"FGA_status\"] == value\n",
    "    time_cell, survival_prob_cell = kaplan_meier_estimator(data_y[\"Overall Survival Status\"][mask],\n",
    "                                                           data_y[\"Overall Survival (Days)\"][mask])\n",
    "    plt.step(time_cell, survival_prob_cell, where=\"post\",\n",
    "             label=\"%s (n = %d)\" % (value, mask.sum()))\n",
    "\n",
    "plt.ylabel(\"est. probability of survival $\\hat{S}(t)$\")\n",
    "plt.xlabel(\"time $t$\")\n",
    "plt.legend(loc=\"best\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "89c4efde",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}