notebooks/Step0_Generate_feature_matrix_Finland.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "056b2369",
   "metadata": {},
   "source": [
    "##### This notebook is used to formating the datasets from "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d6193cd9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matrix_convert as mc\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "17985210",
   "metadata": {},
   "outputs": [],
   "source": [
    "Data_dir = '~/Documents/GitHub_project/AML_BeatAML/project/Data_resource/FIMM/'\n",
    "FIMM_mut = pd.read_csv(Data_dir + 'File_6_Binary_mutation_225S_57G.xlsx.Sheet1.csv', index_col = 'Unnamed: 0')\n",
    "FIMM_cli = pd.read_csv(Data_dir + 'File_1.1_Clinical_summary_186_Patients.xlsx.ClinicalSummary.csv')\n",
    "FIMM_DR = pd.read_csv(Data_dir + 'File_3.2_Drug_response_DSS_sDSS_164S_17Healthy.xlsx.Table7.csv')\n",
    "FIMM_RNASeq = pd.read_csv(Data_dir + 'File_7_RNA_seq_CPM_163S_4Healthy.csv', index_col=\"Unnamed: 0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a58f8b7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NPM1</th>\n",
       "      <th>DNMT3A</th>\n",
       "      <th>IDH2</th>\n",
       "      <th>MAML2</th>\n",
       "      <th>FLT3</th>\n",
       "      <th>AR</th>\n",
       "      <th>NRAS</th>\n",
       "      <th>WT1</th>\n",
       "      <th>ASXL1</th>\n",
       "      <th>RUNX1</th>\n",
       "      <th>...</th>\n",
       "      <th>SMC3</th>\n",
       "      <th>WRN</th>\n",
       "      <th>WWTR1</th>\n",
       "      <th>ARID1B</th>\n",
       "      <th>CLTC</th>\n",
       "      <th>EZH2</th>\n",
       "      <th>KDM6A</th>\n",
       "      <th>MTOR</th>\n",
       "      <th>RBM10</th>\n",
       "      <th>STIL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AML_081_01</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AML_033_03</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AML_033_02</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            NPM1  DNMT3A  IDH2  MAML2  FLT3  AR  NRAS  WT1  ASXL1  RUNX1  ...  \\\n",
       "AML_081_01     1       1     0      0     0   0     0    0      0      0  ...   \n",
       "AML_033_03     1       1     0      0     0   0     0    0      0      0  ...   \n",
       "AML_033_02     1       1     0      0     0   0     0    0      0      0  ...   \n",
       "\n",
       "            SMC3  WRN  WWTR1  ARID1B  CLTC  EZH2  KDM6A  MTOR  RBM10  STIL  \n",
       "AML_081_01     0    0      0       0     0     0      0     0      0     0  \n",
       "AML_033_03     0    0      0       0     0     0      0     0      1     0  \n",
       "AML_033_02     0    0      0       0     0     0      0     0      1     0  \n",
       "\n",
       "[3 rows x 57 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FIMM_mut_matrix = FIMM_mut.transpose()\n",
    "FIMM_mut_matrix.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "009fce7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>EC50</th>\n",
       "      <th>DSS</th>\n",
       "      <th>log_EC50</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sample_ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AML_079_01</th>\n",
       "      <td>0.3</td>\n",
       "      <td>30.0</td>\n",
       "      <td>-1.203973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AML_083_01</th>\n",
       "      <td>1.8</td>\n",
       "      <td>39.4</td>\n",
       "      <td>0.587787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AML_084_02</th>\n",
       "      <td>23.6</td>\n",
       "      <td>22.9</td>\n",
       "      <td>3.161247</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            EC50   DSS  log_EC50\n",
       "Sample_ID                       \n",
       "AML_079_01   0.3  30.0 -1.203973\n",
       "AML_083_01   1.8  39.4  0.587787\n",
       "AML_084_02  23.6  22.9  3.161247"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cur_drug = 'Venetoclax'\n",
    "FIMM_DR_cur_drug = FIMM_DR.loc[FIMM_DR['Chemical_compound']==cur_drug, ['Sample_ID','EC50', 'DSS', 'log_EC50']]\n",
    "FIMM_DR_cur_drug.index = FIMM_DR_cur_drug['Sample_ID']\n",
    "FIMM_DR_cur_drug = FIMM_DR_cur_drug.drop(columns = 'Sample_ID')\n",
    "FIMM_DR_cur_drug.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3aca4c36",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ENSG00000000003</th>\n",
