notebooks/Step0_Generate_feature_matrix_beatAML_wave12.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "056b2369",
   "metadata": {},
   "source": [
    "#### Processing Data of Beat AML data wave 1/2\n",
    "#### Data were downloaded from the orginal paper (doi: 10.1038/s41586-018-0623-z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ddf02f0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import sys\n",
    "sys.path.append('../src/')\n",
    "import matrix_convert as mc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca06b5b9",
   "metadata": {},
   "source": [
    "# Loading BeatAML wave1/2 dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "760164c8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.45261900330956\n"
     ]
    }
   ],
   "source": [
    "Data_dir = \"/Users/guangrong/Documents/GitHub_project/AML_BeatAML/project/Data_resource/\"\n",
    "BeatAML_mut = pd.read_csv(Data_dir +\"Mutation.csv\")\n",
    "BeatAML_drug_response = pd.read_csv(Data_dir + \"Drug_Response.csv\")\n",
    "print(np.median(BeatAML_drug_response.loc[BeatAML_drug_response['inhibitor'] == 'Venetoclax']['ic50']))\n",
    "# The median value for Venetoclax IC50 is 1.45 uM.\n",
    "BeatAML_rnaseq = pd.read_csv(Data_dir + \"RPKM.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10d16ce7",
   "metadata": {},
   "source": [
    "# Select high frequently mutated genes \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fb973bfd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of unique mutations in BeatAML_mut_s identified by either mutect or varscan: \n",
      "4522\n",
      "The number of unique mutations in BeatAML_mut_s identified by mutect: \n",
      "3409\n",
      "The number of unique mutations in BeatAML_mut_s identified by varscan: \n",
      "3583\n",
      "The number of unique mutations in BeatAML_mut_s identified by both mutect and varscan: \n",
      "2538\n"
     ]
    }
   ],
   "source": [
    "BeatAML_mut_s = BeatAML_mut.loc[:,['labId','chosen_consequence', 'impact', 'symbol','amino_acids','genotyper']]\n",
    "\n",
    "#select variants from BeatAML_mut_s if the genotyper includes both mutect and varsan\n",
    "BeatAML_mut_s['new_id'] = BeatAML_mut_s['symbol'] +':'+ BeatAML_mut_s['amino_acids']\n",
    "\n",
    "print(\"The number of unique mutations in BeatAML_mut_s identified by either mutect or varscan: \")\n",
    "print(len(BeatAML_mut_s['new_id'].unique()))\n",
    "print(\"The number of unique mutations in BeatAML_mut_s identified by mutect: \")\n",
    "print(len(BeatAML_mut_s.loc[BeatAML_mut_s['genotyper'] == 'mutect']['new_id'].unique()))\n",
    "print(\"The number of unique mutations in BeatAML_mut_s identified by varscan: \")\n",
    "print(len(BeatAML_mut_s.loc[BeatAML_mut_s['genotyper'] == 'varscan']['new_id'].unique()))\n",
    "print(\"The number of unique mutations in BeatAML_mut_s identified by both mutect and varscan: \")\n",
    "print(len(set(BeatAML_mut_s.loc[BeatAML_mut_s['genotyper'] == 'mutect']['new_id'].unique()).intersection(BeatAML_mut_s.loc[BeatAML_mut_s['genotyper'] == 'varscan']['new_id'].unique())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cfc32eb1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(608, 22)\n"
     ]
    }
   ],
   "source": [
    "# Convert gene mutation to a matrix\n",
    "BeatAML_mut_matrix = mc.convert_df2matrix_bi(BeatAML_mut,\"labId\",\"symbol\")\n",
    "\n",
    "# Select highly frequent mutated genes\n",
    "selected_genes = []\n",
    "for gene in BeatAML_mut_matrix.columns:\n",
    "    if BeatAML_mut_matrix.loc[BeatAML_mut_matrix[gene] == 1].shape[0] >= 0.03*BeatAML_mut_matrix.shape[0]:\n",
    "        selected_genes.append(gene)\n",
    "\n",
    "selected_mutation_matrix = BeatAML_mut_matrix[selected_genes]\n",
    "# Save the selected mutation matrix\n",
    "print(selected_mutation_matrix.shape )\n",
    "selected_mutation_matrix.to_csv(\"../data/Feature_set1_mutation_matrix_w12.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2c681953",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the frequency of gene mutation\n",
    "df_gene_mut_freq = selected_mutation_matrix.sum(axis = 0)/selected_mutation_matrix.shape[0] * 100\n",
    "df_gene_mut_freq = df_gene_mut_freq.sort_values(ascending = False)\n",
    " \n",
    "# convert the gene mutation frequency to a dataframe\n",
    "df_gene_mut_freq = pd.DataFrame(df_gene_mut_freq, columns = ['Frequency'])\n",
    "df_gene_mut_freq['Gene'] = df_gene_mut_freq.index\n",
    "\n",
    "# bar plot for the frequency of gene mutation\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# set background style\n",
    "sns.set(style=\"white\")\n",
    "plt.figure(figsize=(4, 4), dpi=300)\n",
    "sns.barplot(x = \"Frequency\", y = \"Gene\", \n",
    "            data = df_gene_mut_freq.sort_values(by = \"Frequency\", ascending = False),\n",
    "            color=\"grey\")\n",
    "plt.xlabel(\"% of patients (Total: \" + str(selected_mutation_matrix.shape[0])+ \" ) with gene mutations\")\n",
    "plt.ylabel(\"Mutated genes\")\n",
    "plt.title(\"Frequency of gene mutations in Beat AML wave 1/2\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50ae34cc",
   "metadata": {},
   "source": [
    "# Select variants or regions with high mutation frequency\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "27cc2e4b",
   "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>Unnamed: 0</th>\n",
       "      <th>chrom</th>\n",
       "      <th>pos_start</th>\n",
       "      <th>pos_end</th>\n",
       "      <th>ref</th>\n",
       "      <th>alt</th>\n",
       "      <th>labId</th>\n",
       "      <th>tumor_only</th>\n",
       "      <th>genotyper</th>\n",
       "      <th>total_reads</th>\n",
       "      <th>...</th>\n",
       "      <th>existing_variation</th>\n",
       "      <th>variant_class</th>\n",
       "      <th>sift</th>\n",
       "      <th>polyphen</th>\n",
       "      <th>exac_af</th>\n",
       "      <th>short_aa_change</th>\n",
       "      <th>validation</th>\n",
       "      <th>rna_status</th>\n",
       "      <th>new_id</th>\n",
       "      <th>new_id_patient</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>914477</td>\n",
       "      <td>914477</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>14-00141</td>\n",
       "      <td>0</td>\n",
       "      <td>mutect</td>\n",
       "      <td>33</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SNV</td>\n",
       "      <td>tolerated(0.12)</td>\n",
       "      <td>benign(0.002)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>p.A551T</td>\n",
       "      <td>not_covered</td>\n",
       "      <td>not_covered</td>\n",
       "      <td>C1orf170:p.A551T:914477</td>\n",
       "      <td>14-00141:C1orf170:p.A551T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>914477</td>\n",
       "      <td>914477</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>14-00141</td>\n",
       "      <td>0</td>\n",
       "      <td>varscan</td>\n",
       "      <td>31</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SNV</td>\n",
       "      <td>tolerated(0.12)</td>\n",
       "      <td>benign(0.002)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>p.A551T</td>\n",
       "      <td>not_covered</td>\n",
       "      <td>not_covered</td>\n",
       "      <td>C1orf170:p.A551T:914477</td>\n",
       "      <td>14-00141:C1orf170:p.A551T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>914941</td>\n",
       "      <td>914941</td>\n",
       "      <td>G</td>\n",
       "      <td>A</td>\n",
       "      <td>15-00492</td>\n",
       "      <td>0</td>\n",
       "      <td>mutect</td>\n",
       "      <td>74</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SNV</td>\n",
       "      <td>tolerated(0.11)</td>\n",
       "      <td>benign(0.003)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>p.A396V</td>\n",
       "      <td>not_done</td>\n",
       "      <td>not_done</td>\n",
       "      <td>C1orf170:p.A396V:914941</td>\n",
       "      <td>15-00492:C1orf170:p.A396V</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>914941</td>\n",
       "      <td>914941</td>\n",
       "      <td>G</td>\n",
       "      <td>A</td>\n",
       "      <td>15-00492</td>\n",
       "      <td>0</td>\n",
       "      <td>varscan</td>\n",
       "      <td>85</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SNV</td>\n",
       "      <td>tolerated(0.11)</td>\n",
