cellchat_eg.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "ffd78733-f48a-4ec4-9274-12840a233053",
   "metadata": {},
   "outputs": [],
   "source": [
    "library(CellChat)\n",
    "#library(patchwork)\n",
    "options(stringsAsFactors = FALSE)\n",
    "#library(Seurat)\n",
    "library(reticulate)\n",
    "use_condaenv(\"semi\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c2532ae-ffd1-46c8-a8ca-8fe1e03808f9",
   "metadata": {},
   "source": [
    "### Real-profiled version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "44934ad3-294c-4a46-99e6-c7f43be2d55c",
   "metadata": {},
   "outputs": [],
   "source": [
    "name = 'runexample'\n",
    "\n",
    "dataname = 'moderate_real'\n",
    "\n",
    "celltype_key = 'celltypes'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "a6de7232-83a4-4412-a2ba-eeb112be08ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "ad <- import(\"anndata\", convert = FALSE)\n",
    "\n",
    "fname = paste(name,'/',dataname,'.h5ad',sep='')\n",
    "adata <- ad$read_h5ad(fname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "422d87ca-ab47-4294-aa65-c067d29f2f55",
   "metadata": {},
   "outputs": [],
   "source": [
    "gtx = as.matrix(adata$X$todense()) # add todense if is sparse matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "2bd79977-0ce6-442a-8759-d0781df5ab98",
   "metadata": {},
   "outputs": [],
   "source": [
    "genes = reticulate::py_to_r(adata$var$index)\n",
    "genes = c()\n",
    "for (i in 1:length(adata$var$index)){\n",
    "    gene = as.character(adata$var$index[i-1])\n",
    "    genes = c(genes,gene)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "686e335b-4af0-4589-a6f1-7f9f5dbbea25",
   "metadata": {},
   "outputs": [],
   "source": [
    "colnames(gtx) = genes\n",
    "totalcid = c()\n",
    "\n",
    "for (i in 1:length(adata$obs$index)){\n",
    "    cid = as.character(adata$obs$index[i-1])\n",
    "    totalcid = c(totalcid,cid)\n",
    "}\n",
    "ctypes = c()\n",
    "for (i in 1:length(adata$obs[celltype_key])){\n",
    "    ctype = as.character(adata$obs[celltype_key][i-1])\n",
    "    ctypes = c(ctypes,ctype)\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "3e1f5b14-47f0-46e6-86c3-7d8cd614589f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"Create a CellChat object from a data matrix\"\n",
      "Set cell identities for the new CellChat object \n",
      "The cell groups used for CellChat analysis are  B_cell CD14 CD16 CD4 CD8 DCs gdT HSC Lymph_prolif MAIT Mono_prolif NK_16hi NK_56hi pDC Plasmablast Platelets RBC Treg \n"
     ]
    }
   ],
   "source": [
    "row.names(gtx)=totalcid\n",
    "gtmeta = data.frame(labels = ctypes, row.names = totalcid) \n",
    "cellchat <- createCellChat(object = t(gtx), meta = gtmeta, group.by = \"labels\")\n",
    "CellChatDB <- CellChatDB.human\n",
    "CellChatDB.use <- CellChatDB \n",
    "cellchat@DB <- CellChatDB.use\n",
    "cellchat <- subsetData(cellchat) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "71681def-8333-4468-a7e6-f7792aeb2679",
   "metadata": {},
   "outputs": [],
   "source": [
    "cellchat <- identifyOverExpressedGenes(cellchat)\n",
    "cellchat <- identifyOverExpressedInteractions(cellchat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "ded65afc-972d-47e4-8240-59e95877e7be",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "truncatedMean is used for calculating the average gene expression per cell group. \n",
      "[1] \">>> Run CellChat on sc/snRNA-seq data <<< [2023-12-11 18:34:55.236592]\"\n",
      "[1] \">>> CellChat inference is done. Parameter values are stored in `object@options$parameter` <<< [2023-12-11 18:35:36.502491]\"\n"
     ]
    }
   ],
   "source": [
    "trim = 0.1\n",
    "cellchat <- computeCommunProb(cellchat, type = \"truncatedMean\", trim = trim)\n",