       "      <th>ENSG00000000005</th>\n",
       "      <th>ENSG00000000419</th>\n",
       "      <th>ENSG00000000457</th>\n",
       "      <th>ENSG00000000460</th>\n",
       "      <th>ENSG00000000938</th>\n",
       "      <th>ENSG00000000971</th>\n",
       "      <th>ENSG00000001036</th>\n",
       "      <th>ENSG00000001084</th>\n",
       "      <th>ENSG00000001167</th>\n",
       "      <th>...</th>\n",
       "      <th>ENSG00000282034</th>\n",
       "      <th>ENSG00000282218</th>\n",
       "      <th>ENSG00000282246</th>\n",
       "      <th>ENSG00000282278</th>\n",
       "      <th>ENSG00000282301</th>\n",
       "      <th>ENSG00000282558</th>\n",
       "      <th>ENSG00000282608</th>\n",
       "      <th>ENSG00000282682</th>\n",
       "      <th>ENSG00000282804</th>\n",
       "      <th>ENSG00000282815</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AML_084_01</th>\n",
       "      <td>0.763342</td>\n",
       "      <td>0.031207</td>\n",
       "      <td>5.427380</td>\n",
       "      <td>5.473681</td>\n",
       "      <td>5.494689</td>\n",
       "      <td>4.202562</td>\n",
       "      <td>6.370664</td>\n",
       "      <td>4.368549</td>\n",
       "      <td>5.271645</td>\n",
       "      <td>5.708440</td>\n",
       "      <td>...</td>\n",
       "      <td>5.528521</td>\n",
       "      <td>3.429405</td>\n",
       "      <td>4.851682</td>\n",
       "      <td>5.884019</td>\n",
       "      <td>0.381969</td>\n",
       "      <td>3.600998</td>\n",
       "      <td>1.575122</td>\n",
       "      <td>1.971743</td>\n",
       "      <td>3.296012</td>\n",
       "      <td>-0.025491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AML_084_03</th>\n",
       "      <td>3.567312</td>\n",
       "      <td>0.071181</td>\n",
       "      <td>6.151697</td>\n",
       "      <td>5.917921</td>\n",
       "      <td>5.714683</td>\n",
       "      <td>3.005208</td>\n",
       "      <td>5.251795</td>\n",
       "      <td>4.196382</td>\n",
       "      <td>5.652702</td>\n",
       "      <td>5.952670</td>\n",
       "      <td>...</td>\n",
       "      <td>5.627161</td>\n",
       "      <td>4.843229</td>\n",
       "      <td>5.641565</td>\n",
       "      <td>7.068436</td>\n",
       "      <td>0.495412</td>\n",
       "      <td>3.054641</td>\n",
       "      <td>0.247448</td>\n",
       "      <td>1.771945</td>\n",
       "      <td>3.010628</td>\n",
       "      <td>-0.025491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AML_086_02</th>\n",
       "      <td>0.149730</td>\n",
       "      <td>0.024696</td>\n",
       "      <td>5.719492</td>\n",
       "      <td>4.542656</td>\n",
       "      <td>4.327447</td>\n",
       "      <td>3.899219</td>\n",
       "      <td>4.098220</td>\n",
       "      <td>4.452957</td>\n",
       "      <td>5.250376</td>\n",
       "      <td>5.837264</td>\n",
       "      <td>...</td>\n",
       "      <td>6.450077</td>\n",
       "      <td>2.801679</td>\n",
       "      <td>4.993588</td>\n",
       "      <td>6.189583</td>\n",
       "      <td>0.519943</td>\n",
       "      <td>4.587421</td>\n",
       "      <td>1.162421</td>\n",
       "      <td>1.493100</td>\n",
       "      <td>1.187590</td>\n",
       "      <td>0.025491</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 18202 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ENSG00000000003  ENSG00000000005  ENSG00000000419  \\\n",
       "AML_084_01         0.763342         0.031207         5.427380   \n",
       "AML_084_03         3.567312         0.071181         6.151697   \n",
       "AML_086_02         0.149730         0.024696         5.719492   \n",
       "\n",
       "            ENSG00000000457  ENSG00000000460  ENSG00000000938  \\\n",
       "AML_084_01         5.473681         5.494689         4.202562   \n",
       "AML_084_03         5.917921         5.714683         3.005208   \n",
       "AML_086_02         4.542656         4.327447         3.899219   \n",
       "\n",
       "            ENSG00000000971  ENSG00000001036  ENSG00000001084  \\\n",
       "AML_084_01         6.370664         4.368549         5.271645   \n",
       "AML_084_03         5.251795         4.196382         5.652702   \n",
       "AML_086_02         4.098220         4.452957         5.250376   \n",
       "\n",
