{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quick Start Guide\n",
    "This notebook demonstrates the core functionality of the BioNeuralNet package. It covers data loading, network generation, network embedding via GNNs, subject representation integration, downstream disease prediction, evaluation metrics, clustering, and use of external tools.\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### BioNeuralNet offers a number of classes and functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bioneuralnet.downstream_task import SubjectRepresentation\n",
    "from bioneuralnet.downstream_task import DPMON\n",
    "from bioneuralnet.clustering import CorrelatedPageRank\n",
    "from bioneuralnet.clustering import CorrelatedLouvain\n",
    "from bioneuralnet.clustering import HybridLouvain\n",
    "\n",
    "from bioneuralnet.metrics import omics_correlation\n",
    "from bioneuralnet.metrics import cluster_correlation\n",
    "from bioneuralnet.metrics import louvain_to_adjacency\n",
    "from bioneuralnet.metrics import evaluate_rf\n",
    "from bioneuralnet.metrics import plot_performance_three\n",
    "from bioneuralnet.metrics import plot_variance_distribution\n",
    "from bioneuralnet.metrics import plot_variance_by_feature\n",
    "from bioneuralnet.metrics import plot_performance\n",
    "from bioneuralnet.metrics import plot_embeddings\n",
    "from bioneuralnet.metrics import plot_network\n",
    "from bioneuralnet.metrics import compare_clusters\n",
    "\n",
    "from bioneuralnet.utils import get_logger\n",
    "from bioneuralnet.utils import rdata_to_df\n",
    "from bioneuralnet.utils import variance_summary\n",
    "from bioneuralnet.utils import zero_fraction_summary\n",
    "from bioneuralnet.utils import expression_summary\n",
    "from bioneuralnet.utils import correlation_summary\n",
    "from bioneuralnet.utils import explore_data_stats\n",
    "from bioneuralnet.utils import preprocess_clinical\n",
    "from bioneuralnet.utils import clean_inf_nan\n",
    "from bioneuralnet.utils import select_top_k_variance\n",
    "from bioneuralnet.utils import select_top_k_correlation\n",
    "from bioneuralnet.utils import select_top_randomforest\n",
    "from bioneuralnet.utils import top_anova_f_features\n",
    "from bioneuralnet.utils import prune_network\n",
    "from bioneuralnet.utils import prune_network_by_quantile\n",
    "from bioneuralnet.utils import network_remove_low_variance\n",
    "from bioneuralnet.utils import network_remove_high_zero_fraction\n",
    "from bioneuralnet.utils import gen_similarity_graph\n",
    "from bioneuralnet.utils import gen_correlation_graph\n",
    "from bioneuralnet.utils import gen_threshold_graph\n",
    "from bioneuralnet.utils import gen_gaussian_knn_graph\n",
    "from bioneuralnet.utils import gen_lasso_graph\n",
    "from bioneuralnet.utils import gen_mst_graph\n",
    "from bioneuralnet.utils import gen_snn_graph\n",
    "\n",
    "from bioneuralnet.datasets import DatasetLoader\n",
    "from bioneuralnet.external_tools import SmCCNet\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gene_1</th>\n",
       "      <th>Gene_2</th>\n",
       "      <th>Gene_3</th>\n",
       "      <th>Gene_4</th>\n",
       "      <th>Gene_5</th>\n",
       "      <th>Gene_6</th>\n",
       "      <th>Gene_7</th>\n",
       "      <th>Gene_8</th>\n",
       "      <th>Gene_9</th>\n",
       "      <th>Gene_10</th>\n",
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       "      <th>Gene_491</th>\n",
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       "      <th>Gene_497</th>\n",
       "      <th>Gene_498</th>\n",
       "      <th>Gene_499</th>\n",
       "      <th>Gene_500</th>\n",
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       "      <th>Samp_1</th>\n",
       "      <td>22.485701</td>\n",
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       "      <td>26.697293</td>\n",
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       "      <td>23.512005</td>\n",
       "      <td>33.677622</td>\n",
       "      <td>19.430333</td>\n",
       "      <td>30.260153</td>\n",
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       "      <td>13.262070</td>\n",
       "      <td>13.608147</td>\n",
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       "      <td>15.247613</td>\n",
       "      <td>13.603157</td>\n",
       "      <td>14.727795</td>\n",
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       "      <td>23.531461</td>\n",
       "      <td>26.754628</td>\n",
       "      <td>31.735945</td>\n",
       "      <td>22.795952</td>\n",
       "      <td>29.301536</td>\n",
       "      <td>14.936397</td>\n",
       "      <td>30.823015</td>\n",
       "      <td>...</td>\n",
       "      <td>11.886247</td>\n",
       "      <td>13.241386</td>\n",
       "      <td>12.445773</td>\n",
       "      <td>13.400288</td>\n",
       "      <td>12.587993</td>\n",
       "      <td>15.048676</td>\n",
       "      <td>12.018609</td>\n",
       "      <td>14.513958</td>\n",
       "      <td>12.066379</td>\n",
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       "      <td>20.530767</td>\n",
       "      <td>31.669623</td>\n",
       "      <td>35.189567</td>\n",
       "      <td>20.952544</td>\n",
       "      <td>25.018826</td>\n",
       "      <td>32.157235</td>\n",
       "      <td>25.069464</td>\n",
       "      <td>22.853719</td>\n",
       "      <td>18.220225</td>\n",
       "      <td>23.092805</td>\n",
       "      <td>...</td>\n",
       "      <td>12.198357</td>\n",
       "      <td>12.869640</td>\n",
       "      <td>12.841290</td>\n",
       "      <td>13.127437</td>\n",
       "      <td>12.607377</td>\n",
       "      <td>14.398177</td>\n",
       "      <td>12.554904</td>\n",
       "      <td>14.339382</td>\n",
       "      <td>12.891962</td>\n",
       "      <td>12.760553</td>\n",
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       "      <th>Samp_4</th>\n",
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       "      <td>38.480880</td>\n",
       "      <td>18.897097</td>\n",
       "      <td>31.823300</td>\n",
       "      <td>34.049383</td>\n",
       "      <td>38.799887</td>\n",
       "      <td>24.106468</td>\n",
       "      <td>12.397175</td>\n",
       "      <td>13.724255</td>\n",
       "      <td>27.703085</td>\n",
       "      <td>...</td>\n",
       "      <td>12.197502</td>\n",
       "      <td>13.312536</td>\n",
       "      <td>11.645099</td>\n",
       "      <td>13.933684</td>\n",
       "      <td>12.103087</td>\n",
       "      <td>15.133432</td>\n",
       "      <td>12.436027</td>\n",
       "      <td>15.116888</td>\n",
       "      <td>12.810732</td>\n",
       "      <td>12.972879</td>\n",
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       "      <th>Samp_5</th>\n",