    "cellchat <- computeCommunProbPathway(cellchat)\n",
    "cellchat <- aggregateNet(cellchat)\n",
    "cellchat <- netAnalysis_computeCentrality(cellchat)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "629973da-03fc-4fc2-93ee-5a9579f32f04",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Do heatmap based on a single object \n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
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FJFsCszHh4e6uXq1avb2dm5ubm5ubmF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rxcjIqKCgoGbLkSNHgoODDx8+rK2tPWvW\nrOzs7J07d44aNer27dv79u0jhBw/fnzatGl79+61tLQMDQ0dP358bGysaPe6Ww8ePFhz95kz\nZzZr1mzdunUFBQUzZ85UV1cfP368nM8aAAAAgGmF3bt3706fPr1s2bKajfb29nFxccJRPX9/\n/+XLl3M4HHV1dS6Xq6+vTwhZuXLl3Llz+/fvTwjZtm2boaHhixcvRLvX3frmzZuau79//97M\nzMzS0pLL5d66dYvFwi0pAAAAoABMKOyys7P79OlDCKmoqLh3797o0aO//vrrmh2sra3379+/\nd+/eoqKi7OzsysrKWkd4+vRpXFxcUlKS8C2bzU5PT5dwKyFky5YtQUFBzZs3d3NzGzdu3KRJ\nkyiKkvppAgAAAIjHhMLOwMAgNDSUEMLhcGxsbPT09Gp18PHxyc/PX7ZsmaGh4enTp9etW1f3\nCKNGjfrqq6+Eb0NDQy0tLQ8cOCBm65UrV0S729vbnz9/Pi8v78yZM4sXL379+vXChQtlcKIA\nAAAA4jBh0lBNTa1Hjx49evRwcXGpW9URQq5cueLv7+/m5mZtbf3PP//w+XxCCIvFqq6uFnbw\n9PS8d++eg4ODg4ODpaXlxYsX1dXVRbvXu1W0e3V19ezZs/Py8vT09MaPHz927NjHjx/L5bwB\nAAAA/oMJhd1H+fj4zJ8/39fX18vLq1+/fq9evZo5c6aDg0NiYmK/fv3evXsXEhKSmZnp6urq\n4+Pj4OCQm5urovK/scx6t4p2z8/P19TU7Ny58/jx44cMGRITEzN79mwFniwAAAB8sSiaphWd\nA/NtZvcWs3U2/5zote+kzbJPByQ1LGGnrEMc6zND1iGYwfF1sqJTkIJ3WiayDpGlIfMQIDmv\nh8dlHSLRbrCsQ8hB1L5/B0QqC0t26CnLGY2/udPQwVrRWXyyL2LEDgAAAOBLgMIOAAAAgCFQ\n2AEAAAAwBAo7AAAAAIZAYQcAAABQQ1O+rRSFHQAAACgFtiqHo6mm6CwIoQhLha3aTEPReXwO\nJjx5AgAAABiAzePOeBNXXVah6EQIW5Wroq6q6Cw+Bwo7AAAAUBZsHpfN4yo6iyYMU7EAAAAA\nDIHCDgAAAIAhUNgBAAAAMAQKOwAAAACGQGEHAAAAwBAUTTflZfiaCCrlrpitdJeOcssEPkm0\nk7esQ0xIPivrEMywbMQiRacgBSG/r1Z0CgDAcBixAwAAAGAIFHYAAAAADIHCDgAAAIAhUNgB\nAAAAMAQKOwAAAACGwLNiAQAAQClU0bTb44w8Pl98Nx7FSrCxMOZw5JNV04LCDgAAAJRCqUCQ\nXFomSc/XVdUo7OqFqVgAAAAAhkBhBwAAAMAQKOwAAAAAGAKFHQAAAABDoLADAAAAYAgUdmTH\njh0sFov3/wwNDQcOHPjgwYNaW9XU1HR1dd3d3S9duiTaNz8/f+7cuRYWFqqqqi1atBg9evT9\n+/cVdB4AAADwpUNhRwghtra25f8vPT3dwsJiwIABNE3X3FpWVpaTk+Ph4TF48OCqqipCSHFx\ncffu3ZOTkw8fPlxYWHjjxg1TU1NXV9eMjAyFng0AAAB8oVDY1aajoxMYGJiVlfXmzZtam9TU\n1KZOnfrhwwfhpm3bthUWFp4+fdrZ2ZnH45mZmW3YsGHz5s0qKlgdEAAAABQAJUht+fn5GzZs\nsLOza9GiRa1NJSUl27dvd3NzMzU1JYScPXt25MiRGhoaNft8/fXX8ssVAAAAoAYUdoQQkp6e\nrqOjQwgRCAQlJSUTJ048c+YMRVG1thYXFxsbG+/fv1/Ynpuba2xsrKicAQAAAGrBVCwhhNjY\n2BQUFBQUFGRmZurq6g4bNqxVq1Z1t1ZUVBw5cmTixInHjh0jhDRv3vz58+eKyxoAAADgP1DY\n/Yeenl5YWNjs2bOLiorqbmWz2a6urt7e3rGxsYSQr776KiYm5v379zX7hISEnDt3Tk7pAgAA\nANSAwq62GTNmtGjR4scff6x36927d8+ePdu5c2dCiL+/f8uWLXv37n3x4sXi4uKsrKygoKCd\nO3daW1vLN2UAAAAAQlDY1cVisbZu3frLL7/cvHlT2JKWliZc4k5dXX3EiBGBgYHz5s0jhKir\nq1+6dKl3795TpkzR09NzdXUtKSlJSkoyMzNT6BkAAADAF4oSrdYGskOl3BWzle7SUW6ZwCeJ\ndvKWdYgJyWdlHYIZlo1YpOgUpCDk99WKTgFAqRXy+Tp3HkjSM6WtTWd1NVnn0xRhxA4AAACA\nIVDYAQAAADAECjsAAAAAhkBhBwAAAMAQKOwAAAAAGAKPFAMAAACloMZi2aiq5lZXi++mzmI1\n56CAqR8+FwAAAFAKXIpKa99G0Vk0bZiKBQAAAGAIFHYAAAAADIHCDgAAAIAhUNgBAAAAMAQK\nOwAAAACGwF2x8hBN6Sk6BQAAAGA+jNgBAAAAMAQKOwAAAACGQGEHAAAAwBAo7AAAAAAYAoUd\nAAAAAEOgsAMAAABgCCx3AgAAAEpBQNNx915V8gXiu7FZ1EC7Fhpc1DD1wIgdAAAAKAW+gP5o\nVff/3Wg55NMUobADAAAAYAgUdgAAAAAMgcIOAAAAgCFQ2AEAAAAwBAo7AAAAAIZAYfev5ORk\nqj6xsbGKTg0AAABAIlgD5l9OTk40TRNCiouLtbS0bt265eDgoOikAAAAAD4BRuw+bubMmXPm\nzHFycho3blx1dfWSJUtsbW0tLS29vLyysrIIIfn5+SNGjDA1NXV0dIyOjqYoStEpAwAAwJcI\nI3Yfx+FwYmNjz50716ZNm7Vr18bHx1+7dk1PT2/9+vWDBg26e/duaGjohw8fnj59WllZOWzY\nMEXnCwAAAF8ojNhJxMXFpU2bNoSQ3377bebMmXp6eoSQoKCgx48fp6amnj17durUqVwuV1NT\nc/bs2YpOFgAAAL5QKOwkYmhoKHzx/v375cuXt27dunXr1jY2NhoaGq9fv87NzTUwMBB2MDMz\nU1yaAAAA8EXDVKxERJfNmZqazpkzZ/LkyTW36ujoFBQUCF+/fPlS3skBAAAAEEIwYvepxo4d\nu23btg8fPhBCbt68Kbydwt3dPTo6WiAQlJSUbNmyRdE5AgAAwBcKI3afZu7cuYWFhU5OToQQ\nLS2tFStWqKioLF++fNKkSRYWFq1atZo+ffqZM2cUnSYAAAB8iVDY1aapqSlc0E5k69atotcc\nDmflypUrV66s2cHExOSvv/5is9mEkH/++adZs2bySRUAAACgJkzFSsH69etdXV1LSkoEAsGv\nv/7q4eGh6IwAAADgS4QROynw9/e/e/dumzZt2Gx2x44dt2/fruiMAAAA4EuEwk4K1NXVd+/e\nregsAAAA4EuHqVgAAAAAhkBhBwAAAMAQmIoFAAAApaDCYhlr8yqqBeK7sVmUOoctn5SaHBR2\nAAAAoBQoivSyMlB0Fk0bpmIBAAAAGAKFHQAAAABDoLADAAAAYAgUdgAAAAAMgZsnAAAAQFns\n3LlTR0eHoihJOj958sTS0lJ2nVVUVLy9vbW0tCTZRUlQtR54DwAAAKAQhYWFOjo62trabPbH\nVzOhabqgoEDWnXfv3j1kyBCJslcOKOwAAABAKQgLu5SUlM6dO3+0c0FBga6u7q1btxwcHKTb\nOT8/X09P7/bt2506dZIob2WCa+wAAAAAGAKFHQAAAABDoLADAAAAYAjcFatcXrZsJesQI/0i\nZR2ieefNsg5BCBm4a7ysQ0zoO1XWITjvE2Qd4oqpzO/nenvGR9Yhfp8g8w8qJWSTrENUzJH5\n39LbPfVlHaLzs4WyDmGUESHrELkbCmUdghBy5PEpWYeYc2OjrENEU3qyDjG+s6nwhZaWVmBg\noIWFhSR7CTu3bt1a6p21tbUl76xsUNgBAACAUmCxWFu3bpWwM5vNVobOygZTsQAAAAAMgcIO\nAAAAgCEwFQsAAABK4d27dyUlJZqamgYGBk2ls7LBiB0AAAAoUllZWXBwsKGhYfPmzS0sLAwN\nDU1MTJYuXVpVVaW0nZUWRuwAAABAkQIDA7Oysg4fPmxnZ6ehoVFcXHz37t2QkJD8/PwtW7Yo\nZ2elhcIOAAAAFOn06dNpaWmamprCt9ra2iYmJo6Ojo6OjnUrKiXprLQwFQsAAACKJBAI2Gx2\nrUYej1fvHKiSdFZaFE3Tis4BAAAAvlyjR4+maTosLMzW1pbFYvH5/EePHi1atEhHR2ffvn3K\n2VlpYcQOAAAAFCkiIoLL5Xbs2JHD4airq3O5XCcnpxYtWmzbtk1pOystjNgBAACA4pWVlWVk\nZBQXF2tpadnY2Kiqqn5SZz6fX3citZFHbtWqVbNmzRp1VnKHwg4AAACaPB6PV15eXqvx7du3\nCxcuTE1N7dOnz48//qimpiZs19TULC4urtX5/fv3wcHBqampY8aMmTVr1sCBAxMSEtq3b3/0\n6NE2bdrI4xykAVOxAAAAwEz+/v6vX7/28/O7c+eOt7d3WVmZsL26urpu56CgoOzs7AkTJuzf\nvz8gIMDIyCg5OdnDw2PevHnyzbpRMGIHEomJiSGEjB49WorHLCkpqaio0NPTKykp2bt3b2Zm\nZtu2bSdMmCB+kLwxZHEWhJCrV6/m5eX16dOHw+Hs3bs3PT198ODB3bp1k24U2UlPTz958uSc\nOXMUnUhj7dy5c8aMGVFRUb6+vjIKMWvWLFk/GjwmJqZPnz6nTp0aPny4aHQBFCgrK0tDQ0Nf\nX1/Ucv/+fXV1dUtLSwVmpYTy8vJSUlJqNbJYLBMTE+G9CNIK1NC3a1JSkkAgqNVoaGj47Nkz\nTU1NmqYDAwPfv39/+PBh0sDwnpGRUXp6upaWVlpaWtu2bV+8eGFiYlJeXm5mZvb27Vtp5S9r\nKOyaHj8/v+Tk5Ho3RUZGOjk5NT7EpUuXLl26VLPl6tWrhJDOXBgAACAASURBVBBXV1d3d3d3\nd/fGh8jLy3Nyclq3bl3//v27dOnCZrM7dux4584dLpd77do1Lpfb+BByOAtCSGBg4O7du7W0\ntIyNjceMGbN//34bG5uEhIS//vrLzc1NKiGE4uPjS0tLx40bd/DgwcWLF7dv337fvn16enqN\nP/KFCxdCQ0MvXLjQ+EOJd/DgQQsLC9GX8ubNm62srAYOHCit4+vp6SUnJw8YMKDuuRgZGUkl\nBEXJ/Duzb9++AQEBa9asiYyMrPXvq6enJ5VfDT8/v9GjR8fExNT9JpHWd4gcQhBC3rx5ExkZ\n+cMPPwjfFhQULFiwYMOGDVpaWlI5vlBoaKi9vf2oUaNELT/++KOGhsaiRYukGEV2v+CEkKqq\nqrCwsIULF2poaAhbgoKCgoKCbG1tpXJ8oRs3bowaNSorK4vNZqurqxcVFWlqaqqrq+fm5jo4\nOJw5c0Zaj+dq3769h4dHx44da7UHBQXVXZfE0NAwKytL+DcSn88fNGiQi4tLaGhovYWdvr7+\n69evORwOTdOqqqqVlZWEkOrqal1d3aKiIqkkLwdYoLjpGTt2bK9everd1KpVK6mESEpKCgkJ\nGTJkiOii0Xfv3hFCMjIy7O3tpRIiJiamS5cuw4cP//33383NzU+ePCn8X+aAAQP++OMPqQyq\nyeEs3r59m5CQ8OrVK21t7aVLl+7evfvevXtcLvfQoUO7du2SYmFXVFQ0ffr0EydOlJWVBQQE\nbN68+Z9//tm0adOyZcukFULW4uPj/fz8jh49KmoxNjYeP378mTNnXF1dpRKiZ8+eVlZWwiPX\n2tSE/oLt16/f8OHDCSHt27evten8+fMN/e5/krFjx9ra2tb7TSKt7xA5hBAIBIMGDdLW1v7+\n++8pihK2PH/+fMKECcePH5dKCEKIcKiGzWb7+fkJW2iaLioqiouLk1YIIvtf8EWLFh09etTX\n11dY2Amrlj59+ty5c0dXV1cqIQghXbt27d69+4oVK8aPH8/hcLKysubPn79kyRJbW9vZs2ev\nWbNmzZo1Ugm0Z88ePz+/9evX83i8mu3ffvtt3c49e/b85ptvVq1aZWxszGazDx482Lt378LC\nwnq/E7p16/bDDz/88MMPzZo1y8/PJ4RUV1evWrWqa9euUslcPlDYNT3e3t6yDjF//nw2m71l\ny5YtW7YIB1Q2btxIGvi1+Tz5+fmdOnUihOTm5rq7uwu/lymK6tmz59OnT6USQg5nkZmZ6erq\nqq2tTQgZMGBASkqKcEDF0dFxz5490opCCHn48GHPnj27du166tSp9u3bT5o0ycnJaeHChdI6\n/osXL4QfTi2mpqY1ByoaY+3atRs3buzXr5+oZfTo0a9evVq5cuWJEyekEuKPP/7Iz893c3O7\nfPmyVA5Yr3o/KCK9/67mzZs3Y8aMr776ateuXbUGbKR1d57wO8Tc3Dw7O/vhw4fCYQkhFRXp\n/E9BDiEuXLiQl5d3+fJl4bcHIURPT++PP/5o06ZNcnKytAYFnz17Nn/+fAMDA1GFSlGUsbGx\ndOdhZfoLXlxcvHPnzhs3bpiZmQlbKIpau3bt06dPo6KiFixYIJUohJAHDx5UVFRMnjxZ+NbM\nzCwkJGT16tX79+//9ttvpfh95eTktHTp0vT09A4dOtRs7927d93OW7ZsmTRpUkJCwqRJkwgh\nOjo6iYmJgYGBNf+bFNm6devIkSM7dOgwadIkYREcGRm5devWU6dOSSt5OUBh1/TIYSqWoqi5\nc+f269dv8uTJx44dW79+feOPWYubm5ufn9/06dP79OkTGBgYHBysoqKSl5d38ODBn3/+WSoh\n5HAWLVu2vH37dnV1tYqKypUrV9LT04X329+/f7/uoFFjcLlc4RRDQkKCsDaqqKiQ4vHfvHmz\nf//+uu2Ojo7SKuzu3r07ZsyYWo0TJkwICwuTyvGFdHV1k5KSpDsTV0u9HxSR6h8MmpqaZ86c\n0dDQEJUsshAbGztu3DgDA4Oawx6HDh2qeTGZMoe4c+fO0KFDa43ZqKurDx06NCkpSVqFHZvN\nXrNmDZvNbmgdDamQ6S94enq6jY1N27Zta7VPmDDhyJEj0opCCGGz2c+ePau55khWVlZpaSkh\nJDk5WVrzsEIjRoyo23jy5Mm6jS1btjx37lzNFl1d3ejo6F9++aVuZwsLi5SUFD6fL2oZM2bM\nlClTmtbVrijsmh45TMUK2dnZXb16dfny5V26dOnatauzs7MUD+7u7j5mzBgrK6sePXpkZ2fb\n2tqam5vfunVr5MiRAwYMkGIgmZ5Fy5Yt7ezsrK2tDQ0Nc3NzJ02a1KtXr/bt2x85ckR4fa60\n2NnZ3bp1y9fXNzY2NiUlpby8fM2aNVI8F0dHR1lfY1fv/6h4PJ4Ur1xxcHBITEz08vKqu+n2\n7dvSitLQn1XSIp+r0wgh0dHRO3funDZtmrQOKOcQDZU+0v2PihDC5XJ/+umnoUOHtm/ffv78\n+TExMSNGjGho4PbzyPQXXG4flK2tLY/Hc3Bw6NWrl5aWVnZ29rFjxyIiIm7cuBEQEHD27Fkp\nxmo8MXPQNYt4aV3mKE8o7Joe0VRsaWlpXFxcWlrazJkzCSF6enq1/nhtPBUVleXLlw8aNMjP\nz69nz57SPXhYWNi0adNOnTqVmZlJCDE1Nf3ll1/atWsn3ShExmexf/9+4Qzg8OHDtbW1mzVr\n9uDBg127dkl3xlxVVfXPP/88cOBAbGyslZWV8Ot4/vz5UgwhazY2NhcvXhwyZEjNxj/++KPu\nQMJnW7BggYaGhhSnlhRCDlenCdE03aVLFykeUM4hbG1tY2NjaZquOa5ZVVV16tSpn376SYqB\nEhMTjxw54uvre+XKlUOHDkVFRa1YseL8+fOenp7SCiHTX3AbG5tHjx69e/fO0NCwZrt0f/sI\nISwW66+//tq7d+/Nmzffvn1rZGQUHx/v6elZVFSUkpLShNaBa/JoaJpevnzZsmVLBwcHExOT\nW7du7dixY8iQIbIOeunSpcTExKYeAmq5dOlSv379ZB1lw4YNrVq1unnzpqglMTFRX19/69at\nsg4tRRoaGopOQWoSExMDAgIqKyubaIjS0lJjY+N58+aVlZUJWwoLC6dMmWJqaipqkYqff/55\ny5YtNE0vXLjwhx9+oGl627Zta9eulWKIgoKCJ0+e1Gx5+/btP//8I63jDx061MvLKycnR/iW\nz+dv3rxZRUXl9u3b0gohcvv27fDw8N27d9M0XeukQD4wYtdULVu27Ntvv12wYMGwYcMIITNm\nzIiIiMjKyhJdHisLV65cKS8vr/cCVaUNkZ6eHhkZ+fDhQzab7eDg4Ofn17JlS2kdXKiwsDAi\nIuL69esVFRXW1tY+Pj5SnC8jsl+qwN7efv78+QkJCXU36ejoSOtcZs+effPmTScnJ3t7e2Nj\n4+fPnz9+/HjGjBkBAQFSOT4hxMHBoaFN0pqKrbtUvdTJ4SLayZMnJyUlsdnsd+/e7du3z8TE\nRLRp7969UpkBlEMINTW1mJiYYcOG7dmzx97evrq6+t69exoaGvHx8dKdu6h5AdymTZuItK9w\nJYTcunUrNja25hKJd+/eDQ8PP336tFSOHxER0b9/fysrqw4dOmhpaaWmpr5//z4iIkJ4B5sU\nLVu2bOPGje3atTM0NJw8eXLv3r0PHz7s4uIi3SggHgq7pur58+ffffed6C1FUXZ2dq9fv5ZK\nYZeRkZGRkVG3PS0tTVqFoxxCEEJOnjw5YsSIrl27uri4FBQUxMbGrl279tixY/VehvV5MjMz\n3d3deTxe3759KYq6c+fO5s2bV61aVfNfp5FkvVTBw4cPfXx8CCECgeDdu3eqqqqqqqofPnzQ\n0tIaOnTovn37Gh+CEMJisfbt2xcUFHT27Nnc3NxevXr1799fTCn2GeQwCXvt2rWGNklrSWo5\nXETr6+tba05cxMLCoqmEIIR07979yZMnR48eTU1NpSjK399/+PDhor9/pKVXr16DBw++fv16\nYWGhm5vby5cvo6KipPhU+AkTJsTHx1dVVdW8L6e4uHj27NnSCtGiRYsbN26cPHny+vXrpaWl\nw4YNGz58uNT/xM3Jydm1a1dGRkZ2dnZoaChFURs3boyIiEBhJ2+KHjKEz+Tv7//LL7/QND10\n6NBbt26VlJRYWlq+fftWKgdfsWIFj8drUYempmZISEhTCVFSUmJgYCCcQxESCASrVq0yMDAo\nKiqSSgiapvv37z9x4sTy8nJRS2JiopqamrSmUYSLfD58+LBW+/Dhw8PDw6USQkggEIwaNSoh\nIUH49tWrV+PHjz9//rwUQ9SNKKMj3759e8WKFbNmzfrpp5/qfnSNIc/v0tevX69bt2727NlL\nly4V/btIS1ZWlvDFs2fPfv755x9++OHPP/9sciHk5vjx4999992jR49omj537lxwcPCHDx+k\nePzY2NgRI0ZcruHWrVuy+wWRkatXr06aNImm6Vu3bg0dOpSm6bS0tP79+ys6ry8OCrum6vHj\nx9ra2n379m3duvWoUaOsrKxmzpwprYPn5OS0adPm9evXtdpXrVolrapLDiH+/PNPV1fXuu2u\nrq6HDx+WSoji/2vv3uOhTtvHgX9QyqzDUK3R41hO5ZBDyplqI6dyaAtrO7FPWKldUdv2VJ5o\nW1Ra2dLDLpXDhhxSSonKJkYqtMphkDaEYZE1TOb7x+f3fH7zOLStuWcm0/X+y9zzel3XXZFr\n7s9939fAgLi4eHd395jxb775xs/PD0mKyspKfX398ePp6emffvopkhS4qqoqDw+PMand3NxQ\nxf/zzz8DAwPxv6tXr16ZmpqKiora29vT6XRUKXAXLlyYPXu2nZ2dl5eXjY2NmJhYbm4uquAj\nk0OVAvfs2TNxcXETExMvLy8XFxcymbxnzx5Uwe/du/fRRx91dnY+efLko48+WrFixcaNGykU\nir+//zRKgaurqwsJCXFycnJ2dj506NCLFy/Qxid0dXU1NTU1NTXRaLTg4OCIiAiEwZlMJoPB\n4N7utJGRkby8vPT09KGhoc7OTgcHBzk5uT179qCtHdva2lRVVfv6+ojC7vTp019++SXCFOBd\nQGE3jT1//jwkJOTTTz/18/O7ePEi2h/RlJQUFxeXMYMIqy4epIiJifn666/Hj4eEhISHhyNJ\nUV1dbWBgMH786tWrq1evRpKitLR0wsLu8uXLaE881NTUGBkZMZlMYiQtLQ1hYRcYGKinp4eX\n8tu3b7eysrp+/bqTk9OE/0ac0NHRqaqqIl6Wl5dP+G+EUH9//5kzZ9DG9PPz+/HHH4mXdDpd\nRUWlq6sLSXB3d3d8JXvHjh3fffcdkYJCoaBa9edBChaLdeXKlVmzZpmbmwcFBXl7e2tra4uL\niyNf3WQwGGM2b0hKSiJfzD506BCZTDY1NV23bt3o6KiSktL9+/dRBXd3dxcTE6NQKCYmJgEB\nAdu3b4+Pj1dSUkpOTkaVAvfPf/5TQUHBwcFhwYIFLi4uUlJS9fX1aFOAvwR77KYxBQUF4i5f\n1v+e+eech4eHh4fHmEEvL6/xLZbf2xTd3d1jjvfjpKWlx7cIRJ5iwmvNp4BnVxVoamoKCwsv\nWbLE1NRUTEzsxYsXV69eTU5ORhU/IyPj3r17srKyLBYrIyPj+vXrhoaGixYtMjMzO3bsGKos\nGIYNDw+z30dvZGSEX5HKDVVVVWfOnLlw4YKioiJ+6xAqzc3N7FsGpaWlzc3NaTQakqt92fu+\nED+D0tLSOjo6NBptwm/p9zDF4ODg5s2bo6KiAgIC8BEWi/X999+7u7vjTd85T4HLyspiMBi1\ntbUFBQUYhmlqaubk5KBqNo3j6u60tra2/Px8Go2Gr5gWFRXV1NRgGDZr1qyrV696enpynoIQ\nFxeXlpZ27do1Y2NjVVXVmJgY5Dv5wF8S5vcEwBT19/e7uroSvZh0dHRycnK4nVReXp6rp27R\npmCxWAMDA+3jIDzYyGKxhoeHx6eg0+moUsyZM8fGxsbDw6OtrQ0fGR0djYmJSUxM3LJlC6os\nGIaJiIjgnXZGR0c7OjqUlJQKCwsnvN59ahgMhpKSEoZhv/3225s3b/DrzRQUFHp7e1GlwM2c\nOZP9XE5dXd3MmTPRphgaGjp//ryZmZm+vr60tPSvv/6K/6ZESFFR8c6dO+wZ2VtCccjU1PTk\nyZMMBsPBwYG4rP/Ro0eVlZWojlrzIEVxcbGamhpR1WEYJiQktHfvXjU1tQk7EExZU1OTl5eX\npqamuLg4fkwKv6ENYYrnz59bWlqyV+1aWlrt7e1Igre0tOjp6VEoFAzDXF1diaY4KioqxP8q\nSJSVlbm5ubm7uycmJiYnJ4eGhkJVxxewYjddRUVFiYiIEJ/nIiMjvb29V61ahfBzKg8uCuF2\nivDw8PDw8PHjBw8eRJWiqKhowu5hVlZWqFLw5qoCOp1eWVmppqampqaGjwwODt66dWv+/Pnq\n6urCwpx+CJwxY8bo6KiwsPDdu3fNzMzwBWYGg4F310Vo165dBgYGDg4OsrKynZ2dubm5E/YO\nmpr6+vq4uLgLFy7gzcI9PT0n/Abj3I4dO5YvX56enr5gwQIGg5Gfn29jYyMrK4sk+O7du93c\n3OTl5c3MzEpKSq5evTpr1qyqqqoTJ06gagnPgxQ0Gs3ExGT8uIWFxYQn7qdMVla2tLQUwzAy\nmUylUjEMU1BQePr0KcIUysrKpaWl7H0gCgsLUbWjHRoaIu5/ERcXJ9oqiIiIsPfO4tzixYvx\nXZVaWloIw4K/Cwq76YpKpX733XfEEw07OztDQ8Pa2lojIyMk8XlwUQi3UwQEBLi7u0/4Fqqu\nhcuWLautrZ3wLRKJhCQFxqurChobG729vZ8/fy4iIkIikfDTuCQSqaurS09P7/r16xz+pS1Z\nsuQ///mPs7NzbGzsl19+iQ9eunRp0aJFKKb//3l7e6urq2dmZra3t8vJyV2/ft3U1BRVcGNj\n46CgoIcPH6LtBTyelpZWdXV1QkICjUaTkpKKiIiY7Jt5CkgkUn5+/v379+/cubNgwQISiaSk\npOTs7IzkCSnPUvBgrwXOxcXl4MGDe/bsCQoK+uKLL/r6+q5du4Z2/wCFQlm5cqWWlpaurm5t\nba2rq+utW7cQNq/DHyxgGEan09m/RhUfR6PRhoeHlyxZQqFQiCWGZcuWnTt3Dm0i8Bf4usMP\nTJ2Xl9f58+eJl/39/crKyg0NDUiC8+CiEN7cRQL+Fg8Pj6SkJLxPQEtLy/r16x89ejQ4OOjj\n4xMcHMxh8LKyMgkJCey/m95YLFZ+fj6JRLp06RKCqbOZP38+2oDs1q5du2DBgn/9618tLS0s\nFktKSopLiRwdHSsrK7kUfDJJSUk0Gg1JqP7+fuIgTnNz8+HDh4ODg/Pz85EExx08ePDbb79t\nG+fbb79FeMYL19PTg991UlBQ4OHhERkZyY27SFJTUzdv3uzp6XngwAGEx3uLioomKwCsrKxQ\nZWGxWO3t7Wlpaen/q7i4GGEK8C6gsJuuysrKpKSkXFxcAgMDvb29FRQUPvvsM1TBeXBRCA9S\nsFis9vb2sLAw4mVPT4+3tzfaC6iGh4cPHDgwMDBAjAQEBDx79gxhChaL1dvb+/3337u6ujo4\nOOzcuZNKpaKNz2KxampqXF1d2Ueqq6vxb6qamhp7e3vOU9Dp9KqqKuJmkKqqKm5cbPbZZ58h\n/BYar6Wl5ZtvvpGTk7OzsyORSMgvOsGdOXPm66+/ZjAY3Ag+GVtbW1SHPa2srEpLS1ksVkND\ng6SkpIWFhZubG5lM3r9/P5L4LBbrLRsqkBd209rr169rJ4F/PkEiOjoaVSjAIXgUO10tW7as\ntLQ0MTGxpaVFUlLy6NGjGzduxN+qqKjgsO8QDzav8CDF6Oioo6OjpKTkvn378B1do6OjLS0t\nnp6ely9fRpIC435bCIwnzS0wDBMREWlqanrz5g2xBef58+f4edKKigokD6+lpaXZ/050dHTY\nj6+i0tra6u3t7e/vP2fOHOKoOMIdUYqKikeOHDl06FBGRsYff/whJyf36aefenp6mpubo0qB\nYVhtbW16enpcXJycnBzxL4KqGVd5efmEj+G6uro4Dz5GbGysr68vfn6/tbVVX18/ODhYUlKS\n88g82GuBTd6nztfX19fXl6spli5dGh8fz3l8EomE9gT9hLKysnbu3MntLOBdQGE3jS1atIi4\n7oRdVFRUWloaJ5H5e1EIqhTFxcV0Ov3u3bvEb3cZGZmcnBwNDQ3Oa1/cwMDA2bNn2Y8rCgkJ\nRUVF0Wi0hIQEVB2u/P39LS0tExISZs2ahY/cunXL0dHR0tJywuJ4atTV1WfPnq2np2dtbS0h\nIdHa2pqdnR0XF0elUv39/W/cuMFh/Ld0vVyzZg2Hwdn5+voiPwY7nqioqKenp6enZ1VVVWxs\n7Jo1a9C2kXV0dBxfKaJqxrVv3z4qlSomJjZmvKenB0l8dr///jtxcFVBQUFfX7+urg7JT9/c\nuXPxAq67u/uXX36pr68XEhLS0NDYsGEDqs9U2OR96nR1dbmdAtVZGVxJSUlbW9uaNWvwHREY\nhvX29uIfShFmAe8DKOzABFj/vShkzPjAwMCMGWi+Z3iQ4vHjx+vWrRvTDpxEIq1bt668vBzJ\nr5b6+no1NbXxn4Y9PT0vXrzIeXwMw16/fn337t2WlhaiqsMwbOXKlbt27Tp//jzCwk5YWLig\noODcuXMPHjx49eoVfqHDihUr+vv7KysrNTQ0OIy/fv164uvXr1+TSCSi4EZbEnl4eNy+ffvm\nzZt0On3u3Lk2NjZmZmYI44+hq6sbFxcXERGBNuwnn3xSV1eXmZn5+++/S0hILF26dO3atagK\n1uDg4KNHjxYWFo457Iy2wsZpa2s3NDRYWFhgGMZkMuvr62VkZBDGb2trW7p0KYVCUVdXf/Pm\nTX5+fnh4eHl5OX67B+fwNsp0Oj01NbWxsVFISEhdXd3d3V1KSgpJfCIFhmGPHz++cePGvHnz\nNm/eTKPRUJ2KxTAsJCQkOjpaQkJCQkKCSqXOmzcvNTX1q6++sra2RlXYvXjxIjo6evy4vLw8\n+88+4AEo7MDEeHBRCLdTMBiMCcdnz57Nfq3Ae56iqalJXV19/O9CCwuLEydOIElBEBcX9/f3\nHzMoISHBeVWH/W/1Nnfu3EePHsnLy3MedrzQ0NATJ05YWFhISUk1NjZGRkbu379/3759SIK/\n5XlrSUkJkhS4wsJCJycnY2NjOTm533///aeffjp79uy1a9eQ3ENua2ubnZ39ww8/7Nq1i/No\nk1m7du3cuXNFRESEhIS2bt3KZDJXr14tJyeHsF7BMOzy5cs+Pj6hoaHEyObNm9PS0hD+0dra\n2vT19WVkZPBbPK5cuXL48OEHDx6gXVELDQ2Njo5evHjxvHnzNm3atHLlyl9++QXJBcU9PT2n\nT59+8uTJwoULP//880OHDtXX1z948ODw4cOoniZjGNbR0XHhwoXx44aGhlDY8RgUdmACPNi8\nwoMU6urqGRkZrP/tyTEyMpKfn3/kyBEkKXjQFoIHzS0ETGZmZn19PfGXVl9fb2Jigqqwq6ys\nlJGRsbe3t7CwQNvrZYyEhIQrV66sWLECfzk4OLh06dLHjx9Pth/r7zp9+vT4wWPHjuHVdkVF\nBX4f75TjJyYmvnz5sqenh9jMN2PGjOXLl4eEhOAvEW6HGHOdjbm5OdpeI9nZ2atXrz5//jwx\nsm3btuzsbIS9RrjaeaKhoWHJkiX4/ZSbN2+2s7Pz9vZOTU1F0sWEYGhoWFxcjDAgmDIo7MAE\niM0r0zqFnZ1dQEDA7t27w8PD8QeyfX19gYGBfX19tra2SFIQbSHOnz+PX2w2OjoaGxubmJiI\n6g4q1n+bW4wZR34HlcCgUCjspbCamhrClZW2traUlJSEhIQbN25s3bp169atCgoKqIKzGxgY\nYH/OTiKR9PX1uVpKYhhG3CsbFRV16NAhTj6cKCsrKysrjxk8evQo8TXnW4Fxa9euPXDgwLJl\ny/B9dV1dXXl5eTExMZxHJgwNDRkaGrKPmJiYvH79GmEKovNEa2srPqKlpXX27FkkwV+/fk3U\n6JKSkqtXr0YVGbyfoKUYmFhHRwf7c9Le3l4fHx9Ujxd5k0JMTCw9Pf3cuXPy8vLW1tbm5uYK\nCgoFBQVZWVljNt5xIi4ujk6nL1y4cPny5Z988om8vPzu3bvRtoXAm1uM4eDggCq+gNHQ0MjP\nzydepqWl2dvbowouJSXl5+dXUVGRlZXV2dlpYGBgZ2eXkZGBfPXUw8MjIiKCyWTiL2tqanp7\ne7lxiHi6KykpKS4ulpOTW7x4saqq6vz58ysrK9euXaunp6enp3fmzBnOU7i5uV29epX4cNXd\n3Z2Xl+fm5sZ5ZAJXO0/wxvizOIBfYMUOTIAHF4Xw5i4SMzOzxsbGzMzM3377TUhIyNfX18XF\nBb+XBBVut4XgTXMLHmBfdGSxWJ2dncQpGVT73HFUKvXUqVNycnIyMjIdHR29vb3a2trEE8xH\njx4hyaKnpxcTExMZGZmamrpz505/f/9Xr14hiYy7d+/ezz//fPz4cXl5+b6+vhcvXmhoaOAN\ndjF0fwoBsGTJkrecXOH87Cr+nUOn0xUUFBQUFERERJ4/fy4rK1tYWIiwWTNfOk9gGCYqKorq\nLAv7pynAX1DYCSDijNWU8eCiEB6kwElKSm7duhVVtAmJiIg4OTk5OTlxIzhv7qDigTE9uIga\nBcMwFouFMJGfnx97Y3h2b7mC/+9isVi3b9+Oj4/Pycmxtrb28fFBFRnn4OAw2f4qhL/vBYC+\nvr6+vj734k94F8kff/yBfDktLi4uLS3t2rVrxsbGqqqqMTExCD8fjmlpTXxtZWUFG+MEDxR2\n01JjY2Npaamenp62tnZSUlJoaCiZTD537py2tjaGYY6OjhzG58FFITxIAd4rk607Ird58+bJ\n3oqKiuI8fkdHR2JiYkJCApPJ3LZt2/fff4+8by/2RX663AAADthJREFU1ptH8vLykKcDkyE+\nJ3d3d+OPSlks1unTpwcHBy0tLVFl+eOPP7q7u93d3YkjZZ2dnaWlpUjuMxKYVX/wjqCwm34e\nPnxobm5OJpN7enpiY2OPHDny7bffVlRUuLm5PXv2DEkKwbgoBLxXBGPd0dXV9e7du7a2trGx\nsZ988gm3TzOA98Hw8LC9vX1hYSExIikpmZOTgzDFw4cPMzIyTp06RYxUVVVFRka+5Vrvdycw\nq/7gHUFhN/2cPXv2yy+/jIiIaGpqMjIyOn78+KZNm7y9vVVVVRsaGlRVVTlPwYOLQniQAgDk\nsrKyyGRyXl5ednb2mLfQXrMM3h9ZWVkMBqO2tragoADDME1NzZycHITLdZ6enrm5uSMjI+z3\nwA0MDAQGBqJKAT4oUNhNP01NTXv37sUwTEVFRVNTc+HChfi4iopKW1sbksKOBxeF8CAFAMjx\n7IEyXwwODvb19VEoFC8vr48//pjbKbgRnxuampq8vLw0NTXv3bvHZDJtbGzKyspyc3OdnZ2R\nxE9JScnMzExJSfnqq6+IwdmzZ3PpBm8g8KCwm36GhoaIrWni4uJEg3AREZE3b94gSYFfFOLs\n7JyUlKStrc1kMqurqz/66KPc3FxUF4XwIAUAyAnGI60TJ04EBASMaVDW0dHh5OQUERFBoVA4\n36fLgxQ8IysrW1paimEYmUymUqkYhikoKDx9+hRhCmdnZycnp5GRka6uLvwsUWVl5cGDB69c\nuYIwC/hAwD120xKdTm9vb29vbx8eHmb/GmEK/KKQyMhIIyMjU1PT2NjY+vp6tGcaeJACADBe\nVVXV+vXrR0ZGiJHa2lpjY2NFRUUkrQ54k4JnXFxcrl27tmfPHnNzc3wnzOHDh9GW+CIiIv/+\n978lJCSUlZVVVFRUVFQ2btxoZWWFMAX4gLDAdPOWn/aioiJ+zw6A99eSJUv4PQUENm7cyGGE\noaEhR0fHtWvXDg8Ps1isoqIiaWnpvXv3jo6Oopggj1LwUk9Pz9OnT1ksVkFBgYeHR2RkJNo/\nyMuXLykUSklJCZVK3bBhQ01NzaZNm169eoUwBfhwCLGQ3iAFAAB8V1NT09rayr4zAX/wd+7c\nuU2bNvFvXn9PR0dHcnJyS0sLmUy2tLRctWoVPp6Xl8f5c8yRkZGNGze+efPG2dk5MDDw1KlT\nb7km5r1NITDu379/8uTJ1NRUGo22f//+lJSUu3fvZmZmRkdH83tqYPqBwg4AIFB27dp16tQp\nCoVCdLbAMKy5uZl/M5qKuro6Q0NDHR2dhQsXvn79uqioaPv27ey9VjnHZDK9vLzS09MLCwut\nra0RRuZlCh7o7+/ftGlTSUkJ+01M+/fv379/P6oUTU1N69ato1Kpr1+/dnBwKC0tbW5u9vX1\nRXLdCfjQwOEJAIBASU5Orq2tVVNT4/dEOBIdHR0REeHn54e/7OnpMTQ0DA4OnjNnDufB8b5S\nGIYdO3asr6+vqKiI2DEmIyMjKio6LVLwTHJy8syZM7Ozs9m7EaLtg6eioqKsrGxpaVlWVjY8\nPOzh4dHW1kb0wQPgb4EVOwCAQFFWVp5263Pj2dvbnzp1ir1v1aZNm3bs2GFkZMR5cGtr69u3\nb0/4VlFREZKlNR6k4Jnjx49ra2vb2NhwNQuTyXz8+LGhoWFjY2NYWJi0tPS//vUvaWlpriYF\nAgkKOwCAQAkPD5eTk9u2bRu/J8IRX19fY2Njos380NCQvr5+cXGxrKws58GfP38+ODg44VuK\niopI2kzxIAXPNDc3h4WFHT9+XFJSkt9zAeCvQWEHABAQ+MO+mTNnNjQ0SElJkclk4i20t47x\nwJMnT5YvX25lZbVgwQIGg5Gfn29jY5OQkMDveX2I+vr67Ozs7t+/P2fOHGHh/3dH2O7du3fv\n3o0k/mSPXJcuXRofH48kBfigwB47AICACAsL4/cUkNHS0qqurk5ISKDRaFJSUhEREUR7eM6V\nl5fT6fQJ31q2bJmMjMy0SMEzycnJZDI5NzeXfY+dsrIyqviTFYhIVmfBBwhW7AAAgub27