       "      <td>benign(0.003)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>p.A396V</td>\n",
       "      <td>not_done</td>\n",
       "      <td>not_done</td>\n",
       "      <td>C1orf170:p.A396V:914941</td>\n",
       "      <td>15-00492:C1orf170:p.A396V</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0 chrom  pos_start  pos_end ref alt     labId  tumor_only  \\\n",
       "0           0     1     914477   914477   C   T  14-00141           0   \n",
       "1           1     1     914477   914477   C   T  14-00141           0   \n",
       "2           2     1     914941   914941   G   A  15-00492           0   \n",
       "3           3     1     914941   914941   G   A  15-00492           0   \n",
       "\n",
       "  genotyper  total_reads  ...  existing_variation  variant_class  \\\n",
       "0    mutect           33  ...                 NaN            SNV   \n",
       "1   varscan           31  ...                 NaN            SNV   \n",
       "2    mutect           74  ...                 NaN            SNV   \n",
       "3   varscan           85  ...                 NaN            SNV   \n",
       "\n",
       "              sift       polyphen  exac_af short_aa_change   validation  \\\n",
       "0  tolerated(0.12)  benign(0.002)      NaN         p.A551T  not_covered   \n",
       "1  tolerated(0.12)  benign(0.002)      NaN         p.A551T  not_covered   \n",
       "2  tolerated(0.11)  benign(0.003)      NaN         p.A396V     not_done   \n",
       "3  tolerated(0.11)  benign(0.003)      NaN         p.A396V     not_done   \n",
       "\n",
       "    rna_status                   new_id             new_id_patient  \n",
       "0  not_covered  C1orf170:p.A551T:914477  14-00141:C1orf170:p.A551T  \n",
       "1  not_covered  C1orf170:p.A551T:914477  14-00141:C1orf170:p.A551T  \n",
       "2     not_done  C1orf170:p.A396V:914941  15-00492:C1orf170:p.A396V  \n",
       "3     not_done  C1orf170:p.A396V:914941  15-00492:C1orf170:p.A396V  \n",
       "\n",
       "[4 rows x 41 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "BeatAML_mut['new_id'] = BeatAML_mut['symbol'] +':'+ BeatAML_mut['short_aa_change'] + ':' + BeatAML_mut['pos_start'].astype(str)\n",
    "BeatAML_mut['new_id_patient'] = BeatAML_mut['labId'] + ':'+ BeatAML_mut['symbol'] +':'+ BeatAML_mut['short_aa_change']\n",
    "BeatAML_mut.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2698b8e1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4664\n",
      "6305\n"
     ]
    }
   ],
   "source": [
    "all_ids = set()\n",
    "remain_index = set()\n",
    "\n",
    "for i in range(0, BeatAML_mut.shape[0]):\n",
    "    newid = BeatAML_mut.iloc[i,40]\n",
    "\n",
    "    genotyper = BeatAML_mut.iloc[i,8]\n",
    "    if genotyper == \"mutect\":\n",
    "        if newid not in all_ids:\n",
    "            remain_index.add(i)\n",
    "        all_ids.add(newid)\n",
    "print(len(remain_index))\n",
    "for i in range(0, BeatAML_mut.shape[0]):\n",
    "    newid = BeatAML_mut.iloc[i,40]\n",
    "\n",
    "    genotyper = BeatAML_mut.iloc[i,8]\n",
    "    if genotyper == \"varscan\":\n",
    "        if newid in all_ids:\n",
    "            all_ids.add(newid)\n",
    "        else:\n",
    "            remain_index.add(i)\n",
    "            all_ids.add(newid)\n",
    "\n",
    "print(len(remain_index))\n",
    "\n",
    "BeatAML_mut_unique_vaf = BeatAML_mut.iloc[list(remain_index),]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8357ed5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Select highly frequently mutated variants\n",
    "BeatAML_mut_matrix_vaf = mc.convert_df2matrix_cont(BeatAML_mut_unique_vaf,'new_id','labId','t_vaf')\n",
    "BeatAML_mut_matrix_vaf = BeatAML_mut_matrix_vaf.transpose()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0815d156",
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RFC4:p.P142L:186510722</th>\n",
       "      <th>ST13:p.G296R:41223195</th>\n",
       "      <th>GRIK2:p.G410Afs*2:102266268</th>\n",
       "      <th>ADAMDEC1:p.P109A:24251622</th>\n",
       "      <th>TSHR:p.R701C:81610503</th>\n",
       "      <th>LRP4:p.T353M:46917560</th>\n",
       "      <th>KRAS:p.G12V:25398284</th>\n",
       "      <th>KCNAB3:p.P35S:7832651</th>\n",
       "      <th>SHROOM1:p.G649A:132159322</th>\n",
       "      <th>ADAM15:p.R553Q:155030568</th>\n",
       "      <th>...</th>\n",
       "      <th>NEUROG1:p.I141T:134870959</th>\n",
       "      <th>ALKBH8:p.L212*:107422599</th>\n",
       "      <th>RP11-167N24.6:p.P50L:95771036</th>\n",
       "      <th>TPTE2:p.F161Lfs*15:20041393</th>\n",
       "      <th>CNOT6:p.F120L:179980446</th>\n",
       "      <th>AL583828.1:p.R25*:13470440</th>\n",
       "      <th>SHROOM4:p.E1151del:50350713</th>\n",
       "      <th>CD151:p.A145T:837331</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>14-00279</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>16-00041</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>16-00510</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>15-00819</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15-00693</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16-00307</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>16-00460</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14-00787</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>603 rows × 4811 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          RFC4:p.P142L:186510722  ST13:p.G296R:41223195  \\\n",
       "16-01047                     NaN                    NaN   \n",
       "16-01123                     NaN                    NaN   \n",
       "14-00279                     NaN                    NaN   \n",
       "16-00041                     NaN                    NaN   \n",
       "16-00510                     NaN                    NaN   \n",
       "...                          ...                    ...   \n",
       "15-00819                     NaN                    NaN   \n",
       "15-00693                     NaN                    NaN   \n",
       "16-00307                     NaN                    NaN   \n",
       "16-00460                     NaN                    NaN   \n",
       "14-00787                     NaN                    NaN   \n",
       "\n",
       "          GRIK2:p.G410Afs*2:102266268  ADAMDEC1:p.P109A:24251622  \\\n",
       "16-01047                          NaN                        NaN   \n",
       "16-01123                          NaN                        NaN   \n",
       "14-00279                          NaN                        NaN   \n",
       "16-00041                          NaN                        NaN   \n",
       "16-00510                          NaN                        NaN   \n",
       "...                               ...                        ...   \n",
       "15-00819                          NaN                        NaN   \n",
       "15-00693                          NaN                        NaN   \n",
       "16-00307                          NaN                        NaN   \n",
       "16-00460                          NaN                        NaN   \n",
       "14-00787                          NaN                        NaN   \n",
       "\n",
       "          TSHR:p.R701C:81610503  LRP4:p.T353M:46917560  KRAS:p.G12V:25398284  \\\n",
       "16-01047                    NaN                    NaN                   NaN   \n",
       "16-01123                    NaN                    NaN                   NaN   \n",
       "14-00279                    NaN                    NaN                   NaN   \n",
       "16-00041                    NaN                    NaN                   NaN   \n",
       "16-00510                    NaN                    NaN                   NaN   \n",
       "...                         ...                    ...                   ...   \n",
       "15-00819                    NaN                    NaN                   NaN   \n",
       "15-00693                    NaN                    NaN                   NaN   \n",
       "16-00307                    NaN                    NaN                   NaN   \n",
       "16-00460                    NaN                    NaN                   NaN   \n",
       "14-00787                    NaN                    NaN                   NaN   \n",
       "\n",
       "          KCNAB3:p.P35S:7832651  SHROOM1:p.G649A:132159322  \\\n",
       "16-01047                    NaN                        NaN   \n",
