melina.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import loompy\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt \n",
    "import seaborn as sns\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p>31053 rows, 292495 columns, 5 layers<br/>(showing up to 10x10)<br/>dev_all.loom<br/>name: <em>20210503T184438.399646Z</em><br/><table><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age</strong></td><td>e7.0</td><td>e7.0</td><td>e7.0</td><td>e7.0</td><td>e7.0</td><td>e7.0</td><td>e7.0</td><td>e7.0</td><td>e8.0</td><td>e7.0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>BTSNE</strong></td><td>[-31.85552615 -61.93306125]</td><td>[ -2.87413797 -57.27298664]</td><td>[ -2.77695001 -56.40269395]</td><td>[-27.60967517 -38.25846626]</td><td>[ -9.55072307 -39.07598744]</td><td>[-32.11604733 -62.34137016]</td><td>[-30.93707251 -57.51320106]</td><td>[ -3.34237798 -56.85237163]</td><td>[-56.05262281 -29.958472  ]</td><td>[ -2.96161651 -57.16943392]</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>CellCycle</strong></td><td>0.0045682960255824575</td><td>0.01088139281828074</td><td>0.011940902651285164</td><td>0.010640900195694716</td><td>0.009254807692307692</td><td>0.008029569207239358</td><td>0.009945962878847208</td><td>0.008352823254259938</td><td>0.009412528399870172</td><td>0.008047585724282717</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>CellID</strong></td><td>10X39_2_A_1:AAACTTGAGAGCAGx</td><td>10X39_3_A_1:AAGTTCCTAGCCTAx</td><td>10X39_2_A_1:GGGACCACAGCGTTx</td><td>10X39_2_A_1:CAGCAATGGGTAGGx</td><td>10X39_3_A_1:CAGCCTACAGAGATx</td><td>10X39_3_A_1:TGATACCTAGGGTGx</td><td>10X39_2_A_1:TGAAATTGTGTCCCx</td><td>10X39_3_A_1:TAGAATACCTACGAx</td><td>10X21_2_A_1:AAAGTTTGACTGTGx</td><td>10X39_2_A_1:TGGAGACTAACTGCx</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Cell_Conc</strong></td><td>500</td><td>500</td><td>500</td><td>500</td><td>500</td><td>500</td><td>500</td><td>500</td><td>600</td><td>500</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Chemistry</strong></td><td>v2</td><td>v2</td><td>v2</td><td>v2</td><td>v2</td><td>v2</td><td>v2</td><td>v2</td><td>v2</td><td>v2</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>ChipID</strong></td><td>10X39</td><td>10X39</td><td>10X39</td><td>10X39</td><td>10X39</td><td>10X39</td><td>10X39</td><td>10X39</td><td>10X21</td><td>10X39</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Class</strong></td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>ClusterName</strong></td><td>ParEndo</td><td>ParEndo</td><td>ParEndo</td><td>ParEndo</td><td>ParEndo</td><td>ParEndo</td><td>ParEndo</td><td>ParEndo</td><td>ParEndo</td><td>ParEndo</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Clusters</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Date_Captured</strong></td><td>2016-09-30</td><td>2016-09-30</td><td>2016-09-30</td><td>2016-09-30</td><td>2016-09-30</td><td>2016-09-30</td><td>2016-09-30</td><td>2016-09-30</td><td>2016-09-09</td><td>2016-09-30</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>DonorID</strong></td><td>Batch09F-1/2</td><td>Batch09F-1/2</td><td>Batch09F-1/2</td><td>Batch09F-1/2</td><td>Batch09F-1/2</td><td>Batch09F-1/2</td><td>Batch09F-1/2</td><td>Batch09F-1/2</td><td>Batch03C-0</td><td>Batch09F-1/2</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>DoubletFinderPCA</strong></td><td>0.0</td><td>0.0</td><td>0.034482758620689655</td><td>0.034482758620689655</td><td>0.14285714285714285</td><td>0.18181818181818182</td><td>0.034482758620689655</td><td>0.0</td><td>0.06818181818181818</td><td>0.034482758620689655</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>HPF</strong></td><td>[0.00111483 0.00120836 0.00122097 0.00113805 0.00127379 0.00128903\n",
       " 0.00142434 0.00137882 0.00087503 0.00133263 0.00088407 0.04747298\n",
       " 0.00149719 0.00129356 0.000934   0.00127298 0.00091146 0.0016324\n",
       " 0.00135461 0.10695366 0.00134678 0.00112689 0.0012642  0.00076447\n",
       " 0.00161696 0.00079896 0.00139222 0.01524913 0.00152742 0.00108777\n",
       " 0.00173508 0.00093015 0.0015311  0.00098087 0.00146454 0.00110193\n",
       " 0.00128852 0.00085946 0.00089745 0.00091167 0.00119738 0.00157064\n",
       " 0.00131231 0.00110347 0.00109871 0.00189334 0.00167557 0.00214199\n",
       " 0.00113332 0.00118355 0.00186117 0.04157492 0.00212376 0.00142247\n",
       " 0.06977176 0.00109681 0.00217537 0.00114835 0.00105067 0.00148607\n",
       " 0.00236649 0.48076784 0.00180206 0.00287679 0.00118587 0.00136267\n",
       " 0.00139733 0.00230283 0.00152214 0.00193257 0.0014856  0.00144611\n",
       " 0.00179661 0.00200787 0.00217882 0.00330986 0.00218376 0.00202658\n",
       " 0.0030454  0.00584168 0.00208811 0.00399843 0.00379333 0.00548665\n",
       " 0.00382851 0.00483274 0.00529124 0.00622962 0.01041493 0.01020526\n",
       " 0.0121174  0.01073397 0.01088641 0.01059874 0.01174333 0.01255251]</td><td>[0.00099792 0.00108255 0.00109382 0.00101889 0.00114164 0.00115544\n",
       " 0.00127809 0.00123674 0.00117274 0.00119491 0.00084593 0.36470193\n",
       " 0.00134404 0.00115945 0.00085962 0.00114089 0.00082102 0.00146319\n",
       " 0.00121485 0.07480544 0.00120771 0.05693718 0.00158479 0.00097579\n",
       " 0.00145311 0.00071837 0.00130051 0.00153112 0.00137155 0.00097109\n",
       " 0.00156053 0.00095166 0.00137553 0.00088851 0.00131457 0.00103885\n",
       " 0.00116712 0.00172663 0.00085474 0.00081951 0.00111721 0.00155187\n",
       " 0.00127134 0.00159109 0.00691294 0.00170526 0.00150681 0.00192345\n",
       " 0.00103031 0.00107855 0.00167561 0.00722829 0.00191587 0.01436738\n",
       " 0.06863245 0.0009947  0.00196355 0.00129261 0.00122689 0.00133896\n",
       " 0.00213904 0.15472329 0.00166741 0.00257425 0.0011439  0.00216493\n",
       " 0.00131408 0.00207844 0.00164588 0.00171258 0.00138036 0.00160452\n",
       " 0.00162229 0.00214089 0.00621649 0.00301383 0.00304668 0.02065765\n",
       " 0.00276768 0.00536492 0.0022569  0.00380584 0.00344956 0.00508377\n",
       " 0.0034987  0.00439017 0.00490514 0.00705777 0.0100655  0.00983439\n",
       " 0.01185499 0.01039379 0.01056919 0.01023478 0.0114706  0.01234667]</td><td>[0.00057138 0.00062152 0.00062825 0.00058378 0.00065674 0.00066498\n",
       " 0.00073847 0.00071363 0.00047154 0.00068859 0.00043898 0.32233865\n",
       " 0.00077838 0.00066734 0.00053299 0.00065625 0.0005113  0.00085174\n",
       " 0.00070051 0.10100822 0.00069543 0.04897423 0.00066068 0.0004008\n",
       " 0.00084453 0.00040463 0.00072992 0.00089907 0.00079496 0.00054324\n",
       " 0.00091005 0.00050727 0.00079593 0.00207682 0.00076052 0.00057154\n",
       " 0.00068075 0.00053073 0.00046745 0.00046677 0.00342298 0.0037528\n",
       " 0.00066875 0.00057252 0.00070664 0.00099938 0.00087694 0.00113836\n",
       " 0.0005855  0.00061404 0.00098114 0.06827034 0.00113069 0.00074695\n",
       " 0.04983264 0.00056393 0.0011605  0.00060886 0.00054466 0.00078391\n",
       " 0.00127067 0.05330011 0.00096893 0.00156177 0.00061    0.00080532\n",
       " 0.00132913 0.00123296 0.00081954 0.00100039 0.00077466 0.00076727\n",
       " 0.00089178 0.00107717 0.1592027  0.00184185 0.03427512 0.00115449\n",
       " 0.00168171 0.00509513 0.00114383 0.00238457 0.00214734 0.00335851\n",
       " 0.00218138 0.0030034  0.00321722 0.00401012 0.00815379 0.00786267\n",
       " 0.01049666 0.00857606 0.00872545 0.00839963 0.0099669  0.0112117 ]</td><td>[3.63703884e-04 3.96710409e-04 4.00608917e-04 3.71753836e-04\n",
       " 4.19154600e-04 4.24523712e-04 4.73110228e-04 4.56319944e-04\n",
       " 2.77099384e-04 4.39923230e-04 2.84315789e-04 1.97467340e-01\n",
       " 4.99618189e-04 4.26119090e-04 2.97442663e-04 4.19156081e-04\n",
       " 2.94092824e-04 5.48593052e-04 4.47753637e-04 6.76856530e-02\n",
       " 4.45806205e-04 4.50154342e-02 1.31984352e-03 2.45473241e-04\n",
       " 5.42208796e-04 2.56483794e-04 4.88795600e-04 7.39131382e-03\n",
       " 5.09597599e-04 4.23759000e-04 5.85529893e-04 2.92244111e-04\n",
       " 5.11269212e-04 3.18303146e-04 4.86992477e-04 3.69799642e-04\n",
       " 4.52376775e-04 2.88933907e-04 3.01575252e-04 2.95351956e-04\n",
       " 5.69972237e-02 5.47808155e-04 4.22761122e-04 3.96976239e-04\n",
       " 4.00338900e-04 6.44788607e-04 5.64167285e-04 7.40570395e-04\n",
       " 3.73568915e-04 3.90209325e-04 6.32750676e-04 9.23710068e-02\n",
       " 7.32585463e-04 4.78408579e-04 2.98471046e-01 3.50582984e-04\n",
       " 7.52770950e-04 3.72697463e-04 3.39758822e-04 4.96494474e-04\n",
       " 8.31381992e-04 1.03614600e-01 7.53518761e-04 1.03665589e-03\n",
       " 3.84486363e-04 4.50474592e-04 4.52712698e-04 8.01434271e-04\n",
       " 5.15510456e-04 6.52817920e-04 5.18840340e-04 4.84935601e-04\n",
       " 5.59801719e-04 6.90221908e-04 1.46440993e-02 1.22069069e-03\n",
       " 9.30646915e-04 7.30595553e-04 1.10906449e-03 7.05350456e-04\n",
       " 7.15898495e-04 1.54415686e-03 1.44450687e-03 2.34330666e-03\n",
       " 1.46203460e-03 1.93903796e-03 2.23066204e-03 3.29766514e-03\n",
       " 6.78640072e-03 6.47169820e-03 9.71943801e-03 7.29758347e-03\n",
       " 7.46130724e-03 7.09824683e-03 8.99235141e-03 1.06972658e-02]</td><td>[3.18405104e-04 3.47222963e-04 3.50874772e-04 3.25487033e-04\n",
       " 3.67200461e-04 3.71929301e-04 4.14519515e-04 3.99960651e-04\n",
       " 2.48215754e-04 3.85497463e-04 2.50920174e-04 2.33884118e-01\n",
       " 4.37566461e-04 3.73375855e-04 2.62859303e-04 3.67043610e-04\n",
       " 2.68649839e-04 4.81367977e-04 3.92377942e-04 1.64697569e-01\n",
       " 3.91624116e-04 2.86740161e-01 1.01470075e-02 1.74880212e-03\n",
       " 4.75734079e-04 2.29763028e-04 4.23299767e-04 2.54896141e-03\n",
       " 4.46985699e-04 3.15177651e-04 5.14125026e-04 2.65015473e-04\n",
       " 4.49653866e-04 3.39810882e-04 4.26982366e-04 3.38148159e-04\n",
       " 4.78858074e-04 2.41473256e-03 2.66790318e-04 2.63027768e-04\n",
       " 1.08031072e-02 5.00549486e-04 3.84659224e-04 3.21574070e-04\n",
       " 3.20935876e-04 5.66457160e-04 4.95508130e-04 6.51434949e-04\n",
       " 3.33383787e-04 3.40819948e-04 5.55775969e-04 4.30511728e-02\n",
       " 6.44310279e-04 4.53519851e-04 4.22559894e-02 3.40567017e-04\n",
       " 6.62246975e-04 4.11530731e-04 3.21989751e-04 6.45003597e-04\n",
       " 7.34422656e-04 7.59043878e-02 1.25748327e-03 9.15861845e-04\n",
       " 3.47265208e-04 3.94190393e-04 4.10270703e-04 7.05475702e-04\n",
       " 4.56361210e-04 5.75124263e-04 4.50134098e-04 4.36989711e-04\n",
       " 2.85060019e-03 6.20166220e-04 5.81165847e-03 1.08125817e-03\n",
       " 3.99504943e-03 6.11039162e-04 9.79995948e-04 3.81318986e-03\n",
       " 6.34063873e-04 1.51516960e-03 1.28828806e-03 2.10322326e-03\n",
       " 1.29788912e-03 4.98577841e-03 1.99881477e-03 2.81949889e-03\n",
       " 6.46021015e-03 6.15878833e-03 9.64107079e-03 6.97346754e-03\n",
       " 7.20887804e-03 6.77875807e-03 8.80882664e-03 1.07459918e-02]</td><td>[3.58865477e-04 3.91002163e-04 3.95285282e-04 3.66859364e-04\n",
       " 4.13580894e-04 4.18883102e-04 4.66211116e-04 4.50381611e-04\n",
       " 4.19635374e-03 4.34090240e-04 2.77126998e-04 7.85258033e-02\n",
       " 4.92547219e-04 4.20685408e-04 3.20203624e-04 4.13466307e-04\n",
       " 2.96370455e-04 5.38917941e-04 4.41884590e-04 4.23920557e-02\n",
       " 4.38188310e-04 3.80766552e-02 3.89670500e-04 2.53942164e-04\n",
       " 5.35076464e-04 2.55521996e-04 4.63484365e-04 2.64288421e-02\n",
       " 5.03023063e-04 3.39184369e-04 5.78367661e-04 3.79386996e-04\n",
       " 5.03619299e-04 9.96884486e-04 4.80557508e-04 3.53732438e-04\n",
       " 4.32841034e-04 2.75004030e-04 2.90150425e-04 2.97252284e-04\n",
       " 4.76829616e-04 5.24454769e-04 4.28144583e-04 3.58551067e-04\n",
       " 3.66712659e-04 6.36362876e-04 5.56368289e-04 7.24708584e-04\n",
       " 3.71148352e-04 3.81483006e-04 6.24571655e-04 7.22170030e-02\n",
       " 7.23146378e-04 5.37726876e-04 1.48395426e-01 3.61909016e-04\n",
       " 7.43149377e-04 3.74278898e-04 3.36638739e-04 4.94048429e-04\n",
       " 8.14940277e-04 4.34123404e-01 3.53560979e-02 1.00925925e-03\n",
       " 3.97974502e-04 4.29746280e-04 5.06316051e-04 7.91146545e-04\n",
       " 5.08723556e-04 6.43987101e-04 4.90160950e-04 4.78799228e-04\n",
       " 5.71287197e-04 6.84462717e-04 7.52846584e-04 1.20756000e-03\n",
       " 7.37016594e-04 6.70100167e-04 1.09490873e-03 6.44598906e-03\n",
       " 7.06669627e-04 1.50423674e-03 1.41016664e-03 2.31604429e-03\n",
       " 1.44429619e-03 1.88254438e-03 2.21116783e-03 3.01191838e-03\n",
       " 6.72650182e-03 6.41154868e-03 9.61375342e-03 7.21798222e-03\n",
       " 7.34310899e-03 7.02008513e-03 8.91891701e-03 1.06317100e-02]</td><td>[2.25727703e-04 2.46176724e-04 2.48950139e-04 2.30789118e-04\n",
       " 2.60640792e-04 2.64027766e-04 2.94313010e-04 2.84123217e-04\n",
       " 1.77191555e-04 2.73753519e-04 1.76847744e-04 7.36992933e-02\n",
       " 3.11042486e-04 2.65065609e-04 1.86937821e-04 2.60457977e-04\n",
       " 1.82951943e-04 3.41003793e-04 2.78675438e-04 1.08129018e-01\n",
       " 2.76223070e-04 2.97878482e-02 2.55665947e-04 1.59938431e-04\n",
       " 3.38608390e-04 1.61218776e-04 2.98773033e-04 4.48338795e-03\n",
       " 3.17908498e-04 2.23004358e-04 3.66257948e-04 1.92301682e-04\n",
       " 3.18140413e-04 1.99535414e-04 3.03524430e-04 2.23523418e-04\n",
       " 2.65765485e-04 1.80569095e-04 1.86991861e-04 1.83070061e-04\n",
       " 2.43541574e-04 4.41693392e-04 5.35625885e-04 5.65671039e-04\n",
       " 2.41467394e-04 4.04108377e-04 3.52308461e-04 4.62534819e-04\n",
       " 2.36845866e-04 2.42454474e-04 3.96340926e-04 1.13664241e-01\n",
       " 4.60499976e-04 2.94313308e-04 7.01804538e-02 2.32643659e-04\n",
       " 4.73561270e-04 2.56460716e-04 2.17351224e-04 3.07781039e-04\n",
       " 5.20487328e-04 4.58362211e-01 4.35495168e-02 6.48865536e-04\n",
       " 2.55441408e-04 2.79821160e-04 6.53498485e-04 5.04506497e-04\n",
       " 3.15024257e-04 4.08790617e-04 3.12965537e-04 3.03372370e-04\n",
       " 3.65182520e-04 4.43456400e-04 8.40146103e-03 7.80962628e-04\n",
       " 1.74234044e-03 6.02084526e-04 7.06518111e-04 4.55997785e-04\n",
       " 4.53912010e-04 1.00445482e-03 9.22399681e-04 1.56021238e-03\n",
       " 9.43407115e-04 1.25343390e-03 1.48257551e-03 2.05771420e-03\n",
       " 5.41875332e-03 5.09389199e-03 8.87344988e-03 5.93956057e-03\n",
       " 6.10760879e-03 5.70948864e-03 7.96049408e-03 1.03369964e-02]</td><td>[0.00103601 0.00112357 0.00113527 0.0010577  0.00118478 0.00119905\n",
       " 0.00132594 0.00128297 0.00081897 0.0012399  0.00083448 0.33521337\n",
       " 0.0013944  0.00120301 0.00085963 0.00118388 0.00084222 0.00152532\n",
       " 0.00126038 0.15585126 0.00125719 0.0033455  0.01042119 0.00082437\n",
       " 0.00150682 0.0007482  0.00135196 0.00158838 0.00142245 0.00107247\n",
