{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "09073a3d",
   "metadata": {},
   "source": [
    "## 12/20 Analyze and explore Cell Profiler Output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "75ae2014",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as patches\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "import os\n",
    "import sys\n",
    "import glob\n",
    "import pandas as pd\n",
    "import xml.etree.ElementTree as et\n",
    "import datetime\n",
    "from imageio import volread as imread\n",
    "\n",
    "import tifffile\n",
    "\n",
    "# from pystackreg import StackReg --> don't run this, run this with imlab environment\n",
    "from skimage.filters import threshold_otsu\n",
    "\n",
    "import seaborn as sns\n",
    "#from pystackreg.util import to_uint16\n",
    "\n",
    "from skimage import measure\n",
    "from scipy import stats\n",
    "import umap\n",
    "#from umap.umap_ import UMAP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9848237a",
   "metadata": {},
   "outputs": [],
   "source": [
    "CP_DIR = 'cp_output'\n",
    "DATA_DIR = 'max_clean'\n",
    "# compartments: SYTO_ (soma), FilteredNuclei, Cyoplasm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "de8ec226",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>ImageNumber</th>\n",
       "      <th>ObjectNumber</th>\n",
       "      <th>FileName_max_clean</th>\n",
       "      <th>PathName_max_clean</th>\n",
       "      <th>AreaShape_Area</th>\n",
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       "      <td>F000_max_clean.tif</td>\n",
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       "      <td>F000_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>528</td>\n",
       "      <td>2220</td>\n",
       "      <td>1250</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>F000_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>271</td>\n",
       "      <td>600</td>\n",
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       "      <td>2.164931</td>\n",
       "      <td>1.055556</td>\n",
       "      <td>1.549169</td>\n",
       "      <td>2.845556</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>F000_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
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       "      <td>F224_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>940</td>\n",
       "      <td>1960</td>\n",
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       "      <td>1741</td>\n",
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       "      <td>2.187500</td>\n",
       "      <td>1.551038</td>\n",
       "      <td>1.969436</td>\n",
       "      <td>1.243827</td>\n",
       "      <td>1.347826</td>\n",
       "      <td>1.254931</td>\n",
       "      <td>1.916571</td>\n",
       "      <td>0.845065</td>\n",
       "      <td>1.281142</td>\n",
       "      <td>1.383878</td>\n",
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       "      <th>133696</th>\n",
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       "      <td>F224_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>533</td>\n",
       "      <td>1600</td>\n",
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       "    <tr>\n",
       "      <th>133697</th>\n",
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       "      <td>F224_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>670</td>\n",
       "      <td>1665</td>\n",
       "      <td>1441</td>\n",
       "      <td>1999</td>\n",
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       "      <td>1962</td>\n",
       "      <td>...</td>\n",
       "      <td>1.764463</td>\n",
       "      <td>2.256920</td>\n",
       "      <td>1.469050</td>\n",
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       "    <tr>\n",
       "      <th>133698</th>\n",
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       "      <td>261</td>\n",
       "      <td>F224_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>215</td>\n",
       "      <td>870</td>\n",
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       "      <td>2005</td>\n",
       "      <td>1841</td>\n",
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       "    <tr>\n",
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       "      <td>225</td>\n",
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       "      <td>F224_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
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       "<p>133700 rows × 3785 columns</p>\n",
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      "text/plain": [
       "        ImageNumber  ObjectNumber  FileName_max_clean  \\\n",
       "0                 1             1  F000_max_clean.tif   \n",
       "1                 1             2  F000_max_clean.tif   \n",
       "2                 1             3  F000_max_clean.tif   \n",
       "3                 1             4  F000_max_clean.tif   \n",
       "4                 1             5  F000_max_clean.tif   \n",
       "...             ...           ...                 ...   \n",
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       "133696          225           259  F224_max_clean.tif   \n",
       "133697          225           260  F224_max_clean.tif   \n",
       "133698          225           261  F224_max_clean.tif   \n",
       "133699          225           262  F224_max_clean.tif   \n",
       "\n",
       "                                       PathName_max_clean  AreaShape_Area  \\\n",
       "0       /mnt/disks/store/101222_D10_Coverslip1_Process...             300   \n",
       "1       /mnt/disks/store/101222_D10_Coverslip1_Process...             314   \n",
       "2       /mnt/disks/store/101222_D10_Coverslip1_Process...             528   \n",
       "3       /mnt/disks/store/101222_D10_Coverslip1_Process...             271   \n",
       "4       /mnt/disks/store/101222_D10_Coverslip1_Process...             696   \n",
       "...                                                   ...             ...   \n",
       "133695  /mnt/disks/store/101222_D10_Coverslip1_Process...             940   \n",
       "133696  /mnt/disks/store/101222_D10_Coverslip1_Process...             533   \n",
       "133697  /mnt/disks/store/101222_D10_Coverslip1_Process...             670   \n",
       "133698  /mnt/disks/store/101222_D10_Coverslip1_Process...             215   \n",
       "133699  /mnt/disks/store/101222_D10_Coverslip1_Process...            1086   \n",
       "\n",
       "        AreaShape_BoundingBoxArea  AreaShape_BoundingBoxMaximum_X  \\\n",
       "0                             784                            1534   \n",
       "1                             728                            1744   \n",
       "2                            2220                            1250   \n",
       "3                             600                              54   \n",
       "4                            1440                            1559   \n",
       "...                           ...                             ...   \n",
       "133695                       1960                            1790   \n",
       "133696                       1600                            1619   \n",
       "133697                       1665                            1441   \n",
       "133698                        870                            1871   \n",
       "133699                       2703                            1258   \n",
       "\n",
       "        AreaShape_BoundingBoxMaximum_Y  AreaShape_BoundingBoxMinimum_X  \\\n",
       "0                                   31                            1506   \n",
       "1                                   48                            1716   \n",
       "2                                   63                            1190   \n",
       "3                                   56                              30   \n",
       "4                                   70                            1527   \n",
       "...                                ...                             ...   \n",
       "133695                            1974                            1741   \n",
       "133696                            1980                            1569   \n",
       "133697                            1999                            1396   \n",
       "133698                            2005                            1841   \n",
       "133699                            2005                            1207   \n",
       "\n",
       "        AreaShape_BoundingBoxMinimum_Y  ...  Texture_Variance_pRPS6_10_02_256  \\\n",
       "0                                    3  ...                          0.000000   \n",
       "1                                   22  ...                          0.000000   \n",
       "2                                   26  ...                          0.000000   \n",
       "3                                   31  ...                          2.576389   \n",
       "4                                   25  ...                          0.000000   \n",
       "...                                ...  ...                               ...   \n",
       "133695                            1934  ...                          2.187500   \n",
       "133696                            1948  ...                          3.134354   \n",
       "133697                            1962  ...                          1.764463   \n",
       "133698                            1976  ...                          0.000000   \n",
       "133699                            1952  ...                        605.738697   \n",
       "\n",
       "        Texture_Variance_pRPS6_10_03_256  Texture_Variance_pRPS6_3_00_256  \\\n",
       "0                               0.000000                         0.000000   \n",
       "1                               0.000000                         0.000000   \n",
       "2                               0.000000                         0.000000   \n",
       "3                               2.805556                         1.867769   \n",
       "4                               0.000000                         0.109375   \n",
       "...                                  ...                              ...   \n",
       "133695                          1.551038                         1.969436   \n",
       "133696                          4.380165                         8.739692   \n",
       "133697                          2.256920                         1.469050   \n",
       "133698                          0.000000                         4.519375   \n",
       "133699                        540.519267                       618.618869   \n",
       "\n",
       "        Texture_Variance_pRPS6_3_01_256  Texture_Variance_pRPS6_3_02_256  \\\n",
       "0                              0.000000                         0.000000   \n",
       "1                              0.000000                         0.000000   \n",
       "2                              0.000000                         0.555556   \n",
       "3                              1.007785                         1.668639   \n",
       "4                              0.250000                         0.000000   \n",
       "...                                 ...                              ...   \n",
       "133695                         1.243827                         1.347826   \n",
       "133696                         5.266173                         7.643882   \n",
       "133697                         2.097029                         1.677123   \n",
       "133698                         3.765571                         4.742883   \n",
       "133699                       621.026603                       593.234845   \n",
       "\n",
       "        Texture_Variance_pRPS6_3_03_256  Texture_Variance_pRPS6_5_00_256  \\\n",
       "0                              0.000000                         0.000000   \n",
       "1                              0.000000                         0.000000   \n",
       "2                              0.000000                         0.000000   \n",
       "3                              1.897377                         2.164931   \n",
       "4                              0.187500                         0.187500   \n",
       "...                                 ...                              ...   \n",
       "133695                         1.254931                         1.916571   \n",
       "133696                         8.437500                         6.986226   \n",
       "133697                         2.573307                         1.520672   \n",
       "133698                         4.647598                         5.282136   \n",
       "133699                       644.965061                       670.038591   \n",
       "\n",
       "        Texture_Variance_pRPS6_5_01_256  Texture_Variance_pRPS6_5_02_256  \\\n",
       "0                              0.000000                         0.000000   \n",
       "1                              0.000000                         0.000000   \n",
       "2                              0.000000                         0.000000   \n",
       "3                              1.055556                         1.549169   \n",
       "4                              0.138889                         0.187500   \n",
       "...                                 ...                              ...   \n",
       "133695                         0.845065                         1.281142   \n",
       "133696                         3.464286                         7.586238   \n",
       "133697                         2.552411                         2.081690   \n",
       "133698                         0.000000                         4.423554   \n",
       "133699                       662.290754                       628.805697   \n",
       "\n",
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       "...                                 ...  \n",
       "133695                         1.383878  \n",
       "133696                         9.596246  \n",
       "133697                         1.991736  \n",
       "133698                         1.956314  \n",
       "133699                       704.896454  \n",
       "\n",
       "[133700 rows x 3785 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cp_df = pd.read_csv(f'{CP_DIR}/AllFeat_Cytoplasm.csv', sep=',')\n",
    "cp_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "15a3b812",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1030\n",
      "NAN columns 1030\n"
     ]
    }
   ],
   "source": [
    "df_in = cp_df\n",
    "nan_cols = [i for i in df_in.columns if df_in[i].isnull().any()]\n",
    "print(len(nan_cols))\n",
    "print(\"NAN columns\", len(nan_cols))\n",
    "df_in = df_in[df_in.columns[~df_in.columns.isin(nan_cols)]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4252abda",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AreaShape_NormalizedMoment_0_0\n",
      "AreaShape_NormalizedMoment_0_1\n",
      "AreaShape_NormalizedMoment_1_0\n",
      "Correlation_Correlation_AGP_DNA\n",
      "Correlation_Correlation_AGP_ER\n",
      "Correlation_Correlation_AGP_G3BP1\n",
      "Correlation_Correlation_AGP_GM130\n",
      "Correlation_Correlation_AGP_Golgin97\n",
      "Correlation_Correlation_AGP_LAMP1\n",
      "Correlation_Correlation_AGP_NFKB\n",
      "Correlation_Correlation_AGP_NeuN\n",
      "Correlation_Correlation_AGP_RANGAP1\n",
      "Correlation_Correlation_AGP_SYTO\n",
      "Correlation_Correlation_AGP_TDP43\n",
      "Correlation_Correlation_AGP_TOM20\n",
      "Correlation_Correlation_AGP_pRPS6\n",
      "Correlation_Correlation_DNA_ER\n",
      "Correlation_Correlation_DNA_G3BP1\n",
      "Correlation_Correlation_DNA_GM130\n",
      "Correlation_Correlation_DNA_Golgin97\n",
      "Correlation_Correlation_DNA_LAMP1\n",
      "Correlation_Correlation_DNA_NFKB\n",
      "Correlation_Correlation_DNA_NeuN\n",
      "Correlation_Correlation_DNA_RANGAP1\n",
      "Correlation_Correlation_DNA_SYTO\n",
      "Correlation_Correlation_DNA_TDP43\n",
      "Correlation_Correlation_DNA_TOM20\n",
      "Correlation_Correlation_DNA_pRPS6\n",
      "Correlation_Correlation_ER_G3BP1\n",
      "Correlation_Correlation_ER_GM130\n",
      "Correlation_Correlation_ER_Golgin97\n",
      "Correlation_Correlation_ER_LAMP1\n",
      "Correlation_Correlation_ER_NFKB\n",
      "Correlation_Correlation_ER_NeuN\n",
      "Correlation_Correlation_ER_RANGAP1\n",
      "Correlation_Correlation_ER_SYTO\n",
      "Correlation_Correlation_ER_TDP43\n",
      "Correlation_Correlation_ER_TOM20\n",
      "Correlation_Correlation_ER_pRPS6\n",
      "Correlation_Correlation_G3BP1_GM130\n",
      "Correlation_Correlation_G3BP1_Golgin97\n",
      "Correlation_Correlation_G3BP1_LAMP1\n",
      "Correlation_Correlation_G3BP1_NFKB\n",
      "Correlation_Correlation_G3BP1_NeuN\n",
      "Correlation_Correlation_G3BP1_RANGAP1\n",
      "Correlation_Correlation_G3BP1_SYTO\n",
      "Correlation_Correlation_G3BP1_TDP43\n",
      "Correlation_Correlation_G3BP1_TOM20\n",
      "Correlation_Correlation_G3BP1_pRPS6\n",
      "Correlation_Correlation_GM130_Golgin97\n",
      "Correlation_Correlation_GM130_LAMP1\n",
      "Correlation_Correlation_GM130_NFKB\n",
      "Correlation_Correlation_GM130_NeuN\n",
      "Correlation_Correlation_GM130_RANGAP1\n",
      "Correlation_Correlation_GM130_SYTO\n",
      "Correlation_Correlation_GM130_TDP43\n",
      "Correlation_Correlation_GM130_TOM20\n",