       "16-01123                    NaN                        NaN   \n",
       "14-00279                    NaN                        NaN   \n",
       "16-00041                    NaN                        NaN   \n",
       "16-00510                    NaN                        NaN   \n",
       "...                         ...                        ...   \n",
       "15-00819                    NaN                        NaN   \n",
       "15-00693                    NaN                        NaN   \n",
       "16-00307                    NaN                        NaN   \n",
       "16-00460                    NaN                        NaN   \n",
       "14-00787                    NaN                        NaN   \n",
       "\n",
       "          ADAM15:p.R553Q:155030568  ...  NEUROG1:p.I141T:134870959  \\\n",
       "16-01047                       NaN  ...                        NaN   \n",
       "16-01123                       NaN  ...                        NaN   \n",
       "14-00279                       NaN  ...                        NaN   \n",
       "16-00041                       NaN  ...                        NaN   \n",
       "16-00510                       NaN  ...                        NaN   \n",
       "...                            ...  ...                        ...   \n",
       "15-00819                       NaN  ...                        NaN   \n",
       "15-00693                       NaN  ...                        NaN   \n",
       "16-00307                       NaN  ...                        NaN   \n",
       "16-00460                       NaN  ...                        NaN   \n",
       "14-00787                       NaN  ...                        NaN   \n",
       "\n",
       "          ALKBH8:p.L212*:107422599  RP11-167N24.6:p.P50L:95771036  \\\n",
       "16-01047                       NaN                            NaN   \n",
       "16-01123                       NaN                            NaN   \n",
       "14-00279                       NaN                            NaN   \n",
       "16-00041                       NaN                            NaN   \n",
       "16-00510                       NaN                            NaN   \n",
       "...                            ...                            ...   \n",
       "15-00819                       NaN                            NaN   \n",
       "15-00693                       NaN                            NaN   \n",
       "16-00307                       NaN                            NaN   \n",
       "16-00460                       NaN                            NaN   \n",
       "14-00787                       NaN                            NaN   \n",
       "\n",
       "          TPTE2:p.F161Lfs*15:20041393  CNOT6:p.F120L:179980446  \\\n",
       "16-01047                          NaN                      NaN   \n",
       "16-01123                          NaN                      NaN   \n",
       "14-00279                          NaN                      NaN   \n",
       "16-00041                          NaN                      NaN   \n",
       "16-00510                          NaN                      NaN   \n",
       "...                               ...                      ...   \n",
       "15-00819                          NaN                      NaN   \n",
       "15-00693                          NaN                      NaN   \n",
       "16-00307                          NaN                      NaN   \n",
       "16-00460                          NaN                      NaN   \n",
       "14-00787                          NaN                      NaN   \n",
       "\n",
       "          AL583828.1:p.R25*:13470440  SHROOM4:p.E1151del:50350713  \\\n",
       "16-01047                         NaN                          NaN   \n",
       "16-01123                         NaN                          NaN   \n",
       "14-00279                         NaN                          NaN   \n",
       "16-00041                         NaN                          NaN   \n",
       "16-00510                         NaN                          NaN   \n",
       "...                              ...                          ...   \n",
       "15-00819                         NaN                          NaN   \n",
       "15-00693                         NaN                          NaN   \n",
       "16-00307                         NaN                          NaN   \n",
       "16-00460                         NaN                          NaN   \n",
       "14-00787                         NaN                          NaN   \n",
       "\n",
       "          CD151:p.A145T:837331  PHF6:p.C283S:133551211  FLT3:p.D835E:28592640  \n",
       "16-01047                   NaN                     NaN                    NaN  \n",
       "16-01123                   NaN                     NaN                    NaN  \n",
       "14-00279                   NaN                     NaN                    NaN  \n",
       "16-00041                   NaN                     NaN                    NaN  \n",
       "16-00510                   NaN                     NaN                    NaN  \n",
       "...                        ...                     ...                    ...  \n",
       "15-00819                   NaN                     NaN                    NaN  \n",
       "15-00693                   NaN                     NaN                    NaN  \n",
       "16-00307                   NaN                     NaN                    NaN  \n",
       "16-00460                   NaN                     NaN                    NaN  \n",
       "14-00787                   NaN                     NaN                    NaN  \n",
       "\n",
       "[603 rows x 4811 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BeatAML_mut_matrix_vaf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9199e553",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['IDH2:p.R140Q:90631934', 'NPM1:p.W288Cfs*12:170837545',\n",
       "       'SF3B1:p.K666N:198267359', 'FLT3:p.D835H:28592642',\n",
       "       'SRSF2:p.P95_R102del:74732935', 'NRAS:p.G12D:115258747',\n",
       "       'NRAS:p.G13D:115258744', 'DNMT3A:p.R882C:25457243',\n",
       "       'NPM1:p.W288Cfs*12:170837544', 'SF3B1:p.K700E:198266834',\n",
       "       'U2AF1:p.Q157P:44514777', 'JAK2:p.V617F:5073770',\n",
       "       'IDH1:p.R132C:209113113', 'SRSF2:p.P95R:74732959',\n",
       "       'U2AF1:p.S34F:44524456', 'NRAS:p.Q61K:115256530',\n",
       "       'IDH2:p.R172K:90631838', 'SRSF2:p.P95L:74732959',\n",
       "       'DNMT3A:p.R882H:25457242', 'ASXL1:p.G645Vfs*58:31022441',\n",
       "       'ZNF687:p.R939Pfs*36:151262327', 'IDH1:p.R132H:209113112',\n",
       "       'NPM1:p.W288Cfs*12:170837543', 'FLT3:p.D835Y:28592642',\n",
       "       'NRAS:p.Q61H:115256528', 'SRSF2:p.P95H:74732959',\n",
       "       'ASXL1:p.G646Wfs*12:31022441', 'FLT3:p.I836del:28592634',\n",
       "       'FAM194A:p.V56E:150421519'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select highly frequent mutated variants\n",
    "selected_variants = []\n",
    "for gene in BeatAML_mut_matrix_vaf.columns:\n",
    "    if BeatAML_mut_matrix_vaf.loc[BeatAML_mut_matrix_vaf[gene] > 0].shape[0] > 0.01*BeatAML_mut_matrix_vaf.shape[0]:\n",
    "        selected_variants.append(gene)\n",
    "\n",
    "BeatAML_mut_matrix_vaf_sele = BeatAML_mut_matrix_vaf[selected_variants]\n",
    "BeatAML_mut_matrix_vaf_sele.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f74cb2eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_variants = {\n",
    "    \"DNMT3A:p.R882\":['DNMT3A:p.R882H:25457242','DNMT3A:p.R882C:25457243'],\n",
    "    \"ASXL1:p.G645-646\":[\"ASXL1:p.G645Vfs*58:31022441\",\n",
    "                        'ASXL1:p.G646Wfs*12:31022441', \n",
    "                        'ASXL1:p.G645Wfs*12:31022441',],\n",
    "    \"FLT3:p.835-839\":['FLT3:p.D835E:28592640',\n",
    "                      'FLT3:p.D835H:28592642',\n",
    "                      'FLT3:p.D835N:28592642',\n",
    "                      'FLT3:p.D835V:28592641',\n",
    "                      'FLT3:p.D835Y:28592642',\n",
    "                      'FLT3:p.D839G:28592629',\n",
    "                      'FLT3:p.I836del:28592634'],\n",
    "                                          \n",
    "     \"IDH1:p.R132\":['IDH1:p.R132C:209113113',\n",
    "                        'IDH1:p.R132G:209113113',\n",
    "                        'IDH1:p.R132H:209113112',\n",