       " 0.0016171  0.00085352 0.00142713 0.00093368 0.0013636  0.00106978\n",
       " 0.00126435 0.00087965 0.00096713 0.00085203 0.00254045 0.00160077\n",
       " 0.00123142 0.00287433 0.00115379 0.00176708 0.00156216 0.00200799\n",
       " 0.00107506 0.00113655 0.00173656 0.09481181 0.00198393 0.00135191\n",
       " 0.00270792 0.00114425 0.00203266 0.0012508  0.00108256 0.00139016\n",
       " 0.00222958 0.06707548 0.00173159 0.00270572 0.00115506 0.00135811\n",
       " 0.00132589 0.00214723 0.00141552 0.00177005 0.00144639 0.00142844\n",
       " 0.00155118 0.00193371 0.05444664 0.00309656 0.04924401 0.0021368\n",
       " 0.00286064 0.00187155 0.00201302 0.0037311  0.0035913  0.00522361\n",
       " 0.00360924 0.00446084 0.0050553  0.00890726 0.01018346 0.0099202\n",
       " 0.01196077 0.01053532 0.01063982 0.01040454 0.01159745 0.01245584]</td><td>[3.66475304e-04 3.99689802e-04 4.03642498e-04 3.74641860e-04\n",
       " 4.22265663e-04 4.27768065e-04 4.76417056e-04 4.59987941e-04\n",
       " 3.16888851e-03 4.43206712e-04 2.92395729e-04 1.15198442e-01\n",
       " 5.02856275e-04 4.29779253e-04 3.59655142e-04 4.22168336e-04\n",
       " 3.09761777e-04 5.53171318e-04 4.51339700e-04 2.50911212e-01\n",
       " 4.54110230e-04 1.09629571e-02 6.88701468e-02 2.73522758e-04\n",
       " 5.46367008e-04 2.65614288e-04 4.71981556e-04 5.77546567e-04\n",
       " 5.13477420e-04 2.53056549e-03 5.90107336e-04 3.32532920e-04\n",
       " 5.19115467e-04 1.55469785e-03 4.90592029e-04 3.76456504e-04\n",
       " 4.54394695e-04 2.87724678e-04 3.14041757e-04 3.19359667e-04\n",
       " 4.17287860e-04 5.36124979e-04 9.15463911e-03 4.34187806e-04\n",
       " 3.79329760e-04 6.50081312e-04 5.69661453e-04 7.48005108e-04\n",
       " 3.88979968e-04 3.93917626e-04 6.37696915e-04 2.68391100e-01\n",
       " 7.39102406e-04 2.30038330e-03 5.22698684e-04 4.07002241e-04\n",
       " 7.58828366e-04 4.77073214e-03 4.42784726e-04 5.03519006e-04\n",
       " 8.47313283e-04 1.69012205e-02 6.15577435e-04 1.05710854e-03\n",
       " 4.03036207e-04 4.60809451e-04 4.77403484e-03 8.07938888e-04\n",
       " 5.88619332e-04 6.74885732e-04 5.26899393e-04 5.15394580e-04\n",
       " 1.78256299e-03 7.01719624e-04 4.71074560e-02 1.23426944e-03\n",
       " 7.82511118e-02 7.53520631e-04 1.11845784e-03 6.56214523e-04\n",
       " 7.40964947e-04 1.58260528e-03 1.47514422e-03 2.36296830e-03\n",
       " 1.47277553e-03 1.93840765e-03 2.25349135e-03 3.12760677e-03\n",
       " 6.86791515e-03 6.53081636e-03 9.76017027e-03 7.33182728e-03\n",
       " 7.56652610e-03 7.15490187e-03 9.05686138e-03 1.07737269e-02]</td><td>[0.00112601 0.00122038 0.00123317 0.00114944 0.00128655 0.00130195\n",
       " 0.00143817 0.00139246 0.00088975 0.00134598 0.00095107 0.38958046\n",
       " 0.00151198 0.00130628 0.00093599 0.00128567 0.00091291 0.00164156\n",
       " 0.0013681  0.05442034 0.00135669 0.00112552 0.00128812 0.0016714\n",
       " 0.00163312 0.00082844 0.00144326 0.0017128  0.00154253 0.00112114\n",
       " 0.00175174 0.00097013 0.00154326 0.00586875 0.00147917 0.00113908\n",
       " 0.00134524 0.00094481 0.00093294 0.00093146 0.00127521 0.00909072\n",
       " 0.0013401  0.00140798 0.00115286 0.00191226 0.00169179 0.00215041\n",
       " 0.00115233 0.00120241 0.00187954 0.03295482 0.00214427 0.0014812\n",
       " 0.20497914 0.00142357 0.00219635 0.0011868  0.00126912 0.00152199\n",
       " 0.00237902 0.05254875 0.0018411  0.00286001 0.00290759 0.00142345\n",
       " 0.0015795  0.00231935 0.00154439 0.0019328  0.00149287 0.00159762\n",
       " 0.0017571  0.00207263 0.00234786 0.00332884 0.00565657 0.00214297\n",
       " 0.00307542 0.00892029 0.00225483 0.00396604 0.00379594 0.00553846\n",
       " 0.00386345 0.00475762 0.00535481 0.00646198 0.01048936 0.01025407\n",
       " 0.01220115 0.01083774 0.01093421 0.0106861  0.01186275 0.01267266]</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>HPF_LogPP</strong></td><td>-936555.1809497576</td><td>-1392946.0035388658</td><td>-2295063.000008551</td><td>-3322995.223196471</td><td>-5530380.775234937</td><td>-3976133.288250344</td><td>-4981867.481776507</td><td>-1324102.6545238378</td><td>-3969957.407995618</td><td>-1371789.7936430394</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>HPF_theta</strong></td><td>[   26.52614763    28.7514732     29.05145887    27.07863444\n",
       "    30.30827715    30.67097478    33.89044058    32.80730238\n",
       "    20.82022521    31.70835269    21.03534583  1129.56419378\n",
       "    35.6237928     30.77884092    22.22337886    30.2891211\n",
       "    21.68720055    38.84108343    32.231423    2544.83762412\n",
       "    32.04496125    26.81296636    30.08019041    18.18960844\n",
       "    38.47359986    19.01025468    33.12618836   362.83537648\n",
       "    36.34319582    25.88220645    41.28428964    22.13195052\n",
       "    36.43065981    23.33875582    34.84700094    26.21923232\n",
       "    30.65892247    20.44981904    21.35384625    21.69201391\n",
       "    28.49025691    37.37154679    31.22483208    26.25573417\n",
       "    26.14241932    45.04991272    39.86816809    50.96618743\n",
       "    26.9661041     28.16124692    44.28428728   989.22686027\n",
       "    50.53245947    33.84600602  1660.13764316    26.09725665\n",
       "    51.76047634    27.32376108    24.99938656    35.35918447\n",
       "    56.30777218 11439.31019342    42.87782472    68.44986139\n",
       "    28.21641639    32.4231213     33.247884      54.79304043\n",
       "    36.21759547    45.98319972    35.34800852    34.40858549\n",
       "    42.74835829    47.77487153    51.84255934    78.75419558\n",
       "    51.95997143    48.22010618    72.46185107   138.99596577\n",
       "    49.68420313    95.13802729    90.25797658   130.54849143\n",
       "    91.09499553   114.989342     125.89892189   148.2265891\n",
       "   247.81101623   242.822213     288.31929469   255.40231456\n",
       "   259.02937729   252.18470338   279.41888632   298.67235137]</td><td>[  26.75872846   29.02798039   29.3301456    27.32103887   30.61233964\n",
       "   30.98241736   34.27124654   33.1625501    31.44625612   32.04093582\n",
       "   22.68311994 9779.27446791   36.03971129   31.08988599   23.05025172\n",
       "   30.59231214   22.01511348   39.23453823   32.57549534 2005.86515918\n",
       "   32.38397879 1526.73805344   42.49526254   26.16529368   38.96432171\n",
       "   19.26276379   34.87240245   41.05622872   36.77722111   26.03926596\n",
       "   41.84468777   25.51828802   36.88397978   23.82499011   35.24945157\n",
       "   27.85620492   31.29578813   46.2985977    22.91947697   21.97458877\n",
       "   29.95732395   41.61252996   34.09034797   42.66424559  185.36665446\n",
       "   45.72549844   40.40418234   51.57615746   27.6271516    28.92074196\n",
       "   44.93058238  193.82247522   51.37287566  385.25299091 1840.3399548\n",
       "   26.67244533   52.65160007   34.66070895   32.8984322    35.90339661\n",
       "   57.35714604 4148.81687655   44.71070927   69.02703809   30.67311357\n",
       "   58.05128922   35.23625541   55.73214255   44.13327972   45.92180465\n",
       "   37.01365124   43.02419082   43.50081705   57.4068196   166.69174023\n",
       "   80.81402945   81.69488638  553.92314626   74.21373622  143.85724687\n",
       "   60.51756934  102.05134334   92.49802944  136.31827557   93.81565076\n",
       "  117.71993     131.52860025  189.2501315   269.90064034  263.70350382\n",
       "  317.88491238  278.70342349  283.40674064  274.43968534  307.5777099\n",
       "  331.06899671]</td><td>[   27.6280429     30.05247953    30.37759329    28.2277002\n",
       "    31.75541844    32.15379768    35.70712077    34.50617204\n",
       "    22.80057322    33.295474      21.22592076 15586.0678031\n",
       "    37.63725307    32.26792711    25.77156472    31.7319422\n",
       "    24.72311432    41.18415548    33.8718877   4884.05874511\n",
       "    33.62617454  2368.05513668    31.94574001    19.37986956\n",
       "    40.8354212     19.56505612    35.29390975    43.47282845\n",
       "    38.43889537    26.26737225    44.00352842    24.5282332\n",
       "    38.48566371   100.42063812    36.77337353    27.635911\n",
       "    32.91622246    25.66235657    22.60270163    22.56991498\n",
       "   165.51181216   181.45948209    32.33635954    27.68332063\n",
       "    34.16817362    48.32307088    42.40285349    55.04299399\n",
       "    28.31082754    29.69056795    47.44106445  3301.08133944\n",
       "    54.67225642    36.11727077  2409.56173697    27.26780136\n",
       "    56.11393312    29.44041116    26.33607799    37.90441704\n",
       "    61.44078669  2577.2244759     46.85066756    75.51626494\n",
       "    29.49523993    38.93988573    64.26772863    59.61722244\n",
       "    39.62730203    48.3719717     37.45704881    37.09992147\n",
       "    43.12011175    52.08440742  7697.94179428    89.05914364\n",
       "  1657.307602      55.82298042    81.31574158   246.36534702\n",
       "    55.30753554   115.30130284   103.83065489   162.39419919\n",
       "   105.47655995   145.22377415   155.56238317   193.90162588\n",
       "   394.26099964   380.1841607    507.54608178   414.67874809\n",
       "   421.90257758   406.14783563   481.93030702   542.12041668]</td><td>[2.81221507e+01 3.06742666e+01 3.09757052e+01 2.87445854e+01\n",
       " 3.24096864e+01 3.28248345e+01 3.65816195e+01 3.52833686e+01\n",
       " 2.14257559e+01 3.40155492e+01 2.19837395e+01 1.52684822e+04\n",
       " 3.86312564e+01 3.29481916e+01 2.29987298e+01 3.24098008e+01\n",
       " 2.27397151e+01 4.24180690e+01 3.46210084e+01 5.23356008e+03\n",
       " 3.44704299e+01 3.48066347e+03 1.02052356e+02 1.89803732e+01\n",
       " 4.19244284e+01 1.98317263e+01 3.77944369e+01 5.71507893e+02\n",
       " 3.94028798e+01 3.27657057e+01 4.52740831e+01 2.25967698e+01\n",
       " 3.95321316e+01 2.46116949e+01 3.76550166e+01 2.85934841e+01\n",
       " 3.49784766e+01 2.23408196e+01 2.33182681e+01 2.28370731e+01\n",
       " 4.40711409e+03 4.23573795e+01 3.26885482e+01 3.06948209e+01\n",
       " 3.09548271e+01 4.98560591e+01 4.36222929e+01 5.72620561e+01\n",
       " 2.88849302e+01 3.01715926e+01 4.89252676e+01 7.14227007e+03\n",
       " 5.66446487e+01 3.69912963e+01 2.30782461e+04 2.71076222e+01\n",
       " 5.82054220e+01 2.88175482e+01 2.62706811e+01 3.83897258e+01\n",
       " 6.42837502e+01 8.01164219e+03 5.82632439e+01 8.01558475e+01\n",
       " 2.97290843e+01 3.48313969e+01 3.50044508e+01 6.19681457e+01\n",
       " 3.98600712e+01 5.04768981e+01 4.01175430e+01 3.74959758e+01\n",
       " 4.32847406e+01 5.33690326e+01 1.13230456e+03 9.43857053e+01\n",
       " 7.19590686e+01 5.64907857e+01 8.57545931e+01 5.45387955e+01\n",
       " 5.53543864e+01 1.19396613e+02 1.11691521e+02 1.81188120e+02\n",
       " 1.13046792e+02 1.49929434e+02 1.72478262e+02 2.54980603e+02\n",
       " 5.24735071e+02 5.00401782e+02 7.51522081e+02 5.64260517e+02\n",
       " 5.76919894e+02 5.48847498e+02 6.95302613e+02 8.27129249e+02]</td><td>[2.82494324e+01 3.08062010e+01 3.11301956e+01 2.88777530e+01\n",
       " 3.25786380e+01 3.29981886e+01 3.67768635e+01 3.54851767e+01\n",
       " 2.20221161e+01 3.42019786e+01 2.22620568e+01 2.07505895e+04\n",
       " 3.88216270e+01 3.31265293e+01 2.33213162e+01 3.25647219e+01\n",
       " 2.38350623e+01 4.27077706e+01 3.48124261e+01 1.46122433e+04\n",
       " 3.47455455e+01 2.54400659e+04 9.00259444e+02 1.55156644e+02\n",
       " 4.22079218e+01 2.03849595e+01 3.75558621e+01 2.26148113e+02\n",
       " 3.96573176e+01 2.79630874e+01 4.56140308e+01 2.35126153e+01\n",
       " 3.98940418e+01 3.01485889e+01 3.78825884e+01 3.00010692e+01\n",
       " 4.24850879e+01 2.14239105e+02 2.36700824e+01 2.33362628e+01\n",
       " 9.58469712e+02 4.44095862e+01 3.41276086e+01 2.85305884e+01\n",
       " 2.84739668e+01 5.02570250e+01 4.39623086e+01 5.77963963e+01\n",
       " 2.95783663e+01 3.02381148e+01 4.93093720e+01 3.81957193e+03\n",
       " 5.71642837e+01 4.02370384e+01 3.74902193e+03 3.02156744e+01\n",
       " 5.87556573e+01 3.65116936e+01 2.85674684e+01 5.72257961e+01\n",
       " 6.51592043e+01 6.73436402e+03 1.11566016e+02 8.12567920e+01\n",
       " 3.08099490e+01 3.49732298e+01 3.63999018e+01 6.25909822e+01\n",
       " 4.04891285e+01 5.10259848e+01 3.99366487e+01 3.87704568e+01\n",
       " 2.52910008e+02 5.50221825e+01 5.15620043e+02 9.59310301e+01\n",
       " 3.54447455e+02 5.42124147e+01 8.69468768e+01 3.38312571e+02\n",
       " 5.62552055e+01 1.34428377e+02 1.14299068e+02 1.86601479e+02\n",
       " 1.15150890e+02 4.42346585e+02 1.77338184e+02 2.50150649e+02\n",
       " 5.73160631e+02 5.46417984e+02 8.55371898e+02 6.18697684e+02\n",
       " 6.39583696e+02 6.01422734e+02 7.81533807e+02 9.53402339e+02]</td><td>[2.81302637e+01 3.06493510e+01 3.09850903e+01 2.87568778e+01\n",
       " 3.24192222e+01 3.28348445e+01 3.65447291e+01 3.53039072e+01\n",
       " 3.28938125e+02 3.40268812e+01 2.17230579e+01 6.15537491e+03\n",
       " 3.86091281e+01 3.29761212e+01 2.50996904e+01 3.24102400e+01\n",
       " 2.32314881e+01 4.22439738e+01 3.46378541e+01 3.32297137e+03\n",
       " 3.43481151e+01 2.98470157e+03 3.05449664e+01 1.99056764e+01\n",
       " 4.19428533e+01 2.00295141e+01 3.63309882e+01 2.07166848e+03\n",
       " 3.94302945e+01 2.65875275e+01 4.53363053e+01 2.97388769e+01\n",
       " 3.94770313e+01 7.81424385e+01 3.76692948e+01 2.77279019e+01\n",
       " 3.39289600e+01 2.15566456e+01 2.27439207e+01 2.33006117e+01\n",
       " 3.73770777e+01 4.11102541e+01 3.35608210e+01 2.81056182e+01\n",
       " 2.87453780e+01 4.98823561e+01 4.36118481e+01 5.68074805e+01\n",
       " 2.90930772e+01 2.99031761e+01 4.89580817e+01 5.66084917e+03\n",
       " 5.66850244e+01 4.21506102e+01 1.16322208e+04 2.83688365e+01\n",
       " 5.82529925e+01 2.93384702e+01 2.63879841e+01 3.87268029e+01\n",
       " 6.38804409e+01 3.40294807e+04 2.77144619e+03 7.91124546e+01\n",
       " 3.11958893e+01 3.36863726e+01 3.96884207e+01 6.20153299e+01\n",
       " 3.98771370e+01 5.04799936e+01 3.84220764e+01 3.75314690e+01\n",
       " 4.47812914e+01 5.36527417e+01 5.90131241e+01 9.46565870e+01\n",
       " 5.77722642e+01 5.25269094e+01 8.58262312e+01 5.05279509e+02\n",
       " 5.53934670e+01 1.17912084e+02 1.10538244e+02 1.81546961e+02\n",
       " 1.13213545e+02 1.47566353e+02 1.73326046e+02 2.36094201e+02\n",
       " 5.27267966e+02 5.02579843e+02 7.53589956e+02 5.65793469e+02\n",
       " 5.75601739e+02 5.50280979e+02 6.99124055e+02 8.33384168e+02]</td><td>[2.84764325e+01 3.10561565e+01 3.14060336e+01 2.91149498e+01\n",
       " 3.28808553e+01 3.33081352e+01 3.71287372e+01 3.58432549e+01\n",
       " 2.23534076e+01 3.45350771e+01 2.23100345e+01 9.29745407e+03\n",
       " 3.92392260e+01 3.34390632e+01 2.35829372e+01 3.28577924e+01\n",
