figures-cancer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import umap\n",
    "import matplotlib.lines as mlines\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "sns.set_style(\"whitegrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "c_icut = \"#e4eaed\"\n",
    "c_icut2 = \"#34495e\"\n",
    "c_rxnenum = \"#065535\"\n",
    "c_rxnenum = \"#cf9b00\"\n",
    "c_dexom = \"#e74c3c\"\n",
    "c_maxdist = \"#6a3d9a\"\n",
    "\n",
    "m_dexom = 'dexom' #dexom diversity-enum (or dexom-default method)\n",
    "m_maxdist = 'icut'\n",
    "m_icut = 'maxdist'\n",
    "m_rxnenum = 'rxnenum' # Reaction-enum method\n",
    "\n",
    "list_methods = [m_dexom, m_maxdist, m_rxnenum, m_icut]\n",
    "list_colors = [c_dexom, c_maxdist, c_rxnenum, c_icut2]\n",
    "\n",
    "\n",
    "pal_rxnenum = sns.color_palette([c_icut, c_rxnenum])\n",
    "pal_dexom = sns.color_palette([c_icut, c_dexom])\n",
    "pal_maxdist = sns.color_palette([c_icut, c_maxdist])\n",
    "pal_icut = sns.color_palette([c_icut, c_icut2])\n",
    "\n",
    "state = np.random.RandomState(seed=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_embedding(ax, df_embedding, method, color, title, x='UMAP1', y='UMAP2'):\n",
    "    ax.set(aspect='equal')\n",
    "    sns.scatterplot(x=x, y=y, data = df_embedding[[x,y]], ax = ax, linewidth=0,\n",
    "                    alpha=background_alpha, color=c_icut, rasterized=True)\n",
    "    df = df_embedding[df_embedding.method==method]\n",
    "    sns.scatterplot(x=x, y=y, data = df, ax = ax, linewidth=0, alpha=method_alpha, color=color, rasterized=True)\n",
    "    ax.set_title(title, fontsize=14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load cancer cell line reconstruction"
   ]
  },
  {
   "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>s1</th>\n",
       "      <th>s2</th>\n",
       "      <th>s3</th>\n",
       "      <th>s4</th>\n",
       "      <th>s5</th>\n",
       "      <th>s6</th>\n",
       "      <th>s7</th>\n",
       "      <th>s8</th>\n",
       "      <th>s9</th>\n",
       "      <th>s10</th>\n",
       "      <th>...</th>\n",
       "      <th>s2508</th>\n",
       "      <th>s2509</th>\n",
       "      <th>s2510</th>\n",
       "      <th>s2511</th>\n",
       "      <th>s2512</th>\n",
       "      <th>s2513</th>\n",
       "      <th>s2514</th>\n",
       "      <th>s2515</th>\n",
       "      <th>s2516</th>\n",
       "      <th>s2517</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10964</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10965</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10966</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10967</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10968</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10969 rows × 2517 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       s1  s2  s3  s4  s5  s6  s7  s8  s9  s10  ...  s2508  s2509  s2510  \\\n",
       "0       0   0   0   0   0   0   0   0   0    0  ...      1      1      0   \n",
       "1       0   0   0   0   0   0   0   0   0    0  ...      1      1      0   \n",
       "2       0   0   0   0   0   0   0   0   0    0  ...      1      1      0   \n",
       "3       0   0   0   0   0   0   0   0   0    0  ...      1      1      0   \n",
       "4       0   0   0   0   0   0   0   1   0    0  ...      1      1      0   \n",
       "...    ..  ..  ..  ..  ..  ..  ..  ..  ..  ...  ...    ...    ...    ...   \n",
       "10964   1   1   0   0   0   0   1   1   0    0  ...      1      1      0   \n",
       "10965   1   1   0   0   0   0   1   1   0    0  ...      1      1      0   \n",
       "10966   1   1   0   0   0   0   1   1   0    0  ...      1      1      0   \n",
       "10967   1   1   0   0   0   0   1   1   0    0  ...      1      1      0   \n",
       "10968   1   1   0   0   0   0   1   1   0    1  ...      1      1      0   \n",