       "      <td>28.961981</td>\n",
       "      <td>41.060494</td>\n",
       "      <td>28.494956</td>\n",
       "      <td>18.374495</td>\n",
       "      <td>30.815238</td>\n",
       "      <td>24.004535</td>\n",
       "      <td>29.616296</td>\n",
       "      <td>24.364045</td>\n",
       "      <td>11.409338</td>\n",
       "      <td>33.599828</td>\n",
       "      <td>...</td>\n",
       "      <td>14.157141</td>\n",
       "      <td>13.386978</td>\n",
       "      <td>13.007109</td>\n",
       "      <td>13.826532</td>\n",
       "      <td>12.343930</td>\n",
       "      <td>15.280175</td>\n",
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       "      <td>14.008675</td>\n",
       "      <td>12.479124</td>\n",
       "      <td>12.156407</td>\n",
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       "      <td>25.089732</td>\n",
       "      <td>14.437588</td>\n",
       "      <td>27.261916</td>\n",
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       "      <td>11.748228</td>\n",
       "      <td>13.096453</td>\n",
       "      <td>12.768936</td>\n",
       "      <td>13.228560</td>\n",
       "      <td>11.595884</td>\n",
       "      <td>15.251601</td>\n",
       "      <td>12.055375</td>\n",
       "      <td>15.530606</td>\n",
       "      <td>13.644383</td>\n",
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       "      <td>13.445404</td>\n",
       "      <td>12.457436</td>\n",
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       "      <td>13.662274</td>\n",
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       "      <td>...</td>\n",
       "      <td>12.519057</td>\n",
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       "      <td>13.166209</td>\n",
       "      <td>15.295902</td>\n",
       "      <td>13.257230</td>\n",
       "      <td>13.178058</td>\n",
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       "<p>358 rows × 500 columns</p>\n",
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      "text/plain": [
       "             Gene_1     Gene_2     Gene_3     Gene_4     Gene_5     Gene_6  \\\n",
       "Samp_1    22.485701  40.353720  31.025745  20.847206  26.697293  30.205449   \n",
       "Samp_2    37.058850  34.052233  33.487020  23.531461  26.754628  31.735945   \n",
       "Samp_3    20.530767  31.669623  35.189567  20.952544  25.018826  32.157235   \n",
       "Samp_4    33.186888  38.480880  18.897097  31.823300  34.049383  38.799887   \n",
       "Samp_5    28.961981  41.060494  28.494956  18.374495  30.815238  24.004535   \n",
       "...             ...        ...        ...        ...        ...        ...   \n",
       "Samp_354  24.520652  28.595409  31.299666  32.095379  33.659730  29.353948   \n",
       "Samp_355  31.252789  28.988087  29.574195  31.189288  32.098841  26.849138   \n",
       "Samp_356  24.894826  25.944887  30.852641  26.705158  30.102546  37.197952   \n",
       "Samp_357  17.034337  38.574705  25.095201  37.062442  35.417758  29.753145   \n",
       "Samp_358  20.839167  27.099788  31.038453  19.410859  31.818995  33.493625   \n",
       "\n",
       "             Gene_7     Gene_8     Gene_9    Gene_10  ...   Gene_491  \\\n",
       "Samp_1    23.512005  33.677622  19.430333  30.260153  ...  12.967210   \n",
       "Samp_2    22.795952  29.301536  14.936397  30.823015  ...  11.886247   \n",
       "Samp_3    25.069464  22.853719  18.220225  23.092805  ...  12.198357   \n",
       "Samp_4    24.106468  12.397175  13.724255  27.703085  ...  12.197502   \n",
       "Samp_5    29.616296  24.364045  11.409338  33.599828  ...  14.157141   \n",
       "...             ...        ...        ...        ...  ...        ...   \n",
       "Samp_354  29.871659  25.089732  14.437588  27.261916  ...  11.748228   \n",
       "Samp_355  22.619669  28.006670   8.615549  30.838843  ...  11.460876   \n",
       "Samp_356  35.032309  34.775576  13.354611  29.697348  ...  12.884821   \n",
       "Samp_357  25.855997  25.603043  13.180794  31.188598  ...  13.278454   \n",
       "Samp_358  22.769369  22.869481  16.839248  24.644476  ...  12.519057   \n",
       "\n",
       "           Gene_492   Gene_493   Gene_494   Gene_495   Gene_496   Gene_497  \\\n",
       "Samp_1    13.334132  13.262070  13.608147  13.338606  15.247613  13.603157   \n",
       "Samp_2    13.241386  12.445773  13.400288  12.587993  15.048676  12.018609   \n",
       "Samp_3    12.869640  12.841290  13.127437  12.607377  14.398177  12.554904   \n",
       "Samp_4    13.312536  11.645099  13.933684  12.103087  15.133432  12.436027   \n",
       "Samp_5    13.386978  13.007109  13.826532  12.343930  15.280175  13.363962   \n",
       "...             ...        ...        ...        ...        ...        ...   \n",
       "Samp_354  13.096453  12.768936  13.228560  11.595884  15.251601  12.055375   \n",
       "Samp_355  12.994504  13.325608  13.386970  12.335143  14.966097  13.998975   \n",
       "Samp_356  12.785372  12.954534  13.906209  12.074805  15.519179  12.742078   \n",
       "Samp_357  13.445404  12.457436  14.036252  13.412114  14.158416  13.284701   \n",
       "Samp_358  13.308512  12.261076  11.211687  12.058898  15.349873  13.166209   \n",
       "\n",
       "           Gene_498   Gene_499   Gene_500  \n",
       "Samp_1    14.727795  13.400950  12.769172  \n",
       "Samp_2    14.513958  12.066379  12.583460  \n",
       "Samp_3    14.339382  12.891962  12.760553  \n",
       "Samp_4    15.116888  12.810732  12.972879  \n",
       "Samp_5    14.008675  12.479124  12.156407  \n",
       "...             ...        ...        ...  \n",
       "Samp_354  15.530606  13.644383  13.018032  \n",
       "Samp_355  13.250821  12.947672  13.161434  \n",
       "Samp_356  14.445011  12.129990  13.844271  \n",
       "Samp_357  13.662274  12.943670  13.996352  \n",
       "Samp_358  15.295902  13.257230  13.178058  \n",
       "\n",
       "[358 rows x 500 columns]"
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       "    .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>Mir_1</th>\n",
       "      <th>Mir_2</th>\n",
       "      <th>Mir_3</th>\n",
       "      <th>Mir_4</th>\n",
       "      <th>Mir_5</th>\n",
       "      <th>Mir_6</th>\n",
       "      <th>Mir_7</th>\n",
       "      <th>Mir_8</th>\n",
       "      <th>Mir_9</th>\n",
       "      <th>Mir_10</th>\n",
       "      <th>...</th>\n",
       "      <th>Mir_91</th>\n",
       "      <th>Mir_92</th>\n",
       "      <th>Mir_93</th>\n",
       "      <th>Mir_94</th>\n",
       "      <th>Mir_95</th>\n",
       "      <th>Mir_96</th>\n",
       "      <th>Mir_97</th>\n",
       "      <th>Mir_98</th>\n",
       "      <th>Mir_99</th>\n",
       "      <th>Mir_100</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Samp_1</th>\n",
