analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "744b1c7f-1379-40a8-959f-094d1d1837a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import scanpy as sc\n",
    "import pandas as pd\n",
    "import anndata\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import matplotlib.patches as mpatches\n",
    "import numpy as np\n",
    "import glob\n",
    "from os.path import basename"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9af3cca8-8e82-4a55-bdb2-00993493a1ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "#read 10x expression data\n",
    "adata = sc.read_h5ad('GEX_anndata/10k_pbmc.h5ad')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e4cc7098-499d-4ef8-b3b7-19ff07479e21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 9913 × 2000\n",
       "    obs: 'n_genes', 'doublet_scores', 'predicted_doublets', '_scvi_batch', '_scvi_labels', 'leiden', 'Cell types'\n",
       "    var: 'gene_ids', 'feature_types', 'genome', 'n_cells', 'highly_variable', 'highly_variable_rank', 'means', 'variances', 'variances_norm'\n",
       "    uns: 'Cell types_colors', '_scvi_manager_uuid', '_scvi_uuid', 'hvg', 'leiden', 'leiden_colors', 'log1p', 'neighbors', 'umap'\n",
       "    obsm: 'X_scVI', 'X_umap'\n",
       "    layers: 'counts'\n",
       "    obsp: 'connectivities', 'distances'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "486238dd-9776-4770-89f3-ec200c2b1767",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/adavydov/miniconda3/envs/scanpy/lib/python3.11/site-packages/scanpy/plotting/_tools/scatterplots.py:392: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n",
      "  cax = scatter(\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pl.umap(\n",
    "    adata,\n",
    "    color=['Cell types'],\n",
    "    use_raw=True,\n",
    "    frameon=False,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "887a0d08",
   "metadata": {},
   "source": [
    "## Performance comparison (figure 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f48e583d-b7e9-42b7-9bc0-64e47f0c8572",
   "metadata": {},
   "outputs": [],
   "source": [
    "#reading MiXCR VDJ data\n",
    "mixcr_vdj_t = pd.read_table('mixcr_results/10k_PBMC_5pv2_nextgem_Chromium_Controller_vdj_t_mixcr.tsv', sep='\\t')\n",
    "mixcr_vdj_b = pd.read_table('mixcr_results/10k_PBMC_5pv2_nextgem_Chromium_Controller_vdj_b_mixcr.tsv', sep='\\t')\n",
    "#reading Cell Ranger VDJ data\n",
    "cr_vdj_b = pd.read_table('cellranger_results/10k_PBMC_5pv2_nextgem_Chromium_Controller_vdj_b_cellranger.csv', sep=',')\n",
    "cr_vdj_t = pd.read_table('cellranger_results/10k_PBMC_5pv2_nextgem_Chromium_Controller_vdj_t_cellranger.csv', sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "72af8cb4-5c82-448d-a6ba-df18b50f3306",
   "metadata": {},
   "outputs": [],
   "source": [
    "#label cells that have T/B cell receptor\n",
    "cr_b_barcodes = cr_vdj_b['barcode'].tolist()\n",
    "cr_t_barcodes = cr_vdj_t['barcode'].tolist()\n",
    "mixcr_b_barcodes = mixcr_vdj_b['tagValueCELL'].tolist()\n",
    "mixcr_t_barcodes = mixcr_vdj_t['tagValueCELL'].tolist()\n",
    "\n",
    "adata.obs['barcode'] = adata.obs.index\n",
    "adata.obs['barcode'] = adata.obs['barcode'].apply(lambda x: x.split('-')[0])\n",
    "\n",
    "cr_b_barcodes = [b.split('-')[0] for b in cr_b_barcodes]\n",
    "cr_t_barcodes = [b.split('-')[0] for b in cr_t_barcodes]\n",
    "\n",
    "adata.obs['VDJ B cellranger'] = np.where(adata.obs['barcode'].isin(cr_b_barcodes), 1, 0)\n",
    "adata.obs['VDJ T cellranger'] = np.where(adata.obs['barcode'].isin(cr_t_barcodes), 1, 0)\n",
    "adata.obs['VDJ B MiXCR'] = np.where(adata.obs['barcode'].isin(mixcr_b_barcodes), 1, 0)\n",
    "adata.obs['VDJ T MiXCR'] = np.where(adata.obs['barcode'].isin(mixcr_t_barcodes), 1, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "dbe97e07-cb58-43e9-ad3e-f6eddd2d0d24",
   "metadata": {},
   "outputs": [],
   "source": [
    "#extract barcodes for cells with paired chains\n",
    "def paired_cells_cr(df, chain):\n",
    "    cr_chains = df.groupby('barcode')['chain'].apply(set).reset_index()\n",
    "    cr_paired_barcodes = []\n",
    "    for i, row in cr_chains.iterrows():\n",
    "        chains = row['chain']\n",
    "        if chain in chains and len(chains)>1:\n",
    "            cr_paired_barcodes.append(row['barcode'])\n",
    "        else:\n",
    "            continue\n",
    "    return cr_paired_barcodes\n",
    "\n",
    "def paired_cells_mixcr(df, chain):\n",
    "    mixcr_chains = df.groupby('tagValueCELL')['topChains'].apply(set).reset_index()\n",
    "    mixcr_paired_barcodes = []\n",
    "    for i, row in mixcr_chains.iterrows():\n",
    "        chains = row['topChains']\n",
    "        if chain in chains and len(chains)>1:\n",
    "            mixcr_paired_barcodes.append(row['tagValueCELL'])\n",
    "        else:\n",
    "            continue\n",
    "    return mixcr_paired_barcodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fc009974-ef64-4cb1-aa6f-4ccee171822a",
   "metadata": {},
   "outputs": [],
   "source": [
    "cr_b_paired_barcodes = paired_cells_cr(cr_vdj_b, 'IGH')\n",
    "cr_t_paired_barcodes = paired_cells_cr(cr_vdj_t, 'TRB')\n",
    "mixcr_b_paired_barcodes = paired_cells_mixcr(mixcr_vdj_b, 'IGH')\n",
    "mixcr_t_paired_barcodes = paired_cells_mixcr(mixcr_vdj_t, 'TRB')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1671802c-f75f-426b-9ba5-3018a5e06849",
   "metadata": {},
   "outputs": [],
   "source": [
    "#label cells with paired alpha/beta TCRs or heavy/light IG chains\n",
    "cr_b_paired_barcodes = [b.split('-')[0] for b in cr_b_paired_barcodes]\n",
    "cr_t_paired_barcodes = [b.split('-')[0] for b in cr_t_paired_barcodes]\n",
    "adata.obs['VDJ B cellranger paired'] = np.where(adata.obs['barcode'].isin(cr_b_paired_barcodes), 1, 0)\n",
    "adata.obs['VDJ T cellranger paired'] = np.where(adata.obs['barcode'].isin(cr_t_paired_barcodes), 1, 0)\n",
    "adata.obs['VDJ B MiXCR paired'] = np.where(adata.obs['barcode'].isin(mixcr_b_paired_barcodes), 1, 0)\n",
    "adata.obs['VDJ T MiXCR paired'] = np.where(adata.obs['barcode'].isin(mixcr_t_paired_barcodes), 1, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a42e382a-8735-467d-be6e-ef3799b73741",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Fraction of cells in cluster containing one/pair chains of TCR/IG\n",
    "cells_df = adata.obs\n",
    "vdj_stats = cells_df.groupby('Cell types').aggregate({'VDJ B MiXCR' : lambda x: x.sum() / len(x),\n",
    "                                         'VDJ T MiXCR': lambda x: x.sum() / len(x),\n",
    "                                        'VDJ B MiXCR paired' : lambda x: x.sum() / len(x),\n",
    "                                         'VDJ T MiXCR paired': lambda x: x.sum() / len(x),\n",
