notebooks/Step0_Generate_feature_matrix_beatAML_wave1_4.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "056b2369",
   "metadata": {},
   "source": [
    "#### Processing Data of Beat AML data wave 3/4\n",
    "#### Data were downloaded from the paper for Beat AML data wave 3/4 (doi: 10.1016/j.ccell.2022.07.002)\n"
   ]
  },
  {
   "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 wave1/4 dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "760164c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "Data_dir = \"~/Documents/Datasets/AML/BeatAML-wave1-4/Beat AML collaborator files Waves 1-4/\"\n",
    "# read from xlsx file\n",
    "BeatAML_mut_w14 = pd.read_excel(Data_dir +\"mutations/beataml_wes_wv1to4_mutations_v4.xlsx\")\n",
    "# read tsv file\n",
    "BeatAML_drug_response_w14= pd.read_csv(Data_dir + \"inhibitor/beataml_probit_curve_fits_v4_distr_nonproprietary.txt\", sep = \"\\t\")\n",
    "BeatAML_rnaseq_w14 = pd.read_csv(Data_dir + \"rnaseq/beataml_waves1to4_allnorm.txt\", sep = \"\\t\")"
   ]
  },
  {
   "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",
      "4909\n",
      "The number of unique mutations in BeatAML_mut_s identified by mutect: \n",
      "3725\n",
      "The number of unique mutations in BeatAML_mut_s identified by varscan: \n",
      "3981\n",
      "The number of unique mutations in BeatAML_mut_s identified by both mutect and varscan: \n",
      "2797\n"
     ]
    }
   ],
   "source": [
    "BeatAML_mut_s = BeatAML_mut_w14.loc[:,['original_id','variant_classification',  '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": [],
   "source": [
    "# Convert gene mutation to a matrix\n",
    "BeatAML_mut_matrix = mc.convert_df2matrix_bi(BeatAML_mut_s,\"original_id\",\"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",
    "#selected_mutation_matrix.to_csv(\"Feature_set1_mutation_matrix_w14.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9e02123a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "603\n",
      "268\n"
     ]
    }
   ],
   "source": [
    "BeatAML_mut = BeatAML_mut_w14\n",
    "w12 = set(BeatAML_mut.loc[BeatAML_mut['wave'] == \"wave1+2\"]['original_id'])\n",
    "w34 = set(BeatAML_mut.loc[BeatAML_mut['wave'] == \"wave3+4\"]['original_id'])\n",
    "print(len(w12))\n",
    "print(len(w34))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "389304db",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1946, 33)\n"
     ]
    }
   ],
   "source": [
    "BeatAML_mut_34 = BeatAML_mut.loc[BeatAML_mut['original_id'].isin(w34)]\n",
    "print(BeatAML_mut_34.shape)\n",
    "#BeatAML_mut_34"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "dc5001c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(268, 22)\n"
     ]
    }
   ],
   "source": [
    "selected_mutation_matrix_34 = mc.convert_df2matrix_bi(BeatAML_mut_34,\"original_id\",\"symbol\")\n",
    "\n",
    "# Select highly frequent mutated genes\n",
    "selected_genes = []\n",
    "for gene in selected_mutation_matrix_34.columns:\n",
    "    if selected_mutation_matrix_34.loc[selected_mutation_matrix_34[gene] == 1].shape[0] >= 0.03*selected_mutation_matrix_34.shape[0]:\n",
    "        selected_genes.append(gene)\n",
    "\n",
    "selected_mutation_matrix_34 = selected_mutation_matrix_34[selected_genes]\n",
    "print(selected_mutation_matrix_34.shape)\n",
    "# Save the selected mutation matrix\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "89c26c71",
   "metadata": {},
   "outputs": [
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       "          FLT3  IDH2  KRAS  SRSF2  GATA2  BCOR  WT1  PDS5B  TET2  IDH1  ...  \\\n",
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       "...        ...   ...   ...    ...    ...   ...  ...    ...   ...   ...  ...   \n",
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       "\n",
       "          DNMT3A  NRAS  NF1  SF3B1  ASXL1  NPM1  RUNX1  CEBPA  PTPN11  STAG2  \n",
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       "...          ...   ...  ...    ...    ...   ...    ...    ...     ...    ...  \n",
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       "\n",
       "[268 rows x 22 columns]"
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     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "selected_mutation_matrix_34"
   ]
  },
  {
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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_34.sum(axis = 0)/selected_mutation_matrix_34.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_34.shape[0])+ \" ) with gene mutations\")\n",
    "plt.ylabel(\"Mutated genes\")\n",
    "plt.title(\"Frequency of gene mutations in BeatAML wave 3/4\")\n",
    "\n",
    "plt.xlim(0,30)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50ae34cc",
   "metadata": {},
   "source": [
    "# Select variants or regions with high mutation frequency\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "050a753e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['seqnames', 'pos_start', 'pos_end', 'ref', 'alt', 'genotyper', 'wave',\n",
       "       'seq_id', 'original_id', 'tumor_only', 'total_reads', 'allele_reads',\n",
