synthetic scRNA-Seq from star network.ipynb

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    "# Synthetic expression data from asynchronous random walks on star network\n",
    "\n",
    "In this series of notebooks, we demonstrate how scBoolSeq can be employed to generate synthetic scRNA-Seq datasets from Boolean states of trajectories of mechanistic Boolean models.\n",
    "\n",
    "This notebook focuses on a toy model where a transcription factor progressively activates its target genes."
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    "from IPython.display import display, HTML\n",
    "display(HTML(\"<style>.container { width:100% !important; }</style>\"))\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import random\n",
    "from colomoto.minibn import * # for Boolean network manipulation\n",
    "from scboolseq import scBoolSeq\n",
    "\n",
    "# set seed for reproducible results\n",
    "_rng_seed = 19834650\n",
    "# use a Generator instead of numpy's singleton\n",
    "_rng = np.random.default_rng(_rng_seed)\n",
    "random.seed(_rng_seed)"
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   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "## Load Boolean network model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4a9e3bae",
   "metadata": {},
   "outputs": [
    {
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       "gene1 <- tf\n",
       "gene10 <- tf\n",
       "gene2 <- tf\n",
       "gene3 <- tf\n",
       "gene4 <- tf\n",
       "gene5 <- tf\n",
       "gene6 <- tf\n",
       "gene7 <- tf\n",
       "gene8 <- tf\n",
       "gene9 <- tf\n",
       "tf <- 1"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bn = BooleanNetwork.load(\"models/star.bnet\")\n",
    "bn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "09653812",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# computing graph layout...\n"
     ]
    },
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       "</g>\n",
       "<!-- gene4 -->\n",
       "<g id=\"node5\" class=\"node\">\n",
       "<title>gene4</title>\n",
       "<ellipse fill=\"none\" stroke=\"black\" cx=\"344.74\" cy=\"-18\" rx=\"41.74\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"344.74\" y=\"-13.32\" font-family=\"Times,serif\" font-size=\"14.00\">gene4</text>\n",
       "</g>\n",
       "<!-- tf&#45;&gt;gene4 -->\n",
       "<g id=\"edge4\" class=\"edge\">\n",
       "<title>tf&#45;&gt;gene4</title>\n",
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       "<text text-anchor=\"middle\" x=\"445.74\" y=\"-13.32\" font-family=\"Times,serif\" font-size=\"14.00\">gene5</text>\n",
       "</g>\n",
       "<!-- tf&#45;&gt;gene5 -->\n",
       "<g id=\"edge1\" class=\"edge\">\n",
       "<title>tf&#45;&gt;gene5</title>\n",
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       "</g>\n",
       "<!-- gene6 -->\n",
       "<g id=\"node7\" class=\"node\">\n",
       "<title>gene6</title>\n",
       "<ellipse fill=\"none\" stroke=\"black\" cx=\"546.74\" cy=\"-18\" rx=\"41.74\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"546.74\" y=\"-13.32\" font-family=\"Times,serif\" font-size=\"14.00\">gene6</text>\n",
       "</g>\n",
       "<!-- tf&#45;&gt;gene6 -->\n",
       "<g id=\"edge2\" class=\"edge\">\n",
       "<title>tf&#45;&gt;gene6</title>\n",
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       "</g>\n",
       "<!-- gene7 -->\n",
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       "</g>\n",
       "<!-- tf&#45;&gt;gene7 -->\n",
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       "<title>tf&#45;&gt;gene7</title>\n",
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       "<!-- gene8 -->\n",
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       "<title>gene8</title>\n",
       "<ellipse fill=\"none\" stroke=\"black\" cx=\"748.74\" cy=\"-18\" rx=\"41.74\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"748.74\" y=\"-13.32\" font-family=\"Times,serif\" font-size=\"14.00\">gene8</text>\n",
       "</g>\n",
       "<!-- tf&#45;&gt;gene8 -->\n",
       "<g id=\"edge6\" class=\"edge\">\n",
       "<title>tf&#45;&gt;gene8</title>\n",
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       "<text text-anchor=\"middle\" x=\"656.74\" y=\"-57.95\" font-family=\"Times,serif\" font-size=\"14.00\">+</text>\n",
       "</g>\n",
       "<!-- gene9 -->\n",
       "<g id=\"node10\" class=\"node\">\n",
       "<title>gene9</title>\n",
       "<ellipse fill=\"none\" stroke=\"black\" cx=\"849.74\" cy=\"-18\" rx=\"41.74\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"849.74\" y=\"-13.32\" font-family=\"Times,serif\" font-size=\"14.00\">gene9</text>\n",
       "</g>\n",
       "<!-- tf&#45;&gt;gene9 -->\n",
       "<g id=\"edge7\" class=\"edge\">\n",
       "<title>tf&#45;&gt;gene9</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M521.62,-101.43C555.2,-95.07 615.55,-83.26 666.74,-71.25 726.27,-57.28 741.2,-53.69 799.74,-36 802.26,-35.24 804.84,-34.44 807.44,-33.61\"/>\n",
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       "</g>\n",
       "<!-- gene10 -->\n",
       "<g id=\"node11\" class=\"node\">\n",
       "<title>gene10</title>\n",
       "<ellipse fill=\"none\" stroke=\"black\" cx=\"957.74\" cy=\"-18\" rx=\"48.05\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"957.74\" y=\"-13.32\" font-family=\"Times,serif\" font-size=\"14.00\">gene10</text>\n",
       "</g>\n",
       "<!-- tf&#45;&gt;gene10 -->\n",
       "<g id=\"edge9\" class=\"edge\">\n",
       "<title>tf&#45;&gt;gene10</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M522.52,-103.48C569.4,-98.44 669.3,-86.83 752.74,-71.25 819.21,-58.84 835.42,-53.5 900.74,-36 903.87,-35.16 907.09,-34.27 910.33,-33.36\"/>\n",
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       "</g>\n",
       "</g>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "<networkx.classes.multidigraph.MultiDiGraph at 0x72baac1caa50>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bn.influence_graph()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77abe8f3",
   "metadata": {},
   "source": [
    "## Simulation with random walk\n",
    "\n",
    "With the asynchronous update mode, the activation of the genes can be made in any order. Here, we randomly sample one trajectory of this model, which essentially boils down to selecting a random ordering of genes that get activated.\n",
    "\n",
    "Let us first specify the initial state of the network:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ee4a6403",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'tf': 1,\n",
       " 'gene1': 0,\n",
       " 'gene2': 0,\n",
       " 'gene3': 0,\n",
       " 'gene4': 0,\n",
       " 'gene5': 0,\n",
       " 'gene6': 0,\n",
       " 'gene7': 0,\n",
       " 'gene8': 0,\n",
       " 'gene9': 0,\n",
       " 'gene10': 0}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "initial_state = bn.zero()\n",
    "initial_state[\"tf\"] = 1\n",
    "initial_state"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60cedafe",
   "metadata": {},
   "source": [
    "Then, we use `minibn` to generate a random walk in the asynchronous dynamics of the Boolean network from the given initial state:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "05646298",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>tf</th>\n",
       "      <th>gene1</th>\n",
       "      <th>gene2</th>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    tf  gene1  gene2  gene3  gene4  gene5  gene6  gene7  gene8  gene9  gene10\n",
       "0    1      0      0      0      0      0      0      0      0      0       0\n",
       "1    1      0      0      0      0      0      0      0      1      0       0\n",
       "2    1      1      0      0      0      0      0      0      1      0       0\n",
       "3    1      1      0      1      0      0      0      0      1      0       0\n",
       "4    1      1      0      1      0      0      1      0      1      0       0\n",
       "5    1      1      0      1      0      0      1      0      1      1       0\n",
       "6    1      1      0      1      0      0      1      0      1      1       1\n",
       "7    1      1      0      1      1      0      1      0      1      1       1\n",
       "8    1      1      1      1      1      0      1      0      1      1       1\n",
       "9    1      1      1      1      1      0      1      1      1      1       1\n",
       "10   1      1      1      1      1      1      1      1      1      1       1"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dynamics = FullyAsynchronousDynamics(bn)\n",
    "random_walk_df = pd.DataFrame(dynamics.random_walk(initial_state, steps=10))\n",
    "random_walk_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a835af87",
   "metadata": {},
   "source": [
    "## Retrieve reference dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b37f8e8a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data_filtered_vargenes/GSE122466_Retina.csv\n",
      "data_filtered_vargenes/GSE122466_Retina_vargenes_batch1.csv\n",
      "data_filtered_vargenes/GSE130973_human_skin.csv\n",
      "data_filtered_vargenes/GSE156234_Macrophages.csv\n",
      "data_filtered_vargenes/GSE60361_mouse_brain.csv\n",
      "data_filtered_vargenes/GSE81682_Hematopoiesis.csv\n"
     ]
    }
   ],
   "source": [
    "%ls data_filtered_vargenes/*csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7e1f185f",
   "metadata": {},
   "outputs": [
    {
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       "      <th>Msn</th>\n",
       "      <th>Gm37124</th>\n",
       "      <th>Srd5a1</th>\n",
       "      <th>Bhlhe40</th>\n",
       "      <th>Pomgnt2</th>\n",
       "      <th>Fcer1g</th>\n",
       "      <th>Gm37298</th>\n",
       "      <th>Lmo1</th>\n",
       "      <th>Rab20</th>\n",
       "      <th>Cd69</th>\n",
       "      <th>Gm2788</th>\n",
       "      <th>Gm14276</th>\n",
       "      <th>Napa</th>\n",
       "      <th>Cd24a</th>\n",
       "      <th>Nsun2</th>\n",
       "      <th>Marveld2</th>\n",
       "      <th>Ms4a4b</th>\n",
       "      <th>Gm17590</th>\n",
       "      <th>Cdk6</th>\n",
       "      <th>Tada2b</th>\n",
       "      <th>Gm5113</th>\n",
       "      <th>Mki67</th>\n",
       "      <th>Btg2</th>\n",
       "      <th>Gnat2</th>\n",
       "      <th>Tcaf1</th>\n",
       "      <th>Slc35e4</th>\n",
       "      <th>Reep2</th>\n",
       "      <th>8430419K02Rik</th>\n",
       "      <th>Pdgfd</th>\n",
       "      <th>H2-K1</th>\n",
       "      <th>Sesn1</th>\n",
       "      <th>Bcap29</th>\n",
       "      <th>Gm21814</th>\n",
       "      <th>Eif5a</th>\n",
       "      <th>Stk25</th>\n",
       "      <th>Maged1</th>\n",
       "      <th>Zfp449</th>\n",
       "      <th>9130604C24Rik</th>\n",
       "      <th>6430590A07Rik</th>\n",
       "      <th>Tcirg1</th>\n",
       "      <th>Il4</th>\n",
       "      <th>Slc35a4</th>\n",
       "      <th>Cysltr2</th>\n",
       "      <th>Ap3m2</th>\n",
       "      <th>Dsel</th>\n",
       "      <th>Cmtm7</th>\n",
       "      <th>Arl8b</th>\n",
       "      <th>Gbx2</th>\n",
       "      <th>Smim10l2a</th>\n",
       "      <th>Cyth4</th>\n",
       "      <th>S1pr4</th>\n",
       "      <th>Gdi1</th>\n",
       "      <th>Hdhd3</th>\n",
       "      <th>Vill</th>\n",
       "      <th>Slc38a6</th>\n",
       "      <th>Calu</th>\n",
       "      <th>Gm16565</th>\n",
       "      <th>Smim3</th>\n",
       "      <th>Sar1a</th>\n",
       "      <th>4833407H14Rik</th>\n",
       "      <th>B230217O12Rik</th>\n",
       "      <th>Ccdc39</th>\n",
       "      <th>Spata2l</th>\n",
       "      <th>Arxes2</th>\n",
       "      <th>Dut</th>\n",
       "      <th>Ifngr1</th>\n",
       "      <th>Rasa3</th>\n",
       "      <th>Fbxl2</th>\n",
       "      <th>Pde4b</th>\n",
       "      <th>Ptp4a3</th>\n",
       "      <th>Cdt1</th>\n",
       "      <th>Fxyd1</th>\n",
       "      <th>Arl11</th>\n",
       "      <th>Shisa8</th>\n",
       "      <th>Dleu7</th>\n",
       "      <th>Tmem173</th>\n",
       "      <th>Atxn10</th>\n",
       "      <th>Rpn2</th>\n",
       "      <th>Ccl3</th>\n",
       "      <th>Nudt16</th>\n",
       "      <th>Kif3c</th>\n",
       "      <th>Hars</th>\n",
       "      <th>Ccl4</th>\n",
       "      <th>Myo1g</th>\n",
       "      <th>Cpq</th>\n",
       "      <th>Cox6a2</th>\n",
       "      <th>Sdc3</th>\n",
       "      <th>Dok2</th>\n",
       "      <th>Fcgrt</th>\n",
       "      <th>Elmo1</th>\n",
       "      <th>Cyc1</th>\n",
       "      <th>Calr</th>\n",
       "      <th>Gpr18</th>\n",
       "      <th>Tbxa2r</th>\n",
       "      <th>Gpr183</th>\n",
       "      <th>Naaa</th>\n",
       "      <th>Gm11110</th>\n",
       "      <th>Alad</th>\n",
       "      <th>Taz</th>\n",
       "      <th>Echdc3</th>\n",
       "      <th>Cd300a</th>\n",
       "      <th>Slc39a4</th>\n",
       "      <th>Zfp128</th>\n",
       "      <th>Gm26819</th>\n",
       "      <th>Ispd</th>\n",
       "      <th>Itm2b</th>\n",
       "      <th>Zfp647</th>\n",
       "      <th>Gm16861</th>\n",
       "      <th>Nek3</th>\n",
       "      <th>Gata2</th>\n",
       "      <th>Prss16</th>\n",
       "      <th>Lppos</th>\n",
       "      <th>Lhcgr</th>\n",
       "      <th>Fundc1</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Tnfrsf26</th>\n",
       "      <th>Prr36</th>\n",
       "      <th>Vldlr</th>\n",
       "      <th>Mfge8</th>\n",
       "      <th>Enkur</th>\n",
       "      <th>Rcor2</th>\n",
       "      <th>Ndn</th>\n",
       "      <th>Btla</th>\n",
       "      <th>Zyx</th>\n",
       "      <th>Cd33</th>\n",
       "      <th>Dkc1</th>\n",
       "      <th>Rab37</th>\n",
       "      <th>Cdcp1</th>\n",
       "      <th>Hoxa9</th>\n",
       "      <th>Oat</th>\n",
       "      <th>Vegfc</th>\n",
       "      <th>Gas6</th>\n",
       "      <th>Oasl2</th>\n",
       "      <th>Tacc1</th>\n",
       "      <th>Colgalt1</th>\n",
       "      <th>Xdh</th>\n",
       "      <th>Rab32</th>\n",
       "      <th>Dusp2</th>\n",
       "      <th>Tmem176a</th>\n",
       "      <th>Gnai3</th>\n",
       "      <th>Rnf13</th>\n",
       "      <th>Elane</th>\n",
       "      <th>Cd48</th>\n",
       "      <th>Mthfd1</th>\n",
       "      <th>Igkc</th>\n",
       "      <th>Fnta</th>\n",
       "      <th>Bok</th>\n",
       "      <th>Ripply3</th>\n",
       "      <th>Ptger2</th>\n",
       "      <th>P2rx7</th>\n",
       "      <th>Wdfy2</th>\n",
       "      <th>Eif1a</th>\n",
       "      <th>Gstm7</th>\n",
       "      <th>Tmem14c</th>\n",
       "      <th>2900018N21Rik</th>\n",
       "      <th>Mpl</th>\n",
       "      <th>Sash3</th>\n",
       "      <th>Tgm2</th>\n",
       "      <th>Gm19569</th>\n",
       "      <th>Ehd3</th>\n",
       "      <th>Cish</th>\n",
       "      <th>Calml4</th>\n",
       "      <th>Mesdc2</th>\n",
       "      <th>Nfil3</th>\n",
       "      <th>Tcn2</th>\n",
       "      <th>Saraf</th>\n",
       "      <th>Meis1</th>\n",
       "      <th>Serpina3g</th>\n",
       "      <th>Pcx</th>\n",
       "      <th>Gpr171</th>\n",
       "      <th>Cks1b</th>\n",
       "      <th>Coa5</th>\n",
       "      <th>Arhgap27os3</th>\n",
       "      <th>Farsa</th>\n",
       "      <th>Ctsl</th>\n",
       "      <th>Iigp1</th>\n",
       "      <th>P2ry14</th>\n",
       "      <th>Cd82</th>\n",
       "      <th>Slc18a2</th>\n",
       "      <th>Cd302</th>\n",
       "      <th>Parp12</th>\n",
       "      <th>Isyna1</th>\n",
       "      <th>S100a8</th>\n",
       "      <th>B130034C11Rik</th>\n",
       "      <th>Arhgap27</th>\n",
       "      <th>Klf1</th>\n",
       "      <th>Gm26740</th>\n",
       "      <th>Cd84</th>\n",
       "      <th>Bag2</th>\n",
       "      <th>Tmem123</th>\n",
       "      <th>Emilin1</th>\n",
       "      <th>4930568A12Rik</th>\n",
       "      <th>Clec11a</th>\n",
       "      <th>Mat2a</th>\n",
       "      <th>Tespa1</th>\n",
       "      <th>Wfdc17</th>\n",
       "      <th>Tspan13</th>\n",
       "      <th>Dyrk2</th>\n",
       "      <th>S100a9</th>\n",
       "      <th>F10</th>\n",
       "      <th>Pde1b</th>\n",
       "      <th>Gcnt2</th>\n",
       "      <th>Ppic</th>\n",
       "      <th>Zfp72</th>\n",
       "      <th>Gm4841</th>\n",
       "      <th>Ckb</th>\n",
       "      <th>C130013H08Rik</th>\n",
       "      <th>Spo11</th>\n",
       "      <th>Ctss</th>\n",
       "      <th>Vwa5a</th>\n",
       "      <th>Serpinb1a</th>\n",
       "      <th>Trib3</th>\n",
       "      <th>Slc28a2</th>\n",
       "      <th>Xbp1</th>\n",
       "      <th>Tsc22d3</th>\n",
       "      <th>Cd74</th>\n",
       "      <th>Nhlrc1</th>\n",
       "      <th>Rac2</th>\n",
       "      <th>Il15</th>\n",
       "      <th>Ift43</th>\n",
       "      <th>Tnfrsf13c</th>\n",
       "      <th>Gm10451</th>\n",
       "      <th>Plod2</th>\n",
       "      <th>Minpp1</th>\n",
       "      <th>Cs</th>\n",
       "      <th>Gm21967</th>\n",
       "      <th>Trim27</th>\n",
       "      <th>Rrm1</th>\n",
       "      <th>Krt18</th>\n",
       "      <th>Rap1b</th>\n",
       "      <th>Anxa2</th>\n",
       "      <th>D130040H23Rik</th>\n",
       "      <th>Tmsb4x</th>\n",
       "      <th>1810034E14Rik</th>\n",
       "      <th>2810021J22Rik</th>\n",
       "      <th>F630028O10Rik</th>\n",
       "      <th>Cyb5r3</th>\n",
       "      <th>B3gnt3</th>\n",
       "      <th>Laptm5</th>\n",
       "      <th>Adam11</th>\n",
       "      <th>Rab17</th>\n",
       "      <th>Pkia</th>\n",
       "      <th>Hist3h2ba</th>\n",
       "      <th>Cyp27a1</th>\n",
       "      <th>Zfp36</th>\n",
       "      <th>Mcm5</th>\n",
       "      <th>Ssc4d</th>\n",
       "      <th>Gm45837</th>\n",
       "      <th>Lmcd1</th>\n",
       "      <th>Fgf3</th>\n",
       "      <th>Car1</th>\n",
       "      <th>Adssl1</th>\n",
       "      <th>Il21r</th>\n",
       "      <th>Slc50a1</th>\n",
       "      <th>Serpinb9</th>\n",
       "      <th>Pttg1ip</th>\n",
       "      <th>Fam83d</th>\n",
       "      <th>Tspan32</th>\n",
       "      <th>Tnfrsf13b</th>\n",
       "      <th>Gdi2</th>\n",
       "      <th>Nim1k</th>\n",
       "      <th>Mapk12</th>\n",
       "      <th>Wfdc18</th>\n",
       "      <th>Thbs1</th>\n",
       "      <th>Chil5</th>\n",
       "      <th>Mpst</th>\n",
       "      <th>Selenop</th>\n",
       "      <th>Gm43852</th>\n",
       "      <th>Hk3</th>\n",
       "      <th>Irgm1</th>\n",
       "      <th>Nceh1</th>\n",
       "      <th>Myl10</th>\n",
       "      <th>Tmx1</th>\n",
       "      <th>Zcchc24</th>\n",
       "      <th>Acsl5</th>\n",
       "      <th>Tnfaip8</th>\n",
       "      <th>4632427E13Rik</th>\n",
       "      <th>Hspa9</th>\n",
       "      <th>Hid1</th>\n",
       "      <th>Gstt1</th>\n",
       "      <th>Il12rb1</th>\n",
       "      <th>Ficd</th>\n",
       "      <th>Bbs10</th>\n",
       "      <th>Esam</th>\n",
       "      <th>Unc93b1</th>\n",
       "      <th>Casp4</th>\n",
       "      <th>F2r</th>\n",
       "      <th>Dynlt3</th>\n",
       "      <th>Adgrg1</th>\n",
       "      <th>Tmem38a</th>\n",
       "      <th>Stap1</th>\n",
       "      <th>Cep170b</th>\n",
       "      <th>Lpxn</th>\n",
       "      <th>Frmd8</th>\n",
       "      <th>Doc2g</th>\n",
       "      <th>Ighv1-23</th>\n",
       "      <th>Hrh2</th>\n",
       "      <th>Bgn</th>\n",
       "      <th>Ifi206</th>\n",
       "      <th>Fes</th>\n",
       "      <th>Apol7e</th>\n",
       "      <th>Srl</th>\n",
       "      <th>Ifi47</th>\n",
       "      <th>Cdca7</th>\n",
       "      <th>Srm</th>\n",
       "      <th>Smagp</th>\n",
       "      <th>Zfp418</th>\n",
       "      <th>Zfp882</th>\n",
       "      <th>Mmp2</th>\n",
       "      <th>Fam32a</th>\n",
       "      <th>Flna</th>\n",
       "      <th>Lyz2</th>\n",
       "      <th>Cd53</th>\n",
       "      <th>Mapk11</th>\n",
       "      <th>Sptbn1</th>\n",
       "      <th>Mapre3</th>\n",
       "      <th>Nr0b2</th>\n",
       "      <th>Ptprc</th>\n",
       "      <th>Gulp1</th>\n",
       "      <th>Cd63</th>\n",
       "      <th>Nsg1</th>\n",
       "      <th>Fam131a</th>\n",
       "      <th>Dntt</th>\n",
       "      <th>Ifi213</th>\n",
       "      <th>Tcp1</th>\n",
       "      <th>Stard8</th>\n",
       "      <th>Clptm1l</th>\n",
       "      <th>Sigirr</th>\n",
       "      <th>Robo3</th>\n",
       "      <th>Il17rb</th>\n",
       "      <th>Mcfd2</th>\n",
       "      <th>Vpreb1</th>\n",
       "      <th>Casp12</th>\n",
       "      <th>Zbtb3</th>\n",
       "      <th>Ppt1</th>\n",
       "      <th>H1f0</th>\n",
       "      <th>C730034F03Rik</th>\n",
       "      <th>Tpst2</th>\n",
       "      <th>Pnrc1</th>\n",
       "      <th>Sdhaf2</th>\n",
       "      <th>Hnrnpdl</th>\n",
       "      <th>Cyp7b1</th>\n",
       "      <th>Ptpre</th>\n",
       "      <th>Slc25a45</th>\n",
       "      <th>Wdr35</th>\n",
       "      <th>Capg</th>\n",
       "      <th>Sf3b3</th>\n",
       "      <th>Gata1</th>\n",
       "      <th>Spry1</th>\n",
       "      <th>Abce1</th>\n",
       "      <th>Rnf180</th>\n",
       "      <th>Golph3l</th>\n",
       "      <th>P2ry10</th>\n",
       "      <th>Adgrg3</th>\n",
       "      <th>Fkbp4</th>\n",
       "      <th>F2rl2</th>\n",
       "      <th>Gbp2</th>\n",
       "      <th>Plcg2</th>\n",
       "      <th>Ccdc189</th>\n",
       "      <th>4930486L24Rik</th>\n",
       "      <th>E230001N04Rik</th>\n",
       "      <th>Itih5</th>\n",
       "      <th>Chrnb1</th>\n",
       "      <th>Gm16386</th>\n",
       "      <th>Thnsl2</th>\n",
       "      <th>Gm16712</th>\n",
       "      <th>Top2a</th>\n",
       "      <th>Gm5577</th>\n",
       "      <th>Nt5c3</th>\n",
       "      <th>Nlrp10</th>\n",
       "      <th>Ctf1</th>\n",
       "      <th>Il18bp</th>\n",
       "      <th>Il1rl2</th>\n",
       "      <th>Gm5148</th>\n",
       "      <th>Car2</th>\n",
       "      <th>Vim</th>\n",
       "      <th>A630033H20Rik</th>\n",
       "      <th>Cd81</th>\n",
       "      <th>Zfp563</th>\n",
       "      <th>Ctla2a</th>\n",
       "      <th>Mfsd2b</th>\n",
       "      <th>Idh2</th>\n",
       "      <th>Tert</th>\n",
       "      <th>Pwwp2b</th>\n",
       "      <th>Atp6ap2</th>\n",
       "      <th>Ces2g</th>\n",
       "      <th>Gba2</th>\n",
       "      <th>4931428F04Rik</th>\n",
       "      <th>Apoe</th>\n",
       "      <th>Sdha</th>\n",
       "      <th>Dlg3</th>\n",
       "      <th>Igkv4-50</th>\n",
       "      <th>Dhx58</th>\n",
       "      <th>Zfp661</th>\n",
       "      <th>Ccr9</th>\n",
       "      <th>Rgs2</th>\n",
       "      <th>Ctsc</th>\n",
       "      <th>Parp8</th>\n",
       "      <th>Tspo2</th>\n",
       "      <th>5430420F09Rik</th>\n",
       "      <th>Pear1</th>\n",
       "      <th>Ltb</th>\n",
       "      <th>Gm26512</th>\n",
       "      <th>AA467197</th>\n",