       "            ENSG00000001167  ...  ENSG00000282034  ENSG00000282218  \\\n",
       "AML_084_01         5.708440  ...         5.528521         3.429405   \n",
       "AML_084_03         5.952670  ...         5.627161         4.843229   \n",
       "AML_086_02         5.837264  ...         6.450077         2.801679   \n",
       "\n",
       "            ENSG00000282246  ENSG00000282278  ENSG00000282301  \\\n",
       "AML_084_01         4.851682         5.884019         0.381969   \n",
       "AML_084_03         5.641565         7.068436         0.495412   \n",
       "AML_086_02         4.993588         6.189583         0.519943   \n",
       "\n",
       "            ENSG00000282558  ENSG00000282608  ENSG00000282682  \\\n",
       "AML_084_01         3.600998         1.575122         1.971743   \n",
       "AML_084_03         3.054641         0.247448         1.771945   \n",
       "AML_086_02         4.587421         1.162421         1.493100   \n",
       "\n",
       "            ENSG00000282804  ENSG00000282815  \n",
       "AML_084_01         3.296012        -0.025491  \n",
       "AML_084_03         3.010628        -0.025491  \n",
       "AML_086_02         1.187590         0.025491  \n",
       "\n",
       "[3 rows x 18202 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FIMM_RNASeq_matrix = FIMM_RNASeq.transpose()\n",
    "FIMM_RNASeq_matrix.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "322c0744",
   "metadata": {},
   "outputs": [],
   "source": [
    "GE = pd.read_csv(\"/Users/guangrong/Documents/GitHub_project/AML_BeatAML/project/Data_resource/RPKM.csv\",index_col = \"Unnamed: 0\")\n",
    "\n",
    "GE.index = GE['Gene']\n",
    "gene_map = GE.loc[:,['Gene','Symbol']]\n",
    "dic_gene_map = {}\n",
    "for i in range(0,gene_map.shape[0]):\n",
    "    dic_gene_map[gene_map.iloc[i,0]] = gene_map.iloc[i,1]\n",
    "    dic_gene_map[gene_map.iloc[i,1]] = gene_map.iloc[i,0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cb47ea1b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "44\n"
     ]
    }
   ],
   "source": [
    "sele_house_keeping = ['RPS10','FNTA','COX6A1','BECN1', 'SF3B2','PSMB2','AUP1','SRP14','HNRNPK', 'CCNI', 'RHOA', 'PABPC1','RPS11','TPT1','FTL']\n",
    "#KG_expr_resp = pd.read_csv(\"./Data/Supplementary_table_1_KG_Expr_drug_lasso_Coef_features_over0_gt50p.csv\")\n",
    "KG_expr_resp = pd.read_csv(\"../Data/Supplementary_table_1_KG_Expr_drug_lasso_Coef_features_over0_gt50p.csv\")\n",
    "#KG_reg = pd.read_csv(\"../Data/KG_regulatory_graph_Mar1_2023.csv\")\n",
    "KG_reg = pd.read_csv(\"../Data/KG_regulatory_graph_Mar11_2024.csv\")\n",
    "\n",
    "\n",
    "#Drug = \"Trametinib (GSK1120212)\"\n",
    "#Drug = \"Selumetinib (AZD6244)\"\n",
    "Drug = \"Venetoclax\"\n",
    "#Drug = \"Vandetanib (ZD6474)\"\n",
    "#Drug = \"Idelalisib\"\n",
    "res1 = KG_expr_resp.loc[KG_expr_resp['Drug'] == Drug]\n",
    "res1 = res1.sort_values(by = ['coef'])\n",
    "predictors = list(res1['Gene'])\n",
    "predictors.remove(Drug+\"_RSS\")\n",
    "predictors.remove(Drug+\"_intercept\")\n",
    "\n",
    "# Selection of the second neighbors\n",
    "#res2 = KG_reg.loc[KG_reg['Target_gene'].isin( predictors[0:5] +  predictors[len(predictors)-5:len(predictors)])]\n",
    "res2 = KG_reg.loc[KG_reg['Target_gene'].isin( predictors)]\n",
    "res2 = res2.loc[res2['Coef'] <0]\n",
    "\n",
    "selected_genes = list(KG_expr_resp.loc[KG_expr_resp['Drug'] == Drug]['Symbol'])\n",
    "selected_genes.remove(Drug+\"_RSS\")\n",
    "selected_genes.remove(Drug+\"_intercept\")\n",
    "print(len(selected_genes))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5c14f5aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Formating house keeping gene ids\n",
    "sele_house_keeping_id = []\n",
    "selected_genes_id = []\n",
    "\n",
    "for g in selected_genes:\n",
    "    selected_genes_id.append(dic_gene_map[g])\n",
    "    \n",
    "for g in sele_house_keeping:\n",
    "    if g in dic_gene_map:\n",
    "        sele_house_keeping_id.append(dic_gene_map[g])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b7239bbb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "44\n",
      "30\n",
      "15\n",
      "15\n"
     ]
    }
   ],
   "source": [
    "print(len(selected_genes_id))\n",
    "selected_genes_id = list(set(selected_genes_id).intersection(set(FIMM_RNASeq_matrix.columns)))\n",