       " 2.30801031e+01 4.30189621e+01 3.51559963e+01 1.36408985e+04\n",
       " 3.48466205e+01 3.75785354e+03 3.22532591e+01 2.01768585e+01\n",
       " 4.27167727e+01 2.03383790e+01 3.76913865e+01 5.65596923e+02\n",
       " 4.01054003e+01 2.81328719e+01 4.62048724e+01 2.42596092e+01\n",
       " 4.01346572e+01 2.51721729e+01 3.82907939e+01 2.81983533e+01\n",
       " 3.35273553e+01 2.27794975e+01 2.35897546e+01 2.30950042e+01\n",
       " 3.07237219e+01 5.57213487e+01 6.75713000e+01 7.13616138e+01\n",
       " 3.04620561e+01 5.09798521e+01 4.44450901e+01 5.83505763e+01\n",
       " 2.98790323e+01 3.05865801e+01 4.99999578e+01 1.43391885e+04\n",
       " 5.80938728e+01 3.71287748e+01 8.85353871e+03 2.93489074e+01\n",
       " 5.97416061e+01 3.23535223e+01 2.74197070e+01 3.88277817e+01\n",
       " 6.56615120e+01 5.78241855e+04 5.49394186e+03 8.18569249e+01\n",
       " 3.22249326e+01 3.53005337e+01 8.24413896e+01 6.36454676e+01\n",
       " 3.97415420e+01 5.15705350e+01 3.94818265e+01 3.82716109e+01\n",
       " 4.60692030e+01 5.59437591e+01 1.05987717e+03 9.85214897e+01\n",
       " 2.19803060e+02 7.59553176e+01 8.91300227e+01 5.75259039e+01\n",
       " 5.72627752e+01 1.26715903e+02 1.16364327e+02 1.96826894e+02\n",
       " 1.19014497e+02 1.58125589e+02 1.87032698e+02 2.59588694e+02\n",
       " 6.83596922e+02 6.42614396e+02 1.11942040e+03 7.49298793e+02\n",
       " 7.70498735e+02 7.20274320e+02 1.00424746e+03 1.30405252e+03]</td><td>[  26.69019056   28.94583048   29.24739688   27.24892271   30.52272089\n",
       "   30.89059628   34.15949462   33.05254001   21.09868084   31.94289271\n",
       "   21.49824643 8635.92033377   35.92323529   30.99255564   22.14618258\n",
       "   30.49965208   21.69775805   39.29596125   32.47054669 4015.1116044\n",
       "   32.38822864   86.18820414  268.47541339   21.23785536   38.81928201\n",
       "   19.27555533   34.82990192   40.92063198   36.64574338   27.62941972\n",
       "   41.66048582   21.9887797    36.76626815   24.0538684    35.12971772\n",
       "   27.56011553   32.57284082   22.66203021   24.91561525   21.95035718\n",
       "   65.44822263   41.23989721   31.72449213   74.04970294   29.724444\n",
       "   45.52430633   40.24510391   51.73085784   27.69619154   29.28040787\n",
       "   44.73796172 2442.58524067   51.11087736   34.82851222   69.76260075\n",
       "   29.47874666   52.36624771   32.22359324   27.88940391   35.81403704\n",
       "   57.43953659 1728.02925509   44.60994793   69.70604728   29.75728101\n",
       "   34.98830218   34.15824799   55.31782231   36.46717894   45.60080782\n",
       "   37.2625478    36.80003784   39.96210838   49.81724782 1402.6791629\n",
       "   79.77502223 1268.64683406   55.0493389    73.69704875   48.21563972\n",
       "   51.86042562   96.12240707   92.52061061  134.57306584   92.98279259\n",
       "  114.92221927  130.23685492  229.47295134  262.35107093  255.56877589\n",
       "  308.13885239  271.41570485  274.10778673  268.04650811  298.7788567\n",
       "  320.89311616]</td><td>[2.81301823e+01 3.06796853e+01 3.09830892e+01 2.87570368e+01\n",
       " 3.24125799e+01 3.28349373e+01 3.65691725e+01 3.53080944e+01\n",
       " 2.43239887e+02 3.40199884e+01 2.24439275e+01 8.84248714e+03\n",
       " 3.85986136e+01 3.29893136e+01 2.76066752e+01 3.24051092e+01\n",
       " 2.37769234e+01 4.24607329e+01 3.46442663e+01 1.92596282e+04\n",
       " 3.48569287e+01 8.41502763e+02 5.28638564e+03 2.09952620e+01\n",
       " 4.19384426e+01 2.03882179e+01 3.62287091e+01 4.43317463e+01\n",
       " 3.94138793e+01 1.94243016e+02 4.52958951e+01 2.55248076e+01\n",
       " 3.98466488e+01 1.19336647e+02 3.76572256e+01 2.88963266e+01\n",
       " 3.48787638e+01 2.20853835e+01 2.41054493e+01 2.45136454e+01\n",
       " 3.20304900e+01 4.11522774e+01 7.02698556e+02 3.33277086e+01\n",
       " 2.91168741e+01 4.98994219e+01 4.37264949e+01 5.74159290e+01\n",
       " 2.98576119e+01 3.02366203e+01 4.89488111e+01 2.06013625e+04\n",
       " 5.67325688e+01 1.76574522e+02 4.01216919e+01 3.12409789e+01\n",
       " 5.82467087e+01 3.66195384e+02 3.39875973e+01 3.86494840e+01\n",
       " 6.50386993e+01 1.29731638e+03 4.72509478e+01 8.11423186e+01\n",
       " 3.09365511e+01 3.53711524e+01 3.66448895e+02 6.20163703e+01\n",
       " 4.51816777e+01 5.18033778e+01 4.04441331e+01 3.95610381e+01\n",
       " 1.36827288e+02 5.38631136e+01 3.61590893e+03 9.47409659e+01\n",
       " 6.00645668e+03 5.78392936e+01 8.58514138e+01 5.03701994e+01\n",
       " 5.68755351e+01 1.21478786e+02 1.13230210e+02 1.81378467e+02\n",
       " 1.13048393e+02 1.48789727e+02 1.72975155e+02 2.40071152e+02\n",
       " 5.27172508e+02 5.01297230e+02 7.49178364e+02 5.62781818e+02\n",
       " 5.80797003e+02 5.49201246e+02 6.95193261e+02 8.26977692e+02]</td><td>[  26.52489338   28.74793992   29.04916133   27.07677226   30.30668259\n",
       "   30.66940663   33.87818478   32.801444     20.95942551   31.7064303\n",
       "   22.40384559 9177.13707432   35.61682787   30.77132643   22.04867232\n",
       "   30.28592481   21.50491083   38.66942849   32.22768348 1281.95067257\n",
       "   31.95878293   26.5133538    30.34359151   39.37217363   38.47046323\n",
       "   19.51502276   33.99800228   40.34757573   36.33648713   26.41013529\n",
       "   41.2647485    22.85275972   36.35375886  138.2470892    34.84408645\n",
       "   26.83275462   31.68914471   22.25638522   21.97675436   21.94196759\n",
       "   30.0393733   214.14530075   31.56806011   33.16693982   27.15738495\n",
       "   45.04611958   39.8526662    50.65611643   27.14483937   28.32453724\n",
       "   44.27522119  776.29885908   50.51152481   34.89174167 4828.58320221\n",
       "   33.53430277   51.73818065   27.95670315   29.89608794   35.85258707\n",
       "   56.04132068 1237.86268343   43.3697847    67.37181812   68.49243015\n",
       "   33.53155509   37.20736027   54.63557703   36.3803225    45.52998421\n",
       "   35.1667645    37.63433116   41.39107061   48.82379487   55.30737845\n",
       "   78.41563555  133.24865718   50.4808       72.44603848  210.13047194\n",
       "   53.11586867   93.42583288   89.41887218  130.4666174    91.00921544\n",
       "  112.07260694  126.14033225  152.22130779  247.09210748  241.5496734\n",
       "  287.41589322  255.29875708  257.57124698  251.72659737  279.44438657\n",
       "  298.52307055]</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>IsCycling</strong></td><td>0</td><td>1</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Label</strong></td><td>G66</td><td>G67</td><td>G66</td><td>G66</td><td>G67</td><td>G67</td><td>G66</td><td>G67</td><td>G34</td><td>G66</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Location_E9_E11</strong></td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>NCellsCluster</strong></td><td>21</td><td>21</td><td>21</td><td>21</td><td>21</td><td>21</td><td>21</td><td>21</td><td>21</td><td>21</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>NGenes</strong></td><td>1032.0</td><td>1436.0</td><td>1831.0</td><td>2559.0</td><td>4084.0</td><td>2478.0</td><td>3449.0</td><td>1426.0</td><td>3405.0</td><td>1408.0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Num_Pooled_Animals</strong></td><td>18</td><td>18</td><td>18</td><td>18</td><td>18</td><td>18</td><td>18</td><td>18</td><td>10</td><td>18</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>PCA</strong></td><td>[-4.61599464  1.37712846 -1.00436856 -1.32450197  0.15986299 -2.48003509\n",
       " -0.27139645  0.39139764 -0.95083853  3.18528661  0.67692877  0.75177287\n",
       " -0.37586534 -0.32372571  0.28109046  0.19482973  1.98599158  0.63499673\n",
       " -0.35881493  0.30498964  0.21050756  0.88805016 -0.20181596 -0.09254861\n",
       " -0.08905014  0.43033333  0.36697656  0.39477385 -0.00754566 -0.27280585\n",
       " -0.14845221 -0.22348466  1.14033073  0.86408645 -0.05922257 -0.17965211\n",
       "  0.42376554  0.61117647 -0.00873047  0.21144339  0.2705709  -0.12315068\n",
       "  0.11806172 -0.04083693 -0.36727115  0.14400051 -0.15080106 -0.50116002\n",
       "  0.47983571 -0.30324772]</td><td>[-4.29762612  0.33252377 -0.32270103 -1.87280273  0.94597268 -0.60550791\n",
       "  0.32135178  0.29787223  0.5375489   2.08730593 -0.26658371  0.12372089\n",
       " -0.50307179  0.49669483  0.20436069  0.23861282  0.36497    -0.50015736\n",
       " -0.56650704 -0.08278936 -0.20288761  0.28426354 -0.55637465 -0.4490847\n",
       " -0.40116537  0.24120386 -0.85675111  0.26809652  0.11352348 -0.68643272\n",
       " -0.12650395  0.05656738  0.88275037  0.57002722 -0.03110474 -0.45334092\n",
       "  0.81486809 -0.0393012  -0.88805517 -0.17916812 -0.07626975 -0.31098539\n",
       "  0.05096837 -0.35349776  0.51400034 -0.24435869 -0.47732851  0.43334221\n",
       " -0.14948775 -0.07881997]</td><td>[-4.82502228  0.24514512 -0.81864162 -2.05926984  1.06075764 -0.87957307\n",
       " -0.24417477  0.27821678  0.57217946  2.01574293  0.22377421  0.24883198\n",
       " -0.66002921  0.08051235 -0.57961746  0.0102096   0.98839817  0.03174948\n",
       " -0.27527549 -0.00989366  0.22230001  0.21299143 -0.15307485 -0.83139306\n",
       " -1.04040959  0.20484606 -0.4858176   0.15549705  0.20080454 -0.85447938\n",
       "  0.07077162  0.11352901  0.38634446  0.97932005  0.48306166  0.77567412\n",
       "  0.16683956  0.76709188 -0.46670325  0.05219484  0.44388861 -0.14163326\n",
       "  0.53004535 -0.36427025  0.6125393  -0.38015436  0.17966772  0.46979557\n",
       "  0.14009814 -0.23859021]</td><td>[-5.68405948e+00  1.11599787e-01 -9.41352857e-01 -1.84588372e+00\n",
       "  7.49081500e-01 -1.66886692e+00 -3.97243990e-01  1.65511659e-01\n",
       "  8.22583276e-02  2.83514574e+00  7.07608797e-01 -2.32052473e-01\n",
       " -5.96518274e-01  1.98169748e-03 -4.63533293e-01  6.55927656e-02\n",
       "  6.05822412e-01  4.81105658e-02 -2.12739879e-01  2.99442681e-01\n",
       "  1.60435681e-01 -1.32592173e-01 -3.81519604e-01 -6.18571989e-01\n",
       " -1.68959871e-01  9.29089938e-02 -7.08788848e-01  2.34364427e-01\n",
       " -1.43903007e-01 -2.95894623e-01  7.50254433e-02  7.37494560e-02\n",
       "  3.02670048e-01  2.72282438e-01  6.99312964e-01  3.96564582e-01\n",
       "  2.32870900e-01  2.75491740e-01 -1.17924022e+00 -2.70873603e-01\n",
       "  2.52487559e-01 -1.04724846e-01 -4.31196672e-01 -4.11578530e-01\n",
       "  6.59524307e-01  1.12300821e-01  2.62085572e-01  4.51883708e-01\n",
       " -4.81879081e-02  2.84722345e-01]</td><td>[-4.99096565e+00  6.16722039e-01 -1.56090617e+00 -1.37804264e+00\n",
       "  2.24865836e-01 -1.78633292e+00 -7.73792247e-01  3.73580870e-01\n",
       "  5.97245477e-02  2.31213531e+00  1.71892529e-01  6.25254728e-01\n",
       "  1.68545691e-01  3.15959254e-01 -2.59437078e-01  1.10420475e-01\n",
       "  1.56185129e+00 -1.04658420e-02  1.51577064e-01  3.16648835e-01\n",
       "  5.54496738e-01  2.84011328e-01 -1.12747929e+00 -5.20317333e-02\n",
       " -5.63382089e-01  3.53566752e-01 -1.38963742e-01  2.89261185e-01\n",
       "  6.12117955e-01 -8.89397913e-01 -1.04894094e-01  1.62186798e-01\n",
       " -3.61909482e-01  1.27948467e-01  3.36228521e-03  3.94818184e-01\n",
       " -1.00943265e-01 -1.12998933e-01 -4.37676041e-01  3.56604144e-01\n",
       " -1.39564901e-01 -3.10222705e-01  7.53720169e-01  4.49328815e-02\n",
       "  2.15931535e-01 -5.59912138e-01  8.82656526e-02  7.35556937e-02\n",
       " -4.75328403e-02  2.54751916e-01]</td><td>[-5.54754944 -0.08283802 -1.11234096 -2.70501893  0.82895979 -3.55665962\n",
       "  0.04658474 -0.09349918 -1.35935811  5.91018483  0.60225227 -0.08357877\n",
       "  0.24537507  0.75985862  0.89097785  0.09178561  0.77363727  0.61737282\n",
       " -0.09110908  0.32819151 -0.84122537  0.13384207  0.79419415 -0.27205359\n",
       " -0.19334183 -0.58849469 -1.14536843  0.05711191 -0.88646436  0.48504376\n",
       "  0.32770099 -0.46948136  1.66607166  0.41764171  0.65192847 -0.3679523\n",
       "  0.44308501  0.14005205 -0.43862426 -0.17318876 -0.06088093 -0.03470392\n",
       " -0.55883128 -0.32070746  0.37764624 -0.22385763  0.14728863 -0.33306742\n",
       "  0.22716209  0.02321261]</td><td>[-5.61995017  0.17781749 -1.27530471 -2.69475859  0.77191529 -3.10071715\n",
       "  0.04895461  0.09100791 -0.90734091  4.48865554  0.45366389  0.20361531\n",
       " -0.03181363  0.70946682  0.50067494  0.0314889   0.66875007  0.09087647\n",
       " -0.17399993  0.58776432  0.12207854  0.25988638  0.00800619 -0.13383848\n",
       " -0.69076867 -0.02564747 -0.88350707 -0.14641752 -0.5310103  -0.07163011\n",
       "  0.25315364 -0.04818313  0.92767551  0.28742921  0.68852751 -0.28282007\n",
       "  0.36388395 -0.06493183 -1.11409413 -0.2683294   0.10986231  0.00622941\n",
       " -0.18710452 -0.22884297  0.07431766 -0.36212709  0.15426741 -0.17192702\n",
       "  0.07256329  0.14063213]</td><td>[-4.49780599  0.33094802 -0.78793504 -1.51846983  0.76186715 -0.65205102\n",
       " -0.23901522  0.34366008  0.41443501  1.91655103 -0.24385833  0.34550627\n",
       " -0.66620143  0.03950938 -0.24466032  0.4568808   0.55442281 -0.0854654\n",
       " -0.47272759  0.16762929  0.33569294 -0.09786582 -0.36756274 -0.84901314\n",
       " -0.36488431  0.13975067 -0.76960619  0.22780048  0.45111948 -0.92138061\n",
       "  0.23599227  0.40857188  0.21570433  1.05594939  0.05783872  0.96243724\n",
       "  0.2082372   1.38495537  0.07477541 -0.10188626  0.54874117  0.33685074\n",
       "  1.12399326 -0.23936257  0.24587079 -0.29741015 -0.12873773  0.21321309\n",
       " -0.00802044  0.06976305]</td><td>[-5.67051219 -0.4355449  -2.1232541  -2.89555296  0.92716177 -0.37676833\n",
       " -2.03811633  0.83803094  0.74929294  1.20463999  0.06755927  0.56124741\n",
       " -0.25820852  0.53275908  0.19759818 -0.89451119  0.6164195  -1.59334662\n",
       "  0.70769548  0.16901347  0.4112637   0.14743123  1.07166647 -0.83756755\n",
       " -0.53946822  0.20029624 -0.41380473 -1.12919062  0.56680072 -0.9147479\n",
       "  0.55696161  0.19124778 -0.54410882  0.02739673  0.25752985  1.43885449\n",
       " -0.03555736  0.08383475 -0.71045082 -0.06296559 -0.26863803  0.18054718\n",
       " -0.14755286  0.42653858  0.8939082  -0.30497866  0.16700542  0.23045109\n",
       " -0.62057749 -0.11989452]</td><td>[-4.4351039   0.23922234 -0.71944074 -1.88576885  1.30680568 -1.02321125\n",
       " -0.08419035  0.58306275  0.85578127  1.90662254 -0.18600659  0.39845568\n",
       "  0.14498357  0.36360513 -0.14145488 -0.15005032  0.8897451   0.06949224\n",
       " -0.12265601 -0.47738903 -0.63408135  0.46903651  0.11674813 -0.05055125\n",
       " -1.36406293 -0.06470725 -0.31541586 -0.42993707 -0.45160529 -0.29539907\n",
       " -0.36001539  0.29219104  0.84460581  0.38824233  0.41319995  0.1823029\n",