       "      <th>Unc5cl</th>\n",
       "      <th>Mtpn</th>\n",
       "      <th>Mcm6</th>\n",
       "      <th>Atp2a3</th>\n",
       "      <th>Tyms</th>\n",
       "      <th>Il12a</th>\n",
       "      <th>Celf2</th>\n",
       "      <th>Axl</th>\n",
       "      <th>Tpm4</th>\n",
       "      <th>Gm3739</th>\n",
       "      <th>Cyp2j9</th>\n",
       "      <th>Fxyd5</th>\n",
       "      <th>B230216N24Rik</th>\n",
       "      <th>Trbc2</th>\n",
       "      <th>Fam161b</th>\n",
       "      <th>Gm30948</th>\n",
       "      <th>Apbb1</th>\n",
       "      <th>Igfbp4</th>\n",
       "      <th>Pcp4l1</th>\n",
       "      <th>Rassf5</th>\n",
       "      <th>Cyp2r1</th>\n",
       "      <th>Smoc1</th>\n",
       "      <th>Srgn</th>\n",
       "      <th>Pygm</th>\n",
       "      <th>Gm43200</th>\n",
       "      <th>Gca</th>\n",
       "      <th>Arhgef6</th>\n",
       "      <th>Fah</th>\n",
       "      <th>BC017643</th>\n",
       "      <th>Ak3</th>\n",
       "      <th>Icam1</th>\n",
       "      <th>Gm10505</th>\n",
       "      <th>C1qbp</th>\n",
       "      <th>Efna1</th>\n",
       "      <th>AW112010</th>\n",
       "      <th>Tnks1bp1</th>\n",
       "      <th>Anxa1</th>\n",
       "      <th>Fgf11</th>\n",
       "      <th>Layn</th>\n",
       "      <th>Gm19331</th>\n",
       "      <th>Rbpms2</th>\n",
       "      <th>Tspan3</th>\n",
       "      <th>Ighv9-1</th>\n",
       "      <th>Gm43201</th>\n",
       "      <th>Arrdc1</th>\n",
       "      <th>Hjurp</th>\n",
       "      <th>4921507P07Rik</th>\n",
       "      <th>Sla</th>\n",
       "      <th>Ms4a6b</th>\n",
       "      <th>Zfp551</th>\n",
       "      <th>2810468N07Rik</th>\n",
       "      <th>Tnf</th>\n",
       "      <th>Serp1</th>\n",
       "      <th>Mfap2</th>\n",
       "      <th>Arhgef18</th>\n",
       "      <th>Slc25a29</th>\n",
       "      <th>Hmox1</th>\n",
       "      <th>Pkm</th>\n",
       "      <th>Arhgap15</th>\n",
       "      <th>Ddx39</th>\n",
       "      <th>Fv1</th>\n",
       "      <th>Gnb5</th>\n",
       "      <th>Tes</th>\n",
       "      <th>Lysmd2</th>\n",
       "      <th>Mmp11</th>\n",
       "      <th>Pgrmc1</th>\n",
       "      <th>Gm42979</th>\n",
       "      <th>Efna4</th>\n",
       "      <th>Uba7</th>\n",
       "      <th>Xist</th>\n",
       "      <th>Sumo3</th>\n",
       "      <th>Flt3</th>\n",
       "      <th>Mycn</th>\n",
       "      <th>1300017J02Rik</th>\n",
       "      <th>Scn1b</th>\n",
       "      <th>Rab38</th>\n",
       "      <th>ENSMUSG00000096970</th>\n",
       "      <th>Tnfaip2</th>\n",
       "      <th>Hdac2</th>\n",
       "      <th>Ccr7</th>\n",
       "      <th>Irf6</th>\n",
       "      <th>Mndal</th>\n",
       "      <th>Fut4</th>\n",
       "      <th>Casp1</th>\n",
       "      <th>Slc14a1</th>\n",
       "      <th>Rit1</th>\n",
       "      <th>Ifi203</th>\n",
       "      <th>Zfp93</th>\n",
       "      <th>Calr3</th>\n",
       "      <th>2210010C04Rik</th>\n",
       "      <th>Gm38243</th>\n",
       "      <th>Gm43313</th>\n",
       "      <th>Slc25a5</th>\n",
       "      <th>Bcam</th>\n",
       "      <th>Ighv1-74</th>\n",
       "      <th>Traf3ip3</th>\n",
       "      <th>Lgals9</th>\n",
       "      <th>Gm26982</th>\n",
       "      <th>Clec10a</th>\n",
       "      <th>Klhl8</th>\n",
       "      <th>Islr</th>\n",
       "      <th>Ighv1-76</th>\n",
       "      <th>Crlf3</th>\n",
       "      <th>Ighv1-77</th>\n",
       "      <th>Lcp2</th>\n",
       "      <th>Rapsn</th>\n",
       "      <th>Cd38</th>\n",
       "      <th>Gm37423</th>\n",
       "      <th>Selplg</th>\n",
       "      <th>Clip3</th>\n",
       "      <th>Ccdc157</th>\n",
       "      <th>Uggt2</th>\n",
       "      <th>Mpo</th>\n",
       "      <th>Eya1</th>\n",
       "      <th>Ctso</th>\n",
       "      <th>Gm26917</th>\n",
       "      <th>Rarb</th>\n",
       "      <th>Cmtm6</th>\n",
       "      <th>Metrnl</th>\n",
       "      <th>Rgs1</th>\n",
       "      <th>Ptpn6</th>\n",
       "      <th>Cd1d1</th>\n",
       "      <th>Lyrm1</th>\n",
       "      <th>Prkaa2</th>\n",
       "      <th>Gm4759</th>\n",
       "      <th>Aplp2</th>\n",
       "      <th>Gm8995</th>\n",
       "      <th>Gng11</th>\n",
       "      <th>Tmem150b</th>\n",
       "      <th>Abhd6</th>\n",
       "      <th>Gm5111</th>\n",
       "      <th>Ankrd50</th>\n",
       "      <th>Neurl3</th>\n",
       "      <th>Slc44a2</th>\n",
       "      <th>Gm128</th>\n",
       "      <th>Fam132a</th>\n",
       "      <th>2810414N06Rik</th>\n",
       "      <th>M6pr</th>\n",
       "      <th>Ankrd33b</th>\n",
       "      <th>Hexa</th>\n",
       "      <th>Pdcd1lg2</th>\n",
       "      <th>Dnajc9</th>\n",
       "      <th>Lck</th>\n",
       "      <th>Ccnb2</th>\n",
       "      <th>Wls</th>\n",
       "      <th>Gramd1a</th>\n",
       "      <th>Gm37642</th>\n",
       "      <th>St8sia4</th>\n",
       "      <th>Igkv12-44</th>\n",
       "      <th>Sqstm1</th>\n",
       "      <th>Slc25a35</th>\n",
       "      <th>Tipin</th>\n",
       "      <th>4930555A03Rik</th>\n",
       "      <th>Rn18s-rs5</th>\n",
       "      <th>Samd12</th>\n",
       "      <th>B9d1</th>\n",
       "      <th>Ncf4</th>\n",
       "      <th>Myc</th>\n",
       "      <th>Uaca</th>\n",
       "      <th>Irf9</th>\n",
       "      <th>Paics</th>\n",
       "      <th>Gstm1</th>\n",
       "      <th>Padi4</th>\n",
       "      <th>Tor3a</th>\n",
       "      <th>Rgs18</th>\n",
       "      <th>Slc26a6</th>\n",
       "      <th>Ppm1g</th>\n",
       "      <th>Zfand5</th>\n",
       "      <th>Smpd5</th>\n",
       "      <th>Hdac9</th>\n",
       "      <th>Gnl3</th>\n",
       "      <th>Ecm1</th>\n",
       "      <th>Rnase6</th>\n",
       "      <th>Lgals3bp</th>\n",
       "      <th>Slc2a10</th>\n",
       "      <th>Rdh14</th>\n",
       "      <th>Icos</th>\n",
       "      <th>Dnah1</th>\n",
       "      <th>Amt</th>\n",
       "      <th>Fut8</th>\n",
       "      <th>Itpkc</th>\n",
       "      <th>Ap1s2</th>\n",
       "      <th>Rgs11</th>\n",
       "      <th>Hpcal1</th>\n",
       "      <th>Gm43178</th>\n",
       "      <th>Rnase4</th>\n",
       "      <th>Adgrl4</th>\n",
       "      <th>Nek6</th>\n",
       "      <th>Clk1</th>\n",
       "      <th>Eya2</th>\n",
       "      <th>Csf3r</th>\n",
       "      <th>Fkbp1b</th>\n",
       "      <th>Pirb</th>\n",
       "      <th>Msmo1</th>\n",
       "      <th>Gm15133</th>\n",
       "      <th>Pim2</th>\n",
       "      <th>Cldn15</th>\n",
       "      <th>Gm28557</th>\n",
       "      <th>Ric8a</th>\n",
       "      <th>Triqk</th>\n",
       "      <th>Spns2</th>\n",
       "      <th>Cebpe</th>\n",
       "      <th>Tspan14</th>\n",
       "      <th>Itm2a</th>\n",
       "      <th>Ddx1</th>\n",
       "      <th>Sh3tc1</th>\n",
       "      <th>Slc22a18</th>\n",
       "      <th>Lcp1</th>\n",
       "      <th>Casp2</th>\n",
       "      <th>Epsti1</th>\n",
       "      <th>Ifi44</th>\n",
       "      <th>Phf11b</th>\n",
       "      <th>Ctsb</th>\n",
       "      <th>H2afy</th>\n",
       "      <th>Ctsg</th>\n",
       "      <th>Gimap9</th>\n",
       "      <th>Hsd3b7</th>\n",
       "      <th>Smpdl3a</th>\n",
       "      <th>Gm43162</th>\n",
       "      <th>Trim47</th>\n",
       "      <th>Cpa3</th>\n",
       "      <th>Cat</th>\n",
       "      <th>Cers2</th>\n",
       "      <th>Ifit3</th>\n",
       "      <th>Ifit1bl1</th>\n",
       "      <th>Slc9a3r2</th>\n",
       "      <th>Mcm3</th>\n",
       "      <th>Fscn1</th>\n",
       "      <th>Thbd</th>\n",
       "      <th>Cd93</th>\n",
       "      <th>Sept6</th>\n",
       "      <th>Irf5</th>\n",
       "      <th>Rab19</th>\n",
       "      <th>Ctsz</th>\n",
       "      <th>Rhbdf1</th>\n",
       "      <th>Wfs1</th>\n",
       "      <th>Mef2c</th>\n",
       "      <th>Blvrb</th>\n",
       "      <th>Gimap1</th>\n",
       "      <th>Gimap7</th>\n",
       "      <th>Gimap4</th>\n",
       "      <th>4930515G01Rik</th>\n",
       "      <th>Hgfac</th>\n",
       "      <th>Gimap6</th>\n",
       "      <th>Gm15201</th>\n",
       "      <th>Gimap5</th>\n",
       "      <th>BC035044</th>\n",
       "      <th>Ly6e</th>\n",
       "      <th>Hs3st1</th>\n",
       "      <th>Zfp62</th>\n",
       "      <th>Vpreb3</th>\n",
       "      <th>Kcnh2</th>\n",
       "      <th>Hn1l</th>\n",
       "      <th>Hlf</th>\n",
       "      <th>9930012K11Rik</th>\n",
       "      <th>Sgsm1</th>\n",
       "      <th>Gmpr</th>\n",
       "      <th>Lancl1</th>\n",
       "      <th>Slc16a1</th>\n",
       "      <th>Plcb2</th>\n",
       "      <th>Sdpr</th>\n",
       "      <th>Rhoh</th>\n",
       "      <th>Gm38250</th>\n",
       "      <th>Gm26532</th>\n",
       "      <th>Dock2</th>\n",
       "      <th>Pdlim2</th>\n",
       "      <th>Clk4</th>\n",
       "      <th>Nubp2</th>\n",
       "      <th>Treml2</th>\n",
       "      <th>Sell</th>\n",
       "      <th>Polm</th>\n",
       "      <th>Pglyrp2</th>\n",
       "      <th>Gm37829</th>\n",
       "      <th>Tsc22d1</th>\n",
       "      <th>9130008F23Rik</th>\n",
       "      <th>Gm37558</th>\n",
       "      <th>Gm37706</th>\n",
       "      <th>Ptprcap</th>\n",
       "      <th>Hck</th>\n",
       "      <th>Adamts10</th>\n",
       "      <th>Ly6a</th>\n",
       "      <th>Gm37598</th>\n",
       "      <th>Anxa5</th>\n",
       "      <th>Parvg</th>\n",
       "      <th>Acer2</th>\n",
       "      <th>Cd79a</th>\n",
       "      <th>Tmem175</th>\n",
       "      <th>Fcrl1</th>\n",
       "      <th>Dusp22</th>\n",
       "      <th>Ms4a4c</th>\n",
       "      <th>Bank1</th>\n",
       "      <th>Gm43149</th>\n",
       "      <th>Gatsl3</th>\n",
       "      <th>BC026585</th>\n",
       "      <th>Wfdc2</th>\n",
       "      <th>Camk1</th>\n",
       "      <th>Dgkq</th>\n",
       "      <th>Treml1</th>\n",
       "      <th>Ebi3</th>\n",
       "      <th>Gm27252</th>\n",
       "      <th>Magee1</th>\n",
       "      <th>Sdc2</th>\n",
       "      <th>Ldhb</th>\n",
       "      <th>Kmo</th>\n",
       "      <th>Bpifb5</th>\n",
       "      <th>Trim30a</th>\n",
       "      <th>Ifitm1</th>\n",
       "      <th>Ddx58</th>\n",
       "      <th>Ifitm3</th>\n",
       "      <th>Rmnd5b</th>\n",
       "      <th>Gm26772</th>\n",
       "      <th>Gm16151</th>\n",
       "      <th>Gm16150</th>\n",
       "      <th>Tagln2</th>\n",
       "      <th>3110083C13Rik</th>\n",
       "      <th>Cyp39a1</th>\n",
       "      <th>Tspyl3</th>\n",
       "      <th>Dennd1c</th>\n",
       "      <th>Slc2a1</th>\n",
       "      <th>Large1</th>\n",
       "      <th>AB124611</th>\n",
       "      <th>Gm17096</th>\n",
       "      <th>Stxbp4</th>\n",
       "      <th>Muc3a</th>\n",
       "      <th>Awat2</th>\n",
       "      <th>Plac8</th>\n",
       "      <th>AI506816</th>\n",
       "      <th>Canx</th>\n",
       "      <th>Alox5</th>\n",
       "      <th>Prdx6</th>\n",
       "      <th>F11r</th>\n",
       "      <th>Alg2</th>\n",
       "      <th>Lurap1</th>\n",
       "      <th>Ttc30b</th>\n",
       "      <th>Inpp5k</th>\n",
       "      <th>Dcdc2b</th>\n",
       "      <th>Tnfsf4</th>\n",
       "      <th>Atp6ap1</th>\n",
       "      <th>Dapp1</th>\n",
       "      <th>1500002C15Rik</th>\n",
       "      <th>Tuba4a</th>\n",
       "      <th>Gm43254</th>\n",
       "      <th>ENSMUSG00000029333</th>\n",
       "      <th>Gclm</th>\n",
       "      <th>Ruvbl2</th>\n",
       "      <th>Apobr</th>\n",
       "      <th>Nap1l3</th>\n",
       "      <th>Cct6a</th>\n",
       "      <th>Vav1</th>\n",
       "      <th>Rfc2</th>\n",
       "      <th>Gm16001</th>\n",
       "      <th>Atp1b1</th>\n",
       "      <th>Gm19708</th>\n",
       "      <th>Nradd</th>\n",
       "      <th>Ypel3</th>\n",
       "      <th>Tor4a</th>\n",
       "      <th>Gm19590</th>\n",
       "      <th>Ivns1abp</th>\n",
       "      <th>Gm15991</th>\n",
       "      <th>Upp1</th>\n",
       "      <th>Gm6157</th>\n",
       "      <th>Eif5a2</th>\n",
       "      <th>C1qtnf6</th>\n",
       "      <th>4933424M12Rik</th>\n",
       "      <th>Mageh1</th>\n",
       "      <th>Gm11696</th>\n",
       "      <th>Cbfb</th>\n",
       "      <th>Zfp422</th>\n",
       "      <th>Mfng</th>\n",
       "      <th>Klf8</th>\n",
       "      <th>Stk17b</th>\n",
       "      <th>Met</th>\n",
       "      <th>Ufsp1</th>\n",
       "      <th>Tmem150a</th>\n",
       "      <th>AI606181</th>\n",
       "      <th>Ikzf2</th>\n",
       "      <th>Slc34a2</th>\n",
       "      <th>1700066B19Rik</th>\n",
       "      <th>Mcm7</th>\n",
       "      <th>Fbxo48</th>\n",
       "      <th>Ecscr</th>\n",
       "      <th>Lyplal1</th>\n",
       "      <th>Ankrd37</th>\n",
       "      <th>Plek</th>\n",
       "      <th>Mapkbp1</th>\n",
       "      <th>Ppp1r3d</th>\n",
       "      <th>Exoc3l2</th>\n",
       "      <th>Tmem53</th>\n",
       "      <th>Wsb1</th>\n",
       "      <th>Rtkn</th>\n",
       "      <th>Tfr2</th>\n",
       "      <th>Leprot</th>\n",
       "      <th>Arhgap25</th>\n",
       "      <th>Nupr1</th>\n",
       "      <th>Plpp7</th>\n",
       "      <th>G730003C15Rik</th>\n",
       "      <th>Rsrp1</th>\n",
       "      <th>Samsn1</th>\n",
       "      <th>Prdx3</th>\n",
       "      <th>Gm37663</th>\n",
       "      <th>Itgb3</th>\n",
       "      <th>Rtn4r</th>\n",
       "      <th>Nrros</th>\n",
       "      <th>Dennd2d</th>\n",
       "      <th>Por</th>\n",
       "      <th>Tspear</th>\n",
       "      <th>Hsd17b12</th>\n",
       "      <th>Capza2</th>\n",
       "      <th>Osgin1</th>\n",
       "      <th>Spns3</th>\n",
       "      <th>Cd34</th>\n",
       "      <th>4921531C22Rik</th>\n",
       "      <th>Trmt2a</th>\n",
       "      <th>Gm26692</th>\n",
       "      <th>Col16a1</th>\n",
       "      <th>Cd46</th>\n",
       "      <th>Ptgds</th>\n",
       "      <th>Uqcrc1</th>\n",
       "      <th>Gm28512</th>\n",
       "      <th>Hacd4</th>\n",
       "      <th>Ttc39c</th>\n",
       "      <th>Igkv1-135</th>\n",
       "      <th>Fam129c</th>\n",
       "      <th>Rhof</th>\n",
       "      <th>Sdcbp</th>\n",
       "      <th>Rcsd1</th>\n",
       "      <th>Mmrn1</th>\n",
       "      <th>Ccser1</th>\n",
       "      <th>Ccdc92b</th>\n",
       "      <th>Tnfaip8l1</th>\n",
       "      <th>Tprgl</th>\n",
       "      <th>Gem</th>\n",
       "      <th>D630039A03Rik</th>\n",
       "      <th>Lrrc36</th>\n",
       "      <th>Map10</th>\n",
       "      <th>Gm38071</th>\n",
       "      <th>Ccng2</th>\n",
       "      <th>Ldha</th>\n",
       "      <th>Ramp1</th>\n",
       "      <th>Ucp2</th>\n",
       "      <th>Sdsl</th>\n",
       "      <th>Ttc4</th>\n",
       "      <th>Afap1l1</th>\n",
       "      <th>Ccnd2</th>\n",
       "      <th>Sult1a1</th>\n",
       "      <th>Ube2l6</th>\n",
       "      <th>Clec12a</th>\n",
       "      <th>Gm43643</th>\n",
       "      <th>Smtnl1</th>\n",
       "      <th>Aqp1</th>\n",
       "      <th>Large2</th>\n",
       "      <th>Creg1</th>\n",
       "      <th>Fam221a</th>\n",
       "      <th>Muc13</th>\n",
       "      <th>Slc25a11</th>\n",
       "      <th>Grap</th>\n",
       "      <th>Ncf1</th>\n",
       "      <th>B4galt4</th>\n",
       "      <th>Gm16758</th>\n",
       "      <th>Nucb1</th>\n",
       "      <th>Fam69b</th>\n",
       "      <th>Tmem35b</th>\n",
       "      <th>Mx1</th>\n",
       "      <th>Ppp1r26</th>\n",
       "      <th>Mx2</th>\n",
       "      <th>Ppp1r15a</th>\n",
       "      <th>Pdzk1ip1</th>\n",
       "      <th>Coro1a</th>\n",
       "      <th>Mob3c</th>\n",
       "      <th>Oas2</th>\n",
       "      <th>Kctd12b</th>\n",
       "      <th>Mefv</th>\n",
       "      <th>Gm12250</th>\n",
       "      <th>Sh2d5</th>\n",
       "      <th>Igtp</th>\n",
       "      <th>Ermap</th>\n",
       "      <th>Smu1</th>\n",
       "      <th>Maged2</th>\n",
       "      <th>Mcm4</th>\n",
       "      <th>Gm42576</th>\n",
       "      <th>Anxa6</th>\n",
       "      <th>1700123M08Rik</th>\n",
       "      <th>Rtp4</th>\n",
       "      <th>Sh3bgrl</th>\n",
       "      <th>Napsa</th>\n",
       "      <th>Kctd21</th>\n",
       "      <th>Chpf</th>\n",
       "      <th>Gm7160</th>\n",
       "      <th>Neurl1b</th>\n",
       "      <th>Cct3</th>\n",
       "      <th>Nkx2-3</th>\n",
       "      <th>Wdr78</th>\n",
       "      <th>Dusp1</th>\n",
       "      <th>Def8</th>\n",
       "      <th>Rbm5</th>\n",
       "      <th>BC016579</th>\n",
       "      <th>Emb</th>\n",
       "      <th>Elovl1</th>\n",
       "      <th>Myo1f</th>\n",
       "      <th>Lax1</th>\n",
       "      <th>Cyp2j6</th>\n",
       "      <th>Pstpip1</th>\n",
       "      <th>Emp1</th>\n",
       "      <th>Cd44</th>\n",
       "      <th>Mtch2</th>\n",
       "      <th>Pgm2</th>\n",
       "      <th>Krt7</th>\n",
       "      <th>Mir155hg</th>\n",
       "      <th>1110028F11Rik</th>\n",
       "      <th>Acot7</th>\n",
       "      <th>Rnd2</th>\n",
       "      <th>Irf1</th>\n",
       "      <th>H2-DMa</th>\n",
       "      <th>Zfp263</th>\n",
       "      <th>Rxra</th>\n",
       "      <th>Klhl6</th>\n",
       "      <th>A130014A01Rik</th>\n",
       "      <th>Ssbp2</th>\n",
       "      <th>Rbp1</th>\n",
       "      <th>Rsl1d1</th>\n",
       "      <th>Gjb3</th>\n",
       "      <th>Asah1</th>\n",
       "      <th>Tmem37</th>\n",
       "      <th>Spcs3</th>\n",
       "      <th>Cenpa</th>\n",
       "      <th>Gfpt2</th>\n",
       "      <th>Tmprss3</th>\n",
       "      <th>Pqlc3</th>\n",
       "      <th>Dhrs3</th>\n",
       "      <th>Jak3</th>\n",
       "      <th>Fam213b</th>\n",
       "      <th>Pafah2</th>\n",
       "      <th>Jun</th>\n",
       "      <th>Lamp1</th>\n",
       "      <th>Camsap3</th>\n",
       "      <th>Grtp1</th>\n",
       "      <th>Gm16794</th>\n",
       "      <th>Cacybp</th>\n",
       "      <th>Slfn8</th>\n",
       "      <th>Stom</th>\n",
       "      <th>H2-DMb1</th>\n",
       "      <th>H2-D1</th>\n",
       "      <th>Oas1c</th>\n",
       "      <th>Tas1r1</th>\n",
       "      <th>Rab44</th>\n",
       "      <th>4930579K19Rik</th>\n",
       "      <th>Fos</th>\n",
       "      <th>Nedd4</th>\n",
       "      <th>Cyb561</th>\n",
       "      <th>Mapkapk3</th>\n",
       "      <th>Inpp4b</th>\n",
       "      <th>Ccdc69</th>\n",
       "      <th>Slfn2</th>\n",
       "      <th>Tmem220</th>\n",
       "      <th>2610035D17Rik</th>\n",
       "      <th>Snap23</th>\n",
       "      <th>Nprl2</th>\n",
       "      <th>Rasal3</th>\n",
       "      <th>Ighv1-82</th>\n",
       "      <th>Batf</th>\n",
       "      <th>Tmem121</th>\n",
       "      <th>Rrm2</th>\n",
       "      <th>Surf4</th>\n",
       "      <th>Zfp386</th>\n",
       "      <th>Mamdc4</th>\n",
       "      <th>B230217C12Rik</th>\n",
       "      <th>Zbtb42</th>\n",
       "      <th>Sstr2</th>\n",
       "      <th>Pld2</th>\n",
       "      <th>Cers5</th>\n",
       "      <th>Ighd</th>\n",
       "      <th>Ighm</th>\n",
       "      <th>Cyp4v3</th>\n",
       "      <th>Limd2</th>\n",
       "      <th>Nlrp1a</th>\n",
       "      <th>H2-Q6</th>\n",
       "      <th>P4hb</th>\n",
       "      <th>Grn</th>\n",
       "      <th>H2-Q7</th>\n",
       "      <th>Gm10863</th>\n",
       "      <th>Hhex</th>\n",
       "      <th>Pcbp4</th>\n",
       "      <th>Tubb5</th>\n",
       "      <th>Itgb7</th>\n",
       "      <th>Gpam</th>\n",
       "      <th>Cbx5</th>\n",
       "      <th>Fam184a</th>\n",
       "      <th>Tmem106a</th>\n",
       "      <th>Adamtsl5</th>\n",
       "      <th>Cd79b</th>\n",
       "      <th>Nfe2</th>\n",
       "      <th>H2-Ob</th>\n",
       "      <th>Tcp11l2</th>\n",
       "      <th>Shisa5</th>\n",
       "      <th>Samd10</th>\n",
       "      <th>Hspa12b</th>\n",
       "      <th>Tcea2</th>\n",
       "      <th>Ctsd</th>\n",
       "      <th>Rgs19</th>\n",
       "      <th>Procr</th>\n",
       "      <th>Tnni2</th>\n",
       "      <th>Acap1</th>\n",
       "      <th>Bin2</th>\n",
       "      <th>Ropn1l</th>\n",
       "      <th>Lmbrd2</th>\n",
       "      <th>Laptm4b</th>\n",
       "      <th>Il7r</th>\n",
       "      <th>Capsl</th>\n",
       "      <th>Angpt1</th>\n",
       "      <th>Spag1</th>\n",
       "      <th>H2-Ab1</th>\n",
       "      <th>Gfi1b</th>\n",
       "      <th>H2-Aa</th>\n",
       "      <th>Ctsw</th>\n",
       "      <th>Hspa5</th>\n",
       "      <th>Tbc1d10c</th>\n",
       "      <th>Rom1</th>\n",
       "      <th>Smpd2</th>\n",
       "      <th>Ctsf</th>\n",
       "      <th>Fgd2</th>\n",
       "      <th>Cct8</th>\n",
       "      <th>Mamdc2</th>\n",
       "      <th>Stip1</th>\n",
       "      <th>Gm28043</th>\n",
       "      <th>Cd27</th>\n",
       "      <th>Rdh5</th>\n",
       "      <th>Aldoc</th>\n",
       "      <th>Prss57</th>\n",
       "      <th>Arpc1b</th>\n",
       "      <th>Fut7</th>\n",
       "      <th>Cd86</th>\n",
       "      <th>Serpinf1</th>\n",
       "      <th>Cd9</th>\n",
       "      <th>Gm37274</th>\n",
       "      <th>Wdr38</th>\n",
       "      <th>Angptl6</th>\n",
       "      <th>Smad6</th>\n",
       "      <th>Chad</th>\n",
       "      <th>Arhgdib</th>\n",
       "      <th>Eogt</th>\n",
       "      <th>Llgl2</th>\n",
       "      <th>Cst7</th>\n",
       "      <th>E130215H24Rik</th>\n",
       "      <th>Gm27201</th>\n",
       "      <th>Pcna</th>\n",
       "      <th>Rnf114</th>\n",
       "      <th>Gchfr</th>\n",
       "      <th>Cacfd1</th>\n",
       "      <th>Jam3</th>\n",
       "      <th>Fkbp1a</th>\n",
       "      <th>Eps8</th>\n",
       "      <th>Epb41l1</th>\n",
       "      <th>Traf1</th>\n",
       "      <th>Pdia3</th>\n",
       "      <th>Mgst1</th>\n",
       "      <th>Slc2a6</th>\n",
       "      <th>Spint1</th>\n",
       "      <th>Lmo2</th>\n",
       "      <th>Eng</th>\n",
       "      <th>Skap2</th>\n",
       "      <th>Vamp5</th>\n",
       "      <th>Plxna1</th>\n",
       "      <th>Klrb1f</th>\n",
       "      <th>Tmem176b</th>\n",
       "      <th>Mcm2</th>\n",
       "      <th>Slc52a3</th>\n",
       "      <th>Cct7</th>\n",
       "      <th>Ptgs1</th>\n",
       "      <th>Cnn2</th>\n",
       "      <th>Prim1</th>\n",
       "      <th>Rwdd2a</th>\n",
       "      <th>Matk</th>\n",
       "      <th>Atp5b</th>\n",
       "      <th>Cdk4</th>\n",
       "      <th>Robo4</th>\n",
       "      <th>Gm15915</th>\n",
       "      <th>Gm10101</th>\n",
       "      <th>Abhd4</th>\n",
       "      <th>Rab36</th>\n",
       "      <th>Metap2</th>\n",
       "      <th>Fzr1</th>\n",
       "      <th>Pa2g4</th>\n",
       "      <th>Smim24</th>\n",
       "      <th>Gm16104</th>\n",
       "      <th>Perp</th>\n",
       "      <th>Fig4</th>\n",
       "      <th>Myct1</th>\n",