       "      <td>15.223913</td>\n",
       "      <td>17.545826</td>\n",
       "      <td>15.784719</td>\n",
       "      <td>14.891983</td>\n",
       "      <td>10.348205</td>\n",
       "      <td>9.689755</td>\n",
       "      <td>11.093630</td>\n",
       "      <td>13.189246</td>\n",
       "      <td>12.526561</td>\n",
       "      <td>10.311609</td>\n",
       "      <td>...</td>\n",
       "      <td>7.551462</td>\n",
       "      <td>5.407878</td>\n",
       "      <td>13.933045</td>\n",
       "      <td>10.287521</td>\n",
       "      <td>10.213316</td>\n",
       "      <td>10.609973</td>\n",
       "      <td>14.554996</td>\n",
       "      <td>10.955650</td>\n",
       "      <td>11.422531</td>\n",
       "      <td>10.862970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_2</th>\n",
       "      <td>16.306965</td>\n",
       "      <td>16.672830</td>\n",
       "      <td>13.361529</td>\n",
       "      <td>14.488549</td>\n",
       "      <td>12.660905</td>\n",
       "      <td>11.333613</td>\n",
       "      <td>11.254930</td>\n",
       "      <td>13.457435</td>\n",
       "      <td>13.279747</td>\n",
       "      <td>10.428848</td>\n",
       "      <td>...</td>\n",
       "      <td>6.862413</td>\n",
       "      <td>7.309226</td>\n",
       "      <td>13.586180</td>\n",
       "      <td>11.975544</td>\n",
       "      <td>11.496937</td>\n",
       "      <td>10.653742</td>\n",
       "      <td>14.414225</td>\n",
       "      <td>11.811004</td>\n",
       "      <td>12.413667</td>\n",
       "      <td>10.719110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_3</th>\n",
       "      <td>16.545119</td>\n",
       "      <td>16.735005</td>\n",
       "      <td>14.617472</td>\n",
       "      <td>17.845267</td>\n",
       "      <td>13.822790</td>\n",
       "      <td>11.329333</td>\n",
       "      <td>11.171749</td>\n",
       "      <td>12.715107</td>\n",
       "      <td>13.787771</td>\n",
       "      <td>10.364577</td>\n",
       "      <td>...</td>\n",
       "      <td>6.874958</td>\n",
       "      <td>7.754733</td>\n",
       "      <td>13.847029</td>\n",
       "      <td>12.424403</td>\n",
       "      <td>10.930177</td>\n",
       "      <td>10.255484</td>\n",
       "      <td>13.570352</td>\n",
       "      <td>11.311925</td>\n",
       "      <td>11.072915</td>\n",
       "      <td>11.418794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_4</th>\n",
       "      <td>13.986899</td>\n",
       "      <td>16.207432</td>\n",
       "      <td>16.293078</td>\n",
       "      <td>17.725286</td>\n",
       "      <td>12.300565</td>\n",
       "      <td>9.844108</td>\n",
       "      <td>11.586551</td>\n",
       "      <td>11.878702</td>\n",
       "      <td>14.594392</td>\n",
       "      <td>10.936651</td>\n",
       "      <td>...</td>\n",
       "      <td>9.615623</td>\n",
       "      <td>6.693593</td>\n",
       "      <td>13.840728</td>\n",
       "      <td>12.245466</td>\n",
       "      <td>10.836894</td>\n",
       "      <td>11.502232</td>\n",
       "      <td>15.483399</td>\n",
       "      <td>10.812811</td>\n",
       "      <td>10.121957</td>\n",
       "      <td>11.039089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_5</th>\n",
       "      <td>16.338332</td>\n",
       "      <td>17.393869</td>\n",
       "      <td>16.397925</td>\n",
       "      <td>15.853725</td>\n",
       "      <td>13.387675</td>\n",
       "      <td>10.599414</td>\n",
       "      <td>12.355466</td>\n",
       "      <td>12.450426</td>\n",
       "      <td>13.778779</td>\n",
       "      <td>10.405327</td>\n",
       "      <td>...</td>\n",
       "      <td>9.146865</td>\n",
       "      <td>8.104206</td>\n",
       "      <td>13.903452</td>\n",
       "      <td>11.423350</td>\n",
       "      <td>9.997107</td>\n",
       "      <td>10.744586</td>\n",
       "      <td>14.465583</td>\n",
       "      <td>11.730166</td>\n",
       "      <td>12.206151</td>\n",
       "      <td>10.724849</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>Samp_354</th>\n",
       "      <td>15.065065</td>\n",
       "      <td>16.079830</td>\n",
       "      <td>14.635616</td>\n",
       "      <td>17.013845</td>\n",
       "      <td>11.612843</td>\n",
       "      <td>9.850100</td>\n",
       "      <td>11.375670</td>\n",
       "      <td>12.870558</td>\n",
       "      <td>13.873811</td>\n",
       "      <td>11.369083</td>\n",
       "      <td>...</td>\n",
       "      <td>8.110691</td>\n",
       "      <td>8.124900</td>\n",
       "      <td>14.316491</td>\n",
       "      <td>12.599296</td>\n",
       "      <td>10.302683</td>\n",
       "      <td>11.286541</td>\n",
       "      <td>14.478041</td>\n",
       "      <td>11.141163</td>\n",
       "      <td>11.102427</td>\n",
       "      <td>11.993050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_355</th>\n",
       "      <td>15.997576</td>\n",
       "      <td>15.448951</td>\n",
       "      <td>15.355566</td>\n",
       "      <td>16.501752</td>\n",
       "      <td>11.701778</td>\n",
       "      <td>11.323521</td>\n",
       "      <td>11.610163</td>\n",
       "      <td>12.733208</td>\n",
       "      <td>13.650662</td>\n",
       "      <td>10.770903</td>\n",
       "      <td>...</td>\n",
       "      <td>8.711232</td>\n",
       "      <td>6.977555</td>\n",
       "      <td>14.805837</td>\n",
       "      <td>12.283549</td>\n",
       "      <td>10.847157</td>\n",
       "      <td>9.833187</td>\n",
       "      <td>14.037476</td>\n",
       "      <td>11.082880</td>\n",
       "      <td>11.708466</td>\n",
       "      <td>10.654141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_356</th>\n",
       "      <td>15.206862</td>\n",
       "      <td>14.395378</td>\n",
       "      <td>16.218001</td>\n",
       "      <td>16.044955</td>\n",
       "      <td>13.650741</td>\n",
       "      <td>11.057462</td>\n",
       "      <td>13.324846</td>\n",
       "      <td>13.070428</td>\n",
       "      <td>16.109746</td>\n",
       "      <td>11.253359</td>\n",
       "      <td>...</td>\n",
       "      <td>7.497926</td>\n",
       "      <td>6.840175</td>\n",
       "      <td>15.048896</td>\n",
       "      <td>12.615673</td>\n",
       "      <td>10.583973</td>\n",
       "      <td>12.708186</td>\n",
       "      <td>16.325254</td>\n",
       "      <td>10.789635</td>\n",
       "      <td>10.830833</td>\n",
       "      <td>10.983455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_357</th>\n",
       "      <td>14.474129</td>\n",
       "      <td>15.482863</td>\n",
       "      <td>15.512549</td>\n",
       "      <td>15.136613</td>\n",
       "      <td>14.531277</td>\n",
       "      <td>10.713539</td>\n",