       "  0.31233689  0.62413224 -0.14126753 -0.52793252  0.89830563 -0.13877926\n",
       " -0.61054654 -0.36093186  0.21305669 -0.09979615  0.2074927   0.2283857\n",
       " -0.31174386  0.04361978]</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>PCR_Cycles</strong></td><td>13</td><td>13</td><td>13</td><td>13</td><td>13</td><td>13</td><td>13</td><td>13</td><td>13</td><td>13</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Plug_Date</strong></td><td>2016-09-23</td><td>2016-09-23</td><td>2016-09-23</td><td>2016-09-23</td><td>2016-09-23</td><td>2016-09-23</td><td>2016-09-23</td><td>2016-09-23</td><td>2106-08-31</td><td>2016-09-23</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Project</strong></td><td>Dev</td><td>Dev</td><td>Dev</td><td>Dev</td><td>Dev</td><td>Dev</td><td>Dev</td><td>Dev</td><td>Dev</td><td>Dev</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>PseudoAge</strong></td><td>7.05</td><td>9.22</td><td>9.265</td><td>9.545</td><td>8.685</td><td>6.99</td><td>7.04</td><td>9.085</td><td>8.835</td><td>9.36</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>PseudoTissue</strong></td><td>All</td><td>Forebrain</td><td>Head</td><td>All</td><td>All</td><td>All</td><td>All</td><td>Head</td><td>Head</td><td>Forebrain</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Region</strong></td><td>Head</td><td>Head</td><td>Head</td><td>Head</td><td>Head</td><td>Head</td><td>Head</td><td>Head</td><td>Head</td><td>Head</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID</strong></td><td>10X39_2</td><td>10X39_3</td><td>10X39_2</td><td>10X39_2</td><td>10X39_3</td><td>10X39_3</td><td>10X39_2</td><td>10X39_3</td><td>10X21_2</td><td>10X39_2</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleName</strong></td><td>G66</td><td>G67</td><td>G66</td><td>G66</td><td>G67</td><td>G67</td><td>G66</td><td>G67</td><td>G34</td><td>G66</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Sample_Index</strong></td><td>SI-3A-B5</td><td>SI-3A-C5</td><td>SI-3A-B5</td><td>SI-3A-B5</td><td>SI-3A-C5</td><td>SI-3A-C5</td><td>SI-3A-B5</td><td>SI-3A-C5</td><td>SI-3A-D10</td><td>SI-3A-B5</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Sex</strong></td><td>?</td><td>?</td><td>?</td><td>?</td><td>?</td><td>?</td><td>?</td><td>?</td><td>?</td><td>?</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Species</strong></td><td>Mm</td><td>Mm</td><td>Mm</td><td>Mm</td><td>Mm</td><td>Mm</td><td>Mm</td><td>Mm</td><td>Mm</td><td>Mm</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Split</strong></td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Strain</strong></td><td>CD-1</td><td>CD-1</td><td>CD-1</td><td>CD-1</td><td>CD-1</td><td>CD-1</td><td>CD-1</td><td>CD-1</td><td>CD-1</td><td>CD-1</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Subclass</strong></td><td>Parietal endoderm</td><td>Parietal endoderm</td><td>Parietal endoderm</td><td>Parietal endoderm</td><td>Parietal endoderm</td><td>Parietal endoderm</td><td>Parietal endoderm</td><td>Parietal endoderm</td><td>Parietal endoderm</td><td>Parietal endoderm</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>TSNE</strong></td><td>[-31.85552615 -61.93306125]</td><td>[ -2.87413797 -57.27298664]</td><td>[ -2.77695001 -56.40269395]</td><td>[-27.60967517 -38.25846626]</td><td>[ -9.55072307 -39.07598744]</td><td>[-32.11604733 -62.34137016]</td><td>[-30.93707251 -57.51320106]</td><td>[ -3.34237798 -56.85237163]</td><td>[-56.05262281 -29.958472  ]</td><td>[ -2.96161651 -57.16943392]</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Target_Num_Cells</strong></td><td>3500.0</td><td>3500.0</td><td>3500.0</td><td>3500.0</td><td>3500.0</td><td>3500.0</td><td>3500.0</td><td>3500.0</td><td>3500.0</td><td>3500.0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Tissue</strong></td><td>All (No extraembryonal)</td><td>All (No extraembryonal)</td><td>All (No extraembryonal)</td><td>All (No extraembryonal)</td><td>All (No extraembryonal)</td><td>All (No extraembryonal)</td><td>All (No extraembryonal)</td><td>All (No extraembryonal)</td><td>Head</td><td>All (No extraembryonal)</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>TotalUMI</strong></td><td>2189.0</td><td>2757.0</td><td>4941.0</td><td>8176.0</td><td>16640.0</td><td>7846.0</td><td>12769.0</td><td>2993.0</td><td>9243.0</td><td>2858.0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Transcriptome</strong></td><td>mm10</td><td>mm10</td><td>mm10</td><td>mm10</td><td>mm10</td><td>mm10</td><td>mm10</td><td>mm10</td><td>mm10</td><td>mm10</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>UMAP</strong></td><td>[-1.7688403  4.42517  ]</td><td>[-1.7824202  4.4122787]</td><td>[-1.7751874  4.4206305]</td><td>[-1.7727247  4.4222918]</td><td>[-1.7763555  4.4188786]</td><td>[-1.7699778  4.424189 ]</td><td>[-1.7733016  4.4216337]</td><td>[-1.7525274  4.4418197]</td><td>[-1.8098601  4.385667 ]</td><td>[-1.7760859  4.4190483]</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>UMAP3D</strong></td><td>[ 3.9687433 11.975078   8.770226 ]</td><td>[ 4.0159307 11.924571   8.71211  ]</td><td>[ 4.0117636 11.935408   8.734231 ]</td><td>[ 4.018781 11.950559  8.7496  ]</td><td>[ 4.011503 11.935353  8.737354]</td><td>[ 4.009768 11.92584   8.701618]</td><td>[ 4.003745 11.951762  8.757965]</td><td>[ 4.006823 11.938546  8.738004]</td><td>[ 4.0158134 11.931681   8.732885 ]</td><td>[ 4.021581 11.918505  8.705254]</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>cDNA_Lib_Ok</strong></td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>ngperul_cDNA</strong></td><td>9,4</td><td>10,5</td><td>9,4</td><td>9,4</td><td>10,5</td><td>10,5</td><td>9,4</td><td>10,5</td><td>10,1</td><td>9,4</td><td>...</td></tr><tr><td><strong>Accession</strong></td><td><strong>Chromosome</strong></td><td><strong>End</strong></td><td><strong>Gamma</strong></td><td><strong>Gene</strong></td><td><strong>HPF</strong></td><td><strong>HPF_beta</strong></td><td><strong>MultilevelMarkers</strong></td><td><strong>Selected</strong></td><td><strong>Start</strong></td><td><strong>Strand</strong></td><td><strong>Valid</strong></td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>...</td></tr><tr><td>ENSMUSG00000038751</td><td>2</td><td>181202789</td><td>0.0</td><td>Ptk6</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0.]</td><td>0</td><td>181193721</td><td>-</td><td>1</td><td>&nbsp;</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>...</td></tr><tr><td>ENSMUSG00000030762</td><td>7</td><td>123468004</td><td>0.11823044717311859</td><td>Aqp8</td><td>[2.53021242e-05 7.84920473e-03 3.36675965e-05 3.68077717e-05\n",
       " 3.23020591e-05 3.56011849e-05 6.40611420e-03 3.55862126e-05\n",
       " 6.57725071e-05 3.88546881e-05 7.54039820e-05 4.30482745e-05\n",
       " 9.12159873e-04 4.82795377e-05 7.91420159e-05 5.96506170e-05\n",
       " 8.11080013e-05 3.29989544e-02 5.24548942e-05 8.49899107e-05\n",
       " 1.36967078e-01 1.14778577e-04 1.20345508e-04 1.19636572e-04\n",
       " 5.03367006e-05 1.18116405e-04 6.68605478e-05 6.17962796e-05\n",
       " 6.02759652e-05 1.06424321e-04 5.26811981e-05 1.15245462e-04\n",
       " 8.26296367e-02 1.16729680e-04 6.96691696e-05 1.06229099e-04\n",
       " 9.01420651e-05 1.41741327e-04 1.46311289e-04 1.45900397e-04\n",
       " 1.25861448e-04 4.06104148e-04 1.28447780e-04 1.53791796e-04\n",
       " 1.46540643e-04 7.48850023e-05 1.91510935e-02 4.39371400e-02\n",
       " 1.51741813e-04 1.51091692e-04 8.87008602e-05 3.42213393e-03\n",
       " 7.64365995e-05 1.40667453e-04 2.91403927e-02 1.85296247e-04\n",
       " 8.42023882e-05 1.87896040e-04 2.08507211e-04 1.44623675e-04\n",
       " 8.88849080e-02 3.82068212e-01 1.32469899e-04 8.75072240e-02\n",
       " 2.19922884e-04 2.09804204e-04 1.98435844e-04 1.15256964e-04\n",
       " 1.94467928e-04 2.69868266e-03 2.24126812e-04 2.25661150e-04\n",
       " 2.38276630e-04 2.01668238e-04 2.61588364e-04 1.07240129e-04\n",
       " 2.72638388e-04 2.31568587e-04 1.23656960e-04 2.53115152e-04\n",
       " 2.30290613e-04 1.11228879e-04 6.13757673e-02 7.65887164e-05\n",
       " 1.76360462e-04 1.45434428e-04 1.41309223e-04 3.22446389e-04\n",
       " 5.82831422e-05 7.26939787e-05 2.14731187e-05 1.10263073e-04\n",
       " 3.95672206e-03 1.42828834e-04 1.05421379e-04 8.40695384e-05]</td><td>[2.76637744e-10 8.58183396e-08 3.68100633e-10 4.02433362e-10\n",
       " 3.53170694e-10 3.89241290e-10 7.00404821e-08 3.89077592e-10\n",
       " 7.19115827e-10 4.24813077e-10 8.24420404e-10 4.70663152e-10\n",
       " 9.97299069e-09 5.27858541e-10 8.65289749e-10 6.52182874e-10\n",
       " 8.86784616e-10 3.60790115e-07 5.73509302e-10 9.29227007e-10\n",
       " 1.49751313e-06 1.25491782e-09 1.31578320e-09 1.30803213e-09\n",
       " 5.50350286e-10 1.29141156e-09 7.31011790e-10 6.75642220e-10\n",
       " 6.59020044e-10 1.16357756e-09 5.75983569e-10 1.26002245e-09\n",
       " 9.03421234e-07 1.27624998e-09 7.61719520e-10 1.16144312e-09\n",
       " 9.85557470e-10 1.54971182e-09 1.59967696e-09 1.59518451e-09\n",
       " 1.37609107e-09 4.44009105e-09 1.40436842e-09 1.68146417e-09\n",
       " 1.60218456e-09 8.18746202e-10 2.09386187e-07 4.80381457e-07\n",
       " 1.65905093e-09 1.65194292e-09 9.69800229e-10 3.74154913e-08\n",
       " 8.35710403e-10 1.53797074e-09 3.18602992e-07 2.02591432e-09\n",
       " 9.20616724e-10 2.05433884e-09 2.27968861e-09 1.58122562e-09\n",
       " 9.71812493e-07 4.17729702e-06 1.44834377e-09 9.56749750e-07\n",
       " 2.40450051e-09 2.29386913e-09 2.16957452e-09 1.26014821e-09\n",
       " 2.12619179e-09 2.95057236e-08 2.45046365e-09 2.46723915e-09\n",
       " 2.60516899e-09 2.20491552e-09 2.86004504e-09 1.17249710e-09\n",
       " 2.98085915e-09 2.53182740e-09 1.35198855e-09 2.76740419e-09\n",
       " 2.51785483e-09 1.21610762e-09 6.71044599e-07 8.37373555e-10\n",
       " 1.92821599e-09 1.59008990e-09 1.54498746e-09 3.52542897e-09\n",
       " 6.37231753e-10 7.94790907e-10 2.34773771e-10 1.20554810e-09\n",
       " 4.32603467e-08 1.56160195e-09 1.15261202e-09 9.19164227e-10]</td><td>[0. 0. 0. 0.]</td><td>1</td><td>123462291</td><td>+</td><td>1</td><td>&nbsp;</td><td>0.0</td><td>2.0</td><td>0.0</td><td>3.0</td><td>7.0</td><td>2.0</td><td>1.0</td><td>1.0</td><td>4.0</td><td>0.0</td><td>...</td></tr><tr><td>ENSMUSG00000035121</td><td>14</td><td>63193856</td><td>0.0</td><td>Neil2</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0.]</td><td>0</td><td>63182443</td><td>-</td><td>1</td><td>&nbsp;</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>...</td></tr><tr><td>ENSMUSG00000026478</td><td>1</td><td>153332786</td><td>0.0</td><td>Lamc1</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0.]</td><td>0</td><td>153218922</td><td>-</td><td>1</td><td>&nbsp;</td><td>0.0</td><td>11.0</td><td>7.0</td><td>2.0</td><td>8.0</td><td>4.0</td><td>16.0</td><td>10.0</td><td>10.0</td><td>8.0</td><td>...</td></tr><tr><td>ENSMUSG00000057092</td><td>7</td><td>31076704</td><td>0.0</td><td>Fxyd3</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0.]</td><td>0</td><td>31068172</td><td>-</td><td>1</td><td>&nbsp;</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>2.0</td><td>1.0</td><td>0.0</td><td>...</td></tr><tr><td>ENSMUSG00000032796</td><td>17</td><td>67822645</td><td>0.0</td><td>Lama1</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0.]</td><td>0</td><td>67697265</td><td>+</td><td>1</td><td>&nbsp;</td><td>2.0</td><td>15.0</td><td>22.0</td><td>1.0</td><td>19.0</td><td>10.0</td><td>12.0</td><td>9.0</td><td>11.0</td><td>12.0</td><td>...</td></tr><tr><td>ENSMUSG00000051022</td><td>5</td><td>39755475</td><td>0.0</td><td>Hs3st1</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0.]</td><td>0</td><td>39613935</td><td>-</td><td>1</td><td>&nbsp;</td><td>0.0</td><td>3.0</td><td>1.0</td><td>8.0</td><td>4.0</td><td>2.0</td><td>7.0</td><td>0.0</td><td>5.0</td><td>5.0</td><td>...</td></tr><tr><td>ENSMUSG00000028773</td><td>4</td><td>130315463</td><td>0.0</td><td>Fabp3</td><td>[1.23533804e-06 1.47350074e-06 1.64852313e-06 1.85132890e-06\n",
       " 1.66826891e-06 1.78144888e-06 1.62604754e-06 1.83620101e-06\n",
       " 1.44323961e-01 1.94652886e-06 9.94389649e-04 1.91062560e-06\n",
       " 1.80470888e-06 2.40434675e-06 1.89359487e-01 2.36428107e-06\n",
       " 8.07888426e-02 4.98005093e-05 2.35359670e-06 6.46994681e-03\n",
       " 8.62611062e-06 2.49042639e-02 2.88146115e-03 9.81383324e-03\n",
       " 2.74647040e-06 8.98334470e-04 6.54889806e-03 2.37676910e-02\n",
       " 7.17101490e-06 3.38203484e-03 2.69783646e-06 1.67094084e-01\n",
       " 1.42535264e-05 5.99337049e-02 3.33859326e-06 5.25942272e-06\n",
       " 4.15615995e-06 6.58414441e-06 1.39454497e-05 3.73730746e-02\n",
       " 5.75471175e-06 1.26977908e-05 1.50682111e-03 9.37412116e-06\n",
       " 7.08712701e-04 3.63607044e-06 4.17394833e-06 2.01965416e-04\n",
       " 1.59103545e-03 1.87357418e-05 1.14552520e-04 6.64048836e-02\n",
       " 4.15627251e-06 6.67246325e-06 4.20677080e-03 4.82448494e-03\n",
       " 4.02078436e-06 3.93987503e-04 5.77314587e-03 6.89184865e-06\n",
       " 5.15095321e-05 3.77624638e-06 1.07320075e-05 3.80978823e-04\n",
       " 5.39785637e-03 9.44260462e-06 6.39258281e-02 9.70786927e-04\n",
       " 6.13229319e-02 3.57716673e-03 1.07073881e-05 1.13490903e-03\n",
       " 1.81786072e-03 1.11396852e-05 1.05037119e-05 6.39084437e-06\n",
       " 6.15997336e-03 1.85582424e-04 5.77650637e-06 1.53166096e-03\n",
       " 2.02044660e-03 6.13744852e-03 5.45893456e-04 3.42416273e-06\n",
       " 1.28332215e-04 6.24574528e-06 6.52718364e-06 8.78120414e-06\n",
       " 2.68596325e-06 3.93945656e-06 1.16170475e-06 4.87437691e-06\n",
       " 3.88438796e-06 1.12015460e-04 4.32870816e-06 3.53196388e-06]</td><td>[3.23595067e-10 3.85981450e-10 4.31828321e-10 4.84953006e-10\n",
       " 4.37000699e-10 4.66648033e-10 4.25940871e-10 4.80990278e-10\n",
       " 3.78054591e-05 5.09890503e-10 2.60478973e-07 5.00485694e-10\n",
       " 4.72740959e-10 6.29815258e-10 4.96024519e-05 6.19320109e-10\n",
       " 2.11625240e-05 1.30451735e-08 6.16521353e-10 1.69479349e-06\n",
       " 2.25959757e-09 6.52363699e-06 7.54794705e-07 2.57071984e-06\n",
       " 7.19434067e-10 2.35317454e-07 1.71547466e-06 6.22591329e-06\n",
       " 1.87843729e-09 8.85919280e-07 7.06694475e-10 4.37700607e-05\n",
       " 3.73369125e-09 1.56995499e-05 8.74539819e-10 1.37769840e-09\n",
       " 1.08870027e-09 1.72470739e-09 3.65299098e-09 9.78982445e-06\n",
       " 1.50743867e-09 3.32616847e-09 3.94709674e-07 2.45553788e-09\n",
       " 1.85646297e-07 9.52463548e-10 1.09335991e-09 5.29045573e-08\n",
       " 4.16769504e-07 4.90780127e-09 3.00068719e-08 1.73946661e-05\n",
       " 1.08872975e-09 1.74784238e-09 1.10195771e-06 1.26376706e-06\n",
       " 1.05323882e-09 1.03204474e-07 1.51226746e-06 1.80531008e-09\n",