       "      <th>Lsp1</th>\n",
       "      <th>Alpk3</th>\n",
       "      <th>Zfp28</th>\n",
       "      <th>Zfp78</th>\n",
       "      <th>Zfp773</th>\n",
       "      <th>Mill2</th>\n",
       "      <th>Gpr4</th>\n",
       "      <th>Nectin2</th>\n",
       "      <th>Tyrobp</th>\n",
       "      <th>Plekhf1</th>\n",
       "      <th>Nkg7</th>\n",
       "      <th>Osbpl1a</th>\n",
       "      <th>Slc27a6</th>\n",
       "      <th>Gm4951</th>\n",
       "      <th>Zfp438</th>\n",
       "      <th>Rab18</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>HSPC_025</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.392129</td>\n",
       "      <td>8.852337</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.614548</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.711045</td>\n",
       "      <td>7.977803</td>\n",
       "      <td>8.117451</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.195180</td>\n",
       "      <td>7.977803</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.173640</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.912375</td>\n",
       "      <td>8.427644</td>\n",
       "      <td>7.839405</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.935712</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.021134</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.309000</td>\n",
       "      <td>10.293674</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.275971</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.014787</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.832751</td>\n",
       "      <td>8.774285</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>1.832751</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.118770</td>\n",
       "      <td>7.285499</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.135838</td>\n",
       "      <td>8.744431</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.852337</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.832751</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.225016</td>\n",
       "      <td>8.876132</td>\n",
       "      <td>7.940672</td>\n",
       "      <td>6.184685</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.691769</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.491677</td>\n",
       "      <td>7.161885</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.832751</td>\n",
       "      <td>6.779938</td>\n",
       "      <td>8.490658</td>\n",
       "      <td>11.925211</td>\n",
       "      <td>7.410259</td>\n",
       "      <td>3.317239</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10.416407</td>\n",
       "      <td>4.242991</td>\n",
       "      <td>2.275971</td>\n",
       "      <td>1.832751</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.894815</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.681046</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.723202</td>\n",
       "      <td>4.141925</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.574401</td>\n",
       "      <td>7.174734</td>\n",
       "      <td>2.275971</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.614548</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.888576</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.806760</td>\n",
       "      <td>8.268934</td>\n",
       "      <td>3.491677</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.585122</td>\n",
       "      <td>2.888576</td>\n",
       "      <td>2.614548</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.344797</td>\n",
       "      <td>6.461289</td>\n",
       "      <td>7.285499</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.593666</td>\n",
       "      <td>6.657127</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.275971</td>\n",
       "      <td>8.655561</td>\n",
       "      <td>9.077708</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.832751</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>7.695253</td>\n",
       "      <td>10.437884</td>\n",
       "      <td>1.832751</td>\n",
       "      <td>7.814991</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>5.935712</td>\n",
       "      <td>4.588530</td>\n",
       "      <td>2.275971</td>\n",
       "      <td>9.025466</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.118771</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>7.161885</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10.103505</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.888576</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.977803</td>\n",
       "      <td>6.675324</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.054751</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.101455</td>\n",
       "      <td>7.040782</td>\n",
       "      <td>9.449536</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.310278</td>\n",
       "      <td>8.495788</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.888576</td>\n",
       "      <td>8.687292</td>\n",
       "      <td>7.940672</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>11.307754</td>\n",
       "      <td>7.781782</td>\n",
       "      <td>7.894815</td>\n",
       "      <td>8.361752</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.888576</td>\n",
       "      <td>9.067410</td>\n",
       "      <td>4.509590</td>\n",
       "      <td>8.310278</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.343549</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.671352</td>\n",
       "      <td>7.564672</td>\n",
       "      <td>10.551846</td>\n",
       "      <td>6.763021</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>9.272583</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>8.021134</td>\n",
       "      <td>8.150349</td>\n",
       "      <td>2.275971</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.747791</td>\n",
       "      <td>8.130700</td>\n",
       "      <td>3.647281</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.593666</td>\n",
       "      <td>1.832751</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>7.790156</td>\n",
       "      <td>7.421084</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.779938</td>\n",
       "      <td>2.275971</td>\n",
       "      <td>6.079295</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.275971</td>\n",
       "      <td>2.888576</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.014787</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>8.182512</td>\n",
       "      <td>7.977803</td>\n",
       "      <td>4.141925</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>9.826553</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.822478</td>\n",
       "      <td>8.594715</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.796659</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.273603</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.141925</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>6.845691</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>6.923879</td>\n",
       "      <td>2.888576</td>\n",
       "      <td>5.776244</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.118771</td>\n",
       "      <td>8.475161</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.807313</td>\n",
       "      <td>7.122636</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.711045</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.242991</td>\n",
       "      <td>7.525084</td>\n",
       "      <td>2.275971</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.033241</td>\n",
       "      <td>9.167225</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.317239</td>\n",
       "      <td>7.747791</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.816341</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.088305</td>\n",
       "      <td>7.955639</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.315027</td>\n",
       "      <td>7.631440</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>6.079295</td>\n",
       "      <td>8.356122</td>\n",
       "      <td>7.554876</td>\n",
       "      <td>9.390178</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.887028</td>\n",
       "      <td>1.832751</td>\n",
       "      <td>9.681046</td>\n",
       "      <td>9.032541</td>\n",
       "      <td>10.105184</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.282898</td>\n",
       "      <td>6.502641</td>\n",
       "      <td>3.787723</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.730490</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.992392</td>\n",
       "      <td>7.902559</td>\n",
       "      <td>8.274914</td>\n",
       "      <td>7.668250</td>\n",
       "      <td>9.339726</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.063203</td>\n",
       "      <td>9.710022</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>4.337438</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.593666</td>\n",
       "      <td>7.320609</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.832751</td>\n",
       "      <td>7.871328</td>\n",
       "      <td>7.584065</td>\n",
       "      <td>1.189716</td>\n",
       "      <td>1.832751</td>\n",
       "      <td>10.034692</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.832751</td>\n",
       "      <td>3.317239</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.347433</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.377367</td>\n",
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       "      <td>1.318950</td>\n",
       "      <td>0.377367</td>\n",
       "      <td>6.563421</td>\n",
       "      <td>0.377367</td>\n",
       "      <td>9.440054</td>\n",
       "      <td>1.134796</td>\n",
       "      <td>1.134796</td>\n",
       "      <td>7.707927</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.377367</td>\n",
       "      <td>5.359726</td>\n",
       "      <td>9.581316</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.134796</td>\n",
       "      <td>1.134796</td>\n",
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       "      <td>1.883902</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.318950</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            8430408G22Rik  Plp1  Zfp947    Bhlhb9     Vps35   Slc18a1  \\\n",
       "HSPC_025              0.0   0.0     0.0  5.392129  8.852337  0.000000   \n",
       "HSPC_031              0.0   0.0     0.0  0.686872  7.637939  0.000000   \n",
       "HSPC_037              0.0   0.0     0.0  1.869808  7.938080  0.000000   \n",
       "LT-HSC_001            0.0   0.0     0.0  7.965715  5.885018  0.000000   \n",
       "HSPC_001              0.0   0.0     0.0  8.395500  0.000000  0.377367   \n",
       "\n",
       "             Fam107b  Gm14230   Plekhn1  Ankrd6  9030619P08Rik     Prtn3  \\\n",
       "HSPC_025    2.614548      0.0  0.000000     0.0       6.711045  7.977803   \n",
       "HSPC_031    6.838205      0.0  0.000000     0.0       8.951078  8.584765   \n",
       "HSPC_037    9.405107      0.0  0.000000     0.0       7.199831  9.495433   \n",
       "LT-HSC_001  8.962827      0.0  0.000000     0.0       2.364517  8.080749   \n",
       "HSPC_001    0.676211      0.0  0.676211     0.0       0.000000  8.923709   \n",
       "\n",
       "               Lrrn4  Mrgpre   Gm25926    Plppr3     Memo1    Cdkn1c  \\\n",
       "HSPC_025    8.117451     0.0  0.000000  8.195180  7.977803  0.000000   \n",
       "HSPC_031    0.000000     0.0  0.000000  6.956259  7.579348  0.000000   \n",
       "HSPC_037    0.000000     0.0  0.000000  7.394504  3.164226  0.000000   \n",
       "LT-HSC_001  0.000000     0.0  4.137438  3.749470  2.364517  0.000000   \n",
       "HSPC_001    0.377367     0.0  0.000000  8.851780  9.012407  7.123321   \n",
       "\n",
       "                Gm2a  Phxr4        B2m    Tbxas1    Glipr2  Tcf15    Trim58  \\\n",
       "HSPC_025    9.173640    0.0  12.912375  8.427644  7.839405    0.0  1.189716   \n",
       "HSPC_031    4.175851    0.0  13.622584  7.800662  0.000000    0.0  0.686872   \n",
       "HSPC_037    8.086368    0.0  13.104234  9.083711  8.014129    0.0  0.000000   \n",
       "LT-HSC_001  7.347331    0.0  13.944537  8.516418  3.749470    0.0  0.000000   \n",
       "HSPC_001    7.640356    0.0  12.746870  9.232729  9.914646    0.0  0.000000   \n",
       "\n",
       "            D930028M14Rik  1700010I14Rik   Gm10384      Sla2  Trp53i13  \\\n",
       "HSPC_025              0.0            0.0  0.000000  0.000000  5.935712   \n",
       "HSPC_031              0.0            0.0  0.686872  0.000000  0.000000   \n",
       "HSPC_037              0.0            0.0  0.000000  8.418471  0.000000   \n",
       "LT-HSC_001            0.0            0.0  0.000000  0.000000  0.000000   \n",
       "HSPC_001              0.0            0.0  5.069857  0.000000  0.000000   \n",
       "\n",
       "            Gm17586      Gypc     Clic5    Tubb4b  AC149090.1   Gm26580  \\\n",
       "HSPC_025        0.0  8.021134  0.000000  7.309000   10.293674  0.000000   \n",
       "HSPC_031        0.0  7.018651  1.150286  3.253543    7.387780  0.686872   \n",
       "HSPC_037        0.0  2.657566  0.000000  8.337902   10.692584  0.000000   \n",
       "LT-HSC_001      0.0  7.552600  0.000000  3.749470    9.893764  6.820748   \n",
       "HSPC_001        0.0  1.628905  0.000000  9.412471   11.118833  0.000000   \n",
       "\n",
       "              Clec1a      Ccl9    Gimap3  Zscan18      Spi1  Ccl6  \\\n",
       "HSPC_025    0.000000  2.275971  0.000000      0.0  9.014787   0.0   \n",
       "HSPC_031    0.000000  0.000000  0.000000      0.0  6.348589   0.0   \n",
       "HSPC_037    1.218731  8.500077  0.000000      0.0  8.308001   0.0   \n",
       "LT-HSC_001  2.364517  0.000000  0.000000      0.0  6.872760   0.0   \n",
       "HSPC_001    0.000000  0.676211  0.377367      0.0  6.802432   0.0   \n",
       "\n",
       "            2900041M22Rik      Klk8   Gm37637       Gp9     Idh3a   Akr1c13  \\\n",
       "HSPC_025         0.000000  0.000000  0.000000  1.832751  8.774285  1.189716   \n",
       "HSPC_031         0.686872  0.686872  0.000000  0.000000  2.827390  8.409573   \n",
       "HSPC_037         0.000000  7.275944  0.000000  0.000000  8.862937  0.000000   \n",
       "LT-HSC_001       0.000000  7.520353  0.000000  0.000000  2.364517  0.000000   \n",
       "HSPC_001         0.000000  4.414804  0.377367  7.107768  8.010188  5.867946   \n",
       "\n",
       "            2810408A11Rik      Npr2  Ephx1   Pik3ip1  ENSMUSG00000043858  \\\n",
       "HSPC_025         1.189716  1.832751    0.0  3.118770            7.285499   \n",
       "HSPC_031         0.686872  1.782055    0.0  8.765434            8.059983   \n",
       "HSPC_037         0.000000  1.218731    0.0  8.954567            2.316800   \n",
       "LT-HSC_001       0.000000  3.217169    0.0  7.232592            7.107933   \n",
       "HSPC_001         0.000000  9.303379    0.0  8.824449            1.134796   \n",
       "\n",
       "            Gm26789     Grina      Txnip   Gm26541  Dnajb3       Msn  Gm37124  \\\n",
       "HSPC_025        0.0  7.135838   8.744431  0.000000     0.0  8.852337      0.0   \n",
       "HSPC_031        0.0  8.638735   9.676164  0.686872     0.0  1.782055      0.0   \n",
       "HSPC_037        0.0  2.316800  11.106246  0.000000     0.0  8.510617      0.0   \n",
       "LT-HSC_001      0.0  8.564652  11.130502  0.000000     0.0  9.931038      0.0   \n",
       "HSPC_001        0.0  1.482235   8.987981  0.000000     0.0  1.318950      0.0   \n",
       "\n",
       "            Srd5a1  Bhlhe40   Pomgnt2    Fcer1g  Gm37298  Lmo1  Rab20  \\\n",
       "HSPC_025       0.0      0.0  1.832751  1.189716      0.0   0.0    0.0   \n",
       "HSPC_031       0.0      0.0  1.150286  1.150286      0.0   0.0    0.0   \n",
       "HSPC_037       0.0      0.0  1.869808  5.397461      0.0   0.0    0.0   \n",
       "LT-HSC_001     0.0      0.0  0.000000  7.584142      0.0   0.0    0.0   \n",
       "HSPC_001       0.0      0.0  0.377367  0.000000      0.0   0.0    0.0   \n",
       "\n",
       "                Cd69  Gm2788   Gm14276      Napa      Cd24a     Nsun2  \\\n",
       "HSPC_025    1.189716     0.0  0.000000  7.225016   8.876132  7.940672   \n",
       "HSPC_031    0.000000     0.0  0.000000  9.235683  10.222019  2.946297   \n",
       "HSPC_037    2.316800     0.0  0.000000  8.006701   9.250198  6.744074   \n",
       "LT-HSC_001  8.397178     0.0  5.095857  8.414827   9.184807  3.217169   \n",
       "HSPC_001    0.377367     0.0  0.000000  1.482235   7.239191  8.617097   \n",
       "\n",
       "            Marveld2    Ms4a4b  Gm17590       Cdk6    Tada2b  Gm5113  \\\n",
       "HSPC_025    6.184685  1.189716      0.0   8.691769  1.189716     0.0   \n",
       "HSPC_031    0.000000  0.000000      0.0   9.531507  0.000000     0.0   \n",
       "HSPC_037    1.869808  0.000000      0.0  10.085909  0.000000     0.0   \n",
       "LT-HSC_001  0.000000  2.364517      0.0   4.442877  0.000000     0.0   \n",
       "HSPC_001    0.000000  0.000000      0.0   2.921687  0.000000     0.0   \n",
       "\n",
       "               Mki67      Btg2  Gnat2  Tcaf1  Slc35e4     Reep2  \\\n",
       "HSPC_025    3.491677  7.161885    0.0    0.0      0.0  1.832751   \n",
       "HSPC_031    1.500480  0.686872    0.0    0.0      0.0  0.000000   \n",
       "HSPC_037    1.218731  6.928313    0.0    0.0      0.0  0.000000   \n",
       "LT-HSC_001  2.364517  0.000000    0.0    0.0      0.0  0.000000   \n",
       "HSPC_001    1.762030  0.000000    0.0    0.0      0.0  0.000000   \n",
       "\n",
       "            8430419K02Rik     Pdgfd      H2-K1     Sesn1    Bcap29   Gm21814  \\\n",
       "HSPC_025         6.779938  8.490658  11.925211  7.410259  3.317239  0.000000   \n",
       "HSPC_031         0.000000  0.000000  11.665664  9.216587  5.672502  0.000000   \n",
       "HSPC_037         0.000000  1.218731  12.131326  5.568630  8.093396  1.218731   \n",
       "LT-HSC_001       0.000000  0.000000  13.092126  4.137438  3.217169  0.000000   \n",
       "HSPC_001         0.000000  0.000000  12.396286  0.000000  0.676211  0.000000   \n",
       "\n",
       "                Eif5a     Stk25    Maged1    Zfp449  9130604C24Rik  \\\n",
       "HSPC_025    10.416407  4.242991  2.275971  1.832751       1.189716   \n",
       "HSPC_031     9.484386  0.000000  1.150286  0.000000       0.000000   \n",
       "HSPC_037    10.313640  2.657566  1.869808  1.218731       0.000000   \n",
       "LT-HSC_001   9.639814  3.217169  8.187283  0.000000       0.000000   \n",
       "HSPC_001    11.169149  0.377367  9.699115  0.000000       0.000000   \n",
       "\n",
       "            6430590A07Rik    Tcirg1       Il4   Slc35a4   Cysltr2  Ap3m2  \\\n",
       "HSPC_025         0.000000  7.894815  0.000000  9.681046  1.189716    0.0   \n",
       "HSPC_031         0.000000  0.000000  0.000000  6.991254  0.000000    0.0   \n",
       "HSPC_037         7.682451  1.869808  1.218731  2.933024  0.000000    0.0   \n",
       "LT-HSC_001       0.000000  3.749470  6.074609  2.364517  2.364517    0.0   \n",
       "HSPC_001         0.377367  0.000000  0.000000  8.285068  0.000000    0.0   \n",
       "\n",
       "            Dsel      Cmtm7     Arl8b      Gbx2  Smim10l2a     Cyth4  \\\n",
       "HSPC_025     0.0   9.723202  4.141925  0.000000        0.0  7.574401   \n",
       "HSPC_031     0.0   9.159273  3.158217  7.403453        0.0  8.372889   \n",
       "HSPC_037     0.0   9.998750  7.772788  0.000000        0.0  1.218731   \n",
       "LT-HSC_001   0.0   8.742914  8.888979  0.000000        0.0  0.000000   \n",
       "HSPC_001     0.0  11.201561  0.923649  0.377367        0.0  0.676211   \n",
       "\n",
       "               S1pr4      Gdi1  Hdhd3      Vill   Slc38a6      Calu   Gm16565  \\\n",
       "HSPC_025    7.174734  2.275971    0.0  2.614548  0.000000  2.888576  0.000000   \n",
       "HSPC_031    8.587055  1.500480    0.0  8.401790  0.686872  2.017546  0.686872   \n",
       "HSPC_037    1.218731  8.148427    0.0  1.218731  0.000000  2.657566  1.218731   \n",
       "LT-HSC_001  8.227787  3.217169    0.0  2.364517  0.000000  8.685906  0.000000   \n",
       "HSPC_001    5.216270  9.912410    0.0  8.639983  0.000000  2.374501  7.993360   \n",
       "\n",
       "               Smim3     Sar1a  4833407H14Rik  B230217O12Rik  Ccdc39  Spata2l  \\\n",
       "HSPC_025    7.806760  8.268934       3.491677            0.0     0.0      0.0   \n",
       "HSPC_031    0.686872  1.500480       7.574740            0.0     0.0      0.0   \n",
       "HSPC_037    8.621744  7.815920       0.000000            0.0     0.0      0.0   \n",
       "LT-HSC_001  7.271861  9.312700       8.914017            0.0     0.0      0.0   \n",
       "HSPC_001    0.000000  7.224846       0.676211            0.0     0.0      0.0   \n",
       "\n",
       "            Arxes2       Dut    Ifngr1     Rasa3     Fbxl2     Pde4b  \\\n",
       "HSPC_025       0.0  8.585122  2.888576  2.614548  0.000000  8.344797   \n",
       "HSPC_031       0.0  7.527841  3.342958  0.000000  1.150286  8.598449   \n",
       "HSPC_037       0.0  4.637700  8.546913  2.316800  0.000000  3.538458   \n",
       "LT-HSC_001     0.0  7.487369  4.909226  0.000000  0.000000  7.271861   \n",
       "HSPC_001       0.0  7.224846  9.392715  0.000000  0.000000  9.060862   \n",
       "\n",
       "              Ptp4a3      Cdt1     Fxyd1     Arl11    Shisa8  Dleu7   Tmem173  \\\n",
       "HSPC_025    6.461289  7.285499  0.000000  7.593666  6.657127    0.0  2.275971   \n",
       "HSPC_031    1.782055  1.782055  0.000000  0.686872  1.150286    0.0  2.219938   \n",
       "HSPC_037    8.592276  1.218731  0.000000  0.000000  1.218731    0.0  7.615671   \n",
       "LT-HSC_001  2.364517  3.217169  5.982925  0.000000  8.548753    0.0  4.137438   \n",
       "HSPC_001    1.628905  0.923649  0.000000  0.000000  4.434885    0.0  8.771148   \n",
       "\n",
       "              Atxn10       Rpn2      Ccl3    Nudt16     Kif3c      Hars  \\\n",
       "HSPC_025    8.655561   9.077708  0.000000  1.832751  1.189716  7.695253   \n",
       "HSPC_031    2.219938   9.404856  0.686872  1.150286  0.686872  2.017546   \n",
       "HSPC_037    1.218731   7.514567  8.833854  2.316800  1.218731  2.657566   \n",
       "LT-HSC_001  2.364517   3.749470  0.000000  2.364517  0.000000  3.749470   \n",
       "HSPC_001    1.628905  10.008081  8.286449  8.276747  8.061140  1.762030   \n",
       "\n",
       "                 Ccl4     Myo1g       Cpq  Cox6a2  Sdc3      Dok2     Fcgrt  \\\n",
       "HSPC_025    10.437884  1.832751  7.814991     0.0   0.0  1.189716  5.935712   \n",
       "HSPC_031     0.000000  0.686872  0.000000     0.0   0.0  7.824144  7.148337   \n",
       "HSPC_037     4.475001  6.943951  3.694521     0.0   0.0  1.218731  0.000000   \n",
       "LT-HSC_001   7.645229  2.364517  3.749470     0.0   0.0  3.217169  7.917005   \n",
       "HSPC_001     0.000000  8.663575  4.586200     0.0   0.0  8.923709  0.000000   \n",
       "\n",