    "                        'IDH1:p.R132L:209113112',\n",
    "                        'IDH1:p.R132S:209113113'],\n",
    "    \"IDH2:p.R140\":['IDH2:p.R140L:90631934',\n",
    "                    'IDH2:p.R140Q:90631934',\n",
    "                    'IDH2:p.R140W:90631935'],\n",
    "\n",
    "    \"IDH2:p.R172\":[\"IDH2:p.R172K:90631838\"],\n",
    "\n",
    "    \"JAK2:p.V617\":[\"JAK2:p.V617F:5073770\"],\n",
    "    \"KIT:p.D816\":[ 'KIT:p.D816H:55599320',\n",
    "                    'KIT:p.D816V:55599321',\n",
    "                    'KIT:p.D816Y:55599320'],\n",
    "    \"KRAS:p.G12/13\":['KRAS:p.G12A:25398284',\n",
    "                        'KRAS:p.G12C:25398285',\n",
    "                        'KRAS:p.G12D:25398284',\n",
    "                        'KRAS:p.G12R:25398285',\n",
    "                        'KRAS:p.G12V:25398284',\n",
    "                        'KRAS:p.G13D:25398281',\n",
    "                        'KRAS:p.G13R:25398282'],\n",
    "   # \"NF1:p.I679Dfs*21:29553477\":[\"NF1:p.I679Dfs*21:29553477\"],\n",
    "    \"NPM1:p.W288-90\":['NPM1:p.W288Cfs*12:170837543',\n",
    "                    'NPM1:p.W288Cfs*12:170837544',\n",
    "                    'NPM1:p.W288Cfs*12:170837545',\n",
    "                    'NPM1:p.W288Cfs*12:170837546',\n",
    "                    'NPM1:p.W288Cfs*12:170837547',\n",
    "                    'NPM1:p.W290Cfs*10:170837553',\n",
    "                    'NPM1:p.W290Rfs*10:170837551'],\n",
    "    \"NRAS:p.G12/13\":['NRAS:p.G12A:115258747',\n",
    "                    'NRAS:p.G12C:115258748',\n",
    "                    'NRAS:p.G12D:115258747',\n",
    "                    'NRAS:p.G12R:115258748',\n",
    "                    'NRAS:p.G12S:115258748',\n",
    "                    'NRAS:p.G13C:115258745',\n",
    "                    'NRAS:p.G13D:115258744',\n",
    "                    'NRAS:p.G13R:115258745',\n",
    "                    'NRAS:p.G13V:115258744',],\n",
    "    \"NRAS:p.Q61\":['NRAS:p.Q61H:115256528',\n",
    "                    'NRAS:p.Q61K:115256530',\n",
    "                    'NRAS:p.Q61L:115256529',\n",
    "                    'NRAS:p.Q61P:115256529',\n",
    "                    'NRAS:p.Q61R:115256529'],\n",
    "    \"SF3B1:p.K700E\":[\"SF3B1:p.K700E:198266834\"],\n",
    "    \"SF3B1:p.K666\":['SF3B1:p.K666E:198267361',\n",
    "                    'SF3B1:p.K666M:198267360',\n",
    "                    'SF3B1:p.K666N:198267359',\n",
    "                    'SF3B1:p.K666Q:198267361',\n",
    "                    'SF3B1:p.K666T:198267360'],\n",
    "    \"SRSF2:p.94-95\":['SRSF2:p.P95H:74732959',\n",
    "                        'SRSF2:p.P95L:74732959',\n",
    "                        'SRSF2:p.P95R:74732959',\n",
    "                        'SRSF2:p.P95_R102del:74732935',\n",
    "                        'SRSF2:p.P95delinsRA:74732959',\n",
    "                        'SRSF2:p.R94dup:74732959'],\n",
    "    \"U2AF1:p.S34\":['U2AF1:p.S34F:44524456',\n",
    "                    'U2AF1:p.S34Y:44524456'],\n",
    "    \"U2AF1:p.156-157\":['U2AF1:p.Q157P:44514777',\n",
    "                        'U2AF1:p.Q157R:44514777',\n",
    "                        'U2AF1:p.R156H:44514780',],\n",
    "    \"ZNF687:p.R939Pfs*36:151262327\":[\"ZNF687:p.R939Pfs*36:151262327\"],\n",
    "    }\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "59a68eb9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7c75db0d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_select_variants = pd.DataFrame()\n",
    "for i in selected_variants:\n",
    "    df_select_variants[i] = BeatAML_mut_matrix_vaf.loc[:,list(set(selected_variants[i]).intersection(set(BeatAML_mut_matrix_vaf.columns)))].sum(axis = 1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4804b09c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(603, 18)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "DNMT3A:p.R882                    32.848633\n",
       "ASXL1:p.G645-646                  6.580722\n",
       "FLT3:p.835-839                   11.355035\n",
       "IDH1:p.R132                      20.942126\n",
       "IDH2:p.R140                      22.519558\n",
       "IDH2:p.R172                       4.976342\n",
       "JAK2:p.V617                      10.386895\n",
       "KIT:p.D816                        3.467462\n",
       "KRAS:p.G12/13                     4.799768\n",
       "NPM1:p.W288-90                   36.037696\n",
       "NRAS:p.G12/13                    18.801233\n",
       "NRAS:p.Q61                        8.130113\n",
       "SF3B1:p.K700E                     3.693759\n",
       "SF3B1:p.K666                      8.033271\n",
       "SRSF2:p.94-95                    29.915678\n",
       "U2AF1:p.S34                       5.539027\n",
       "U2AF1:p.156-157                   4.675217\n",
       "ZNF687:p.R939Pfs*36:151262327     1.752414\n",
       "dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(df_select_variants.shape)\n",
    "df_select_variants.sum(axis = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fb03fe74",
   "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>DNMT3A:p.R882</th>\n",
       "      <th>ASXL1:p.G645-646</th>\n",
       "      <th>FLT3:p.835-839</th>\n",
       "      <th>IDH1:p.R132</th>\n",
       "      <th>IDH2:p.R140</th>\n",
       "      <th>IDH2:p.R172</th>\n",
       "      <th>JAK2:p.V617</th>\n",
       "      <th>KIT:p.D816</th>\n",
       "      <th>KRAS:p.G12/13</th>\n",
       "      <th>NPM1:p.W288-90</th>\n",
       "      <th>NRAS:p.G12/13</th>\n",
       "      <th>NRAS:p.Q61</th>\n",
       "      <th>SF3B1:p.K700E</th>\n",
       "      <th>SF3B1:p.K666</th>\n",
       "      <th>SRSF2:p.94-95</th>\n",
       "      <th>U2AF1:p.S34</th>\n",
       "      <th>U2AF1:p.156-157</th>\n",
       "      <th>ZNF687:p.R939Pfs*36:151262327</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16-01047</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.441860</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.309091</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16-01123</th>\n",
       "      <td>0.235294</td>\n",
       "      <td>0.12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14-00279</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16-00041</th>\n",
       "      <td>0.472727</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.309091</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16-00510</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.363636</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15-00819</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.479592</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15-00693</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16-00307</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.412844</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.646067</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16-00460</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.360000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14-00787</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>603 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          DNMT3A:p.R882  ASXL1:p.G645-646  FLT3:p.835-839  IDH1:p.R132  \\\n",
       "16-01047       0.000000              0.00             0.0     0.441860   \n",
       "16-01123       0.235294              0.12             0.0     0.000000   \n",
       "14-00279       0.000000              0.00             0.0     0.000000   \n",
       "16-00041       0.472727              0.00             0.0     0.000000   \n",
       "16-00510       0.000000              0.00             0.0     0.000000   \n",
       "...                 ...               ...             ...          ...   \n",
       "15-00819       0.000000              0.00             0.0     0.000000   \n",
       "15-00693       0.000000              0.00             0.0     0.000000   \n",
       "16-00307       0.000000              0.00             0.0     0.412844   \n",
       "16-00460       0.000000              0.00             0.0     0.360000   \n",
       "14-00787       0.000000              0.00             0.0     0.000000   \n",
       "\n",
       "          IDH2:p.R140  IDH2:p.R172  JAK2:p.V617  KIT:p.D816  KRAS:p.G12/13  \\\n",
       "16-01047          0.0          0.0     0.000000    0.000000            0.0   \n",
       "16-01123          0.0          0.0     0.000000    0.000000            0.0   \n",