       " 1.34928497e-08 9.89182440e-10 2.81123431e-09 9.97968682e-08\n",
       " 1.41396090e-06 2.47347703e-09 1.67452810e-05 2.54296273e-07\n",
       " 1.60634559e-05 9.37033804e-07 2.80478530e-09 2.97287827e-07\n",
       " 4.76186065e-07 2.91802491e-09 2.75143258e-09 1.67407272e-09\n",
       " 1.61359638e-06 4.86130555e-08 1.51314774e-09 4.01216439e-07\n",
       " 5.29253151e-07 1.60769603e-06 1.42996025e-07 8.96954622e-10\n",
       " 3.36164437e-08 1.63606421e-09 1.70978659e-09 2.30022410e-09\n",
       " 7.03584304e-10 1.03193512e-09 3.04306929e-10 1.27683619e-09\n",
       " 1.01750998e-09 2.93422925e-08 1.13389903e-09 9.25192982e-10]</td><td>[0. 0. 0. 0.]</td><td>1</td><td>130308595</td><td>+</td><td>1</td><td>&nbsp;</td><td>3.0</td><td>0.0</td><td>14.0</td><td>8.0</td><td>15.0</td><td>11.0</td><td>21.0</td><td>2.0</td><td>24.0</td><td>1.0</td><td>...</td></tr><tr><td>ENSMUSG00000060275</td><td>18</td><td>36197380</td><td>0.0</td><td>Nrg2</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0.]</td><td>0</td><td>36017707</td><td>-</td><td>1</td><td>&nbsp;</td><td>0.0</td><td>0.0</td><td>1.0</td><td>0.0</td><td>1.0</td><td>3.0</td><td>0.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>...</td></tr><tr><td>ENSMUSG00000010830</td><td>15</td><td>79527739</td><td>0.0</td><td>Kdelr3</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0.]</td><td>0</td><td>79516411</td><td>+</td><td>1</td><td>&nbsp;</td><td>2.0</td><td>3.0</td><td>0.0</td><td>12.0</td><td>10.0</td><td>1.0</td><td>2.0</td><td>1.0</td><td>3.0</td><td>2.0</td><td>...</td></tr><tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr></table>"
      ],
      "text/plain": [
       "<loompy.loompy.LoomConnection at 0x2b8efc825a30>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_single_cells = loompy.connect(\"dev_all.loom\", validate = False)\n",
    "ds_single_cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "CountData_sc = pd.DataFrame(data = ds_single_cells[:,:], index = ds_single_cells.ra.Gene, columns=ds_single_cells.ca.ClusterName)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "stxbp1_counts_per_cell = CountData_sc.T[\"Stxbp1\"]\n",
    "aqp8_counts_per_cell = CountData_sc.T[\"Aqp8\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "dyrk1a_counts_per_cell = CountData_sc.T[\"Dyrk1a\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "47844.0"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(dyrk1a_counts_per_cell)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "stxbp1_per_ParEndo = stxbp1_counts_per_cell[\"ParEndo\"]\n",
    "aqp8_per_ParEndo =  aqp8_counts_per_cell[\"ParEndo\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.8181818181818181"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(aqp8_per_ParEndo)/11"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p>31053 rows, 798 columns, 3 layers<br/>(showing up to 10x10)<br/>dev_all.agg.loom<br/>name: <em>20210503T181815.387814Z</em><br/><table><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e10_0</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e11_0</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e12_0</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e12_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e13_0</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e13_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e14_0</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e14_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e15_0</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e15_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e16_0</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e16_25</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e16_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e17_0</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e17_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e18_0</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e7_0</strong></td><td>10</td><td>22</td><td>438</td><td>1</td><td>22</td><td>3</td><td>0</td><td>245</td><td>98</td><td>301</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e8_0</strong></td><td>1</td><td>4</td><td>0</td><td>48</td><td>56</td><td>60</td><td>21</td><td>2</td><td>0</td><td>2</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e8_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Age_e9_0</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>AutoAnnotation</strong></td><td>@CC EDEndo</td><td>@CC @Cldn ExVE Tropho</td><td>@CC @Cldn CrPr Tropho</td><td>@CC @Cldn EDEndo FGut Periderm</td><td>@CC EDEndo FGut Periderm RglFb</td><td>@CC EDEndo FGut Periderm RglFb</td><td>@CC @Cldn EDEndo FGut Periderm</td><td>@CC EDEndo ExVE Periderm</td><td>@CC DVE EDEndo ExVE Periderm</td><td>@CC @Cldn @IEG DVE EDEndo ExVE Periderm</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Class</strong></td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>Gastrulation</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>ClusterName</strong></td><td>ParEndo</td><td>nan</td><td>TrophEct</td><td>FGut4</td><td>FGut1</td><td>FGut3</td><td>FGut2</td><td>VEnd1</td><td>VEnd3</td><td>VEnd2</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Clusters</strong></td><td>0</td><td>1</td><td>2</td><td>3</td><td>4</td><td>5</td><td>6</td><td>7</td><td>8</td><td>9</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Location_E9_E11</strong></td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>MarkerGenes</strong></td><td>Srgn Dppa5a Gata4 Pth1r Tinagl1 Fxyd3</td><td>Rhox5 Zbtb7b Trap1a Apoc1 Zfp42 AC158554.1</td><td>Tex19.1 Elf5 Gjb3 Dppa4 Zfp42 AC158554.1</td><td>Apela Habp2 Hhex Car4 Dpp4 Rfx6</td><td>Apela Apoa1 Gpx2 Krt18 Cpn1 Pcbd1</td><td>Apela Plscr1 Hhex Krt18 Foxa3 Tnnc1</td><td>Pyy Nme2 Krt8 Krt18 Cpn1 Kdf1</td><td>Spink1 Eprn Trap1a Xlr3a Vil1 Fmr1nb</td><td>Pga5 Arid3c Cdkn2a Akr1c13 Pla2g12b Nxf7</td><td>Pga5 Fgfbp1 Cdkn2a Slc39a4 Amn Ctsh</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>MarkerRobustness</strong></td><td>1.0 1.0 1.0 1.0 1.0 1.0</td><td>1.0 0.97 0.97 0.97 0.94 0.94</td><td>1.0 1.0 1.0 1.0 1.0 1.0</td><td>1.0 1.0 1.0 1.0 1.0 1.0</td><td>1.0 0.99 0.99 0.99 0.99 0.99</td><td>1.0 0.96 0.96 0.96 0.95 0.91</td><td>1.0 0.99 0.99 0.99 0.97 0.94</td><td>1.0 1.0 1.0 1.0 1.0 1.0</td><td>1.0 0.97 0.97 0.97 0.97 0.97</td><td>1.0 1.0 1.0 1.0 1.0 1.0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>MarkerSelectivity</strong></td><td>16 2 1 1 1 1</td><td>26 1 1 1 1 1</td><td>27 2 1 1 1 1</td><td>22 1 1 1 1 1</td><td>13 1 1 1 1 1</td><td>17 1 1 1 1 1</td><td>17 1 1 1 1 1</td><td>12 1 1 1 1 1</td><td>22 1 1 1 1 1</td><td>51 1 1 1 1 1</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>MarkerSpecificity</strong></td><td>0.0 0.0041 0.69 0.75 0.81</td><td>7e-14 0.065 0.074 0.2 0.2</td><td>0.0 1.8e-07 0.67 0.67 1.0</td><td>0.0 0.1 0.17 0.17 0.39</td><td>0.0 0.92 0.99 0.99 0.99</td><td>0.0 0.03 0.03 0.03 0.9</td><td>0.0 0.14 0.26 0.26 0.84</td><td>0.0 0.48 0.48 0.5 0.5</td><td>0.0 0.28 0.28 0.3 0.3</td><td>0.0 0.062 0.062 0.062 0.062</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>NCells</strong></td><td>11</td><td>26</td><td>438</td><td>49</td><td>78</td><td>63</td><td>22</td><td>247</td><td>98</td><td>303</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Outliers</strong></td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X08_1</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X10_2</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X10_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X12_2</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X12_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X12_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X13_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X13_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X14_2</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X14_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X14_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X15_2</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X15_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X15_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X15_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X16_2</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X16_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X16_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X16_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X17_2</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X17_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X17_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X17_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X18_2</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X18_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X18_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X18_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nb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ID_10X29_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X30_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X30_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X31_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X32_2</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X32_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X32_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X32_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X32_6</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X37_2</strong></td><td>1</td><td>7</td><td>108</td><td>1</td><td>10</td><td>2</td><td>0</td><td>57</td><td>30</td><td>96</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X39_2</strong></td><td>5</td><td>11</td><td>161</td><td>0</td><td>6</td><td>0</td><td>0</td><td>96</td><td>33</td><td>100</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X39_3</strong></td><td>4</td><td>4</td><td>169</td><td>0</td><td>6</td><td>1</td><td>0</td><td>92</td><td>35</td><td>105</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X40_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X40_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X40_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X40_6</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X41_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X41_6</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X42_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X44_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X45_2</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X45_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X45_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X45_6</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X58_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X59_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X59_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X59_7</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X60_2</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X60_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X61_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X62_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X64_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X66_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X66_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X68_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X68_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X68_6</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X69_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X70_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X70_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X70_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X70_6</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X70_7</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X71_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X71_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X71_7</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X72_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X73_3</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X73_5</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X73_6</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>SampleID_10X74_4</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Sex_?</strong></td><td>11</td><td>26</td><td>438</td><td>49</td><td>78</td><td>63</td><td>22</td><td>247</td><td>98</td><td>303</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Subclass</strong></td><td>Parietal endoderm</td><td>Undefined</td><td>Extraembryonic ectoderm</td><td>Endoderm</td><td>Endoderm</td><td>Endoderm</td><td>Endoderm</td><td>Endoderm</td><td>Visceral endoderm</td><td>Visceral endoderm</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Tissue_All</strong></td><td>10</td><td>22</td><td>438</td><td>1</td><td>22</td><td>3</td><td>0</td><td>245</td><td>98</td><td>301</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Tissue_Forebrain</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Tissue_ForebrainDorsal</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Tissue_ForebrainVentral</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Tissue_ForebrainVentroLateral</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Tissue_ForebrainVentroThalamic</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Tissue_Head</strong></td><td>1</td><td>4</td><td>0</td><td>48</td><td>56</td><td>60</td><td>22</td><td>2</td><td>0</td><td>2</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Tissue_Hindbrain</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Tissue_Midbrain</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Tissue_MidbrainDorsal</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td><strong>Tissue_MidbrainVentral</strong></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>...</td></tr><tr><td><strong>Accession</strong></td><td><strong>Chromosome</strong></td><td><strong>End</strong></td><td><strong>Gamma</strong></td><td><strong>Gene</strong></td><td><strong>HPF</strong></td><td><strong>HPF_beta</strong></td><td><strong>MultilevelMarkers</strong></td><td><strong>Selected</strong></td><td><strong>Start</strong></td><td><strong>Strand</strong></td><td><strong>Valid</strong></td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>&nbsp;</td><td>...</td></tr><tr><td>ENSMUSG00000038751</td><td>2</td><td>181202789</td><td>0.0</td><td>Ptk6</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0.]</td><td>0</td><td>181193721</td><td>-</td><td>1</td><td>&nbsp;</td><td>0.09090909090909091</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>...</td></tr><tr><td>ENSMUSG00000030762</td><td>7</td><td>123468004</td><td>0.11823044717311859</td><td>Aqp8</td><td>[2.53021242e-05 7.84920473e-03 3.36675965e-05 3.68077717e-05\n",