       "               Elmo1      Cyc1      Calr  Gpr18    Tbxa2r    Gpr183  Naaa  \\\n",
       "HSPC_025    4.588530  2.275971  9.025466    0.0  1.189716  0.000000   0.0   \n",
       "HSPC_031    2.827390  2.397399  9.564413    0.0  6.623022  0.000000   0.0   \n",
       "HSPC_037    8.664848  6.490844  7.482801    0.0  5.647156  1.218731   0.0   \n",
       "LT-HSC_001  7.989468  7.674830  8.397178    0.0  2.364517  0.000000   0.0   \n",
       "HSPC_001    7.925790  1.482235  9.740544    0.0  8.240127  0.000000   0.0   \n",
       "\n",
       "            Gm11110      Alad       Taz    Echdc3    Cd300a  Slc39a4  Zfp128  \\\n",
       "HSPC_025        0.0  3.118771  1.189716  1.189716  7.161885      0.0     0.0   \n",
       "HSPC_031        0.0  2.397399  7.032157  0.000000  0.000000      0.0     0.0   \n",
       "HSPC_037        0.0  2.316800  1.218731  0.000000  0.000000      0.0     0.0   \n",
       "LT-HSC_001      0.0  8.207678  7.866592  0.000000  0.000000      0.0     0.0   \n",
       "HSPC_001        0.0  1.883902  8.577000  0.000000  0.000000      0.0     0.0   \n",
       "\n",
       "            Gm26819      Ispd      Itm2b  Zfp647  Gm16861  Nek3     Gata2  \\\n",
       "HSPC_025        0.0  0.000000  10.103505     0.0      0.0   0.0  2.888576   \n",
       "HSPC_031        0.0  0.000000  11.892010     0.0      0.0   0.0  1.782055   \n",
       "HSPC_037        0.0  0.000000  10.392692     0.0      0.0   0.0  7.160213   \n",
       "LT-HSC_001      0.0  0.000000  10.297362     0.0      0.0   0.0  7.584142   \n",
       "HSPC_001        0.0  7.520972   9.818564     0.0      0.0   0.0  0.000000   \n",
       "\n",
       "              Prss16    Lppos     Lhcgr    Fundc1       Lat  Tnfrsf26  \\\n",
       "HSPC_025    0.000000  0.00000  0.000000  7.977803  6.675324  0.000000   \n",
       "HSPC_031    0.000000  0.00000  1.150286  0.000000  7.828021  1.150286   \n",
       "HSPC_037    0.000000  0.00000  0.000000  2.316800  1.218731  8.355550   \n",
       "LT-HSC_001  0.000000  5.77998  0.000000  8.267186  4.137438  2.364517   \n",
       "HSPC_001    0.377367  0.00000  0.000000  0.377367  9.422563  0.377367   \n",
       "\n",
       "               Prr36     Vldlr     Mfge8     Enkur  Rcor2       Ndn      Btla  \\\n",
       "HSPC_025    0.000000  7.054751  0.000000  0.000000    0.0  0.000000  0.000000   \n",
       "HSPC_031    5.925034  0.000000  0.686872  0.000000    0.0  0.000000  0.686872   \n",
       "HSPC_037    0.000000  2.933024  0.000000  1.218731    0.0  0.000000  0.000000   \n",
       "LT-HSC_001  0.000000  2.364517  2.364517  0.000000    0.0  0.000000  0.000000   \n",
       "HSPC_001    0.000000  8.668884  0.377367  0.000000    0.0  5.918739  0.000000   \n",
       "\n",
       "                 Zyx      Cd33      Dkc1     Rab37     Cdcp1     Hoxa9  \\\n",
       "HSPC_025    9.101455  7.040782  9.449536  0.000000  0.000000  8.310278   \n",
       "HSPC_031    8.915083  0.000000  9.006865  8.155637  0.000000  9.640235   \n",
       "HSPC_037    8.669560  9.162687  9.873687  7.755167  1.218731  7.615671   \n",
       "LT-HSC_001  7.645229  3.217169  8.058464  7.107933  0.000000  7.232592   \n",
       "HSPC_001    4.265819  0.000000  9.042166  0.923649  0.000000  3.519027   \n",
       "\n",
       "                 Oat  Vegfc      Gas6     Oasl2     Tacc1  Colgalt1  Xdh  \\\n",
       "HSPC_025    8.495788    0.0  0.000000  2.888576  8.687292  7.940672  0.0   \n",
       "HSPC_031    2.397399    0.0  0.000000  2.017546  9.543345  0.686872  0.0   \n",
       "HSPC_037    1.218731    0.0  0.000000  8.626598  9.247050  2.316800  0.0   \n",
       "LT-HSC_001  7.760152    0.0  8.267186  4.137438  9.967373  0.000000  0.0   \n",
       "HSPC_001    8.720921    0.0  0.000000  8.950983  8.410789  0.676211  0.0   \n",
       "\n",
       "               Rab32      Dusp2  Tmem176a     Gnai3     Rnf13     Elane  \\\n",
       "HSPC_025    1.189716  11.307754  7.781782  7.894815  8.361752  0.000000   \n",
       "HSPC_031    0.000000   9.419062  9.750561  1.150286  0.686872  0.686872   \n",
       "HSPC_037    7.371559   6.779369  7.133183  1.869807  8.246273  0.000000   \n",
       "LT-HSC_001  8.187283   6.971475  8.926375  9.143059  7.063866  0.000000   \n",
       "HSPC_001    0.000000   0.676211  8.584884  6.136699  7.233470  1.628905   \n",
       "\n",
       "                Cd48    Mthfd1       Igkc      Fnta  Bok   Ripply3    Ptger2  \\\n",
       "HSPC_025    2.888576  9.067410   4.509590  8.310278  0.0  0.000000  0.000000   \n",
       "HSPC_031    6.549791  8.233698   3.653748  1.500480  0.0  0.000000  0.000000   \n",
       "HSPC_037    6.183499  7.348242   3.963623  8.808450  0.0  1.218731  1.218731   \n",
       "LT-HSC_001  3.749470  3.217169  12.461628  5.543737  0.0  0.000000  0.000000   \n",
       "HSPC_001    0.377367  1.996276   2.288830  9.442536  0.0  0.000000  0.000000   \n",
       "\n",
       "               P2rx7     Wdfy2     Eif1a     Gstm7   Tmem14c  2900018N21Rik  \\\n",
       "HSPC_025    0.000000  0.000000  7.343549  0.000000  5.671352       7.564672   \n",
       "HSPC_031    0.000000  0.000000  8.662811  0.000000  3.253543       0.000000   \n",
       "HSPC_037    1.218731  1.218731  7.914462  4.190334  7.133183       0.000000   \n",
       "LT-HSC_001  0.000000  0.000000  9.110936  0.000000  3.217169       0.000000   \n",
       "HSPC_001    0.000000  0.000000  6.111968  0.000000  2.604657       0.000000   \n",
       "\n",
       "                  Mpl     Sash3      Tgm2   Gm19569      Ehd3      Cish  \\\n",
       "HSPC_025    10.551846  6.763021  0.000000  1.189716  0.000000  0.000000   \n",
       "HSPC_031     2.219938  9.646834  0.000000  0.000000  0.000000  0.000000   \n",
       "HSPC_037     1.869807  6.813823  0.000000  0.000000  0.000000  1.218731   \n",
       "LT-HSC_001  10.136473  8.483344  0.000000  0.000000  2.364517  9.033078   \n",
       "HSPC_001    10.683373  8.965724  3.853357  0.000000  0.377367  0.000000   \n",
       "\n",
       "              Calml4    Mesdc2     Nfil3      Tcn2     Saraf     Meis1  \\\n",
       "HSPC_025    1.189716  9.272583  0.000000  1.189716  8.021134  8.150349   \n",
       "HSPC_031    0.000000  9.962022  0.686872  8.785511  9.802712  8.826781   \n",
       "HSPC_037    0.000000  9.162687  0.000000  6.689457  9.741228  7.605873   \n",
       "LT-HSC_001  0.000000  8.397178  0.000000  8.305537  8.466517  7.760152   \n",
       "HSPC_001    0.000000  1.482235  0.000000  0.000000  9.960822  7.587515   \n",
       "\n",
       "            Serpina3g       Pcx    Gpr171     Cks1b      Coa5  Arhgap27os3  \\\n",
       "HSPC_025     2.275971  0.000000  7.747791  8.130700  3.647281          0.0   \n",
       "HSPC_031     0.686872  0.000000  8.545278  2.697797  9.449579          0.0   \n",
       "HSPC_037     2.316800  1.218731  8.760682  3.363442  2.933024          0.0   \n",
       "LT-HSC_001   9.522611  0.000000  7.760152  2.364517  2.364517          0.0   \n",
       "HSPC_001     1.318950  0.000000  9.564895  7.530335  1.628905          0.0   \n",
       "\n",
       "               Farsa      Ctsl     Iigp1     P2ry14      Cd82   Slc18a2  \\\n",
       "HSPC_025    7.593666  1.832751  1.189716   7.790156  7.421084  0.000000   \n",
       "HSPC_031    8.201186  0.000000  0.000000   8.900430  2.397399  1.500480   \n",
       "HSPC_037    8.636256  7.160213  1.869807  10.783395  8.057904  0.000000   \n",
       "LT-HSC_001  4.137438  8.058464  4.909226   3.749470  3.749470  0.000000   \n",
       "HSPC_001    8.609387  8.121239  0.676211   8.514683  1.762030  0.377367   \n",
       "\n",
       "               Cd302    Parp12    Isyna1    S100a8  B130034C11Rik  Arhgap27  \\\n",
       "HSPC_025    0.000000  6.779938  2.275971  6.079295       0.000000  2.275971   \n",
       "HSPC_031    0.000000  0.686872  3.582099  0.000000       0.000000  3.506705   \n",
       "HSPC_037    0.000000  6.235258  3.164226  0.000000       0.000000  8.429623   \n",
       "LT-HSC_001  2.364517  8.700371  0.000000  0.000000       2.364517  8.080749   \n",
       "HSPC_001    0.000000  0.000000  1.628905  0.377367       0.000000  0.000000   \n",
       "\n",
       "                Klf1  Gm26740       Cd84      Bag2   Tmem123   Emilin1  \\\n",
       "HSPC_025    2.888576      0.0   9.014787  1.189716  8.182512  7.977803   \n",
       "HSPC_031    2.219938      0.0  10.152610  1.150286  6.348589  0.000000   \n",
       "HSPC_037    3.694520      0.0   1.869807  0.000000  7.710151  1.218731   \n",
       "LT-HSC_001  0.000000      0.0   8.532677  8.580378  7.674830  8.305537   \n",
       "HSPC_001    2.288830      0.0   1.628905  1.134796  1.134796  0.000000   \n",
       "\n",
       "            4930568A12Rik   Clec11a      Mat2a    Tespa1     Wfdc17  \\\n",
       "HSPC_025         4.141925  1.189716   9.826553  0.000000   9.822478   \n",
       "HSPC_031         0.000000  0.000000   7.780798  1.150286   1.150286   \n",
       "HSPC_037         0.000000  0.000000   9.498083  0.000000  10.651504   \n",
       "LT-HSC_001       0.000000  0.000000   4.137438  0.000000   7.645229   \n",
       "HSPC_001         0.000000  0.377367  10.135483  0.676211   1.318950   \n",
       "\n",
       "              Tspan13  Dyrk2    S100a9  F10  Pde1b     Gcnt2      Ppic  \\\n",
       "HSPC_025     8.594715    0.0  6.796659  0.0    0.0  7.273603  0.000000   \n",
       "HSPC_031     8.951078    0.0  0.000000  0.0    0.0  0.000000  0.000000   \n",
       "HSPC_037    10.660998    0.0  0.000000  0.0    0.0  7.482801  0.000000   \n",
       "LT-HSC_001   8.685906    0.0  0.000000  0.0    0.0  8.901552  2.364517   \n",
       "HSPC_001     8.785881    0.0  0.000000  0.0    0.0  7.854899  0.377367   \n",
       "\n",
       "               Zfp72    Gm4841       Ckb  C130013H08Rik     Spo11      Ctss  \\\n",
       "HSPC_025    4.141925  1.189716  6.845691       0.000000  1.189716  6.923879   \n",
       "HSPC_031    0.000000  0.000000  6.293577       8.896743  7.116992  0.686872   \n",
       "HSPC_037    0.000000  0.000000  0.000000       0.000000  0.000000  8.729440   \n",
       "LT-HSC_001  0.000000  2.364517  2.364517       0.000000  8.227787  5.885018   \n",
       "HSPC_001    0.000000  7.663942  0.000000       0.377367  0.000000  5.670382   \n",
       "\n",
       "               Vwa5a  Serpinb1a     Trib3   Slc28a2      Xbp1   Tsc22d3  \\\n",
       "HSPC_025    2.888576   5.776244  0.000000  0.000000  3.118771  8.475161   \n",
       "HSPC_031    8.445345   8.842198  0.000000  0.686872  7.045538  1.782055   \n",
       "HSPC_037    1.218731   8.854687  1.218731  0.000000  5.303604  9.218403   \n",
       "LT-HSC_001  0.000000   3.217169  5.982925  7.645229  5.543737  9.705823   \n",
       "HSPC_001    0.000000   7.499681  0.000000  0.000000  9.520952  9.448104   \n",
       "\n",
       "                 Cd74  Nhlrc1       Rac2      Il15     Ift43  Tnfrsf13c  \\\n",
       "HSPC_025     0.000000     0.0  10.807313  7.122636  0.000000   6.711045   \n",
       "HSPC_031     0.000000     0.0   8.900430  0.686872  1.500480   9.076959   \n",
       "HSPC_037     1.869807     0.0  11.052258  1.218731  0.000000   0.000000   \n",
       "LT-HSC_001  10.273376     0.0   9.438827  0.000000  0.000000   8.863498   \n",
       "HSPC_001     0.000000     0.0   8.703439  1.318950  6.563421   0.377367   \n",
       "\n",
       "            Gm10451     Plod2    Minpp1        Cs  Gm21967    Trim27  \\\n",
       "HSPC_025        0.0  4.242991  7.525084  2.275971      0.0  4.033241   \n",
       "HSPC_031        0.0  0.000000  2.219938  9.871007      0.0  8.938581   \n",
       "HSPC_037        0.0  0.000000  3.164226  6.156907      0.0  7.755167   \n",
       "LT-HSC_001      0.0  0.000000  8.166596  4.694814      0.0  3.217169   \n",
       "HSPC_001        0.0  0.000000  8.443370  1.318950      0.0  9.606986   \n",
       "\n",
       "                Rrm1     Krt18     Rap1b     Anxa2  D130040H23Rik     Tmsb4x  \\\n",
       "HSPC_025    9.167225  0.000000  3.317239  7.747791       0.000000   9.816341   \n",
       "HSPC_031    2.017546  6.977358  2.697797  1.150286       8.195195  10.778556   \n",
       "HSPC_037    2.933024  0.000000  2.933024  3.164226       0.000000   9.700377   \n",
       "LT-HSC_001  3.217169  8.516418  9.464477  2.364517       3.217169  10.330287   \n",
       "HSPC_001    6.723001  0.377367  8.671001  0.377367       0.000000  10.844519   \n",
       "\n",
       "            1810034E14Rik  2810021J22Rik  F630028O10Rik    Cyb5r3  B3gnt3  \\\n",
       "HSPC_025         0.000000       0.000000       0.000000  1.189716     0.0   \n",
       "HSPC_031         0.000000       0.000000       0.000000  2.017546     0.0   \n",
       "HSPC_037         0.000000       0.000000       8.977543  8.577312     0.0   \n",
       "LT-HSC_001       2.364517       2.364517       0.000000  2.364517     0.0   \n",
       "HSPC_001         0.000000       0.000000       0.676211  1.883902     0.0   \n",
       "\n",
       "               Laptm5    Adam11     Rab17     Pkia  Hist3h2ba  Cyp27a1  \\\n",
       "HSPC_025    10.088305  7.955639  0.000000  0.00000   0.000000      0.0   \n",
       "HSPC_031    10.784055  0.000000  0.000000  0.00000   5.004467      0.0   \n",
       "HSPC_037     9.332705  1.869807  0.000000  0.00000   0.000000      0.0   \n",
       "LT-HSC_001  10.442098  0.000000  7.107933  3.74947   5.885018      0.0   \n",
       "HSPC_001    10.464271  3.882894  0.000000  0.00000   0.000000      0.0   \n",
       "\n",
       "                Zfp36      Mcm5     Ssc4d   Gm45837  Lmcd1      Fgf3  \\\n",
       "HSPC_025    11.315027  7.631440  0.000000  0.000000    0.0  1.189716   \n",
       "HSPC_031     5.565109  3.506705  0.000000  0.000000    0.0  0.000000   \n",
       "HSPC_037     3.835337  2.933024  1.218731  1.218731    0.0  1.218731   \n",
       "LT-HSC_001   8.449492  2.364517  0.000000  0.000000    0.0  0.000000   \n",
       "HSPC_001     8.356553  1.482235  0.000000  7.281391    0.0  0.000000   \n",
       "\n",
       "                Car1    Adssl1     Il21r   Slc50a1  Serpinb9   Pttg1ip  \\\n",
       "HSPC_025    6.079295  8.356122  7.554876  9.390178  0.000000  7.887028   \n",
       "HSPC_031    5.706594  0.686872  7.135881  7.615685  0.000000  9.234223   \n",
       "HSPC_037    6.016053  7.348242  7.999236  8.367196  6.285223  8.531469   \n",
       "LT-HSC_001  4.442877  0.000000  7.192224  8.286489  3.217169  3.749470   \n",
       "HSPC_001    4.173225  8.508774  0.923649  7.330454  0.000000  9.775414   \n",
       "\n",
       "              Fam83d    Tspan32  Tnfrsf13b       Gdi2  Nim1k    Mapk12  \\\n",
       "HSPC_025    1.832751   9.681046   9.032541  10.105184    0.0  6.282898   \n",
       "HSPC_031    0.000000   9.659944   1.500480   8.627656    0.0  0.000000   \n",
       "HSPC_037    0.000000  10.283226   2.316800   7.930251    0.0  0.000000   \n",
       "LT-HSC_001  0.000000   9.312700   7.150694   8.595934    0.0  0.000000   \n",
       "HSPC_001    0.377367   8.996450   0.377367   9.137149    0.0  0.000000   \n",
       "\n",
       "              Wfdc18     Thbs1  Chil5  Mpst   Selenop   Gm43852       Hk3  \\\n",
       "HSPC_025    6.502641  3.787723    0.0   0.0  7.730490  0.000000  7.992392   \n",
       "HSPC_031    0.000000  2.017546    0.0   0.0  9.060576  0.000000  8.904107   \n",
       "HSPC_037    9.087235  0.000000    0.0   0.0  9.492777  0.000000  1.869807   \n",
       "LT-HSC_001  2.364517  2.364517    0.0   0.0  8.671295  0.000000  3.217169   \n",
       "HSPC_001    0.000000  0.000000    0.0   0.0  9.482276  7.088883  0.377367   \n",
       "\n",
       "               Irgm1     Nceh1     Myl10      Tmx1  Zcchc24     Acsl5  \\\n",
       "HSPC_025    7.902559  8.274914  7.668250  9.339726      0.0  8.063203   \n",
       "HSPC_031    1.782055  6.942020  8.069839  8.233698      0.0  4.631208   \n",
       "HSPC_037    6.864006  2.657566  1.869807  5.303604      0.0  7.336441   \n",
       "LT-HSC_001  8.058464  3.217169  2.364517  3.749470      0.0  8.166596   \n",
       "HSPC_001    1.318950  8.542711  7.809477  1.482235      0.0  9.920888   \n",
       "\n",
       "             Tnfaip8  4632427E13Rik     Hspa9  Hid1     Gstt1   Il12rb1  Ficd  \\\n",
       "HSPC_025    9.710022       1.189716  4.337438   0.0  7.593666  7.320609   0.0   \n",
       "HSPC_031    9.284465       6.783355  7.214989   0.0  0.000000  0.000000   0.0   \n",
       "HSPC_037    7.450320       1.869807  4.190334   0.0  0.000000  0.000000   0.0   \n",
       "LT-HSC_001  7.018409       7.150694  6.160812   0.0  0.000000  0.000000   0.0   \n",
       "HSPC_001    3.968042       1.318950  9.261827   0.0  0.000000  0.000000   0.0   \n",
       "\n",
       "            Bbs10      Esam   Unc93b1     Casp4       F2r    Dynlt3  \\\n",
       "HSPC_025      0.0  1.832751  7.871328  7.584065  1.189716  1.832751   \n",
       "HSPC_031      0.0  7.377236  0.686872  0.000000  0.686872  0.686872   \n",
       "HSPC_037      0.0  1.218731  9.111674  4.386210  1.869807  8.467986   \n",
       "LT-HSC_001    0.0  2.364517  4.442877  2.364517  0.000000  2.364517   \n",
       "HSPC_001      0.0  9.772458  6.786892  0.676211  0.676211  5.030808   \n",
       "\n",
       "               Adgrg1   Tmem38a     Stap1   Cep170b  Lpxn     Frmd8  Doc2g  \\\n",
       "HSPC_025    10.034692  0.000000  1.832751  3.317239   0.0  5.347433    0.0   \n",
       "HSPC_031    10.663397  0.000000  0.000000  0.000000   0.0  7.255855    0.0   \n",
       "HSPC_037     7.849521  0.000000  9.859326  0.000000   0.0  7.953614    0.0   \n",
       "LT-HSC_001  11.081615  4.137438  3.217169  3.749470   0.0  9.594069    0.0   \n",
       "HSPC_001    11.404691  0.000000  7.758600  7.079347   0.0  7.278616    0.0   \n",
       "\n",
       "            Ighv1-23  Hrh2       Bgn    Ifi206       Fes    Apol7e  Srl  \\\n",
       "HSPC_025         0.0   0.0  0.000000  5.634622  7.554876  6.502641  0.0   \n",
       "HSPC_031         0.0   0.0  0.686872  1.150286  4.021900  0.000000  0.0   \n",
       "HSPC_037         0.0   0.0  1.218731  0.000000  1.218731  0.000000  0.0   \n",
       "LT-HSC_001       0.0   0.0  2.364517  0.000000  2.364517  0.000000  0.0   \n",
       "HSPC_001         0.0   0.0  6.625896  0.000000  0.000000  0.000000  0.0   \n",
       "\n",
       "               Ifi47     Cdca7       Srm  Smagp    Zfp418    Zfp882      Mmp2  \\\n",
       "HSPC_025    7.640730  9.278547  8.971261    0.0  0.000000  7.012433  0.000000   \n",
       "HSPC_031    2.219938  3.849535  2.827391    0.0  0.000000  0.000000  8.467882   \n",
       "HSPC_037    6.813823  7.428252  3.164226    0.0  0.000000  0.000000  2.316800   \n",
       "LT-HSC_001  2.364517  3.217169  0.000000    0.0  0.000000  0.000000  0.000000   \n",
       "HSPC_001    9.288282  8.392936  9.193486    0.0  0.377367  0.000000  0.000000   \n",
       "\n",
       "              Fam32a      Flna       Lyz2       Cd53  Mapk11    Sptbn1  \\\n",
       "HSPC_025    8.035294  1.832751   9.438924   7.879200     0.0  6.159051   \n",
       "HSPC_031    9.385257  8.095797  10.225698   7.393023     0.0  9.179137   \n",
       "HSPC_037    8.907487  3.164226   4.386210  10.124163     0.0  9.413556   \n",
       "LT-HSC_001  8.532677  6.820749   9.979284   8.124310     0.0  6.461820   \n",
       "HSPC_001    0.923649  9.289661  10.363761   7.273049     0.0  4.099659   \n",
       "\n",
       "              Mapre3  Nr0b2     Ptprc     Gulp1      Cd63  Nsg1   Fam131a  \\\n",
       "HSPC_025    0.000000    0.0  8.028232  0.000000  8.156838   0.0  0.000000   \n",
       "HSPC_031    0.000000    0.0  1.782055  5.637585  8.561668   0.0  5.449074   \n",
       "HSPC_037    3.164226    0.0  9.759018  0.000000  1.218731   0.0  0.000000   \n",
       "LT-HSC_001  0.000000    0.0  5.261087  0.000000  8.305537   0.0  0.000000   \n",
       "HSPC_001    1.134796    0.0  2.977514  0.000000  9.935939   0.0  0.000000   \n",
       "\n",
       "                Dntt    Ifi213      Tcp1  Stard8   Clptm1l    Sigirr  \\\n",
       "HSPC_025    2.888576  1.832751  8.400554     0.0  4.426081  1.832751   \n",
       "HSPC_031    9.228369  4.223722  2.946297     0.0  6.380618  9.852094   \n",
       "HSPC_037    3.164226  0.000000  7.275944     0.0  7.238389  2.933024   \n",
       "LT-HSC_001  4.694814  0.000000  9.522611     0.0  8.124310  7.703835   \n",
       "HSPC_001    1.996276  0.000000  4.493504     0.0  1.134796  9.102259   \n",
       "\n",
       "               Robo3  Il17rb     Mcfd2    Vpreb1    Casp12  Zbtb3      Ppt1  \\\n",
       "HSPC_025    0.000000     0.0  9.345421  0.000000  0.000000    0.0  8.400554   \n",
       "HSPC_031    0.000000     0.0  9.311023  0.000000  0.686872    0.0  0.000000   \n",
       "HSPC_037    0.000000     0.0  3.164226  0.000000  1.869807    0.0  4.978682   \n",
       "LT-HSC_001  0.000000     0.0  0.000000  3.217169  3.217169    0.0  9.849024   \n",
       "HSPC_001    3.592379     0.0  0.923649  0.000000  7.607558    0.0  0.377367   \n",
       "\n",
       "                H1f0  C730034F03Rik     Tpst2     Pnrc1    Sdhaf2   Hnrnpdl  \\\n",
       "HSPC_025    3.118771            0.0  8.989556  7.174734  7.704143  7.273603   \n",
       "HSPC_031    7.273021            0.0  1.500480  9.495397  7.209055  3.427154   \n",
       "HSPC_037    9.915931            0.0  7.173540  2.933024  0.000000  9.615036   \n",
       "LT-HSC_001  7.674830            0.0  8.770595  6.652419  3.749470  2.364517   \n",
       "HSPC_001    0.377367            0.0  0.000000  3.995344  7.902545  9.643577   \n",
       "\n",
       "              Cyp7b1      Ptpre  Slc25a45     Wdr35      Capg     Sf3b3  \\\n",
       "HSPC_025    0.000000   8.433001  4.337438  0.000000  8.124090  9.656065   \n",
       "HSPC_031    0.000000  10.735345  6.022986  0.000000  7.565481  2.555402   \n",
       "HSPC_037    0.000000   8.678935  7.874218  3.164226  7.383077  2.316800   \n",
       "LT-HSC_001  0.000000   4.442877  3.217169  0.000000  4.442877  9.455977   \n",
       "HSPC_001    0.377367   0.923649  8.056288  0.000000  1.883902  1.628905   \n",
       "\n",
       "               Gata1  Spry1     Abce1  Rnf180   Golph3l    P2ry10    Adgrg3  \\\n",
       "HSPC_025    0.000000    0.0  7.095865     0.0  8.454235  0.000000  6.132952   \n",
       "HSPC_031    2.397399    0.0  8.570951     0.0  8.009667  8.874422  1.150286   \n",
       "HSPC_037    1.869807    0.0  2.316800     0.0  3.363442  0.000000  9.080177   \n",
       "LT-HSC_001  2.364517    0.0  3.749470     0.0  9.055756  0.000000  2.364517   \n",
       "HSPC_001    1.628905    0.0  8.057907     0.0  9.902980  0.676211  1.482235   \n",
       "\n",
       "               Fkbp4  F2rl2      Gbp2     Plcg2  Ccdc189  4930486L24Rik  \\\n",
       "HSPC_025    7.040782    0.0  0.000000  5.905197      0.0       0.000000   \n",
       "HSPC_031    9.864415    0.0  0.000000  6.984322      0.0       0.000000   \n",
       "HSPC_037    9.040723    0.0  0.000000  8.283626      0.0       0.000000   \n",
       "LT-HSC_001  9.264843    0.0  9.174482  9.530727      0.0       7.917005   \n",