    "                                         'VDJ B cellranger' : lambda x: x.sum() / len(x),\n",
    "                                         'VDJ T cellranger': lambda x: x.sum() / len(x),\n",
    "                                        'VDJ B cellranger paired' : lambda x: x.sum() / len(x),\n",
    "                                         'VDJ T cellranger paired': lambda x: x.sum() / len(x)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "57c69cdd-aa6a-47fd-b64b-04a3ff977270",
   "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>VDJ B MiXCR</th>\n",
       "      <th>VDJ T MiXCR</th>\n",
       "      <th>VDJ B MiXCR paired</th>\n",
       "      <th>VDJ T MiXCR paired</th>\n",
       "      <th>VDJ B cellranger</th>\n",
       "      <th>VDJ T cellranger</th>\n",
       "      <th>VDJ B cellranger paired</th>\n",
       "      <th>VDJ T cellranger paired</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cell types</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>B cells</th>\n",
       "      <td>0.896887</td>\n",
       "      <td>0.105058</td>\n",
       "      <td>0.854086</td>\n",
       "      <td>0.066148</td>\n",
       "      <td>0.891051</td>\n",
       "      <td>0.075875</td>\n",
       "      <td>0.836576</td>\n",
       "      <td>0.062257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD4 T cells</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.805992</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.703310</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.761295</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.674076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 T cells</th>\n",
       "      <td>0.000655</td>\n",
       "      <td>0.861166</td>\n",
       "      <td>0.000655</td>\n",
       "      <td>0.736084</td>\n",
       "      <td>0.001310</td>\n",
       "      <td>0.811395</td>\n",
       "      <td>0.000655</td>\n",
       "      <td>0.690897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Monocytes</th>\n",
       "      <td>0.002441</td>\n",
       "      <td>0.050448</td>\n",
       "      <td>0.002441</td>\n",
       "      <td>0.039056</td>\n",
       "      <td>0.002441</td>\n",
       "      <td>0.045159</td>\n",
       "      <td>0.002034</td>\n",
       "      <td>0.034988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK cells</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.045260</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.019641</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.025619</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.012810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Undefined</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.057692</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.048077</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.057692</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.048077</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             VDJ B MiXCR  VDJ T MiXCR  VDJ B MiXCR paired  VDJ T MiXCR paired  \\\n",
       "Cell types                                                                      \n",
       "B cells         0.896887     0.105058            0.854086            0.066148   \n",
       "CD4 T cells     0.000000     0.805992            0.000000            0.703310   \n",
       "CD8 T cells     0.000655     0.861166            0.000655            0.736084   \n",
       "Monocytes       0.002441     0.050448            0.002441            0.039056   \n",
       "NK cells        0.000000     0.045260            0.000000            0.019641   \n",
       "Undefined       0.000000     0.057692            0.000000            0.048077   \n",
       "\n",
       "             VDJ B cellranger  VDJ T cellranger  VDJ B cellranger paired  \\\n",
       "Cell types                                                                 \n",
       "B cells              0.891051          0.075875                 0.836576   \n",
       "CD4 T cells          0.000000          0.761295                 0.000000   \n",
       "CD8 T cells          0.001310          0.811395                 0.000655   \n",
       "Monocytes            0.002441          0.045159                 0.002034   \n",
       "NK cells             0.000000          0.025619                 0.000000   \n",
       "Undefined            0.000000          0.057692                 0.000000   \n",
       "\n",
       "             VDJ T cellranger paired  \n",
       "Cell types                            \n",
       "B cells                     0.062257  \n",
       "CD4 T cells                 0.674076  \n",
       "CD8 T cells                 0.690897  \n",
       "Monocytes                   0.034988  \n",
       "NK cells                    0.012810  \n",
       "Undefined                   0.048077  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vdj_stats"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c70b500",
   "metadata": {},
   "source": [
    "# Cells/clones overlap analyses (figure 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8ec85ec0-968f-499a-90a3-09f89b22c510",
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib_venn import venn2, venn2_circles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ec190fc1-719a-4db0-8de0-3ff4bfc8923a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vdj_T_mixcr_barcodes = adata.obs[adata.obs['VDJ T MiXCR']==1]['barcode'].tolist()\n",
    "vdj_B_mixcr_barcodes = adata.obs[adata.obs['VDJ B MiXCR']==1]['barcode'].tolist()\n",
    "vdj_T_cr_barcodes = adata.obs[adata.obs['VDJ T cellranger']==1]['barcode'].tolist()\n",
    "vdj_B_cr_barcodes = adata.obs[adata.obs['VDJ B cellranger']==1]['barcode'].tolist()\n",
    "venn2([set(vdj_B_mixcr_barcodes), set(vdj_B_cr_barcodes)], ('MiXCR', 'Cell Ranger'), )\n",
    "plt.gcf().suptitle(\"B cells\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0f137bd8-fafc-4924-8c65-caeeffd01899",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "venn2([set(vdj_T_mixcr_barcodes), set(vdj_T_cr_barcodes)], ('MiXCR', 'Cell Ranger'), )\n",
    "plt.gcf().suptitle(\"T cells\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a31d5f05-6817-4f6b-b913-512a99a504b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#create columns with nt or aa VDJ sequences\n",
    "mixcr_vdj_t['ntVDJ'] = mixcr_vdj_t['nSeqFR1']+mixcr_vdj_t['nSeqCDR1']+mixcr_vdj_t['nSeqFR2']+mixcr_vdj_t['nSeqCDR2']+mixcr_vdj_t['nSeqFR3']+mixcr_vdj_t['nSeqCDR3']+mixcr_vdj_t['nSeqFR4']\n",
    "mixcr_vdj_b['ntVDJ'] = mixcr_vdj_b['nSeqFR1']+mixcr_vdj_b['nSeqCDR1']+mixcr_vdj_b['nSeqFR2']+mixcr_vdj_b['nSeqCDR2']+mixcr_vdj_b['nSeqFR3']+mixcr_vdj_b['nSeqCDR3']+mixcr_vdj_b['nSeqFR4']\n",
    "mixcr_vdj_t['aaVDJ_part'] = mixcr_vdj_t['aaSeqFR1']+mixcr_vdj_t['aaSeqCDR1']+mixcr_vdj_t['aaSeqFR2']+mixcr_vdj_t['aaSeqCDR2']+mixcr_vdj_t['aaSeqFR3']+mixcr_vdj_t['aaSeqCDR3']\n",