       " 3.23020591e-05 3.56011849e-05 6.40611420e-03 3.55862126e-05\n",
       " 6.57725071e-05 3.88546881e-05 7.54039820e-05 4.30482745e-05\n",
       " 9.12159873e-04 4.82795377e-05 7.91420159e-05 5.96506170e-05\n",
       " 8.11080013e-05 3.29989544e-02 5.24548942e-05 8.49899107e-05\n",
       " 1.36967078e-01 1.14778577e-04 1.20345508e-04 1.19636572e-04\n",
       " 5.03367006e-05 1.18116405e-04 6.68605478e-05 6.17962796e-05\n",
       " 6.02759652e-05 1.06424321e-04 5.26811981e-05 1.15245462e-04\n",
       " 8.26296367e-02 1.16729680e-04 6.96691696e-05 1.06229099e-04\n",
       " 9.01420651e-05 1.41741327e-04 1.46311289e-04 1.45900397e-04\n",
       " 1.25861448e-04 4.06104148e-04 1.28447780e-04 1.53791796e-04\n",
       " 1.46540643e-04 7.48850023e-05 1.91510935e-02 4.39371400e-02\n",
       " 1.51741813e-04 1.51091692e-04 8.87008602e-05 3.42213393e-03\n",
       " 7.64365995e-05 1.40667453e-04 2.91403927e-02 1.85296247e-04\n",
       " 8.42023882e-05 1.87896040e-04 2.08507211e-04 1.44623675e-04\n",
       " 8.88849080e-02 3.82068212e-01 1.32469899e-04 8.75072240e-02\n",
       " 2.19922884e-04 2.09804204e-04 1.98435844e-04 1.15256964e-04\n",
       " 1.94467928e-04 2.69868266e-03 2.24126812e-04 2.25661150e-04\n",
       " 2.38276630e-04 2.01668238e-04 2.61588364e-04 1.07240129e-04\n",
       " 2.72638388e-04 2.31568587e-04 1.23656960e-04 2.53115152e-04\n",
       " 2.30290613e-04 1.11228879e-04 6.13757673e-02 7.65887164e-05\n",
       " 1.76360462e-04 1.45434428e-04 1.41309223e-04 3.22446389e-04\n",
       " 5.82831422e-05 7.26939787e-05 2.14731187e-05 1.10263073e-04\n",
       " 3.95672206e-03 1.42828834e-04 1.05421379e-04 8.40695384e-05]</td><td>[2.76637744e-10 8.58183396e-08 3.68100633e-10 4.02433362e-10\n",
       " 3.53170694e-10 3.89241290e-10 7.00404821e-08 3.89077592e-10\n",
       " 7.19115827e-10 4.24813077e-10 8.24420404e-10 4.70663152e-10\n",
       " 9.97299069e-09 5.27858541e-10 8.65289749e-10 6.52182874e-10\n",
       " 8.86784616e-10 3.60790115e-07 5.73509302e-10 9.29227007e-10\n",
       " 1.49751313e-06 1.25491782e-09 1.31578320e-09 1.30803213e-09\n",
       " 5.50350286e-10 1.29141156e-09 7.31011790e-10 6.75642220e-10\n",
       " 6.59020044e-10 1.16357756e-09 5.75983569e-10 1.26002245e-09\n",
       " 9.03421234e-07 1.27624998e-09 7.61719520e-10 1.16144312e-09\n",
       " 9.85557470e-10 1.54971182e-09 1.59967696e-09 1.59518451e-09\n",
       " 1.37609107e-09 4.44009105e-09 1.40436842e-09 1.68146417e-09\n",
       " 1.60218456e-09 8.18746202e-10 2.09386187e-07 4.80381457e-07\n",
       " 1.65905093e-09 1.65194292e-09 9.69800229e-10 3.74154913e-08\n",
       " 8.35710403e-10 1.53797074e-09 3.18602992e-07 2.02591432e-09\n",
       " 9.20616724e-10 2.05433884e-09 2.27968861e-09 1.58122562e-09\n",
       " 9.71812493e-07 4.17729702e-06 1.44834377e-09 9.56749750e-07\n",
       " 2.40450051e-09 2.29386913e-09 2.16957452e-09 1.26014821e-09\n",
       " 2.12619179e-09 2.95057236e-08 2.45046365e-09 2.46723915e-09\n",
       " 2.60516899e-09 2.20491552e-09 2.86004504e-09 1.17249710e-09\n",
       " 2.98085915e-09 2.53182740e-09 1.35198855e-09 2.76740419e-09\n",
       " 2.51785483e-09 1.21610762e-09 6.71044599e-07 8.37373555e-10\n",
       " 1.92821599e-09 1.59008990e-09 1.54498746e-09 3.52542897e-09\n",
       " 6.37231753e-10 7.94790907e-10 2.34773771e-10 1.20554810e-09\n",
       " 4.32603467e-08 1.56160195e-09 1.15261202e-09 9.19164227e-10]</td><td>[0.]</td><td>1</td><td>123462291</td><td>+</td><td>1</td><td>&nbsp;</td><td>1.8181818181818181</td><td>0.34615384615384615</td><td>0.0045662100456621</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.048582995951417005</td><td>0.030612244897959183</td><td>0.0627062706270627</td><td>...</td></tr><tr><td>ENSMUSG00000035121</td><td>14</td><td>63193856</td><td>0.0</td><td>Neil2</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0.]</td><td>0</td><td>63182443</td><td>-</td><td>1</td><td>&nbsp;</td><td>0.18181818181818182</td><td>0.07692307692307693</td><td>0.00684931506849315</td><td>0.0</td><td>0.01282051282051282</td><td>0.031746031746031744</td><td>0.045454545454545456</td><td>0.0</td><td>0.01020408163265306</td><td>0.026402640264026403</td><td>...</td></tr><tr><td>ENSMUSG00000026478</td><td>1</td><td>153332786</td><td>0.0</td><td>Lamc1</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0.]</td><td>0</td><td>153218922</td><td>-</td><td>1</td><td>&nbsp;</td><td>7.090909090909091</td><td>0.46153846153846156</td><td>0.22146118721461186</td><td>0.46938775510204084</td><td>0.0</td><td>0.0</td><td>0.09090909090909091</td><td>0.008097165991902834</td><td>0.01020408163265306</td><td>0.5643564356435643</td><td>...</td></tr><tr><td>ENSMUSG00000057092</td><td>7</td><td>31076704</td><td>0.0</td><td>Fxyd3</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0.]</td><td>0</td><td>31068172</td><td>-</td><td>1</td><td>&nbsp;</td><td>0.7272727272727273</td><td>0.038461538461538464</td><td>0.0045662100456621</td><td>0.3673469387755102</td><td>0.038461538461538464</td><td>0.031746031746031744</td><td>0.09090909090909091</td><td>0.02834008097165992</td><td>0.04081632653061224</td><td>0.1617161716171617</td><td>...</td></tr><tr><td>ENSMUSG00000032796</td><td>17</td><td>67822645</td><td>0.0</td><td>Lama1</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0.]</td><td>0</td><td>67697265</td><td>+</td><td>1</td><td>&nbsp;</td><td>10.727272727272727</td><td>0.2692307692307692</td><td>0.0091324200913242</td><td>0.30612244897959184</td><td>0.01282051282051282</td><td>0.015873015873015872</td><td>0.0</td><td>0.008097165991902834</td><td>0.0</td><td>0.264026402640264</td><td>...</td></tr><tr><td>ENSMUSG00000051022</td><td>5</td><td>39755475</td><td>0.0</td><td>Hs3st1</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0.]</td><td>0</td><td>39613935</td><td>-</td><td>1</td><td>&nbsp;</td><td>3.1818181818181817</td><td>0.0</td><td>0.05707762557077625</td><td>0.061224489795918366</td><td>0.01282051282051282</td><td>0.015873015873015872</td><td>0.045454545454545456</td><td>0.004048582995951417</td><td>0.0</td><td>0.006600660066006601</td><td>...</td></tr><tr><td>ENSMUSG00000028773</td><td>4</td><td>130315463</td><td>0.0</td><td>Fabp3</td><td>[1.23533804e-06 1.47350074e-06 1.64852313e-06 1.85132890e-06\n",
       " 1.66826891e-06 1.78144888e-06 1.62604754e-06 1.83620101e-06\n",
       " 1.44323961e-01 1.94652886e-06 9.94389649e-04 1.91062560e-06\n",
       " 1.80470888e-06 2.40434675e-06 1.89359487e-01 2.36428107e-06\n",
       " 8.07888426e-02 4.98005093e-05 2.35359670e-06 6.46994681e-03\n",
       " 8.62611062e-06 2.49042639e-02 2.88146115e-03 9.81383324e-03\n",
       " 2.74647040e-06 8.98334470e-04 6.54889806e-03 2.37676910e-02\n",
       " 7.17101490e-06 3.38203484e-03 2.69783646e-06 1.67094084e-01\n",
       " 1.42535264e-05 5.99337049e-02 3.33859326e-06 5.25942272e-06\n",
       " 4.15615995e-06 6.58414441e-06 1.39454497e-05 3.73730746e-02\n",
       " 5.75471175e-06 1.26977908e-05 1.50682111e-03 9.37412116e-06\n",
       " 7.08712701e-04 3.63607044e-06 4.17394833e-06 2.01965416e-04\n",
       " 1.59103545e-03 1.87357418e-05 1.14552520e-04 6.64048836e-02\n",
       " 4.15627251e-06 6.67246325e-06 4.20677080e-03 4.82448494e-03\n",
       " 4.02078436e-06 3.93987503e-04 5.77314587e-03 6.89184865e-06\n",
       " 5.15095321e-05 3.77624638e-06 1.07320075e-05 3.80978823e-04\n",
       " 5.39785637e-03 9.44260462e-06 6.39258281e-02 9.70786927e-04\n",
       " 6.13229319e-02 3.57716673e-03 1.07073881e-05 1.13490903e-03\n",
       " 1.81786072e-03 1.11396852e-05 1.05037119e-05 6.39084437e-06\n",
       " 6.15997336e-03 1.85582424e-04 5.77650637e-06 1.53166096e-03\n",
       " 2.02044660e-03 6.13744852e-03 5.45893456e-04 3.42416273e-06\n",
       " 1.28332215e-04 6.24574528e-06 6.52718364e-06 8.78120414e-06\n",
       " 2.68596325e-06 3.93945656e-06 1.16170475e-06 4.87437691e-06\n",
       " 3.88438796e-06 1.12015460e-04 4.32870816e-06 3.53196388e-06]</td><td>[3.23595067e-10 3.85981450e-10 4.31828321e-10 4.84953006e-10\n",
       " 4.37000699e-10 4.66648033e-10 4.25940871e-10 4.80990278e-10\n",
       " 3.78054591e-05 5.09890503e-10 2.60478973e-07 5.00485694e-10\n",
       " 4.72740959e-10 6.29815258e-10 4.96024519e-05 6.19320109e-10\n",
       " 2.11625240e-05 1.30451735e-08 6.16521353e-10 1.69479349e-06\n",
       " 2.25959757e-09 6.52363699e-06 7.54794705e-07 2.57071984e-06\n",
       " 7.19434067e-10 2.35317454e-07 1.71547466e-06 6.22591329e-06\n",
       " 1.87843729e-09 8.85919280e-07 7.06694475e-10 4.37700607e-05\n",
       " 3.73369125e-09 1.56995499e-05 8.74539819e-10 1.37769840e-09\n",
       " 1.08870027e-09 1.72470739e-09 3.65299098e-09 9.78982445e-06\n",
       " 1.50743867e-09 3.32616847e-09 3.94709674e-07 2.45553788e-09\n",
       " 1.85646297e-07 9.52463548e-10 1.09335991e-09 5.29045573e-08\n",
       " 4.16769504e-07 4.90780127e-09 3.00068719e-08 1.73946661e-05\n",
       " 1.08872975e-09 1.74784238e-09 1.10195771e-06 1.26376706e-06\n",
       " 1.05323882e-09 1.03204474e-07 1.51226746e-06 1.80531008e-09\n",
       " 1.34928497e-08 9.89182440e-10 2.81123431e-09 9.97968682e-08\n",
       " 1.41396090e-06 2.47347703e-09 1.67452810e-05 2.54296273e-07\n",
       " 1.60634559e-05 9.37033804e-07 2.80478530e-09 2.97287827e-07\n",
       " 4.76186065e-07 2.91802491e-09 2.75143258e-09 1.67407272e-09\n",
       " 1.61359638e-06 4.86130555e-08 1.51314774e-09 4.01216439e-07\n",
       " 5.29253151e-07 1.60769603e-06 1.42996025e-07 8.96954622e-10\n",
       " 3.36164437e-08 1.63606421e-09 1.70978659e-09 2.30022410e-09\n",
       " 7.03584304e-10 1.03193512e-09 3.04306929e-10 1.27683619e-09\n",
       " 1.01750998e-09 2.93422925e-08 1.13389903e-09 9.25192982e-10]</td><td>[0.]</td><td>1</td><td>130308595</td><td>+</td><td>1</td><td>&nbsp;</td><td>9.454545454545455</td><td>2.3846153846153846</td><td>6.755707762557078</td><td>0.061224489795918366</td><td>0.0</td><td>0.047619047619047616</td><td>0.0</td><td>0.016194331983805668</td><td>0.0</td><td>0.0462046204620462</td><td>...</td></tr><tr><td>ENSMUSG00000060275</td><td>18</td><td>36197380</td><td>0.0</td><td>Nrg2</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0.]</td><td>0</td><td>36017707</td><td>-</td><td>1</td><td>&nbsp;</td><td>0.5454545454545454</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>...</td></tr><tr><td>ENSMUSG00000010830</td><td>15</td><td>79527739</td><td>0.0</td><td>Kdelr3</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
       " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]</td><td>[0.]</td><td>0</td><td>79516411</td><td>+</td><td>1</td><td>&nbsp;</td><td>3.3636363636363638</td><td>0.6538461538461539</td><td>0.07534246575342465</td><td>0.3469387755102041</td><td>0.16666666666666666</td><td>0.14285714285714285</td><td>0.13636363636363635</td><td>0.13360323886639677</td><td>0.02040816326530612</td><td>0.21782178217821782</td><td>...</td></tr><tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr></table>"
      ],
      "text/plain": [
       "<loompy.loompy.LoomConnection at 0x2b8f49477f10>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_dev = loompy.connect(\"dev_all.agg.loom\", validate = False)\n",
    "ds_dev"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "ages = ds_dev.ca.keys()[0:20]\n",
    "ages = ages[-4:] +  ages[:-4] # right order\n",
    "CountData = pd.DataFrame(data = ds_dev[:,:], index = ds_dev.ra.Gene, columns=ds_dev.ca.ClusterName)\n",
    "metadata = {}\n",
    "for i in ages:\n",
    "    new = {i : ds_dev.ca[i]}\n",
    "    metadata.update(new)\n",
    "metadata = pd.DataFrame(metadata, index = ds_dev.ca.ClusterName).T\n",
    "classes = pd.DataFrame(ds_dev.ca.Class, index = ds_dev.ca.ClusterName).T\n",
    "classes_unique = classes.T[0].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "stxbp1_counts_per_cluster = CountData.T[\"Stxbp1\"]\n",
    "aqp8_counts_per_cluster = CountData.T[\"Aqp8\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "total_total_number_of_counts = np.sum(stxbp1_counts_per_cluster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ParEndo     0.090909\n",
       "nan         0.000000\n",
       "TrophEct    0.025114\n",
       "FGut4       0.020408\n",
       "FGut1       0.000000\n",
       "              ...   \n",
       "Neur793     0.293706\n",
       "Neur794     0.523810\n",
       "Neur795     0.245614\n",
       "Neur796     0.655172\n",
       "Neur797     0.416667\n",
       "Name: Stxbp1, Length: 798, dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stxbp1_counts_per_cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "aqp8_counts_per_cluster.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = metadata.append(CountData)\n",
    "df_small = metadata.append(stxbp1_counts_per_cluster)\n",
    "df_small = df_small.append(classes)\n",
    "df_small = df_small.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "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>ParEndo</th>\n",
       "      <th>nan</th>\n",
       "      <th>TrophEct</th>\n",
       "      <th>FGut4</th>\n",
       "      <th>FGut1</th>\n",
       "      <th>FGut3</th>\n",
       "      <th>FGut2</th>\n",
       "      <th>VEnd1</th>\n",
       "      <th>VEnd3</th>\n",
       "      <th>VEnd2</th>\n",
       "      <th>...</th>\n",
       "      <th>Neur788</th>\n",
       "      <th>Neur789</th>\n",
       "      <th>Neur790</th>\n",
       "      <th>Neur791</th>\n",
       "      <th>Neur792</th>\n",
       "      <th>Neur793</th>\n",
       "      <th>Neur794</th>\n",
       "      <th>Neur795</th>\n",
       "      <th>Neur796</th>\n",
       "      <th>Neur797</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Gastrulation</td>\n",
       "      <td>Gastrulation</td>\n",
       "      <td>Gastrulation</td>\n",
       "      <td>Gastrulation</td>\n",
       "      <td>Gastrulation</td>\n",
       "      <td>Gastrulation</td>\n",
       "      <td>Gastrulation</td>\n",
       "      <td>Gastrulation</td>\n",
       "      <td>Gastrulation</td>\n",
       "      <td>Gastrulation</td>\n",
       "      <td>...</td>\n",
       "      <td>Neuron</td>\n",
       "      <td>Neuron</td>\n",
       "      <td>Neuron</td>\n",
       "      <td>Neuron</td>\n",
       "      <td>Neuron</td>\n",
       "      <td>Neuron</td>\n",
       "      <td>Neuron</td>\n",
       "      <td>Neuron</td>\n",
       "      <td>Neuron</td>\n",
       "      <td>Neuron</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 798 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ParEndo           nan      TrophEct         FGut4         FGut1  \\\n",
       "0  Gastrulation  Gastrulation  Gastrulation  Gastrulation  Gastrulation   \n",
       "\n",
       "          FGut3         FGut2         VEnd1         VEnd3         VEnd2  ...  \\\n",
       "0  Gastrulation  Gastrulation  Gastrulation  Gastrulation  Gastrulation  ...   \n",