       "\n",
       "       s2511  s2512  s2513  s2514  s2515  s2516  s2517  \n",
       "0          0      1      0      0      0      0      0  \n",
       "1          0      1      0      0      0      0      0  \n",
       "2          0      1      0      0      0      0      0  \n",
       "3          0      1      0      0      0      0      0  \n",
       "4          0      1      0      0      0      0      0  \n",
       "...      ...    ...    ...    ...    ...    ...    ...  \n",
       "10964      0      1      0      0      0      1      0  \n",
       "10965      0      1      0      0      0      0      0  \n",
       "10966      0      1      0      0      0      0      0  \n",
       "10967      0      1      0      0      0      0      0  \n",
       "10968      0      1      0      0      0      0      0  \n",
       "\n",
       "[10969 rows x 2517 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_reconstruction = pd.read_csv('results/cancer/csv/A375_10_90.csv.zip')\n",
    "df_reactions = df_reconstruction.drop('label', axis=1)\n",
    "labels = df_reconstruction.label.squeeze().values.tolist()\n",
    "df_reactions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\pablo\\miniconda3\\lib\\site-packages\\umap\\umap_.py:1530: UserWarning: gradient function is not yet implemented for hamming distance metric; inverse_transform will be unavailable\n",
      "  \"inverse_transform will be unavailable\".format(self.metric)\n"
     ]
    },
    {
     "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>UMAP1</th>\n",
       "      <th>UMAP2</th>\n",
       "      <th>method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.598049</td>\n",
       "      <td>11.924226</td>\n",
       "      <td>dexom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.907703</td>\n",
       "      <td>9.642414</td>\n",
       "      <td>dexom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.782621</td>\n",
       "      <td>10.872744</td>\n",
       "      <td>dexom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.651143</td>\n",
       "      <td>12.375160</td>\n",
       "      <td>dexom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.287293</td>\n",
       "      <td>5.225927</td>\n",
       "      <td>dexom</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      UMAP1      UMAP2 method\n",
       "0  1.598049  11.924226  dexom\n",
       "1  3.907703   9.642414  dexom\n",
       "2  3.782621  10.872744  dexom\n",
       "3 -0.651143  12.375160  dexom\n",
       "4  1.287293   5.225927  dexom"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# NOTE: Results are exported using the exportResults.m script included in DEXOM\n",
    "embedding = umap.UMAP(metric=\"hamming\", random_state=state, n_neighbors=30, unique=True).fit_transform(df_reactions)\n",
    "\n",
    "df_embedding = pd.DataFrame(embedding, columns=['UMAP1','UMAP2'])\n",
    "df_embedding['method'] = labels\n",
    "df_embedding.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"ticks\")\n",
    "\n",
    "fig, axs = plt.subplots(2, 2, figsize=(10, 10), sharey=False)\n",
    "\n",
    "background_alpha = 0.1\n",
    "method_alpha = 0.3\n",
    "\n",
    "ax = axs[0,0]\n",
    "plot_embedding(ax, df_embedding, m_dexom, c_dexom, '(A) Diversity-enum')\n",
    "\n",
    "ax = axs[0,1]\n",
    "plot_embedding(ax, df_embedding, m_maxdist, c_maxdist, '(B) Maxdist-enum')\n",
    "\n",
    "ax = axs[1,0]\n",
    "plot_embedding(ax, df_embedding, m_rxnenum, c_rxnenum, '(C) Reaction-enum')\n",
    "\n",
    "ax = axs[1,1]\n",
    "plot_embedding(ax, df_embedding, m_icut, c_icut2, '(D) Icut-enum')\n",
    "\n",
    "\n",
    "sns.despine(offset=15, trim=True);\n",
    "plt.tight_layout()\n",
    "\n",
    "#fig.savefig('figures/figure_cancer.pdf')"
   ]
  }
 ],
 "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}