    "mixcr_vdj_b['aaVDJ_part'] = mixcr_vdj_b['aaSeqFR1']+mixcr_vdj_b['aaSeqCDR1']+mixcr_vdj_b['aaSeqFR2']+mixcr_vdj_b['aaSeqCDR2']+mixcr_vdj_b['aaSeqFR3']+mixcr_vdj_b['aaSeqCDR3']\n",
    "\n",
    "cr_vdj_t['ntVDJ'] = cr_vdj_t['fwr1_nt'] + cr_vdj_t['cdr1_nt'] + cr_vdj_t['fwr2_nt'] + cr_vdj_t['cdr2_nt'] + cr_vdj_t['fwr3_nt'] + cr_vdj_t['cdr3_nt'] + cr_vdj_t['fwr4_nt']\n",
    "cr_vdj_t['aaVDJ'] = cr_vdj_t['fwr1'] + cr_vdj_t['cdr1'] + cr_vdj_t['fwr2'] + cr_vdj_t['cdr2'] + cr_vdj_t['fwr3'] + cr_vdj_t['cdr3'] + cr_vdj_t['fwr4']\n",
    "cr_vdj_b['ntVDJ'] = cr_vdj_b['fwr1_nt'] + cr_vdj_b['cdr1_nt'] + cr_vdj_b['fwr2_nt'] + cr_vdj_b['cdr2_nt'] + cr_vdj_b['fwr3_nt'] + cr_vdj_b['cdr3_nt'] + cr_vdj_b['fwr4_nt']\n",
    "cr_vdj_b['aaVDJ'] = cr_vdj_b['fwr1'] + cr_vdj_b['cdr1'] + cr_vdj_b['fwr2'] + cr_vdj_b['cdr2'] + cr_vdj_b['fwr3'] + cr_vdj_b['cdr3'] + cr_vdj_b['fwr4']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "210453ef-e645-45a7-9d74-a1425b81ad37",
   "metadata": {},
   "outputs": [],
   "source": [
    "#filtering clones (remove non productive)\n",
    "mixcr_vdj_t['VDJ_len'] = mixcr_vdj_t['ntVDJ'].str.len()\n",
    "mixcr_vdj_t = mixcr_vdj_t[mixcr_vdj_t['VDJ_len']>=250]\n",
    "mixcr_vdj_b['VDJ_len'] = mixcr_vdj_b['ntVDJ'].str.len()\n",
    "mixcr_vdj_b = mixcr_vdj_b[mixcr_vdj_b['VDJ_len']>=250]\n",
    "\n",
    "mixcr_vdj_b = mixcr_vdj_b[~mixcr_vdj_b['aaVDJ_part'].str.contains('\\*')]\n",
    "mixcr_vdj_b = mixcr_vdj_b[~mixcr_vdj_b['aaVDJ_part'].str.contains('_')]\n",
    "\n",
    "mixcr_vdj_t = mixcr_vdj_t[~mixcr_vdj_t['aaVDJ_part'].str.contains('\\*')]\n",
    "mixcr_vdj_t = mixcr_vdj_t[~mixcr_vdj_t['aaVDJ_part'].str.contains('_')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "296d47b6-800a-4786-87bc-d5ca79a5598d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xefNmr3bz588XAMSSJUuEEEJMnjxZABA5OTl+n9ullGxXsmMZOHCg1+1z584VAMSGDRvK3M7lcgm73S6OHj0qAIj//ve/nvtKXruXXnrJa5sNGzYIAOKdd97xuv348ePCYDB4wtOFCxeEXq8XN910k1e7X3/9VQBQHBANBoNX6HQ4HKJFixaiSZMmntsefPBBYTabxdGjR722L3ntSoLauXPnBAAxfvz4Ur/rrrvuEo0aNfL8u2/fvuL+++8XUVFRni8EJbWvWLFCCCHEsWPHhFqtFo8++qjXY+Xn54uEhASvcNaiRQvRsWNHzwGlxKBBg0RiYqJwOp1CiL8/E5e+R9966y0BQJw+fdrva3ZxQJw5c6bQ6XQiKyvLswMrOVgFEhCFEOLrr78WAERCQoLIz8/3uk+v15faMfpTElzsdruw2+3i/Pnz4qOPPhKyLHt9BpUqeR+vXbtWABA7duzw+l0AxNy5c722GThwoGjevLnn3x999FGpz4AQ7i9DSgJiIK9BMPaRJe0q+jo7HA5hs9lE06ZNxWOPPea5Xem+Jjs7W+h0OjF06FCvdiX7j4s//0r3oUK49wkREREiOzu73OcvhBAtW7YUAwYMKHV7t27dRHx8vNd72eFwiDZt2ojk5GTPceX9998XAMTevXs97Uqe27hx4zy39e/fXyQnJ4vc3Fyv3/PII48IvV7vqbfk9evZs2epmsoKiJdyOByioKBAmEwm8d5773luL3mf+NrfTpw40XNbybGtrPe6LMue/ejs2bMFAPHtt996tdu8ebMA4MkMJcfVi98nQggxa9YsAUBxQKxfv74oLi723J6Xlyeio6NF3759Sz3P33//3XPbb7/9VurETVkC2be2bt3a5zGqZB9bEhqFEGLRokUCgPj000+92pYXEJcuXSoAiDfffNNzm6+AuHLlSgFALF261O/zvFiFupi//PJLbN68GZs3b8bSpUsxfPhwPPzww/j3v//td7uVK1fC6XTi4Ycf9tlm/fr1yM7OxvDhw+FwODw/LpcLAwYMwObNm0t1GwRq/fr1yMvLw5gxYwIau7FmzRoAKDWrqmvXrmjZsmWp7p2EhAR07drV67Z27dp5nQ5evHgx2rRpgw4dOng93/79+3vNSOvSpQsA4LbbbsPcuXMVz2gMZLsbbrihVK0AvOo9e/YsHnroIaSkpECtVkOj0SA1NRUA8Ndff5V6zFtuucXr34sXL4YkSbjrrru8nm9CQgLat2/veb4bNmyAxWLBnXfe6bX9VVdd5fl9SvTp0wf16tXz/FulUmHo0KE4cOCAZ1jA4sWL0atXL9SvX9+rpuuuuw4AsHbtWkW/59ChQzh8+DAsFgt++eUXDBgwAL169fJ0065atQo6nQ7XXHMNAGD58uVwOBy45557vH6vXq9Henq657U4cOAA9uzZ43ktLm47cOBAnD59ulT3nJK/ZXluvfVWaLVazJo1C0uWLMGZM2fKnVFYFpfLhQ8++ACyLOPs2bPYsWNHwI9xqcLCQmg0Gmg0GsTGxmL06NEYOnQoXnvtNUXbHzp0CHfccQcSEhKgUqmg0WiQnp4OoPT7WJKkUmOrL/0cr1mzBmFhYaVe90DG+ygVjH1kCaWvs8PhwOuvv45WrVpBq9VCrVZDq9Vi//79Ze4Xynt/bty4EVarFbfddptXu27dupWaga10H1qid+/eiIqKUvT8T506hfj4+FKvyaZNmzBkyBCYzWbP7SqVCnfffTdOnDjh+Tzeeeed0Ol0XkMvZs+eDavVipEjRwIALBYLfvzxR9x0000wGo2lPt8WiwUbN270quHS/aovBQUFePrpp9GkSROo1Wqo1WqYzWYUFhaW+Xfxtb8tOfaV8PVed7lc+PnnnwG4/y6RkZEYPHiw13Pq0KEDEhISPH+Xkse+9HffdtttUKuVT5O4+eabodfrvWocPHgwfv75Z0/X9+233474+HivrvsPPvgAcXFxGDp0qKLfc7n71pEjR0KWZa/JKjNnzoTJZFJcQwkhhOK2Je/jQFZDqNAklZYtW5aapHL06FE89dRTuOuuuxAZGVnmdiXjDpKTk30+dsm4Fn+z5LKzsy9rwLCSOsqSlZUFwD1j81L169cv9Qa5dBAq4B7MX1xc7Pl3ZmYmDhw44HP8ZsnYvp49e2LBggV4//33cc8998BqtaJ169Z4/vnncfvtt/usOZDtLq1Xp9MBgKdel8uFfv364dSpU3jxxRfRtm1bmEwmuFwudOvWzet5lbj0tcrMzIQQwiu0XaxRo0YA/n6tExISSrUp6zZf/G2flZWF5ORkZGZmYtGiReX+Dfzp27cvAHcIbNiwIex2O3r37o3MzEy8+uqrnvuuvvpqz4D4kvd6SYi/VMnkkJJ2TzzxBJ544glFNZb3t1SiZIc1Y8YMpKamom/fvgGF8xKTJ0/Ghg0bMGfOHIwfPx6jRo3C9u3bPa9DgwYNcPjw4YAe02AweA5EZ86cwTvvvIPZs2ejXbt2eOaZZ/xuW1BQgB49ekCv12PixIlo1qwZjEYjjh8/jptvvrnUa2Q0Gr0OPID79bRYLJ5/Z2VllfmeVvpeDeQ1CMY+soTS1/nxxx/Hhx9+iKeffhrp6emIioqCLMu47777ynzPlff+LPn8l/WaXnqb0n1oibL2374UFxeX+ttfuHABQgifx4GL64+OjsYNN9yAL7/8Eq+++ipUKhU+//xzdO3a1TM+OSsrCw6HAx988AE++OCDSn0Od9xxB3788Ue8+OKL6NKli2eJqoEDB5b5d/G1vyx5PiX8vddL2mZmZiInJwdardbvc/K1r1er1WUeQ33xVbvNZkNBQQEiIiKg0+nw4IMP4p133sHbb78Nu92OuXPn4vHHH/e8B8tzufvW1NRU9OnTB19//TUmT56M/Px8LF68GHfccQfCwsIUPUaJksxR8r7zp+R9HMgxoEIBsSzt2rXD8uXLsW/fvlJnzUqUDPI/ceIEUlJSymwTGxsLwJ3qL525U8JXuFDq4joCUfLGOH36dKlweerUKU/tgYiNjYXBYPA59f3ix7zxxhtx4403wmq1YuPGjZg0aRLuuOMOpKWloXv37j5/R0W3u9TOnTuxY8cOfP755xg+fLjndl8DpAGUOkMbGxsLSZKwbt26Mj+QJbeVvNZlDfI/c+aM4rUufW1/8e+IjY1Fu3btfJ59UvLhS05ORrNmzbBq1SqkpaWhc+fOiIyMRJ8+fTBmzBhs2rQJGzduxIQJEzzblPxt58+f7zd4lbR79tlnfU7WaN68ebk1VsSoUaPw2Wef4Y8//sCsWbMC3n737t146aWXcM8992Do0KFITU3F1Vdfjeeffx5TpkwBAPTv3x8ffPABNm7c6PMzfylZlr2+pF577bXo1KkTJkyYgDvvvNPn/gUAVq9ejVOnTuGnn37ynDUEgJycnICfX4mYmJgyB9UrnaQSyGsQjH1kCaWv83/+8x/cc889eP311722P3/+vM8TBv6UfDbLmnB06ec/kH0oUHqf5E9sbCyys7O9bisJv6dPny7VvmSywsW/c+TIkZg3bx5WrlyJBg0aYPPmzfjoo4+8Hq/k7KOv3rVLZ4sreQ65ublYvHgxxo8f7xXmrVZrqedUwtf+skmTJl63+fq7AN771ZiYGJ/r/pWEoYv39UlJSZ77HQ5HqWDqj6/atVqt15ne0aNH44033sCMGTNgsVjgcDjw0EMPKf49leHee+/FypUr8d///henTp2CzWbDvffeG/DjLFy4EJIkoWfPnuW2LfmbB5JTKi0gbt++HcDf4ass/fr1g0qlwkcffeQzmFx99dWIjIzE7t27K3WR44tdddVViIiIwLRp0zBs2DDFO4zevXsDcO8MLz7rs3nzZvz11194/vnnA65l0KBBeP311xETE6N4yQidTof09HRERkZi+fLl+P333xUFvYpuV6Lkdbo02H388ceKH2PQoEF44403cPLkyVLdRxfr1q0b9Ho9Zs2a5dWdsn79ehw9elRxQPzxxx+RmZnpOWA6nU588803aNy4sSfkDxo0CEuWLEHjxo39dj2V902xb9++mDt3LlJSUjzrATZr1gwNGjTASy+9BLvd7jnTCLhDgVqtxsGDB/12GTVv3hxNmzbFjh07Sh2Aq1r37t0xatQo5Obm4qabbgpoW4fDgeHDhyM2NhbvvfceAPff9fHHH8eUKVNwyy234Oqrr8Zjjz2GGTNmYMyYMaWWeAHc3SgLFizw+/t1Oh0+/PBDZGRkYOLEiX7fk5XxPr5Ur169MHfuXCxcuNCrC6qs2YplCeQ1CMY+0hdfr7MkSaVezx9++AEnT54sFS6UuPLKK6HT6fDNN994fSnauHFjqc9/RfahSrVo0QIHDx70us1kMuHKK6/Ed999h8mTJ3vOhLtcLvznP//xfFks0a9fPyQlJWHmzJmeGbYX994YjUb06tULv//+O9q1a+fzjFugJEmCEKLU3+Wzzz4rNdu4hK/97X333efVLj8/v8z3uizLnrAyaNAgzJkzB06nE1deeaXPOktmpM+aNctrhYe5c+d6VpFQ4rvvvsPbb7/tOVOWn5+PRYsWoUePHlCpVJ52iYmJuPXWWzF16lTYbDYMHjwYDRo0UPx7lLi0p/BS//jHPxATE4MZM2bg9OnTaNasmWfokVIzZ87E0qVLcccddyiqv2Q2eqtWrRT/jgoFxJ07d3r+cFlZWfjuu++wcuVK3HTTTX4/oGlpaXjuuefw6quvori4GLfffjsiIiKwe/dunD9/HhMmTIDZbMYHH3yA4cOHIzs7G0OGDEF8fDzOnTuHHTt24Ny5c17fvirCbDbjnXfewX333Ye+ffvi/vvvR7169XDgwAHs2LHD51jK5s2b44EHHvCMp7ruuutw5MgRvPjii0hJScFjjz0WcC3/93//h2+//RY9e/bEY489hnbt2sHlcuHYsWNYsWIFxo0bhyuvvBIvvfQSTpw4gT59+iA5ORk5OTl47733vMZOlaWi25WlRYsWaNy4MZ555hkIIRAdHY1FixZ5LYVSnquvvhoPPPAARo4ciS1btqBnz54wmUw4ffo0fvnlF7Rt2xajR49GVFQUnnjiCUycOBH33Xcfbr31Vhw/fhwvv/xyQF3MsbGx6N27N1588UWYTCZMnToVe/bs8Vrq5pVXXsHKlStx1VVXYezYsWjevDksFguOHDmCJUuWYNq0aUhOTkZYWBhSU1Px3//+F3369EF0dDRiY2M9B6s+ffpg6tSpOH/+vGeNv5LbZ86ciaioKK8dYFpaGl555RU8//zzOHTokGc90czMTPz2228wmUyeM44ff/wxrrvuOvTv3x8jRoxAUlISsrOz8ddff2Hbtm1eS+xUtrKW6VBi0qRJ2LJlC5YuXep1FunVV1/FokWLPF3NDRs2xJw5czB06FB06NABjzzyCDp27AjAfQZyxowZEEKUG1DT09MxcOBAzJw5E88884zPfdFVV12FqKgoPPTQQxg/fjw0Gg1mzZp1WWMj77nnHvzrX//CPffcg9deew1NmzbFkiVLsHz5ckXbB/IaBGMf6U9Zr/OgQYPw+eefo0WLFmjXrh22bt2Kt99+O+BhPCWio6Px+OOPY9KkSYiKisJNN92EEydOYMKECUhMTPRam1PpPrQiMjIy8Morr5Raw3XSpEm49tpr0atXLzzxxBPQarWYOnUqdu7cidmzZ3uddFCpVLjnnnswZcoUhIeH4+abby71BeC9997DNddcgx49emD06NFIS0tDfn4+Dhw4gEWLFmH16tUB1x4eHo6ePXvi7bff9uyn1q5di+nTp/s8q7tlyxav/e3zzz+PpKQkjBkzxqtdTEwMRo8ejWPHjqFZs2ZYsmQJPv30U4wePdoTVoYNG4ZZs2Zh4MCB+Oc//4muXbtCo9HgxIkTWLNmDW688UbcdNNNaNmyJe666y68++670Gg06Nu3L3bu3InJkycjPDxc8fNVqVS49tpr8fjjj8PlcuHNN99EXl6eV69NiX/+85+e90RZFwS4XG3btsWcOXPwzTffoFGjRtDr9Wjbtq3nfp1OhzvvvBMffPABhBB+r9JTXFzsGYNaXFyMQ4cOYcGCBVi8eDHS09PLXLqmrJNeGzduRExMjFcd5VI8nUWUPYs5IiJCdOjQQUyZMkVYLBZFj/Pll1+KLl26CL1eL8xms+jYsWOpWX5r164V119/vYiOjhYajUYkJSWJ66+/3mt5ksuZoSeEEEuWLBHp6enCZDIJo9EoWrVq5TUbqKxlbpxOp3jzzTdFs2bNhEajEbGxseKuu+4Sx48f92rna/ZRWfUVFBSIF154QTRv3lxotVrPcgePPfaYZwbu4sWLxXXXXSeSkpKEVqsV8fHxYuDAgWLdunV+n6OS7Upmv1382gpR9szU3bt3i2uvvVaEhYWJqKgoceutt4pjx46Vmt178WzYssyYMUNceeWVwmQyCYPBIBo3bizuuecesWXLFk8bl8slJk2aJFJSUoRWqxXt2rUTixYtEunp6YpnMT/88MNi6tSponHjxkKj0YgWLVqIWbNmlWp77tw5MXbsWNGwYUOh0WhEdHS06NSpk3j++edFQUGBp92qVatEx44dhU6nKzXD7sKFC0KWZWEymbyW/CmZjXfzzTeXWeeCBQtEr169RHh4uNDpdCI1NVUMGTLEa7kSIYTYsWOHZ3kMjUYjEhISRO/evcW0adM8bUo+E5fO6FQyw1GI8v9uJcqbxbx9+3ah0WjE/fffX+b2GzZsELIse81cPHjwoBgzZoxo0qSJ0Ol0wmAwiFatWonHH3+81Ge8rOVXhBDizz//FLIsi5EjR/qtf/369aJ79+7CaDSKuLg4cd9994lt27aVer/7+l1l7RtOnDghbrnlFmE2m0VYWJi45ZZbxPr16xXNYg70NRCi6veRgbzOFy5cEPfee6+Ij48XRqNRXHPNNWLdunWlPquB7GtcLpeYOHGiSE5O9nz+Fy9eLNq3b19qtq2SfagQf+8TlDpw4ICQJKnULHYhhFi3bp3o3bu3Zx/WrVs3sWjRojIfZ9++fZ5j5sqVK8tsc/jwYTFq1CiRlJQkNBqNiIuLE1dddZXXDGJfr9/F9138GS95T0ZFRYmwsDAxYMAAsXPnTpGamur1+S15n6xYsULcfffdIjIyUhgMBjFw4ECxf/9+r99Tcmz76aefROfOnYVOpxOJiYniueeeK7XKgt1uF5MnTxbt27f3HO9btGghHnzwQa/HtVqtYty4cSI+Pt4zo3/Dhg2l6vT1uuF/M3knTJjgeb907NhRLF++3Od2aWlpomXLln4f+2KB7FuPHDki+vXrJ8LCwgT+t9zbpXbs2CEACJVKJU6dOlXm7yyZMV7yYzKZRKNGjcSQIUPEvHnzPKtXXCwuLk7ccsstXre5XC6RmppaasWM8khCBDANhoiIqJocPnwYLVq0wPjx4/Hcc88F5XeWzMKtyCL9oeLzzz/HyJEjsXnzZq8xp2XJyMjA+fPnsXPnziBVV/n++OMPtG/fHh9++GGps6OhLCsrC/Hx8Rg3bhzeeustz+0//vgj+vXrh127dqFFixaKH6/SxiASERFVlh07dmD27Nm46qqrEB4ejr179+Ktt95CeHh4hQb0V9SkSZPQsWNHbN682eeKAxQaDh48iKNHj+K5555DYmJihZbtqonOnTuHbdu2eYbHDRs2zOv+iRMnYtSoUQGFQ4ABkYiIaiCTyYQtW7Zg+vTpyMnJQUREBDIyMvDaa69V2ixtJdq0aYOZM2cqnpFONderr76Kr776Ci1btsS8efO8xpWGsh9++AH3338/mjdvjq+//hpXXHGF574LFy4gPT29QmdK2cVMRERERF4qdCUVIiIiIqq9GBCJiIiIyAsDIhERERF5YUAkIiIiIi8MiERERETkhQGRiIiIiLwwIBIRERGRFwZEIiIiIvLCgEhEREREXhgQiYiIiMgLAyIREREReWFAJCIiIiIvDIhERERE5IUBkYiIiIi8MCASERERkRcGRCIiIiLywoBIRERERF4YEImIiIjICwMiEREREXlhQCQiIiIiLwyIREREROSFAZGIiIiIvDAgEhEREZEXBkQiIiIi8sKASEREREReGBCJiIiIyAsDIhERERF5YUAkIiIiIi8MiERERETkhQGRiIiIiLwwIBIRERGRFwZEIiIiIvLCgEhEREREXhgQiYiIiMgLAyIREREReWFAJCIiIiIvDIhERERE5IUBkYiIiIi8MCASERERkRcGRCIiIiLywoBIRERERF4YEImIiIjICwMiEREREXlhQCQiIiIiLwyIREREROSFAZGIiIiIvDAgEhEREZEXBkQiIiIi8sKASEREREReGBCJiIiIyAsDIhERERF5YUAkIiIiIi8MiERERETkhQGRiIiIiLwwIBIRERGRFwZEIiIiIvLCgEhEREREXhgQiYiIiMgLAyIREREReWFAJCIiIiIv6uougIioyjgcgMXi/rFavf+/5MfhAFwu3z9CALIMqNXuH5Xq7/8u+bdGAxiNgMHg/in5b42mul8BIqIKYUAkotDlcgEFBUBeHpCf7/65+L8tlkr/lUIChCxByBIgSe5/S4AkSZBcAnAJSE4B2SXcAbIkMIaFARER3j9abaXXR0RUGSQhhKjuIoiIylVQAGRluX/Onweys90h8DJ2YU6NDIdBDYdWBZcacKkkOFWASxZwSgIuyeX+gQsuOAFIAT2+BECCDOl//1MJGbJLgsolQRYyVGodVAYzZGMYVOYIqM1RkKNjAb2+ws+JiKgyMCASUc2TmwucPesOgiWh0Gqt0EM5DGrYjGo4tDIcGsChcsEhu+CEAy64KrnwyydDhlpvhjosGrI5CjBFQjZHwayPgEbFLmsiCg4GRCKqXkK4A+Dp08CZM+6f4uKAH8YlS7CbNbAZVbBrAZvaBbtkr5EhsCKsWi3sBhOEKRwOYxiM5lgkmBMQrguv7tKIqBZiQCSi4MvJAU6cAE6dcgfDCpwdtBvUsIZrYNEDNrUDdtgrv84azKbRIEenQa5eC8kcjXphCUgwJyDGEANJCqwrnIjoUgyIRFT1hHCfGTx6FDhyxD2RJJDNAdjNWljMKlj1gFVlgxPOKik1FLlkGfl6Hc6qBc6qBSJM7rOLCeYExJvi2TVNRAFjQCSiqmG3A8ePu0PhsWMBnyV06lQojtSi2ChgkW21pqs4GIp1OmRpVTgl25ErOxFtiEaCOQFJYUlIDk+GSlZVd4lEVMMxIBJR5XE4gMOHgQMH3N3HzsDO8lnDtSgOV6NY54ANtioqsm5xqNXI0WlwWu3CKckKjaxBamQqGkU1Qkp4CsMiEZWJAZGILt+pU8C+fe5waA9sLKAlUoeicBlFGjuccFRRgQQAdo0amXotDqusKIITGlmDBhEN3GExIgVqmUvjEpEbAyIRVUxOjjsUHjjgXqMwADazBoVRGhRpbXAwFAafBOTp9TihBU7AAiEBalntCYsNIhowLBLVcQyIRKSc0wkcPAjs3u1epzAADr0ahdFaFBocsLP7uMZwqNQ4Z9TikMqGgv+FdbWsRkp4iicscpILUd3DgEhE5SsqcofCv/4KaI1CIQFFsQYUhLlgkSq20DUFT6FejxM6CcekYs+UII2sQfPY5mgT34ZrLhLVIQyIROTb2bPAzp3AoUPu6x4r5NCpUBCnQ4HOyuVoQpBTpcJ5gw771O6xigAgQUJKRAraxLdBcnhyNVdIRFWNAZGIvAnh7kbeuTPgbmRLpA75URKKZQu4Ywl9QpKQZdRjj9qGQunvoB+lj0Kb+DZoGtOUYxWJaikGRCJyEwLYvx/4/Xf3tZCVbiZLKIjXI99U965mUlcISUK2UY89GrtnnCIA6FQ6tIhtgdbxrWHWmquxQiKqbAyIRHVdSTDcti2gK5y4ZAkF9QzIM7Ibuc6QgCyjoVRQlCAhLTINbeLbIDEssRoLJKLKwoBIVFdVNBiqZeTX0yNfz2BYZ0lAttGAPWo78iXvZYpiDDG4IvEKNIxqWE3FEVFlYEAkqov27we2bg0oGDo1/wuGOgsve0duEpBt0GOv1oG8S9azjDfFo1tyNySYE6qpOCK6HAyIRHXJmTPAhg3AuXOKN3HJEvITDcjTMxiSbxdMBuzU2Dyznks0iGiAK5OuRJQhqpoqI6KKYEAkqgvy84FNm9zL1SgkABTWMyDHbGNXMinikmWcMOmxRy6CkP6+XYKEZjHN0Ll+Z5i0puorkIgUY0Akqs3sdves5D//dF8FRaGiaB1yolyclUwVYtVqscco4Qy8F0dXy2q0iW+DDgkdoFVpq6k6IlKCAZGoNhLCfZ3kzZvdV0FRyBquRU6sxKueUKW4YDLgD40VlkuGJuhUOnRM7IjWca2hklXVVB0R+cOASFTb5OQAa9cCmZmKN3FqZOTU16FArfwyekRKuGQZx8w67JOKvbqdAcCsNaNL/S5oEt0EkiSV/QBEVC0YEIlqC5cL2L7d3aUcQHdyQbwBOWEcZ0hVy6LVYrcBOCfZSt1Xz1QPGWkZiNBHVENlRFQWBkSi2uDcOfdZw+xsxZvYjRpkJ8jsTqagyjIZ8KfaCqvk3e2sltXoXL8z2sa35dlEohqAAZEolDkcwJYt7kkoCj/KQpaQW9+APF0xBK+YTNXAqVLhgFmLI1LpIQ31TPWQnpaOSH1k8AsjIg8GRKJQdfq0+6xhAItdWyN0yIrl7GSqGbKMBmzXWuC45IuKSlKhc/3OaFevHc8mElUTBkSiUONyua+Csn278rOGEpCbZESuTvmMZqJgsGk02GECssv40hJvikdGWgbPJhJVAwZEolBSUAD8+GNAM5TtRg3OJ0qwofTkAKKaQEgSjobpsVcu3eWsklToVL8T2tdrz7OJREHEgEgUKg4dAn7+GbApD3p5iUbkGDnWkEJDnkGPbVpbqQksgPtsYnpqOi/ZRxQkDIhENZ3DAaxfD+zZo3gTp06F8/U1sMiWKiyMqPI51GrsMqtKXYUF+PtsYoeEDsEvjKiOYUAkqsmys4FVq9yLXytUHKVHVrSd6xpSSDsdZsSfl1zTuURaZBp6pfWCRqUJfmFEdQQDIlFNdfCge5ayw6F4k9wkI3L0nIhCtUORTodtegcKpdJfdiL1kejXuB8nsBBVEQZEoppGCOC334AdOxRv4lLLOJ+iRTG7lKmWcckydoZpcLqMBd21Ki16N+yNBhENqqEyotqNAZGoJrHZ3F3KJ04o38Ssxbl6Ljig/EwjUUiRgP3hBhwqY2FtAOhcvzOuSLwiyEUR1W4MiEQ1RW4usHx5QOMNC+INyA6zcJYy1Qmnwoz4U1X2EAqOSySqXAyIRDXByZPuM4dWZddFFgAuNDAiX8PxhlS3ZBsN2KotRumFcNzjEvs37o8IfUTQ6yKqbRgQiarb3r3AunXuK6Qo4FJJON9Ax/GGVGcV6vX4TW+DrYyYyHGJRJWDAZGoOm3f7p6QopBDp8K5ZBWvikJ1nlWrxRajCwU+xt5yXCLR5WFAJKouGzcCf/yhuLnNrMHZegJOTkYhAgA4VSpsD1PhvI8vTI2iGqF3w96QJTnIlRGFPgZEomBzudzrG+7fr3gTS6QO52LscJU58oqo7hKyjL/CtDgulT3kokFEA1zb6FqoZFWQKyMKbQyIRMHkcLgnoxw7pniTwjgDssKLOU+ZyI8j4QbslcteBicpLAn9m/SHWlYHuSqi0MWASBQsViuwbBmQmal4k4J6BmSZyz7oEZG34+FG7JbLntmfYE7AdU2u4zI4RAoxIBIFg8UCLF7svrayQvkJBmSbGA6JAnE03Ig9PkJinDEOA5sOhE6tC3JVRKGHI3eJqprVCixZElA4zEs0MhwSVUBqXhGauQxl3neu6BwW71sMi4NLRBGVh2cQiaqSzQb88ANw7pziTXKTjMjRcwFsostxMMKAAz4uzRepj8SgZoNg1BiDXBVR6GBAJKoqdrs7HJ49q3iTnGQjcnUMh0SVYX+E7+s3h+vCMajZIJi15iBXRRQa2MVMVBXsdmDpUoZDomrUNK8YaUJf5n151jws3LsQeda8IFdFFBoYEIkqm8Phnq185oziTfLqMxwSVToBNM+zIMVHSCywFWDh3oW4UHwhyIUR1XwMiESVyeUCVqwATp9WvElBPQMuGBgOiaqEAFrmWZHkIyQW2Yvww/4fUGArCHJhRDUbAyJRZfr5Z+DECcXNi2L1XOeQqIpJQqB1vhX1RdnL2xTZi7Bk/xLObia6CAMiUWXZsgXYt09x8+IoHc5H8IBEFAySS6BNvg31fITEHEsOlh1YBoeL1zonAhgQiSrHnj3Atm2Km1vDtTgXbePl84iCSHIJtC1wIEyUfcm9s4VnserQKnBxDyIGRKLLd/w48MsvipvbjRqcjXNAMB4SBZ3K6UTnIglaH4e/Y7nHsO7YuiBXRVTzMCASXY7z54FVq9yTUxRwamScTRRwQVl7Iqp8WrsdXSxaSD6+o+05vwfbTivvESCqjRgQiSqqoMC9nI3drqi5kIDzKRo4wDFORNXNbLGgo9P3lVS2nNqCQxcOBbEiopqFAZGoIpxOYOVKoEj58jTZDQywSNYqLIqIAhFX4Pu6zQDw05GfcLZQ+WL3RLUJAyJRRfz6a0DXV85LNKJAzeVsiGqahvnFSEDZM5sdLgdWHFzBNRKpTmJAJArUnj3uH4WKo/S4YORC2EQ1kgDa5DtghKrMu4vsRVh+YDnsTmVDSYhqCwZEokCcO+c+e6iQ3ajB+WhbFRZERJdL5XSic7Ha5wExqzgLa46sCWpNRNWNAZFIKYvFPe7Q6VTU3CVLOJcIzlgmCgEGqxVX2H2PRzyScwQ7z+4MYkVE1YsBkUgJIYAff3TPXFboQooedrBbiihUxBQWo6mfSSubTmxCdnF2ECsiqj4MiERKbNkCnDypuHlBvIGTUohCUMN8CyKhKfM+p3Bi1aFVvBwf1QkMiETlOX0a2L5dcXO7UYMLYVzOhigUSUKgfZHk8+CYY8nBhuMbgloTUXVgQCTyx2YD1qxxdzErIGQJ5xIljjskCmF6mw2t/Syi/df5v3Ak50jwCiKqBgyIRP78+mtA4w6zU/Swg7OWiUJd/YIixELr8/61R9ai0FYYxIqIgosBkciXQ4eA/fsVNy+M5bhDolpDAG2KfB8krU4rVh9eDaGwd4Eo1DAgEpWlqAhYt05xc6dWhQsRPHNIVJvobDa0c/juaj5dcBq/n/k9iBURBQ8DIlFZfvoJsCqfaJKdpIETytZHJKLQUa+gCPVE2ZfiA4Btp7chsyAziBURBQcDItGldu0CTpxQ3LwwzoAi2VKFBRFRdWpd5IIaUpn3uYQLqw+vhs3JHgSqXRgQiS5WWAj89pvi5k6tChfCeWAgqs00djva2/U+78+35eOXY78EsSKiqseASHSxX38F7MqvfsKuZaK6IbawGPX9dDUfyD6A47nHg1gRUdViQCQqcfQocOSI4ubsWiaqW1oWOqH1c9hcf3w9XIJroFLtwIBIBAAOh/vsoUJOtcSuZaI6Ru1woJ3d91nEXGsu/sj8I4gVEVUdBkQiANi6NaAFsXPr69m1TFQHxRQWI0qUfa1mwD2rmQtoU23AgEiUnQ38+afi5rYwLfI1XBCbqK5qafV96HS4HNh4YmMQqyGqGgyIROvWAS7l44ay48pe7oKI6oYwixVJwves5oMXDuJU/qkgVkRU+RgQqW7bvx/IVL7IbUGcHlZJ+QLaRFQ7NS12QfJzlT1OWKFQx4BIdZfTCWzerLi5Sy0jJ1z5EjhEVHvpbDY08XMWMbs4G7vO7gpiRUSViwGR6q5duwKbmJLIiSlE9LfUQjs0wveQk62nt6LYzvHKFJoYEKluslqB339X3Nxu1CBfW1SFBRFRqFE5nWjl9H0W0ea0YdPJTUGsiKjyMCBS3fT77+6QqFBOvBp+hhsRUR1Vr9ACM9Q+79+XtQ+ZBcrHORPVFAyIVPcUFLi7lxWymbUoUrGbiIhKk4RAa5vvgAgAvx5Xvgg/UU3BgEh1z+bN7gkqCuXE8WNCRL5FFlkQD63P+88XnceRnCPBK4ioEvDIR3VLdjZw4IDi5tYIHYp5vWUiKkeLYv/ro24/sz04hRBVEgZEqlu2bgWE8tGEOTFVWAsR1RoGqxX1Xb6v03y28CxO5p0MYkVEl4cBkeqOCxeAw4cVNy+O0sPCRbGJSKFGNv9nEX8/o3zlBKLqxoBIdUcAy9oAQE4Ur4JARMqZLBbECN9jEU/ln+KMZgoZDIhUN+TmAgcPKm5eHKWHTbJVYUFEVBs1sav83s+ziBQqGBCpbtixI6Cxh3lRXPWQiAIXWVwMk/AdEo/lHkNWUVYQKyKqGAZEqv2KioD9+xU3t4ZrOfaQiCpGAM2cvierADyLSKGBAZFqv507A1r3MC+GHwsiqrjYIgu0fg6vhy8cRo4lJ3gFEVUAj4RUu9ntwO7dypsb1CjiuodEdBlklwtN/VyjWUBwXUSq8RgQqXY7cACwKZ9skh/newYiEZFSCUU2vwfYA9kHUGArCFo9RIFiQKTaLYCzhy61jEINzx4S0eVTOx1oJAw+73cJF3ac2RHEiogCw4BItdfZs0CW8tmCBXF6uMC1D4mociQX+x/7vDdrL2xOLqdFNRMDItVeAZw9BIACo72KCiGiukhnsyFJ+B6L6HA5cOjCoSBWRKQcAyLVTlZrQAtjWyJ0sIMBkYgqV4NyThDuy9oXnEKIAsSASLXT3r0BLW1TEMmPAhFVvnCLBTrhe/9ypuAM8qx5QayISBkeFal2+usvxU1dahlFak5OIaIqIIAGfq7PDAB7z+8NUjFEyjEgUu1z6pT72ssKFcbqIMBL6xFR1Uiw+t+/7M9WfqUnomBhQKTaJ4DL6gFAgUl5VzQRUaCMVivMUPu8v8BWgJN5J4NYEVH5GBCpdnG5gMOHFTe3hWlhA5eZIKKqler0383MySpU0zAgUu1y/HhAV04pjPT9rZ6IqLLEWR1+7z+ccxh2J1dSoJqDAZFqlwCWtgGAQi3PHhJR1dPZbIiGxuf9XBORahoGRKo9HA7gyBHFza0ROjjh/1s9EVFlaeDwHRAB95VViGoKBkSqPY4edYdEhYrCVVVYDBGRtxiL/x4LrolINQkDItUeAXYvF7F7mYiCSO1wIFHo/LbhZBWqKRgQqXaw2dwTVBSyhmvhYPcyEQVZssP/YffwBeWrMBBVJQZEqh1OnAjo0npFEZy9TETBF1ls9XvgvWC5gEJbYdDqIfKFAZFqhwDOHgLsXiai6iG7XIgrp5v5RN6JIFVD5BsDItUOAQREm0nD7mUiqjbxLv8T5I7nBfaFl6gqMCBS6MvKAoqKFDe3hLN7mYiqT6TN/3CYk3knIQSvD0/ViwGRQl+A3cvFelcVFUJEVD6jzQo1JJ/3W51WnCs6F8SKiEpjQKTQF0BAdMkSrDLHHxJRNRJAPY5DpBqOAZFCm80GZGYqbm6N0EKAXTdEVL3inP4PvwyIVN0YECm0nTwJuJR3GVvMfMsTUfWLtPmfKHe28CxsTvZ2UPXh0ZJC28mTATUv1nD2MhFVP53NBr2fQ7BLuHAq/1QQKyLyxoBIoS2A7mWnTgW7ZK/CYoiIlEvgOESqwRgQKXTZ7UB2tuLmlnBtFRZDRBSY2HI6NI7ncj1Eqj4MiBS6zp4FAlgrzKb3vawEEVGwhZczDjHflo9cS26QqiHyxoBIoSuA7mUAsGqUX6uZiKiqaex2mOF/4X6OQ6TqwoBIoSuAgCgkwCZxRiAR1SwJQuP3/qzirCBVQuSNAZFCVwAB0RbG9Q+JqOYJc/of+pJdrHycNVFlYkCk0HThgnuRbIVsRlUVFkNEVDEmh/91XBkQqbowIFJoCnT8oY5nD4mo5tHb/S+9ZXPakG/ND1I1RH9jQKTQFMDyNgBgVXOBbCKqeVROJ3TC/6GY4xCpOjAgUmi6cEFxU5dKggMMiERUM0XD/0QVdjNTdWBApNAUQEC0m/zvfImIqlNEeWcQi3gGkYKPAZFCj9UKFBUpbm7Xc4IKEdVcpnKWaGUXM1UHBkQKPQGcPQQAu45XUCGimqu8mcz51nw4XBwmQ8HFgEihJ9CAqPa/8yUiqk66cmYyCwiOQ6SgY0Ck0BNoQJT4zZuIai7Z5YJJ+B8Kw3GIFGwMiBR6AljiRsgSHAyIRFTDRZUzk5njECnYGBAp9OTmKm5qN6qrsBAiosoR4fJ/OGYXMwUbAyKFFiECmsHs0HEGMxHVfCaX/6s95VnzglQJkRsDIoWWoiJ3SFTIoeVbnIhqPq3T/37N4rAEqRIiNx49KbQUFATU3MkeZiIKAWqX/9UWXMLFkEhBxYBIoaWwMKDmTpXys41ERNVF5Sx/Ml2xvTgIlRC5MSBSaAn0DKLMNRCJqOZTO12Qyvk+W+xgQKTgYUCk0BLgGUSHVM41rIiIagid5P+QXGRXPkGP6HIxIFJoCbSLGQyIRBQaDOUsls0uZgomBkQKLQF0MTs1MgQ4BpGIQoOhnEMyu5gpmBgQKbRYrYqbOrVcA5GIQodWSH7v5xlECiYGRAotNpvipi6V/50tEVFNoi8vIPIMIgURAyKFFrtdcVOh5tubiEKHFv4DIiepUDDxCEqhw+UCHOWvFeZpLvMMIhGFDm05l9tjFzMFEwMihY4Azh4CQDkTAomIahRNeQGRXcwURAyIFDoCGH8I8AwiEYWW8gKiS7hgdSifqEd0ORgQKXQEHBC5xA0RhQ5ZlL/PcriUD7MhuhySEArekUQ1wZkzwMKFmLR0KZ5bsAD/7N0b7w4dCgAosFjwzPffY8H27cgqLERaTAzuu6U/htx0VTUXTaHA4XTi3S8WYcHq33AuOw/x0REY0r87Hr1zIGTZ/T26sNiCNz/7Hit+3Y4LeYVITojBiH/0xt03pHsex2qz4/WP52Phms2w2Oy4umMLvDr2DiTGRVXXU6Ma7sOvl2L5L7/j4PEz0Om0SGnfCDc/ejMS0hI8bSxFFnz/wffYvnY7LHkWpKWlYezYsRg9enQ1Vk61nbq6CyBSzG7H5iNH8Mm6dWiXnOx112Pz5mHN3r34z6hRSIuJwYrduzHmo68QHm9Ev6s7VE+9FDKmzVmOWYt/xjtPjUTTtET8ue8onnz7C4SZDBh1cx8AwKtT52HDjr341zOjkJwQg3VbduPF92ejXkyE5z32ytS5+HHjH/jg+fsRGW7Cax/Px6gX/o3FU5+HSsUOGypt0x/7cPeNGWjfPA0WScLzM7/Fe4+8h5fnvQydQQcAmDdlHvZu2YtRr4zCiIwR2LB2A8aMGYP69evjxhtvrOZnQLUV91gUMgry83Hn9On49O67EWU0et234dAhDO/eHRnNmyMtNhYP9OyJ1o0a4M99R6upWgol23YfwrVXdUDvbm2RkhCLgT07oUenVl7vn21/HcIt/bqje4fmSEmIxR2DeqJl42RPm7yCYsxd9iuef3AIrunUEm2aNsC7z4zC3sMn8cu2v6rrqVEN9+Ub/8St/a9Cs7T6aNk4BcPHD0f2mWwc/evv996hPw6h+6DuaN65OVJSU/DAAw+gffv22LJlSzVWTrUdAyKFjIdffBHXt22Lvi1blrrvmiZNsHDHDpy8cAFCCKzZuxcHT55Bz86tq6FSCjWd2zTBr7/vwaETmQCA3QePY8vOA8jo2sarzar1O3DmvPs9tn77Xhw+kel5j+3cfxR2hxM9O7fybFMvNhLN0pKwdffB4D4hCkkSgOIC90xlU7jJc3uTDk2w4+cduHD2ApwuJ9asWYN9+/ahf//+1VQp1QXsYqaQMGfOHGzbuRObx44t8/73hw7F/V99heRnnoFaliHLMv712L3o0rZJkCulUDR6WH/kFxajz8jxUMkSnC6BJ0beiBt7d/W0efnhoXhmylfoNuwZqFXu99gbj9/teY+dy86DVqNGRJjJ67HjosJwLjsvqM+HQpTLhXlT5qFJhyZIapLkuXnok0Px1cSv8MzAZ/CC+gXIsozPPvsM11xzTTUWS7UdAyLVeMePH8c///lPrJgxA/qTJ8ts8/7q1dh4+DAWjhmD1JgY/Lx/P5769xeIiDXgmk6lzzgSXWzRT1uw4MdNeO+5e9EstT52HzyOV6bORb3YSAzp1x0A8Pn3q7H9r8P47NUxSKoXg9/+2I8X3/8a8dERft9jQgCSxCWXqHwvv/c1Th44iSc/e9Lr9tVzVuPwn4cxZsoY3HbVbfhz858YM2YMEhMT0bdv32qqlmo7BkSq8bZu3YqzZ8+i0403uo+2AJwuF37evx///ukn5L77Lp5bsADfjx6N69u2BQC0S07GxpzT+GTeCgZEKtekT77F6GH9cUOvLgCAFo2ScDIzC1NnL8WQft1hsdrw9owF+Pjl0ejdzf0ea9koGbsPHve8x+Kiw2GzO5CbX+h1FvF8Tj6uaN2oWp4XhY7xH8zGqvU78PhnTyCq3t+z3m0WGxZ8uACjJ49G22vaonXL1ki/Mh3bt2/H5MmTGRCpyjAgUo3Xp08f/Pnnn8DJk8D69QCAkV98gRYJCXi6f384XS7YnU7Il5ylUckyuIoTKVFssUGSvIdky7IM8b+Fi+0OJ+wOJ6RLFl+XL3qPtWmaCo1ahXVb/8KgjM4AgLNZudh35CSevf/mIDwLCkVCCIz/9xws/2U7Zr37FA4mxXjd73Q44XQ4PWeh5f+9T1UqFVwuV9DrpbqDAZFqvLCwMLRp0