      "Correlation_Correlation_GM130_pRPS6\n",
      "Correlation_Correlation_Golgin97_LAMP1\n",
      "Correlation_Correlation_Golgin97_NFKB\n",
      "Correlation_Correlation_Golgin97_NeuN\n",
      "Correlation_Correlation_Golgin97_RANGAP1\n",
      "Correlation_Correlation_Golgin97_SYTO\n",
      "Correlation_Correlation_Golgin97_TDP43\n",
      "Correlation_Correlation_Golgin97_TOM20\n",
      "Correlation_Correlation_Golgin97_pRPS6\n",
      "Correlation_Correlation_LAMP1_NFKB\n",
      "Correlation_Correlation_LAMP1_NeuN\n",
      "Correlation_Correlation_LAMP1_RANGAP1\n",
      "Correlation_Correlation_LAMP1_SYTO\n",
      "Correlation_Correlation_LAMP1_TDP43\n",
      "Correlation_Correlation_LAMP1_TOM20\n",
      "Correlation_Correlation_LAMP1_pRPS6\n",
      "Correlation_Correlation_NFKB_NeuN\n",
      "Correlation_Correlation_NFKB_RANGAP1\n",
      "Correlation_Correlation_NFKB_SYTO\n",
      "Correlation_Correlation_NFKB_TDP43\n",
      "Correlation_Correlation_NFKB_TOM20\n",
      "Correlation_Correlation_NFKB_pRPS6\n",
      "Correlation_Correlation_NeuN_RANGAP1\n",
      "Correlation_Correlation_NeuN_SYTO\n",
      "Correlation_Correlation_NeuN_TDP43\n",
      "Correlation_Correlation_NeuN_TOM20\n",
      "Correlation_Correlation_NeuN_pRPS6\n",
      "Correlation_Correlation_RANGAP1_SYTO\n",
      "Correlation_Correlation_RANGAP1_TDP43\n",
      "Correlation_Correlation_RANGAP1_TOM20\n",
      "Correlation_Correlation_RANGAP1_pRPS6\n",
      "Correlation_Correlation_SYTO_TDP43\n",
      "Correlation_Correlation_SYTO_TOM20\n",
      "Correlation_Correlation_SYTO_pRPS6\n",
      "Correlation_Correlation_TDP43_TOM20\n",
      "Correlation_Correlation_TDP43_pRPS6\n",
      "Correlation_Correlation_TOM20_pRPS6\n",
      "Correlation_Costes_AGP_DNA\n",
      "Correlation_Costes_AGP_ER\n",
      "Correlation_Costes_AGP_G3BP1\n",
      "Correlation_Costes_AGP_GM130\n",
      "Correlation_Costes_AGP_Golgin97\n",
      "Correlation_Costes_AGP_LAMP1\n",
      "Correlation_Costes_AGP_NFKB\n",
      "Correlation_Costes_AGP_NeuN\n",
      "Correlation_Costes_AGP_RANGAP1\n",
      "Correlation_Costes_AGP_SYTO\n",
      "Correlation_Costes_AGP_TDP43\n",
      "Correlation_Costes_AGP_TOM20\n",
      "Correlation_Costes_AGP_pRPS6\n",
      "Correlation_Costes_DNA_AGP\n",
      "Correlation_Costes_ER_AGP\n",
      "Correlation_Costes_ER_DNA\n",
      "Correlation_Costes_ER_G3BP1\n",
      "Correlation_Costes_ER_GM130\n",
      "Correlation_Costes_ER_Golgin97\n",
      "Correlation_Costes_ER_LAMP1\n",
      "Correlation_Costes_ER_NFKB\n",
      "Correlation_Costes_ER_NeuN\n",
      "Correlation_Costes_ER_RANGAP1\n",
      "Correlation_Costes_ER_SYTO\n",
      "Correlation_Costes_ER_TDP43\n",
      "Correlation_Costes_ER_TOM20\n",
      "Correlation_Costes_ER_pRPS6\n",
      "Correlation_Costes_G3BP1_AGP\n",
      "Correlation_Costes_G3BP1_DNA\n",
      "Correlation_Costes_G3BP1_ER\n",
      "Correlation_Costes_G3BP1_GM130\n",
      "Correlation_Costes_G3BP1_Golgin97\n",
      "Correlation_Costes_G3BP1_LAMP1\n",
      "Correlation_Costes_G3BP1_NFKB\n",
      "Correlation_Costes_G3BP1_NeuN\n",
      "Correlation_Costes_G3BP1_RANGAP1\n",
      "Correlation_Costes_G3BP1_SYTO\n",
      "Correlation_Costes_G3BP1_TDP43\n",
      "Correlation_Costes_G3BP1_TOM20\n",
      "Correlation_Costes_G3BP1_pRPS6\n",
      "Correlation_Costes_GM130_AGP\n",
      "Correlation_Costes_GM130_DNA\n",
      "Correlation_Costes_GM130_ER\n",
      "Correlation_Costes_GM130_G3BP1\n",
      "Correlation_Costes_GM130_Golgin97\n",
      "Correlation_Costes_GM130_LAMP1\n",
      "Correlation_Costes_GM130_NFKB\n",
      "Correlation_Costes_GM130_NeuN\n",
      "Correlation_Costes_GM130_RANGAP1\n",
      "Correlation_Costes_GM130_SYTO\n",
      "Correlation_Costes_GM130_TDP43\n",
      "Correlation_Costes_GM130_TOM20\n",
      "Correlation_Costes_GM130_pRPS6\n",
      "Correlation_Costes_Golgin97_AGP\n",
      "Correlation_Costes_Golgin97_DNA\n",
      "Correlation_Costes_Golgin97_ER\n",
      "Correlation_Costes_Golgin97_G3BP1\n",
      "Correlation_Costes_Golgin97_GM130\n",
      "Correlation_Costes_Golgin97_LAMP1\n",
      "Correlation_Costes_Golgin97_NFKB\n",
      "Correlation_Costes_Golgin97_NeuN\n",
      "Correlation_Costes_Golgin97_RANGAP1\n",
      "Correlation_Costes_Golgin97_SYTO\n",
      "Correlation_Costes_Golgin97_TDP43\n",
      "Correlation_Costes_Golgin97_TOM20\n",
      "Correlation_Costes_Golgin97_pRPS6\n",
      "Correlation_Costes_LAMP1_AGP\n",
      "Correlation_Costes_LAMP1_DNA\n",
      "Correlation_Costes_LAMP1_ER\n",
      "Correlation_Costes_LAMP1_G3BP1\n",
      "Correlation_Costes_LAMP1_GM130\n",
      "Correlation_Costes_LAMP1_Golgin97\n",
      "Correlation_Costes_LAMP1_NFKB\n",
      "Correlation_Costes_LAMP1_NeuN\n",
      "Correlation_Costes_LAMP1_RANGAP1\n",
      "Correlation_Costes_LAMP1_SYTO\n",
      "Correlation_Costes_LAMP1_TDP43\n",
      "Correlation_Costes_LAMP1_TOM20\n",
      "Correlation_Costes_LAMP1_pRPS6\n",
      "Correlation_Costes_NFKB_AGP\n",
      "Correlation_Costes_NFKB_DNA\n",
      "Correlation_Costes_NFKB_ER\n",
      "Correlation_Costes_NFKB_G3BP1\n",
      "Correlation_Costes_NFKB_GM130\n",
      "Correlation_Costes_NFKB_Golgin97\n",
      "Correlation_Costes_NFKB_LAMP1\n",
      "Correlation_Costes_NFKB_NeuN\n",
      "Correlation_Costes_NFKB_RANGAP1\n",
      "Correlation_Costes_NFKB_SYTO\n",
      "Correlation_Costes_NFKB_TDP43\n",
      "Correlation_Costes_NFKB_TOM20\n",
      "Correlation_Costes_NFKB_pRPS6\n",
      "Correlation_Costes_NeuN_AGP\n",
      "Correlation_Costes_NeuN_DNA\n",
      "Correlation_Costes_NeuN_ER\n",
      "Correlation_Costes_NeuN_G3BP1\n",
      "Correlation_Costes_NeuN_GM130\n",
      "Correlation_Costes_NeuN_Golgin97\n",
      "Correlation_Costes_NeuN_LAMP1\n",
      "Correlation_Costes_NeuN_NFKB\n",
      "Correlation_Costes_NeuN_RANGAP1\n",
      "Correlation_Costes_NeuN_SYTO\n",
      "Correlation_Costes_NeuN_TDP43\n",
      "Correlation_Costes_NeuN_TOM20\n",
      "Correlation_Costes_NeuN_pRPS6\n",
      "Correlation_Costes_RANGAP1_AGP\n",
      "Correlation_Costes_RANGAP1_DNA\n",
      "Correlation_Costes_RANGAP1_ER\n",
      "Correlation_Costes_RANGAP1_G3BP1\n",
      "Correlation_Costes_RANGAP1_GM130\n",
      "Correlation_Costes_RANGAP1_Golgin97\n",
      "Correlation_Costes_RANGAP1_LAMP1\n",
      "Correlation_Costes_RANGAP1_NFKB\n",
      "Correlation_Costes_RANGAP1_NeuN\n",
      "Correlation_Costes_RANGAP1_SYTO\n",
      "Correlation_Costes_RANGAP1_TDP43\n",
      "Correlation_Costes_RANGAP1_TOM20\n",
      "Correlation_Costes_RANGAP1_pRPS6\n",
      "Correlation_Costes_SYTO_AGP\n",
      "Correlation_Costes_SYTO_DNA\n",
      "Correlation_Costes_SYTO_ER\n",
      "Correlation_Costes_SYTO_G3BP1\n",
      "Correlation_Costes_SYTO_GM130\n",
      "Correlation_Costes_SYTO_Golgin97\n",
      "Correlation_Costes_SYTO_LAMP1\n",
      "Correlation_Costes_SYTO_NFKB\n",
      "Correlation_Costes_SYTO_NeuN\n",
      "Correlation_Costes_SYTO_RANGAP1\n",
      "Correlation_Costes_SYTO_TDP43\n",
      "Correlation_Costes_SYTO_TOM20\n",
      "Correlation_Costes_SYTO_pRPS6\n",
      "Correlation_Costes_TDP43_AGP\n",
      "Correlation_Costes_TDP43_DNA\n",
      "Correlation_Costes_TDP43_ER\n",
      "Correlation_Costes_TDP43_G3BP1\n",
      "Correlation_Costes_TDP43_GM130\n",
      "Correlation_Costes_TDP43_Golgin97\n",
      "Correlation_Costes_TDP43_LAMP1\n",
      "Correlation_Costes_TDP43_NFKB\n",
      "Correlation_Costes_TDP43_NeuN\n",
      "Correlation_Costes_TDP43_RANGAP1\n",
      "Correlation_Costes_TDP43_SYTO\n",
      "Correlation_Costes_TDP43_TOM20\n",
      "Correlation_Costes_TDP43_pRPS6\n",
      "Correlation_Costes_TOM20_AGP\n",
      "Correlation_Costes_TOM20_DNA\n",
      "Correlation_Costes_TOM20_ER\n",
      "Correlation_Costes_TOM20_G3BP1\n",
      "Correlation_Costes_TOM20_GM130\n",
      "Correlation_Costes_TOM20_Golgin97\n",
      "Correlation_Costes_TOM20_LAMP1\n",
      "Correlation_Costes_TOM20_NFKB\n",
      "Correlation_Costes_TOM20_NeuN\n",
      "Correlation_Costes_TOM20_RANGAP1\n",
      "Correlation_Costes_TOM20_SYTO\n",
      "Correlation_Costes_TOM20_TDP43\n",
      "Correlation_Costes_TOM20_pRPS6\n",
      "Correlation_Costes_pRPS6_AGP\n",
      "Correlation_Costes_pRPS6_DNA\n",
      "Correlation_Costes_pRPS6_ER\n",
      "Correlation_Costes_pRPS6_G3BP1\n",
      "Correlation_Costes_pRPS6_GM130\n",
      "Correlation_Costes_pRPS6_Golgin97\n",
      "Correlation_Costes_pRPS6_LAMP1\n",
      "Correlation_Costes_pRPS6_NFKB\n",
      "Correlation_Costes_pRPS6_NeuN\n",
      "Correlation_Costes_pRPS6_RANGAP1\n",
      "Correlation_Costes_pRPS6_SYTO\n",
      "Correlation_Costes_pRPS6_TDP43\n",
      "Correlation_Costes_pRPS6_TOM20\n",
      "Correlation_K_AGP_DNA\n",
      "Correlation_K_AGP_ER\n",
      "Correlation_K_AGP_G3BP1\n",
      "Correlation_K_AGP_GM130\n",
      "Correlation_K_AGP_Golgin97\n",
      "Correlation_K_AGP_LAMP1\n",
      "Correlation_K_AGP_NFKB\n",
      "Correlation_K_AGP_NeuN\n",
      "Correlation_K_AGP_RANGAP1\n",
      "Correlation_K_AGP_SYTO\n",
      "Correlation_K_AGP_TDP43\n",
      "Correlation_K_AGP_TOM20\n",
      "Correlation_K_AGP_pRPS6\n",
      "Correlation_K_DNA_AGP\n",
      "Correlation_K_DNA_ER\n",
      "Correlation_K_DNA_G3BP1\n",
      "Correlation_K_DNA_GM130\n",
      "Correlation_K_DNA_Golgin97\n",
      "Correlation_K_DNA_LAMP1\n",
      "Correlation_K_DNA_NFKB\n",
      "Correlation_K_DNA_NeuN\n",
      "Correlation_K_DNA_RANGAP1\n",
      "Correlation_K_DNA_TDP43\n",
      "Correlation_K_DNA_TOM20\n",
      "Correlation_K_DNA_pRPS6\n",
      "Correlation_K_ER_AGP\n",
      "Correlation_K_ER_DNA\n",
      "Correlation_K_ER_G3BP1\n",
      "Correlation_K_ER_GM130\n",
      "Correlation_K_ER_Golgin97\n",
      "Correlation_K_ER_LAMP1\n",
      "Correlation_K_ER_NFKB\n",
      "Correlation_K_ER_NeuN\n",
      "Correlation_K_ER_RANGAP1\n",
      "Correlation_K_ER_SYTO\n",
      "Correlation_K_ER_TDP43\n",
      "Correlation_K_ER_TOM20\n",
      "Correlation_K_ER_pRPS6\n",
      "Correlation_K_G3BP1_AGP\n",
      "Correlation_K_G3BP1_DNA\n",
      "Correlation_K_G3BP1_ER\n",
      "Correlation_K_G3BP1_GM130\n",
      "Correlation_K_G3BP1_Golgin97\n",
      "Correlation_K_G3BP1_LAMP1\n",
      "Correlation_K_G3BP1_NFKB\n",
      "Correlation_K_G3BP1_NeuN\n",
      "Correlation_K_G3BP1_RANGAP1\n",
      "Correlation_K_G3BP1_SYTO\n",
      "Correlation_K_G3BP1_TDP43\n",
      "Correlation_K_G3BP1_TOM20\n",
      "Correlation_K_G3BP1_pRPS6\n",
      "Correlation_K_GM130_AGP\n",
      "Correlation_K_GM130_DNA\n",
      "Correlation_K_GM130_ER\n",
      "Correlation_K_GM130_G3BP1\n",
      "Correlation_K_GM130_Golgin97\n",
      "Correlation_K_GM130_LAMP1\n",
      "Correlation_K_GM130_NFKB\n",
      "Correlation_K_GM130_NeuN\n",
      "Correlation_K_GM130_RANGAP1\n",
      "Correlation_K_GM130_SYTO\n",
      "Correlation_K_GM130_TDP43\n",
      "Correlation_K_GM130_TOM20\n",
      "Correlation_K_GM130_pRPS6\n",
      "Correlation_K_Golgin97_AGP\n",
      "Correlation_K_Golgin97_DNA\n",
      "Correlation_K_Golgin97_ER\n",
      "Correlation_K_Golgin97_G3BP1\n",
      "Correlation_K_Golgin97_GM130\n",
      "Correlation_K_Golgin97_LAMP1\n",
      "Correlation_K_Golgin97_NFKB\n",
      "Correlation_K_Golgin97_NeuN\n",
      "Correlation_K_Golgin97_RANGAP1\n",
      "Correlation_K_Golgin97_SYTO\n",
      "Correlation_K_Golgin97_TDP43\n",
      "Correlation_K_Golgin97_TOM20\n",
      "Correlation_K_Golgin97_pRPS6\n",
      "Correlation_K_LAMP1_AGP\n",
      "Correlation_K_LAMP1_DNA\n",
      "Correlation_K_LAMP1_ER\n",
      "Correlation_K_LAMP1_G3BP1\n",
      "Correlation_K_LAMP1_GM130\n",
      "Correlation_K_LAMP1_Golgin97\n",
      "Correlation_K_LAMP1_NFKB\n",
      "Correlation_K_LAMP1_NeuN\n",
      "Correlation_K_LAMP1_RANGAP1\n",
      "Correlation_K_LAMP1_SYTO\n",
      "Correlation_K_LAMP1_TDP43\n",
      "Correlation_K_LAMP1_TOM20\n",
      "Correlation_K_LAMP1_pRPS6\n",
      "Correlation_K_NFKB_AGP\n",
      "Correlation_K_NFKB_DNA\n",
      "Correlation_K_NFKB_ER\n",
      "Correlation_K_NFKB_G3BP1\n",
      "Correlation_K_NFKB_GM130\n",
      "Correlation_K_NFKB_Golgin97\n",
      "Correlation_K_NFKB_LAMP1\n",
      "Correlation_K_NFKB_NeuN\n",
      "Correlation_K_NFKB_RANGAP1\n",
      "Correlation_K_NFKB_SYTO\n",
      "Correlation_K_NFKB_TDP43\n",
      "Correlation_K_NFKB_TOM20\n",
      "Correlation_K_NFKB_pRPS6\n",
      "Correlation_K_NeuN_AGP\n",
      "Correlation_K_NeuN_DNA\n",
      "Correlation_K_NeuN_ER\n",
      "Correlation_K_NeuN_G3BP1\n",
      "Correlation_K_NeuN_GM130\n",
      "Correlation_K_NeuN_Golgin97\n",
      "Correlation_K_NeuN_LAMP1\n",
      "Correlation_K_NeuN_NFKB\n",
      "Correlation_K_NeuN_RANGAP1\n",
      "Correlation_K_NeuN_SYTO\n",
      "Correlation_K_NeuN_TDP43\n",
      "Correlation_K_NeuN_TOM20\n",
      "Correlation_K_NeuN_pRPS6\n",
      "Correlation_K_RANGAP1_AGP\n",
      "Correlation_K_RANGAP1_DNA\n",
      "Correlation_K_RANGAP1_ER\n",
      "Correlation_K_RANGAP1_G3BP1\n",
      "Correlation_K_RANGAP1_GM130\n",
      "Correlation_K_RANGAP1_Golgin97\n",
      "Correlation_K_RANGAP1_LAMP1\n",
      "Correlation_K_RANGAP1_NFKB\n",
      "Correlation_K_RANGAP1_NeuN\n",
      "Correlation_K_RANGAP1_SYTO\n",
      "Correlation_K_RANGAP1_TDP43\n",
      "Correlation_K_RANGAP1_TOM20\n",
      "Correlation_K_RANGAP1_pRPS6\n",
      "Correlation_K_SYTO_AGP\n",
      "Correlation_K_SYTO_DNA\n",
      "Correlation_K_SYTO_ER\n",
      "Correlation_K_SYTO_G3BP1\n",
      "Correlation_K_SYTO_GM130\n",
      "Correlation_K_SYTO_Golgin97\n",
      "Correlation_K_SYTO_LAMP1\n",
      "Correlation_K_SYTO_NFKB\n",
      "Correlation_K_SYTO_NeuN\n",
      "Correlation_K_SYTO_RANGAP1\n",
      "Correlation_K_SYTO_TDP43\n",
      "Correlation_K_SYTO_TOM20\n",
      "Correlation_K_SYTO_pRPS6\n",
      "Correlation_K_TDP43_AGP\n",
      "Correlation_K_TDP43_DNA\n",
      "Correlation_K_TDP43_ER\n",
      "Correlation_K_TDP43_G3BP1\n",
      "Correlation_K_TDP43_GM130\n",
      "Correlation_K_TDP43_Golgin97\n",
      "Correlation_K_TDP43_LAMP1\n",
      "Correlation_K_TDP43_NFKB\n",
      "Correlation_K_TDP43_NeuN\n",
      "Correlation_K_TDP43_RANGAP1\n",
      "Correlation_K_TDP43_SYTO\n",
      "Correlation_K_TDP43_TOM20\n",
      "Correlation_K_TDP43_pRPS6\n",
      "Correlation_K_TOM20_AGP\n",
      "Correlation_K_TOM20_DNA\n",
      "Correlation_K_TOM20_ER\n",
      "Correlation_K_TOM20_G3BP1\n",
      "Correlation_K_TOM20_GM130\n",
      "Correlation_K_TOM20_Golgin97\n",
      "Correlation_K_TOM20_LAMP1\n",
      "Correlation_K_TOM20_NFKB\n",
      "Correlation_K_TOM20_NeuN\n",
      "Correlation_K_TOM20_RANGAP1\n",
      "Correlation_K_TOM20_SYTO\n",
      "Correlation_K_TOM20_TDP43\n",
      "Correlation_K_TOM20_pRPS6\n",
      "Correlation_K_pRPS6_AGP\n",
      "Correlation_K_pRPS6_DNA\n",
      "Correlation_K_pRPS6_ER\n",
      "Correlation_K_pRPS6_G3BP1\n",
      "Correlation_K_pRPS6_GM130\n",
      "Correlation_K_pRPS6_Golgin97\n",
      "Correlation_K_pRPS6_LAMP1\n",
      "Correlation_K_pRPS6_NFKB\n",
      "Correlation_K_pRPS6_NeuN\n",
      "Correlation_K_pRPS6_RANGAP1\n",
      "Correlation_K_pRPS6_SYTO\n",
      "Correlation_K_pRPS6_TDP43\n",
      "Correlation_K_pRPS6_TOM20\n",
      "Correlation_Manders_AGP_DNA\n",
      "Correlation_Manders_AGP_ER\n",
      "Correlation_Manders_AGP_G3BP1\n",
      "Correlation_Manders_AGP_GM130\n",
      "Correlation_Manders_AGP_Golgin97\n",
      "Correlation_Manders_AGP_LAMP1\n",
      "Correlation_Manders_AGP_NFKB\n",
      "Correlation_Manders_AGP_NeuN\n",
      "Correlation_Manders_AGP_RANGAP1\n",
      "Correlation_Manders_AGP_SYTO\n",
      "Correlation_Manders_AGP_TDP43\n",
      "Correlation_Manders_AGP_TOM20\n",
      "Correlation_Manders_AGP_pRPS6\n",
      "Correlation_Manders_ER_AGP\n",
      "Correlation_Manders_ER_DNA\n",
      "Correlation_Manders_ER_G3BP1\n",
      "Correlation_Manders_ER_GM130\n",
      "Correlation_Manders_ER_Golgin97\n",
      "Correlation_Manders_ER_LAMP1\n",
      "Correlation_Manders_ER_NFKB\n",
      "Correlation_Manders_ER_NeuN\n",
      "Correlation_Manders_ER_RANGAP1\n",
      "Correlation_Manders_ER_SYTO\n",
      "Correlation_Manders_ER_TDP43\n",
      "Correlation_Manders_ER_TOM20\n",
      "Correlation_Manders_ER_pRPS6\n",
      "Correlation_Manders_G3BP1_AGP\n",
      "Correlation_Manders_G3BP1_DNA\n",
      "Correlation_Manders_G3BP1_ER\n",
      "Correlation_Manders_G3BP1_GM130\n",
      "Correlation_Manders_G3BP1_Golgin97\n",
      "Correlation_Manders_G3BP1_LAMP1\n",
      "Correlation_Manders_G3BP1_NFKB\n",
      "Correlation_Manders_G3BP1_NeuN\n",
      "Correlation_Manders_G3BP1_RANGAP1\n",
      "Correlation_Manders_G3BP1_SYTO\n",
      "Correlation_Manders_G3BP1_TDP43\n",
      "Correlation_Manders_G3BP1_TOM20\n",
      "Correlation_Manders_G3BP1_pRPS6\n",
      "Correlation_Manders_GM130_AGP\n",
      "Correlation_Manders_GM130_DNA\n",
      "Correlation_Manders_GM130_ER\n",
      "Correlation_Manders_GM130_G3BP1\n",
      "Correlation_Manders_GM130_Golgin97\n",
      "Correlation_Manders_GM130_LAMP1\n",
      "Correlation_Manders_GM130_NFKB\n",
      "Correlation_Manders_GM130_NeuN\n",
      "Correlation_Manders_GM130_RANGAP1\n",
      "Correlation_Manders_GM130_SYTO\n",
      "Correlation_Manders_GM130_TDP43\n",
      "Correlation_Manders_GM130_TOM20\n",
      "Correlation_Manders_GM130_pRPS6\n",
      "Correlation_Manders_Golgin97_AGP\n",
      "Correlation_Manders_Golgin97_DNA\n",
      "Correlation_Manders_Golgin97_ER\n",
      "Correlation_Manders_Golgin97_G3BP1\n",