       "       'normal_total_reads', 'normal_allele_reads', 't_vaf', 'n_vaf',\n",
       "       'variant_classification', 'hgvsp_short', 'gene', 'symbol', 'biotype',\n",
       "       'hgvsc', 'hgvsp', 'cdna_position', 'cds_position', 'protein_position',\n",
       "       'amino_acids', 'codons', 'existing_variation', 'refseq', 'sift',\n",
       "       'polyphen', 'exac_af'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BeatAML_mut.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7d33a7aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11721, 35)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "BeatAML_mut['new_id'] = BeatAML_mut['symbol'] +':'+ BeatAML_mut['hgvsp_short'] + ':' + BeatAML_mut['pos_start'].astype(str)\n",
    "BeatAML_mut['new_id_patient'] = BeatAML_mut['original_id'] + ':'+ BeatAML_mut['symbol'] +':'+ BeatAML_mut['hgvsp_short']\n",
    "BeatAML_mut.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2698b8e1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5498\n",
      "7607\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,34]\n",
    "\n",
    "    genotyper = BeatAML_mut.iloc[i,5]\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,34]\n",
    "\n",
    "    genotyper = BeatAML_mut.iloc[i,5]\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": 20,
   "id": "cd6aa436",
   "metadata": {},
   "outputs": [],
   "source": [
    "#BeatAML_mut_unique_vaf_w34 = BeatAML_mut_unique_vaf.loc[BeatAML_mut_unique_vaf['wave'] == \"wave3+4\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bc30be76",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "871\n",
      "871\n"
     ]
    }
   ],
   "source": [
    "print(len(set(BeatAML_mut_unique_vaf['original_id'].unique())))\n",
    "print(len(set(BeatAML_mut_unique_vaf['original_id'].unique())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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','original_id','t_vaf')\n",
    "BeatAML_mut_matrix_vaf = BeatAML_mut_matrix_vaf.transpose()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "683d1ea5",
   "metadata": {},
   "outputs": [],
   "source": [
    "BeatAML_mut_matrix_vaf_w34 = BeatAML_mut_matrix_vaf.loc[list(w34),:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9199e553",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['NPM1:p.W288Cfs*12:170837543', 'ASXL1:p.G645Vfs*58:31022441',\n",
       "       'NRAS:p.Q61H:115256528', 'SRSF2:p.P95L:74732959',\n",
       "       'NF1:p.I679Dfs*21:29553477', 'IDH2:p.R172K:90631838',\n",
       "       'NPM1:p.W288Cfs*12:170837545', 'IDH1:p.R132C:209113113',\n",
       "       'SF3B1:p.K700E:198266834', 'DNMT3A:p.R882H:25457242',\n",
       "       'U2AF1:p.Q157P:44514777', 'ASXL1:p.G646Wfs*12:31022441',\n",
       "       'IDH2:p.R140Q:90631934', 'U2AF1:p.S34F:44524456',\n",
       "       'IDH1:p.R132H:209113112', 'SRSF2:p.P95H:74732959',\n",
       "       'SRSF2:p.P95_R102del:74732935', 'JAK2:p.V617F:5073770',\n",
       "       'SF3B1:p.K666N:198267359', 'NRAS:p.G12D:115258747',\n",
       "       'NRAS:p.G13D:115258744', 'FLT3:p.I836del:28592634',\n",
       "       'NPM1:p.W288Cfs*12:170837544', 'KRAS:p.G12D:25398284',\n",
       "       'SRSF2:p.P95R:74732959', 'DNMT3A:p.R882C:25457243',\n",
       "       'KIT:p.D816V:55599321', 'PDS5B:p.V1024F:33332238',\n",
       "       'NRAS:p.Q61K:115256530', 'FLT3:p.D835Y:28592642',\n",
       "       'KRAS:p.G13D:25398281', 'FLT3:p.D835H:28592642',\n",
       "       'ZNF687:p.R939Pfs*36:151262327'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 18,
     "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": 19,
   "id": "5ed083b9",
   "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": 20,
   "id": "b733beb3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['DNMT3A:p.R882', 'ASXL1:p.G645-646', 'FLT3:p.835-839', 'IDH1:p.R132', 'IDH2:p.R140', 'IDH2:p.R172', 'JAK2:p.V617', 'KIT:p.D816', 'KRAS:p.G12/13', 'NPM1:p.W288-90', 'NRAS:p.G12/13', 'NRAS:p.Q61', 'SF3B1:p.K700E', 'SF3B1:p.K666', 'SRSF2:p.94-95', 'U2AF1:p.S34', 'U2AF1:p.156-157', 'ZNF687:p.R939Pfs*36:151262327'])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_variants.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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_w34[selected_variants[i]].sum(axis = 1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "867c8916",
   "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>13-00150</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>17-00187</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.192982</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>13-00092</th>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <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>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17-00551</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</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>0.400000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17-00319</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.108108</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</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>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <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",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13-00075</th>\n",