    "print(len(selected_genes_id))\n",
    "\n",
    "print(len(sele_house_keeping_id))\n",
    "sele_house_keeping_id = list(set(sele_house_keeping_id).intersection(set(FIMM_RNASeq_matrix.columns)))\n",
    "print(len(sele_house_keeping_id))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8323c3c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "FIMM_RNASeq_matrix_t = FIMM_RNASeq_matrix.transpose()\n",
    "new_feature_df_FIMM = mc.formating_relative_expression(FIMM_RNASeq_matrix_t,selected_genes_id, sele_house_keeping_id, KG_reg, dic_gene_map= dic_gene_map)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "fbdb9b23",
   "metadata": {},
   "outputs": [
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       "      <td>0</td>\n",
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       "    <tr>\n",
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       "                NIPBL-PSMB2  NIPBL-HNRNPK  NIPBL-CCNI  NIPBL-COX6A1  \\\n",
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       "...                     ...           ...         ...           ...   \n",
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       "\n",
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       "\n",
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       "AML_084_01               0           0             0            0   \n",
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       "AML_086_02               0           0             0            0   \n",
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       "...                    ...         ...           ...          ...   \n",
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       "\n",
       "                ACOT9-RPS11  ACOT9-SF3B2  ACOT9-TPT1  \n",
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       "AML_086_02                0            0           0  \n",
       "AML_089_01                0            0           0  \n",
       "AML_019_01                0            0           0  \n",
       "...                     ...          ...         ...  \n",
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       "\n",
       "[167 rows x 450 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_feature_df_FIMM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "5ed083b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_matrix = pd.concat([FIMM_mut_matrix, FIMM_RNASeq_matrix, new_feature_df_FIMM,FIMM_DR_cur_drug], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "c15a00b5",
   "metadata": {},
   "outputs": [
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       "      <td>1.0</td>\n",
       "      <td>1.0</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",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</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",
       "      <td>0.0</td>\n",
       "      <td>366.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>5.902633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AML_122_01</th>\n",
       "      <td>1.0</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",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</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",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>6.907755</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>AML_045_01</th>\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",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</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",
       "      <td>0.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>23.2</td>\n",
       "      <td>3.637586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AML_051_01</th>\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",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</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",
       "      <td>0.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>17.6</td>\n",
       "      <td>4.941642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AML_054_01</th>\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",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</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",
       "      <td>0.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>38.5</td>\n",