      "Correlation_Manders_Golgin97_GM130\n",
      "Correlation_Manders_Golgin97_LAMP1\n",
      "Correlation_Manders_Golgin97_NFKB\n",
      "Correlation_Manders_Golgin97_NeuN\n",
      "Correlation_Manders_Golgin97_RANGAP1\n",
      "Correlation_Manders_Golgin97_SYTO\n",
      "Correlation_Manders_Golgin97_TDP43\n",
      "Correlation_Manders_Golgin97_TOM20\n",
      "Correlation_Manders_Golgin97_pRPS6\n",
      "Correlation_Manders_LAMP1_AGP\n",
      "Correlation_Manders_LAMP1_DNA\n",
      "Correlation_Manders_LAMP1_ER\n",
      "Correlation_Manders_LAMP1_G3BP1\n",
      "Correlation_Manders_LAMP1_GM130\n",
      "Correlation_Manders_LAMP1_Golgin97\n",
      "Correlation_Manders_LAMP1_NFKB\n",
      "Correlation_Manders_LAMP1_NeuN\n",
      "Correlation_Manders_LAMP1_RANGAP1\n",
      "Correlation_Manders_LAMP1_SYTO\n",
      "Correlation_Manders_LAMP1_TDP43\n",
      "Correlation_Manders_LAMP1_TOM20\n",
      "Correlation_Manders_LAMP1_pRPS6\n",
      "Correlation_Manders_NFKB_AGP\n",
      "Correlation_Manders_NFKB_DNA\n",
      "Correlation_Manders_NFKB_ER\n",
      "Correlation_Manders_NFKB_G3BP1\n",
      "Correlation_Manders_NFKB_GM130\n",
      "Correlation_Manders_NFKB_Golgin97\n",
      "Correlation_Manders_NFKB_LAMP1\n",
      "Correlation_Manders_NFKB_NeuN\n",
      "Correlation_Manders_NFKB_RANGAP1\n",
      "Correlation_Manders_NFKB_SYTO\n",
      "Correlation_Manders_NFKB_TDP43\n",
      "Correlation_Manders_NFKB_TOM20\n",
      "Correlation_Manders_NFKB_pRPS6\n",
      "Correlation_Manders_NeuN_AGP\n",
      "Correlation_Manders_NeuN_DNA\n",
      "Correlation_Manders_NeuN_ER\n",
      "Correlation_Manders_NeuN_G3BP1\n",
      "Correlation_Manders_NeuN_GM130\n",
      "Correlation_Manders_NeuN_Golgin97\n",
      "Correlation_Manders_NeuN_LAMP1\n",
      "Correlation_Manders_NeuN_NFKB\n",
      "Correlation_Manders_NeuN_RANGAP1\n",
      "Correlation_Manders_NeuN_SYTO\n",
      "Correlation_Manders_NeuN_TDP43\n",
      "Correlation_Manders_NeuN_TOM20\n",
      "Correlation_Manders_NeuN_pRPS6\n",
      "Correlation_Manders_RANGAP1_AGP\n",
      "Correlation_Manders_RANGAP1_DNA\n",
      "Correlation_Manders_RANGAP1_ER\n",
      "Correlation_Manders_RANGAP1_G3BP1\n",
      "Correlation_Manders_RANGAP1_GM130\n",
      "Correlation_Manders_RANGAP1_Golgin97\n",
      "Correlation_Manders_RANGAP1_LAMP1\n",
      "Correlation_Manders_RANGAP1_NFKB\n",
      "Correlation_Manders_RANGAP1_NeuN\n",
      "Correlation_Manders_RANGAP1_SYTO\n",
      "Correlation_Manders_RANGAP1_TDP43\n",
      "Correlation_Manders_RANGAP1_TOM20\n",
      "Correlation_Manders_RANGAP1_pRPS6\n",
      "Correlation_Manders_SYTO_AGP\n",
      "Correlation_Manders_SYTO_DNA\n",
      "Correlation_Manders_SYTO_ER\n",
      "Correlation_Manders_SYTO_G3BP1\n",
      "Correlation_Manders_SYTO_GM130\n",
      "Correlation_Manders_SYTO_Golgin97\n",
      "Correlation_Manders_SYTO_LAMP1\n",
      "Correlation_Manders_SYTO_NFKB\n",
      "Correlation_Manders_SYTO_NeuN\n",
      "Correlation_Manders_SYTO_RANGAP1\n",
      "Correlation_Manders_SYTO_TDP43\n",
      "Correlation_Manders_SYTO_TOM20\n",
      "Correlation_Manders_SYTO_pRPS6\n",
      "Correlation_Manders_TDP43_AGP\n",
      "Correlation_Manders_TDP43_DNA\n",
      "Correlation_Manders_TDP43_ER\n",
      "Correlation_Manders_TDP43_G3BP1\n",
      "Correlation_Manders_TDP43_GM130\n",
      "Correlation_Manders_TDP43_Golgin97\n",
      "Correlation_Manders_TDP43_LAMP1\n",
      "Correlation_Manders_TDP43_NFKB\n",
      "Correlation_Manders_TDP43_NeuN\n",
      "Correlation_Manders_TDP43_RANGAP1\n",
      "Correlation_Manders_TDP43_SYTO\n",
      "Correlation_Manders_TDP43_TOM20\n",
      "Correlation_Manders_TDP43_pRPS6\n",
      "Correlation_Manders_TOM20_AGP\n",
      "Correlation_Manders_TOM20_DNA\n",
      "Correlation_Manders_TOM20_ER\n",
      "Correlation_Manders_TOM20_G3BP1\n",
      "Correlation_Manders_TOM20_GM130\n",
      "Correlation_Manders_TOM20_Golgin97\n",
      "Correlation_Manders_TOM20_LAMP1\n",
      "Correlation_Manders_TOM20_NFKB\n",
      "Correlation_Manders_TOM20_NeuN\n",
      "Correlation_Manders_TOM20_RANGAP1\n",
      "Correlation_Manders_TOM20_SYTO\n",
      "Correlation_Manders_TOM20_TDP43\n",
      "Correlation_Manders_TOM20_pRPS6\n",
      "Correlation_Manders_pRPS6_AGP\n",
      "Correlation_Manders_pRPS6_DNA\n",
      "Correlation_Manders_pRPS6_ER\n",
      "Correlation_Manders_pRPS6_G3BP1\n",
      "Correlation_Manders_pRPS6_GM130\n",
      "Correlation_Manders_pRPS6_Golgin97\n",
      "Correlation_Manders_pRPS6_LAMP1\n",
      "Correlation_Manders_pRPS6_NFKB\n",
      "Correlation_Manders_pRPS6_NeuN\n",
      "Correlation_Manders_pRPS6_RANGAP1\n",
      "Correlation_Manders_pRPS6_SYTO\n",
      "Correlation_Manders_pRPS6_TDP43\n",
      "Correlation_Manders_pRPS6_TOM20\n",
      "Correlation_Overlap_AGP_DNA\n",
      "Correlation_Overlap_AGP_ER\n",
      "Correlation_Overlap_AGP_G3BP1\n",
      "Correlation_Overlap_AGP_GM130\n",
      "Correlation_Overlap_AGP_Golgin97\n",
      "Correlation_Overlap_AGP_LAMP1\n",
      "Correlation_Overlap_AGP_NFKB\n",
      "Correlation_Overlap_AGP_NeuN\n",
      "Correlation_Overlap_AGP_RANGAP1\n",
      "Correlation_Overlap_AGP_SYTO\n",
      "Correlation_Overlap_AGP_TDP43\n",
      "Correlation_Overlap_AGP_TOM20\n",
      "Correlation_Overlap_AGP_pRPS6\n",
      "Correlation_Overlap_DNA_ER\n",
      "Correlation_Overlap_DNA_G3BP1\n",
      "Correlation_Overlap_DNA_GM130\n",
      "Correlation_Overlap_DNA_Golgin97\n",
      "Correlation_Overlap_DNA_LAMP1\n",
      "Correlation_Overlap_DNA_NFKB\n",
      "Correlation_Overlap_DNA_NeuN\n",
      "Correlation_Overlap_DNA_RANGAP1\n",
      "Correlation_Overlap_DNA_SYTO\n",
      "Correlation_Overlap_DNA_TDP43\n",
      "Correlation_Overlap_DNA_TOM20\n",
      "Correlation_Overlap_DNA_pRPS6\n",
      "Correlation_Overlap_ER_G3BP1\n",
      "Correlation_Overlap_ER_GM130\n",
      "Correlation_Overlap_ER_Golgin97\n",
      "Correlation_Overlap_ER_LAMP1\n",
      "Correlation_Overlap_ER_NFKB\n",
      "Correlation_Overlap_ER_NeuN\n",
      "Correlation_Overlap_ER_RANGAP1\n",
      "Correlation_Overlap_ER_SYTO\n",
      "Correlation_Overlap_ER_TDP43\n",
      "Correlation_Overlap_ER_TOM20\n",
      "Correlation_Overlap_ER_pRPS6\n",
      "Correlation_Overlap_G3BP1_GM130\n",
      "Correlation_Overlap_G3BP1_Golgin97\n",
      "Correlation_Overlap_G3BP1_LAMP1\n",
      "Correlation_Overlap_G3BP1_NFKB\n",
      "Correlation_Overlap_G3BP1_NeuN\n",
      "Correlation_Overlap_G3BP1_RANGAP1\n",
      "Correlation_Overlap_G3BP1_SYTO\n",
      "Correlation_Overlap_G3BP1_TDP43\n",
      "Correlation_Overlap_G3BP1_TOM20\n",
      "Correlation_Overlap_G3BP1_pRPS6\n",
      "Correlation_Overlap_GM130_Golgin97\n",
      "Correlation_Overlap_GM130_LAMP1\n",
      "Correlation_Overlap_GM130_NFKB\n",
      "Correlation_Overlap_GM130_NeuN\n",
      "Correlation_Overlap_GM130_RANGAP1\n",
      "Correlation_Overlap_GM130_SYTO\n",
      "Correlation_Overlap_GM130_TDP43\n",
      "Correlation_Overlap_GM130_TOM20\n",
      "Correlation_Overlap_GM130_pRPS6\n",
      "Correlation_Overlap_Golgin97_LAMP1\n",
      "Correlation_Overlap_Golgin97_NFKB\n",
      "Correlation_Overlap_Golgin97_NeuN\n",
      "Correlation_Overlap_Golgin97_RANGAP1\n",
      "Correlation_Overlap_Golgin97_SYTO\n",
      "Correlation_Overlap_Golgin97_TDP43\n",
      "Correlation_Overlap_Golgin97_TOM20\n",
      "Correlation_Overlap_Golgin97_pRPS6\n",
      "Correlation_Overlap_LAMP1_NFKB\n",
      "Correlation_Overlap_LAMP1_NeuN\n",
      "Correlation_Overlap_LAMP1_RANGAP1\n",
      "Correlation_Overlap_LAMP1_SYTO\n",
      "Correlation_Overlap_LAMP1_TDP43\n",
      "Correlation_Overlap_LAMP1_TOM20\n",
      "Correlation_Overlap_LAMP1_pRPS6\n",
      "Correlation_Overlap_NFKB_NeuN\n",
      "Correlation_Overlap_NFKB_RANGAP1\n",
      "Correlation_Overlap_NFKB_SYTO\n",
      "Correlation_Overlap_NFKB_TDP43\n",
      "Correlation_Overlap_NFKB_TOM20\n",
      "Correlation_Overlap_NFKB_pRPS6\n",
      "Correlation_Overlap_NeuN_RANGAP1\n",
      "Correlation_Overlap_NeuN_SYTO\n",
      "Correlation_Overlap_NeuN_TDP43\n",
      "Correlation_Overlap_NeuN_TOM20\n",
      "Correlation_Overlap_NeuN_pRPS6\n",
      "Correlation_Overlap_RANGAP1_SYTO\n",
      "Correlation_Overlap_RANGAP1_TDP43\n",
      "Correlation_Overlap_RANGAP1_TOM20\n",
      "Correlation_Overlap_RANGAP1_pRPS6\n",
      "Correlation_Overlap_SYTO_TDP43\n",
      "Correlation_Overlap_SYTO_TOM20\n",
      "Correlation_Overlap_SYTO_pRPS6\n",
      "Correlation_Overlap_TDP43_TOM20\n",
      "Correlation_Overlap_TDP43_pRPS6\n",
      "Correlation_Overlap_TOM20_pRPS6\n",
      "Correlation_RWC_AGP_DNA\n",
      "Correlation_RWC_AGP_ER\n",
      "Correlation_RWC_AGP_G3BP1\n",
      "Correlation_RWC_AGP_GM130\n",
      "Correlation_RWC_AGP_Golgin97\n",
      "Correlation_RWC_AGP_LAMP1\n",
      "Correlation_RWC_AGP_NFKB\n",
      "Correlation_RWC_AGP_NeuN\n",
      "Correlation_RWC_AGP_RANGAP1\n",
      "Correlation_RWC_AGP_SYTO\n",
      "Correlation_RWC_AGP_TDP43\n",
      "Correlation_RWC_AGP_TOM20\n",
      "Correlation_RWC_AGP_pRPS6\n",
      "Correlation_RWC_ER_AGP\n",
      "Correlation_RWC_ER_DNA\n",
      "Correlation_RWC_ER_G3BP1\n",
      "Correlation_RWC_ER_GM130\n",
      "Correlation_RWC_ER_Golgin97\n",
      "Correlation_RWC_ER_LAMP1\n",
      "Correlation_RWC_ER_NFKB\n",
      "Correlation_RWC_ER_NeuN\n",
      "Correlation_RWC_ER_RANGAP1\n",
      "Correlation_RWC_ER_SYTO\n",
      "Correlation_RWC_ER_TDP43\n",
      "Correlation_RWC_ER_TOM20\n",
      "Correlation_RWC_ER_pRPS6\n",
      "Correlation_RWC_G3BP1_AGP\n",
      "Correlation_RWC_G3BP1_DNA\n",
      "Correlation_RWC_G3BP1_ER\n",
      "Correlation_RWC_G3BP1_GM130\n",
      "Correlation_RWC_G3BP1_Golgin97\n",
      "Correlation_RWC_G3BP1_LAMP1\n",
      "Correlation_RWC_G3BP1_NFKB\n",
      "Correlation_RWC_G3BP1_NeuN\n",
      "Correlation_RWC_G3BP1_RANGAP1\n",
      "Correlation_RWC_G3BP1_SYTO\n",
      "Correlation_RWC_G3BP1_TDP43\n",
      "Correlation_RWC_G3BP1_TOM20\n",
      "Correlation_RWC_G3BP1_pRPS6\n",
      "Correlation_RWC_GM130_AGP\n",
      "Correlation_RWC_GM130_DNA\n",
      "Correlation_RWC_GM130_ER\n",
      "Correlation_RWC_GM130_G3BP1\n",
      "Correlation_RWC_GM130_Golgin97\n",
      "Correlation_RWC_GM130_LAMP1\n",
      "Correlation_RWC_GM130_NFKB\n",
      "Correlation_RWC_GM130_NeuN\n",
      "Correlation_RWC_GM130_RANGAP1\n",
      "Correlation_RWC_GM130_SYTO\n",
      "Correlation_RWC_GM130_TDP43\n",
      "Correlation_RWC_GM130_TOM20\n",
      "Correlation_RWC_GM130_pRPS6\n",
      "Correlation_RWC_Golgin97_AGP\n",
      "Correlation_RWC_Golgin97_DNA\n",
      "Correlation_RWC_Golgin97_ER\n",
      "Correlation_RWC_Golgin97_G3BP1\n",
      "Correlation_RWC_Golgin97_GM130\n",
      "Correlation_RWC_Golgin97_LAMP1\n",
      "Correlation_RWC_Golgin97_NFKB\n",
      "Correlation_RWC_Golgin97_NeuN\n",
      "Correlation_RWC_Golgin97_RANGAP1\n",
      "Correlation_RWC_Golgin97_SYTO\n",
      "Correlation_RWC_Golgin97_TDP43\n",
      "Correlation_RWC_Golgin97_TOM20\n",
      "Correlation_RWC_Golgin97_pRPS6\n",
      "Correlation_RWC_LAMP1_AGP\n",
      "Correlation_RWC_LAMP1_DNA\n",
      "Correlation_RWC_LAMP1_ER\n",
      "Correlation_RWC_LAMP1_G3BP1\n",
      "Correlation_RWC_LAMP1_GM130\n",
      "Correlation_RWC_LAMP1_Golgin97\n",
      "Correlation_RWC_LAMP1_NFKB\n",
      "Correlation_RWC_LAMP1_NeuN\n",
      "Correlation_RWC_LAMP1_RANGAP1\n",
      "Correlation_RWC_LAMP1_SYTO\n",
      "Correlation_RWC_LAMP1_TDP43\n",
      "Correlation_RWC_LAMP1_TOM20\n",
      "Correlation_RWC_LAMP1_pRPS6\n",
      "Correlation_RWC_NFKB_AGP\n",
      "Correlation_RWC_NFKB_DNA\n",
      "Correlation_RWC_NFKB_ER\n",
      "Correlation_RWC_NFKB_G3BP1\n",
      "Correlation_RWC_NFKB_GM130\n",
      "Correlation_RWC_NFKB_Golgin97\n",
      "Correlation_RWC_NFKB_LAMP1\n",
      "Correlation_RWC_NFKB_NeuN\n",
      "Correlation_RWC_NFKB_RANGAP1\n",
      "Correlation_RWC_NFKB_SYTO\n",
      "Correlation_RWC_NFKB_TDP43\n",
      "Correlation_RWC_NFKB_TOM20\n",
      "Correlation_RWC_NFKB_pRPS6\n",
      "Correlation_RWC_NeuN_AGP\n",
      "Correlation_RWC_NeuN_DNA\n",
      "Correlation_RWC_NeuN_ER\n",
      "Correlation_RWC_NeuN_G3BP1\n",
      "Correlation_RWC_NeuN_GM130\n",
      "Correlation_RWC_NeuN_Golgin97\n",
      "Correlation_RWC_NeuN_LAMP1\n",
      "Correlation_RWC_NeuN_NFKB\n",
      "Correlation_RWC_NeuN_RANGAP1\n",
      "Correlation_RWC_NeuN_SYTO\n",
      "Correlation_RWC_NeuN_TDP43\n",
      "Correlation_RWC_NeuN_TOM20\n",
      "Correlation_RWC_NeuN_pRPS6\n",
      "Correlation_RWC_RANGAP1_AGP\n",
      "Correlation_RWC_RANGAP1_DNA\n",
      "Correlation_RWC_RANGAP1_ER\n",
      "Correlation_RWC_RANGAP1_G3BP1\n",
      "Correlation_RWC_RANGAP1_GM130\n",
      "Correlation_RWC_RANGAP1_Golgin97\n",
      "Correlation_RWC_RANGAP1_LAMP1\n",
      "Correlation_RWC_RANGAP1_NFKB\n",
      "Correlation_RWC_RANGAP1_NeuN\n",
      "Correlation_RWC_RANGAP1_SYTO\n",
      "Correlation_RWC_RANGAP1_TDP43\n",
      "Correlation_RWC_RANGAP1_TOM20\n",
      "Correlation_RWC_RANGAP1_pRPS6\n",
      "Correlation_RWC_SYTO_AGP\n",
      "Correlation_RWC_SYTO_DNA\n",
      "Correlation_RWC_SYTO_ER\n",
      "Correlation_RWC_SYTO_G3BP1\n",
      "Correlation_RWC_SYTO_GM130\n",
      "Correlation_RWC_SYTO_Golgin97\n",
      "Correlation_RWC_SYTO_LAMP1\n",
      "Correlation_RWC_SYTO_NFKB\n",
      "Correlation_RWC_SYTO_NeuN\n",
      "Correlation_RWC_SYTO_RANGAP1\n",
      "Correlation_RWC_SYTO_TDP43\n",
      "Correlation_RWC_SYTO_TOM20\n",
      "Correlation_RWC_SYTO_pRPS6\n",
      "Correlation_RWC_TDP43_AGP\n",
      "Correlation_RWC_TDP43_DNA\n",
      "Correlation_RWC_TDP43_ER\n",
      "Correlation_RWC_TDP43_G3BP1\n",
      "Correlation_RWC_TDP43_GM130\n",
      "Correlation_RWC_TDP43_Golgin97\n",
      "Correlation_RWC_TDP43_LAMP1\n",
      "Correlation_RWC_TDP43_NFKB\n",
      "Correlation_RWC_TDP43_NeuN\n",
      "Correlation_RWC_TDP43_RANGAP1\n",
      "Correlation_RWC_TDP43_SYTO\n",
      "Correlation_RWC_TDP43_TOM20\n",
      "Correlation_RWC_TDP43_pRPS6\n",
      "Correlation_RWC_TOM20_AGP\n",
      "Correlation_RWC_TOM20_DNA\n",
      "Correlation_RWC_TOM20_ER\n",
      "Correlation_RWC_TOM20_G3BP1\n",
      "Correlation_RWC_TOM20_GM130\n",
      "Correlation_RWC_TOM20_Golgin97\n",
      "Correlation_RWC_TOM20_LAMP1\n",
      "Correlation_RWC_TOM20_NFKB\n",
      "Correlation_RWC_TOM20_NeuN\n",
      "Correlation_RWC_TOM20_RANGAP1\n",
      "Correlation_RWC_TOM20_SYTO\n",
      "Correlation_RWC_TOM20_TDP43\n",
      "Correlation_RWC_TOM20_pRPS6\n",
      "Correlation_RWC_pRPS6_AGP\n",
      "Correlation_RWC_pRPS6_DNA\n",
      "Correlation_RWC_pRPS6_ER\n",
      "Correlation_RWC_pRPS6_G3BP1\n",
      "Correlation_RWC_pRPS6_GM130\n",
      "Correlation_RWC_pRPS6_Golgin97\n",
      "Correlation_RWC_pRPS6_LAMP1\n",
      "Correlation_RWC_pRPS6_NFKB\n",
      "Correlation_RWC_pRPS6_NeuN\n",
      "Correlation_RWC_pRPS6_RANGAP1\n",
      "Correlation_RWC_pRPS6_SYTO\n",
      "Correlation_RWC_pRPS6_TDP43\n",
      "Correlation_RWC_pRPS6_TOM20\n",
      "Intensity_MassDisplacement_AGP\n",
      "Intensity_MassDisplacement_ER\n",
      "Intensity_MassDisplacement_G3BP1\n",
      "Intensity_MassDisplacement_GM130\n",
      "Intensity_MassDisplacement_Golgin97\n",
      "Intensity_MassDisplacement_LAMP1\n",
      "Intensity_MassDisplacement_NFKB\n",
      "Intensity_MassDisplacement_NeuN\n",
      "Intensity_MassDisplacement_RANGAP1\n",
      "Intensity_MassDisplacement_SYTO\n",
      "Intensity_MassDisplacement_TDP43\n",
      "Intensity_MassDisplacement_TOM20\n",
      "Intensity_MassDisplacement_pRPS6\n",
      "Location_CenterMassIntensity_X_AGP\n",
      "Location_CenterMassIntensity_X_ER\n",
      "Location_CenterMassIntensity_X_G3BP1\n",
      "Location_CenterMassIntensity_X_GM130\n",
      "Location_CenterMassIntensity_X_Golgin97\n",
      "Location_CenterMassIntensity_X_LAMP1\n",
      "Location_CenterMassIntensity_X_NFKB\n",
      "Location_CenterMassIntensity_X_NeuN\n",
      "Location_CenterMassIntensity_X_RANGAP1\n",
      "Location_CenterMassIntensity_X_SYTO\n",
      "Location_CenterMassIntensity_X_TDP43\n",
      "Location_CenterMassIntensity_X_TOM20\n",
      "Location_CenterMassIntensity_X_pRPS6\n",
      "Location_CenterMassIntensity_Y_AGP\n",
      "Location_CenterMassIntensity_Y_ER\n",
      "Location_CenterMassIntensity_Y_G3BP1\n",
      "Location_CenterMassIntensity_Y_GM130\n",
      "Location_CenterMassIntensity_Y_Golgin97\n",
      "Location_CenterMassIntensity_Y_LAMP1\n",
      "Location_CenterMassIntensity_Y_NFKB\n",
      "Location_CenterMassIntensity_Y_NeuN\n",
      "Location_CenterMassIntensity_Y_RANGAP1\n",
      "Location_CenterMassIntensity_Y_SYTO\n",
      "Location_CenterMassIntensity_Y_TDP43\n",
      "Location_CenterMassIntensity_Y_TOM20\n",
      "Location_CenterMassIntensity_Y_pRPS6\n",
      "Location_CenterMassIntensity_Z_AGP\n",
      "Location_CenterMassIntensity_Z_ER\n",
      "Location_CenterMassIntensity_Z_G3BP1\n",
      "Location_CenterMassIntensity_Z_GM130\n",
      "Location_CenterMassIntensity_Z_Golgin97\n",
      "Location_CenterMassIntensity_Z_LAMP1\n",
      "Location_CenterMassIntensity_Z_NFKB\n",
      "Location_CenterMassIntensity_Z_NeuN\n",
      "Location_CenterMassIntensity_Z_RANGAP1\n",
      "Location_CenterMassIntensity_Z_SYTO\n",
      "Location_CenterMassIntensity_Z_TDP43\n",
      "Location_CenterMassIntensity_Z_TOM20\n",
      "Location_CenterMassIntensity_Z_pRPS6\n",
      "RadialDistribution_FracAtD_AGP_1of4\n",
      "RadialDistribution_FracAtD_AGP_2of4\n",