       "      <td>0.390625</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.743902</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13-00147</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</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>0.277778</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19-00154</th>\n",
       "      <td>0.491453</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</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>0.431373</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>17-00748</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17-00908</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.555556</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>268 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          DNMT3A:p.R882  ASXL1:p.G645-646  FLT3:p.835-839  IDH1:p.R132  \\\n",
       "13-00150       0.000000          0.000000        0.000000          0.0   \n",
       "17-00187       0.000000          0.000000        0.000000          0.0   \n",
       "13-00092       0.000000          0.000000        0.000000          0.0   \n",
       "17-00551       0.000000          0.000000        0.000000          0.0   \n",
       "17-00319       0.000000          0.108108        0.000000          0.0   \n",
       "...                 ...               ...             ...          ...   \n",
       "13-00075       0.390625          0.000000        0.743902          0.0   \n",
       "13-00147       0.000000          0.000000        0.000000          0.0   \n",
       "19-00154       0.491453          0.000000        0.000000          0.0   \n",
       "17-00748       0.000000          0.000000        0.000000          0.0   \n",
       "17-00908       0.000000          0.000000        0.000000          0.0   \n",
       "\n",
       "          IDH2:p.R140  IDH2:p.R172  JAK2:p.V617  KIT:p.D816  KRAS:p.G12/13  \\\n",
       "13-00150          0.0     0.000000          0.0         0.0            0.0   \n",
       "17-00187          0.0     0.000000          0.0         0.0            0.0   \n",
       "13-00092          0.0     0.000000          0.0         0.0            0.0   \n",
       "17-00551          0.0     0.000000          0.0         0.0            0.0   \n",
       "17-00319          0.0     0.000000          0.0         0.0            0.0   \n",
       "...               ...          ...          ...         ...            ...   \n",
       "13-00075          0.0     0.000000          0.0         0.0            0.0   \n",
       "13-00147          0.0     0.000000          0.0         0.0            0.0   \n",
       "19-00154          0.0     0.000000          0.0         0.0            0.0   \n",
       "17-00748          0.0     0.000000          0.0         0.0            0.0   \n",
       "17-00908          0.0     0.555556          0.0         0.0            0.0   \n",
       "\n",
       "          NPM1:p.W288-90  NRAS:p.G12/13  NRAS:p.Q61  SF3B1:p.K700E  \\\n",
       "13-00150        0.000000            0.0         0.0            0.0   \n",
       "17-00187        0.000000            0.0         0.0            0.0   \n",
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       "...                  ...            ...         ...            ...   \n",
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       "17-00748        0.000000            0.0         0.0            0.0   \n",
       "17-00908        0.000000            0.0         0.0            0.0   \n",
       "\n",
       "          SF3B1:p.K666  SRSF2:p.94-95  U2AF1:p.S34  U2AF1:p.156-157  \\\n",
       "13-00150           0.0       0.000000          0.0              0.0   \n",
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       "13-00092           0.0       0.000000          0.0              0.0   \n",
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       "...                ...            ...          ...              ...   \n",
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       "17-00748           0.0       0.000000          0.0              0.0   \n",
       "17-00908           0.0       0.000000          0.0              0.0   \n",
       "\n",
       "          ZNF687:p.R939Pfs*36:151262327  \n",
       "13-00150                            0.0  \n",
       "17-00187                            0.0  \n",
       "13-00092                            0.0  \n",
       "17-00551                            0.0  \n",
       "17-00319                            0.0  \n",
       "...                                 ...  \n",
       "13-00075                            0.0  \n",
       "13-00147                            0.0  \n",
       "19-00154                            0.0  \n",
       "17-00748                            0.0  \n",
       "17-00908                            0.0  \n",
       "\n",