       "      <td>1.193922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AML_065_01</th>\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",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</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",
       "      <td>0.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>24.2</td>\n",
       "      <td>1.308333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AML_067_01</th>\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",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</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",
       "      <td>0.0</td>\n",
       "      <td>87.5</td>\n",
       "      <td>12.7</td>\n",
       "      <td>4.471639</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>106 rows × 18712 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            NPM1  DNMT3A  IDH2  MAML2  FLT3   AR  NRAS  WT1  ASXL1  RUNX1  \\\n",
       "AML_033_02   1.0     1.0   0.0    0.0   0.0  0.0   0.0  0.0    0.0    0.0   \n",
       "AML_033_01   1.0     1.0   0.0    0.0   0.0  0.0   0.0  0.0    0.0    0.0   \n",
       "AML_052_01   1.0     0.0   0.0    0.0   0.0  0.0   0.0  0.0    0.0    0.0   \n",
       "AML_119_01   1.0     1.0   1.0    0.0   0.0  0.0   0.0  0.0    0.0    0.0   \n",
       "AML_122_01   1.0     0.0   0.0    0.0   0.0  0.0   0.0  0.0    1.0    0.0   \n",
       "...          ...     ...   ...    ...   ...  ...   ...  ...    ...    ...   \n",
       "AML_045_01   0.0     0.0   0.0    0.0   0.0  0.0   0.0  0.0    0.0    0.0   \n",
       "AML_051_01   0.0     0.0   0.0    0.0   0.0  0.0   0.0  0.0    0.0    0.0   \n",
       "AML_054_01   0.0     0.0   0.0    0.0   0.0  0.0   0.0  0.0    0.0    0.0   \n",
       "AML_065_01   0.0     0.0   0.0    0.0   0.0  0.0   0.0  0.0    0.0    0.0   \n",
       "AML_067_01   0.0     0.0   0.0    0.0   0.0  0.0   0.0  0.0    0.0    0.0   \n",
       "\n",
       "            ...  ACOT9-FNTA  ACOT9-RHOA  ACOT9-PABPC1  ACOT9-SRP14  \\\n",
       "AML_033_02  ...         0.0         0.0           0.0          0.0   \n",
       "AML_033_01  ...         0.0         0.0           0.0          0.0   \n",
       "AML_052_01  ...         0.0         0.0           0.0          0.0   \n",
       "AML_119_01  ...         1.0         0.0           0.0          0.0   \n",
       "AML_122_01  ...         1.0         0.0           0.0          0.0   \n",
       "...         ...         ...         ...           ...          ...   \n",
       "AML_045_01  ...         0.0         0.0           0.0          0.0   \n",
       "AML_051_01  ...         0.0         0.0           0.0          0.0   \n",
       "AML_054_01  ...         0.0         0.0           0.0          0.0   \n",
       "AML_065_01  ...         0.0         0.0           0.0          0.0   \n",
       "AML_067_01  ...         0.0         0.0           0.0          0.0   \n",
       "\n",
       "            ACOT9-RPS11  ACOT9-SF3B2  ACOT9-TPT1    EC50   DSS  log_EC50  \n",
       "AML_033_02          0.0          0.0         0.0   101.7   3.5  4.622027  \n",
       "AML_033_01          0.0          0.0         0.0    24.0  10.8  3.178054  \n",
       "AML_052_01          0.0          0.0         0.0   250.5   2.1  5.523459  \n",
       "AML_119_01          0.0          0.0         0.0   366.0   2.3  5.902633  \n",
       "AML_122_01          0.0          0.0         0.0  1000.0   0.3  6.907755  \n",
       "...                 ...          ...         ...     ...   ...       ...  \n",
       "AML_045_01          0.0          0.0         0.0    38.0  23.2  3.637586  \n",
       "AML_051_01          0.0          0.0         0.0   140.0  17.6  4.941642  \n",
       "AML_054_01          0.0          0.0         0.0     3.3  38.5  1.193922  \n",
       "AML_065_01          0.0          0.0         0.0     3.7  24.2  1.308333  \n",
       "AML_067_01          0.0          0.0         0.0    87.5  12.7  4.471639  \n",
       "\n",
       "[106 rows x 18712 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_matrix.loc[feature_matrix['EC50']> 0, ].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "21b86dd4",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "feature_matrix.loc[feature_matrix['EC50']> 0, ].dropna().to_csv(\"../Data/feature_matrix_FIMM_venetoclax.csv\")"
   ]
  }
 ],
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