       "      <td>11.632242</td>\n",
       "      <td>13.792981</td>\n",
       "      <td>13.486404</td>\n",
       "      <td>10.870028</td>\n",
       "      <td>...</td>\n",
       "      <td>7.902283</td>\n",
       "      <td>7.339226</td>\n",
       "      <td>14.295151</td>\n",
       "      <td>11.853855</td>\n",
       "      <td>10.439473</td>\n",
       "      <td>11.897782</td>\n",
       "      <td>16.684790</td>\n",
       "      <td>10.847185</td>\n",
       "      <td>11.491449</td>\n",
       "      <td>11.684467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_358</th>\n",
       "      <td>15.094188</td>\n",
       "      <td>16.047304</td>\n",
       "      <td>15.298871</td>\n",
       "      <td>17.022665</td>\n",
       "      <td>15.046043</td>\n",
       "      <td>10.931386</td>\n",
       "      <td>12.289466</td>\n",
       "      <td>14.327210</td>\n",
       "      <td>13.533348</td>\n",
       "      <td>9.792684</td>\n",
       "      <td>...</td>\n",
       "      <td>8.017328</td>\n",
       "      <td>7.814296</td>\n",
       "      <td>14.267007</td>\n",
       "      <td>12.117150</td>\n",
       "      <td>11.832061</td>\n",
       "      <td>11.021241</td>\n",
       "      <td>14.533734</td>\n",
       "      <td>12.015799</td>\n",
       "      <td>11.551237</td>\n",
       "      <td>11.221372</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>358 rows × 100 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Mir_1      Mir_2      Mir_3      Mir_4      Mir_5      Mir_6  \\\n",
       "Samp_1    15.223913  17.545826  15.784719  14.891983  10.348205   9.689755   \n",
       "Samp_2    16.306965  16.672830  13.361529  14.488549  12.660905  11.333613   \n",
       "Samp_3    16.545119  16.735005  14.617472  17.845267  13.822790  11.329333   \n",
       "Samp_4    13.986899  16.207432  16.293078  17.725286  12.300565   9.844108   \n",
       "Samp_5    16.338332  17.393869  16.397925  15.853725  13.387675  10.599414   \n",
       "...             ...        ...        ...        ...        ...        ...   \n",
       "Samp_354  15.065065  16.079830  14.635616  17.013845  11.612843   9.850100   \n",
       "Samp_355  15.997576  15.448951  15.355566  16.501752  11.701778  11.323521   \n",
       "Samp_356  15.206862  14.395378  16.218001  16.044955  13.650741  11.057462   \n",
       "Samp_357  14.474129  15.482863  15.512549  15.136613  14.531277  10.713539   \n",
       "Samp_358  15.094188  16.047304  15.298871  17.022665  15.046043  10.931386   \n",
       "\n",
       "              Mir_7      Mir_8      Mir_9     Mir_10  ...    Mir_91    Mir_92  \\\n",
       "Samp_1    11.093630  13.189246  12.526561  10.311609  ...  7.551462  5.407878   \n",
       "Samp_2    11.254930  13.457435  13.279747  10.428848  ...  6.862413  7.309226   \n",
       "Samp_3    11.171749  12.715107  13.787771  10.364577  ...  6.874958  7.754733   \n",
       "Samp_4    11.586551  11.878702  14.594392  10.936651  ...  9.615623  6.693593   \n",
       "Samp_5    12.355466  12.450426  13.778779  10.405327  ...  9.146865  8.104206   \n",
       "...             ...        ...        ...        ...  ...       ...       ...   \n",
       "Samp_354  11.375670  12.870558  13.873811  11.369083  ...  8.110691  8.124900   \n",
       "Samp_355  11.610163  12.733208  13.650662  10.770903  ...  8.711232  6.977555   \n",
       "Samp_356  13.324846  13.070428  16.109746  11.253359  ...  7.497926  6.840175   \n",
       "Samp_357  11.632242  13.792981  13.486404  10.870028  ...  7.902283  7.339226   \n",
       "Samp_358  12.289466  14.327210  13.533348   9.792684  ...  8.017328  7.814296   \n",
       "\n",
       "             Mir_93     Mir_94     Mir_95     Mir_96     Mir_97     Mir_98  \\\n",
       "Samp_1    13.933045  10.287521  10.213316  10.609973  14.554996  10.955650   \n",
       "Samp_2    13.586180  11.975544  11.496937  10.653742  14.414225  11.811004   \n",
       "Samp_3    13.847029  12.424403  10.930177  10.255484  13.570352  11.311925   \n",
       "Samp_4    13.840728  12.245466  10.836894  11.502232  15.483399  10.812811   \n",
       "Samp_5    13.903452  11.423350   9.997107  10.744586  14.465583  11.730166   \n",
       "...             ...        ...        ...        ...        ...        ...   \n",
       "Samp_354  14.316491  12.599296  10.302683  11.286541  14.478041  11.141163   \n",
       "Samp_355  14.805837  12.283549  10.847157   9.833187  14.037476  11.082880   \n",
       "Samp_356  15.048896  12.615673  10.583973  12.708186  16.325254  10.789635   \n",
       "Samp_357  14.295151  11.853855  10.439473  11.897782  16.684790  10.847185   \n",
       "Samp_358  14.267007  12.117150  11.832061  11.021241  14.533734  12.015799   \n",
       "\n",
       "             Mir_99    Mir_100  \n",
       "Samp_1    11.422531  10.862970  \n",
       "Samp_2    12.413667  10.719110  \n",
       "Samp_3    11.072915  11.418794  \n",
       "Samp_4    10.121957  11.039089  \n",
       "Samp_5    12.206151  10.724849  \n",
       "...             ...        ...  \n",
       "Samp_354  11.102427  11.993050  \n",
       "Samp_355  11.708466  10.654141  \n",
       "Samp_356  10.830833  10.983455  \n",
       "Samp_357  11.491449  11.684467  \n",
       "Samp_358  11.551237  11.221372  \n",
       "\n",
       "[358 rows x 100 columns]"
      ]
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       "      <th>phenotype</th>\n",
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       "      <td>234.204994</td>\n",
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       "      <th>Samp_5</th>\n",
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       "      <td>236.120451</td>\n",
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       "      <th>Samp_355</th>\n",
       "      <td>222.572359</td>\n",
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       "      <th>Samp_357</th>\n",
       "      <td>235.808167</td>\n",
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       "           phenotype\n",
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       "Samp_4    281.035429\n",
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       "...              ...\n",
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       "Samp_358  213.886123\n",
       "\n",
       "[358 rows x 1 columns]"
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       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Chronic_Bronchitis</th>\n",
       "      <th>Emphysema</th>\n",
       "      <th>Asthma</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PatientID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Samp_1</th>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>31.2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_2</th>\n",
       "      <td>68</td>\n",
       "      <td>1</td>\n",