       "14-00279          0.0          0.0     0.000000    0.000000            0.0   \n",
       "16-00041          0.0          0.0     0.000000    0.000000            0.0   \n",
       "16-00510          0.0          0.0     0.000000    0.000000            0.0   \n",
       "...               ...          ...          ...         ...            ...   \n",
       "15-00819          0.0          0.0     0.000000    0.479592            0.0   \n",
       "15-00693          0.0          0.0     0.000000    0.000000            0.0   \n",
       "16-00307          0.0          0.0     0.646067    0.000000            0.0   \n",
       "16-00460          0.0          0.0     0.000000    0.000000            0.0   \n",
       "14-00787          0.0          0.0     0.000000    0.000000            0.0   \n",
       "\n",
       "          NPM1:p.W288-90  NRAS:p.G12/13  NRAS:p.Q61  SF3B1:p.K700E  \\\n",
       "16-01047        0.309091            0.0    0.000000            0.0   \n",
       "16-01123        0.000000            0.0    0.000000            0.0   \n",
       "14-00279        0.000000            0.0    0.000000            0.0   \n",
       "16-00041        0.309091            0.0    0.000000            0.0   \n",
       "16-00510        0.000000            0.0    0.363636            0.0   \n",
       "...                  ...            ...         ...            ...   \n",
       "15-00819        0.000000            0.0    0.000000            0.0   \n",
       "15-00693        0.000000            0.0    0.000000            0.0   \n",
       "16-00307        0.000000            0.0    0.000000            0.0   \n",
       "16-00460        0.000000            0.0    0.000000            0.0   \n",
       "14-00787        0.000000            0.0    0.000000            0.0   \n",
       "\n",
       "          SF3B1:p.K666  SRSF2:p.94-95  U2AF1:p.S34  U2AF1:p.156-157  \\\n",
       "16-01047           0.0            0.0          0.0              0.0   \n",
       "16-01123           0.0            0.0          0.0              0.0   \n",
       "14-00279           0.0            0.0          0.0              0.0   \n",
       "16-00041           0.0            0.0          0.0              0.0   \n",
       "16-00510           0.0            0.0          0.0              0.0   \n",
       "...                ...            ...          ...              ...   \n",
       "15-00819           0.0            0.0          0.0              0.0   \n",
       "15-00693           0.0            0.0          0.0              0.0   \n",
       "16-00307           0.0            0.0          0.0              0.0   \n",
       "16-00460           0.0            0.0          0.0              0.0   \n",
       "14-00787           0.0            0.0          0.0              0.0   \n",
       "\n",
       "          ZNF687:p.R939Pfs*36:151262327  \n",
       "16-01047                            0.0  \n",
       "16-01123                            0.0  \n",
       "14-00279                            0.0  \n",
       "16-00041                            0.0  \n",
       "16-00510                            0.0  \n",
       "...                                 ...  \n",
       "15-00819                            0.0  \n",
       "15-00693                            0.0  \n",
       "16-00307                            0.0  \n",
       "16-00460                            0.0  \n",
       "14-00787                            0.0  \n",
       "\n",
       "[603 rows x 18 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_select_variants.sum()\n",
    "\n",
    "# remove the variants with zero frequency\n",
    "df_select_variants1 = df_select_variants.loc[:,df_select_variants.sum(axis = 0) > 0]\n",
    "df_select_variants1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "07cbe69e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_select_variants1.to_csv(\"../data/Feature_set2_variants_matrix_w12.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "971438fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "variants = pd.DataFrame()\n",
    "Genes = []\n",
    "variants = []\n",
    "freq = []\n",
    "for i in selected_variants:\n",
    "    variants.append(i)\n",
    "    Genes.append(i.split(\":\")[0])\n",
    "    freq.append(df_select_variants.loc[df_select_variants[i] > 0].shape[0]/608*100)\n",
    "\n",
    "variants = pd.DataFrame({\"Gene\":Genes,\"variants\":variants,\"freq\":freq})\n",
    "variants\n",
    "\n",
    "# barplot of the frequency of the selected variants ordered by the frequency\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(4, 4), dpi=300)\n",
    "sns.barplot(x = \"freq\", y = \"variants\", \n",
    "            data = variants.sort_values(by = \"freq\", ascending = False),\n",
    "            color=\"grey\")\n",
    "plt.xlabel(\"% of patients (Total: \" +str(str(selected_mutation_matrix.shape[0])) + \" ) with the selected variants\")\n",
    "plt.ylabel(\"Variants\")\n",
    "plt.title(\"Frequency in Beat AML wave 1/2\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "864c894b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(603, 18)\n",
      "(608, 22)\n",
      "(608, 40)\n"
     ]
    }
   ],
   "source": [
    "# outer join  df_select_variants and selected_mutation_matrix\n",
    "print(df_select_variants1.shape)\n",
    "print(selected_mutation_matrix.shape)\n",
    "#selected_merged_matrix = selected_mutation_matrix.join(df_select_variants1)\n",
    "#selected_merged_matrix = selected_merged_matrix.fillna(0)\n",
    "\n",
    "selected_merged_matrix = pd.concat([ selected_mutation_matrix, df_select_variants1], axis = 1, join = \"outer\")\n",
    "print(selected_merged_matrix.shape)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8c8998f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_merged_matrix.to_csv(\"../data/Feature_set12_merged_matrix_w12.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "040707cc",
   "metadata": {},
   "source": [
    "## RNASeq data processing\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e0e2eea9",
   "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>Unnamed: 0</th>\n",
       "      <th>Gene</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>12-00023</th>\n",
       "      <th>12-00051</th>\n",
       "      <th>12-00066</th>\n",
       "      <th>12-00150</th>\n",
       "      <th>12-00211</th>\n",
       "      <th>12-00258</th>\n",
       "      <th>12-00294</th>\n",
       "      <th>...</th>\n",
       "      <th>16-01216</th>\n",
       "      <th>16-01219</th>\n",
       "      <th>16-01223</th>\n",
       "      <th>16-01225</th>\n",
       "      <th>16-01227</th>\n",
       "      <th>16-01237</th>\n",
       "      <th>16-01254</th>\n",
       "      <th>16-01262</th>\n",
       "      <th>16-01270</th>\n",
       "      <th>16-01272</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>ENSG00000000003</td>\n",
       "      <td>TSPAN6</td>\n",
       "      <td>-1.562506</td>\n",
       "      <td>2.352541</td>\n",
       "      <td>-2.825696</td>\n",
       "      <td>1.688537</td>\n",
       "      <td>-3.272121</td>\n",
       "      <td>-3.561056</td>\n",
       "      <td>-3.287483</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.382494</td>\n",
       "      <td>-1.896718</td>\n",
       "      <td>1.435855</td>\n",
       "      <td>-0.534799</td>\n",
       "      <td>0.509947</td>\n",
       "      <td>-0.830946</td>\n",
       "      <td>-2.923977</td>\n",
       "      <td>-0.998217</td>\n",
       "      <td>-0.964051</td>\n",
       "      <td>-1.042746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>ENSG00000000419</td>\n",
       "      <td>DPM1</td>\n",
       "      <td>6.886609</td>\n",
       "      <td>6.438417</td>\n",
       "      <td>6.554495</td>\n",
       "      <td>6.852558</td>\n",
       "      <td>6.613863</td>\n",
       "      <td>7.045231</td>\n",
       "      <td>7.019496</td>\n",
       "      <td>...</td>\n",
       "      <td>7.203169</td>\n",
       "      <td>6.885383</td>\n",
       "      <td>7.166459</td>\n",
       "      <td>7.174516</td>\n",
       "      <td>6.500557</td>\n",
       "      <td>7.545959</td>\n",
       "      <td>6.882087</td>\n",
       "      <td>7.331555</td>\n",
       "      <td>6.254707</td>\n",
       "      <td>6.641892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>ENSG00000000457</td>\n",
       "      <td>SCYL3</td>\n",
       "      <td>3.817626</td>\n",
       "      <td>3.987133</td>\n",
       "      <td>3.207921</td>\n",