wYICwOOumf2mXQ6xJhMaJPkHqeT3qwZnvz2Wxg0GqTGxGDtvn2Yu+oXPP/QrdVZOoWIPt3b4cOvlyApPhpN0xKx68BxTP92FW4d4F5HM8xkwJXtmmHSJ99Cr9UguV4MNv6xD9+t3IgX/vceCzcbcNuAq/Hax/MRFW5CRJgJr38yH80bJuGaK3gWm8r24vuz8d/Vv+HTV8bAZNQj93wuAMBgNkCr18JgNqDZFc3w7XvfQqPT4JjxGBZuWogvv/wSU6ZMqebqqTbjQtkUOo4dA5YtAwBkvPMOOiQnexbKPpObi2e//x4r/voL2YWFSI2Oxp039Mbdt6Vz/BeVq6DIgnc+/y9W/LId53PyUS8mAjf06oKxdw+CVuP+Hn02OxdvTf8e67b8hZz8QiTVi8Yd1/fAvbf09bzHLDY7Jn08H/9dvRkWm82zUHb9+OjqfHpUg6X1fbDM24ePH46rBru/oOSez8X3H36Pvzb+BUu+BampqXjggQfw2GOPcf9GVYYBkULHyZPADz8obp7dwIB8DS9uT0ShwaZRY43J/6X0hrUZhnBdeJAqorqM6yBS6NBoAmouCX6zJqJQUv4+S5Z42Kbg4DuNQodWG1Bz2cmT40QUOoSC7mIGRAoWvtModAR4BlHmBD8iCiEOBQFRqwrsizJRRTEgUugI8AyixIBIRCHErvJ/SNbIGqhlLj5CwcGASKFDowECmLHHLmYiCiW2cnZvRo0xOIUQgQGRQk0A3cwSAyIRhRBbOUdkg8YQnEKIwIBIoSaAbmbZxYBIRKGjvDOIBjUDIgUPAyKFlkACop2DEIkodFgl/19qeQaRgokBkUKLQfkOUm11VmEhRESVy1LOzDqOQaRgYkCk0GIyKW4quQRkvsWJKEQUC/9fatnFTMHEoyeFFrM5oOYqoaqiQoiIKlcxygmI7GKmIGJApNASwBlEAFAzIBJRCBCyBAeXuaEahAGRQkuAAVHl5PWYiajmc8rlf5llFzMFEwMihZYAu5jVDIhEFAIc5VxFBWAXMwUXAyKFlkDPIHKpGyIKAQ6Zl9mjmoUBkUKLTgeole8kVXYulk1ENV9xOWcQOf6Qgo0BkUJPWJjipppiroVIRDVfvuz/y2ykPjI4hRD9DwMihZ7ISMVN1RYH10IkohovV/b/ZTbGGBOkSojceOSk0BMVFVBzteC4HSKq2S4Iu9/7ow3RQaqEyI0BkUJPdGA7So2TayESUc3lUKthL+c6zDEGnkGk4GJApNAT4BlEjZ1L3RBRzVWs8d/LoZbVCNeFB6kaIjcGRAo9ERFAOUtCXExj5VI3RFRzFar8f4mNNkRDkvhFl4KLAZFCjyy7Q6JCmiJHFRZDRHR58ssZBcPxh1QdGBApNAXQzawudkACv30TUc2UI/n/Esvxh1QdGBApNAUQECUAWqGtulqIiCpKAnLgfwYzl7ih6sCASKEpNjag5jo73+pEVPNY1RqUN0qaXcxUHXjUpNBUr15AzbXFVVQHEdFlsJQzg9msNUOrYg8IBR8DIoUmvT6giSq6Av9dOERE1aGgnBnMHH9I1YUBkUJXAGcR1RYHVOCC2URUs1yQ/Xcwc/whVRcGRApdAXYz61yaKiqEiChwQpKQKVn9tokzxgWpGiJvDIgUugIdh2jl252Iao5inRYO+L7EnizJqB9WP4gVEf2NR0wKXVFRgFb54G1dkbMKiyEiCkyOxv+wl3hTPDQq9nxQ9WBApNAlSUB8vOLmujwbF8wmohrjrOz/S2tKeEqQKiEqjQGRQltCguKmkktA5+JyEURU/VyyjHPljD9MDk8OUjVEpTEgUmhLCewbtsHCtzwRVb9CndbvAtl6tR6xxsAuCEBUmXi0pNAWF+deE1EhfZ7/a54SEQVDtsb/4TcpLAmSxCExVH0YECn0JSvvhtEW2qGC/ysXEBFVtbOy/8X7UyI4/pCqFwMihb4GDQJqrncwIBJR9XGqVMiG/4DI8YdU3RgQKfQlJ7tnNCtkKKrCWoiIypGv8z9ZLtoQDaPGGKRqiMrGgEihT68HYpUP5tbn2KqwGCIi/7LL6cTg2UOqCRgQqXYIYDazyu6CXuiqsBgiIt9OlzP+kAGRagIGRKodAhyHaCziW5+Igs+q1aIAvldTUMtqJJoTg1gRUdl4lKTaIT4eMJsVNzdeYDczEQXfOZ3//uVEcyJUsv9L8BEFAwMi1R6NGiluqrI62c1MREF3RPZ/9ZSmMU2DVAmRfwyIVHs0bhxQc3YzE1EwFel1KJR8X39Zq9IiLTIteAUR+cEjJNUecXFAeLji5uxmJqJgOqP1f8htFNUIapnrtFLNwIBItUuTJoqbqqxO6NjNTERBICQJR8vpXm4W0yxI1RCVjwGRapcAu5lN7GYmoiDI1+tgg8vn/eG6cCSYE4JYEZF/PDpS7RIVBURHK25uzLJCgvKrsBARVcRp/xdP4dlDqnEYEKn2CaSb2e6C0amvwmKIqK5zyTKOg93LFFoYEKn2ado0oGszm3N8d/sQEV2uHIMOTkn4vL9+WH2YtcrXcSUKBgZEqn1MJiA1VXFzfY4VGmiqsCAiqstOqv1/CW0e0zxIlRApx4BItVPLlgE1NxUzIBJR5XOo1Djtp3tZI2vQMKphECsiUoYBkWqnlJSA1kQ0Z1k5VYWIKl2WQQvhZ+fCtQ+ppmJApNorgLOIKqsTBhcnqxBRJZKAA2r/C/JzcgrVVAyIVHs1bw7Iyt/i5pyqK4WI6p4cgwEFcPi8P0IXgcSwxCBWRKQcAyLVXno90KiR4uaGCxZOViGiSnNA4/u6ywDQPqF9kCohChwDItVurVoF1Dw8X1VFhRBRXVKg1yFL8t29bNaa2b1MNRoDItVuCQlAbKzi5qbzVqjAkEhEl+eIzv+0t3b12kGWeAimmovvTqr92ivvxpFcAmEWXRUWQ0S1nVWrxUnJ4vN+g9qAFrEtglgRUeAYEKn2a9QosCVvzlog86NBRBV0XO+/F6JtvbZc2oZqPB4FqfaTJKBdO8XNVXYXzDYueUNEgXOo1DgsF/u8X6vSolVcYGOjiaoDAyLVDc2bAwaD4uZhZ7lwNhEF7rRJC38X1msT3wZalTZo9RBVFAMi1Q0qVUBjEdVWJ8x25YGSiMglyzgg+x57qJbVaBPfJogVEVUcAyLVHa1auddGVCgi0waJ5xGJSKFzBh1sfs4ftoxtCb2aw1coNDAgUt2hVgNt2ypurrI6EWbjWUQiUkAC9vu5rJ4syVwYm0IKAyLVLW3aBDQWMfwMZzQTUfnOmowolHxfOaV5THMYNcYgVkR0eXjko7pFowE6dVLcXGV3cV1EIvLLqVJhl9r32EMJEs8eUshhQKS6p0ULICJCcfPwMxZeXYWIfDph1Pode9gqrhXCdcrXYiWqCRgQqe6RZaBrV+XNnQLhxTyLSESl2TQa7FP5XvdQr9ajc/3OQayIqHIwIFLd1LAhUK+e4uZhZ4qhBq98QETeDhhVftc97JrUFTo1v2BS6GFApLrryisVN5VcAlE5DIhE9LdCvR7H/VxzOd4Uz2suU8hiQKS6KyEBSEtT3NyYZYHexTXMiMhtt973rGUJEq5OuTqI1RBVLgZEqtu6dnWPSVQoOtPJpbOJCNkmA7Jh93l/89jmiDPFBbEiosrFgEh1W2Qk0K6d4uaaIjvCbFzLjKguE7KMXRrfi2LrVDp0TVI+EY6oJmJAJLriCiAsTHHziFPFXPaGqA47ZdShCL67lzvX78xL6lHIY0AkUquBa65R3Fx2CkTlaauwICKqqRxqNfb4WRQ7xhCDVnGtglgRUdVgQCQCgJQUoFEjxc1N54qhFzxDQFTXHDRp4IDwef/VDa6GJHGkMoU+BkSiEldd5b4Un0Ixpx28TjNRHZJrNOCI5HtR7KbRTZFgTghiRURVh0c3ohJGI9Cli+Lm6mIHIgu5AC5RXeBUqbBda/V5v1alxZXJytdWJarpGBCJLta6NRAbq7h52Bl2NRPVBfvMGlj8XDPl6pSrYdRwhQOqPRgQiS4mSUBGBqBSPkuZXc1EtdsFkwHH/FwxpWl0UzSNaRrEioiqHo9qRJeKjmZXMxEBcM9a3q7x3bUcrgvHNQ2Ur4JAFCoYEInK0q4dUL++4ubsaiaqnf4yqWDz0bUsSzJ6N+wNjUr55DaiUMGASORLRgagVb7eYcwpdjUT1SbnTQacknyfPexcvzPiTfFBrIgoeHg0I/LFbA5oAW21xYGYHC6gTVQb2DVq7ND4HndYP6w+2tdrH8SKiIKLAZHInyZNgMaNFTc3ZlkQbjNUYUFEFAy7jCqfC2Lr1Xr0btibC2JTrcaASFSeHj0Ak0lx88gTxdAJnkkkClVnzAZk+ulaTk9N55I2VOsxIBKVR6sF+vQBZGUfF0kAsaddHI9IFIKsWi12qnx3LbeKa4XUyNQgVkRUPXgEI1IiIQHo1k1xc3UxxyMShRqXLGOb0QWnVHbXcrQhGt2Tuwe5KqLqwYBIpFSbNu4xiQoZsywIs7MbiihU7A7TIg+OMu9TSSr0btgbKln5IvpEoYwBkSgQPXu6F9JWKOp4EfSCi2gT1XQnw4w46edqKT1SeyDaoPyzTxTqGBCJAqFWA/36KV4fURJA7HE71FBXcWFEVFF5Bj12qop83t8hoQOaxTQLYkVE1Y8BkShQ4eFAr16Km6vsLsSfljhphagGsmk02KL1PWO5YWRDdE3qGsSKiGoGHrGIKiI1FbjiCsXNNUV2xGZz0gpRTeKSZWw1Cdh9TEqJNcaiV0PlXwaJahMGRKKK6tw5oEW0DRcsiCripBWiGkECdoZpfE5KMWlMGNBkANQyh4dQ3cSASHQ5MjKAxETFzcNPF8Hs4JVWiKrboTADTvtYDFsja9C/SX8uhk11GgMi0eVQqdyTViIjFW8SfawYBpe+6moiIr/Omo3YLxeXeZ8sybi28bWINcYGuSqimoUBkehy6XTAddcBRmVnGyQBxB61Qsflb4iCLt+gx3Y/M5bTU9ORHJ4cxIqIaiYGRKLKEBYGDBjgXgZHAdklEH/MDi04cYUoWIp0Ovyms0JIZd9/ZdKVaBrTNLhFEdVQDIhElSU2FujbF5B8HH0uITtciD/uhAaaKi6MiIp1OmzU2+BA2TOW28a3RfuE9kGuiqjmYkAkqkwNGrivtqKQyuZE/EkBFRfSJqoyFq0WGw12n8vZNIlugu4pvMYy0cUYEIkqW/PmwDXXKG6utjhQ77QEFXiNV6LKZtVqsdHggA2uMu9vFtMMvdK41iHRpRgQiapCq1bA1Vcrbq4psiP+rIohkagS2TQabDQ6YJXKDoctY1siIy0DksJhIUR1CQMiUVVp3RrorrzbSptvQ3ymzJBIVAnsGg02mVyw+Dhz2Da+LXqk9ghyVUShQxJClD0og4gqx44dwKZNipvbjRpkJrrghLMKiyKqvewaNTYZBQqlsj9DHRM6oktSlyBXRRRaGBCJguH334HNmxU3txvUOFsfcPi4DBgRlc2hVmOTGSjw8dnpUr8LOiZ2DHJVRKGHXcxEwdCxo/vazQppih2odwpQc3YzkWJOlQqb/YTD7sndGQ6JFOIZRKJg2r0b+PVXQOHHzqFT4WyyDDvsVVwYUWhzqlTYEiYjx8dnpUeDHmgZ1zLIVRGFLgZEomA7dAhYvRpwlT14/lJOrQpnk1WwSbYqLowoNFm1Wmw2OMsccyhBQnpaOprFNKuGyohCFwMiUXU4eRJYsQKwKzsz6JIlnE/VoVi2VHFhRKGlUK/Hb3pbmescypKM3g17o1FUo2qojCi0MSASVZfz54ElSwCLstAnAGSnGlCgLq7auohCRLbJgK2a4jIXstGqtOjTsA9SIlKCXhdRbcCASFSdcnPdITE/X/EmeYkGXDAyJFLddjLMiJ2qojLvi9JHoV/jfojQRwS5KqLagwGRqLoVFQHLlrnPKCrdJFaP8xFWCPDjS3WLAHAgwoBDUtlfktIi09ArrRc0Kk1wCyOqZRgQiWoChwP46Sf3BBaFrOFanI9zca1EqjNcsoydYRqclqyl7pMgoVP9Trgi8YpqqIyo9mFAJKpJtmwBtm1T3NypkXE+RQuLxMkrVLvZNWpsM0llLmOjVWnRu2FvNIhoUA2VEdVODIhENc2hQ+6ziQ5lZwYFgJwUI/K0ZY/HIgp1Fp0WmwyOMq+rHKmPRP/G/TnekKiSMSAS1UTZ2e5lcPLyFG9SFKNHVqQNrjLndBKFphyjAVu1FjjKGG/L8YZEVYcBkaimslqBH38ETpxQvIndoMa5+jLs4KLaFNqELOOgWYeDctmTUTrX78zxhkRViAGRqCYTAti+Hdi6VfGVV1yyhOwUPQq5XiKFKKtWi98NArkSxxsSVRcGRKJQcPas+2xiAOslFsXqkR1hhxOlLz9GVFOdNRuxQ11U5kCJ5PBk9EztCbPWHPS6iOoaBkSiUGGzAevWAQcPKt7EqVMhq76Gl+ijGs+pUmGPWYMTZczI16q06JbcDS1iW1RDZUR1EwMiUajZuxf49VfFs5wBID/BgAsmCxfWphqpUK/HNr0dRWWc7eZZQ6LqwYBIFIpyctxdzllZijexGzU4nyDBJnECC9UQEnDCbMSuMi6Zx7OGRNWLAZEoVLlcwO+/u38UTmAREpCXaESuoZhnE6laOdRq/GmWcbaMGfcp4SnomdoTJq2pGiojIoABkSj0XbgArF3rnsiikN2gRnaCGhaOTaRqkGUy4A+NFbZLpqJoVVp0T+6O5rHNq6kyIirBgEhUGwgB7NoF/PZbQGMTC+MMuBBu40xnCgqLTotdBuB8GWcNG0Q0QI8GPXjWkKiGYEAkqk3y890znQNYXNullpFTX4d8DddNpKrhkmUcNeuwXyqGkLzvM6gNuDL5SjSLaVY9xRFRmRgQiWqjffuAjRsBi/IuZGu4Ftmx4CQWqlTZJgP+1FhLXUdZI2vQrl47tKvXjpfKI6qBGBCJaiubDdi2Ddi5U/EkFsDd7ZwTbocDyruqiS5l1Wrxl0FCpmT1ul2WZLSIbYFOiZ1g0BiqqToiKg8DIlFtl5sLbNoEHDmieBMhAfkJRuQaLXCVeU0LorK5ZBnHzXrslYpKdSc3imqELvW7IEIfUT3FEZFiDIhEdcWpU8D69UB2tuJNXGoZuYl65Gu5LA6VL8dowJ9aW6kFrxPNibgy+UrEm+KrqTIiChQDIlFdIgSwZw+wZQtQrHxSikOvRk49DYrUxYyJVEqhXo/9OlGqOznaEI2uSV3RIKJBNVVGRBXFgEhUF9nt7mVx/vgjoIksDoMaeXEaFGh42T4CCgx67Ne5Si12bdaa0SmxE5rFNIMkST62JqKajAGRqC6rYFB06lTIi9ex67mOytfrsF8ncO6SGe9R+ii0iW+DZjHNoJJV1VQdEVUGBkQici+uvXNn4EFRIyO/nh75Ok5mqQvy/nfG8NKFrhtENECb+DZIDk+upsqIqLIxIBLR3xwO9xnFHTsCCooutYyCOD0KjHbYYa/CAqk65Bn02Kd1IeuiM4YaWYPmsc3RJr4NwnXh1VgdEVUFBkQiKs3pBA4ccJ9VzMoKaNPiKB0KIiUU8TrPIS/XaMA+rQPZF4X+cF042sS3QfOY5lzgmqgWY0AkIv9On3YHxSNH3LOgFXLo1SiI1aJAZ+W1nkOIU6XCeYMOh9Q25F20WHpyeDLaxLdBSngKJ54Q1QEMiESkTEGBu/t5zx7Aai2//f8ICSiKNaDQLGCRLZzSUkMVGPQ4oQWOS39fFE+v1qNRVCO0jmuNKENUtdZHRMHFgEhEgXE4gIMH3dd7Pn06oE2dGhlFMToUGl2wSspDJlUNh1qNswYtDqtsKPjf2UK9Wo+GkQ3RMKoh6ofVhyzJ1VwlEVUHBkQiqriCAndQ3L/ffUm/ANgNahRFa1Go58SWoJKAPL0ex7TAKVggJMCgNqBhVEM0imqERHMiu5CJiAGRiCrJ2bPusHjwYEBd0ABgM2tRHKFGkd4B2yVLqFDlsGs0yNRrcEi2olhywqgxes4UMhQS0aUYEImocrlcwPHj7kktx44FdEk/AHDoVCiO0qLYIGCRrVyI+zIU63TI0qpwSrbjgmSHUWNEo6hGaBTVCPVM9RgKicgnBkQiqjpCuM8sHjkCHD0K5OQEtrkswRKhhcWsglXjgE2yMS764ZJl5Ot1OKsWOCXboNWZkWBO8PxE6iOru0QiChEMiEQUPLm57qB49CiQmek+2xgAlyzBFl4SGJ2wyrY6f4bRptEgR6dBpsoFpykM8eYE1DPXQ4I5AUaNsbrLI6IQxYBIRNXD4QDOnAFOnXL/nDsX0DqLgHsJHVuYFlaTGjatgF3thB21+yyjkGUUabXI1WvhCIuCKSwOCeYExJvioZbV1V0eEdUSDIhEVDPY7e7u6NOn3cHx3Dn3bQESEmA3aWAzqGDXy7CpXbDL9pBdrNul0wOmSAhTJFzGMMjGCEQaIhGlj+IYQiKqMgyIRFQzCQHk5bkv9Xf+vPv/s7KAoqIKPZxLluDUq+HQq+DQSnBoJDjULjhkFxxwwIXAursri/y//6mEDLXeDFVYNDThMVCHx0A2R0GrM1VLXURUtzEgElFoKS7+Oyzm5gL5+e6fgoKAxzReTEiAS6OCUy3BpVHBpZbcPyoJThUgJAEhwT3mUZLc3diSewRkyU5UAiAJCZIQkCC5/9slIAlAFhJkhwsqSQ3ZEAaVMQyy0Qw5PBIIDwciIwGt9nJfHSKiSsGASES1gxDukFgSGPPy3P+2WgGL5e8fWxWus6jXA0YjYDC4fy7+77AwICLCfRsRUQ3HgEhEdYsQ3qHR4XCfefT3o1IBavXf/3/pf2s07nAo87J0RFQ7MCASERERkRd+3SUiIiIiLwyIREREROSFAZGIiIiIvDAgEhEREZEXBkQiIiIi8sKASEREREReGBCJiIiIyAsDIhERERF5YUAkIiIiIi8MiERERETkhQGRiIiIiLwwIBIRERGRFwZEIqJK9Mcff2DkyJFo2LAh9Ho9zGYzrrjiCrz11lvIzs4O+PFefvllSJLkdVtGRgYyMjLK3TYjIwOSJHl+9Ho9WrVqhYkTJ8JmswVcCxHVHerqLoCIqLb49NNPMWbMGDRv3hxPPvkkWrVqBbvdji1btmDatGnYsGEDvv/++6DW1KhRI8yaNQsAcO7cOXz22Wd48cUXcezYMXzyySdBrYWIQgfPIBJRpfr88889Z6x++umnUvcLIdCkSRNIkuR1FkySJLz88suef7/yyiuQJAnLly8v9RjffPMNJEnCv//9b89tmZmZeOaZZ9C2bVuYzWbo9Xo0bdoU//znP7F//35Pu5IzciU/Go0GDRo0wP33348zZ85U+Hlv2LABo0ePRt++fbF161aMGTMGGRkZuPbaa/Hss89iz549GDlyZIUfv6IMBgO6deuGbt26YfDgwfj222/RtGlTfPHFF7BYLEGvp7I5nU5YrdbqLoOo1mFAJKIqERYWhunTp5e6fe3atTh48CDCwsK8bt+wYQPuu+8+z7+fe+45dOrUCffddx9yc3M9t58+fRpjxoxBr1698PDDDwMAfvvtN7Rt2xbTp0/HkCFD8N1332HZsmV44oknsG3bNnTt2rVUHcuWLcOGDRuwdOlSDBs2DDNmzECfPn1gt9sr9Hxff/11SJKETz75BDqdrtT9Wq0WN9xwg9dt33zzDbp37w6TyQSz2Yz+/fvj999/r9DvV0qtVqNDhw6w2WzIycnx3L5lyxYMGzYMaWlpMBgMSEtLw+23346jR496bV/yBWDNmjUYPXo0YmNjERMTg5tvvhmnTp3yamu1WjFu3DgkJCTAaDSiZ8+e2Lp1K9LS0jBixAivtmfOnMGDDz6I5ORkaLVaNGzYEBMmTIDD4fC0OXLkCCRJwltvvYWJEyeiYcOG0Ol0WLNmTaW/TkR1HbuYiahKDB06FLNmzcKHH36I8PBwz+3Tp09H9+7dkZeX59W+W7duXv9Wq9X44osv0KlTJ4wdOxZffPEFAOC+++6D3W7HzJkzIUkS8vLycOONN0Kv12P9+vVITk72PEZGRgYefPBBzJ8/v1R9nTp1QmxsLACgb9++OH/+PGbOnIlffvkFvXr1Cui5Op1OrF69Gp06dUJKSoqibV5//XW88MILGDlyJF544QXYbDa8/fbb6NGjB3777Te0atUqoBoCcfjwYURGRiIuLs5z25EjR9C8eXMMGzYM0dHROH36ND766CN06dIFu3fv9rxWJe677z5cf/31+Prrr3H8+HE8+eSTuOuuu7B69WpPm5EjR+Kbb77BU089hd69e2P37t246aabSv3tz5w5g65du0KWZbz00kto3LgxNmzYgIkTJ+LIkSOYOXOmV/v3338fzZo1w+TJkxEeHo6mTZtWwatEVMcJIqJKNHPmTAFA/Pjjj8JgMIhp06Z57svJyREGg0F8+umnonXr1iI9Pd1zHwAxfvz4Uo/35ptvCgDiv//9r/jkk08EAPHpp5967p88ebIAIGbPnq2ovvHjxwsA4ty5c163f/jhhwE9zsXOnDkjAIhhw4Ypan/s2DGhVqvFo48+6nV7fn6+SEhIELfddlupei+Wnp7u9dr5kp6eLlq3bi3sdruw2+3i9OnT4qWXXhIAvP4uZXE4HKKgoECYTCbx3nvveW4v+fuOGTPGq/1bb70lAIjTp08LIYTYtWuXACCefvppr3azZ88WAMTw4cM9tz344IPCbDaLo0ePerUt+dvu2rVLCCHE4cOHBQDRuHFjYbPZyn3+RFRx7GImoioRHh6OIUOGYMaMGZ7bZs+eDVmWMXToUMWPM27cOHTv3h33338/Hn/8cVx33XVeXdErVqyASqXC4MGDL6vew4cPAwCaNWt2WY+jxPLly+FwOHDPPffA4XB4fvR6PdLT08scu1lRu3btgkajgUajQWJiIl555RU8++yzePDBB73aFRQU4Omnn0aTJk2gVquhVqthNptRWFiIv/76q9TjXtpd3q5dOwDwdEmvXbsWAHDbbbd5tRsyZAjUau/Oq8WLF6NXr16oX7++1+tx3XXXeT3Wxb9bo9EE+lIQUQDYxUxEVWbUqFHo1asXdu3ahdatW2PGjBm49dZbS40/9EelUuGdd97BVVddBZ1Oh88++8zr/mPHjiEuLg4mkymg2pxOJxwOBwoKCrBy5Up89NFHuP3223HFFVcE9DgAEBsbC6PR6AmZ5cnMzAQAdOnSpcz7Zbnyvrs3btwYc+bMgRACR48excSJEzFp0iS0a9cOw4YN87S744478OOPP+LFF19Ely5dEB4eDkmSMHDgQBQXF5d63JiYGK9/l4y7LGmblZUFAKhXr55XO7VaXWrbzMxMLFq0yGfoO3/+vNe/ExMTlTx1IroMDIhEVGXS09PRuHFjzJgxAyNGjMDmzZvxzjvvBPw47777LmRZhtVqxc8//+wVbCoqISHB6989e/b0jHMMlEqlQp8+fbB06VKcOHHCaxxkWUrG882fPx+pqakV+p1K6fV6dO7cGYA7kPbq1QutW7fG//3f/2HQoEEwm83Izc3F4sWLMX78eDzzzDOeba1Wa4XWbgT+DpCZmZlISkry3O5wODzhsURsbCzatWuH1157rczHql+/vte/L10XkogqH7uYiajKSJKEkSNH4j//+Q+mTZuGZs2aoUePHgE9xrx58zB37lxMmTIFGRkZeOSRRzxn4ACgQYMGOHfuHAoLCwN63FWrVmHz5s1Yvnw5brnlFvz888949NFHA3qMiz377LMQQuD+++8vcxFqu92ORYsWAQD69+8PtVqNgwcPonPnzmX+VJWYmBi88cYbyMzMxAcffADA/XcSQpSaff3ZZ5/B6XRW6Pf07NkTgHum9sXmz5/vNTMZAAYNGoSdO3eicePGZb4WlwZEIqp6PINIRFVqxIgReOmllzBt2jSfZ4h8yczM9KwnOHbsWNxwww1o27YtRo8eje+++w6AO2ytWLECixYtCujMYvv27T1n8q699lr0798fn3zyCe69916fXb/+dO/eHR999BHGjBmDTp06YfTo0WjdujXsdjt+//13fPLJJ2jTpg0GDx6MtLQ0vPLKK3j++edx6NAhDBgwAFFRUcjMzMRvv/0Gk8mECRMmBFyDUvfccw+mTJmCyZMn4+GHH0Z4eDh69uyJt99+G7GxsUhLS8PatWsxffp0REZGVuh3tG7dGrfffjveeecdqFQq9O7dG7t27cI777yDiIgIr270V155BStXrsRVV12FsWPHonnz5rBYLDhy5AiWLFmCadOmlXtWlogqF88gElGVSkpKwpNPPonBgwdj+PDhAW370EMPwWKxYMaMGZAkCQ0bNsSbb76J77//HnPmzAEA3HvvvUhISMBTTz2FkydPlvk4JWHSF0mS8OGHH0KlUuGFF14IqMaL3X///diyZQs6deqEN998E/369cM//vEPzJ49G3fccYfXlUueffZZzJ8/H/v27cPw4cPRv39/PPXUUzh69Kjn7FtVkWUZb7zxBrKzs/Huu+8CAL7++mv06tULTz31FG6++WZs2bIFK1euRERERIV/z8yZM/HPf/4T06dPx+DBgzFnzhzMnTsXALyCZ2JiIrZs2YJ+/frh7bffxoABA3D33XdjxowZ6NChA6Kioi7n6RJRRVTzLGoiqmVKlkHZvHmz33blLXPz5Zdflrkci8vlEhkZGSImJkacOXNGCCHEpk2bRFxcnIiLixMTJkwQK1asED/99JP49NNPRXp6uoiMjPRs72uZGyGEGDNmjAAg1q1bV4FnTkr8+uuvAoCYNWtWdZdCRH7wDCIR1TinTp3C2LFj0a9fv1LLsUiShBkzZsBisWD06NEAgK5du+LPP//EqFGjMHfuXPzjH/9A//798eabb6JFixZYt26dot87fvx4mM1mvPTSS5X+nOqilStX4pVXXsEPP/yA1atX41//+hduuukmNG3aFDfffHN1l0dEfkhCCFHdRRARUe2zadMmjBs3Drt370Z+fj5iY2PRv39/TJo0iUvVENVwDIhERERE5IVdzERERETkhQGRiIiIiLwwIBIRERGRFwZEIiIiIvLCgEhEREREXhgQiYiIiMgLAyIREREReWFAJCIiIiIvDIhERERE5IUBkYiIiIi8MCASERERkZf/B92qBhvYerrEAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cr_list = cr_vdj_b['ntVDJ'].tolist()\n",
    "mixcr_list = mixcr_vdj_b['ntVDJ'].tolist()\n",
    "venn2([set(mixcr_list), set(cr_list)], ('MiXCR', 'Cell Ranger'), )\n",
    "plt.gcf().suptitle(\"B cell clones shared between MiXCR and Cell Ranger (overlapped by ntVDJ)\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a55ab115-d81f-4033-8361-e3ee03886d69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cr_list = cr_vdj_t['ntVDJ'].tolist()\n",
    "mixcr_list = mixcr_vdj_t['ntVDJ'].tolist()\n",