       "\n",
       "  Neur788 Neur789 Neur790 Neur791 Neur792 Neur793 Neur794 Neur795 Neur796  \\\n",
       "0  Neuron  Neuron  Neuron  Neuron  Neuron  Neuron  Neuron  Neuron  Neuron   \n",
       "\n",
       "  Neur797  \n",
       "0  Neuron  \n",
       "\n",
       "[1 rows x 798 columns]"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "counts_per_age_vector = np.zeros(len(ages))\n",
    "counts_per_cluster_per_age = np.zeros([len(ages),df_small.shape[0]])\n",
    "j = 0\n",
    "for i in ages:\n",
    "    for k in range(df_small.shape[0]):\n",
    "        counts_per_cluster_per_age[j,k] = df_small[i][k]*df_small[\"Stxbp1\"][k]\n",
    "        counts_per_age_vector[j] += counts_per_cluster_per_age[j,k] \n",
    "    j+= 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get Counts per Class per Age "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "counts_per_class_per_age = np.zeros([classes_unique.shape[0],len(ages)])\n",
    "counts_per_class_per_age = pd.DataFrame(counts_per_class_per_age, index = classes_unique, columns = ages).T\n",
    "\n",
    "j = 0\n",
    "for i in ages:\n",
    "    for k in range(df_small.shape[0]):\n",
    "        current_class = classes.T[0][k]\n",
    "        counts_per_class_per_age[current_class][j] += df_small[i][k]*df_small[\"Stxbp1\"][k]\n",
    "    j+= 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gastrulation</th>\n",
       "      <th>Radial glia</th>\n",
       "      <th>Mesenchyme</th>\n",
       "      <th>Neural tube</th>\n",
       "      <th>Mesoderm</th>\n",
       "      <th>Neural crest</th>\n",
       "      <th>Bad cells</th>\n",
       "      <th>Endoderm</th>\n",
       "      <th>Ectoderm</th>\n",
       "      <th>Blood</th>\n",
       "      <th>...</th>\n",
       "      <th>Choroid plexus</th>\n",
       "      <th>Ependymal</th>\n",
       "      <th>Pineal gland</th>\n",
       "      <th>Subcommissural organ</th>\n",
       "      <th>Olfactory ensheathing cell</th>\n",
       "      <th>Schwann cell</th>\n",
       "      <th>Oligodendrocyte</th>\n",
       "      <th>Neuroblast</th>\n",
       "      <th>Undefined</th>\n",
       "      <th>Neuron</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Age_e7_0</th>\n",
       "      <td>496.836378</td>\n",
       "      <td>0.100604</td>\n",
       "      <td>0.088729</td>\n",
       "      <td>0.325112</td>\n",
       "      <td>0.947373</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.071522</td>\n",
       "      <td>0.299107</td>\n",
       "      <td>0.173593</td>\n",
       "      <td>1.579847</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>0.000000</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>Age_e8_0</th>\n",
       "      <td>59.211207</td>\n",
       "      <td>12.198076</td>\n",
       "      <td>11.665957</td>\n",
       "      <td>286.025668</td>\n",
       "      <td>79.389134</td>\n",
       "      <td>55.753663</td>\n",
       "      <td>9.423270</td>\n",
       "      <td>7.734017</td>\n",
       "      <td>15.352892</td>\n",
       "      <td>4.091758</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.874442</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e8_5</th>\n",
       "      <td>4.216791</td>\n",
       "      <td>26.347285</td>\n",
       "      <td>27.589306</td>\n",
       "      <td>41.718828</td>\n",
       "      <td>59.181616</td>\n",
       "      <td>78.529691</td>\n",
       "      <td>10.841760</td>\n",
       "      <td>0.327491</td>\n",
       "      <td>2.114473</td>\n",
       "      <td>1.688706</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>41.570599</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e9_0</th>\n",
       "      <td>1.254664</td>\n",
       "      <td>639.311877</td>\n",
       "      <td>341.547636</td>\n",
       "      <td>60.179862</td>\n",
       "      <td>10.622369</td>\n",
       "      <td>37.946269</td>\n",
       "      <td>46.445336</td>\n",
       "      <td>0.540289</td>\n",
       "      <td>21.852432</td>\n",
       "      <td>6.619810</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>643.117360</td>\n",
       "      <td>8.301775</td>\n",
       "      <td>4.930411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e10_0</th>\n",
       "      <td>0.700996</td>\n",
       "      <td>1013.044431</td>\n",
       "      <td>552.165124</td>\n",
       "      <td>65.938998</td>\n",
       "      <td>4.997423</td>\n",
       "      <td>35.215188</td>\n",
       "      <td>112.401166</td>\n",
       "      <td>0.099096</td>\n",
       "      <td>26.228474</td>\n",
       "      <td>19.764341</td>\n",
       "      <td>...</td>\n",
       "      <td>1.612903</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",
       "      <td>0.000000</td>\n",
       "      <td>1584.710847</td>\n",
       "      <td>14.153846</td>\n",
       "      <td>135.527282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e11_0</th>\n",
       "      <td>0.569451</td>\n",
       "      <td>391.890750</td>\n",
       "      <td>48.427860</td>\n",
       "      <td>0.240462</td>\n",
       "      <td>0.862085</td>\n",
       "      <td>1.067194</td>\n",
       "      <td>4.948978</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.310995</td>\n",
       "      <td>21.595093</td>\n",
       "      <td>...</td>\n",
       "      <td>1.917155</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.788618</td>\n",
       "      <td>0.379310</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1815.411278</td>\n",
       "      <td>0.136095</td>\n",
       "      <td>2240.368219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e12_0</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>508.855304</td>\n",
       "      <td>18.790060</td>\n",
       "      <td>0.112710</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.237154</td>\n",
       "      <td>0.868574</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.863554</td>\n",
       "      <td>25.855168</td>\n",
       "      <td>...</td>\n",
       "      <td>5.565822</td>\n",
       "      <td>0.324786</td>\n",
       "      <td>1.577236</td>\n",
       "      <td>0.379310</td>\n",
       "      <td>0.441176</td>\n",
       "      <td>0.921503</td>\n",
       "      <td>0.587283</td>\n",
       "      <td>1844.453965</td>\n",
       "      <td>0.408284</td>\n",
       "      <td>5703.497571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e12_5</th>\n",
       "      <td>0.072581</td>\n",
       "      <td>110.386911</td>\n",
       "      <td>1.239123</td>\n",
       "      <td>0.338129</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.612460</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.737386</td>\n",
       "      <td>...</td>\n",
       "      <td>1.050999</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.156925</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>460.699495</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>847.026798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e13_0</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>43.935753</td>\n",
       "      <td>0.127981</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.132265</td>\n",
       "      <td>0.087494</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.940064</td>\n",
       "      <td>...</td>\n",
       "      <td>0.201613</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.704266</td>\n",
       "      <td>1.190728</td>\n",
       "      <td>1.471146</td>\n",
       "      <td>660.706625</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3567.106670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e13_5</th>\n",
       "      <td>0.072581</td>\n",
       "      <td>203.329818</td>\n",
       "      <td>1.217161</td>\n",
       "      <td>0.120231</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.777705</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.012676</td>\n",
       "      <td>11.259028</td>\n",
       "      <td>...</td>\n",
       "      <td>0.974260</td>\n",
       "      <td>0.672414</td>\n",
       "      <td>1.276423</td>\n",
       "      <td>1.517241</td>\n",
       "      <td>0.220588</td>\n",
       "      <td>2.299255</td>\n",
       "      <td>4.554483</td>\n",
       "      <td>1128.873655</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4540.553646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e14_0</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>30.023070</td>\n",
       "      <td>0.455312</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.118577</td>\n",
       "      <td>0.019438</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>23.786914</td>\n",
       "      <td>...</td>\n",
       "      <td>10.882734</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>11.850923</td>\n",
       "      <td>10.840975</td>\n",
       "      <td>403.981144</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2890.368276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e14_5</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>120.041607</td>\n",
       "      <td>0.522150</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.217096</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.152329</td>\n",
       "      <td>...</td>\n",
       "      <td>2.718567</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.154472</td>\n",
       "      <td>1.706897</td>\n",
       "      <td>1.544118</td>\n",
       "      <td>0.105691</td>\n",
       "      <td>3.479912</td>\n",
       "      <td>812.247333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4548.019275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e15_0</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>113.673141</td>\n",
       "      <td>0.305439</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.132881</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>35.298574</td>\n",
       "      <td>...</td>\n",
       "      <td>40.924410</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.821138</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.530933</td>\n",
       "      <td>11.849112</td>\n",
       "      <td>25.102779</td>\n",
       "      <td>1140.330398</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5576.685823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e15_5</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>46.619111</td>\n",
       "      <td>0.127981</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.051850</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.106684</td>\n",
       "      <td>...</td>\n",
       "      <td>1.713103</td>\n",
       "      <td>1.994400</td>\n",
       "      <td>2.276423</td>\n",
       "      <td>2.275862</td>\n",
       "      <td>2.138504</td>\n",
       "      <td>0.105691</td>\n",
       "      <td>8.830002</td>\n",
       "      <td>375.763728</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3177.674858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e16_0</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>53.058082</td>\n",
       "      <td>0.336011</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.016206</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>42.624809</td>\n",
       "      <td>...</td>\n",
       "      <td>16.573281</td>\n",
       "      <td>14.291430</td>\n",
       "      <td>2.455285</td>\n",
       "      <td>2.844828</td>\n",
       "      <td>0.310345</td>\n",
       "      <td>7.798883</td>\n",
       "      <td>37.922699</td>\n",
       "      <td>391.966166</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6072.632889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e16_25</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.948869</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",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.261177</td>\n",
       "      <td>...</td>\n",
       "      <td>0.732978</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.297893</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.250458</td>\n",
       "      <td>144.540557</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1419.922882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e16_5</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>44.501230</td>\n",
       "      <td>0.088729</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",
       "      <td>0.000000</td>\n",
       "      <td>11.061684</td>\n",
       "      <td>...</td>\n",
       "      <td>10.451649</td>\n",
       "      <td>1.180241</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.948276</td>\n",
       "      <td>8.779040</td>\n",
       "      <td>2.853702</td>\n",
       "      <td>41.075645</td>\n",
       "      <td>565.563016</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4523.385641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e17_0</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>60.830652</td>\n",
       "      <td>0.088729</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.032412</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>40.515283</td>\n",
       "      <td>...</td>\n",
       "      <td>39.956967</td>\n",
       "      <td>35.966228</td>\n",
       "      <td>11.373984</td>\n",
       "      <td>6.258621</td>\n",
       "      <td>4.984039</td>\n",
       "      <td>2.037890</td>\n",
       "      <td>59.459240</td>\n",
       "      <td>487.794594</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8168.077503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e17_5</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>38.628721</td>\n",
       "      <td>0.127981</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.035644</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.587016</td>\n",
       "      <td>...</td>\n",
       "      <td>39.583676</td>\n",
       "      <td>5.105191</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.568966</td>\n",
       "      <td>6.253964</td>\n",
       "      <td>2.523412</td>\n",
       "      <td>49.800375</td>\n",
       "      <td>421.859541</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2854.576856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_e18_0</th>\n",
       "      <td>0.065352</td>\n",
       "      <td>82.274707</td>\n",
       "      <td>0.088729</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.016206</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.090909</td>\n",
       "      <td>55.474327</td>\n",
       "      <td>...</td>\n",
       "      <td>22.139884</td>\n",
       "      <td>59.465309</td>\n",
       "      <td>5.276423</td>\n",
       "      <td>5.120690</td>\n",
       "      <td>24.795134</td>\n",
       "      <td>2.708463</td>\n",
       "      <td>176.625005</td>\n",