       "HSPC_001    8.315172    0.0  0.000000  8.858300      0.0       0.000000   \n",
       "\n",
       "            E230001N04Rik     Itih5    Chrnb1  Gm16386  Thnsl2   Gm16712  \\\n",
       "HSPC_025         1.189716  7.839405  5.809578      0.0     0.0  7.297297   \n",
       "HSPC_031         0.000000  7.694245  0.000000      0.0     0.0  0.000000   \n",
       "HSPC_037         0.000000  1.218731  0.000000      0.0     0.0  0.000000   \n",
       "LT-HSC_001       0.000000  8.080749  3.217169      0.0     0.0  0.000000   \n",
       "HSPC_001         0.000000  3.083081  0.000000      0.0     0.0  0.000000   \n",
       "\n",
       "               Top2a    Gm5577     Nt5c3  Nlrp10      Ctf1  Il18bp    Il1rl2  \\\n",
       "HSPC_025    3.491677  0.000000  8.490658     0.0  0.000000     0.0  0.000000   \n",
       "HSPC_031    2.397399  0.686872  8.259764     0.0  0.000000     0.0  0.686872   \n",
       "HSPC_037    1.869807  0.000000  8.314031     0.0  0.000000     0.0  4.190334   \n",
       "LT-HSC_001  8.286489  0.000000  3.217169     0.0  0.000000     0.0  0.000000   \n",
       "HSPC_001    2.921687  0.000000  9.107741     0.0  0.377367     0.0  0.000000   \n",
       "\n",
       "              Gm5148       Car2       Vim  A630033H20Rik      Cd81    Zfp563  \\\n",
       "HSPC_025    0.000000  11.130318  8.207737       0.000000  8.993188  0.000000   \n",
       "HSPC_031    0.000000   9.967304  8.682216       0.000000  4.520574  5.723342   \n",
       "HSPC_037    0.000000  10.867803  1.218731       1.218731  8.014129  0.000000   \n",
       "LT-HSC_001  5.779980   8.227787  3.217169       0.000000  9.055756  0.000000   \n",
       "HSPC_001    6.608321  10.655834  1.628905       0.000000  9.932853  0.000000   \n",
       "\n",
       "              Ctla2a    Mfsd2b      Idh2  Tert  Pwwp2b   Atp6ap2     Ces2g  \\\n",
       "HSPC_025    9.521714  2.614548  9.882450   0.0     0.0  9.506549  2.275971   \n",
       "HSPC_031    8.989663  1.782055  2.827391   0.0     0.0  8.030005  3.342958   \n",
       "HSPC_037    9.506006  3.164226  7.472055   0.0     0.0  7.119476  3.164226   \n",
       "LT-HSC_001  8.414827  0.000000  7.453613   0.0     0.0  3.749470  2.364517   \n",
       "HSPC_001    8.069193  0.676211  8.487300   0.0     0.0  8.833932  1.628905   \n",
       "\n",
       "                Gba2  4931428F04Rik      Apoe      Sdha      Dlg3  Igkv4-50  \\\n",
       "HSPC_025    3.915699            0.0  6.923879  9.690023  1.189716       0.0   \n",
       "HSPC_031    0.000000            0.0  8.137007  2.017546  0.686872       0.0   \n",
       "HSPC_037    1.869807            0.0  2.316800  7.428252  0.000000       0.0   \n",
       "LT-HSC_001  0.000000            0.0  7.965715  6.971475  0.000000       0.0   \n",
       "HSPC_001    5.509264            0.0  2.604657  1.883902  8.511140       0.0   \n",
       "\n",
       "               Dhx58  Zfp661      Ccr9      Rgs2      Ctsc     Parp8  \\\n",
       "HSPC_025    0.000000     0.0  0.000000  7.285499  7.631440  3.118771   \n",
       "HSPC_031    0.686872     0.0  0.000000  8.477787  8.566318  6.502060   \n",
       "HSPC_037    4.558643     0.0  1.218731  9.457801  2.316800  2.316800   \n",
       "LT-HSC_001  0.000000     0.0  2.364517  9.078081  7.271861  2.364517   \n",
       "HSPC_001    7.281391     0.0  0.000000  0.377367  9.534391  0.676211   \n",
       "\n",
       "               Tspo2  5430420F09Rik     Pear1       Ltb  Gm26512  AA467197  \\\n",
       "HSPC_025    2.275971            0.0  7.161885  8.926381      0.0  1.189716   \n",
       "HSPC_031    1.500480            0.0  0.000000  1.500480      0.0  0.000000   \n",
       "HSPC_037    2.316800            0.0  1.218731  2.933024      0.0  0.000000   \n",
       "LT-HSC_001  0.000000            0.0  8.837559  9.021605      0.0  0.000000   \n",
       "HSPC_001    1.318950            0.0  0.676211  7.709989      0.0  0.000000   \n",
       "\n",
       "              Unc5cl      Mtpn       Mcm6    Atp2a3      Tyms     Il12a  \\\n",
       "HSPC_025    0.000000  9.342576  10.287772  5.742120  2.275971  8.350471   \n",
       "HSPC_031    0.686872  2.397399   3.253543  8.393966  2.017546  8.251127   \n",
       "HSPC_037    0.000000  9.855197   7.968982  1.869807  2.933024  9.090753   \n",
       "LT-HSC_001  0.000000  7.941566   8.548753  8.286489  0.000000  0.000000   \n",
       "HSPC_001    6.074058  0.923649   6.970060  0.676211  1.628905  1.134796   \n",
       "\n",
       "               Celf2       Axl      Tpm4  Gm3739    Cyp2j9     Fxyd5  \\\n",
       "HSPC_025    8.744431  7.847452  2.614548     0.0  1.189716  9.812235   \n",
       "HSPC_031    7.719509  0.000000  0.686872     0.0  1.500480  9.514768   \n",
       "HSPC_037    8.577312  1.218731  8.148427     0.0  8.320036  9.018738   \n",
       "LT-HSC_001  9.078081  0.000000  4.137438     0.0  7.347332  9.078081   \n",
       "HSPC_001    3.519027  0.000000  0.676211     0.0  8.524086  8.845230   \n",
       "\n",
       "            B230216N24Rik     Trbc2   Fam161b   Gm30948     Apbb1    Igfbp4  \\\n",
       "HSPC_025         3.915699  0.000000  1.189716  1.189716  0.000000  6.796659   \n",
       "HSPC_031         0.000000  0.000000  0.686872  8.533455  0.686872  7.664200   \n",
       "HSPC_037         0.000000  0.000000  7.535363  0.000000  0.000000  7.849521   \n",
       "LT-HSC_001       0.000000  2.364517  0.000000  2.364517  0.000000  3.217169   \n",
       "HSPC_001         0.377367  0.000000  0.000000  0.000000  0.000000  4.394439   \n",
       "\n",
       "              Pcp4l1    Rassf5    Cyp2r1  Smoc1       Srgn      Pygm  Gm43200  \\\n",
       "HSPC_025    7.695253  7.659135  0.000000    0.0   9.716627  7.320609      0.0   \n",
       "HSPC_031    8.304972  1.150286  0.000000    0.0  10.264835  0.000000      0.0   \n",
       "HSPC_037    2.657566  5.150271  5.303604    0.0  11.012021  0.000000      0.0   \n",
       "LT-HSC_001  3.217169  4.442877  2.364517    0.0  10.437787  8.483344      0.0   \n",
       "HSPC_001    0.000000  9.883934  0.000000    0.0  10.435905  0.000000      0.0   \n",
       "\n",
       "            Gca   Arhgef6       Fah  BC017643       Ak3     Icam1   Gm10505  \\\n",
       "HSPC_025    0.0  9.428233  0.000000  1.189716  6.983514  1.189716  0.000000   \n",
       "HSPC_031    0.0  9.858742  9.715412  8.730652  1.500480  6.462704  0.686872   \n",
       "HSPC_037    0.0  2.933024  0.000000  0.000000  9.275141  1.869807  0.000000   \n",
       "LT-HSC_001  0.0  4.909226  0.000000  3.749470  8.449492  0.000000  0.000000   \n",
       "HSPC_001    0.0  9.766528  0.377367  9.098330  6.086805  0.000000  0.000000   \n",
       "\n",
       "               C1qbp     Efna1   AW112010  Tnks1bp1     Anxa1     Fgf11  \\\n",
       "HSPC_025    8.536176  0.000000   8.156838       0.0  1.832751  0.000000   \n",
       "HSPC_031    4.595264  0.000000  10.762946       0.0  0.686872  0.000000   \n",
       "HSPC_037    7.644670  0.000000   8.289759       0.0  7.146761  0.000000   \n",
       "LT-HSC_001  8.124310  2.364517   4.694814       0.0  3.217169  6.766791   \n",
       "HSPC_001    8.816817  0.000000   7.525660       0.0  8.147335  0.377367   \n",
       "\n",
       "                Layn  Gm19331  Rbpms2    Tspan3  Ighv9-1   Gm43201     Arrdc1  \\\n",
       "HSPC_025    0.000000      0.0     0.0  7.535083      0.0  0.000000   7.515015   \n",
       "HSPC_031    0.000000      0.0     0.0  8.989663      0.0  0.686872   0.686872   \n",
       "HSPC_037    3.164226      0.0     0.0  8.331971      0.0  0.000000  10.386982   \n",
       "LT-HSC_001  7.941566      0.0     0.0  5.666688      0.0  0.000000   8.286489   \n",
       "HSPC_001    3.401495      0.0     0.0  6.237319      0.0  0.000000   1.134796   \n",
       "\n",
       "                Hjurp  4921507P07Rik       Sla    Ms4a6b  Zfp551  \\\n",
       "HSPC_025     8.274914        0.00000  4.242991  6.711045     0.0   \n",
       "HSPC_031     7.892380        0.00000  1.782055  2.697797     0.0   \n",
       "HSPC_037    10.113830        6.55335  2.657566  1.218731     0.0   \n",
       "LT-HSC_001   8.863498        0.00000  3.217169  2.364517     0.0   \n",
       "HSPC_001     1.482235        0.00000  8.566798  0.000000     0.0   \n",
       "\n",
       "            2810468N07Rik  Tnf     Serp1  Mfap2  Arhgef18  Slc25a29     Hmox1  \\\n",
       "HSPC_025              0.0  0.0  7.095865    0.0  0.000000       0.0  0.000000   \n",
       "HSPC_031              0.0  0.0  2.219938    0.0  2.697797       0.0  0.686872   \n",
       "HSPC_037              0.0  0.0  7.077557    0.0  4.916631       0.0  0.000000   \n",
       "LT-HSC_001            0.0  0.0  8.305537    0.0  3.749470       0.0  0.000000   \n",
       "HSPC_001              0.0  0.0  1.134796    0.0  9.515068       0.0  0.000000   \n",
       "\n",
       "                  Pkm  Arhgap15     Ddx39  Fv1  Gnb5       Tes    Lysmd2  \\\n",
       "HSPC_025     9.000423  7.712979  5.045572  0.0   0.0  7.871328  1.189716   \n",
       "HSPC_031     8.785511  6.830496  7.317821  0.0   0.0  7.659856  0.000000   \n",
       "HSPC_037    10.516827  8.050700  8.395907  0.0   0.0  6.707893  1.218731   \n",
       "LT-HSC_001  10.229170  4.137438  3.749470  0.0   0.0  8.187283  0.000000   \n",
       "HSPC_001     9.761568  8.943118  1.628905  0.0   0.0  9.188320  7.544266   \n",
       "\n",
       "            Mmp11    Pgrmc1  Gm42979     Efna4      Uba7       Xist     Sumo3  \\\n",
       "HSPC_025      0.0  8.774285      0.0  0.000000  8.256901   9.091325  9.254540   \n",
       "HSPC_031      0.0  2.219938      0.0  0.000000  2.219938   9.460858  3.342958   \n",
       "HSPC_037      0.0  8.107351      0.0  7.700976  8.515859  10.286297  8.546913   \n",
       "LT-HSC_001    0.0  7.674830      0.0  0.000000  9.055756   9.377142  7.787507   \n",
       "HSPC_001      0.0  0.676211      0.0  5.974679  8.515861   9.857676  9.503825   \n",
       "\n",
       "                 Flt3      Mycn  1300017J02Rik     Scn1b      Rab38  \\\n",
       "HSPC_025     7.054751  2.888576       1.832751  0.000000   7.399354   \n",
       "HSPC_031     8.124452  8.716082       0.000000  7.672848   1.500480   \n",
       "HSPC_037    10.304583  2.657566       0.000000  0.000000   2.933024   \n",
       "LT-HSC_001   3.217169  3.217169       0.000000  2.364517  10.104202   \n",
       "HSPC_001     3.882894  8.969171       0.000000  0.000000   1.134796   \n",
       "\n",
       "            ENSMUSG00000096970   Tnfaip2     Hdac2  Ccr7  Irf6     Mndal  \\\n",
       "HSPC_025                   0.0  0.000000  9.681046   0.0   0.0  8.570612   \n",
       "HSPC_031                   0.0  2.017546  8.830651   0.0   0.0  0.686872   \n",
       "HSPC_037                   0.0  2.933024  2.316800   0.0   0.0  8.760682   \n",
       "LT-HSC_001                 0.0  0.000000  9.078081   0.0   0.0  9.153609   \n",
       "HSPC_001                   0.0  0.676211  0.676211   0.0   0.0  5.082642   \n",
       "\n",
       "                Fut4     Casp1   Slc14a1      Rit1     Ifi203  Zfp93  \\\n",
       "HSPC_025    0.000000  6.418716  1.832751  1.189716   1.832751    0.0   \n",
       "HSPC_031    0.000000  8.568637  6.101957  0.000000  10.293858    0.0   \n",
       "HSPC_037    1.218731  7.906503  3.164226  1.869807   8.833854    0.0   \n",
       "LT-HSC_001  0.000000  3.749470  0.000000  0.000000   9.705823    0.0   \n",
       "HSPC_001    7.000696  0.000000  0.923649  0.676211   1.482235    0.0   \n",
       "\n",
       "               Calr3  2210010C04Rik   Gm38243   Gm43313   Slc25a5      Bcam  \\\n",
       "HSPC_025    0.000000            0.0  0.000000  0.000000  9.903830  1.189716   \n",
       "HSPC_031    0.686872            0.0  8.186162  0.000000  3.427154  0.000000   \n",
       "HSPC_037    0.000000            0.0  1.869807  1.218731  8.484121  0.000000   \n",
       "LT-HSC_001  0.000000            0.0  0.000000  0.000000  9.489678  0.000000   \n",
       "HSPC_001    0.000000            0.0  0.377367  0.000000  9.410571  0.000000   \n",
       "\n",
       "            Ighv1-74  Traf3ip3    Lgals9   Gm26982   Clec10a     Klhl8  Islr  \\\n",
       "HSPC_025    1.189716  1.189716  8.459496  0.000000  0.000000  1.832751   0.0   \n",
       "HSPC_031    0.000000  6.076110  4.075063  0.686872  0.686872  0.000000   0.0   \n",
       "HSPC_037    0.000000  9.076634  8.372984  0.000000  6.285223  0.000000   0.0   \n",
       "LT-HSC_001  0.000000  3.217169  9.066961  0.000000  0.000000  0.000000   0.0   \n",
       "HSPC_001    0.000000  8.086751  2.531943  0.000000  0.000000  0.000000   0.0   \n",
       "\n",
       "            Ighv1-76     Crlf3  Ighv1-77      Lcp2  Rapsn  Cd38   Gm37423  \\\n",
       "HSPC_025         0.0  1.832751  1.189716  5.935712    0.0   0.0  1.189716   \n",
       "HSPC_031         0.0  7.065378  0.000000  5.387358    0.0   0.0  0.000000   \n",
       "HSPC_037         0.0  8.484121  0.000000  1.218731    0.0   0.0  0.000000   \n",
       "LT-HSC_001       0.0  2.364517  0.000000  8.466517    0.0   0.0  0.000000   \n",
       "HSPC_001         0.0  8.571341  0.000000  0.377367    0.0   0.0  0.000000   \n",
       "\n",
       "              Selplg     Clip3  Ccdc157  Uggt2       Mpo      Eya1      Ctso  \\\n",
       "HSPC_025    2.275971  1.189716  0.00000    0.0  2.275971  0.000000  1.189716   \n",
       "HSPC_031    2.017546  0.000000  0.00000    0.0  2.697797  7.877493  5.672502   \n",
       "HSPC_037    3.363442  0.000000  0.00000    0.0  2.657566  0.000000  8.765091   \n",
       "LT-HSC_001  9.164084  0.000000  0.00000    0.0  3.217169  0.000000  4.694814   \n",
       "HSPC_001    0.676211  0.000000  6.38397    0.0  3.031264  5.004176  6.759286   \n",
       "\n",
       "              Gm26917      Rarb     Cmtm6  Metrnl       Rgs1     Ptpn6  \\\n",
       "HSPC_025     9.707812  0.000000  0.000000     0.0   8.786894  8.978607   \n",
       "HSPC_031    11.297833  0.686872  2.697797     0.0   1.500480  7.999391   \n",
       "HSPC_037    10.404042  0.000000  7.566005     0.0   3.694520  8.923351   \n",
       "LT-HSC_001   8.756821  0.000000  0.000000     0.0   3.749470  9.121723   \n",
       "HSPC_001    10.834868  0.000000  7.183903     0.0  10.077985  8.673117   \n",
       "\n",
       "               Cd1d1  Lyrm1    Prkaa2    Gm4759     Aplp2    Gm8995     Gng11  \\\n",
       "HSPC_025    8.691769    0.0  0.000000  9.785260  1.832751  8.967574  0.000000   \n",
       "HSPC_031    1.500480    0.0  0.686872  5.967830  2.827391  8.502254  0.686872   \n",
       "HSPC_037    7.545649    0.0  0.000000  5.986154  8.467986  4.190334  0.000000   \n",
       "LT-HSC_001  3.749470    0.0  0.000000  9.184806  8.595934  6.591640  7.271861   \n",
       "HSPC_001    8.596073    0.0  0.377367  0.676211  1.628905  1.628905  8.208397   \n",
       "\n",
       "            Tmem150b  Abhd6    Gm5111  Ankrd50    Neurl3   Slc44a2     Gm128  \\\n",
       "HSPC_025         0.0    0.0  6.983514   0.0000  6.779938  3.491677  0.000000   \n",
       "HSPC_031         0.0    0.0  8.161794   4.0219  8.753254  8.177073  0.686872   \n",
       "HSPC_037         0.0    0.0  6.553350   0.0000  8.301946  7.635068  7.394504   \n",
       "LT-HSC_001       0.0    0.0  0.000000   0.0000  6.591640  8.449492  0.000000   \n",
       "HSPC_001         0.0    0.0  0.000000   0.0000  0.923649  0.676211  0.000000   \n",
       "\n",
       "             Fam132a  2810414N06Rik      M6pr  Ankrd33b      Hexa  Pdcd1lg2  \\\n",
       "HSPC_025    2.614548            0.0  8.782703  0.000000  9.004027  0.000000   \n",
       "HSPC_031    3.722005            0.0  5.865923  8.880034  2.219938  0.000000   \n",
       "HSPC_037    7.348242            0.0  9.388059  0.000000  8.361384  1.218731   \n",
       "LT-HSC_001  3.217169            0.0  4.137438  0.000000  8.548753  0.000000   \n",
       "HSPC_001    4.787026            0.0  8.127421  0.377367  9.011572  7.007417   \n",
       "\n",
       "              Dnajc9       Lck     Ccnb2       Wls   Gramd1a   Gm37642  \\\n",
       "HSPC_025    4.802330  4.734524  3.491677  1.189716  7.320609  0.000000   \n",
       "HSPC_031    2.397399  0.000000  1.500480  7.005018  9.698571  0.686872   \n",
       "HSPC_037    7.682451  8.641061  1.869807  8.636256  9.756806  6.309572   \n",
       "LT-HSC_001  3.217169  0.000000  0.000000  2.364517  9.789383  0.000000   \n",
       "HSPC_001    1.482235  0.676211  0.377367  0.000000  0.377367  0.377367   \n",
       "\n",
       "             St8sia4  Igkv12-44    Sqstm1  Slc25a35     Tipin  4930555A03Rik  \\\n",
       "HSPC_025    9.299230        0.0  9.501458  1.189716  8.555954       0.000000   \n",
       "HSPC_031    1.150286        0.0  9.231299  0.000000  5.449074       6.492322   \n",
       "HSPC_037    9.612592        0.0  9.883858  1.218731  7.615671       2.657566   \n",
       "LT-HSC_001  4.137438        0.0  6.591640  8.641622  4.137438       0.000000   \n",
       "HSPC_001    0.676211        0.0  1.482235  0.377367  8.144289       6.763263   \n",
       "\n",
       "            Rn18s-rs5    Samd12  B9d1      Ncf4        Myc  Uaca       Irf9  \\\n",
       "HSPC_025    15.299863  0.000000   0.0  1.832751   9.365173   0.0   6.106372   \n",
       "HSPC_031    14.849717  0.686872   0.0  0.000000   2.697797   0.0   1.500480   \n",
       "HSPC_037    15.812094  0.000000   0.0  6.074055  10.234780   0.0   7.359948   \n",
       "LT-HSC_001  15.593200  0.000000   0.0  7.063866   9.421470   0.0  10.020216   \n",
       "HSPC_001    14.466537  0.000000   0.0  0.377367   6.021909   0.0   0.676211   \n",
       "\n",
       "               Paics     Gstm1     Padi4     Tor3a     Rgs18  Slc26a6  \\\n",
       "HSPC_025    9.656065  8.176136  6.258964  2.275971  9.118180      0.0   \n",
       "HSPC_031    3.722005  8.149453  8.417314  0.686872  8.817061      0.0   \n",
       "HSPC_037    8.271282  7.312546  1.869807  0.000000  9.998750      0.0   \n",
       "LT-HSC_001  5.261087  7.674830  0.000000  0.000000  7.760152      0.0   \n",
       "HSPC_001    8.618195  9.168968  8.661447  0.000000  8.059525      0.0   \n",
       "\n",
       "               Ppm1g    Zfand5     Smpd5  Hdac9      Gnl3  Ecm1    Rnase6  \\\n",
       "HSPC_025    3.491677  9.901899  0.000000    0.0  9.362368   0.0  1.189716   \n",
       "HSPC_031    7.209055  8.634314  0.686872    0.0  5.925034   0.0  0.686872   \n",
       "HSPC_037    7.857800  9.885883  0.000000    0.0  8.808450   0.0  2.316800   \n",
       "LT-HSC_001  3.217169  7.584142  0.000000    0.0  5.885018   0.0  0.000000   \n",
       "HSPC_001    1.996276  1.996276  0.000000    0.0  8.620389   0.0  0.000000   \n",
       "\n",
       "            Lgals3bp   Slc2a10     Rdh14  Icos     Dnah1  Amt      Fut8  \\\n",
       "HSPC_025    7.764886  0.000000  1.189716   0.0  0.000000  0.0  5.392129   \n",
       "HSPC_031    8.972252  0.000000  7.839589   0.0  0.000000  0.0  8.354193   \n",
       "HSPC_037    7.898499  0.000000  0.000000   0.0  0.000000  0.0  1.869807   \n",
       "LT-HSC_001  8.548753  2.364517  2.364517   0.0  7.107933  0.0  7.018409   \n",
       "HSPC_001    9.508570  0.000000  1.482235   0.0  0.000000  0.0  1.134796   \n",
       "\n",
       "               Itpkc     Ap1s2  Rgs11    Hpcal1   Gm43178  Rnase4     Adgrl4  \\\n",
       "HSPC_025    2.275971  0.000000    0.0  0.000000  0.000000     0.0   8.226370   \n",
       "HSPC_031    0.000000  0.000000    0.0  3.158217  0.686872     0.0   9.163881   \n",
       "HSPC_037    1.218731  2.657566    0.0  0.000000  0.000000     0.0  10.679799   \n",
       "LT-HSC_001  0.000000  0.000000    0.0  4.137438  0.000000     0.0   8.035830   \n",
       "HSPC_001    0.000000  0.000000    0.0  7.676647  0.000000     0.0   8.396780   \n",
       "\n",
       "                Nek6      Clk1      Eya2     Csf3r  Fkbp1b      Pirb  \\\n",
       "HSPC_025    0.000000  9.475731  2.275971  1.832751     0.0  1.189716   \n",
       "HSPC_031    5.084431  9.607904  0.686872  8.894896     0.0  0.686872   \n",
       "HSPC_037    0.000000  9.476740  2.316800  4.291594     0.0  0.000000   \n",
       "LT-HSC_001  3.749470  4.694814  6.710738  0.000000     0.0  8.499976   \n",
       "HSPC_001    0.000000  2.100526  9.437569  0.676211     0.0  0.000000   \n",
       "\n",
       "               Msmo1   Gm15133      Pim2  Cldn15  Gm28557     Ric8a  Triqk  \\\n",
       "HSPC_025    1.832751  3.491677  1.189716     0.0      0.0  7.148920    0.0   \n",
       "HSPC_031    0.000000  0.000000  0.686872     0.0      0.0  1.500480    0.0   \n",
       "HSPC_037    1.218731  0.000000  1.218731     0.0      0.0  9.889926    0.0   \n",
       "LT-HSC_001  9.447428  5.666688  0.000000     0.0      0.0  9.594069    0.0   \n",
       "HSPC_001    0.000000  0.000000  8.639983     0.0      0.0  9.758583    0.0   \n",
       "\n",
       "               Spns2  Cebpe   Tspan14     Itm2a      Ddx1  Sh3tc1  Slc22a18  \\\n",
       "HSPC_025    1.832751    0.0  9.018355  0.000000  8.280868     0.0  0.000000   \n",
       "HSPC_031    0.000000    0.0  6.861088  0.000000  9.492957     0.0  8.775508   \n",
       "HSPC_037    1.218731    0.0  8.233604  0.000000  8.384491     0.0  0.000000   \n",
       "LT-HSC_001  8.483344    0.0  9.340672  2.364517  0.000000     0.0  3.217169   \n",
       "HSPC_001    5.600985    0.0  9.989108  0.000000  1.318950     0.0  0.000000   \n",
       "\n",
       "                 Lcp1     Casp2    Epsti1     Ifi44    Phf11b      Ctsb  \\\n",
       "HSPC_025     9.322510  8.536176  0.000000  8.722721  7.756364  9.457444   \n",
       "HSPC_031     9.517171  0.000000  7.928939  2.397399  0.000000  3.056145   \n",
       "HSPC_037    10.199386  7.824394  1.869807  5.038175  0.000000  6.896517   \n",
       "LT-HSC_001  10.219159  0.000000  3.217169  9.078081  0.000000  9.887456   \n",
       "HSPC_001     9.627852  0.676211  7.553480  0.000000  0.000000  7.478070   \n",
       "\n",
       "                H2afy      Ctsg    Gimap9    Hsd3b7   Smpdl3a   Gm43162  \\\n",
       "HSPC_025     9.874597  0.000000  1.189716  1.832751  1.189716  6.763021   \n",
       "HSPC_031    11.210691  0.686872  9.372041  6.511734  9.587467  0.000000   \n",
       "HSPC_037    11.337700  0.000000  1.218731  2.933024  1.218731  0.000000   \n",
       "LT-HSC_001   8.342895  2.364517  8.876294  2.364517  9.368110  0.000000   \n",
       "HSPC_001     9.471989  1.628905  0.377367  8.708603  0.676211  0.000000   \n",
       "\n",
       "              Trim47      Cpa3       Cat     Cers2     Ifit3  Ifit1bl1  \\\n",
       "HSPC_025    0.000000  1.189716  3.317239  8.887885  1.189716  1.189716   \n",
       "HSPC_031    9.053970  1.500480  9.685810  5.184588  0.000000  0.000000   \n",
       "HSPC_037    1.218731  0.000000  8.867044  9.933662  8.367196  5.527704   \n",
       "LT-HSC_001  0.000000  0.000000  5.666688  5.982925  2.364517  5.095857   \n",
       "HSPC_001    0.000000  0.377367  8.396780  8.817774  0.377367  0.000000   \n",
       "\n",
       "            Slc9a3r2      Mcm3    Fscn1  Thbd      Cd93     Sept6      Irf5  \\\n",