ds3\nb96k0+lz5861sbExMzPj94ym4sWLF7W1tQwGgxgxMTFBcnhi69ateAcFgpCQEJPJfPr0KaoN\ncDxIwTNRUVG6urrc3mMHACpQ2AEABEpoaOiJEycsLCykpKS6urru3Lmzf//+ffv28Xtef09G\nRoanp+ecOXNmzZpFDKalpRkbG3MjXW5urr+//7Jly+Lj47m0nMaDFFzS2Nh48uTJyMhI9n8L\nhFpaWoKCgsrKyigUSlBQEMKlWfBhgsIOACBQdHV1CwsL582bh7+sr683MTHp6uri76z+Lmdn\n55CQEFNTU24nevXqVWBg4J07d2JiYtzc3KZpCq5KTEw8ePBgd3f3/PnziT12AQEBAQEBSOIb\nGhoqKSm5ubm1trZGRERkZmauWLECSWTwYYI9dgAAgUKhUIiqDsMwNTW16bhXSUhIyMDAgNtZ\nkpKSgoKCXF1da2trpaSkpmkKbjM0NIyKihISEmIfXLx4Mar4nZ2d5eXlIiIiGIZJSkqmpqZC\nYQc4AYUdAECgaGho5Ofn29nZ4S/T0tLs7e35O6Up8PHxOXnyZEhIyJh6ApWmpqbt27e3tLRk\nZmZyqdk8D1Lwho6Ojo6ODvfia2ho4FUdhmHa2trZ2dncywU+BML8ngAAAKBEpVLt7e3nz5+v\nra09b968zz///ObNm3r/xe/ZvauCgoKjR4/OmTNHk015eTmS4PHx8QYGBkZGRo8fP+ZSycWD\nFLx05MiRJ0+eYBgWFBSkqKi4a9cuhMGJqg7DMGFh4dHRUYTBwQcI9tgBAARKUlIS+2/KMby8\nvHg5mSkrLCzs6ekZM2hlZcX+lHnKrK2ty8rKSCTS8PDwmF8B+fn5FhYW0yIFzxQWFgYFBV2/\nfr2hoWHDhg0JCQmHDx8OCwtD9cB05cqVKSkp+Nfl5eVRUVEXL17EMExUVHR6nTIB7wko7AAA\n4H3U0dGRnJzc0tJCJpMtLS1XrVqFKrIgtYXggYiICBKJFBAQsGfPnpkzZ4aFhZ0+fXpwcDAo\nKAhJ/MmetltZWRUXFyNJAT4osMcOACBQLl68eODAgdbW1jdv3hCDQ0NDfJzSFNTV1RkaGuro\n6CxcuLC1tfWHH37Yvn370aNHkQRXVFREEucDISoqOjIygmHYzZs3T548iWEY++WCnIPlFYAW\nrNgBAASKqqpqeHi4mpoacTMFNnnXpveWv7+/jo6On58f/rKnp8fQ0JBKpSK5oBj8LY8ePXJy\ncjIzM6uoqKirq2tra1uzZs2PP/44vR4ogw8HrNgBAATKwoULN27cyO9ZcKq5uZm905S0tLS5\nuTmNRoPCjvf09PROnz5dUlISGhoqLCxcV1dnZ2c37T4qgA8HnIoFAAgUPT29W7du8XsWnFJU\nVLxz5w7xcmhoiEqlwiNUfnF0dAwODp41a1ZzczPeJfbMmTP8nhQAE4MVOwCAQNHX17e1tZ09\nezZ7y/b29nY+TmkKduzYsXz58vT09AULFjAYjPz8fBsbm+l407IAGB4etre3LywsJEYkJSVz\ncnL4OCUA3gIKOwCAQNm7d++pU6fG7LGbdrS0tKqrqxMSEmg0mpSUVEREBLQQ5ZesrCwGg1Fb\nW1tQUIBhmKamZk5OjqWlJb/nBcDEoLADAAgUdXX17du383sWCKioqISFhfF7FgBramry8vLS\n1NS8d+8ek8m0sbEpKyvLzc11dnbm99QAmAAUdgAAgaKnp/fgwQNDQ0N+T2SKduzY8fDhwwnf\niomJ0dfX5/F8gKysbGlpKYZhZDKZSqViGKagoPD06VN+zwuAicF1JwAAgWJmZlZWVkahUMTF\nxYnBafRr2N7e/tdff121apWdnZ2YmBj7W6tXr4ZtdrzX29urq6vr4eERFBS0aNEid3f3a9eu\nHTt2DFbswPsJCjsAgEBJS0ubMWPss4j169fzZTJTwGQy8/Ly4uPjS0tLN2zY4OPjM31XHwVG\nb29vR0eHhobGjRs3fv75ZwMDg6CgoMk6RgDAX1DYAQAEyrR+Dsvu5cuXiYmJP/30k7i4uLe3\n92effQadQwEAfwkKOwCAQBETE1NVVd26dauXl9fHH3/M7+lwisViFRUV7dmzp7q6+tdffxWM\nmnUamewiYl9fX19fXx5PBoB3AYcnAAACpaOj49KlS8nJyfv27bO1td2yZYujo+PMmTP5Pa+p\nePbsWXx8fFJSkqKiYnR09KJFi/g9ow8Oe/8Pdrq6ujyeCQDvCFbsAACCqb29PS0t7YcffhgY\nGNiyZcvOnTv/8Y9/8HtS7+TPP/9MT0+Pj4+vrq729PT84osvoIEVAOAdTeMLPAEAYDL9/f2X\nL1++dOnSixcvTExMhoaGDAwM8vLy+D2vv/bdd98pKSklJyf7+Pi8fPkyNjYWqjo+unPnjqWl\npby8vI2NTWVlJb+nA8BfgxU7AIBAuXfvXnx8/MWLF+fPn79t27YtW7ZQKBQMw6hU6oYNG5qa\nmvg9wb9gbW1dUVEhKio6MjIy5v/n/Px8CwsLfk3sw0Qmk7/44gt9ff3y8vKUlJTffvtt7ty5\n/J4UAG8DhR0AQKCQSCQ3NzcfHx8rK6sxb9na2l6/fp0vswLTlKenZ0pKCv71hg0bnJ2dPT09\n+TslAN4ODk8AAARKW1ublJQU+4iDg8OVK1cwDIOqDvxdWlpaxNfa2trNzc38mwsA7wT22AEA\nBMqYqg6Deg5wQEREhPhaWFh4dHSUj5MB4F3Aih0AAAAwsYGBgfb2duJrDMPwl+Li4uw96wB4\nf8AeOwCAgJsxYwaTyeT3LMC0NFnfsIMHDx46dIi3cwHgncCKHQBAQBArKwCgAmsfYNqBFTsA\ngIB4S1N2+I8OAPCBgMIOAAAAAEBAwKlYAAAAAAABAYUdAAAAAICAgMIOAAAAAEBAQGEHAAAA\nACAgoLADAAAAABAQUNgBAAAAAAgIKOwAAAAAAAQEFHYAAAAAAAICCjsAAAAAAAEBhR0AAAAA\ngICAwg4AAAAAQEBAYQcAAAAAICCgsAMAAAAAEBBQ2AEAAAAACAgo7AAAAAAABAQUdgAAAAAA\nAuL/ANK7eX9URP3JAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "netVisual_heatmap(cellchat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b61e393c-cf3c-41a6-a42c-6084070c4abc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "d0f2e5de-b3da-4efe-9598-9b8bada77813",
   "metadata": {},
   "source": [
    "### Semi-profiled version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "0ebe4b52-a45c-4538-8038-25e3081e443c",
   "metadata": {},
   "outputs": [],
   "source": [
    "name = 'runexample'\n",
    "dataname = 'moderate_semi'\n",
    "\n",
    "celltype_key = 'celltypes'\n",
    "\n",
    "ad <- import(\"anndata\", convert = FALSE)\n",
    "\n",