       "      <td>3.878230</td>\n",
       "      <td>4.528385</td>\n",
       "      <td>3.762908</td>\n",
       "      <td>4.514343</td>\n",
       "      <td>...</td>\n",
       "      <td>3.611346</td>\n",
       "      <td>3.871390</td>\n",
       "      <td>3.992470</td>\n",
       "      <td>3.648833</td>\n",
       "      <td>4.503911</td>\n",
       "      <td>3.148649</td>\n",
       "      <td>4.077574</td>\n",
       "      <td>3.734620</td>\n",
       "      <td>3.811903</td>\n",
       "      <td>3.235035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>ENSG00000000460</td>\n",
       "      <td>C1orf112</td>\n",
       "      <td>2.437114</td>\n",
       "      <td>1.862662</td>\n",
       "      <td>3.368360</td>\n",
       "      <td>3.332284</td>\n",
       "      <td>2.984168</td>\n",
       "      <td>2.964634</td>\n",
       "      <td>3.479539</td>\n",
       "      <td>...</td>\n",
       "      <td>2.245470</td>\n",
       "      <td>3.677613</td>\n",
       "      <td>2.523557</td>\n",
       "      <td>3.235564</td>\n",
       "      <td>3.197705</td>\n",
       "      <td>2.645294</td>\n",
       "      <td>3.115359</td>\n",
       "      <td>2.980670</td>\n",
       "      <td>2.670554</td>\n",
       "      <td>3.341608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>ENSG00000000938</td>\n",
       "      <td>FGR</td>\n",
       "      <td>10.131911</td>\n",
       "      <td>5.014124</td>\n",
       "      <td>10.139119</td>\n",
       "      <td>5.941063</td>\n",
       "      <td>7.274613</td>\n",
       "      <td>10.538451</td>\n",
       "      <td>8.762846</td>\n",
       "      <td>...</td>\n",
       "      <td>9.715398</td>\n",
       "      <td>4.877051</td>\n",
       "      <td>6.218219</td>\n",
       "      <td>4.355385</td>\n",
       "      <td>5.746346</td>\n",
       "      <td>6.857559</td>\n",
       "      <td>10.782979</td>\n",
       "      <td>6.045946</td>\n",
       "      <td>6.383498</td>\n",
       "      <td>9.366073</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>22838</th>\n",
       "      <td>22838</td>\n",
       "      <td>ENSG00000273477</td>\n",
       "      <td>RP11-196O16.1</td>\n",
       "      <td>-0.219722</td>\n",
       "      <td>0.676291</td>\n",
       "      <td>0.518714</td>\n",
       "      <td>2.618279</td>\n",
       "      <td>1.581949</td>\n",
       "      <td>0.938443</td>\n",
       "      <td>-1.675077</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.180687</td>\n",
       "      <td>2.245470</td>\n",
       "      <td>3.521457</td>\n",
       "      <td>1.726353</td>\n",
       "      <td>1.182989</td>\n",
       "      <td>2.261786</td>\n",
       "      <td>0.625404</td>\n",
       "      <td>1.414241</td>\n",
       "      <td>3.181330</td>\n",
       "      <td>0.353361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22839</th>\n",
       "      <td>22839</td>\n",
       "      <td>ENSG00000273483</td>\n",
       "      <td>RP4-671G15.2</td>\n",
       "      <td>-1.997200</td>\n",
       "      <td>-0.485151</td>\n",
       "      <td>-0.805189</td>\n",
       "      <td>-3.145493</td>\n",
       "      <td>-0.206438</td>\n",
       "      <td>0.016466</td>\n",
       "      <td>0.798736</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.800714</td>\n",
       "      <td>0.493073</td>\n",
       "      <td>0.752237</td>\n",
       "      <td>1.389106</td>\n",
       "      <td>-1.656215</td>\n",
       "      <td>-1.706690</td>\n",
       "      <td>-1.028051</td>\n",
       "      <td>0.771490</td>\n",
       "      <td>-0.029557</td>\n",
       "      <td>-1.826434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22840</th>\n",
       "      <td>22840</td>\n",
       "      <td>ENSG00000273486</td>\n",
       "      <td>RP11-731C17.2</td>\n",
       "      <td>2.230568</td>\n",
       "      <td>1.029501</td>\n",
       "      <td>2.683986</td>\n",
       "      <td>1.676374</td>\n",
       "      <td>2.879371</td>\n",
       "      <td>2.305506</td>\n",
       "      <td>3.563519</td>\n",
       "      <td>...</td>\n",
       "      <td>4.285504</td>\n",
       "      <td>4.583648</td>\n",
       "      <td>3.716998</td>\n",
       "      <td>3.213924</td>\n",
       "      <td>4.411679</td>\n",
       "      <td>4.070881</td>\n",
       "      <td>2.267735</td>\n",
       "      <td>3.317902</td>\n",
       "      <td>3.403906</td>\n",
       "      <td>1.501366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22841</th>\n",
       "      <td>22841</td>\n",
       "      <td>ENSG00000273487</td>\n",
       "      <td>RP4-621B10.8</td>\n",
       "      <td>-0.633602</td>\n",
       "      <td>-1.905383</td>\n",
       "      <td>-2.185010</td>\n",
       "      <td>-3.561056</td>\n",
       "      <td>0.847544</td>\n",
       "      <td>1.297656</td>\n",
       "      <td>1.458084</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.064365</td>\n",
       "      <td>-1.694540</td>\n",
       "      <td>-0.062792</td>\n",
       "      <td>0.468829</td>\n",
       "      <td>-1.758246</td>\n",
       "      <td>-1.802393</td>\n",
       "      <td>1.330709</td>\n",
       "      <td>0.942407</td>\n",
       "      <td>-2.446318</td>\n",
       "      <td>-2.597849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22842</th>\n",
       "      <td>22842</td>\n",
       "      <td>ENSG00000273488</td>\n",
       "      <td>RP11-114I8.4</td>\n",
       "      <td>0.279923</td>\n",
       "      <td>2.397719</td>\n",
       "      <td>1.871256</td>\n",
       "      <td>0.217633</td>\n",
       "      <td>3.125748</td>\n",
       "      <td>1.531443</td>\n",
       "      <td>2.627441</td>\n",
       "      <td>...</td>\n",
       "      <td>1.939804</td>\n",
       "      <td>3.383642</td>\n",
       "      <td>1.847791</td>\n",
       "      <td>3.356067</td>\n",
       "      <td>1.792823</td>\n",
       "      <td>-2.218280</td>\n",
       "      <td>1.404543</td>\n",
       "      <td>1.970785</td>\n",
       "      <td>2.286737</td>\n",
       "      <td>0.650829</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>22843 rows × 454 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0             Gene         Symbol   12-00023  12-00051  \\\n",
       "0               0  ENSG00000000003         TSPAN6  -1.562506  2.352541   \n",
       "1               1  ENSG00000000419           DPM1   6.886609  6.438417   \n",
       "2               2  ENSG00000000457          SCYL3   3.817626  3.987133   \n",
       "3               3  ENSG00000000460       C1orf112   2.437114  1.862662   \n",
       "4               4  ENSG00000000938            FGR  10.131911  5.014124   \n",
       "...           ...              ...            ...        ...       ...   \n",
       "22838       22838  ENSG00000273477  RP11-196O16.1  -0.219722  0.676291   \n",
       "22839       22839  ENSG00000273483   RP4-671G15.2  -1.997200 -0.485151   \n",
       "22840       22840  ENSG00000273486  RP11-731C17.2   2.230568  1.029501   \n",
       "22841       22841  ENSG00000273487   RP4-621B10.8  -0.633602 -1.905383   \n",
       "22842       22842  ENSG00000273488   RP11-114I8.4   0.279923  2.397719   \n",
       "\n",
       "        12-00066  12-00150  12-00211   12-00258  12-00294  ...  16-01216  \\\n",
       "0      -2.825696  1.688537 -3.272121  -3.561056 -3.287483  ... -0.382494   \n",
       "1       6.554495  6.852558  6.613863   7.045231  7.019496  ...  7.203169   \n",
       "2       3.207921  3.878230  4.528385   3.762908  4.514343  ...  3.611346   \n",
       "3       3.368360  3.332284  2.984168   2.964634  3.479539  ...  2.245470   \n",
       "4      10.139119  5.941063  7.274613  10.538451  8.762846  ...  9.715398   \n",
       "...          ...       ...       ...        ...       ...  ...       ...   \n",
       "22838   0.518714  2.618279  1.581949   0.938443 -1.675077  ... -1.180687   \n",
       "22839  -0.805189 -3.145493 -0.206438   0.016466  0.798736  ... -2.800714   \n",
       "22840   2.683986  1.676374  2.879371   2.305506  3.563519  ...  4.285504   \n",
       "22841  -2.185010 -3.561056  0.847544   1.297656  1.458084  ... -3.064365   \n",
       "22842   1.871256  0.217633  3.125748   1.531443  2.627441  ...  1.939804   \n",
       "\n",
       "       16-01219  16-01223  16-01225  16-01227  16-01237   16-01254  16-01262  \\\n",
       "0     -1.896718  1.435855 -0.534799  0.509947 -0.830946  -2.923977 -0.998217   \n",