      "RadialDistribution_FracAtD_AGP_3of4\n",
      "RadialDistribution_FracAtD_AGP_4of4\n",
      "RadialDistribution_FracAtD_ER_1of4\n",
      "RadialDistribution_FracAtD_ER_2of4\n",
      "RadialDistribution_FracAtD_ER_3of4\n",
      "RadialDistribution_FracAtD_ER_4of4\n",
      "RadialDistribution_FracAtD_G3BP1_1of4\n",
      "RadialDistribution_FracAtD_G3BP1_2of4\n",
      "RadialDistribution_FracAtD_G3BP1_3of4\n",
      "RadialDistribution_FracAtD_G3BP1_4of4\n",
      "RadialDistribution_FracAtD_GM130_1of4\n",
      "RadialDistribution_FracAtD_GM130_2of4\n",
      "RadialDistribution_FracAtD_GM130_3of4\n",
      "RadialDistribution_FracAtD_GM130_4of4\n",
      "RadialDistribution_FracAtD_Golgin97_1of4\n",
      "RadialDistribution_FracAtD_Golgin97_2of4\n",
      "RadialDistribution_FracAtD_Golgin97_3of4\n",
      "RadialDistribution_FracAtD_Golgin97_4of4\n",
      "RadialDistribution_FracAtD_LAMP1_1of4\n",
      "RadialDistribution_FracAtD_LAMP1_2of4\n",
      "RadialDistribution_FracAtD_LAMP1_3of4\n",
      "RadialDistribution_FracAtD_LAMP1_4of4\n",
      "RadialDistribution_FracAtD_NFKB_1of4\n",
      "RadialDistribution_FracAtD_NFKB_2of4\n",
      "RadialDistribution_FracAtD_NFKB_3of4\n",
      "RadialDistribution_FracAtD_NFKB_4of4\n",
      "RadialDistribution_FracAtD_NeuN_1of4\n",
      "RadialDistribution_FracAtD_NeuN_2of4\n",
      "RadialDistribution_FracAtD_NeuN_3of4\n",
      "RadialDistribution_FracAtD_NeuN_4of4\n",
      "RadialDistribution_FracAtD_RANGAP1_1of4\n",
      "RadialDistribution_FracAtD_RANGAP1_2of4\n",
      "RadialDistribution_FracAtD_RANGAP1_3of4\n",
      "RadialDistribution_FracAtD_RANGAP1_4of4\n",
      "RadialDistribution_FracAtD_SYTO_1of4\n",
      "RadialDistribution_FracAtD_SYTO_2of4\n",
      "RadialDistribution_FracAtD_SYTO_3of4\n",
      "RadialDistribution_FracAtD_SYTO_4of4\n",
      "RadialDistribution_FracAtD_TDP43_1of4\n",
      "RadialDistribution_FracAtD_TDP43_2of4\n",
      "RadialDistribution_FracAtD_TDP43_3of4\n",
      "RadialDistribution_FracAtD_TDP43_4of4\n",
      "RadialDistribution_FracAtD_TOM20_1of4\n",
      "RadialDistribution_FracAtD_TOM20_2of4\n",
      "RadialDistribution_FracAtD_TOM20_3of4\n",
      "RadialDistribution_FracAtD_TOM20_4of4\n",
      "RadialDistribution_FracAtD_pRPS6_1of4\n",
      "RadialDistribution_FracAtD_pRPS6_2of4\n",
      "RadialDistribution_FracAtD_pRPS6_3of4\n",
      "RadialDistribution_FracAtD_pRPS6_4of4\n",
      "RadialDistribution_MeanFrac_AGP_1of4\n",
      "RadialDistribution_MeanFrac_AGP_2of4\n",
      "RadialDistribution_MeanFrac_AGP_3of4\n",
      "RadialDistribution_MeanFrac_AGP_4of4\n",
      "RadialDistribution_MeanFrac_ER_1of4\n",
      "RadialDistribution_MeanFrac_ER_2of4\n",
      "RadialDistribution_MeanFrac_ER_3of4\n",
      "RadialDistribution_MeanFrac_ER_4of4\n",
      "RadialDistribution_MeanFrac_G3BP1_1of4\n",
      "RadialDistribution_MeanFrac_G3BP1_2of4\n",
      "RadialDistribution_MeanFrac_G3BP1_3of4\n",
      "RadialDistribution_MeanFrac_G3BP1_4of4\n",
      "RadialDistribution_MeanFrac_GM130_1of4\n",
      "RadialDistribution_MeanFrac_GM130_2of4\n",
      "RadialDistribution_MeanFrac_GM130_3of4\n",
      "RadialDistribution_MeanFrac_GM130_4of4\n",
      "RadialDistribution_MeanFrac_Golgin97_1of4\n",
      "RadialDistribution_MeanFrac_Golgin97_2of4\n",
      "RadialDistribution_MeanFrac_Golgin97_3of4\n",
      "RadialDistribution_MeanFrac_Golgin97_4of4\n",
      "RadialDistribution_MeanFrac_LAMP1_1of4\n",
      "RadialDistribution_MeanFrac_LAMP1_2of4\n",
      "RadialDistribution_MeanFrac_LAMP1_3of4\n",
      "RadialDistribution_MeanFrac_LAMP1_4of4\n",
      "RadialDistribution_MeanFrac_NFKB_1of4\n",
      "RadialDistribution_MeanFrac_NFKB_2of4\n",
      "RadialDistribution_MeanFrac_NFKB_3of4\n",
      "RadialDistribution_MeanFrac_NFKB_4of4\n",
      "RadialDistribution_MeanFrac_NeuN_1of4\n",
      "RadialDistribution_MeanFrac_NeuN_2of4\n",
      "RadialDistribution_MeanFrac_NeuN_3of4\n",
      "RadialDistribution_MeanFrac_NeuN_4of4\n",
      "RadialDistribution_MeanFrac_RANGAP1_1of4\n",
      "RadialDistribution_MeanFrac_RANGAP1_2of4\n",
      "RadialDistribution_MeanFrac_RANGAP1_3of4\n",
      "RadialDistribution_MeanFrac_RANGAP1_4of4\n",
      "RadialDistribution_MeanFrac_SYTO_1of4\n",
      "RadialDistribution_MeanFrac_SYTO_2of4\n",
      "RadialDistribution_MeanFrac_SYTO_3of4\n",
      "RadialDistribution_MeanFrac_SYTO_4of4\n",
      "RadialDistribution_MeanFrac_TDP43_1of4\n",
      "RadialDistribution_MeanFrac_TDP43_2of4\n",
      "RadialDistribution_MeanFrac_TDP43_3of4\n",
      "RadialDistribution_MeanFrac_TDP43_4of4\n",
      "RadialDistribution_MeanFrac_TOM20_1of4\n",
      "RadialDistribution_MeanFrac_TOM20_2of4\n",
      "RadialDistribution_MeanFrac_TOM20_3of4\n",
      "RadialDistribution_MeanFrac_TOM20_4of4\n",
      "RadialDistribution_MeanFrac_pRPS6_1of4\n",
      "RadialDistribution_MeanFrac_pRPS6_2of4\n",
      "RadialDistribution_MeanFrac_pRPS6_3of4\n",
      "RadialDistribution_MeanFrac_pRPS6_4of4\n"
     ]
    }
   ],
   "source": [
    "for col in nan_cols:\n",
    "    print(col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1210956f",
   "metadata": {},
   "outputs": [
    {
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       "    }\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>ImageNumber</th>\n",
       "      <th>ObjectNumber</th>\n",
       "      <th>FileName_max_clean</th>\n",
       "      <th>PathName_max_clean</th>\n",
       "      <th>AreaShape_Area</th>\n",
       "      <th>AreaShape_BoundingBoxArea</th>\n",
       "      <th>AreaShape_BoundingBoxMaximum_X</th>\n",
       "      <th>AreaShape_BoundingBoxMaximum_Y</th>\n",
       "      <th>AreaShape_BoundingBoxMinimum_X</th>\n",
       "      <th>AreaShape_BoundingBoxMinimum_Y</th>\n",
       "      <th>...</th>\n",
       "      <th>Texture_Variance_pRPS6_10_02_256</th>\n",
       "      <th>Texture_Variance_pRPS6_10_03_256</th>\n",
       "      <th>Texture_Variance_pRPS6_3_00_256</th>\n",
       "      <th>Texture_Variance_pRPS6_3_01_256</th>\n",
       "      <th>Texture_Variance_pRPS6_3_02_256</th>\n",
       "      <th>Texture_Variance_pRPS6_3_03_256</th>\n",
       "      <th>Texture_Variance_pRPS6_5_00_256</th>\n",
       "      <th>Texture_Variance_pRPS6_5_01_256</th>\n",
       "      <th>Texture_Variance_pRPS6_5_02_256</th>\n",
       "      <th>Texture_Variance_pRPS6_5_03_256</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>F000_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>300</td>\n",
       "      <td>784</td>\n",
       "      <td>1534</td>\n",
       "      <td>31</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>F000_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>314</td>\n",
       "      <td>728</td>\n",
       "      <td>1744</td>\n",
       "      <td>48</td>\n",
       "      <td>1716</td>\n",
       "      <td>22</td>\n",
       "      <td>...</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>F000_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>528</td>\n",
       "      <td>2220</td>\n",
       "      <td>1250</td>\n",
       "      <td>63</td>\n",
       "      <td>1190</td>\n",
       "      <td>26</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.555556</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>F000_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>271</td>\n",
       "      <td>600</td>\n",
       "      <td>54</td>\n",
       "      <td>56</td>\n",
       "      <td>30</td>\n",
       "      <td>31</td>\n",
       "      <td>...</td>\n",
       "      <td>2.576389</td>\n",
       "      <td>2.805556</td>\n",
       "      <td>1.867769</td>\n",
       "      <td>1.007785</td>\n",
       "      <td>1.668639</td>\n",
       "      <td>1.897377</td>\n",
       "      <td>2.164931</td>\n",
       "      <td>1.055556</td>\n",
       "      <td>1.549169</td>\n",
       "      <td>2.845556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>F000_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>696</td>\n",
       "      <td>1440</td>\n",
       "      <td>1559</td>\n",
       "      <td>70</td>\n",
       "      <td>1527</td>\n",
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       "      <td>...</td>\n",
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       "      <td>0.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.187500</td>\n",
       "      <td>0.187500</td>\n",
       "      <td>0.138889</td>\n",
       "      <td>0.187500</td>\n",
       "      <td>0.000000</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>133695</th>\n",
       "      <td>225</td>\n",
       "      <td>258</td>\n",
       "      <td>F224_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>940</td>\n",
       "      <td>1960</td>\n",
       "      <td>1790</td>\n",
       "      <td>1974</td>\n",
       "      <td>1741</td>\n",
       "      <td>1934</td>\n",
       "      <td>...</td>\n",
       "      <td>2.187500</td>\n",
       "      <td>1.551038</td>\n",
       "      <td>1.969436</td>\n",
       "      <td>1.243827</td>\n",
       "      <td>1.347826</td>\n",
       "      <td>1.254931</td>\n",
       "      <td>1.916571</td>\n",
       "      <td>0.845065</td>\n",
       "      <td>1.281142</td>\n",
       "      <td>1.383878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133696</th>\n",
       "      <td>225</td>\n",
       "      <td>259</td>\n",
       "      <td>F224_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>533</td>\n",
       "      <td>1600</td>\n",
       "      <td>1619</td>\n",
       "      <td>1980</td>\n",
       "      <td>1569</td>\n",
       "      <td>1948</td>\n",
       "      <td>...</td>\n",
       "      <td>3.134354</td>\n",
       "      <td>4.380165</td>\n",
       "      <td>8.739692</td>\n",
       "      <td>5.266173</td>\n",
       "      <td>7.643882</td>\n",
       "      <td>8.437500</td>\n",
       "      <td>6.986226</td>\n",
       "      <td>3.464286</td>\n",
       "      <td>7.586238</td>\n",
       "      <td>9.596246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133697</th>\n",
       "      <td>225</td>\n",
       "      <td>260</td>\n",
       "      <td>F224_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>670</td>\n",
       "      <td>1665</td>\n",
       "      <td>1441</td>\n",
       "      <td>1999</td>\n",
       "      <td>1396</td>\n",
       "      <td>1962</td>\n",
       "      <td>...</td>\n",
       "      <td>1.764463</td>\n",
       "      <td>2.256920</td>\n",
       "      <td>1.469050</td>\n",
       "      <td>2.097029</td>\n",
       "      <td>1.677123</td>\n",
       "      <td>2.573307</td>\n",
       "      <td>1.520672</td>\n",
       "      <td>2.552411</td>\n",
       "      <td>2.081690</td>\n",
       "      <td>1.991736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133698</th>\n",
       "      <td>225</td>\n",
       "      <td>261</td>\n",
       "      <td>F224_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>215</td>\n",
       "      <td>870</td>\n",
       "      <td>1871</td>\n",
       "      <td>2005</td>\n",
       "      <td>1841</td>\n",
       "      <td>1976</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.519375</td>\n",
       "      <td>3.765571</td>\n",
       "      <td>4.742883</td>\n",
       "      <td>4.647598</td>\n",
       "      <td>5.282136</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.423554</td>\n",
       "      <td>1.956314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133699</th>\n",
       "      <td>225</td>\n",
       "      <td>262</td>\n",
       "      <td>F224_max_clean.tif</td>\n",
       "      <td>/mnt/disks/store/101222_D10_Coverslip1_Process...</td>\n",
       "      <td>1086</td>\n",
       "      <td>2703</td>\n",
       "      <td>1258</td>\n",
       "      <td>2005</td>\n",
       "      <td>1207</td>\n",
       "      <td>1952</td>\n",
       "      <td>...</td>\n",
       "      <td>605.738697</td>\n",
       "      <td>540.519267</td>\n",
       "      <td>618.618869</td>\n",
       "      <td>621.026603</td>\n",
       "      <td>593.234845</td>\n",
       "      <td>644.965061</td>\n",
       "      <td>670.038591</td>\n",
       "      <td>662.290754</td>\n",
       "      <td>628.805697</td>\n",
       "      <td>704.896454</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>133700 rows × 3785 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ImageNumber  ObjectNumber  FileName_max_clean  \\\n",
       "0                 1             1  F000_max_clean.tif   \n",
       "1                 1             2  F000_max_clean.tif   \n",
       "2                 1             3  F000_max_clean.tif   \n",
       "3                 1             4  F000_max_clean.tif   \n",
       "4                 1             5  F000_max_clean.tif   \n",
       "...             ...           ...                 ...   \n",
       "133695          225           258  F224_max_clean.tif   \n",
       "133696          225           259  F224_max_clean.tif   \n",
       "133697          225           260  F224_max_clean.tif   \n",
       "133698          225           261  F224_max_clean.tif   \n",
       "133699          225           262  F224_max_clean.tif   \n",
       "\n",
       "                                       PathName_max_clean  AreaShape_Area  \\\n",
       "0       /mnt/disks/store/101222_D10_Coverslip1_Process...             300   \n",
       "1       /mnt/disks/store/101222_D10_Coverslip1_Process...             314   \n",
       "2       /mnt/disks/store/101222_D10_Coverslip1_Process...             528   \n",
       "3       /mnt/disks/store/101222_D10_Coverslip1_Process...             271   \n",
       "4       /mnt/disks/store/101222_D10_Coverslip1_Process...             696   \n",
       "...                                                   ...             ...   \n",
       "133695  /mnt/disks/store/101222_D10_Coverslip1_Process...             940   \n",
       "133696  /mnt/disks/store/101222_D10_Coverslip1_Process...             533   \n",
       "133697  /mnt/disks/store/101222_D10_Coverslip1_Process...             670   \n",
       "133698  /mnt/disks/store/101222_D10_Coverslip1_Process...             215   \n",
       "133699  /mnt/disks/store/101222_D10_Coverslip1_Process...            1086   \n",
       "\n",
       "        AreaShape_BoundingBoxArea  AreaShape_BoundingBoxMaximum_X  \\\n",
       "0                             784                            1534   \n",
       "1                             728                            1744   \n",
       "2                            2220                            1250   \n",
       "3                             600                              54   \n",
       "4                            1440                            1559   \n",
       "...                           ...                             ...   \n",
       "133695                       1960                            1790   \n",
       "133696                       1600                            1619   \n",
       "133697                       1665                            1441   \n",
       "133698                        870                            1871   \n",
       "133699                       2703                            1258   \n",
       "\n",
       "        AreaShape_BoundingBoxMaximum_Y  AreaShape_BoundingBoxMinimum_X  \\\n",
       "0                                   31                            1506   \n",
       "1                                   48                            1716   \n",
       "2                                   63                            1190   \n",
       "3                                   56                              30   \n",
       "4                                   70                            1527   \n",
       "...                                ...                             ...   \n",
       "133695                            1974                            1741   \n",
       "133696                            1980                            1569   \n",
       "133697                            1999                            1396   \n",
       "133698                            2005                            1841   \n",
       "133699                            2005                            1207   \n",
       "\n",
       "        AreaShape_BoundingBoxMinimum_Y  ...  Texture_Variance_pRPS6_10_02_256  \\\n",
       "0                                    3  ...                          0.000000   \n",
       "1                                   22  ...                          0.000000   \n",
       "2                                   26  ...                          0.000000   \n",
       "3                                   31  ...                          2.576389   \n",
       "4                                   25  ...                          0.000000   \n",
       "...                                ...  ...                               ...   \n",
       "133695                            1934  ...                          2.187500   \n",
       "133696                            1948  ...                          3.134354   \n",
       "133697                            1962  ...                          1.764463   \n",
       "133698                            1976  ...                          0.000000   \n",
       "133699                            1952  ...                        605.738697   \n",
       "\n",
       "        Texture_Variance_pRPS6_10_03_256  Texture_Variance_pRPS6_3_00_256  \\\n",
       "0                               0.000000                         0.000000   \n",