       "HSPC_025    1.832751  8.922578  0.00000   0.0  2.275971  2.888576  0.000000   \n",
       "HSPC_031    0.000000  9.000010  0.00000   0.0  4.700515  8.140128  0.000000   \n",
       "HSPC_037    0.000000  7.359948  0.00000   0.0  8.246273  9.231205  1.218731   \n",
       "LT-HSC_001  0.000000  5.261087  0.00000   0.0  4.442877  3.217169  0.000000   \n",
       "HSPC_001    0.000000  1.883902  4.83315   0.0  0.000000  8.618195  0.000000   \n",
       "\n",
       "               Rab19      Ctsz  Rhbdf1      Wfs1     Mef2c     Blvrb  \\\n",
       "HSPC_025    1.189716  9.454813     0.0  6.542841  8.117451  1.832751   \n",
       "HSPC_031    1.500480  8.654102     0.0  0.000000  9.431856  3.909308   \n",
       "HSPC_037    0.000000  8.557117     0.0  0.000000  7.048918  3.963623   \n",
       "LT-HSC_001  0.000000  3.217169     0.0  0.000000  3.217169  3.217169   \n",
       "HSPC_001    0.000000  1.762030     0.0  0.000000  2.977514  3.031264   \n",
       "\n",
       "               Gimap1  Gimap7  Gimap4  4930515G01Rik     Hgfac     Gimap6  \\\n",
       "HSPC_025     8.378509     0.0     0.0            0.0  0.000000   8.627797   \n",
       "HSPC_031     3.506705     0.0     0.0            0.0  5.655149   8.634314   \n",
       "HSPC_037     6.129815     0.0     0.0            0.0  0.000000   9.427529   \n",
       "LT-HSC_001  10.082279     0.0     0.0            0.0  0.000000   7.760152   \n",
       "HSPC_001     8.331331     0.0     0.0            0.0  0.000000  10.336666   \n",
       "\n",
       "             Gm15201    Gimap5  BC035044       Ly6e  Hs3st1     Zfp62  \\\n",
       "HSPC_025    1.189716  1.189716  2.275971  11.533395     0.0  5.842161   \n",
       "HSPC_031    1.500480  6.861088  9.823251  10.901846     0.0  0.000000   \n",
       "HSPC_037    0.000000  7.857800  8.655380  10.146300     0.0  0.000000   \n",
       "LT-HSC_001  0.000000  7.232592  3.749470  11.172608     0.0  0.000000   \n",
       "HSPC_001    0.000000  0.377367  1.134796   9.692875     0.0  5.069857   \n",
       "\n",
       "              Vpreb3  Kcnh2      Hn1l        Hlf  9930012K11Rik  Sgsm1  \\\n",
       "HSPC_025    0.000000    0.0  4.663373   7.814991            0.0    0.0   \n",
       "HSPC_031    0.000000    0.0  1.782055   9.126594            0.0    0.0   \n",
       "HSPC_037    0.000000    0.0  6.235258  10.552968            0.0    0.0   \n",
       "LT-HSC_001  3.217169    0.0  6.591640   7.419049            0.0    0.0   \n",
       "HSPC_001    0.000000    0.0  1.482235   8.778042            0.0    0.0   \n",
       "\n",
       "                Gmpr    Lancl1   Slc16a1     Plcb2      Sdpr      Rhoh  \\\n",
       "HSPC_025    1.189716  1.189716  8.256901  8.333382  1.189716  9.164007   \n",
       "HSPC_031    0.000000  8.728580  2.219938  4.595264  0.000000  9.771850   \n",
       "HSPC_037    1.218731  0.000000  1.218731  8.014129  0.000000  4.783895   \n",
       "LT-HSC_001  8.267186  2.364517  0.000000  8.166596  0.000000  3.217169   \n",
       "HSPC_001    0.000000  0.923649  3.853357  8.359182  0.000000  8.839592   \n",
       "\n",
       "            Gm38250  Gm26532      Dock2    Pdlim2      Clk4     Nubp2  \\\n",
       "HSPC_025        0.0      0.0   7.721761  6.418716  7.879200  7.535083   \n",
       "HSPC_031        0.0      0.0   8.789493  0.000000  1.782055  9.018787   \n",
       "HSPC_037        0.0      0.0   6.943952  6.726097  2.933024  4.291594   \n",
       "LT-HSC_001      0.0      0.0  10.115040  7.732268  4.442877  4.694814   \n",
       "HSPC_001        0.0      0.0   0.923649  0.000000  4.690105  8.598301   \n",
       "\n",
       "              Treml2      Sell      Polm   Pglyrp2  Gm37829   Tsc22d1  \\\n",
       "HSPC_025    6.877476  0.000000  0.000000  6.968835      0.0  9.384659   \n",
       "HSPC_031    3.787179  8.822902  0.000000  5.322884      0.0  2.397399   \n",
       "HSPC_037    0.000000  3.164226  0.000000  8.582317      0.0  9.529518   \n",
       "LT-HSC_001  8.124310  4.137438  0.000000  7.584142      0.0  8.714692   \n",
       "HSPC_001    0.000000  1.318950  0.377367  7.408690      0.0  8.307024   \n",
       "\n",
       "            9130008F23Rik  Gm37558  Gm37706    Ptprcap       Hck  Adamts10  \\\n",
       "HSPC_025         0.000000      0.0      0.0   9.351091  0.000000  3.118771   \n",
       "HSPC_031         1.150286      0.0      0.0  10.055096  0.686872  0.000000   \n",
       "HSPC_037         0.000000      0.0      0.0   9.828064  1.218731  8.214389   \n",
       "LT-HSC_001       0.000000      0.0      0.0   9.912520  0.000000  5.095857   \n",
       "HSPC_001         0.000000      0.0      0.0  11.226616  0.000000  0.377367   \n",
       "\n",
       "                 Ly6a  Gm37598      Anxa5     Parvg  Acer2     Cd79a  \\\n",
       "HSPC_025     9.428233      0.0   7.545014  8.872193    0.0  0.000000   \n",
       "HSPC_031     8.612002      0.0   3.056145  8.751214    0.0  0.000000   \n",
       "HSPC_037     3.363442      0.0   2.316800  9.215184    0.0  0.000000   \n",
       "LT-HSC_001  10.283019      0.0  10.093283  4.442877    0.0  4.909226   \n",
       "HSPC_001     8.840533      0.0   8.171473  8.984579    0.0  0.000000   \n",
       "\n",
       "             Tmem175  Fcrl1  Dusp22    Ms4a4c     Bank1  Gm43149    Gatsl3  \\\n",
       "HSPC_025    6.693295    0.0     0.0  0.000000  1.189716      0.0  0.000000   \n",
       "HSPC_031    9.337102    0.0     0.0  0.000000  0.000000      0.0  0.000000   \n",
       "HSPC_037    1.218731    0.0     0.0  0.000000  0.000000      0.0  0.000000   \n",
       "LT-HSC_001  0.000000    0.0     0.0  2.364517  5.095857      0.0  2.364517   \n",
       "HSPC_001    0.000000    0.0     0.0  0.000000  5.953955      0.0  0.000000   \n",
       "\n",
       "            BC026585     Wfdc2     Camk1  Dgkq    Treml1      Ebi3  Gm27252  \\\n",
       "HSPC_025    2.275971  0.000000  9.124817   0.0  1.832751  6.581951      0.0   \n",
       "HSPC_031    6.807118  0.000000  8.318813   0.0  0.000000  1.150286      0.0   \n",
       "HSPC_037    1.218731  0.000000  1.869807   0.0  0.000000  6.912502      0.0   \n",
       "LT-HSC_001  4.694814  0.000000  3.217169   0.0  0.000000  8.466517      0.0   \n",
       "HSPC_001    0.000000  7.377903  0.923649   0.0  0.000000  7.458585      0.0   \n",
       "\n",
       "              Magee1  Sdc2      Ldhb  Kmo    Bpifb5   Trim30a     Ifitm1  \\\n",
       "HSPC_025    0.000000   0.0  8.464736  0.0  1.832751  8.744431  11.084242   \n",
       "HSPC_031    1.150286   0.0  0.686872  0.0  1.150286  7.925325  11.145000   \n",
       "HSPC_037    0.000000   0.0  2.316800  0.0  1.869807  3.363442   9.865499   \n",
       "LT-HSC_001  0.000000   0.0  8.207678  0.0  0.000000  4.442877  11.771131   \n",
       "HSPC_001    0.000000   0.0  8.116584  0.0  8.717852  9.644115  11.752090   \n",
       "\n",
       "               Ddx58     Ifitm3    Rmnd5b  Gm26772  Gm16151  Gm16150  \\\n",
       "HSPC_025    1.189716  10.748367  7.525084      0.0      0.0      0.0   \n",
       "HSPC_031    0.686872  10.561133  8.130743      0.0      0.0      0.0   \n",
       "HSPC_037    5.859945  10.011792  8.181786      0.0      0.0      0.0   \n",
       "LT-HSC_001  8.012835  10.802043  9.089116      0.0      0.0      0.0   \n",
       "HSPC_001    0.000000  10.211298  9.051950      0.0      0.0      0.0   \n",
       "\n",
       "               Tagln2  3110083C13Rik  Cyp39a1    Tspyl3   Dennd1c    Slc2a1  \\\n",
       "HSPC_025     9.263590            0.0      0.0  1.832751  8.832203  7.012433   \n",
       "HSPC_031     9.722719            0.0      0.0  2.946297  8.765435  0.000000   \n",
       "HSPC_037     9.476740            0.0      0.0  7.225650  7.186745  1.218731   \n",
       "LT-HSC_001  11.133169            0.0      0.0  2.364517  6.461820  3.217169   \n",
       "HSPC_001     9.945156            0.0      0.0  9.002350  9.150871  2.531943   \n",
       "\n",
       "              Large1  AB124611  Gm17096     Stxbp4     Muc3a     Awat2  \\\n",
       "HSPC_025    1.832751       0.0      0.0  10.351401  0.000000  0.000000   \n",
       "HSPC_031    0.000000       0.0      0.0   1.150286  7.267321  0.000000   \n",
       "HSPC_037    1.218731       0.0      0.0   0.000000  0.000000  1.869807   \n",
       "LT-HSC_001  0.000000       0.0      0.0   9.554808  2.364517  0.000000   \n",
       "HSPC_001    0.377367       0.0      0.0   0.377367  0.377367  0.000000   \n",
       "\n",
       "               Plac8  AI506816      Canx  Alox5     Prdx6      F11r      Alg2  \\\n",
       "HSPC_025    8.021134  2.275971  9.658353    0.0  9.000423  1.189716  0.000000   \n",
       "HSPC_031    9.810572  2.219938  9.793820    0.0  9.333015  4.700515  5.184588   \n",
       "HSPC_037    8.462568  3.538458  7.300448    0.0  9.935619  0.000000  1.869807   \n",
       "LT-HSC_001  4.442877  3.217169  5.543737    0.0  5.666688  6.591640  2.364517   \n",
       "HSPC_001    2.921687  7.820968  9.959956    0.0  9.118646  0.377367  8.493298   \n",
       "\n",
       "              Lurap1  Ttc30b    Inpp5k  Dcdc2b  Tnfsf4   Atp6ap1      Dapp1  \\\n",
       "HSPC_025    0.000000     0.0  3.118771     0.0     0.0  8.531189   8.753024   \n",
       "HSPC_031    0.000000     0.0  1.500480     0.0     0.0  1.782055   7.788776   \n",
       "HSPC_037    5.859945     0.0  3.538458     0.0     0.0  8.494778  10.042988   \n",
       "LT-HSC_001  0.000000     0.0  8.656534     0.0     0.0  3.217169   9.554808   \n",
       "HSPC_001    0.000000     0.0  0.923649     0.0     0.0  1.628905   2.197748   \n",
       "\n",
       "            1500002C15Rik    Tuba4a  Gm43254  ENSMUSG00000029333      Gclm  \\\n",
       "HSPC_025              0.0  7.421084      0.0                 0.0  3.118771   \n",
       "HSPC_031              0.0  3.342958      0.0                 0.0  3.253543   \n",
       "HSPC_037              0.0  4.475001      0.0                 0.0  3.363442   \n",
       "LT-HSC_001            0.0  8.532677      0.0                 0.0  2.364517   \n",
       "HSPC_001              0.0  9.216145      0.0                 0.0  3.519027   \n",
       "\n",
       "              Ruvbl2     Apobr  Nap1l3     Cct6a       Vav1      Rfc2  \\\n",
       "HSPC_025    8.367359  5.347433     0.0  9.160781   2.614548  8.327641   \n",
       "HSPC_031    6.807118  0.000000     0.0  7.537344   8.820957  8.288184   \n",
       "HSPC_037    8.355550  0.000000     0.0  3.538458   8.557117  4.978682   \n",
       "LT-HSC_001  6.710738  0.000000     0.0  2.364517   7.840709  3.217169   \n",
       "HSPC_001    1.134796  0.000000     0.0  6.167028  10.550200  7.941667   \n",
       "\n",
       "            Gm16001  Atp1b1  Gm19708     Nradd     Ypel3     Tor4a   Gm19590  \\\n",
       "HSPC_025        0.0     0.0      0.0  4.033241  6.693295  7.187470  9.514152   \n",
       "HSPC_031        0.0     0.0      0.0  0.000000  7.129612  0.686872  6.640763   \n",
       "HSPC_037        0.0     0.0      0.0  0.000000  8.121174  1.218731  8.587306   \n",
       "LT-HSC_001      0.0     0.0      0.0  0.000000  8.611324  5.409323  6.710738   \n",
       "HSPC_001        0.0     0.0      0.0  0.000000  5.537397  0.000000  0.676211   \n",
       "\n",
       "             Ivns1abp  Gm15991  Upp1  Gm6157  Eif5a2   C1qtnf6  4933424M12Rik  \\\n",
       "HSPC_025     8.213975      0.0   0.0     0.0     0.0  6.209872       0.000000   \n",
       "HSPC_031     6.472644      0.0   0.0     0.0     0.0  0.000000       0.000000   \n",
       "HSPC_037     9.111674      0.0   0.0     0.0     0.0  6.553350       0.000000   \n",
       "LT-HSC_001  10.509359      0.0   0.0     0.0     0.0  4.442877       3.217169   \n",
       "HSPC_001     8.250077      0.0   0.0     0.0     0.0  0.377367       0.000000   \n",
       "\n",
       "              Mageh1   Gm11696      Cbfb    Zfp422      Mfng      Klf8  \\\n",
       "HSPC_025    3.317239  0.000000  2.614548  7.122636  9.491221  1.189716   \n",
       "HSPC_031    0.000000  0.000000  3.582099  2.017546  8.043406  0.000000   \n",
       "HSPC_037    0.000000  6.813823  7.914462  8.175175  7.930251  0.000000   \n",
       "LT-HSC_001  0.000000  0.000000  5.261087  0.000000  8.714692  0.000000   \n",
       "HSPC_001    0.000000  0.000000  1.482235  0.377367  9.303379  0.000000   \n",
       "\n",
       "              Stk17b  Met  Ufsp1  Tmem150a  AI606181     Ikzf2    Slc34a2  \\\n",
       "HSPC_025    1.189716  0.0    0.0       0.0  0.000000  8.169733  11.876887   \n",
       "HSPC_031    0.000000  0.0    0.0       0.0  1.150286  7.261599  11.510276   \n",
       "HSPC_037    1.869807  0.0    0.0       0.0  0.000000  8.812716  12.473957   \n",
       "LT-HSC_001  0.000000  0.0    0.0       0.0  0.000000  8.342895  12.910433   \n",
       "HSPC_001    0.377367  0.0    0.0       0.0  0.000000  4.604046  10.497768   \n",
       "\n",
       "            1700066B19Rik      Mcm7  Fbxo48     Ecscr   Lyplal1   Ankrd37  \\\n",
       "HSPC_025         0.000000  8.316089     0.0  0.000000  0.000000  0.000000   \n",
       "HSPC_031         0.686872  2.555402     0.0  0.000000  0.000000  0.000000   \n",
       "HSPC_037         0.000000  5.757471     0.0  0.000000  1.218731  0.000000   \n",
       "LT-HSC_001       0.000000  4.442877     0.0  7.107933  0.000000  2.364517   \n",
       "HSPC_001         0.000000  2.531943     0.0  0.000000  0.000000  0.000000   \n",
       "\n",
       "                Plek  Mapkbp1   Ppp1r3d   Exoc3l2    Tmem53      Wsb1  \\\n",
       "HSPC_025    2.888576      0.0  0.000000  1.189716  6.184685  1.189716   \n",
       "HSPC_031    0.686872      0.0  0.000000  7.655500  0.000000  4.075063   \n",
       "HSPC_037    9.293568      0.0  0.000000  5.351295  0.000000  6.796699   \n",
       "LT-HSC_001  2.364517      0.0  2.364517  0.000000  0.000000  2.364517   \n",
       "HSPC_001    0.000000      0.0  0.000000  0.000000  0.000000  5.867946   \n",
       "\n",
       "                Rtkn      Tfr2    Leprot  Arhgap25  Nupr1     Plpp7  \\\n",
       "HSPC_025    5.558232  2.614548  7.082290  8.083785    0.0  0.000000   \n",
       "HSPC_031    0.000000  9.710171  1.782055  7.877493    0.0  0.000000   \n",
       "HSPC_037    0.000000  2.933024  8.451670  1.869807    0.0  1.218731   \n",
       "LT-HSC_001  0.000000  0.000000  3.217169  8.811145    0.0  0.000000   \n",
       "HSPC_001    0.000000  0.923649  1.762030  4.099659    0.0  0.000000   \n",
       "\n",
       "            G730003C15Rik      Rsrp1     Samsn1     Prdx3   Gm37663     Itgb3  \\\n",
       "HSPC_025              0.0   8.989556   9.202161  3.317239  0.000000  0.000000   \n",
       "HSPC_031              0.0   9.001726   9.143804  6.009394  0.000000  1.150286   \n",
       "HSPC_037              0.0  11.369171  10.099937  7.186745  1.218731  0.000000   \n",
       "LT-HSC_001            0.0  10.120428   6.710738  7.732268  0.000000  0.000000   \n",
       "HSPC_001              0.0  10.043252   1.134796  1.762030  0.000000  0.000000   \n",
       "\n",
       "            Rtn4r      Nrros   Dennd2d        Por  Tspear  Hsd17b12    Capza2  \\\n",
       "HSPC_025      0.0   8.832203  1.189716   8.459496     0.0  7.695253  9.989955   \n",
       "HSPC_031      0.0  10.457334  0.686872   8.482714     0.0  7.220899  5.850759   \n",
       "HSPC_037      0.0   8.283626  0.000000   9.237565     0.0  2.316800  4.081427   \n",
       "LT-HSC_001    0.0   4.694814  0.000000  10.788568     0.0  8.742914  6.971475   \n",
       "HSPC_001      0.0   0.377367  0.000000   7.636025     0.0  1.134796  9.846475   \n",
       "\n",
       "            Osgin1     Spns3       Cd34  4921531C22Rik    Trmt2a   Gm26692  \\\n",
       "HSPC_025       0.0  0.000000  10.686910       0.000000  2.275971  1.189716   \n",
       "HSPC_031       0.0  0.000000   9.467087       7.350532  1.782055  0.000000   \n",
       "HSPC_037       0.0  0.000000  10.726889       7.336441  7.728326  0.000000   \n",
       "LT-HSC_001     0.0  2.364517   4.909226       0.000000  9.768942  0.000000   \n",
       "HSPC_001       0.0  0.676211   9.338449       0.000000  0.377367  0.377367   \n",
       "\n",
       "             Col16a1  Cd46  Ptgds    Uqcrc1  Gm28512     Hacd4  Ttc39c  \\\n",
       "HSPC_025    0.000000   0.0    0.0  7.068586      0.0  7.739166     0.0   \n",
       "HSPC_031    3.158217   0.0    0.0  8.994845      0.0  8.934992     0.0   \n",
       "HSPC_037    0.000000   0.0    0.0  3.835337      0.0  6.880354     0.0   \n",
       "LT-HSC_001  0.000000   0.0    0.0  6.820749      0.0  0.000000     0.0   \n",
       "HSPC_001    0.000000   0.0    0.0  9.600889      0.0  8.113473     0.0   \n",
       "\n",
       "            Igkv1-135   Fam129c      Rhof      Sdcbp     Rcsd1     Mmrn1  \\\n",
       "HSPC_025          0.0  1.189716  0.000000   9.892208  7.970453  1.189716   \n",
       "HSPC_031          0.0  0.000000  0.686872   6.511734  2.219938  0.686872   \n",
       "HSPC_037          0.0  0.000000  0.000000   7.781518  3.164226  1.218731   \n",
       "LT-HSC_001        0.0  0.000000  6.319152   9.340672  8.626553  4.137438   \n",
       "HSPC_001          0.0  0.000000  0.377367  10.449541  2.673882  9.999258   \n",
       "\n",
       "            Ccser1  Ccdc92b  Tnfaip8l1     Tprgl       Gem  D630039A03Rik  \\\n",
       "HSPC_025       0.0      0.0        0.0  7.484379  9.141275            0.0   \n",
       "HSPC_031       0.0      0.0        0.0  0.686872  0.686872            0.0   \n",
       "HSPC_037       0.0      0.0        0.0  4.475001  8.473385            0.0   \n",
       "LT-HSC_001     0.0      0.0        0.0  8.124310  8.247621            0.0   \n",
       "HSPC_001       0.0      0.0        0.0  0.676211  0.000000            0.0   \n",
       "\n",
       "            Lrrc36  Map10   Gm38071     Ccng2       Ldha     Ramp1       Ucp2  \\\n",
       "HSPC_025       0.0    0.0  0.000000  2.275971   8.511066  8.244766  10.309781   \n",
       "HSPC_031       0.0    0.0  0.000000  0.000000  10.249019  9.670777   9.728952   \n",
       "HSPC_037       0.0    0.0  2.933024  7.737329   8.289759  9.379458   9.663070   \n",
       "LT-HSC_001     0.0    0.0  0.000000  0.000000  10.002816  8.926375   5.982925   \n",
       "HSPC_001       0.0    0.0  0.377367  0.000000  10.079579  9.070521  10.222171   \n",
       "\n",
       "                Sdsl      Ttc4   Afap1l1      Ccnd2  Sult1a1    Ube2l6  \\\n",
       "HSPC_025    0.000000  7.068586  5.518464   7.332125      0.0  8.832203   \n",
       "HSPC_031    2.555402  1.500480  9.080214   6.807118      0.0  8.846027   \n",
       "HSPC_037    1.869807  8.424058  7.719267   8.981337      0.0  9.076634   \n",
       "LT-HSC_001  0.000000  3.749470  3.749470   9.669524      0.0  5.982925   \n",
       "HSPC_001    8.300199  0.676211  8.450785  10.698247      0.0  7.622956   \n",
       "\n",
       "             Clec12a   Gm43643  Smtnl1      Aqp1  Large2     Creg1  Fam221a  \\\n",
       "HSPC_025    1.189716  5.965594     0.0  3.118771     0.0  8.384051      0.0   \n",
       "HSPC_031    0.000000  0.000000     0.0  2.397399     0.0  5.278242      0.0   \n",
       "HSPC_037    1.218731  6.333516     0.0  2.657566     0.0  3.694520      0.0   \n",
       "LT-HSC_001  0.000000  0.000000     0.0  0.000000     0.0  8.397178      0.0   \n",
       "HSPC_001    0.923649  0.000000     0.0  0.676211     0.0  8.228669      0.0   \n",
       "\n",
       "               Muc13  Slc25a11  Grap      Ncf1   B4galt4   Gm16758     Nucb1  \\\n",
       "HSPC_025    2.275971  8.238660   0.0  4.588530  1.189716  0.000000  8.411450   \n",
       "HSPC_031    2.397399  7.429204   0.0  7.740229  0.686872  0.000000  2.219938   \n",
       "HSPC_037    4.190334  9.094260   0.0  8.141662  0.000000  0.000000  8.155161   \n",
       "LT-HSC_001  4.137438  7.383635   0.0  0.000000  5.409323  0.000000  9.293747   \n",
       "HSPC_001    8.283684  9.610853   0.0  0.000000  0.000000  2.604657  9.476233   \n",
       "\n",
       "              Fam69b   Tmem35b       Mx1   Ppp1r26       Mx2   Ppp1r15a  \\\n",
       "HSPC_025    6.877476  7.421084  1.832751  6.258964  0.000000   5.842161   \n",
       "HSPC_031    9.839666  8.596177  0.000000  0.000000  0.000000   0.000000   \n",
       "HSPC_037    8.114280  7.790196  4.712649  0.000000  0.000000   1.218731   \n",
       "LT-HSC_001  8.626553  6.160812  0.000000  0.000000  4.694814  10.805393   \n",
       "HSPC_001    6.599451  0.923649  0.000000  0.000000  0.000000   0.000000   \n",
       "\n",
       "            Pdzk1ip1     Coro1a     Mob3c      Oas2   Kctd12b  Mefv   Gm12250  \\\n",
       "HSPC_025    0.000000  11.228325  1.189716  5.253659  1.189716   0.0  6.923879   \n",
       "HSPC_031    0.000000   9.762764  1.150286  0.686872  0.000000   0.0  0.686872   \n",
       "HSPC_037    1.218731   9.991242  1.869807  2.933024  8.378749   0.0  9.149260   \n",
       "LT-HSC_001  6.528191   8.247621  9.205236  0.000000  3.217169   0.0  8.756821   \n",
       "HSPC_001    8.156434   9.612506  0.377367  0.000000  0.000000   0.0  7.873411   \n",
       "\n",
       "               Sh2d5      Igtp     Ermap      Smu1   Maged2      Mcm4  \\\n",
       "HSPC_025    0.000000  1.832751  1.832751  3.118771  0.00000  9.157549   \n",
       "HSPC_031    0.000000  0.000000  1.782055  9.107582  0.00000  2.697797   \n",
       "HSPC_037    6.129815  1.218731  3.363442  8.181786  0.00000  5.150271   \n",
       "LT-HSC_001  0.000000  9.143059  2.364517  7.347332  0.00000  6.319152   \n",
       "HSPC_001    0.000000  0.000000  1.628905  6.414630  5.52808  8.885003   \n",
       "\n",
       "             Gm42576      Anxa6  1700123M08Rik      Rtp4   Sh3bgrl     Napsa  \\\n",
       "HSPC_025    0.000000   0.000000            0.0  8.433001  7.442493  7.261610   \n",
       "HSPC_031    0.686872  10.531721            0.0  1.782055  1.150286  5.255393   \n",
       "HSPC_037    0.000000   1.869807            0.0  8.577312  8.331971  7.439328   \n",
       "LT-HSC_001  0.000000   5.409323            0.0  9.768942  3.217169  3.217169   \n",
       "HSPC_001    0.676211   0.676211            0.0  7.242044  1.318950  2.921687   \n",
       "\n",
       "              Kctd21      Chpf    Gm7160   Neurl1b       Cct3    Nkx2-3  \\\n",
       "HSPC_025    0.000000  7.704143  0.000000  0.000000   9.588054  1.189716   \n",
       "HSPC_031    0.686872  0.686872  0.000000  0.000000   3.506705  4.919811   \n",
       "HSPC_037    0.000000  0.000000  7.394504  0.000000   9.379458  8.510617   \n",
       "LT-HSC_001  7.645229  2.364517  2.364517  0.000000   7.383635  6.319152   \n",
       "HSPC_001    0.000000  0.377367  0.000000  0.377367  10.542702  8.477653   \n",
       "\n",
       "               Wdr78      Dusp1      Def8       Rbm5  BC016579       Emb  \\\n",
       "HSPC_025    0.000000  11.117064  2.275971   9.563837       0.0  8.967574   \n",
       "HSPC_031    0.000000   0.686872  5.565109   9.814485       0.0  9.297106   \n",
       "HSPC_037    1.218731   2.933024  2.316800  10.080613       0.0  9.895967   \n",