       "[268 rows x 18 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_select_variants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d201ffaa",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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",
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       "</table>\n",
       "<p>268 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          DNMT3A:p.R882  ASXL1:p.G645-646  FLT3:p.835-839  IDH1:p.R132  \\\n",
       "13-00150       0.000000          0.000000        0.000000          0.0   \n",
       "17-00187       0.000000          0.000000        0.000000          0.0   \n",
       "13-00092       0.000000          0.000000        0.000000          0.0   \n",
       "17-00551       0.000000          0.000000        0.000000          0.0   \n",
       "17-00319       0.000000          0.108108        0.000000          0.0   \n",
       "...                 ...               ...             ...          ...   \n",
       "13-00075       0.390625          0.000000        0.743902          0.0   \n",
       "13-00147       0.000000          0.000000        0.000000          0.0   \n",
       "19-00154       0.491453          0.000000        0.000000          0.0   \n",
       "17-00748       0.000000          0.000000        0.000000          0.0   \n",
       "17-00908       0.000000          0.000000        0.000000          0.0   \n",
       "\n",
       "          IDH2:p.R140  IDH2:p.R172  JAK2:p.V617  KIT:p.D816  KRAS:p.G12/13  \\\n",
       "13-00150          0.0     0.000000          0.0         0.0            0.0   \n",
       "17-00187          0.0     0.000000          0.0         0.0            0.0   \n",
       "13-00092          0.0     0.000000          0.0         0.0            0.0   \n",
       "17-00551          0.0     0.000000          0.0         0.0            0.0   \n",
       "17-00319          0.0     0.000000          0.0         0.0            0.0   \n",
       "...               ...          ...          ...         ...            ...   \n",
       "13-00075          0.0     0.000000          0.0         0.0            0.0   \n",
       "13-00147          0.0     0.000000          0.0         0.0            0.0   \n",
       "19-00154          0.0     0.000000          0.0         0.0            0.0   \n",
       "17-00748          0.0     0.000000          0.0         0.0            0.0   \n",
       "17-00908          0.0     0.555556          0.0         0.0            0.0   \n",
       "\n",
       "          NPM1:p.W288-90  NRAS:p.G12/13  NRAS:p.Q61  SF3B1:p.K700E  \\\n",
       "13-00150        0.000000            0.0         0.0            0.0   \n",
       "17-00187        0.000000            0.0         0.0            0.0   \n",
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       "17-00551        0.400000            0.0         0.0            0.0   \n",
       "17-00319        0.000000            0.0         0.0            0.0   \n",
       "...                  ...            ...         ...            ...   \n",
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       "17-00748        0.000000            0.0         0.0            0.0   \n",
       "17-00908        0.000000            0.0         0.0            0.0   \n",
       "\n",
       "          SF3B1:p.K666  SRSF2:p.94-95  U2AF1:p.S34  U2AF1:p.156-157  \\\n",
       "13-00150           0.0       0.000000          0.0              0.0   \n",
       "17-00187           0.0       0.192982          0.0              0.0   \n",
       "13-00092           0.0       0.000000          0.0              0.0   \n",
       "17-00551           0.0       0.000000          0.0              0.0   \n",
       "17-00319           0.0       0.000000          0.0              0.0   \n",
       "...                ...            ...          ...              ...   \n",
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       "19-00154           0.0       0.000000          0.0              0.0   \n",
       "17-00748           0.0       0.000000          0.0              0.0   \n",
       "17-00908           0.0       0.000000          0.0              0.0   \n",
       "\n",
       "          ZNF687:p.R939Pfs*36:151262327  \n",
       "13-00150                            0.0  \n",
       "17-00187                            0.0  \n",
       "13-00092                            0.0  \n",
       "17-00551                            0.0  \n",
       "17-00319                            0.0  \n",
       "...                                 ...  \n",
       "13-00075                            0.0  \n",
       "13-00147                            0.0  \n",
       "19-00154                            0.0  \n",
       "17-00748                            0.0  \n",
       "17-00908                            0.0  \n",
       "\n",
       "[268 rows x 18 columns]"
      ]
     },
     "execution_count": 23,
     "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": 24,
   "id": "7d7c8d47",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(268, 18)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "NPM1:p.W288-90                   22.123437\n",