       "1                               0.000000                         0.000000   \n",
       "2                               0.000000                         0.000000   \n",
       "3                               2.805556                         1.867769   \n",
       "4                               0.000000                         0.109375   \n",
       "...                                  ...                              ...   \n",
       "133695                          1.551038                         1.969436   \n",
       "133696                          4.380165                         8.739692   \n",
       "133697                          2.256920                         1.469050   \n",
       "133698                          0.000000                         4.519375   \n",
       "133699                        540.519267                       618.618869   \n",
       "\n",
       "        Texture_Variance_pRPS6_3_01_256  Texture_Variance_pRPS6_3_02_256  \\\n",
       "0                              0.000000                         0.000000   \n",
       "1                              0.000000                         0.000000   \n",
       "2                              0.000000                         0.555556   \n",
       "3                              1.007785                         1.668639   \n",
       "4                              0.250000                         0.000000   \n",
       "...                                 ...                              ...   \n",
       "133695                         1.243827                         1.347826   \n",
       "133696                         5.266173                         7.643882   \n",
       "133697                         2.097029                         1.677123   \n",
       "133698                         3.765571                         4.742883   \n",
       "133699                       621.026603                       593.234845   \n",
       "\n",
       "        Texture_Variance_pRPS6_3_03_256  Texture_Variance_pRPS6_5_00_256  \\\n",
       "0                              0.000000                         0.000000   \n",
       "1                              0.000000                         0.000000   \n",
       "2                              0.000000                         0.000000   \n",
       "3                              1.897377                         2.164931   \n",
       "4                              0.187500                         0.187500   \n",
       "...                                 ...                              ...   \n",
       "133695                         1.254931                         1.916571   \n",
       "133696                         8.437500                         6.986226   \n",
       "133697                         2.573307                         1.520672   \n",
       "133698                         4.647598                         5.282136   \n",
       "133699                       644.965061                       670.038591   \n",
       "\n",
       "        Texture_Variance_pRPS6_5_01_256  Texture_Variance_pRPS6_5_02_256  \\\n",
       "0                              0.000000                         0.000000   \n",
       "1                              0.000000                         0.000000   \n",
       "2                              0.000000                         0.000000   \n",
       "3                              1.055556                         1.549169   \n",
       "4                              0.138889                         0.187500   \n",
       "...                                 ...                              ...   \n",
       "133695                         0.845065                         1.281142   \n",
       "133696                         3.464286                         7.586238   \n",
       "133697                         2.552411                         2.081690   \n",
       "133698                         0.000000                         4.423554   \n",
       "133699                       662.290754                       628.805697   \n",
       "\n",
       "        Texture_Variance_pRPS6_5_03_256  \n",
       "0                              0.000000  \n",
       "1                              0.000000  \n",
       "2                              0.000000  \n",
       "3                              2.845556  \n",
       "4                              0.000000  \n",
       "...                                 ...  \n",
       "133695                         1.383878  \n",
       "133696                         9.596246  \n",
       "133697                         1.991736  \n",
       "133698                         1.956314  \n",
       "133699                       704.896454  \n",
       "\n",
       "[133700 rows x 3785 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cp_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "228d73ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         0.114029\n",
       "1         0.605753\n",
       "2         0.322415\n",
       "3         0.553012\n",
       "4         0.357705\n",
       "            ...   \n",
       "133695   -0.118479\n",
       "133696   -0.209092\n",
       "133697   -0.185486\n",
       "133698   -0.029438\n",
       "133699    0.368773\n",
       "Name: Correlation_Correlation_AGP_DNA, Length: 133700, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cp_df['Correlation_Correlation_AGP_DNA']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f440befb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "43874\n"
     ]
    }
   ],
   "source": [
    "# only select Procode+ cells?\n",
    "soma_df = pd.read_csv('Coverslip1_soma_final.csv',sep=',', index_col = 0)\n",
    "idx = soma_df[soma_df['InfectedCells']==1].index\n",
    "print(len(idx))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "18f9ca62",
   "metadata": {},
   "outputs": [],
   "source": [
    "# MAD normalization after filtering columns\n",
    "def MAD(df_in, veto_list, eps): # seg_df,  ['ImageNumber', 'ObjectNumber',...,'Number', 'Parent'], 1e-15\n",
    "    # filter columns for veto (nonsense columns like object number, location, coordinates, etc)\n",
    "    L = df_in.columns.tolist()\n",
    "    removeL = []\n",
    "    for v in veto:\n",
    "        for l in L:\n",
    "            if l.startswith(v):\n",
    "                removeL.append(l)       \n",
    "    \n",
    "    for l in L:\n",
    "        if 'BoundingBoxMaximum' in l.split('_'):\n",
    "            print(l)\n",
    "            removeL.append(l)\n",
    "        if 'BoundingBoxMinimum' in l.split('_'):\n",
    "            print(l)\n",
    "            removeL.append(l)\n",
    "        \n",
    "    removeL.append('AreaShape_Center_X')\n",
    "    removeL.append('AreaShape_Center_Y')\n",
    "    print('removing ', removeL)\n",
    "    for x in removeL: L.remove(x)\n",
    "        \n",
    "        \n",
    "    # filter nan cols\n",
    "    df_in = df_in[L]\n",
    "    nan_cols = [i for i in df_in.columns if df_in[i].isnull().any()]\n",
    "    print(\"NAN columns\", len(nan_cols))\n",
    "    df_in = df_in[df_in.columns[~df_in.columns.isin(nan_cols)]]\n",
    "    \n",
    "    # calculate MAD\n",
    "    MAD = stats.median_abs_deviation(df_in, nan_policy='omit')\n",
    "    df_in_scaled = df_in - np.median(df_in, axis=0)\n",
    "    df_in_scaled = np.divide(df_in_scaled, MAD+eps)\n",
    "    \n",
    "    return df_in_scaled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0b30c9d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AreaShape_BoundingBoxMaximum_X\n",
      "AreaShape_BoundingBoxMaximum_Y\n",
      "AreaShape_BoundingBoxMinimum_X\n",
      "AreaShape_BoundingBoxMinimum_Y\n",
      "removing  ['ImageNumber', 'ObjectNumber', 'FileName_max_clean', 'PathName_max_clean', 'Location_CenterMassIntensity_X_AGP', 'Location_CenterMassIntensity_X_DNA', 'Location_CenterMassIntensity_X_ER', 'Location_CenterMassIntensity_X_G3BP1', 'Location_CenterMassIntensity_X_GM130', 'Location_CenterMassIntensity_X_Golgin97', 'Location_CenterMassIntensity_X_LAMP1', 'Location_CenterMassIntensity_X_NFKB', 'Location_CenterMassIntensity_X_NeuN', 'Location_CenterMassIntensity_X_RANGAP1', 'Location_CenterMassIntensity_X_SYTO', 'Location_CenterMassIntensity_X_TDP43', 'Location_CenterMassIntensity_X_TOM20', 'Location_CenterMassIntensity_X_pRPS6', 'Location_CenterMassIntensity_Y_AGP', 'Location_CenterMassIntensity_Y_DNA', 'Location_CenterMassIntensity_Y_ER', 'Location_CenterMassIntensity_Y_G3BP1', 'Location_CenterMassIntensity_Y_GM130', 'Location_CenterMassIntensity_Y_Golgin97', 'Location_CenterMassIntensity_Y_LAMP1', 'Location_CenterMassIntensity_Y_NFKB', 'Location_CenterMassIntensity_Y_NeuN', 'Location_CenterMassIntensity_Y_RANGAP1', 'Location_CenterMassIntensity_Y_SYTO', 'Location_CenterMassIntensity_Y_TDP43', 'Location_CenterMassIntensity_Y_TOM20', 'Location_CenterMassIntensity_Y_pRPS6', 'Location_CenterMassIntensity_Z_AGP', 'Location_CenterMassIntensity_Z_DNA', 'Location_CenterMassIntensity_Z_ER', 'Location_CenterMassIntensity_Z_G3BP1', 'Location_CenterMassIntensity_Z_GM130', 'Location_CenterMassIntensity_Z_Golgin97', 'Location_CenterMassIntensity_Z_LAMP1', 'Location_CenterMassIntensity_Z_NFKB', 'Location_CenterMassIntensity_Z_NeuN', 'Location_CenterMassIntensity_Z_RANGAP1', 'Location_CenterMassIntensity_Z_SYTO', 'Location_CenterMassIntensity_Z_TDP43', 'Location_CenterMassIntensity_Z_TOM20', 'Location_CenterMassIntensity_Z_pRPS6', 'Location_Center_X', 'Location_Center_Y', 'Location_MaxIntensity_X_AGP', 'Location_MaxIntensity_X_DNA', 'Location_MaxIntensity_X_ER', 'Location_MaxIntensity_X_G3BP1', 'Location_MaxIntensity_X_GM130', 'Location_MaxIntensity_X_Golgin97', 'Location_MaxIntensity_X_LAMP1', 'Location_MaxIntensity_X_NFKB', 'Location_MaxIntensity_X_NeuN', 'Location_MaxIntensity_X_RANGAP1', 'Location_MaxIntensity_X_SYTO', 'Location_MaxIntensity_X_TDP43', 'Location_MaxIntensity_X_TOM20', 'Location_MaxIntensity_X_pRPS6', 'Location_MaxIntensity_Y_AGP', 'Location_MaxIntensity_Y_DNA', 'Location_MaxIntensity_Y_ER', 'Location_MaxIntensity_Y_G3BP1', 'Location_MaxIntensity_Y_GM130', 'Location_MaxIntensity_Y_Golgin97', 'Location_MaxIntensity_Y_LAMP1', 'Location_MaxIntensity_Y_NFKB', 'Location_MaxIntensity_Y_NeuN', 'Location_MaxIntensity_Y_RANGAP1', 'Location_MaxIntensity_Y_SYTO', 'Location_MaxIntensity_Y_TDP43', 'Location_MaxIntensity_Y_TOM20', 'Location_MaxIntensity_Y_pRPS6', 'Location_MaxIntensity_Z_AGP', 'Location_MaxIntensity_Z_DNA', 'Location_MaxIntensity_Z_ER', 'Location_MaxIntensity_Z_G3BP1', 'Location_MaxIntensity_Z_GM130', 'Location_MaxIntensity_Z_Golgin97', 'Location_MaxIntensity_Z_LAMP1', 'Location_MaxIntensity_Z_NFKB', 'Location_MaxIntensity_Z_NeuN', 'Location_MaxIntensity_Z_RANGAP1', 'Location_MaxIntensity_Z_SYTO', 'Location_MaxIntensity_Z_TDP43', 'Location_MaxIntensity_Z_TOM20', 'Location_MaxIntensity_Z_pRPS6', 'Number_Object_Number', 'Parent_FilteredNuclei', 'Parent_SYTO_', 'AreaShape_BoundingBoxMaximum_X', 'AreaShape_BoundingBoxMaximum_Y', 'AreaShape_BoundingBoxMinimum_X', 'AreaShape_BoundingBoxMinimum_Y', 'AreaShape_Center_X', 'AreaShape_Center_Y']\n",
      "NAN columns 991\n",
      "(133700, 2695)\n"
     ]
    }
   ],
   "source": [
    "veto = ['ImageNumber', 'ObjectNumber','FileName','PathName','Children','Location', 'Number', 'Parent']\n",
    "cp_df_scaled = MAD(cp_df, veto, 1e-10)\n",
    "print(cp_df_scaled.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d38cf3c6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "43874\n",
      "(43874, 2695)\n"
     ]
    }
   ],
   "source": [
    "# only select Procode+ cells?\n",
    "soma_df = pd.read_csv('Coverslip1_soma_final.csv',sep=',', index_col = 0)\n",
    "idx = soma_df[soma_df['InfectedCells']==1].index\n",
    "print(len(idx))\n",
    "cp_df_scaled = cp_df_scaled.loc[idx,:]\n",
    "print(cp_df_scaled.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7857a0a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AreaShape_Area</th>\n",
       "      <th>AreaShape_BoundingBoxArea</th>\n",
       "      <th>AreaShape_CentralMoment_0_0</th>\n",
       "      <th>AreaShape_CentralMoment_0_1</th>\n",
       "      <th>AreaShape_CentralMoment_0_2</th>\n",
       "      <th>AreaShape_CentralMoment_0_3</th>\n",
       "      <th>AreaShape_CentralMoment_1_0</th>\n",
       "      <th>AreaShape_CentralMoment_1_1</th>\n",
       "      <th>AreaShape_CentralMoment_1_2</th>\n",
       "      <th>AreaShape_CentralMoment_1_3</th>\n",
       "      <th>...</th>\n",
       "      <th>Texture_Variance_pRPS6_10_02_256</th>\n",
       "      <th>Texture_Variance_pRPS6_10_03_256</th>\n",
       "      <th>Texture_Variance_pRPS6_3_00_256</th>\n",
       "      <th>Texture_Variance_pRPS6_3_01_256</th>\n",
       "      <th>Texture_Variance_pRPS6_3_02_256</th>\n",
       "      <th>Texture_Variance_pRPS6_3_03_256</th>\n",
       "      <th>Texture_Variance_pRPS6_5_00_256</th>\n",
       "      <th>Texture_Variance_pRPS6_5_01_256</th>\n",
       "      <th>Texture_Variance_pRPS6_5_02_256</th>\n",
       "      <th>Texture_Variance_pRPS6_5_03_256</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.168067</td>\n",
       "      <td>-1.354167</td>\n",
       "      <td>-0.168067</td>\n",
       "      <td>-0.000567</td>\n",
       "      <td>-0.715483</td>\n",
       "      <td>0.557721</td>\n",
       "      <td>-0.003829</td>\n",
       "      <td>-0.634234</td>\n",
       "      <td>0.446961</td>\n",
       "      <td>-0.123880</td>\n",
       "      <td>...</td>\n",
       "      <td>5.942690</td>\n",
       "      <td>10.222222</td>\n",
       "      <td>0.158974</td>\n",
       "      <td>-0.328143</td>\n",
       "      <td>0.001183</td>\n",
       "      <td>0.222970</td>\n",
       "      <td>0.872411</td>\n",
       "      <td>0.027027</td>\n",
       "      <td>0.267502</td>\n",
       "      <td>1.701679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.403361</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>3.403361</td>\n",
       "      <td>-0.002162</td>\n",
       "      <td>1.856816</td>\n",
       "      <td>-0.523144</td>\n",
       "      <td>-0.007977</td>\n",
       "      <td>0.108824</td>\n",
       "      <td>-0.132573</td>\n",
       "      <td>-0.652413</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.932131</td>\n",
       "      <td>-0.833333</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.879145</td>\n",
       "      <td>-0.837834</td>\n",
       "      <td>-0.864865</td>\n",
       "      <td>-0.846591</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.344538</td>\n",
       "      <td>0.739583</td>\n",
       "      <td>1.344538</td>\n",
       "      <td>-0.002977</td>\n",
       "      <td>1.500511</td>\n",
       "      <td>-0.404296</td>\n",
       "      <td>-0.000780</td>\n",
       "      <td>-0.831670</td>\n",
       "      <td>0.104052</td>\n",
       "      <td>-2.730143</td>\n",
       "      <td>...</td>\n",
       "      <td>4.389474</td>\n",
       "      <td>4.786704</td>\n",
       "      <td>0.027279</td>\n",
       "      <td>-0.124523</td>\n",
       "      <td>-0.064451</td>\n",
       "      <td>0.055670</td>\n",
       "      <td>0.416246</td>\n",
       "      <td>-0.513514</td>\n",
       "      <td>0.362280</td>\n",
       "      <td>0.625173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5.764706</td>\n",
       "      <td>3.075521</td>\n",
       "      <td>5.764706</td>\n",
       "      <td>-0.008436</td>\n",
       "      <td>15.999719</td>\n",
       "      <td>-12.195204</td>\n",
       "      <td>-0.035701</td>\n",
       "      <td>2.140157</td>\n",
       "      <td>12.635548</td>\n",
       "      <td>0.241961</td>\n",
       "      <td>...</td>\n",
       "      <td>18446.980661</td>\n",
       "      <td>19461.035101</td>\n",
       "      <td>3626.915127</td>\n",
       "      <td>3537.499415</td>\n",
       "      <td>3286.435600</td>\n",
       "      <td>4024.209271</td>\n",
       "      <td>5032.558348</td>\n",
       "      <td>6117.680955</td>\n",
       "      <td>4420.082433</td>\n",
       "      <td>5489.754308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.201681</td>\n",
       "      <td>-0.651042</td>\n",
       "      <td>0.201681</td>\n",
       "      <td>-0.000532</td>\n",
       "      <td>0.112900</td>\n",
       "      <td>0.779117</td>\n",
       "      <td>-0.001950</td>\n",
       "      <td>0.275717</td>\n",
       "      <td>0.339896</td>\n",
       "      <td>0.142078</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</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>133689</th>\n",
       "      <td>3.134454</td>\n",
       "      <td>2.812500</td>\n",
       "      <td>3.134454</td>\n",
       "      <td>-0.031900</td>\n",
       "      <td>5.430333</td>\n",
       "      <td>-2.606925</td>\n",
       "      <td>-0.014465</td>\n",
       "      <td>-13.658758</td>\n",
       "      <td>16.416950</td>\n",
       "      <td>-22.023362</td>\n",
       "      <td>...</td>\n",
       "      <td>12.184962</td>\n",
       "      <td>6.061728</td>\n",
       "      <td>3.975561</td>\n",
       "      <td>1.605148</td>\n",
       "      <td>3.986986</td>\n",
       "      <td>2.771573</td>\n",
       "      <td>3.893472</td>\n",
       "      <td>9.503257</td>\n",
       "      <td>4.228182</td>\n",
       "      <td>4.012818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133690</th>\n",
       "      <td>1.495798</td>\n",
       "      <td>0.093750</td>\n",
       "      <td>1.495798</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.785333</td>\n",