       "      <td>19.2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_3</th>\n",
       "      <td>54</td>\n",
       "      <td>1</td>\n",
       "      <td>19.3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_4</th>\n",
       "      <td>47</td>\n",
       "      <td>1</td>\n",
       "      <td>36.2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_5</th>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>26.2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_354</th>\n",
       "      <td>71</td>\n",
       "      <td>0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_355</th>\n",
       "      <td>62</td>\n",
       "      <td>1</td>\n",
       "      <td>25.5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_356</th>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>21.1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_357</th>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>37.6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_358</th>\n",
       "      <td>61</td>\n",
       "      <td>1</td>\n",
       "      <td>31.3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>358 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Age  Gender   BMI  Chronic_Bronchitis  Emphysema  Asthma\n",
       "PatientID                                                          \n",
       "Samp_1      78       0  31.2                   1          1       0\n",
       "Samp_2      68       1  19.2                   1          0       0\n",
       "Samp_3      54       1  19.3                   0          1       1\n",
       "Samp_4      47       1  36.2                   0          0       1\n",
       "Samp_5      60       1  26.2                   0          1       1\n",
       "...        ...     ...   ...                 ...        ...     ...\n",
       "Samp_354    71       0  23.0                   1          0       1\n",
       "Samp_355    62       1  25.5                   0          1       1\n",
       "Samp_356    61       0  21.1                   1          0       0\n",
       "Samp_357    64       0  37.6                   0          0       1\n",
       "Samp_358    61       1  31.3                   1          0       0\n",
       "\n",
       "[358 rows x 6 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from bioneuralnet.datasets import DatasetLoader\n",
    "\n",
    "loader = DatasetLoader(\"example1\")\n",
    "omics1, omics2, phenotype, clinical = loader.load_data()\n",
    "\n",
    "display(omics1)\n",
    "display(omics2)\n",
    "display(phenotype)\n",
    "display(clinical)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate Global Network using SmCCNet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bioneuralnet.external_tools import SmCCNet\n",
    "\n",
    "smccnet = SmCCNet(\n",
    "    phenotype_df=phenotype,\n",
    "    omics_dfs=[omics1, omics2],\n",
    "    data_types=[\"genes\", \"proteins\"],\n",
    ")\n",
    "global_network, smccnet_clusters = smccnet.run()\n",
    "\n",
    "print(\"Global network shape:\", global_network.shape)\n",
    "print(\"Number of SmCCnet clusters:\", len(smccnet_clusters))\n",
    "display(global_network.head())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Gene_1</th>\n",
       "      <th>Gene_2</th>\n",
       "      <th>Gene_3</th>\n",
       "      <th>Gene_4</th>\n",
       "      <th>Gene_5</th>\n",
       "      <th>Gene_6</th>\n",
       "      <th>Gene_7</th>\n",
       "      <th>Gene_8</th>\n",
       "      <th>Gene_9</th>\n",
       "      <th>Gene_10</th>\n",
       "      <th>...</th>\n",
       "      <th>Mir_91</th>\n",
       "      <th>Mir_92</th>\n",
       "      <th>Mir_93</th>\n",
       "      <th>Mir_94</th>\n",
       "      <th>Mir_95</th>\n",
       "      <th>Mir_96</th>\n",
       "      <th>Mir_97</th>\n",
       "      <th>Mir_98</th>\n",
       "      <th>Mir_99</th>\n",
       "      <th>Mir_100</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Gene_1</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.160757</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.043592</td>\n",
       "      <td>0.271547</td>\n",
       "      <td>0.277287</td>\n",
       "      <td>0</td>\n",
       "      <td>0.009604</td>\n",
       "      <td>0.043405</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>0.004766</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene_2</th>\n",
       "      <td>0.160757</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.038431</td>\n",
       "      <td>0.243888</td>\n",
       "      <td>0.239016</td>\n",
       "      <td>0</td>\n",
       "      <td>0.008589</td>\n",
       "      <td>0.037873</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>0.005787</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene_3</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</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>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene_4</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</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>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene_5</th>\n",
       "      <td>0.043592</td>\n",
       "      <td>0.038431</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.066452</td>\n",
       "      <td>0.060837</td>\n",
       "      <td>0</td>\n",
       "      <td>0.002207</td>\n",
       "      <td>0.010718</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>0.000953</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 600 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Gene_1    Gene_2  Gene_3  Gene_4    Gene_5    Gene_6    Gene_7  \\\n",
       "Gene_1  0.000000  0.160757       0       0  0.043592  0.271547  0.277287   \n",
       "Gene_2  0.160757  0.000000       0       0  0.038431  0.243888  0.239016   \n",
       "Gene_3  0.000000  0.000000       0       0  0.000000  0.000000  0.000000   \n",
       "Gene_4  0.000000  0.000000       0       0  0.000000  0.000000  0.000000   \n",
       "Gene_5  0.043592  0.038431       0       0  0.000000  0.066452  0.060837   \n",
       "\n",
       "        Gene_8    Gene_9   Gene_10  ...  Mir_91  Mir_92  Mir_93  Mir_94  \\\n",
       "Gene_1       0  0.009604  0.043405  ...       0       0       0       0   \n",
       "Gene_2       0  0.008589  0.037873  ...       0       0       0       0   \n",
       "Gene_3       0  0.000000  0.000000  ...       0       0       0       0   \n",
       "Gene_4       0  0.000000  0.000000  ...       0       0       0       0   \n",
       "Gene_5       0  0.002207  0.010718  ...       0       0       0       0   \n",
       "\n",
       "        Mir_95    Mir_96  Mir_97  Mir_98  Mir_99  Mir_100  \n",
       "Gene_1       0  0.004766       0       0       0        0  \n",
       "Gene_2       0  0.005787       0       0       0        0  \n",