    "venn2([set(mixcr_list), set(cr_list)], ('MiXCR', 'Cell Ranger'), )\n",
    "plt.gcf().suptitle(\"T cell clones shared between MiXCR and Cell Ranger (overlapped by ntVDJ)\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47fb2c58",
   "metadata": {},
   "source": [
    "## Dependence on sequencing depth (figure 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "20621772",
   "metadata": {},
   "outputs": [],
   "source": [
    "MiXCR_RESULT_PATH_TCELLS = 'downsampled_data/T_cells/mixcr'\n",
    "MiXCR_RESULT_PATH_BCELLS = 'downsampled_data/B_cells/mixcr'\n",
    "CR_RESULT_PATH_TCELLS = 'downsampled_data/T_cells/cellranger'\n",
    "CR_RESULT_PATH_BCELLS = 'downsampled_data/B_cells/cellranger'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "0045e1c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def process_data(path):\n",
    "    stats_list = []\n",
    "    software = path.split('/')[-1]\n",
    "    cell_type = path.split('/')[-2]\n",
    "    if software == 'mixcr':\n",
    "        delimeter = '\\t'\n",
    "        ext = '.tsv'\n",
    "        barcode_column = 'tagValueCELL'\n",
    "        chain_column = 'topChains'\n",
    "    else:\n",
    "        barcode_column = 'barcode'\n",
    "        chain_column = 'chain'\n",
    "        delimeter = ','\n",
    "        ext = '.csv'\n",
    "    if cell_type == 'T_cells':\n",
    "        chain = 'TRB'\n",
    "        file_prefix = '10k_PBMC_5pv2_nextgem_Chromium_Controller_vdj_t' \n",
    "    else:\n",
    "        chain = 'IGH'\n",
    "        file_prefix = '10k_PBMC_5pv2_nextgem_Chromium_Controller_vdj_b'\n",
    "    for files in glob.glob(path+f'/{file_prefix}_1_d*{ext}'):\n",
    "        perc = basename(files).split('.')[0].split('_')[-1]\n",
    "        if perc.endswith('pct'):\n",
    "            pct = int(perc[1:-3])\n",
    "        elif perc[1] == '0':\n",
    "            pct = int(perc[2:])*10\n",
    "        else:\n",
    "            pct = int(perc[1:])*10\n",
    "        table = pd.read_table(files, sep=delimeter)\n",
    "        grouped_table = table.groupby(barcode_column)[chain_column].apply(set).reset_index()\n",
    "        paired_cells = []\n",
    "        for index, row in grouped_table.iterrows():\n",
    "            chains = row[chain_column]\n",
    "            if chain in chains and len(chains)>1:\n",
    "                paired_cells.append(row[barcode_column])\n",
    "        stats_list.append([pct, len(grouped_table), len(paired_cells)])\n",
    "        stats_df = pd.DataFrame(stats_list, columns=['Downsampled to, %', 'Number of cells', 'Number of paired cells'])\n",
    "        stats_df.sort_values('Downsampled to, %', ascending=False, inplace=True, ignore_index=True)\n",
    "    return stats_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e111a501",
   "metadata": {},
   "outputs": [],
   "source": [
    "stat_table_mixcr_t = process_data(MiXCR_RESULT_PATH_TCELLS)\n",
    "stat_table_mixcr_b = process_data(MiXCR_RESULT_PATH_BCELLS)\n",
    "stat_table_cr_t = process_data(CR_RESULT_PATH_TCELLS)\n",
    "stat_table_cr_b = process_data(CR_RESULT_PATH_BCELLS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f5eee601",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>Downsampled to, %</th>\n",
       "      <th>Number of cells</th>\n",
       "      <th>Number of paired cells</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>471</td>\n",
       "      <td>448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>90</td>\n",
       "      <td>470</td>\n",
       "      <td>441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>80</td>\n",
       "      <td>470</td>\n",
       "      <td>441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>470</td>\n",
       "      <td>442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>60</td>\n",
       "      <td>471</td>\n",
       "      <td>430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50</td>\n",
       "      <td>467</td>\n",
       "      <td>428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>40</td>\n",
       "      <td>470</td>\n",
       "      <td>416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>30</td>\n",
       "      <td>465</td>\n",
       "      <td>404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20</td>\n",
       "      <td>459</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>447</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1</td>\n",
       "      <td>97</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Downsampled to, %  Number of cells  Number of paired cells\n",
       "0                 100              471                     448\n",
       "1                  90              470                     441\n",
       "2                  80              470                     441\n",
       "3                  70              470                     442\n",
       "4                  60              471                     430\n",
       "5                  50              467                     428\n",
       "6                  40              470                     416\n",
       "7                  30              465                     404\n",
       "8                  20              459                     360\n",
       "9                  10              447                     243\n",
       "10                  1               97                      19"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stat_table_mixcr_b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8db82b02",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Downsampled to, %</th>\n",
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       "    Downsampled to, %  Number of cells  Number of paired cells\n",
       "0                 100              470                     438\n",
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       "3                  70              462                     431\n",
       "4                  60              466                     421\n",
       "5                  50              463                     420\n",
       "6                  40              454                     399\n",
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       "8                  20              419                     338\n",
       "9                  10              286                     220\n",
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       "    Downsampled to, %  Number of cells  Number of paired cells\n",
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   "id": "ef39d20e",
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   "outputs": [
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       "    Downsampled to, %  Number of cells  Number of paired cells\n",
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