       "      <td>2.249659</td>\n",
       "      <td>-0.003829</td>\n",
       "      <td>5.308146</td>\n",
       "      <td>0.201383</td>\n",
       "      <td>5.506446</td>\n",
       "      <td>...</td>\n",
       "      <td>7.541238</td>\n",
       "      <td>5.888889</td>\n",
       "      <td>1.084918</td>\n",
       "      <td>0.473834</td>\n",
       "      <td>0.346098</td>\n",
       "      <td>0.654216</td>\n",
       "      <td>0.596526</td>\n",
       "      <td>-0.167746</td>\n",
       "      <td>2.317112</td>\n",
       "      <td>0.850417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133692</th>\n",
       "      <td>6.319328</td>\n",
       "      <td>5.098958</td>\n",
       "      <td>6.319328</td>\n",
       "      <td>-0.011945</td>\n",
       "      <td>11.683614</td>\n",
       "      <td>-11.465516</td>\n",
       "      <td>0.013047</td>\n",
       "      <td>-19.993063</td>\n",
       "      <td>36.512805</td>\n",
       "      <td>-53.658306</td>\n",
       "      <td>...</td>\n",
       "      <td>77.533477</td>\n",
       "      <td>131.542013</td>\n",
       "      <td>21.177543</td>\n",
       "      <td>19.925170</td>\n",
       "      <td>20.979412</td>\n",
       "      <td>21.560949</td>\n",
       "      <td>12.750735</td>\n",
       "      <td>20.811274</td>\n",
       "      <td>27.974162</td>\n",
       "      <td>23.889670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133694</th>\n",
       "      <td>1.117647</td>\n",
       "      <td>1.226562</td>\n",
       "      <td>1.117647</td>\n",
       "      <td>0.002906</td>\n",
       "      <td>1.464681</td>\n",
       "      <td>3.364549</td>\n",
       "      <td>0.002056</td>\n",
       "      <td>-3.527258</td>\n",
       "      <td>-8.058553</td>\n",
       "      <td>-8.730158</td>\n",
       "      <td>...</td>\n",
       "      <td>7.111158</td>\n",
       "      <td>15.395556</td>\n",
       "      <td>1.306295</td>\n",
       "      <td>1.296296</td>\n",
       "      <td>1.116724</td>\n",
       "      <td>1.680068</td>\n",
       "      <td>2.381452</td>\n",
       "      <td>0.826514</td>\n",
       "      <td>1.125988</td>\n",
       "      <td>2.162056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133699</th>\n",
       "      <td>6.680672</td>\n",
       "      <td>4.122396</td>\n",
       "      <td>6.680672</td>\n",
       "      <td>0.018573</td>\n",
       "      <td>9.125346</td>\n",
       "      <td>3.529823</td>\n",
       "      <td>0.021910</td>\n",
       "      <td>9.119067</td>\n",
       "      <td>-1.235781</td>\n",
       "      <td>6.434976</td>\n",
       "      <td>...</td>\n",
       "      <td>1631.306382</td>\n",
       "      <td>2161.077067</td>\n",
       "      <td>382.860939</td>\n",
       "      <td>413.017736</td>\n",
       "      <td>354.940907</td>\n",
       "      <td>414.717679</td>\n",
       "      <td>578.504894</td>\n",
       "      <td>643.391004</td>\n",
       "      <td>513.477389</td>\n",
       "      <td>668.255622</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>43874 rows × 2695 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        AreaShape_Area  AreaShape_BoundingBoxArea  \\\n",
       "3            -0.168067                  -1.354167   \n",
       "4             3.403361                   0.833333   \n",
       "10            1.344538                   0.739583   \n",
       "11            5.764706                   3.075521   \n",
       "15            0.201681                  -0.651042   \n",
       "...                ...                        ...   \n",
       "133689        3.134454                   2.812500   \n",
       "133690        1.495798                   0.093750   \n",
       "133692        6.319328                   5.098958   \n",
       "133694        1.117647                   1.226562   \n",
       "133699        6.680672                   4.122396   \n",
       "\n",
       "        AreaShape_CentralMoment_0_0  AreaShape_CentralMoment_0_1  \\\n",
       "3                         -0.168067                    -0.000567   \n",
       "4                          3.403361                    -0.002162   \n",
       "10                         1.344538                    -0.002977   \n",
       "11                         5.764706                    -0.008436   \n",
       "15                         0.201681                    -0.000532   \n",
       "...                             ...                          ...   \n",
       "133689                     3.134454                    -0.031900   \n",
       "133690                     1.495798                     0.000000   \n",
       "133692                     6.319328                    -0.011945   \n",
       "133694                     1.117647                     0.002906   \n",
       "133699                     6.680672                     0.018573   \n",
       "\n",
       "        AreaShape_CentralMoment_0_2  AreaShape_CentralMoment_0_3  \\\n",
       "3                         -0.715483                     0.557721   \n",
       "4                          1.856816                    -0.523144   \n",
       "10                         1.500511                    -0.404296   \n",
       "11                        15.999719                   -12.195204   \n",
       "15                         0.112900                     0.779117   \n",
       "...                             ...                          ...   \n",
       "133689                     5.430333                    -2.606925   \n",
       "133690                     1.785333                     2.249659   \n",
       "133692                    11.683614                   -11.465516   \n",
       "133694                     1.464681                     3.364549   \n",
       "133699                     9.125346                     3.529823   \n",
       "\n",
       "        AreaShape_CentralMoment_1_0  AreaShape_CentralMoment_1_1  \\\n",
       "3                         -0.003829                    -0.634234   \n",
       "4                         -0.007977                     0.108824   \n",
       "10                        -0.000780                    -0.831670   \n",
       "11                        -0.035701                     2.140157   \n",
       "15                        -0.001950                     0.275717   \n",
       "...                             ...                          ...   \n",
       "133689                    -0.014465                   -13.658758   \n",
       "133690                    -0.003829                     5.308146   \n",
       "133692                     0.013047                   -19.993063   \n",
       "133694                     0.002056                    -3.527258   \n",
       "133699                     0.021910                     9.119067   \n",
       "\n",
       "        AreaShape_CentralMoment_1_2  AreaShape_CentralMoment_1_3  ...  \\\n",
       "3                          0.446961                    -0.123880  ...   \n",
       "4                         -0.132573                    -0.652413  ...   \n",
       "10                         0.104052                    -2.730143  ...   \n",
       "11                        12.635548                     0.241961  ...   \n",
       "15                         0.339896                     0.142078  ...   \n",
       "...                             ...                          ...  ...   \n",
       "133689                    16.416950                   -22.023362  ...   \n",
       "133690                     0.201383                     5.506446  ...   \n",
       "133692                    36.512805                   -53.658306  ...   \n",
       "133694                    -8.058553                    -8.730158  ...   \n",
       "133699                    -1.235781                     6.434976  ...   \n",
       "\n",
       "        Texture_Variance_pRPS6_10_02_256  Texture_Variance_pRPS6_10_03_256  \\\n",
       "3                               5.942690                         10.222222   \n",
       "4                              -1.000000                         -1.000000   \n",
       "10                              4.389474                          4.786704   \n",
       "11                          18446.980661                      19461.035101   \n",
       "15                             -1.000000                         -1.000000   \n",
       "...                                  ...                               ...   \n",
       "133689                         12.184962                          6.061728   \n",
       "133690                          7.541238                          5.888889   \n",
       "133692                         77.533477                        131.542013   \n",
       "133694                          7.111158                         15.395556   \n",
       "133699                       1631.306382                       2161.077067   \n",
       "\n",
       "        Texture_Variance_pRPS6_3_00_256  Texture_Variance_pRPS6_3_01_256  \\\n",
       "3                              0.158974                        -0.328143   \n",
       "4                             -0.932131                        -0.833333   \n",
       "10                             0.027279                        -0.124523   \n",
       "11                          3626.915127                      3537.499415   \n",
       "15                            -1.000000                        -1.000000   \n",
       "...                                 ...                              ...   \n",
       "133689                         3.975561                         1.605148   \n",
       "133690                         1.084918                         0.473834   \n",
       "133692                        21.177543                        19.925170   \n",
       "133694                         1.306295                         1.296296   \n",
       "133699                       382.860939                       413.017736   \n",
       "\n",
       "        Texture_Variance_pRPS6_3_02_256  Texture_Variance_pRPS6_3_03_256  \\\n",
       "3                              0.001183                         0.222970   \n",
       "4                             -1.000000                        -0.879145   \n",
       "10                            -0.064451                         0.055670   \n",
       "11                          3286.435600                      4024.209271   \n",
       "15                            -1.000000                        -1.000000   \n",
       "...                                 ...                              ...   \n",
       "133689                         3.986986                         2.771573   \n",
       "133690                         0.346098                         0.654216   \n",
       "133692                        20.979412                        21.560949   \n",
       "133694                         1.116724                         1.680068   \n",
       "133699                       354.940907                       414.717679   \n",
       "\n",
       "        Texture_Variance_pRPS6_5_00_256  Texture_Variance_pRPS6_5_01_256  \\\n",
       "3                              0.872411                         0.027027   \n",
       "4                             -0.837834                        -0.864865   \n",
       "10                             0.416246                        -0.513514   \n",
       "11                          5032.558348                      6117.680955   \n",
       "15                            -1.000000                        -1.000000   \n",
       "...                                 ...                              ...   \n",
       "133689                         3.893472                         9.503257   \n",
       "133690                         0.596526                        -0.167746   \n",
       "133692                        12.750735                        20.811274   \n",
       "133694                         2.381452                         0.826514   \n",
       "133699                       578.504894                       643.391004   \n",
       "\n",
       "        Texture_Variance_pRPS6_5_02_256  Texture_Variance_pRPS6_5_03_256  \n",
       "3                              0.267502                         1.701679  \n",
       "4                             -0.846591                        -1.000000  \n",
       "10                             0.362280                         0.625173  \n",
       "11                          4420.082433                      5489.754308  \n",
       "15                            -1.000000                        -1.000000  \n",
       "...                                 ...                              ...  \n",
       "133689                         4.228182                         4.012818  \n",
       "133690                         2.317112                         0.850417  \n",
       "133692                        27.974162                        23.889670  \n",
       "133694                         1.125988                         2.162056  \n",
       "133699                       513.477389                       668.255622  \n",
       "\n",
       "[43874 rows x 2695 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cp_df_scaled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "34512588",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>intensity_mean-5</th>\n",
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       "      <td>-0.655967</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>intensity_mean-0</td>\n",
       "      <td>0.067428</td>\n",
       "      <td>A2</td>\n",
       "      <td>0.054958</td>\n",
       "      <td>0.815054</td>\n",
       "      <td>1.483194</td>\n",
       "      <td>0.793739</td>\n",
       "      <td>0.043299</td>\n",
       "      <td>PGGT1B</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000203</td>\n",
       "      <td>0.006315</td>\n",
       "      <td>0.000928</td>\n",
       "      <td>0.009323</td>\n",
       "      <td>10.795541</td>\n",
       "      <td>8.218206</td>\n",
       "      <td>13.875708</td>\n",
       "      <td>11.552190</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>intensity_mean-8</td>\n",
       "      <td>0.035084</td>\n",
       "      <td>D3</td>\n",
       "      <td>0.024482</td>\n",
       "      <td>0.697820</td>\n",
       "      <td>0.836939</td>\n",
       "      <td>1.319092</td>\n",
       "      <td>0.026690</td>\n",
       "      <td>PPP2R2B</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001660</td>\n",
       "      <td>0.000317</td>\n",
       "      <td>0.014562</td>\n",
       "      <td>0.009024</td>\n",
       "      <td>11.490246</td>\n",
       "      <td>10.536827</td>\n",
       "      <td>6.743976</td>\n",
       "      <td>19.614027</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>intensity_mean-3</td>\n",
       "      <td>0.261197</td>\n",
       "      <td>C12</td>\n",
       "      <td>0.179114</td>\n",
       "      <td>0.685744</td>\n",
       "      <td>0.780298</td>\n",
       "      <td>1.402972</td>\n",
       "      <td>0.108538</td>\n",
       "      <td>HSF1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004378</td>\n",
       "      <td>0.062781</td>\n",
       "      <td>0.061092</td>\n",
       "      <td>0.025526</td>\n",
       "      <td>12.307695</td>\n",
       "      <td>3.216018</td>\n",
       "      <td>10.193657</td>\n",
       "      <td>8.133395</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>intensity_mean-0</td>\n",
       "      <td>0.272067</td>\n",
       "      <td>A2</td>\n",
       "      <td>0.267507</td>\n",
       "      <td>0.983239</td>\n",
       "      <td>4.071811</td>\n",
       "      <td>0.117349</td>\n",
       "      <td>0.142667</td>\n",
       "      <td>PGGT1B</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002689</td>\n",
       "      <td>0.000070</td>\n",
       "      <td>0.001225</td>\n",
       "      <td>0.071709</td>\n",
       "      <td>9.866774</td>\n",
       "      <td>1.810647</td>\n",
       "      <td>7.693904</td>\n",
       "      <td>17.100174</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>133695</th>\n",
       "      <td>258</td>\n",
       "      <td>intensity_mean-13</td>\n",
       "      <td>0.022828</td>\n",
       "      <td>E4</td>\n",
       "      <td>0.019829</td>\n",
       "      <td>0.868626</td>\n",
       "      <td>1.888866</td>\n",
       "      <td>0.667654</td>\n",
       "      <td>0.014764</td>\n",
       "      <td>HRAS</td>\n",
       "      <td>...</td>\n",
       "      <td>0.003234</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>0.000670</td>\n",
       "      <td>0.002336</td>\n",
       "      <td>11.176550</td>\n",
       "      <td>12.540327</td>\n",
       "      <td>-4.482765</td>\n",
       "      <td>7.153024</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133696</th>\n",
       "      <td>259</td>\n",
       "      <td>intensity_mean-13</td>\n",
       "      <td>0.326837</td>\n",
       "      <td>E4</td>\n",
       "      <td>0.114697</td>\n",
       "      <td>0.350931</td>\n",
       "      <td>-0.614949</td>\n",
       "      <td>1.860739</td>\n",
       "      <td>0.119025</td>\n",
       "      <td>HRAS</td>\n",
       "      <td>...</td>\n",
       "      <td>0.032583</td>\n",
       "      <td>0.009312</td>\n",
       "      <td>0.031562</td>\n",
       "      <td>0.001021</td>\n",
       "      <td>11.251929</td>\n",
       "      <td>2.987429</td>\n",
       "      <td>10.204902</td>\n",