       "Gene_3       0  0.000000       0       0       0        0  \n",
       "Gene_4       0  0.000000       0       0       0        0  \n",
       "Gene_5       0  0.000953       0       0       0        0  \n",
       "\n",
       "[5 rows x 600 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(global_network.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate Network Embeddings using GNNEmbedding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bioneuralnet.network_embedding import GNNEmbedding\n",
    "\n",
    "merged_omics = pd.concat([omics1, omics2], axis=1)\n",
    "\n",
    "gnn = GNNEmbedding(\n",
    "    adjacency_matrix=global_network,\n",
    "    omics_data=merged_omics,\n",
    "    phenotype_data=phenotype,\n",
    "    clinical_data=clinical,\n",
    "    phenotype_col=\"phenotype\",\n",
    "    model_type=\"GAT\",\n",
    "    hidden_dim=64,\n",
    "    layer_num=4,\n",
    "    dropout=True,\n",
    "    num_epochs=100,\n",
    "    lr=1e-3,\n",
    "    weight_decay=1e-4,\n",
    "    seed=119,\n",
    ")\n",
    "gnn.fit()\n",
    "embeddings = gnn.embed(as_df=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Embed_1</th>\n",
       "      <th>Embed_2</th>\n",
       "      <th>Embed_3</th>\n",
       "      <th>Embed_4</th>\n",
       "      <th>Embed_5</th>\n",
       "      <th>Embed_6</th>\n",
       "      <th>Embed_7</th>\n",
       "      <th>Embed_8</th>\n",
       "      <th>Embed_9</th>\n",
       "      <th>Embed_10</th>\n",
       "      <th>...</th>\n",
       "      <th>Embed_55</th>\n",
       "      <th>Embed_56</th>\n",
       "      <th>Embed_57</th>\n",
       "      <th>Embed_58</th>\n",
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       "      <th>Embed_61</th>\n",
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       "      <th>Embed_64</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Gene_1</th>\n",
       "      <td>0.037078</td>\n",
       "      <td>0.010051</td>\n",
       "      <td>-0.036622</td>\n",
       "      <td>0.022973</td>\n",
       "      <td>0.029106</td>\n",
       "      <td>-0.024114</td>\n",
       "      <td>0.031300</td>\n",
       "      <td>0.028295</td>\n",
       "      <td>0.047263</td>\n",
       "      <td>0.024042</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.017544</td>\n",
       "      <td>0.042265</td>\n",
       "      <td>0.017295</td>\n",
       "      <td>-0.030349</td>\n",
       "      <td>0.029958</td>\n",
       "      <td>-0.020222</td>\n",
       "      <td>0.029427</td>\n",
       "      <td>-0.026153</td>\n",
       "      <td>-0.025061</td>\n",
       "      <td>0.028961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene_2</th>\n",
       "      <td>0.037078</td>\n",
       "      <td>0.010051</td>\n",
       "      <td>-0.036622</td>\n",
       "      <td>0.022973</td>\n",
       "      <td>0.029106</td>\n",
       "      <td>-0.024114</td>\n",
       "      <td>0.031300</td>\n",
       "      <td>0.028295</td>\n",
       "      <td>0.047263</td>\n",
       "      <td>0.024042</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.017544</td>\n",
       "      <td>0.042265</td>\n",
       "      <td>0.017295</td>\n",
       "      <td>-0.030349</td>\n",
       "      <td>0.029958</td>\n",
       "      <td>-0.020222</td>\n",
       "      <td>0.029427</td>\n",
       "      <td>-0.026153</td>\n",
       "      <td>-0.025061</td>\n",
       "      <td>0.028961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene_3</th>\n",
       "      <td>0.038274</td>\n",
       "      <td>0.007089</td>\n",
       "      <td>-0.050431</td>\n",
       "      <td>0.026016</td>\n",
       "      <td>0.025564</td>\n",
       "      <td>-0.028543</td>\n",
       "      <td>0.030443</td>\n",
       "      <td>0.017762</td>\n",
       "      <td>0.045573</td>\n",
       "      <td>0.018522</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.017076</td>\n",
       "      <td>0.048518</td>\n",
       "      <td>0.014335</td>\n",
       "      <td>-0.023130</td>\n",
       "      <td>0.029575</td>\n",
       "      <td>-0.023226</td>\n",
       "      <td>0.028018</td>\n",
       "      <td>-0.041073</td>\n",
       "      <td>-0.041075</td>\n",
       "      <td>0.030907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene_4</th>\n",
       "      <td>0.032268</td>\n",
       "      <td>0.003910</td>\n",
       "      <td>-0.033076</td>\n",
       "      <td>0.024749</td>\n",
       "      <td>0.044768</td>\n",
       "      <td>-0.014179</td>\n",
       "      <td>0.017665</td>\n",
       "      <td>0.014499</td>\n",
       "      <td>0.052139</td>\n",
       "      <td>0.028020</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.022137</td>\n",
       "      <td>0.030999</td>\n",
       "      <td>0.015979</td>\n",
       "      <td>-0.034100</td>\n",
       "      <td>0.028120</td>\n",
       "      <td>-0.025319</td>\n",
       "      <td>0.027917</td>\n",
       "      <td>-0.012606</td>\n",
       "      <td>-0.028836</td>\n",
       "      <td>0.026390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gene_5</th>\n",
       "      <td>0.037078</td>\n",
       "      <td>0.010051</td>\n",
       "      <td>-0.036622</td>\n",
       "      <td>0.022973</td>\n",
       "      <td>0.029106</td>\n",
       "      <td>-0.024114</td>\n",
       "      <td>0.031300</td>\n",
       "      <td>0.028295</td>\n",
       "      <td>0.047263</td>\n",
       "      <td>0.024042</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.017544</td>\n",
       "      <td>0.042265</td>\n",
       "      <td>0.017295</td>\n",
       "      <td>-0.030349</td>\n",
       "      <td>0.029958</td>\n",
       "      <td>-0.020222</td>\n",
       "      <td>0.029427</td>\n",
       "      <td>-0.026153</td>\n",
       "      <td>-0.025061</td>\n",
       "      <td>0.028961</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 64 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Embed_1   Embed_2   Embed_3   Embed_4   Embed_5   Embed_6   Embed_7  \\\n",
       "Gene_1  0.037078  0.010051 -0.036622  0.022973  0.029106 -0.024114  0.031300   \n",
       "Gene_2  0.037078  0.010051 -0.036622  0.022973  0.029106 -0.024114  0.031300   \n",
       "Gene_3  0.038274  0.007089 -0.050431  0.026016  0.025564 -0.028543  0.030443   \n",
       "Gene_4  0.032268  0.003910 -0.033076  0.024749  0.044768 -0.014179  0.017665   \n",
       "Gene_5  0.037078  0.010051 -0.036622  0.022973  0.029106 -0.024114  0.031300   \n",
       "\n",
       "         Embed_8   Embed_9  Embed_10  ...  Embed_55  Embed_56  Embed_57  \\\n",
       "Gene_1  0.028295  0.047263  0.024042  ... -0.017544  0.042265  0.017295   \n",
       "Gene_2  0.028295  0.047263  0.024042  ... -0.017544  0.042265  0.017295   \n",