       "LT-HSC_001  2.364517   6.392249  3.217169   7.150694       0.0  8.671295   \n",
       "HSPC_001    0.000000   0.923649  8.533429   2.288830       0.0  9.603663   \n",
       "\n",
       "              Elovl1     Myo1f      Lax1    Cyp2j6   Pstpip1  Emp1      Cd44  \\\n",
       "HSPC_025    6.893110  8.575464  1.832751  1.189716  8.673779   0.0  9.114851   \n",
       "HSPC_031    5.689649  8.781518  0.000000  9.254531  7.154525   0.0  2.555402   \n",
       "HSPC_037    3.694520  1.218731  7.091666  0.000000  8.692885   0.0  6.490843   \n",
       "LT-HSC_001  6.766791  5.885018  0.000000  2.364517  7.107933   0.0  8.685906   \n",
       "HSPC_001    9.580752  0.000000  0.000000  5.370192  5.712118   0.0  1.482235   \n",
       "\n",
       "               Mtch2      Pgm2  Krt7  Mir155hg  1110028F11Rik     Acot7  Rnd2  \\\n",
       "HSPC_025    3.118771  0.000000   0.0       0.0       0.000000  8.316089   0.0   \n",
       "HSPC_031    7.873747  1.150286   0.0       0.0       1.150286  8.878166   0.0   \n",
       "HSPC_037    8.277468  0.000000   0.0       0.0       0.000000  8.706702   0.0   \n",
       "LT-HSC_001  8.012835  2.364517   0.0       0.0       0.000000  4.137438   0.0   \n",
       "HSPC_001    1.628905  0.000000   0.0       0.0       0.676211  1.134796   0.0   \n",
       "\n",
       "                 Irf1    H2-DMa    Zfp263  Rxra     Klhl6  A130014A01Rik  \\\n",
       "HSPC_025    10.128487  6.968835  7.174734   0.0  8.056275       1.189716   \n",
       "HSPC_031     1.150286  9.615775  1.500480   0.0  1.782055       0.000000   \n",
       "HSPC_037     1.218731  8.833854  3.538458   0.0  8.923351       0.000000   \n",
       "LT-HSC_001   2.364517  3.217169  7.453613   0.0  8.671295       0.000000   \n",
       "HSPC_001     0.923649  7.362259  9.059246   0.0  0.377367       0.000000   \n",
       "\n",
       "               Ssbp2      Rbp1    Rsl1d1  Gjb3     Asah1    Tmem37     Spcs3  \\\n",
       "HSPC_025    7.442493  1.189716  8.848332   0.0  9.296293  0.000000  7.747791   \n",
       "HSPC_031    8.959939  6.853501  9.008575   0.0  4.358484  0.686872  1.782055   \n",
       "HSPC_037    8.271282  1.218731  8.747376   0.0  1.218731  7.324543  2.657566   \n",
       "LT-HSC_001  7.760152  6.160812  3.217169   0.0  8.499976  0.000000  7.520354   \n",
       "HSPC_001    8.791733  5.661887  8.810106   0.0  0.000000  0.000000  1.482235   \n",
       "\n",
       "               Cenpa  Gfpt2   Tmprss3     Pqlc3     Dhrs3      Jak3   Fam213b  \\\n",
       "HSPC_025    2.275971    0.0  1.189716  0.000000  1.832751  7.730490  0.000000   \n",
       "HSPC_031    2.827391    0.0  0.000000  6.623022  0.000000  0.000000  0.000000   \n",
       "HSPC_037    3.363442    0.0  1.869807  0.000000  1.218731  1.869807  1.218731   \n",
       "LT-HSC_001  0.000000    0.0  0.000000  3.749470  7.814354  8.499976  0.000000   \n",
       "HSPC_001    0.377367    0.0  0.000000  0.000000  0.676211  0.676211  0.000000   \n",
       "\n",
       "              Pafah2       Jun     Lamp1   Camsap3     Grtp1   Gm16794  \\\n",
       "HSPC_025    7.999631  7.535083  9.438924  0.000000  1.189716  0.000000   \n",
       "HSPC_031    1.150286  5.672502  2.017546  0.000000  0.686872  0.000000   \n",
       "HSPC_037    1.869807  2.933024  8.825436  0.000000  0.000000  0.000000   \n",
       "LT-HSC_001  6.766791  9.205236  8.102695  2.364517  0.000000  0.000000   \n",
       "HSPC_001    8.979461  7.441317  0.923649  0.000000  0.000000  0.377367   \n",
       "\n",
       "              Cacybp     Slfn8      Stom   H2-DMb1      H2-D1  Oas1c  Tas1r1  \\\n",
       "HSPC_025    7.212608  9.084533  1.189716  0.000000  11.455247    0.0     0.0   \n",
       "HSPC_031    6.248005  4.595264  1.782055  6.876145  10.860805    0.0     0.0   \n",
       "HSPC_037    8.724920  0.000000  2.316800  1.869807  11.461703    0.0     0.0   \n",
       "LT-HSC_001  5.261087  9.089116  0.000000  3.217169  12.063208    0.0     0.0   \n",
       "HSPC_001    8.317878  0.676211  1.318950  8.222906  12.126537    0.0     0.0   \n",
       "\n",
       "               Rab44  4930579K19Rik       Fos     Nedd4    Cyb561  Mapkapk3  \\\n",
       "HSPC_025    1.189716       0.000000  0.000000  6.418716  0.000000  0.000000   \n",
       "HSPC_031    1.150286       1.150286  0.686872  8.236617  0.000000  8.697130   \n",
       "HSPC_037    0.000000       0.000000  2.316800  6.403053  0.000000  1.869807   \n",
       "LT-HSC_001  0.000000       0.000000  8.938628  9.421470  0.000000  3.217169   \n",
       "HSPC_001    0.000000       0.000000  0.676211  0.676211  0.377367  0.676211   \n",
       "\n",
       "              Inpp4b    Ccdc69     Slfn2  Tmem220  2610035D17Rik    Snap23  \\\n",
       "HSPC_025    0.000000  8.748734  1.189716      0.0       1.189716  6.159051   \n",
       "HSPC_031    0.000000  0.686872  0.000000      0.0       8.470365  0.686872   \n",
       "HSPC_037    6.016053  1.218731  0.000000      0.0       1.218731  7.586077   \n",
       "LT-HSC_001  0.000000  5.666688  9.918720      0.0       7.552600  3.217169   \n",
       "HSPC_001    0.000000  0.377367  0.000000      0.0       8.644301  8.425918   \n",
       "\n",
       "               Nprl2    Rasal3  Ighv1-82      Batf  Tmem121      Rrm2  \\\n",
       "HSPC_025    7.494663  8.718340  1.189716  7.649962      0.0  2.614548   \n",
       "HSPC_031    9.470811  6.152300  0.000000  0.000000      0.0  2.697797   \n",
       "HSPC_037    8.036182  9.734499  0.000000  0.000000      0.0  1.218731   \n",
       "LT-HSC_001  3.749470  7.674830  0.000000  2.364517      0.0  4.442877   \n",
       "HSPC_001    0.377367  0.000000  0.000000  0.000000      0.0  2.739936   \n",
       "\n",
       "               Surf4    Zfp386  Mamdc4  B230217C12Rik  Zbtb42     Sstr2  Pld2  \\\n",
       "HSPC_025    1.832751  6.306441     0.0            0.0     0.0  0.000000   0.0   \n",
       "HSPC_031    5.058266  8.477787     0.0            0.0     0.0  8.164863   0.0   \n",
       "HSPC_037    4.783895  1.869807     0.0            0.0     0.0  0.000000   0.0   \n",
       "LT-HSC_001  4.442877  8.499976     0.0            0.0     0.0  0.000000   0.0   \n",
       "HSPC_001    8.959672  0.377367     0.0            0.0     0.0  0.000000   0.0   \n",
       "\n",
       "               Cers5      Ighd       Ighm    Cyp4v3      Limd2    Nlrp1a  \\\n",
       "HSPC_025    7.135838  0.000000   5.253659  4.337438   8.395074  0.000000   \n",
       "HSPC_031    1.150286  0.000000   7.513468  0.000000   5.739898  5.655149   \n",
       "HSPC_037    7.405841  0.000000   9.115131  0.000000   8.911469  0.000000   \n",
       "LT-HSC_001  2.364517  0.000000  12.165795  0.000000   9.215343  0.000000   \n",
       "HSPC_001    0.000000  0.377367   1.883902  0.000000  10.312110  0.000000   \n",
       "\n",
       "                H2-Q6      P4hb       Grn     H2-Q7  Gm10863      Hhex  \\\n",
       "HSPC_025     8.350471  9.714428  8.526184  7.649962      0.0  8.718340   \n",
       "HSPC_031     9.317932  6.701193  0.000000  8.401790      0.0  1.150286   \n",
       "HSPC_037     7.874218  8.911469  2.657566  7.348242      0.0  6.045346   \n",
       "LT-HSC_001  10.471911  5.982925  0.000000  9.322084      0.0  7.674830   \n",
       "HSPC_001     4.124600  8.799498  1.134796  3.360089      0.0  7.558065   \n",
       "\n",
       "               Pcbp4      Tubb5     Itgb7      Gpam      Cbx5   Fam184a  \\\n",
       "HSPC_025    0.000000  10.165970  8.137279  0.000000  7.309000  1.189716   \n",
       "HSPC_031    0.686872   8.460409  0.686872  0.000000  2.946297  0.000000   \n",
       "HSPC_037    1.869807  10.078843  1.218731  1.218731  2.933024  0.000000   \n",
       "LT-HSC_001  0.000000  10.389508  2.364517  0.000000  9.601794  0.000000   \n",
       "HSPC_001    2.374501  10.136633  1.482235  0.000000  7.551182  0.000000   \n",
       "\n",
       "            Tmem106a  Adamtsl5     Cd79b       Nfe2     H2-Ob   Tcp11l2  \\\n",
       "HSPC_025    0.000000       0.0  1.832751   8.641746  7.992392  0.000000   \n",
       "HSPC_031    0.686872       0.0  0.686872   9.285875  1.782055  5.208578   \n",
       "HSPC_037    1.218731       0.0  0.000000   9.000159  7.417090  9.073083   \n",
       "LT-HSC_001  0.000000       0.0  4.442877  10.104202  0.000000  8.361217   \n",
       "HSPC_001    7.451210       0.0  0.676211  10.394527  8.633481  0.377367   \n",
       "\n",
       "              Shisa5    Samd10  Hspa12b     Tcea2      Ctsd     Rgs19  \\\n",
       "HSPC_025    9.331144  7.431828      0.0  1.189716  9.334011  9.403884   \n",
       "HSPC_031    9.719592  0.000000      0.0  9.479464  6.359344  8.380830   \n",
       "HSPC_037    7.383077  1.218731      0.0  2.316800  4.190334  9.083711   \n",
       "LT-HSC_001  9.164084  0.000000      0.0  7.866592  8.700371  8.548753   \n",
       "HSPC_001    9.589737  0.000000      0.0  0.000000  7.974620  9.727375   \n",
       "\n",
       "               Procr     Tnni2     Acap1       Bin2  Ropn1l    Lmbrd2  \\\n",
       "HSPC_025    0.000000  1.189716  9.007623   9.390178     0.0  0.000000   \n",
       "HSPC_031    0.686872  0.000000  9.978684   9.464599     0.0  0.686872   \n",
       "HSPC_037    2.657566  1.218731  3.164226  10.033882     0.0  0.000000   \n",
       "LT-HSC_001  9.143059  0.000000  0.000000   7.965715     0.0  0.000000   \n",
       "HSPC_001    9.550012  0.000000  9.245576   9.297222     0.0  0.000000   \n",
       "\n",
       "             Laptm4b  Il7r     Capsl     Angpt1     Spag1    H2-Ab1     Gfi1b  \\\n",
       "HSPC_025    8.028232   0.0  0.000000   7.721761  0.000000  0.000000  1.189716   \n",
       "HSPC_031    0.686872   0.0  0.000000   2.397399  0.000000  1.150286  2.017546   \n",
       "HSPC_037    2.657566   0.0  0.000000   8.418471  0.000000  1.869807  1.869807   \n",
       "LT-HSC_001  9.033078   0.0  0.000000  10.577548  0.000000  8.564652  2.364517   \n",
       "HSPC_001    8.703439   0.0  0.377367   8.125878  0.377367  0.000000  1.318950   \n",
       "\n",
       "                H2-Aa      Ctsw     Hspa5   Tbc1d10c      Rom1  Smpd2  \\\n",
       "HSPC_025     1.189716  6.581951  8.475161   7.054751  0.000000    0.0   \n",
       "HSPC_031     0.000000  7.574740  9.898919   0.686872  0.000000    0.0   \n",
       "HSPC_037     7.832819  1.218731  9.101251  10.376936  0.000000    0.0   \n",
       "LT-HSC_001  10.987443  0.000000  9.464477   8.824412  0.000000    0.0   \n",
       "HSPC_001     0.676211  0.676211  6.237319   6.833019  0.377367    0.0   \n",
       "\n",
       "                Ctsf      Fgd2      Cct8    Mamdc2     Stip1  Gm28043  \\\n",
       "HSPC_025    0.000000  6.939021  9.742748  6.829531  7.992392      0.0   \n",
       "HSPC_031    0.686872  0.686872  9.306862  0.000000  1.782055      0.0   \n",
       "HSPC_037    8.966101  5.924429  8.489459  0.000000  3.694520      0.0   \n",
       "LT-HSC_001  0.000000  0.000000  9.802852  0.000000  4.137438      0.0   \n",
       "HSPC_001    7.043829  0.000000  8.814903  0.000000  8.390367      0.0   \n",
       "\n",
       "                 Cd27  Rdh5  Aldoc    Prss57    Arpc1b      Fut7      Cd86  \\\n",
       "HSPC_025     8.130700   0.0    0.0  1.189716  9.214658  7.887028  0.000000   \n",
       "HSPC_031    10.211670   0.0    0.0  0.000000  9.347942  2.017546  0.000000   \n",
       "HSPC_037    10.911210   0.0    0.0  1.218731  9.804700  7.439328  1.218731   \n",
       "LT-HSC_001   9.943251   0.0    0.0  0.000000  9.937158  2.364517  0.000000   \n",
       "HSPC_001     8.732122   0.0    0.0  8.673117  9.525641  0.923649  0.000000   \n",
       "\n",
       "             Serpinf1       Cd9   Gm37274  Wdr38   Angptl6  Smad6  Chad  \\\n",
       "HSPC_025     7.399354  2.275971  1.189716    0.0  6.763021    0.0   0.0   \n",
       "HSPC_031     1.782055  7.985573  0.000000    0.0  0.000000    0.0   0.0   \n",
       "HSPC_037     2.657566  1.218731  0.000000    0.0  1.218731    0.0   0.0   \n",
       "LT-HSC_001   8.324337  2.364517  0.000000    0.0  0.000000    0.0   0.0   \n",
       "HSPC_001    10.337334  3.853357  0.000000    0.0  0.676211    0.0   0.0   \n",
       "\n",
       "              Arhgdib      Eogt  Llgl2      Cst7  E130215H24Rik  Gm27201  \\\n",
       "HSPC_025    10.830842  0.000000    0.0  1.832751            0.0      0.0   \n",
       "HSPC_031     8.713988  0.000000    0.0  0.686872            0.0      0.0   \n",
       "HSPC_037    11.608145  0.000000    0.0  0.000000            0.0      0.0   \n",
       "LT-HSC_001  10.420417  0.000000    0.0  2.364517            0.0      0.0   \n",
       "HSPC_001    11.414046  0.377367    0.0  0.923649            0.0      0.0   \n",
       "\n",
       "                Pcna    Rnf114  Gchfr    Cacfd1      Jam3    Fkbp1a      Eps8  \\\n",
       "HSPC_025    8.608986  8.316089    0.0  1.189716  0.000000  9.173640  5.809578   \n",
       "HSPC_031    3.582099  2.219938    0.0  0.686872  0.000000  8.504679  0.000000   \n",
       "HSPC_037    6.309572  2.657566    0.0  0.000000  0.000000  4.081427  0.000000   \n",
       "LT-HSC_001  8.080749  2.364517    0.0  0.000000  8.145608  6.319152  0.000000   \n",
       "HSPC_001    1.628905  0.676211    0.0  0.000000  0.000000  8.230106  0.000000   \n",
       "\n",
       "            Epb41l1     Traf1     Pdia3     Mgst1  Slc2a6  Spint1       Lmo2  \\\n",
       "HSPC_025        0.0  0.000000  9.414757  7.612677     0.0     0.0  10.214998   \n",
       "HSPC_031        0.0  0.000000  7.961069  7.943307     0.0     0.0  11.641084   \n",
       "HSPC_037        0.0  0.000000  8.816968  6.309572     0.0     0.0  10.319646   \n",
       "LT-HSC_001      0.0  8.811145  9.132430  0.000000     0.0     0.0  10.173233   \n",
       "HSPC_001        0.0  0.000000  9.630032  0.000000     0.0     0.0  10.754757   \n",
       "\n",
       "                 Eng     Skap2     Vamp5  Plxna1  Klrb1f   Tmem176b      Mcm2  \\\n",
       "HSPC_025    6.374848  7.545014  6.051698     0.0     0.0   9.921090  8.860312   \n",
       "HSPC_031    6.783355  8.111786  8.133878     0.0     0.0   9.748516  1.150286   \n",
       "HSPC_037    5.485582  7.019698  8.155161     0.0     0.0   9.396608  2.657566   \n",
       "LT-HSC_001  9.676858  7.989468  8.267186     0.0     0.0  10.812068  2.364517   \n",
       "HSPC_001    8.291965  7.555774  9.070521     0.0     0.0   9.177187  1.762030   \n",
       "\n",
       "             Slc52a3      Cct7     Ptgs1      Cnn2     Prim1  Rwdd2a  \\\n",
       "HSPC_025    0.000000  8.815891  9.269591  7.739166  7.545014     0.0   \n",
       "HSPC_031    0.000000  3.787179  0.000000  8.809238  1.782055     0.0   \n",
       "HSPC_037    0.000000  9.122022  0.000000  1.218731  2.933024     0.0   \n",
       "LT-HSC_001  2.364517  9.264843  7.552600  8.580378  2.364517     0.0   \n",
       "HSPC_001    0.000000  8.746254  0.377367  7.629506  1.134796     0.0   \n",
       "\n",
       "                Matk      Atp5b       Cdk4  Robo4   Gm15915   Gm10101  \\\n",
       "HSPC_025    0.000000   9.953140  10.011602    0.0  2.275971  0.000000   \n",
       "HSPC_031    7.454503  10.444765   8.362235    0.0  2.017546  0.000000   \n",
       "HSPC_037    0.000000  10.647927   8.931218    0.0  2.657566  0.000000   \n",
       "LT-HSC_001  8.166596  10.933363   7.732268    0.0  0.000000  0.000000   \n",
       "HSPC_001    0.000000  10.477341  10.039568    0.0  1.318950  0.377367   \n",
       "\n",
       "               Abhd4     Rab36    Metap2      Fzr1     Pa2g4    Smim24  \\\n",
       "HSPC_025    8.110780  0.000000  8.883978  7.273603  9.449536  0.000000   \n",
       "HSPC_031    0.686872  0.000000  5.508257  0.686872  7.615685  0.686872   \n",
       "HSPC_037    9.287452  0.000000  7.866032  3.363442  8.384491  8.114280   \n",
       "LT-HSC_001  2.364517  0.000000  8.166596  8.770595  2.364517  0.000000   \n",
       "HSPC_001    6.563421  0.377367  9.440054  1.134796  1.134796  7.707927   \n",
       "\n",
       "             Gm16104  Perp      Fig4     Myct1      Lsp1  Alpk3  Zfp28  Zfp78  \\\n",
       "HSPC_025    0.000000   0.0  6.282898  1.189716  9.245434    0.0    0.0    0.0   \n",
       "HSPC_031    0.000000   0.0  0.000000  0.000000  7.439376    0.0    0.0    0.0   \n",
       "HSPC_037    0.000000   0.0  8.320036  8.148427  7.615671    0.0    0.0    0.0   \n",
       "LT-HSC_001  2.364517   0.0  0.000000  9.121723  9.481327    0.0    0.0    0.0   \n",
       "HSPC_001    0.000000   0.0  0.377367  5.359726  9.581316    0.0    0.0    0.0   \n",
       "\n",
       "            Zfp773  Mill2      Gpr4  Nectin2    Tyrobp  Plekhf1      Nkg7  \\\n",
       "HSPC_025       0.0    0.0  0.000000      0.0  1.189716      0.0  2.614548   \n",
       "HSPC_031       0.0    0.0  2.827391      0.0  3.158217      0.0  2.219938   \n",
       "HSPC_037       0.0    0.0  0.000000      0.0  7.336441      0.0  8.407233   \n",
       "LT-HSC_001     0.0    0.0  0.000000      0.0  0.000000      0.0  3.749470   \n",
       "HSPC_001       0.0    0.0  0.000000      0.0  0.377367      0.0  1.134796   \n",
       "\n",
       "             Osbpl1a  Slc27a6    Gm4951    Zfp438     Rab18  \n",
       "HSPC_025    0.000000      0.0  0.000000  1.189716  9.263590  \n",
       "HSPC_031    2.017546      0.0  0.000000  0.000000  0.686872  \n",
       "HSPC_037    1.218731      0.0  0.000000  1.218731  8.641061  \n",
       "LT-HSC_001  6.820749      0.0  7.107933  2.364517  6.242153  \n",
       "HSPC_001    1.134796      0.0  1.883902  0.000000  1.318950  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ref_data = pd.read_csv(\"data_filtered_vargenes/GSE81682_Hematopoiesis.csv\", index_col=0)\n",
    "ref_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "453fdbe5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1min 31s, sys: 1.46 s, total: 1min 32s\n",
      "Wall time: 15.9 s\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>scBoolSeqBinarizer()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;scBoolSeqBinarizer<span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>scBoolSeqBinarizer()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "scBoolSeqBinarizer()"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time scbool = scBoolSeq().fit(ref_data)\n",
    "scbool"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ac21fef",
   "metadata": {},
   "source": [
    "## Generate synthetic RNA-Seq data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d48ebcc9",
   "metadata": {},
   "outputs": [],
   "source": [
    "SEED = 1928327465\n",
    "n_samples = 300\n",
    "counts = synth_pseudocounts = scbool.sample_counts(random_walk_df, n_samples_per_state=n_samples, random_state=SEED)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65715e51-94ee-4a47-9dfe-bafd15000a3e",
   "metadata": {},
   "source": [
    "counts = scbool.sample_counts(random_walk_df, n_samples_per_state=n_samples)\n",
    "counts.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a95920eb",
   "metadata": {},
   "source": [
    "To ease post-analysis with STREAM, we generate unique identifiers for each simulated row (cell):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9ace2312",
   "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>tf</th>\n",
       "      <th>gene1</th>\n",
       "      <th>gene2</th>\n",
       "      <th>gene3</th>\n",
       "      <th>gene4</th>\n",
       "      <th>gene5</th>\n",
       "      <th>gene6</th>\n",
       "      <th>gene7</th>\n",
       "      <th>gene8</th>\n",
       "      <th>gene9</th>\n",
       "      <th>gene10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cellID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>step0_0</th>\n",
       "      <td>11.199946</td>\n",
       "      <td>5.790686</td>\n",
       "      <td>3.239893</td>\n",
       "      <td>1.508778</td>\n",
       "      <td>2.019838</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.859050</td>\n",
       "      <td>2.690069</td>\n",
       "      <td>15.004079</td>\n",
       "      <td>1.684236</td>\n",
       "      <td>0.868850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step1_0</th>\n",
       "      <td>10.728647</td>\n",
       "      <td>8.038792</td>\n",
       "      <td>3.366851</td>\n",
       "      <td>3.182303</td>\n",
       "      <td>0.990765</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.585934</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>15.404062</td>\n",
       "      <td>1.227158</td>\n",
       "      <td>4.214468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step2_0</th>\n",
       "      <td>9.614120</td>\n",
       "      <td>11.935944</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.352651</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.361628</td>\n",
       "      <td>3.206353</td>\n",
       "      <td>15.721765</td>\n",
       "      <td>0.482383</td>\n",
       "      <td>4.521560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step3_0</th>\n",
       "      <td>9.590053</td>\n",
       "      <td>12.294490</td>\n",
       "      <td>1.882482</td>\n",
       "      <td>10.208256</td>\n",
       "      <td>2.830386</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.060899</td>\n",
       "      <td>2.918285</td>\n",
       "      <td>15.987546</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.071320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step4_0</th>\n",
       "      <td>10.289548</td>\n",
       "      <td>11.160468</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.508488</td>\n",
       "      <td>2.313603</td>\n",
       "      <td>0.251617</td>\n",
       "      <td>10.803090</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>16.070024</td>\n",
       "      <td>1.862096</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step6_299</th>\n",
       "      <td>10.108256</td>\n",
       "      <td>10.029623</td>\n",
       "      <td>2.105454</td>\n",
       "      <td>9.715552</td>\n",
       "      <td>2.232493</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.621485</td>\n",
       "      <td>3.976765</td>\n",
       "      <td>15.557578</td>\n",
       "      <td>7.458399</td>\n",
       "      <td>8.457941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step7_299</th>\n",
       "      <td>10.904978</td>\n",
       "      <td>10.145182</td>\n",
       "      <td>3.111604</td>\n",
       "      <td>7.541061</td>\n",
       "      <td>7.537253</td>\n",
       "      <td>0.099348</td>\n",
       "      <td>10.711258</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>15.447946</td>\n",
       "      <td>9.274170</td>\n",
       "      <td>9.297236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step8_299</th>\n",
       "      <td>9.704970</td>\n",
       "      <td>11.674255</td>\n",
       "      <td>11.341400</td>\n",
       "      <td>8.373131</td>\n",
       "      <td>8.625268</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.082755</td>\n",
       "      <td>4.742084</td>\n",
       "      <td>15.915827</td>\n",
       "      <td>7.514682</td>\n",