       "      <td>5.165628</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133697</th>\n",
       "      <td>260</td>\n",
       "      <td>intensity_mean-9</td>\n",
       "      <td>0.188926</td>\n",
       "      <td>D4</td>\n",
       "      <td>0.161259</td>\n",
       "      <td>0.853556</td>\n",
       "      <td>1.762765</td>\n",
       "      <td>0.616539</td>\n",
       "      <td>0.088308</td>\n",
       "      <td>FAN1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000056</td>\n",
       "      <td>0.003363</td>\n",
       "      <td>0.064340</td>\n",
       "      <td>0.027823</td>\n",
       "      <td>9.917559</td>\n",
       "      <td>4.129629</td>\n",
       "      <td>10.297348</td>\n",
       "      <td>1.767311</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133698</th>\n",
       "      <td>261</td>\n",
       "      <td>intensity_mean-19</td>\n",
       "      <td>0.003397</td>\n",
       "      <td>G8</td>\n",
       "      <td>0.002275</td>\n",
       "      <td>0.669709</td>\n",
       "      <td>0.706868</td>\n",
       "      <td>1.034844</td>\n",
       "      <td>0.021284</td>\n",
       "      <td>RAPGEF2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.005305</td>\n",
       "      <td>0.000244</td>\n",
       "      <td>0.010320</td>\n",
       "      <td>0.001827</td>\n",
       "      <td>10.905128</td>\n",
       "      <td>11.772167</td>\n",
       "      <td>8.326226</td>\n",
       "      <td>4.388920</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133699</th>\n",
       "      <td>262</td>\n",
       "      <td>intensity_mean-15</td>\n",
       "      <td>1.048392</td>\n",
       "      <td>E8</td>\n",
       "      <td>0.684923</td>\n",
       "      <td>0.653308</td>\n",
       "      <td>0.633613</td>\n",
       "      <td>1.344290</td>\n",
       "      <td>0.397249</td>\n",
       "      <td>WASL</td>\n",
       "      <td>...</td>\n",
       "      <td>0.141081</td>\n",
       "      <td>0.012467</td>\n",
       "      <td>0.004988</td>\n",
       "      <td>0.119821</td>\n",
       "      <td>6.712374</td>\n",
       "      <td>-2.731318</td>\n",
       "      <td>7.098932</td>\n",
       "      <td>3.543230</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>133700 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        label        Barcode_Idx       SUM Barcode       RAW         P  \\\n",
       "0           1   intensity_mean-0  0.057395      A2  0.038489  0.670602   \n",
       "1           2   intensity_mean-0  0.067428      A2  0.054958  0.815054   \n",
       "2           3   intensity_mean-8  0.035084      D3  0.024482  0.697820   \n",
       "3           4   intensity_mean-3  0.261197     C12  0.179114  0.685744   \n",
       "4           5   intensity_mean-0  0.272067      A2  0.267507  0.983239   \n",
       "...       ...                ...       ...     ...       ...       ...   \n",
       "133695    258  intensity_mean-13  0.022828      E4  0.019829  0.868626   \n",
       "133696    259  intensity_mean-13  0.326837      E4  0.114697  0.350931   \n",
       "133697    260   intensity_mean-9  0.188926      D4  0.161259  0.853556   \n",
       "133698    261  intensity_mean-19  0.003397      G8  0.002275  0.669709   \n",
       "133699    262  intensity_mean-15  1.048392      E8  0.684923  0.653308   \n",
       "\n",
       "           LOGIT   ENTROPY    X_NORM     Gene  ...  intensity_mean-4  \\\n",
       "0       0.710910  0.864662  0.035280   PGGT1B  ...          0.005333   \n",
       "1       1.483194  0.793739  0.043299   PGGT1B  ...          0.000203   \n",
       "2       0.836939  1.319092  0.026690  PPP2R2B  ...          0.001660   \n",
       "3       0.780298  1.402972  0.108538     HSF1  ...          0.004378   \n",
       "4       4.071811  0.117349  0.142667   PGGT1B  ...          0.002689   \n",
       "...          ...       ...       ...      ...  ...               ...   \n",
       "133695  1.888866  0.667654  0.014764     HRAS  ...          0.003234   \n",
       "133696 -0.614949  1.860739  0.119025     HRAS  ...          0.032583   \n",
       "133697  1.762765  0.616539  0.088308     FAN1  ...          0.000056   \n",
       "133698  0.706868  1.034844  0.021284  RAPGEF2  ...          0.005305   \n",
       "133699  0.633613  1.344290  0.397249     WASL  ...          0.141081   \n",
       "\n",
       "        intensity_mean-5  intensity_mean-6     Delta  embedding1  embedding2  \\\n",
       "0               0.000442          0.002411  0.007052    8.919654    8.924275   \n",
       "1               0.006315          0.000928  0.009323   10.795541    8.218206   \n",
       "2               0.000317          0.014562  0.009024   11.490246   10.536827   \n",
       "3               0.062781          0.061092  0.025526   12.307695    3.216018   \n",
       "4               0.000070          0.001225  0.071709    9.866774    1.810647   \n",
       "...                  ...               ...       ...         ...         ...   \n",
       "133695          0.000016          0.000670  0.002336   11.176550   12.540327   \n",
       "133696          0.009312          0.031562  0.001021   11.251929    2.987429   \n",
       "133697          0.003363          0.064340  0.027823    9.917559    4.129629   \n",
       "133698          0.000244          0.010320  0.001827   10.905128   11.772167   \n",
       "133699          0.012467          0.004988  0.119821    6.712374   -2.731318   \n",
       "\n",
       "         MP_UMAP1   MP_UMAP2  True_Label  InfectedCells  \n",
       "0        8.274383  -0.655967           0              0  \n",
       "1       13.875708  11.552190           0              0  \n",
       "2        6.743976  19.614027           0              0  \n",
       "3       10.193657   8.133395           0              1  \n",
       "4        7.693904  17.100174           0              1  \n",
       "...           ...        ...         ...            ...  \n",
       "133695  -4.482765   7.153024           0              0  \n",
       "133696  10.204902   5.165628           0              0  \n",
       "133697  10.297348   1.767311           0              0  \n",
       "133698   8.326226   4.388920           0              0  \n",
       "133699   7.098932   3.543230           0              1  \n",
       "\n",
       "[133700 rows x 28 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "soma_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "20c308da",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/bkang/mambaforge/envs/imlab/lib/python3.9/site-packages/pynndescent/pynndescent_.py:906: UserWarning: Failed to correctly find n_neighbors for some samples.Results may be less than ideal. Try re-running withdifferent parameters.\n",
      "  warn(\n",
      "/Users/bkang/mambaforge/envs/imlab/lib/python3.9/site-packages/umap/umap_.py:125: UserWarning: A few of your vertices were disconnected from the manifold.  This shouldn't cause problems.\n",
      "Disconnection_distance = inf has removed 6780 edges.\n",
      "It has only fully disconnected 452 vertices.\n",
      "Use umap.utils.disconnected_vertices() to identify them.\n",
      "  warn(\n",
      "/Users/bkang/mambaforge/envs/imlab/lib/python3.9/site-packages/sklearn/manifold/_spectral_embedding.py:259: UserWarning: Graph is not fully connected, spectral embedding may not work as expected.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(43874, 2)\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>label</th>\n",
       "      <th>Barcode_Idx</th>\n",
       "      <th>SUM</th>\n",
       "      <th>Barcode</th>\n",
       "      <th>RAW</th>\n",
       "      <th>P</th>\n",
       "      <th>LOGIT</th>\n",
       "      <th>ENTROPY</th>\n",
       "      <th>X_NORM</th>\n",
       "      <th>Gene</th>\n",
       "      <th>...</th>\n",
       "      <th>intensity_mean-6</th>\n",
       "      <th>Delta</th>\n",
       "      <th>embedding1</th>\n",
       "      <th>embedding2</th>\n",
       "      <th>MP_UMAP1</th>\n",
       "      <th>MP_UMAP2</th>\n",
       "      <th>True_Label</th>\n",
       "      <th>InfectedCells</th>\n",
       "      <th>CP_UMAP1</th>\n",
       "      <th>CP_UMAP2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>intensity_mean-3</td>\n",
       "      <td>0.261197</td>\n",
       "      <td>C12</td>\n",
       "      <td>0.179114</td>\n",
       "      <td>0.685744</td>\n",
       "      <td>0.780298</td>\n",
       "      <td>1.402972e+00</td>\n",
       "      <td>0.108538</td>\n",
       "      <td>HSF1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.061092</td>\n",
       "      <td>0.025526</td>\n",
       "      <td>12.307695</td>\n",
       "      <td>3.216018</td>\n",
       "      <td>10.193657</td>\n",
       "      <td>8.133395</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.534910</td>\n",
       "      <td>-2.940054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>intensity_mean-0</td>\n",
       "      <td>0.272067</td>\n",
       "      <td>A2</td>\n",
       "      <td>0.267507</td>\n",
       "      <td>0.983239</td>\n",
       "      <td>4.071811</td>\n",
       "      <td>1.173488e-01</td>\n",
       "      <td>0.142667</td>\n",
       "      <td>PGGT1B</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001225</td>\n",
       "      <td>0.071709</td>\n",
       "      <td>9.866774</td>\n",
       "      <td>1.810647</td>\n",
       "      <td>7.693904</td>\n",
       "      <td>17.100174</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>7.983154</td>\n",
       "      <td>11.489641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>intensity_mean-4</td>\n",
       "      <td>0.428435</td>\n",
       "      <td>C5</td>\n",
       "      <td>0.213025</td>\n",
       "      <td>0.497218</td>\n",
       "      <td>-0.011129</td>\n",
       "      <td>1.503244e+00</td>\n",
       "      <td>0.145746</td>\n",
       "      <td>MINK1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004269</td>\n",
       "      <td>0.015811</td>\n",
       "      <td>5.367204</td>\n",
       "      <td>2.011660</td>\n",
       "      <td>9.780452</td>\n",
       "      <td>6.342386</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>7.694165</td>\n",
       "      <td>3.226536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>intensity_mean-0</td>\n",
       "      <td>1.476978</td>\n",
       "      <td>A2</td>\n",
       "      <td>1.092524</td>\n",
       "      <td>0.739702</td>\n",
       "      <td>1.044421</td>\n",
       "      <td>1.213649e+00</td>\n",
       "      <td>0.642973</td>\n",
       "      <td>PGGT1B</td>\n",
       "      <td>...</td>\n",
       "      <td>0.003848</td>\n",
       "      <td>0.285212</td>\n",
       "      <td>8.681955</td>\n",
       "      <td>-3.529698</td>\n",
       "      <td>8.122533</td>\n",
       "      <td>15.945023</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2.668329</td>\n",
       "      <td>0.179814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>intensity_mean-4</td>\n",
       "      <td>0.755135</td>\n",
       "      <td>C5</td>\n",
       "      <td>0.379874</td>\n",
       "      <td>0.503054</td>\n",
       "      <td>0.012217</td>\n",
       "      <td>1.424048e+00</td>\n",
       "      <td>0.241768</td>\n",
       "      <td>MINK1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000799</td>\n",
       "      <td>0.020766</td>\n",
       "      <td>4.770312</td>\n",
       "      <td>-0.734490</td>\n",
       "      <td>12.128223</td>\n",
       "      <td>12.735119</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>16.930473</td>\n",
       "      <td>3.254287</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>133689</th>\n",
       "      <td>252</td>\n",
       "      <td>intensity_mean-13</td>\n",
       "      <td>1.276954</td>\n",
       "      <td>E4</td>\n",
       "      <td>0.820669</td>\n",
       "      <td>0.642677</td>\n",
       "      <td>0.587001</td>\n",
       "      <td>1.255923e+00</td>\n",
       "      <td>0.479026</td>\n",
       "      <td>HRAS</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013252</td>\n",
       "      <td>0.098225</td>\n",
       "      <td>9.327561</td>\n",
       "      <td>-3.860866</td>\n",
       "      <td>12.809038</td>\n",
       "      <td>11.113274</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5.638993</td>\n",
       "      <td>-3.129690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133690</th>\n",
       "      <td>253</td>\n",
       "      <td>intensity_mean-9</td>\n",
       "      <td>0.716750</td>\n",
       "      <td>D4</td>\n",
       "      <td>0.555203</td>\n",
       "      <td>0.774611</td>\n",
       "      <td>1.234535</td>\n",
       "      <td>9.392205e-01</td>\n",
       "      <td>0.290080</td>\n",
       "      <td>FAN1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.206146</td>\n",
       "      <td>0.117751</td>\n",
       "      <td>9.509022</td>\n",
       "      <td>-2.348243</td>\n",
       "      <td>9.146962</td>\n",
       "      <td>-5.891565</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>10.459499</td>\n",
       "      <td>5.039711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133692</th>\n",
       "      <td>255</td>\n",
       "      <td>intensity_mean-16</td>\n",
       "      <td>0.000165</td>\n",
       "      <td>F5</td>\n",
       "      <td>0.000165</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>25.827986</td>\n",
       "      <td>3.418140e-09</td>\n",
       "      <td>0.004447</td>\n",
       "      <td>ARPC3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001087</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>8.143990</td>\n",
       "      <td>16.397520</td>\n",
       "      <td>9.415496</td>\n",
       "      <td>-10.235467</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5.961916</td>\n",
       "      <td>1.199460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133694</th>\n",
       "      <td>257</td>\n",
       "      <td>intensity_mean-6</td>\n",
       "      <td>1.008588</td>\n",
       "      <td>D10</td>\n",
       "      <td>0.760528</td>\n",
       "      <td>0.754052</td>\n",
       "      <td>1.120341</td>\n",
       "      <td>1.006324e+00</td>\n",
       "      <td>0.537762</td>\n",
       "      <td>SNX8</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004826</td>\n",
       "      <td>0.230901</td>\n",
       "      <td>12.777261</td>\n",
       "      <td>-5.267233</td>\n",
       "      <td>10.556428</td>\n",
       "      <td>7.393644</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8.855773</td>\n",
       "      <td>3.397177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133699</th>\n",
       "      <td>262</td>\n",
       "      <td>intensity_mean-15</td>\n",
       "      <td>1.048392</td>\n",
       "      <td>E8</td>\n",
       "      <td>0.684923</td>\n",
       "      <td>0.653308</td>\n",
       "      <td>0.633613</td>\n",
       "      <td>1.344290e+00</td>\n",
       "      <td>0.397249</td>\n",
       "      <td>WASL</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004988</td>\n",
       "      <td>0.119821</td>\n",
       "      <td>6.712374</td>\n",
       "      <td>-2.731318</td>\n",
       "      <td>7.098932</td>\n",
       "      <td>3.543230</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2.194757</td>\n",
       "      <td>-0.485983</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>43874 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        label        Barcode_Idx       SUM Barcode       RAW         P  \\\n",
       "3           4   intensity_mean-3  0.261197     C12  0.179114  0.685744   \n",
       "4           5   intensity_mean-0  0.272067      A2  0.267507  0.983239   \n",
       "10         11   intensity_mean-4  0.428435      C5  0.213025  0.497218   \n",
       "11         12   intensity_mean-0  1.476978      A2  1.092524  0.739702   \n",
       "15         16   intensity_mean-4  0.755135      C5  0.379874  0.503054   \n",
       "...       ...                ...       ...     ...       ...       ...   \n",
       "133689    252  intensity_mean-13  1.276954      E4  0.820669  0.642677   \n",
       "133690    253   intensity_mean-9  0.716750      D4  0.555203  0.774611   \n",
       "133692    255  intensity_mean-16  0.000165      F5  0.000165  1.000000   \n",
       "133694    257   intensity_mean-6  1.008588     D10  0.760528  0.754052   \n",
       "133699    262  intensity_mean-15  1.048392      E8  0.684923  0.653308   \n",
       "\n",
       "            LOGIT       ENTROPY    X_NORM    Gene  ...  intensity_mean-6  \\\n",
       "3        0.780298  1.402972e+00  0.108538    HSF1  ...          0.061092   \n",
       "4        4.071811  1.173488e-01  0.142667  PGGT1B  ...          0.001225   \n",
       "10      -0.011129  1.503244e+00  0.145746   MINK1  ...          0.004269   \n",
       "11       1.044421  1.213649e+00  0.642973  PGGT1B  ...          0.003848   \n",
       "15       0.012217  1.424048e+00  0.241768   MINK1  ...          0.000799   \n",
       "...           ...           ...       ...     ...  ...               ...   \n",
       "133689   0.587001  1.255923e+00  0.479026    HRAS  ...          0.013252   \n",
       "133690   1.234535  9.392205e-01  0.290080    FAN1  ...          0.206146   \n",
       "133692  25.827986  3.418140e-09  0.004447   ARPC3  ...          0.001087   \n",
       "133694   1.120341  1.006324e+00  0.537762    SNX8  ...          0.004826   \n",