       "Gene_3  0.017762  0.045573  0.018522  ... -0.017076  0.048518  0.014335   \n",
       "Gene_4  0.014499  0.052139  0.028020  ... -0.022137  0.030999  0.015979   \n",
       "Gene_5  0.028295  0.047263  0.024042  ... -0.017544  0.042265  0.017295   \n",
       "\n",
       "        Embed_58  Embed_59  Embed_60  Embed_61  Embed_62  Embed_63  Embed_64  \n",
       "Gene_1 -0.030349  0.029958 -0.020222  0.029427 -0.026153 -0.025061  0.028961  \n",
       "Gene_2 -0.030349  0.029958 -0.020222  0.029427 -0.026153 -0.025061  0.028961  \n",
       "Gene_3 -0.023130  0.029575 -0.023226  0.028018 -0.041073 -0.041075  0.030907  \n",
       "Gene_4 -0.034100  0.028120 -0.025319  0.027917 -0.012606 -0.028836  0.026390  \n",
       "Gene_5 -0.030349  0.029958 -0.020222  0.029427 -0.026153 -0.025061  0.028961  \n",
       "\n",
       "[5 rows x 64 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(embeddings.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Embeddings visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-03-07 12:31:43,802 - bioneuralnet.network_embedding.gnn_embedding - INFO - Preparing node labels by correlating each omics feature with phenotype column 'phenotype'.\n",
      "2025-03-07 12:31:43,803 - bioneuralnet.network_embedding.gnn_embedding - INFO - Index(['Samp_1', 'Samp_2', 'Samp_3', 'Samp_4', 'Samp_5', 'Samp_6', 'Samp_7',\n",
      "       'Samp_8', 'Samp_9', 'Samp_10',\n",
      "       ...\n",
      "       'Samp_349', 'Samp_350', 'Samp_351', 'Samp_352', 'Samp_353', 'Samp_354',\n",
      "       'Samp_355', 'Samp_356', 'Samp_357', 'Samp_358'],\n",
      "      dtype='object', length=358)\n",
      "2025-03-07 12:31:43,875 - bioneuralnet.network_embedding.gnn_embedding - INFO - Node labels prepared successfully.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bioneuralnet.metrics import plot_embeddings\n",
    "\n",
    "# Using our embeddings instance we get the necessary labels for the graph.\n",
    "node_labels = gnn._prepare_node_labels()\n",
    "embeddings_array = embeddings.values  \n",
    "\n",
    "embeddings_plot = plot_embeddings(embeddings_array, node_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Integrate Embeddings into Omics Data with SubjectRepresentation\n",
    "\n",
    "- Let use these omics to enrich the representation of the original dataset.\n",
    "\n",
    "- The `SubjectRepresentation` function takes our previously generated embeddings and our original Omics Dataset and associated Phenotype\n",
    "\n",
    "- This function will use the embeddings to enrich the orignal dataset. For more details and how this is performed please view our `GNN Embeddings for Multi-Omics` tab."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bioneuralnet.downstream_task import SubjectRepresentation\n",
    "\n",
    "graph_embed = SubjectRepresentation(\n",
    "    omics_data=merged_omics,\n",
    "    embeddings=embeddings,\n",
    "    phenotype_data=phenotype,\n",
    "    phenotype_col=\"phenotype\",\n",
    "    reduce_method=\"PCA\",\n",
    "    tune=False,\n",
    ")\n",
    "enhanced_omics = graph_embed.run()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gene_213</th>\n",
       "      <th>Gene_177</th>\n",
       "      <th>Mir_78</th>\n",
       "      <th>Gene_50</th>\n",
       "      <th>Gene_335</th>\n",
       "      <th>Gene_491</th>\n",
       "      <th>Gene_187</th>\n",
       "      <th>Mir_74</th>\n",
       "      <th>Gene_76</th>\n",
       "      <th>Gene_357</th>\n",
       "      <th>...</th>\n",
       "      <th>Gene_371</th>\n",
       "      <th>Mir_84</th>\n",
       "      <th>Mir_40</th>\n",
       "      <th>Gene_266</th>\n",
       "      <th>Gene_62</th>\n",
       "      <th>Gene_239</th>\n",
       "      <th>Gene_496</th>\n",
       "      <th>Mir_33</th>\n",
       "      <th>Gene_495</th>\n",
       "      <th>Gene_249</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Samp_1</th>\n",
       "      <td>31.972913</td>\n",
       "      <td>7.749811</td>\n",
       "      <td>4.713763</td>\n",
       "      <td>-0.749105</td>\n",
       "      <td>-0.823750</td>\n",
       "      <td>-0.784272</td>\n",
       "      <td>-0.611546</td>\n",
       "      <td>-6.206424</td>\n",
       "      <td>-0.764613</td>\n",
       "      <td>0.006680</td>\n",
       "      <td>...</td>\n",
       "      <td>7.257692</td>\n",
       "      <td>9.188055</td>\n",
       "      <td>-0.359187</td>\n",
       "      <td>14.058017</td>\n",
       "      <td>-0.777809</td>\n",
       "      <td>-3.507224</td>\n",
       "      <td>0.545008</td>\n",
       "      <td>-8.300834</td>\n",
       "      <td>3.433189</td>\n",
       "      <td>-17.325618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_2</th>\n",
       "      <td>30.562847</td>\n",
       "      <td>7.616120</td>\n",
       "      <td>3.262150</td>\n",
       "      <td>-0.715228</td>\n",
       "      <td>-0.904390</td>\n",
       "      <td>-0.718894</td>\n",
       "      <td>-0.778848</td>\n",
       "      <td>-7.043132</td>\n",
       "      <td>-0.751795</td>\n",
       "      <td>0.006527</td>\n",
       "      <td>...</td>\n",
       "      <td>6.266241</td>\n",
       "      <td>10.170368</td>\n",
       "      <td>-0.334464</td>\n",
       "      <td>14.220815</td>\n",
       "      <td>-0.754667</td>\n",
       "      <td>-3.325996</td>\n",
       "      <td>0.537897</td>\n",
       "      <td>-7.037332</td>\n",
       "      <td>3.239990</td>\n",
       "      <td>-16.226066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_3</th>\n",
       "      <td>30.319072</td>\n",
       "      <td>7.959335</td>\n",
       "      <td>5.177822</td>\n",
       "      <td>-0.799192</td>\n",
       "      <td>-0.890603</td>\n",
       "      <td>-0.737770</td>\n",
       "      <td>-0.916597</td>\n",
       "      <td>-6.473910</td>\n",
       "      <td>-0.757998</td>\n",
       "      <td>0.006260</td>\n",
       "      <td>...</td>\n",
       "      <td>6.520219</td>\n",
       "      <td>9.402382</td>\n",
       "      <td>-0.359254</td>\n",
       "      <td>14.802170</td>\n",
       "      <td>-0.734408</td>\n",
       "      <td>-3.654560</td>\n",
       "      <td>0.514646</td>\n",
       "      <td>-7.261344</td>\n",
       "      <td>3.244979</td>\n",
       "      <td>-17.947806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_4</th>\n",
       "      <td>33.532754</td>\n",
       "      <td>8.136440</td>\n",
       "      <td>4.885794</td>\n",
       "      <td>-0.715119</td>\n",
       "      <td>-0.800914</td>\n",
       "      <td>-0.737719</td>\n",
       "      <td>-0.601052</td>\n",
       "      <td>-7.031316</td>\n",
       "      <td>-0.744343</td>\n",
       "      <td>0.005747</td>\n",
       "      <td>...</td>\n",
       "      <td>6.069317</td>\n",
       "      <td>8.792790</td>\n",