    "fname = paste(name,'/',dataname,'.h5ad',sep='')\n",
    "adata <- ad$read_h5ad(fname)\n",
    "\n",
    "gtx = as.matrix(adata$X)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "0245d3a3-61a9-43c6-a0f0-c30b4072680b",
   "metadata": {},
   "outputs": [],
   "source": [
    "genes = reticulate::py_to_r(adata$var$index)\n",
    "genes = c()\n",
    "for (i in 1:length(adata$var$index)){\n",
    "    gene = as.character(adata$var$index[i-1])\n",
    "    genes = c(genes,gene)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "94a2bba7-d501-4ed7-91f8-d7e02a3484d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "colnames(gtx) = genes\n",
    "totalcid = c()\n",
    "\n",
    "for (i in 1:length(adata$obs$index)){\n",
    "    cid = as.character(adata$obs$index[i-1])\n",
    "    totalcid = c(totalcid,cid)\n",
    "}\n",
    "ctypes = c()\n",
    "for (i in 1:length(adata$obs[celltype_key])){\n",
    "    ctype = as.character(adata$obs[celltype_key][i-1])\n",
    "    ctypes = c(ctypes,ctype)\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "824ed1f8-888a-4cd1-8092-609d9e854e6c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"Create a CellChat object from a data matrix\"\n",
      "Set cell identities for the new CellChat object \n",
      "The cell groups used for CellChat analysis are  B_cell CD14 CD16 CD4 CD8 DCs gdT HSC Lymph_prolif MAIT Mono_prolif NK_16hi NK_56hi pDC Plasmablast Platelets RBC Treg \n"
     ]
    }
   ],
   "source": [
    "row.names(gtx)=totalcid\n",
    "gtmeta = data.frame(labels = ctypes, row.names = totalcid) \n",
    "cellchat <- createCellChat(object = t(gtx), meta = gtmeta, group.by = \"labels\")\n",
    "CellChatDB <- CellChatDB.human\n",
    "CellChatDB.use <- CellChatDB \n",
    "cellchat@DB <- CellChatDB.use\n",
    "cellchat <- subsetData(cellchat) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "19503bdb-980e-44dd-ad84-63e26c05bc8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "cellchat <- identifyOverExpressedGenes(cellchat)\n",
    "cellchat <- identifyOverExpressedInteractions(cellchat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "80743262-fc6f-47ff-8b47-370574d7fd62",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "truncatedMean is used for calculating the average gene expression per cell group. \n",
      "[1] \">>> Run CellChat on sc/snRNA-seq data <<< [2023-12-11 18:36:01.053584]\"\n",
      "[1] \">>> CellChat inference is done. Parameter values are stored in `object@options$parameter` <<< [2023-12-11 18:36:46.818817]\"\n"
     ]
    }
   ],
   "source": [
    "trim = 0.1\n",
    "cellchat <- computeCommunProb(cellchat, type = \"truncatedMean\", trim = trim)\n",
    "cellchat <- computeCommunProbPathway(cellchat)\n",
    "cellchat <- aggregateNet(cellchat)\n",
    "cellchat <- netAnalysis_computeCentrality(cellchat)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "86169f21-ea79-4802-a573-34c7b437fec0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Do heatmap based on a single object \n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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AAAEkGwAwAAkIiK+EkxAABQDpmZyuvXsE7NzDaksbW5qamC8an8CHYAAKBcMFXI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t7d69+5IlS548eeLv75+bm+vh4REbG0sI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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "netVisual_heatmap(cellchat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9c9dd77b-7c0f-4a4e-b28e-6207a13048ab",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4b494c8e-4bc8-4182-a32e-87c76cfddea6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9184286f-163c-4aec-87e4-9cc9967ef5e2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.3.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}