       "1      6.885383  7.166459  7.174516  6.500557  7.545959   6.882087  7.331555   \n",
       "2      3.871390  3.992470  3.648833  4.503911  3.148649   4.077574  3.734620   \n",
       "3      3.677613  2.523557  3.235564  3.197705  2.645294   3.115359  2.980670   \n",
       "4      4.877051  6.218219  4.355385  5.746346  6.857559  10.782979  6.045946   \n",
       "...         ...       ...       ...       ...       ...        ...       ...   \n",
       "22838  2.245470  3.521457  1.726353  1.182989  2.261786   0.625404  1.414241   \n",
       "22839  0.493073  0.752237  1.389106 -1.656215 -1.706690  -1.028051  0.771490   \n",
       "22840  4.583648  3.716998  3.213924  4.411679  4.070881   2.267735  3.317902   \n",
       "22841 -1.694540 -0.062792  0.468829 -1.758246 -1.802393   1.330709  0.942407   \n",
       "22842  3.383642  1.847791  3.356067  1.792823 -2.218280   1.404543  1.970785   \n",
       "\n",
       "       16-01270  16-01272  \n",
       "0     -0.964051 -1.042746  \n",
       "1      6.254707  6.641892  \n",
       "2      3.811903  3.235035  \n",
       "3      2.670554  3.341608  \n",
       "4      6.383498  9.366073  \n",
       "...         ...       ...  \n",
       "22838  3.181330  0.353361  \n",
       "22839 -0.029557 -1.826434  \n",
       "22840  3.403906  1.501366  \n",
       "22841 -2.446318 -2.597849  \n",
       "22842  2.286737  0.650829  \n",
       "\n",
       "[22843 rows x 454 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BeatAML_rnaseq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "51f30e3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "BeatAML_rnaseq[\"RNAseq_geneSymbol\"] = BeatAML_rnaseq['Gene']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f1dba49f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Gene</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>12-00023</th>\n",
       "      <th>12-00051</th>\n",
       "      <th>12-00066</th>\n",
       "      <th>12-00150</th>\n",
       "      <th>12-00211</th>\n",
       "      <th>12-00258</th>\n",
       "      <th>12-00294</th>\n",
       "      <th>...</th>\n",
       "      <th>16-01219</th>\n",
       "      <th>16-01223</th>\n",
       "      <th>16-01225</th>\n",
       "      <th>16-01227</th>\n",
       "      <th>16-01237</th>\n",
       "      <th>16-01254</th>\n",
       "      <th>16-01262</th>\n",
       "      <th>16-01270</th>\n",
       "      <th>16-01272</th>\n",
       "      <th>RNAseq_geneSymbol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>ENSG00000000003</td>\n",
       "      <td>TSPAN6</td>\n",
       "      <td>-1.562506</td>\n",
       "      <td>2.352541</td>\n",
       "      <td>-2.825696</td>\n",
       "      <td>1.688537</td>\n",
       "      <td>-3.272121</td>\n",
       "      <td>-3.561056</td>\n",
       "      <td>-3.287483</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.896718</td>\n",
       "      <td>1.435855</td>\n",
       "      <td>-0.534799</td>\n",
       "      <td>0.509947</td>\n",
       "      <td>-0.830946</td>\n",
       "      <td>-2.923977</td>\n",
       "      <td>-0.998217</td>\n",
       "      <td>-0.964051</td>\n",
       "      <td>-1.042746</td>\n",
       "      <td>ENSG00000000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>ENSG00000000419</td>\n",
       "      <td>DPM1</td>\n",
       "      <td>6.886609</td>\n",
       "      <td>6.438417</td>\n",
       "      <td>6.554495</td>\n",
       "      <td>6.852558</td>\n",
       "      <td>6.613863</td>\n",
       "      <td>7.045231</td>\n",
       "      <td>7.019496</td>\n",
       "      <td>...</td>\n",
       "      <td>6.885383</td>\n",
       "      <td>7.166459</td>\n",
       "      <td>7.174516</td>\n",
       "      <td>6.500557</td>\n",
       "      <td>7.545959</td>\n",
       "      <td>6.882087</td>\n",
       "      <td>7.331555</td>\n",
       "      <td>6.254707</td>\n",
       "      <td>6.641892</td>\n",
       "      <td>ENSG00000000419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>ENSG00000000457</td>\n",
       "      <td>SCYL3</td>\n",
       "      <td>3.817626</td>\n",
       "      <td>3.987133</td>\n",
       "      <td>3.207921</td>\n",
       "      <td>3.878230</td>\n",
       "      <td>4.528385</td>\n",
       "      <td>3.762908</td>\n",
       "      <td>4.514343</td>\n",
       "      <td>...</td>\n",
       "      <td>3.871390</td>\n",
       "      <td>3.992470</td>\n",
       "      <td>3.648833</td>\n",
       "      <td>4.503911</td>\n",
       "      <td>3.148649</td>\n",
       "      <td>4.077574</td>\n",
       "      <td>3.734620</td>\n",
       "      <td>3.811903</td>\n",
       "      <td>3.235035</td>\n",
       "      <td>ENSG00000000457</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 455 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0             Gene  Symbol  12-00023  12-00051  12-00066  \\\n",
       "0           0  ENSG00000000003  TSPAN6 -1.562506  2.352541 -2.825696   \n",
       "1           1  ENSG00000000419    DPM1  6.886609  6.438417  6.554495   \n",
       "2           2  ENSG00000000457   SCYL3  3.817626  3.987133  3.207921   \n",
       "\n",
       "   12-00150  12-00211  12-00258  12-00294  ...  16-01219  16-01223  16-01225  \\\n",
       "0  1.688537 -3.272121 -3.561056 -3.287483  ... -1.896718  1.435855 -0.534799   \n",
       "1  6.852558  6.613863  7.045231  7.019496  ...  6.885383  7.166459  7.174516   \n",
       "2  3.878230  4.528385  3.762908  4.514343  ...  3.871390  3.992470  3.648833   \n",
       "\n",
       "   16-01227  16-01237  16-01254  16-01262  16-01270  16-01272  \\\n",
       "0  0.509947 -0.830946 -2.923977 -0.998217 -0.964051 -1.042746   \n",
       "1  6.500557  7.545959  6.882087  7.331555  6.254707  6.641892   \n",
       "2  4.503911  3.148649  4.077574  3.734620  3.811903  3.235035   \n",
       "\n",
       "   RNAseq_geneSymbol  \n",
       "0    ENSG00000000003  \n",
       "1    ENSG00000000419  \n",
       "2    ENSG00000000457  \n",
       "\n",
       "[3 rows x 455 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BeatAML_rnaseq.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d2030c4f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(22843, 451)\n"
     ]
    }
   ],
   "source": [
    "BeatAML_rnaseq_matrix = BeatAML_rnaseq.iloc[0:,3:-1]\n",
    "BeatAML_rnaseq_matrix.index = list(BeatAML_rnaseq.iloc[0:,-1])\n",
    "\n",
    "print(BeatAML_rnaseq_matrix.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "35811523",
   "metadata": {},
   "outputs": [],
   "source": [
    "remain_indexs = []\n",
    "for index in range(0,BeatAML_rnaseq_matrix.shape[0] ):\n",
    "    cur_values = BeatAML_rnaseq_matrix.iloc[index,:].values\n",
    "    if len(cur_values[cur_values>0]) >= BeatAML_rnaseq_matrix.shape[1]/2:\n",
    "        remain_indexs.append(index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e39862ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17691\n"
     ]
    },
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>12-00023</th>\n",
       "      <th>12-00051</th>\n",
       "      <th>12-00066</th>\n",
       "      <th>12-00150</th>\n",
       "      <th>12-00211</th>\n",
       "      <th>12-00258</th>\n",
       "      <th>12-00294</th>\n",
       "      <th>12-00372</th>\n",
       "      <th>12-00423</th>\n",
       "      <th>12-00426</th>\n",
       "      <th>...</th>\n",
       "      <th>16-01216</th>\n",
       "      <th>16-01219</th>\n",
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       "      <th>16-01272</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ENSG00000000003</th>\n",
       "      <td>-1.562506</td>\n",
       "      <td>2.352541</td>\n",
       "      <td>-2.825696</td>\n",
       "      <td>1.688537</td>\n",
       "      <td>-3.272121</td>\n",
       "      <td>-3.561056</td>\n",
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       "      <td>-1.232077</td>\n",
       "      <td>-1.778046</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.382494</td>\n",
       "      <td>-1.896718</td>\n",
       "      <td>1.435855</td>\n",
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       "      <td>0.509947</td>\n",
       "      <td>-0.830946</td>\n",
       "      <td>-2.923977</td>\n",
       "      <td>-0.998217</td>\n",
       "      <td>-0.964051</td>\n",
       "      <td>-1.042746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000000419</th>\n",
       "      <td>6.886609</td>\n",
       "      <td>6.438417</td>\n",
       "      <td>6.554495</td>\n",