       "133699   0.633613  1.344290e+00  0.397249    WASL  ...          0.004988   \n",
       "\n",
       "           Delta  embedding1  embedding2   MP_UMAP1   MP_UMAP2  True_Label  \\\n",
       "3       0.025526   12.307695    3.216018  10.193657   8.133395           0   \n",
       "4       0.071709    9.866774    1.810647   7.693904  17.100174           0   \n",
       "10      0.015811    5.367204    2.011660   9.780452   6.342386           0   \n",
       "11      0.285212    8.681955   -3.529698   8.122533  15.945023           0   \n",
       "15      0.020766    4.770312   -0.734490  12.128223  12.735119           0   \n",
       "...          ...         ...         ...        ...        ...         ...   \n",
       "133689  0.098225    9.327561   -3.860866  12.809038  11.113274           0   \n",
       "133690  0.117751    9.509022   -2.348243   9.146962  -5.891565           0   \n",
       "133692  0.000343    8.143990   16.397520   9.415496 -10.235467           0   \n",
       "133694  0.230901   12.777261   -5.267233  10.556428   7.393644           0   \n",
       "133699  0.119821    6.712374   -2.731318   7.098932   3.543230           0   \n",
       "\n",
       "        InfectedCells   CP_UMAP1   CP_UMAP2  \n",
       "3                   1   4.534910  -2.940054  \n",
       "4                   1   7.983154  11.489641  \n",
       "10                  1   7.694165   3.226536  \n",
       "11                  1   2.668329   0.179814  \n",
       "15                  1  16.930473   3.254287  \n",
       "...               ...        ...        ...  \n",
       "133689              1   5.638993  -3.129690  \n",
       "133690              1  10.459499   5.039711  \n",
       "133692              1   5.961916   1.199460  \n",
       "133694              1   8.855773   3.397177  \n",
       "133699              1   2.194757  -0.485983  \n",
       "\n",
       "[43874 rows x 30 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# visualize on UMAP\n",
    "# can we use cell profiler features to predict barcoded vs unbarcoded vs nuclear localized?\n",
    "# can we use area_shape features to filter weird segmented cells?\n",
    "reducer = umap.UMAP(low_memory=True)\n",
    "eps=1e-10\n",
    "\n",
    "cp_embedding = reducer.fit_transform(cp_df_scaled.values)\n",
    "print(cp_embedding.shape)\n",
    "\n",
    "soma_df.loc[idx,['CP_UMAP1','CP_UMAP2']] = cp_embedding\n",
    "soma_df.loc[idx,:]\n",
    "# append embedding to epitope_df and debarcoded_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b56f9d0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ImageNumber                                                                        1\n",
       "ObjectNumber                                                                       4\n",
       "FileName_max_clean                                                F000_max_clean.tif\n",
       "PathName_max_clean                 /mnt/disks/store/101222_D10_Coverslip1_Process...\n",
       "AreaShape_Area                                                                   271\n",
       "                                                         ...                        \n",
       "Texture_Variance_pRPS6_3_03_256                                             1.897377\n",
       "Texture_Variance_pRPS6_5_00_256                                             2.164931\n",
       "Texture_Variance_pRPS6_5_01_256                                             1.055556\n",
       "Texture_Variance_pRPS6_5_02_256                                             1.549169\n",
       "Texture_Variance_pRPS6_5_03_256                                             2.845556\n",
       "Name: 3, Length: 3785, dtype: object"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cp_df.loc[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "c21ee292",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2deff35b0>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot UMAP of 5 images - embedding based on epitope signals\n",
    "fit, ax = plt.subplots(figsize=(10,10))\n",
    "ax.scatter(soma_df.loc[idx, 'CP_UMAP1'], soma_df.loc[idx, 'CP_UMAP2'], c = soma_df.loc[idx,'Overlap_0.3'], s =0.1,\n",
    "          vmin = 0.25, vmax = 0.75)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "f690513c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2b6631520>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot UMAP of 5 images - embedding based on epitope signals\n",
    "fit, ax = plt.subplots(figsize=(10,10))\n",
    "sns.scatterplot(data = soma_df.loc[idx], x='CP_UMAP1', y='CP_UMAP2', hue = 'Gene', ax=ax, s=0.3)\n",
    "ax.legend(bbox_to_anchor=(1.02, 1), loc='upper left', borderaxespad=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "95361b68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>label</th>\n",
       "      <th>Barcode_Idx</th>\n",
       "      <th>SUM</th>\n",
       "      <th>Barcode</th>\n",
       "      <th>RAW</th>\n",
       "      <th>P</th>\n",
       "      <th>LOGIT</th>\n",
       "      <th>ENTROPY</th>\n",
       "      <th>X_NORM</th>\n",
       "      <th>Gene</th>\n",
       "      <th>...</th>\n",
       "      <th>intensity_mean-6</th>\n",
       "      <th>Delta</th>\n",
       "      <th>embedding1</th>\n",
       "      <th>embedding2</th>\n",
       "      <th>MP_UMAP1</th>\n",
       "      <th>MP_UMAP2</th>\n",
       "      <th>True_Label</th>\n",
       "      <th>InfectedCells</th>\n",
       "      <th>CP_UMAP1</th>\n",
       "      <th>CP_UMAP2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>intensity_mean-0</td>\n",
       "      <td>0.272067</td>\n",
       "      <td>A2</td>\n",
       "      <td>0.267507</td>\n",
       "      <td>0.983239</td>\n",
       "      <td>4.071811</td>\n",
       "      <td>0.117349</td>\n",
       "      <td>0.142667</td>\n",
       "      <td>PGGT1B</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001225</td>\n",
       "      <td>0.071709</td>\n",
       "      <td>9.866774</td>\n",
       "      <td>1.810647</td>\n",
       "      <td>7.693904</td>\n",
       "      <td>17.100174</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>7.983154</td>\n",
       "      <td>11.489641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>intensity_mean-8</td>\n",
       "      <td>0.943130</td>\n",
       "      <td>D3</td>\n",
       "      <td>0.379075</td>\n",
       "      <td>0.401933</td>\n",
       "      <td>-0.397417</td>\n",
       "      <td>1.864187</td>\n",
       "      <td>0.286501</td>\n",
       "      <td>PPP2R2B</td>\n",
       "      <td>...</td>\n",
       "      <td>0.115662</td>\n",
       "      <td>0.055923</td>\n",
       "      <td>10.645579</td>\n",
       "      <td>-1.918137</td>\n",
       "      <td>7.798701</td>\n",
       "      <td>3.837843</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.127891</td>\n",
       "      <td>11.547745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>intensity_mean-10</td>\n",
       "      <td>0.451353</td>\n",
       "      <td>D7</td>\n",
       "      <td>0.328098</td>\n",
       "      <td>0.726922</td>\n",
       "      <td>0.979060</td>\n",
       "      <td>1.103500</td>\n",
       "      <td>0.224976</td>\n",
       "      <td>MLH1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.098781</td>\n",
       "      <td>0.071155</td>\n",
       "      <td>8.591884</td>\n",
       "      <td>-0.035811</td>\n",
       "      <td>8.579045</td>\n",
       "      <td>0.181531</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5.476256</td>\n",
       "      <td>11.735186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>intensity_mean-10</td>\n",
       "      <td>1.062280</td>\n",
       "      <td>D7</td>\n",
       "      <td>0.929367</td>\n",
       "      <td>0.874879</td>\n",
       "      <td>1.944809</td>\n",
       "      <td>0.644386</td>\n",
       "      <td>0.521139</td>\n",
       "      <td>MLH1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.281408</td>\n",
       "      <td>0.279432</td>\n",
       "      <td>8.082046</td>\n",
       "      <td>-5.039211</td>\n",
       "      <td>5.964539</td>\n",
       "      <td>14.997520</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5.755919</td>\n",
       "      <td>10.891780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>51</td>\n",
       "      <td>intensity_mean-4</td>\n",
       "      <td>0.463109</td>\n",
       "      <td>C5</td>\n",
       "      <td>0.222259</td>\n",
       "      <td>0.479928</td>\n",
       "      <td>-0.080332</td>\n",
       "      <td>1.609850</td>\n",
       "      <td>0.150446</td>\n",
       "      <td>MINK1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001262</td>\n",
       "      <td>0.013526</td>\n",
       "      <td>5.401435</td>\n",
       "      <td>2.040115</td>\n",
       "      <td>12.822702</td>\n",
       "      <td>13.032553</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5.048604</td>\n",
       "      <td>12.797222</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>133646</th>\n",
       "      <td>209</td>\n",
       "      <td>intensity_mean-8</td>\n",
       "      <td>0.494758</td>\n",
       "      <td>D3</td>\n",
       "      <td>0.408015</td>\n",
       "      <td>0.824675</td>\n",
       "      <td>1.548349</td>\n",
       "      <td>0.824093</td>\n",
       "      <td>0.216177</td>\n",
       "      <td>PPP2R2B</td>\n",
       "      <td>...</td>\n",
       "      <td>0.140794</td>\n",
       "      <td>0.087338</td>\n",
       "      <td>10.724383</td>\n",
       "      <td>-0.760938</td>\n",
       "      <td>9.895672</td>\n",
       "      <td>8.303822</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6.286984</td>\n",
       "      <td>13.631008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133649</th>\n",
       "      <td>212</td>\n",
       "      <td>intensity_mean-6</td>\n",
       "      <td>0.301000</td>\n",
       "      <td>D10</td>\n",
       "      <td>0.249599</td>\n",
       "      <td>0.829231</td>\n",
       "      <td>1.580190</td>\n",
       "      <td>0.783282</td>\n",
       "      <td>0.144134</td>\n",
       "      <td>SNX8</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001348</td>\n",
       "      <td>0.068186</td>\n",
       "      <td>13.391723</td>\n",
       "      <td>1.047378</td>\n",
       "      <td>11.833408</td>\n",
       "      <td>-2.446669</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.065629</td>\n",
       "      <td>11.866267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133656</th>\n",
       "      <td>219</td>\n",
       "      <td>intensity_mean-19</td>\n",
       "      <td>0.317002</td>\n",
       "      <td>G8</td>\n",
       "      <td>0.192399</td>\n",
       "      <td>0.606933</td>\n",
       "      <td>0.434438</td>\n",
       "      <td>1.319244</td>\n",
       "      <td>0.115749</td>\n",
       "      <td>RAPGEF2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.052531</td>\n",
       "      <td>0.018027</td>\n",
       "      <td>11.344922</td>\n",
       "      <td>2.962856</td>\n",
       "      <td>5.101139</td>\n",
       "      <td>-1.933240</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.460780</td>\n",
       "      <td>13.734506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133667</th>\n",
       "      <td>230</td>\n",
       "      <td>intensity_mean-9</td>\n",
       "      <td>0.485306</td>\n",
       "      <td>D4</td>\n",
       "      <td>0.406308</td>\n",
       "      <td>0.837221</td>\n",
       "      <td>1.637693</td>\n",
       "      <td>0.703001</td>\n",
       "      <td>0.214083</td>\n",
       "      <td>FAN1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.161905</td>\n",
       "      <td>0.069524</td>\n",
       "      <td>9.383019</td>\n",
       "      <td>-0.929570</td>\n",
       "      <td>7.190091</td>\n",
       "      <td>-6.467484</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6.040066</td>\n",
       "      <td>15.093230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133670</th>\n",
       "      <td>233</td>\n",
       "      <td>intensity_mean-11</td>\n",
       "      <td>0.070902</td>\n",
       "      <td>D8</td>\n",
       "      <td>0.065909</td>\n",
       "      <td>0.929572</td>\n",
       "      <td>2.580137</td>\n",
       "      <td>0.324526</td>\n",
       "      <td>0.053632</td>\n",
       "      <td>MSH3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001980</td>\n",
       "      <td>0.013021</td>\n",
       "      <td>12.757407</td>\n",
       "      <td>6.884749</td>\n",
       "      <td>10.549284</td>\n",
       "      <td>8.020126</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6.525777</td>\n",
       "      <td>13.900450</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16514 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        label        Barcode_Idx       SUM Barcode       RAW         P  \\\n",
       "4           5   intensity_mean-0  0.272067      A2  0.267507  0.983239   \n",
       "20         21   intensity_mean-8  0.943130      D3  0.379075  0.401933   \n",
       "27         28  intensity_mean-10  0.451353      D7  0.328098  0.726922   \n",
       "30         31  intensity_mean-10  1.062280      D7  0.929367  0.874879   \n",
       "50         51   intensity_mean-4  0.463109      C5  0.222259  0.479928   \n",
       "...       ...                ...       ...     ...       ...       ...   \n",
       "133646    209   intensity_mean-8  0.494758      D3  0.408015  0.824675   \n",
       "133649    212   intensity_mean-6  0.301000     D10  0.249599  0.829231   \n",
       "133656    219  intensity_mean-19  0.317002      G8  0.192399  0.606933   \n",
       "133667    230   intensity_mean-9  0.485306      D4  0.406308  0.837221   \n",
       "133670    233  intensity_mean-11  0.070902      D8  0.065909  0.929572   \n",
       "\n",
       "           LOGIT   ENTROPY    X_NORM     Gene  ...  intensity_mean-6  \\\n",
       "4       4.071811  0.117349  0.142667   PGGT1B  ...          0.001225   \n",
       "20     -0.397417  1.864187  0.286501  PPP2R2B  ...          0.115662   \n",
       "27      0.979060  1.103500  0.224976     MLH1  ...          0.098781   \n",
       "30      1.944809  0.644386  0.521139     MLH1  ...          0.281408   \n",
       "50     -0.080332  1.609850  0.150446    MINK1  ...          0.001262   \n",
       "...          ...       ...       ...      ...  ...               ...   \n",
       "133646  1.548349  0.824093  0.216177  PPP2R2B  ...          0.140794   \n",
       "133649  1.580190  0.783282  0.144134     SNX8  ...          0.001348   \n",
       "133656  0.434438  1.319244  0.115749  RAPGEF2  ...          0.052531   \n",
       "133667  1.637693  0.703001  0.214083     FAN1  ...          0.161905   \n",
       "133670  2.580137  0.324526  0.053632     MSH3  ...          0.001980   \n",
       "\n",
       "           Delta  embedding1  embedding2   MP_UMAP1   MP_UMAP2  True_Label  \\\n",
       "4       0.071709    9.866774    1.810647   7.693904  17.100174           0   \n",
       "20      0.055923   10.645579   -1.918137   7.798701   3.837843           0   \n",
       "27      0.071155    8.591884   -0.035811   8.579045   0.181531           0   \n",
       "30      0.279432    8.082046   -5.039211   5.964539  14.997520           0   \n",
       "50      0.013526    5.401435    2.040115  12.822702  13.032553           0   \n",
       "...          ...         ...         ...        ...        ...         ...   \n",
       "133646  0.087338   10.724383   -0.760938   9.895672   8.303822           0   \n",
       "133649  0.068186   13.391723    1.047378  11.833408  -2.446669           0   \n",
       "133656  0.018027   11.344922    2.962856   5.101139  -1.933240           0   \n",
       "133667  0.069524    9.383019   -0.929570   7.190091  -6.467484           0   \n",
       "133670  0.013021   12.757407    6.884749  10.549284   8.020126           0   \n",
       "\n",
       "        InfectedCells  CP_UMAP1   CP_UMAP2  \n",
       "4                   1  7.983154  11.489641  \n",
       "20                  1  9.127891  11.547745  \n",
       "27                  1  5.476256  11.735186  \n",
       "30                  1  5.755919  10.891780  \n",
       "50                  1  5.048604  12.797222  \n",
       "...               ...       ...        ...  \n",
       "133646              1  6.286984  13.631008  \n",
       "133649              1  9.065629  11.866267  \n",
       "133656              1  4.460780  13.734506  \n",
       "133667              1  6.040066  15.093230  \n",
       "133670              1  6.525777  13.900450  \n",
       "\n",
       "[16514 rows x 30 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "07505711",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2f75d4e20>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot UMAP of 5 images - embedding based on epitope signals\n",
    "fit, ax = plt.subplots(figsize=(10,10))\n",
    "df = soma_df.loc[idx].copy()\n",
    "#df = df[(df.Gene != 'NCK1')&(df.Gene != 'SNX8')]\n",
    "df = df[(df.CP_UMAP1 > 1.5)&(df.CP_UMAP1<10)&(df.CP_UMAP2<16)&(df.CP_UMAP2>6)]\n",
    "sns.scatterplot(data = df, x='CP_UMAP1', y='CP_UMAP2', hue = 'Gene', ax=ax, s=1)\n",
    "ax.legend(bbox_to_anchor=(1.02, 1), loc='upper left', borderaxespad=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79022b0c",
   "metadata": {},
   "source": [
    "## PCA?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "77e288f6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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