       "SRSF2:p.94-95                    14.461332\n",
       "DNMT3A:p.R882                    13.406682\n",
       "IDH2:p.R140                      13.126730\n",
       "ASXL1:p.G645-646                  7.396917\n",
       "IDH1:p.R132                       6.813941\n",
       "NRAS:p.Q61                        6.608028\n",
       "NRAS:p.G12/13                     6.526184\n",
       "FLT3:p.835-839                    5.446509\n",
       "U2AF1:p.S34                       5.406890\n",
       "KRAS:p.G12/13                     4.529595\n",
       "JAK2:p.V617                       4.107686\n",
       "SF3B1:p.K666                      3.195401\n",
       "IDH2:p.R172                       2.320944\n",
       "KIT:p.D816                        1.846102\n",
       "SF3B1:p.K700E                     1.558358\n",
       "U2AF1:p.156-157                   0.900000\n",
       "ZNF687:p.R939Pfs*36:151262327     0.707502\n",
       "dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(df_select_variants1.shape)\n",
    "df_select_variants1.sum(axis = 0).sort_values(ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "f97833f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_select_variants1.to_csv(\"../data/Feature_set2_variants_matrix_w12.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "971438fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(268, 18)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_select_variants_w34 = df_select_variants1.loc[list(w34),]\n",
    "print(df_select_variants_w34.shape)\n",
    "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_w34.loc[df_select_variants_w34[i] > 0].shape[0]/df_select_variants_w34.shape[0]*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(df_select_variants_w34.shape[0])+ \" ) with the selected variants\")\n",
    "plt.ylabel(\"Variants\")\n",
    "plt.title(\"Frequency in BeatAML wave 3/4\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "452da9c8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(268, 18)\n",
      "(871, 23)\n",
      "(871, 41)\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)\n",
    "print(selected_merged_matrix.shape)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7599e452",
   "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>ASXL1:p.G645-646</th>\n",
       "      <th>DNMT3A:p.R882</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.K666</th>\n",
       "      <th>SF3B1:p.K700E</th>\n",
       "      <th>SRSF2:p.94-95</th>\n",
       "      <th>U2AF1:p.156-157</th>\n",
       "      <th>U2AF1:p.S34</th>\n",
       "      <th>ZNF687:p.R939Pfs*36:151262327</th>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>268 rows × 18 columns</p>\n",
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      ],
      "text/plain": [
       "          ASXL1:p.G645-646  DNMT3A:p.R882  FLT3:p.835-839  IDH1:p.R132  \\\n",
       "13-00150          0.000000       0.000000        0.000000          0.0   \n",
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       "...                    ...            ...             ...          ...   \n",
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       "17-00908          0.000000       0.000000        0.000000          0.0   \n",
       "\n",
       "          IDH2:p.R140  IDH2:p.R172  JAK2:p.V617  KIT:p.D816  KRAS:p.G12/13  \\\n",
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       "17-00908          0.0     0.555556          0.0         0.0            0.0   \n",
       "\n",
       "          NPM1:p.W288-90  NRAS:p.G12/13  NRAS:p.Q61  SF3B1:p.K666  \\\n",
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       "...                  ...            ...         ...           ...   \n",
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       "13-00147        0.277778            0.0         0.0           0.0   \n",
       "19-00154        0.431373            0.0         0.0           0.0   \n",
       "17-00748        0.000000            0.0         0.0           0.0   \n",
       "17-00908        0.000000            0.0         0.0           0.0   \n",
       "\n",
       "          SF3B1:p.K700E  SRSF2:p.94-95  U2AF1:p.156-157  U2AF1:p.S34  \\\n",
       "13-00150            0.0       0.000000              0.0          0.0   \n",
       "17-00187            0.0       0.192982              0.0          0.0   \n",
       "13-00092            0.0       0.000000              0.0          0.0   \n",
       "17-00551            0.0       0.000000              0.0          0.0   \n",
       "17-00319            0.0       0.000000              0.0          0.0   \n",
       "...                 ...            ...              ...          ...   \n",
       "13-00075            0.0       0.000000              0.0          0.0   \n",
       "13-00147            0.0       0.000000              0.0          0.0   \n",
       "19-00154            0.0       0.000000              0.0          0.0   \n",
       "17-00748            0.0       0.000000              0.0          0.0   \n",
       "17-00908            0.0       0.000000              0.0          0.0   \n",
       "\n",