       "      <td>6.852558</td>\n",
       "      <td>6.613863</td>\n",
       "      <td>7.045231</td>\n",
       "      <td>7.019496</td>\n",
       "      <td>6.698076</td>\n",
       "      <td>6.565889</td>\n",
       "      <td>6.553925</td>\n",
       "      <td>...</td>\n",
       "      <td>7.203169</td>\n",
       "      <td>6.885383</td>\n",
       "      <td>7.166459</td>\n",
       "      <td>7.174516</td>\n",
       "      <td>6.500557</td>\n",
       "      <td>7.545959</td>\n",
       "      <td>6.882087</td>\n",
       "      <td>7.331555</td>\n",
       "      <td>6.254707</td>\n",
       "      <td>6.641892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000000457</th>\n",
       "      <td>3.817626</td>\n",
       "      <td>3.987133</td>\n",
       "      <td>3.207921</td>\n",
       "      <td>3.878230</td>\n",
       "      <td>4.528385</td>\n",
       "      <td>3.762908</td>\n",
       "      <td>4.514343</td>\n",
       "      <td>4.226222</td>\n",
       "      <td>3.606704</td>\n",
       "      <td>4.574380</td>\n",
       "      <td>...</td>\n",
       "      <td>3.611346</td>\n",
       "      <td>3.871390</td>\n",
       "      <td>3.992470</td>\n",
       "      <td>3.648833</td>\n",
       "      <td>4.503911</td>\n",
       "      <td>3.148649</td>\n",
       "      <td>4.077574</td>\n",
       "      <td>3.734620</td>\n",
       "      <td>3.811903</td>\n",
       "      <td>3.235035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000000460</th>\n",
       "      <td>2.437114</td>\n",
       "      <td>1.862662</td>\n",
       "      <td>3.368360</td>\n",
       "      <td>3.332284</td>\n",
       "      <td>2.984168</td>\n",
       "      <td>2.964634</td>\n",
       "      <td>3.479539</td>\n",
       "      <td>2.549459</td>\n",
       "      <td>3.011702</td>\n",
       "      <td>2.502817</td>\n",
       "      <td>...</td>\n",
       "      <td>2.245470</td>\n",
       "      <td>3.677613</td>\n",
       "      <td>2.523557</td>\n",
       "      <td>3.235564</td>\n",
       "      <td>3.197705</td>\n",
       "      <td>2.645294</td>\n",
       "      <td>3.115359</td>\n",
       "      <td>2.980670</td>\n",
       "      <td>2.670554</td>\n",
       "      <td>3.341608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000000938</th>\n",
       "      <td>10.131911</td>\n",
       "      <td>5.014124</td>\n",
       "      <td>10.139119</td>\n",
       "      <td>5.941063</td>\n",
       "      <td>7.274613</td>\n",
       "      <td>10.538451</td>\n",
       "      <td>8.762846</td>\n",
       "      <td>8.009340</td>\n",
       "      <td>8.170395</td>\n",
       "      <td>6.420402</td>\n",
       "      <td>...</td>\n",
       "      <td>9.715398</td>\n",
       "      <td>4.877051</td>\n",
       "      <td>6.218219</td>\n",
       "      <td>4.355385</td>\n",
       "      <td>5.746346</td>\n",
       "      <td>6.857559</td>\n",
       "      <td>10.782979</td>\n",
       "      <td>6.045946</td>\n",
       "      <td>6.383498</td>\n",
       "      <td>9.366073</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 451 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  12-00023  12-00051   12-00066  12-00150  12-00211  \\\n",
       "ENSG00000000003  -1.562506  2.352541  -2.825696  1.688537 -3.272121   \n",
       "ENSG00000000419   6.886609  6.438417   6.554495  6.852558  6.613863   \n",
       "ENSG00000000457   3.817626  3.987133   3.207921  3.878230  4.528385   \n",
       "ENSG00000000460   2.437114  1.862662   3.368360  3.332284  2.984168   \n",
       "ENSG00000000938  10.131911  5.014124  10.139119  5.941063  7.274613   \n",
       "\n",
       "                  12-00258  12-00294  12-00372  12-00423  12-00426  ...  \\\n",
       "ENSG00000000003  -3.561056 -3.287483 -0.149916 -1.232077 -1.778046  ...   \n",
       "ENSG00000000419   7.045231  7.019496  6.698076  6.565889  6.553925  ...   \n",
       "ENSG00000000457   3.762908  4.514343  4.226222  3.606704  4.574380  ...   \n",
       "ENSG00000000460   2.964634  3.479539  2.549459  3.011702  2.502817  ...   \n",
       "ENSG00000000938  10.538451  8.762846  8.009340  8.170395  6.420402  ...   \n",
       "\n",
       "                 16-01216  16-01219  16-01223  16-01225  16-01227  16-01237  \\\n",
       "ENSG00000000003 -0.382494 -1.896718  1.435855 -0.534799  0.509947 -0.830946   \n",
       "ENSG00000000419  7.203169  6.885383  7.166459  7.174516  6.500557  7.545959   \n",
       "ENSG00000000457  3.611346  3.871390  3.992470  3.648833  4.503911  3.148649   \n",
       "ENSG00000000460  2.245470  3.677613  2.523557  3.235564  3.197705  2.645294   \n",
       "ENSG00000000938  9.715398  4.877051  6.218219  4.355385  5.746346  6.857559   \n",
       "\n",
       "                  16-01254  16-01262  16-01270  16-01272  \n",
       "ENSG00000000003  -2.923977 -0.998217 -0.964051 -1.042746  \n",
       "ENSG00000000419   6.882087  7.331555  6.254707  6.641892  \n",
       "ENSG00000000457   4.077574  3.734620  3.811903  3.235035  \n",
       "ENSG00000000460   3.115359  2.980670  2.670554  3.341608  \n",
       "ENSG00000000938  10.782979  6.045946  6.383498  9.366073  \n",
       "\n",
       "[5 rows x 451 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(len(remain_indexs))\n",
    "\n",
    "BeatAML_rnaseq_matrix.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b2fa7f57",
   "metadata": {},
   "outputs": [],
   "source": [
    "BeatAML_rnaseq_matrix.iloc[remain_indexs,:].transpose().to_csv(\"../data/Feature_set3_RNAseq_matrix_w12.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "21b86dd4",
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_matrix = pd.concat([selected_merged_matrix, BeatAML_rnaseq_matrix.iloc[remain_indexs,:].transpose()], axis = 1, join = \"outer\")\n",
    "#feature_matrix_noNA = feature_matrix.dropna()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "eff758d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_matrix.to_csv(\"../Data/Feature_set123_merged_matrix_w12.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "8106a7e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(608, 22)\n",
      "(603, 18)\n",
      "(608, 40)\n",
      "(660, 17731)\n"
     ]
    }
   ],
   "source": [
    "# Ready to use features\n",
    "\n",
    "## 1. Feature set 1:\n",
    "print(selected_mutation_matrix.shape)\n",
    "\n",
    "## 2. Feature set 2:\n",
    "print(df_select_variants1.shape)\n",
    "\n",
    "## 3. Feature set 1 and 2: \n",
    "print(selected_merged_matrix.shape)\n",
    "\n",
    "## 4. Feature set 1, 2, and 3\n",
    "print(feature_matrix.shape)\n",
    "\n",
    "#selected_mutation_matrix.to_csv(\"../Data/Feature_set1_mutation_matrix_w12.csv\")\n",
    "#df_select_variants.to_csv(\"../Data/Feature_set2_variants_matrix_w12.csv\")\n",
    "#selected_merged_matrix.to_csv( \"../Data/Feature_set12_merged_matrix_w12.csv\")\n",
    "#feature_matrix.to_csv(\"../Data/Feature_set123_merged_matrix_w12.csv\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2cea48ba",
   "metadata": {},
   "source": [
    "# Generate feature and label matrix for IC50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "45d8d5b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#BeatAML_drug_response_ic50_matrix = convert_df2matrix_cont(BeatAML_drug_response, 'lab_id', 'inhibitor', 'ic50') \n",
    "BeatAML_drug_response_ic50_matrix = mc.convert_df2matrix_cont(BeatAML_drug_response, 'lab_id', 'inhibitor', 'ic50') \n",
    "beatAML_data_feature_ic50 = pd.concat([feature_matrix,BeatAML_drug_response_ic50_matrix], axis = 1, join = \"outer\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "8ce2ec56",
   "metadata": {},
   "outputs": [],
   "source": [
    "beatAML_data_feature_ic50.to_csv(\"../data/beatAML_wave12_feature_ic50_highExpr_Apr30_2024_w12.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c75d823",
   "metadata": {},
   "source": [
    "# Generate feature and label matrix for AUC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c349d360",
   "metadata": {},
   "outputs": [],
   "source": [
    "BeatAML_drug_response_auc_matrix = mc.convert_df2matrix_cont(BeatAML_drug_response, 'lab_id', 'inhibitor', 'auc') \n",
    "beatAML_data_feature_auc = pd.concat([feature_matrix,BeatAML_drug_response_auc_matrix], axis = 1, join = \"outer\")\n",
    "beatAML_data_feature_auc.to_csv(\"../Data/beatAML_wave12_feature_auc_highExpr_Apr30_2024_w12.csv\")"
   ]
  }
 ],
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