{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ssm-user/anaconda3/envs/scATAC/lib/python3.8/site-packages/anndata/_core/anndata.py:21: FutureWarning: pandas.core.index is deprecated and will be removed in a future version.  The public classes are available in the top-level namespace.\n",
      "  from pandas.core.index import RangeIndex\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import anndata\n",
    "from nero import Harmonia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "demux = Harmonia.MuxOut(\"/covid/demux/merged/freemux_merged.clust1.samples.gz\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['path', 'label', 'raw', 'muxtype', 'type', 'usefulcols', 'useful_cols_run', 'store_meta_run', 'data', 'num_drops', 'num_sng', 'num_dbl', 'num_amb', 'sngrate', 'dblrate', 'ambrate', 'sngrate_nonamb', 'dblrate_nonamb', 'inds'])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "demux.__dict__.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>NUM.SNPS</th>\n",
       "      <th>NUM.READS</th>\n",
       "      <th>DROPLET.TYPE</th>\n",
       "      <th>BEST.GUESS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BARCODE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>GCGCGATCACAGGTTT-0</th>\n",
       "      <td>2490</td>\n",
       "      <td>7241</td>\n",
       "      <td>SNG</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CTTACCGCACGACTCG-0</th>\n",
       "      <td>1354</td>\n",
       "      <td>2808</td>\n",
       "      <td>SNG</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GCTGGGTGTCTCACCT-0</th>\n",
       "      <td>1200</td>\n",
       "      <td>2222</td>\n",
       "      <td>SNG</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CACACCTTCTTGACGA-0</th>\n",
       "      <td>1529</td>\n",
       "      <td>3593</td>\n",
       "      <td>SNG</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAGCAGCAGACCGGAT-0</th>\n",
       "      <td>462</td>\n",
       "      <td>782</td>\n",
       "      <td>SNG</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    NUM.SNPS  NUM.READS DROPLET.TYPE BEST.GUESS\n",
       "BARCODE                                                        \n",
       "GCGCGATCACAGGTTT-0      2490       7241          SNG          3\n",
       "CTTACCGCACGACTCG-0      1354       2808          SNG         10\n",
       "GCTGGGTGTCTCACCT-0      1200       2222          SNG         17\n",
       "CACACCTTCTTGACGA-0      1529       3593          SNG          4\n",
       "CAGCAGCAGACCGGAT-0       462        782          SNG         16"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "demux.sng().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "demux.llk_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "demux.snp_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "demux.ind_hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SNG rate: 0.7765312710434789\n",
      "DBL rate: 0.218900775441349\n",
      "AMB rate: 0.004567953515172131\n"
     ]
    }
   ],
   "source": [
    "print(\"SNG rate: {}\\nDBL rate: {}\\nAMB rate: {}\".format(demux.sngrate,demux.dblrate,demux.ambrate))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}