       "          ZNF687:p.R939Pfs*36:151262327  \n",
       "13-00150                            0.0  \n",
       "17-00187                            0.0  \n",
       "13-00092                            0.0  \n",
       "17-00551                            0.0  \n",
       "17-00319                            0.0  \n",
       "...                                 ...  \n",
       "13-00075                            0.0  \n",
       "13-00147                            0.0  \n",
       "19-00154                            0.0  \n",
       "17-00748                            0.0  \n",
       "17-00908                            0.0  \n",
       "\n",
       "[268 rows x 18 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_select_variants1.sort_index(axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "f5d4a18e",
   "metadata": {},
   "outputs": [
    {
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       "<p>268 rows × 22 columns</p>\n",
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      ],
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       "          ASXL1  BCOR  CEBPA  DNMT3A  FLT3  GATA2  IDH1  IDH2  KRAS  NF1  ...  \\\n",
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       "\n",
       "          PDS5B  PTPN11  RUNX1  SF3B1  SRSF2  STAG2  TET2  TP53  U2AF1  WT1  \n",
       "13-00150      0       0      0      0      0      0     0     1      0    0  \n",
       "17-00187      0       0      0      0      1      1     0     0      0    0  \n",
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       "...         ...     ...    ...    ...    ...    ...   ...   ...    ...  ...  \n",
       "13-00075      0       0      0      0      0      0     0     0      0    1  \n",
       "13-00147      0       0      0      0      0      0     0     0      0    0  \n",
       "19-00154      0       0      0      0      0      0     0     0      0    0  \n",
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       "\n",
       "[268 rows x 22 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_mutation_matrix_34.sort_index(axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "9eb8c7fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_merged_matrix = selected_mutation_matrix.join(df_select_variants1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "57f4fa7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_merged_matrix = selected_merged_matrix.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "525f25ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_merged_matrix.to_csv(\"../data/Feature_set12_merged_matrix_w1_4.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "046596df",
   "metadata": {},
   "outputs": [
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      "text/plain": [
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       "17-00908     0     0      0      0      0      1     1     0    0      0  ...   \n",
       "\n",
       "          KRAS:p.G12/13  NPM1:p.W288-90  NRAS:p.G12/13  NRAS:p.Q61  \\\n",
       "13-00150            0.0             0.0            0.0         0.0   \n",
       "16-00067            0.0             0.0            0.0         0.0   \n",
       "14-00597            0.0             0.0            0.0         0.0   \n",
       "16-00261            0.0             0.0            0.0         0.0   \n",
       "15-00353            0.0             0.0            0.0         0.0   \n",
       "...                 ...             ...            ...         ...   \n",
       "15-00302            0.0             0.0            0.0         0.0   \n",
       "14-00359            0.0             0.0            0.0         0.0   \n",
       "13-00202            0.0             0.0            0.0         0.0   \n",
       "15-00491            0.0             0.0            0.0         0.0   \n",
       "17-00908            0.0             0.0            0.0         0.0   \n",
       "\n",
       "          SF3B1:p.K700E  SF3B1:p.K666  SRSF2:p.94-95  U2AF1:p.S34  \\\n",
       "13-00150            0.0           0.0            0.0          0.0   \n",
       "16-00067            0.0           0.0            0.0          0.0   \n",
       "14-00597            0.0           0.0            0.0          0.0   \n",
       "16-00261            0.0           0.0            0.0          0.0   \n",
       "15-00353            0.0           0.0            0.0          0.0   \n",
       "...                 ...           ...            ...          ...   \n",
       "15-00302            0.0           0.0            0.0          0.0   \n",
       "14-00359            0.0           0.0            0.0          0.0   \n",
       "13-00202            0.0           0.0            0.0          0.0   \n",
       "15-00491            0.0           0.0            0.0          0.0   \n",
       "17-00908            0.0           0.0            0.0          0.0   \n",
       "\n",
       "          U2AF1:p.156-157  ZNF687:p.R939Pfs*36:151262327  \n",
       "13-00150              0.0                            0.0  \n",
       "16-00067              0.0                            0.0  \n",