       "      <td>837.535257</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9191.645400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Gastrulation  Radial glia  Mesenchyme  Neural tube   Mesoderm  \\\n",
       "Age_e7_0      496.836378     0.100604    0.088729     0.325112   0.947373   \n",
       "Age_e8_0       59.211207    12.198076   11.665957   286.025668  79.389134   \n",
       "Age_e8_5        4.216791    26.347285   27.589306    41.718828  59.181616   \n",
       "Age_e9_0        1.254664   639.311877  341.547636    60.179862  10.622369   \n",
       "Age_e10_0       0.700996  1013.044431  552.165124    65.938998   4.997423   \n",
       "Age_e11_0       0.569451   391.890750   48.427860     0.240462   0.862085   \n",
       "Age_e12_0       0.000000   508.855304   18.790060     0.112710   0.000000   \n",
       "Age_e12_5       0.072581   110.386911    1.239123     0.338129   0.000000   \n",
       "Age_e13_0       0.000000    43.935753    0.127981     0.000000   0.000000   \n",
       "Age_e13_5       0.072581   203.329818    1.217161     0.120231   0.000000   \n",
       "Age_e14_0       0.000000    30.023070    0.455312     0.000000   0.000000   \n",
       "Age_e14_5       0.000000   120.041607    0.522150     0.000000   0.000000   \n",
       "Age_e15_0       0.000000   113.673141    0.305439     0.000000   0.000000   \n",
       "Age_e15_5       0.000000    46.619111    0.127981     0.000000   0.000000   \n",
       "Age_e16_0       0.000000    53.058082    0.336011     0.000000   0.000000   \n",
       "Age_e16_25      0.000000     4.948869    0.000000     0.000000   0.000000   \n",
       "Age_e16_5       0.000000    44.501230    0.088729     0.000000   0.000000   \n",
       "Age_e17_0       0.000000    60.830652    0.088729     0.000000   0.000000   \n",
       "Age_e17_5       0.000000    38.628721    0.127981     0.000000   0.000000   \n",
       "Age_e18_0       0.065352    82.274707    0.088729     0.000000   0.000000   \n",
       "\n",
       "            Neural crest   Bad cells  Endoderm   Ectoderm      Blood  ...  \\\n",
       "Age_e7_0        0.000000    0.071522  0.299107   0.173593   1.579847  ...   \n",
       "Age_e8_0       55.753663    9.423270  7.734017  15.352892   4.091758  ...   \n",
       "Age_e8_5       78.529691   10.841760  0.327491   2.114473   1.688706  ...   \n",
       "Age_e9_0       37.946269   46.445336  0.540289  21.852432   6.619810  ...   \n",
       "Age_e10_0      35.215188  112.401166  0.099096  26.228474  19.764341  ...   \n",
       "Age_e11_0       1.067194    4.948978  0.000000   0.310995  21.595093  ...   \n",
       "Age_e12_0       0.237154    0.868574  0.000000   0.863554  25.855168  ...   \n",
       "Age_e12_5       0.000000    0.612460  0.000000   0.000000   3.737386  ...   \n",
       "Age_e13_0       0.132265    0.087494  0.000000   0.000000   2.940064  ...   \n",
       "Age_e13_5       0.000000    0.777705  0.000000   0.012676  11.259028  ...   \n",
       "Age_e14_0       0.118577    0.019438  0.000000   0.000000  23.786914  ...   \n",
       "Age_e14_5       0.000000    0.217096  0.000000   0.000000   4.152329  ...   \n",
       "Age_e15_0       0.000000    0.132881  0.000000   0.000000  35.298574  ...   \n",
       "Age_e15_5       0.000000    0.051850  0.000000   0.000000   6.106684  ...   \n",
       "Age_e16_0       0.000000    0.016206  0.000000   0.000000  42.624809  ...   \n",
       "Age_e16_25      0.000000    0.000000  0.000000   0.000000   3.261177  ...   \n",
       "Age_e16_5       0.000000    0.000000  0.000000   0.000000  11.061684  ...   \n",
       "Age_e17_0       0.000000    0.032412  0.000000   0.000000  40.515283  ...   \n",
       "Age_e17_5       0.000000    0.035644  0.000000   0.000000   9.587016  ...   \n",
       "Age_e18_0       0.000000    0.016206  0.000000   0.090909  55.474327  ...   \n",
       "\n",
       "            Choroid plexus  Ependymal  Pineal gland  Subcommissural organ  \\\n",
       "Age_e7_0          0.000000   0.000000      0.000000              0.000000   \n",
       "Age_e8_0          0.000000   0.000000      0.000000              0.000000   \n",
       "Age_e8_5          0.000000   0.000000      0.000000              0.000000   \n",
       "Age_e9_0          0.000000   0.000000      0.000000              0.000000   \n",
       "Age_e10_0         1.612903   0.000000      0.000000              0.000000   \n",
       "Age_e11_0         1.917155   0.000000      0.788618              0.379310   \n",
       "Age_e12_0         5.565822   0.324786      1.577236              0.379310   \n",
       "Age_e12_5         1.050999   0.000000      0.000000              0.000000   \n",
       "Age_e13_0         0.201613   0.000000      0.000000              0.000000   \n",
       "Age_e13_5         0.974260   0.672414      1.276423              1.517241   \n",
       "Age_e14_0        10.882734   0.000000      0.000000              0.000000   \n",
       "Age_e14_5         2.718567   0.000000      1.154472              1.706897   \n",
       "Age_e15_0        40.924410   0.000000      0.821138              0.000000   \n",
       "Age_e15_5         1.713103   1.994400      2.276423              2.275862   \n",
       "Age_e16_0        16.573281  14.291430      2.455285              2.844828   \n",
       "Age_e16_25        0.732978   0.000000      0.000000              0.000000   \n",
       "Age_e16_5        10.451649   1.180241      0.000000              0.948276   \n",
       "Age_e17_0        39.956967  35.966228     11.373984              6.258621   \n",
       "Age_e17_5        39.583676   5.105191      0.000000              0.568966   \n",
       "Age_e18_0        22.139884  59.465309      5.276423              5.120690   \n",
       "\n",
       "            Olfactory ensheathing cell  Schwann cell  Oligodendrocyte  \\\n",
       "Age_e7_0                      0.000000      0.000000         0.000000   \n",
       "Age_e8_0                      0.000000      0.000000         0.000000   \n",
       "Age_e8_5                      0.000000      0.000000         0.000000   \n",
       "Age_e9_0                      0.000000      0.000000         0.000000   \n",
       "Age_e10_0                     0.000000      0.000000         0.000000   \n",
       "Age_e11_0                     0.000000      0.597822         0.000000   \n",
       "Age_e12_0                     0.441176      0.921503         0.587283   \n",
       "Age_e12_5                     0.000000      0.156925         0.000000   \n",
       "Age_e13_0                     0.704266      1.190728         1.471146   \n",
       "Age_e13_5                     0.220588      2.299255         4.554483   \n",
       "Age_e14_0                     0.000000     11.850923        10.840975   \n",
       "Age_e14_5                     1.544118      0.105691         3.479912   \n",
       "Age_e15_0                     0.530933     11.849112        25.102779   \n",
       "Age_e15_5                     2.138504      0.105691         8.830002   \n",
       "Age_e16_0                     0.310345      7.798883        37.922699   \n",
       "Age_e16_25                    2.297893      0.000000         5.250458   \n",
       "Age_e16_5                     8.779040      2.853702        41.075645   \n",
       "Age_e17_0                     4.984039      2.037890        59.459240   \n",
       "Age_e17_5                     6.253964      2.523412        49.800375   \n",
       "Age_e18_0                    24.795134      2.708463       176.625005   \n",
       "\n",
       "             Neuroblast  Undefined       Neuron  \n",
       "Age_e7_0       0.000000   0.000000     0.000000  \n",
       "Age_e8_0       1.874442   0.000000     0.000000  \n",
       "Age_e8_5      41.570599   0.000000     0.000000  \n",
       "Age_e9_0     643.117360   8.301775     4.930411  \n",
       "Age_e10_0   1584.710847  14.153846   135.527282  \n",
       "Age_e11_0   1815.411278   0.136095  2240.368219  \n",
       "Age_e12_0   1844.453965   0.408284  5703.497571  \n",
       "Age_e12_5    460.699495   0.000000   847.026798  \n",
       "Age_e13_0    660.706625   0.000000  3567.106670  \n",
       "Age_e13_5   1128.873655   0.000000  4540.553646  \n",
       "Age_e14_0    403.981144   0.000000  2890.368276  \n",
       "Age_e14_5    812.247333   0.000000  4548.019275  \n",
       "Age_e15_0   1140.330398   0.000000  5576.685823  \n",
       "Age_e15_5    375.763728   0.000000  3177.674858  \n",
       "Age_e16_0    391.966166   0.000000  6072.632889  \n",
       "Age_e16_25   144.540557   0.000000  1419.922882  \n",
       "Age_e16_5    565.563016   0.000000  4523.385641  \n",
       "Age_e17_0    487.794594   0.000000  8168.077503  \n",
       "Age_e17_5    421.859541   0.000000  2854.576856  \n",
       "Age_e18_0    837.535257   0.000000  9191.645400  \n",
       "\n",
       "[20 rows x 24 columns]"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts_per_class_per_age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8385.254324642907"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(counts_per_class_per_age.loc[\"Age_e12_0\",:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "number_of_cells_per_cluster = np.zeros(df_small.shape[0])\n",
    "for i in range(df_small.shape[0]):\n",
    "    for k in ages: \n",
    "        number_of_cells_per_cluster[i] += df_small[k][i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "number_of_cells_per_cluster \n",
    "number_of_cells_total = np.sum(number_of_cells_per_cluster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "ages_number = [7,8, 8.5 ,9,10,11,12, 12.5 ,13, 13.5, 14, 14.5, 15, 15.5 ,16, 16.25, 16.5, 17, 17.5, 18]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2ba03fc31070>]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = plt.axes()\n",
    "ax.plot(ages_number, counts_per_age_vector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 4320x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(60,20))\n",
    "heat_map = sns.heatmap(counts_per_class_per_age, linewidth = 0.1 , annot = True, vmax = 1000)\n",
    "plt.title( \"HeatMap for Stxbp1 Counts per Cluster per Age\" )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "701.4462081128747"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts_per_cluster_per_age.max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get Ages of Cells as Index and plot Stxbp1 Counts per Age again based on SC Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "CountData_sc_ages = pd.DataFrame(data = ds_single_cells[:,:], index = ds_single_cells.ra.Gene, columns=ds_single_cells.ca.Age)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "CountData_sc_ages_Stxbp1 = CountData_sc_ages.T.Stxbp1\n",
    "counts_per_age_vector_sc = np.zeros(len(ages))\n",
    "j = 0 \n",
    "ages_modified = [f[4:] for f in ages]\n",
    "ages_modified = [f.replace(\"_\",\".\") for f in ages_modified]\n",
    "for i in ages_modified: \n",
    "    counts_per_age_vector_sc[j] = np.sum(CountData_sc_ages_Stxbp1[i])\n",
    "    j += 1\n",
    "counts_per_age_vector_sc = pd.DataFrame(counts_per_age_vector_sc, index = ages_modified, columns = [\"Total Counts of Stxbp1\"])\n",
    "age_df = pd.DataFrame(ages_number, index=ages_modified, columns=[\"Ages in Embryonic Days\"])\n",
    "counts_per_age_vector_sc = pd.concat([counts_per_age_vector_sc, age_df], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2ba042ebac10>"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(font_scale = 1, rc={\"figure.figsize\":(13, 8)})\n",
    "sns.lineplot(data=counts_per_age_vector_sc, x = \"Ages in Embryonic Days\", y = \"Total Counts of Stxbp1\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Normalize per Age "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "cells_per_age = np.zeros(len(ages)) \n",
    "counts_per_age_normalized  = np.zeros(len(ages)) \n",
    "j = 0 \n",
    "for i in ages_modified:\n",
    "    cells_per_age[j] = CountData_sc_ages_Stxbp1[i].shape[0]\n",
    "    counts_per_age_normalized[j] = counts_per_age_vector_sc[\"Total Counts of Stxbp1\"][j]/cells_per_age[j]\n",
    "    j += 1\n",
    "counts_per_age_normalized = pd.DataFrame(counts_per_age_normalized, index=ages_modified, columns=[\"Counts Normalized by Cells per Age\"])\n",
    "counts_per_age_vector_sc = pd.concat([counts_per_age_vector_sc, counts_per_age_normalized], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "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>Total Counts of Stxbp1</th>\n",
       "      <th>Ages in Embryonic Days</th>\n",
       "      <th>Counts Normalized by Cells per Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>e7.0</th>\n",
       "      <td>502.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.038672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e8.0</th>\n",
       "      <td>653.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.085270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e8.5</th>\n",
       "      <td>293.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.086507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e9.0</th>\n",
       "      <td>2363.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.147937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e10.0</th>\n",
       "      <td>3511.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.116089</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Total Counts of Stxbp1  Ages in Embryonic Days  \\\n",
       "e7.0                    502.0                     7.0   \n",
       "e8.0                    653.0                     8.0   \n",
       "e8.5                    293.0                     8.5   \n",
       "e9.0                   2363.0                     9.0   \n",
       "e10.0                  3511.0                    10.0   \n",
       "\n",
       "       Counts Normalized by Cells per Age  \n",
       "e7.0                             0.038672  \n",
       "e8.0                             0.085270  \n",
       "e8.5                             0.086507  \n",
       "e9.0                             0.147937  \n",
       "e10.0                            0.116089  "
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts_per_age_vector_sc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2ba042ba43a0>"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(font_scale = 1, rc={\"figure.figsize\":(13, 8)})\n",
    "sns.lineplot(data=counts_per_age_vector_sc, x = \"Ages in Embryonic Days\", y = \"Counts Normalized by Cells per Age\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "502.0"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts_per_age_vector_sc[\"Total Counts of Stxbp1\"][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "/gnu/store/nckjv3ccwdi6096j478gvns43ssbls2p-python-wrapper-3.8.2/bin/python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}