       "      <td>6.965558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step9_299</th>\n",
       "      <td>10.027433</td>\n",
       "      <td>10.537213</td>\n",
       "      <td>8.574659</td>\n",
       "      <td>11.888068</td>\n",
       "      <td>7.494142</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10.017759</td>\n",
       "      <td>8.272767</td>\n",
       "      <td>15.929322</td>\n",
       "      <td>10.928268</td>\n",
       "      <td>8.366007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step10_299</th>\n",
       "      <td>9.849068</td>\n",
       "      <td>11.799258</td>\n",
       "      <td>11.705864</td>\n",
       "      <td>7.960316</td>\n",
       "      <td>9.627917</td>\n",
       "      <td>0.661587</td>\n",
       "      <td>9.990342</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>15.407105</td>\n",
       "      <td>8.814410</td>\n",
       "      <td>10.294417</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3300 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   tf      gene1      gene2      gene3     gene4     gene5  \\\n",
       "cellID                                                                       \n",
       "step0_0     11.199946   5.790686   3.239893   1.508778  2.019838  0.000000   \n",
       "step1_0     10.728647   8.038792   3.366851   3.182303  0.990765  0.000000   \n",
       "step2_0      9.614120  11.935944   0.000000   4.352651  0.000000  0.000000   \n",
       "step3_0      9.590053  12.294490   1.882482  10.208256  2.830386  0.000000   \n",
       "step4_0     10.289548  11.160468   0.000000   8.508488  2.313603  0.251617   \n",
       "...               ...        ...        ...        ...       ...       ...   \n",
       "step6_299   10.108256  10.029623   2.105454   9.715552  2.232493  0.000000   \n",
       "step7_299   10.904978  10.145182   3.111604   7.541061  7.537253  0.099348   \n",
       "step8_299    9.704970  11.674255  11.341400   8.373131  8.625268  0.000000   \n",
       "step9_299   10.027433  10.537213   8.574659  11.888068  7.494142  0.000000   \n",
       "step10_299   9.849068  11.799258  11.705864   7.960316  9.627917  0.661587   \n",
       "\n",
       "                gene6     gene7      gene8      gene9     gene10  \n",
       "cellID                                                            \n",
       "step0_0      2.859050  2.690069  15.004079   1.684236   0.868850  \n",
       "step1_0      3.585934  0.000000  15.404062   1.227158   4.214468  \n",
       "step2_0      3.361628  3.206353  15.721765   0.482383   4.521560  \n",
       "step3_0      4.060899  2.918285  15.987546   0.000000   4.071320  \n",
       "step4_0     10.803090  0.000000  16.070024   1.862096   0.000000  \n",
       "...               ...       ...        ...        ...        ...  \n",
       "step6_299    9.621485  3.976765  15.557578   7.458399   8.457941  \n",
       "step7_299   10.711258  0.000000  15.447946   9.274170   9.297236  \n",
       "step8_299    9.082755  4.742084  15.915827   7.514682   6.965558  \n",
       "step9_299   10.017759  8.272767  15.929322  10.928268   8.366007  \n",
       "step10_299   9.990342  0.000000  15.407105   8.814410  10.294417  \n",
       "\n",
       "[3300 rows x 11 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ids = [f\"step{x}_{y}\"  for y in range(n_samples) for x in random_walk_df.index]\n",
    "counts.index = ids\n",
    "counts.index.name = \"cellID\"\n",
    "counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f81a6be2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.27 s, sys: 439 ms, total: 3.71 s\n",
      "Wall time: 433 ms\n"
     ]
    }
   ],
   "source": [
    "%time synth_scbool = scBoolSeq().fit(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e0b234ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Category\n",
       "Bimodal     7\n",
       "Unimodal    3\n",
       "ZeroInf     1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "synth_scbool.criteria_.Category.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a3660d9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Mean', ylabel='Variance'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "synth_scbool.criteria_.plot.scatter(x=\"Mean\", y=\"Variance\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "16181369",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Mean', ylabel='DropOutRate'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "synth_scbool.criteria_.plot.scatter(x=\"Mean\", y=\"DropOutRate\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f521c2c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "from sklearn.manifold import TSNE\n",
    "from sklearn.pipeline import Pipeline, FunctionTransformer\n",
    "from sklearn.manifold import LocallyLinearEmbedding, SpectralEmbedding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "37ac8db3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def rename_columns(df):\n",
    "    \"\"\" \"\"\"\n",
    "    df = pd.DataFrame(df, index=counts.index)\n",
    "    df.columns = [f\"dim{i}\" for i in range(df.shape[1])]\n",
    "    return df\n",
    "\n",
    "N_COMPONENTS = 5\n",
    "\n",
    "vis_pipeline = Pipeline([\n",
    "    ('pca', PCA()),\n",
    "    ('subset_pca', FunctionTransformer(lambda x: x.iloc[:, :N_COMPONENTS] if isinstance(x, pd.DataFrame) else x[:, ][:, :N_COMPONENTS])),\n",
    "    ('lle', LocallyLinearEmbedding(n_neighbors=300, n_components=2, random_state=SEED)),\n",
    "    ('rename_cols', FunctionTransformer(rename_columns))\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7d25afea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1min, sys: 1min 24s, total: 2min 25s\n",
      "Wall time: 13.2 s\n"
     ]
    }
   ],
   "source": [
    "%time _pre_vis = vis_pipeline.fit_transform(synth_pseudocounts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "32c3fa10",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    tf  gene1  gene2  gene3  gene4  gene5  gene6  gene7  gene8  gene9  gene10\n",
       "0    1      0      0      0      0      0      0      0      0      0       0\n",
       "1    1      0      0      0      0      0      0      0      1      0       0\n",
       "2    1      1      0      0      0      0      0      0      1      0       0\n",
       "3    1      1      0      1      0      0      0      0      1      0       0\n",
       "4    1      1      0      1      0      0      1      0      1      0       0\n",
       "5    1      1      0      1      0      0      1      0      1      1       0\n",
       "6    1      1      0      1      0      0      1      0      1      1       1\n",
       "7    1      1      0      1      1      0      1      0      1      1       1\n",
       "8    1      1      1      1      1      0      1      0      1      1       1\n",
       "9    1      1      1      1      1      0      1      1      1      1       1\n",
       "10   1      1      1      1      1      1      1      1      1      1       1"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_walk_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2f937003-7f42-406b-823b-712151672631",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        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>tf</th>\n",
       "      <th>gene1</th>\n",
       "      <th>gene2</th>\n",
       "      <th>gene3</th>\n",
       "      <th>gene4</th>\n",
       "      <th>gene5</th>\n",
       "      <th>gene6</th>\n",
       "      <th>gene7</th>\n",
       "      <th>gene8</th>\n",
       "      <th>gene9</th>\n",
       "      <th>gene10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cellID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>step0_0</th>\n",
       "      <td>11.199946</td>\n",
       "      <td>5.790686</td>\n",
       "      <td>3.239893</td>\n",
       "      <td>1.508778</td>\n",
       "      <td>2.019838</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.859050</td>\n",
       "      <td>2.690069</td>\n",
       "      <td>15.004079</td>\n",
       "      <td>1.684236</td>\n",
       "      <td>0.868850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step1_0</th>\n",
       "      <td>10.728647</td>\n",
       "      <td>8.038792</td>\n",
       "      <td>3.366851</td>\n",
       "      <td>3.182303</td>\n",
       "      <td>0.990765</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.585934</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>15.404062</td>\n",
       "      <td>1.227158</td>\n",
       "      <td>4.214468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step2_0</th>\n",
       "      <td>9.614120</td>\n",
       "      <td>11.935944</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.352651</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.361628</td>\n",
       "      <td>3.206353</td>\n",
       "      <td>15.721765</td>\n",
       "      <td>0.482383</td>\n",
       "      <td>4.521560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step3_0</th>\n",
       "      <td>9.590053</td>\n",
       "      <td>12.294490</td>\n",
       "      <td>1.882482</td>\n",
       "      <td>10.208256</td>\n",
       "      <td>2.830386</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.060899</td>\n",
       "      <td>2.918285</td>\n",
       "      <td>15.987546</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.071320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step4_0</th>\n",
       "      <td>10.289548</td>\n",
       "      <td>11.160468</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.508488</td>\n",
       "      <td>2.313603</td>\n",
       "      <td>0.251617</td>\n",
       "      <td>10.803090</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>16.070024</td>\n",
       "      <td>1.862096</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step6_299</th>\n",
       "      <td>10.108256</td>\n",
       "      <td>10.029623</td>\n",
       "      <td>2.105454</td>\n",
       "      <td>9.715552</td>\n",
       "      <td>2.232493</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.621485</td>\n",
       "      <td>3.976765</td>\n",
       "      <td>15.557578</td>\n",
       "      <td>7.458399</td>\n",
       "      <td>8.457941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step7_299</th>\n",
       "      <td>10.904978</td>\n",
       "      <td>10.145182</td>\n",
       "      <td>3.111604</td>\n",
       "      <td>7.541061</td>\n",
       "      <td>7.537253</td>\n",
       "      <td>0.099348</td>\n",
       "      <td>10.711258</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>15.447946</td>\n",
       "      <td>9.274170</td>\n",
       "      <td>9.297236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step8_299</th>\n",
       "      <td>9.704970</td>\n",
       "      <td>11.674255</td>\n",
       "      <td>11.341400</td>\n",
       "      <td>8.373131</td>\n",
       "      <td>8.625268</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.082755</td>\n",
       "      <td>4.742084</td>\n",
       "      <td>15.915827</td>\n",
       "      <td>7.514682</td>\n",
       "      <td>6.965558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step9_299</th>\n",
       "      <td>10.027433</td>\n",
       "      <td>10.537213</td>\n",
       "      <td>8.574659</td>\n",
       "      <td>11.888068</td>\n",
       "      <td>7.494142</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10.017759</td>\n",
       "      <td>8.272767</td>\n",
       "      <td>15.929322</td>\n",
       "      <td>10.928268</td>\n",
       "      <td>8.366007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>step10_299</th>\n",
       "      <td>9.849068</td>\n",
       "      <td>11.799258</td>\n",
       "      <td>11.705864</td>\n",
       "      <td>7.960316</td>\n",
       "      <td>9.627917</td>\n",
       "      <td>0.661587</td>\n",
       "      <td>9.990342</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>15.407105</td>\n",
       "      <td>8.814410</td>\n",
       "      <td>10.294417</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3300 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   tf      gene1      gene2      gene3     gene4     gene5  \\\n",
       "cellID                                                                       \n",
       "step0_0     11.199946   5.790686   3.239893   1.508778  2.019838  0.000000   \n",
       "step1_0     10.728647   8.038792   3.366851   3.182303  0.990765  0.000000   \n",
       "step2_0      9.614120  11.935944   0.000000   4.352651  0.000000  0.000000   \n",
       "step3_0      9.590053  12.294490   1.882482  10.208256  2.830386  0.000000   \n",
       "step4_0     10.289548  11.160468   0.000000   8.508488  2.313603  0.251617   \n",
       "...               ...        ...        ...        ...       ...       ...   \n",
       "step6_299   10.108256  10.029623   2.105454   9.715552  2.232493  0.000000   \n",
       "step7_299   10.904978  10.145182   3.111604   7.541061  7.537253  0.099348   \n",
       "step8_299    9.704970  11.674255  11.341400   8.373131  8.625268  0.000000   \n",
       "step9_299   10.027433  10.537213   8.574659  11.888068  7.494142  0.000000   \n",
       "step10_299   9.849068  11.799258  11.705864   7.960316  9.627917  0.661587   \n",
       "\n",
       "                gene6     gene7      gene8      gene9     gene10  \n",
       "cellID                                                            \n",
       "step0_0      2.859050  2.690069  15.004079   1.684236   0.868850  \n",
       "step1_0      3.585934  0.000000  15.404062   1.227158   4.214468  \n",
       "step2_0      3.361628  3.206353  15.721765   0.482383   4.521560  \n",
       "step3_0      4.060899  2.918285  15.987546   0.000000   4.071320  \n",
       "step4_0     10.803090  0.000000  16.070024   1.862096   0.000000  \n",
       "...               ...       ...        ...        ...        ...  \n",
       "step6_299    9.621485  3.976765  15.557578   7.458399   8.457941  \n",
       "step7_299   10.711258  0.000000  15.447946   9.274170   9.297236  \n",
       "step8_299    9.082755  4.742084  15.915827   7.514682   6.965558  \n",
       "step9_299   10.017759  8.272767  15.929322  10.928268   8.366007  \n",
       "step10_299   9.990342  0.000000  15.407105   8.814410  10.294417  \n",
       "\n",
       "[3300 rows x 11 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "cf0500cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "def colorFader(c1, c2, mix=0):\n",
    "    \"\"\"fade (linear interpolate) from color c1 (at mix=0) to c2 (mix=1)\n",
    "    taken from:\n",
    "    https://stackoverflow.com/questions/25668828/how-to-create-colour-gradient-in-python\n",
    "    \"\"\"\n",
    "    c1 = np.array(mpl.colors.to_rgb(c1))\n",
    "    c2 = np.array(mpl.colors.to_rgb(c2))\n",
    "    return mpl.colors.to_hex((1 - mix) * c1 + mix * c2) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "eedf3770-bfc6-4b80-8a40-32168da7d19e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "cellID\n",
       "step0_0        1\n",
       "step1_0        2\n",
       "step2_0        3\n",
       "step3_0        4\n",
       "step4_0        5\n",
       "              ..\n",
       "step6_299      7\n",
       "step7_299      8\n",
       "step8_299      9\n",
       "step9_299     10\n",
       "step10_299    11\n",
       "Name: n_active_genes, Length: 3300, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_active_genes = random_walk_df.sum(axis=1)\n",
    "n_active_genes.name = \"n_active_genes\"\n",
    "n_active_genes = pd.concat(n_samples * [n_active_genes], ignore_index=False)\n",
    "n_active_genes.index = _pre_vis.index\n",
    "n_active_genes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0caa6254",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>n_active_genes</th>\n",
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       "      <th>0</th>\n",
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       "      <th>1</th>\n",
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       "      <td>2</td>\n",
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       "      <th>2</th>\n",
       "      <td>-0.019738</td>\n",
       "      <td>-0.003051</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.011879</td>\n",
       "      <td>0.003006</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.009320</td>\n",
       "      <td>0.024486</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       dim0      dim1  n_active_genes\n",
       "0 -0.025423 -0.019914               1\n",
       "1 -0.021633 -0.011200               2\n",
       "2 -0.019738 -0.003051               3\n",
       "3 -0.011879  0.003006               4\n",
       "4 -0.009320  0.024486               5"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vis_frame = _pre_vis.join(n_active_genes)\n",
    "vis_frame.index.name = \"index\"\n",
    "vis_frame = vis_frame.reset_index().drop(\"index\", axis=\"columns\")\n",
    "vis_frame.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "34fe8e59-d34b-4427-a3e5-94cf8ed9e98c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3300, 2)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_pre_vis.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "25f25d8c-3f3c-452a-90f5-55a6e63d142c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3300, 3)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vis_frame.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e1b66ffe-2e34-4c36-8a64-e77d85de9c33",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>3295</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3297</th>\n",
       "      <td>0.019084</td>\n",
       "      <td>-0.021071</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3298</th>\n",
       "      <td>0.022065</td>\n",
       "      <td>-0.020417</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3299</th>\n",
       "      <td>0.021527</td>\n",
       "      <td>-0.003065</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          dim0      dim1  n_active_genes\n",
       "3295  0.007988  0.013451               7\n",
       "3296  0.014505  0.017789               8\n",
       "3297  0.019084 -0.021071               9\n",
       "3298  0.022065 -0.020417              10\n",
       "3299  0.021527 -0.003065              11"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vis_frame.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "5a0ecd96-a328-4041-96ee-d2b2f1df8341",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "n_active_genes\n",
       "1     300\n",
       "2     300\n",
       "3     300\n",
       "4     300\n",
       "5     300\n",
       "6     300\n",
       "7     300\n",
       "8     300\n",
       "9     300\n",
       "10    300\n",
       "11    300\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vis_frame.n_active_genes.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "1248a9e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3300,)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([0.09090909, 0.18181818, 0.27272727, 0.36363636, 0.45454545,\n",
       "       0.54545455, 0.63636364, 0.72727273, 0.81818182, 0.90909091,\n",
       "       1.        ])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "levels = vis_frame.n_active_genes\n",
    "norm_levels = levels / levels.max()\n",
    "print(norm_levels.shape)\n",
    "norm_levels.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b85217af",
   "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>dim0</th>\n",
       "      <th>dim1</th>\n",
       "      <th>n_active_genes</th>\n",
       "      <th>color</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.025423</td>\n",
       "      <td>-0.019914</td>\n",
       "      <td>1</td>\n",
       "      <td>#0d168b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.021633</td>\n",
       "      <td>-0.011200</td>\n",
       "      <td>2</td>\n",
       "      <td>#1a2b8c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.019738</td>\n",
       "      <td>-0.003051</td>\n",
       "      <td>3</td>\n",
       "      <td>#27418c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.011879</td>\n",
       "      <td>0.003006</td>\n",
       "      <td>4</td>\n",
       "      <td>#34578d</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.009320</td>\n",
       "      <td>0.024486</td>\n",
       "      <td>5</td>\n",
       "      <td>#416c8d</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3295</th>\n",
       "      <td>0.007988</td>\n",
       "      <td>0.013451</td>\n",
       "      <td>7</td>\n",
       "      <td>#5c978e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3296</th>\n",
       "      <td>0.014505</td>\n",
       "      <td>0.017789</td>\n",
       "      <td>8</td>\n",
       "      <td>#69ad8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3297</th>\n",
       "      <td>0.019084</td>\n",
       "      <td>-0.021071</td>\n",
       "      <td>9</td>\n",
       "      <td>#76c38f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3298</th>\n",
       "      <td>0.022065</td>\n",
       "      <td>-0.020417</td>\n",
       "      <td>10</td>\n",
       "      <td>#83d890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3299</th>\n",
       "      <td>0.021527</td>\n",
       "      <td>-0.003065</td>\n",
       "      <td>11</td>\n",
       "      <td>#90ee90</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3300 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          dim0      dim1  n_active_genes    color\n",
       "0    -0.025423 -0.019914               1  #0d168b\n",
       "1    -0.021633 -0.011200               2  #1a2b8c\n",
       "2    -0.019738 -0.003051               3  #27418c\n",
       "3    -0.011879  0.003006               4  #34578d\n",
       "4    -0.009320  0.024486               5  #416c8d\n",
       "...        ...       ...             ...      ...\n",
       "3295  0.007988  0.013451               7  #5c978e\n",
       "3296  0.014505  0.017789               8  #69ad8f\n",
       "3297  0.019084 -0.021071               9  #76c38f\n",
       "3298  0.022065 -0.020417              10  #83d890\n",
       "3299  0.021527 -0.003065              11  #90ee90\n",
       "\n",
       "[3300 rows x 4 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "color = norm_levels.apply(lambda x: colorFader(\"darkblue\", \"lightgreen\", x))\n",
    "color.name = \"color\"\n",
    "vis_frame = vis_frame.join(color)\n",
    "vis_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "c173963a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = None\n",
    "for label, frame in vis_frame.groupby('n_active_genes'):\n",
    "    scatter_kwargs = dict(x='dim0', y='dim1', label=label, c=frame['color'], alpha=.8)\n",
    "    if ax is not None:\n",
    "        scatter_kwargs.update({'ax': ax})\n",
    "    ax = frame.plot.scatter(**scatter_kwargs)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f8f6934",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}