       "14-00597              0.0                            0.0  \n",
       "16-00261              0.0                            0.0  \n",
       "15-00353              0.0                            0.0  \n",
       "...                   ...                            ...  \n",
       "15-00302              0.0                            0.0  \n",
       "14-00359              0.0                            0.0  \n",
       "13-00202              0.0                            0.0  \n",
       "15-00491              0.0                            0.0  \n",
       "17-00908              0.0                            0.0  \n",
       "\n",
       "[871 rows x 41 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_merged_matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "040707cc",
   "metadata": {},
   "source": [
    "## RNASeq data processing\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "51f30e3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "BeatAML_rnaseq_w14[\"RNAseq_geneSymbol\"] =BeatAML_rnaseq_w14['stable_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "d2030c4f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(23150, 707)\n"
     ]
    }
   ],
   "source": [
    "BeatAML_rnaseq_matrix = BeatAML_rnaseq_w14.iloc[0:,4:-1]\n",
    "BeatAML_rnaseq_matrix.index = list(BeatAML_rnaseq_w14.iloc[0:,-1])\n",
    "\n",
    "print(BeatAML_rnaseq_matrix.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "35811523",
   "metadata": {},
   "outputs": [],
   "source": [
    "# For the RNASeq data, we updated to the features to the genes with expression value (log(RPKM)) greater than 0 in at least 50% \n",
    "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": 39,
   "id": "b2fa7f57",
   "metadata": {},
   "outputs": [],
   "source": [
    "BeatAML_rnaseq_matrix.iloc[remain_indexs,:].transpose().to_csv(\"../Data/Feature_set3_RNAseq_matrix_w1_4.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "24b23b14",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(871, 41)\n",
      "(707, 19853)\n"
     ]
    }
   ],
   "source": [
    "print(selected_merged_matrix.shape)\n",
    "print(BeatAML_rnaseq_matrix.iloc[remain_indexs,:].transpose().shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "21859900",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(871, 41)\n",
      "(963, 19894)\n",
      "(615, 19894)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FLT3</th>\n",
       "      <th>KRAS</th>\n",
       "      <th>SRSF2</th>\n",
       "      <th>U2AF1</th>\n",
       "      <th>SF3B1</th>\n",
       "      <th>STAG2</th>\n",
       "      <th>IDH2</th>\n",
       "      <th>JAK2</th>\n",
       "      <th>WT1</th>\n",
       "      <th>PDS5B</th>\n",
       "      <th>...</th>\n",
       "      <th>ENSG00000273448</th>\n",
       "      <th>ENSG00000273449</th>\n",
       "      <th>ENSG00000273456</th>\n",
       "      <th>ENSG00000273464</th>\n",
       "      <th>ENSG00000273466</th>\n",
       "      <th>ENSG00000273472</th>\n",
       "      <th>ENSG00000273477</th>\n",
       "      <th>ENSG00000273483</th>\n",
       "      <th>ENSG00000273486</th>\n",
       "      <th>ENSG00000273488</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>13-00150</th>\n",
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       "      <td>...</td>\n",
       "      <td>3.911782</td>\n",
       "      <td>2.658031</td>\n",
       "      <td>3.490017</td>\n",
       "      <td>0.251223</td>\n",
       "      <td>4.278253</td>\n",
       "      <td>-1.224417</td>\n",
       "      <td>3.168143</td>\n",
       "      <td>0.733848</td>\n",
       "      <td>4.112790</td>\n",
       "      <td>2.643124</td>\n",
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       "      <td>...</td>\n",
       "      <td>2.949857</td>\n",
       "      <td>4.160344</td>\n",
       "      <td>3.102009</td>\n",
       "      <td>2.397161</td>\n",
       "      <td>4.038282</td>\n",
       "      <td>3.264091</td>\n",
       "      <td>1.602231</td>\n",
       "      <td>-1.932429</td>\n",
       "      <td>4.791826</td>\n",
       "      <td>2.162298</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.393040</td>\n",
       "      <td>2.134847</td>\n",
       "      <td>3.251115</td>\n",
       "      <td>2.485959</td>\n",
       "      <td>4.514150</td>\n",
       "      <td>2.531049</td>\n",
       "      <td>-0.238150</td>\n",
       "      <td>1.650952</td>\n",
       "      <td>3.703548</td>\n",
       "      <td>2.974672</td>\n",
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       "    <tr>\n",
       "      <th>15-00353</th>\n",
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       "      <td>...</td>\n",
       "      <td>1.615126</td>\n",
       "      <td>1.556277</td>\n",
       "      <td>2.775945</td>\n",
       "      <td>0.130639</td>\n",
       "      <td>3.821515</td>\n",
       "      <td>-0.052933</td>\n",
       "      <td>3.957142</td>\n",
       "      <td>-0.704206</td>\n",
       "      <td>4.587060</td>\n",
       "      <td>3.162867</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 19894 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          FLT3  KRAS  SRSF2  U2AF1  SF3B1  STAG2  IDH2  JAK2  WT1  PDS5B  ...  \\\n",
       "13-00150   0.0   0.0    0.0    0.0    0.0    0.0   0.0   0.0  0.0    0.0  ...   \n",
       "16-00067   0.0   0.0    0.0    0.0    0.0    0.0   1.0   0.0  0.0    0.0  ...   \n",
       "14-00597   0.0   0.0    0.0    0.0    0.0    0.0   0.0   0.0  0.0    0.0  ...   \n",
       "15-00353   0.0   0.0    0.0    0.0    0.0    0.0   0.0   1.0  0.0    0.0  ...   \n",
       "\n",
       "          ENSG00000273448  ENSG00000273449  ENSG00000273456  ENSG00000273464  \\\n",
       "13-00150         3.911782         2.658031         3.490017         0.251223   \n",
       "16-00067         2.949857         4.160344         3.102009         2.397161   \n",
       "14-00597         2.393040         2.134847         3.251115         2.485959   \n",
       "15-00353         1.615126         1.556277         2.775945         0.130639   \n",
       "\n",
       "          ENSG00000273466  ENSG00000273472  ENSG00000273477  ENSG00000273483  \\\n",
       "13-00150         4.278253        -1.224417         3.168143         0.733848   \n",
       "16-00067         4.038282         3.264091         1.602231        -1.932429   \n",
       "14-00597         4.514150         2.531049        -0.238150         1.650952   \n",
       "15-00353         3.821515        -0.052933         3.957142        -0.704206   \n",
       "\n",
       "          ENSG00000273486  ENSG00000273488  \n",
       "13-00150         4.112790         2.643124  \n",
       "16-00067         4.791826         2.162298  \n",
       "14-00597         3.703548         2.974672  \n",
       "15-00353         4.587060         3.162867  \n",
       "\n",
       "[4 rows x 19894 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(selected_merged_matrix.shape)\n",
    "feature_matrix = pd.concat([selected_merged_matrix, BeatAML_rnaseq_matrix.iloc[remain_indexs,:].transpose()], axis = 1,join=\"outer\")\n",
    "print(feature_matrix.shape)\n",
    "print(feature_matrix.dropna().shape)\n",
    "feature_matrix.dropna().head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "21b86dd4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#feature_matrix_noNA = feature_matrix.dropna()\n",
    "feature_matrix.to_csv(\"../Data/Feature_set123_merged_matrix_w1_4.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "8106a7e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(871, 23)\n",
      "(268, 18)\n",
      "(871, 41)\n",
      "(963, 19894)\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": 45,
   "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_w14, 'lab_id', 'inhibitor', 'ic50') \n",
    "beatAML_data_feature_ic50 = pd.concat([feature_matrix,BeatAML_drug_response_ic50_matrix], axis = 1,join = \"outer\")\n",
    "beatAML_data_feature_ic50.to_csv(\"../data/beatAML_wave14_feature_ic50_highExpr_Mar19_2024_w1_4.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "44d30886",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DNMT3A:p.R882                    13.406682\n",
       "ASXL1:p.G645-646                  7.396917\n",
       "FLT3:p.835-839                    5.446509\n",
       "IDH1:p.R132                       6.813941\n",
       "IDH2:p.R140                      13.126730\n",
       "IDH2:p.R172                       2.320944\n",
       "JAK2:p.V617                       4.107686\n",
       "KIT:p.D816                        1.846102\n",
       "KRAS:p.G12/13                     4.529595\n",
       "NPM1:p.W288-90                   22.123437\n",
       "NRAS:p.G12/13                     6.526184\n",
       "NRAS:p.Q61                        6.608028\n",
       "SF3B1:p.K700E                     1.558358\n",
       "SF3B1:p.K666                      3.195401\n",
       "SRSF2:p.94-95                    14.461332\n",
       "U2AF1:p.S34                       5.406890\n",
       "U2AF1:p.156-157                   0.900000\n",
       "ZNF687:p.R939Pfs*36:151262327     0.707502\n",
       "dtype: float64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beatAML_data_feature_ic50.loc[:,['DNMT3A:p.R882', 'ASXL1:p.G645-646', 'FLT3:p.835-839', 'IDH1:p.R132',\n",
    "       'IDH2:p.R140', 'IDH2:p.R172', 'JAK2:p.V617', 'KIT:p.D816',\n",
    "       'KRAS:p.G12/13', 'NPM1:p.W288-90', 'NRAS:p.G12/13', 'NRAS:p.Q61',\n",
    "       'SF3B1:p.K700E', 'SF3B1:p.K666', 'SRSF2:p.94-95', 'U2AF1:p.S34',\n",
    "       'U2AF1:p.156-157', 'ZNF687:p.R939Pfs*36:151262327']].sum(axis = 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c75d823",
   "metadata": {},
   "source": [
    "# Generate feature and label matrix for AUC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "c349d360",
   "metadata": {},
   "outputs": [],
   "source": [
    "BeatAML_drug_response_auc_matrix = mc.convert_df2matrix_cont(BeatAML_drug_response_w14, '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_wave14_feature_auc_highExpr_Mar19_2024_w1_4.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d92271c1",
   "metadata": {},
   "source": []
  }
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