       "      <td>-0.320809</td>\n",
       "      <td>14.675955</td>\n",
       "      <td>-0.778705</td>\n",
       "      <td>-3.532869</td>\n",
       "      <td>0.540927</td>\n",
       "      <td>-6.572756</td>\n",
       "      <td>3.115182</td>\n",
       "      <td>-19.260010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_5</th>\n",
       "      <td>32.241288</td>\n",
       "      <td>8.248584</td>\n",
       "      <td>3.934224</td>\n",
       "      <td>-0.797891</td>\n",
       "      <td>-0.813945</td>\n",
       "      <td>-0.856240</td>\n",
       "      <td>-0.324133</td>\n",
       "      <td>-6.991057</td>\n",
       "      <td>-0.719048</td>\n",
       "      <td>0.007457</td>\n",
       "      <td>...</td>\n",
       "      <td>6.832945</td>\n",
       "      <td>9.096281</td>\n",
       "      <td>-0.414235</td>\n",
       "      <td>14.231641</td>\n",
       "      <td>-0.729173</td>\n",
       "      <td>-3.555468</td>\n",
       "      <td>0.546172</td>\n",
       "      <td>-7.145498</td>\n",
       "      <td>3.177172</td>\n",
       "      <td>-20.107202</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 600 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Gene_213  Gene_177    Mir_78   Gene_50  Gene_335  Gene_491  Gene_187  \\\n",
       "Samp_1  31.972913  7.749811  4.713763 -0.749105 -0.823750 -0.784272 -0.611546   \n",
       "Samp_2  30.562847  7.616120  3.262150 -0.715228 -0.904390 -0.718894 -0.778848   \n",
       "Samp_3  30.319072  7.959335  5.177822 -0.799192 -0.890603 -0.737770 -0.916597   \n",
       "Samp_4  33.532754  8.136440  4.885794 -0.715119 -0.800914 -0.737719 -0.601052   \n",
       "Samp_5  32.241288  8.248584  3.934224 -0.797891 -0.813945 -0.856240 -0.324133   \n",
       "\n",
       "          Mir_74   Gene_76  Gene_357  ...  Gene_371     Mir_84    Mir_40  \\\n",
       "Samp_1 -6.206424 -0.764613  0.006680  ...  7.257692   9.188055 -0.359187   \n",
       "Samp_2 -7.043132 -0.751795  0.006527  ...  6.266241  10.170368 -0.334464   \n",
       "Samp_3 -6.473910 -0.757998  0.006260  ...  6.520219   9.402382 -0.359254   \n",
       "Samp_4 -7.031316 -0.744343  0.005747  ...  6.069317   8.792790 -0.320809   \n",
       "Samp_5 -6.991057 -0.719048  0.007457  ...  6.832945   9.096281 -0.414235   \n",
       "\n",
       "         Gene_266   Gene_62  Gene_239  Gene_496    Mir_33  Gene_495   Gene_249  \n",
       "Samp_1  14.058017 -0.777809 -3.507224  0.545008 -8.300834  3.433189 -17.325618  \n",
       "Samp_2  14.220815 -0.754667 -3.325996  0.537897 -7.037332  3.239990 -16.226066  \n",
       "Samp_3  14.802170 -0.734408 -3.654560  0.514646 -7.261344  3.244979 -17.947806  \n",
       "Samp_4  14.675955 -0.778705 -3.532869  0.540927 -6.572756  3.115182 -19.260010  \n",
       "Samp_5  14.231641 -0.729173 -3.555468  0.546172 -7.145498  3.177172 -20.107202  \n",
       "\n",
       "[5 rows x 600 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(enhanced_omics.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comparing results for prediction task"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\ramos\\Desktop\\GitHub\\BioNeuralNet\\.venv\\lib\\site-packages\\sklearn\\base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
      "  return fit_method(estimator, *args, **kwargs)\n",
      "c:\\Users\\ramos\\Desktop\\GitHub\\BioNeuralNet\\.venv\\lib\\site-packages\\sklearn\\base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
      "  return fit_method(estimator, *args, **kwargs)\n"
     ]
    }
   ],
   "source": [
    "from bioneuralnet.metrics import evaluate_rf\n",
    "from bioneuralnet.metrics import plot_performance\n",
    "\n",
    "y_phenotype = phenotype.values\n",
    "X_enriched_omics = enhanced_omics.values\n",
    "X_raw_omics = merged_omics.values\n",
    "\n",
    "accuracy_with_embeddings = evaluate_rf(X_enriched_omics, y_phenotype, mode=\"regression\")\n",
    "accuracy_alone = evaluate_rf(X_enriched_omics, y_phenotype, mode=\"regression\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_performance(accuracy_with_embeddings, accuracy_alone, \"Raw Omics vs Enriched Omics\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Disease Prediction using DPMON(Disease Prediction using Multi-Omics Networks)\n",
    "\n",
    "- DPMON is a classification task.\n",
    "- We will adjust our phenotype from continus value to a class from 0 to 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>phenotype</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Samp_1</th>\n",
       "      <td>235.067423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_2</th>\n",
       "      <td>253.544991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_3</th>\n",
       "      <td>234.204994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_4</th>\n",
       "      <td>281.035429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_5</th>\n",
       "      <td>245.447781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_354</th>\n",
       "      <td>236.120451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_355</th>\n",
       "      <td>222.572359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_356</th>\n",
       "      <td>268.472285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_357</th>\n",
       "      <td>235.808167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_358</th>\n",
       "      <td>213.886123</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>358 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           phenotype\n",
       "Samp_1    235.067423\n",
       "Samp_2    253.544991\n",
       "Samp_3    234.204994\n",
       "Samp_4    281.035429\n",
       "Samp_5    245.447781\n",
       "...              ...\n",
       "Samp_354  236.120451\n",
       "Samp_355  222.572359\n",
       "Samp_356  268.472285\n",
       "Samp_357  235.808167\n",
       "Samp_358  213.886123\n",
       "\n",
       "[358 rows x 1 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bioneuralnet.datasets import DatasetLoader\n",
    "import numpy as np\n",
    "\n",
    "loader = DatasetLoader(\"example1\")\n",
    "omics1, omics2, phenotype, clinical = loader.load_data()\n",
    "display(phenotype)\n",
    "\n",
    "min_val = phenotype[\"phenotype\"].min()\n",
    "max_val = phenotype[\"phenotype\"].max()\n",
    "\n",
    "# linspace creates an array of evenly spaced values\n",
    "bins = np.linspace(min_val, max_val, 5)\n",
    "\n",
    "phenotype[\"phenotype\"] = pd.cut(phenotype[\"phenotype\"], bins=bins, labels=[0, 1, 2, 3], include_lowest=True)\n",
    "count_values = phenotype[\"phenotype\"].value_counts(sort=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Phenotype after:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>phenotype</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Samp_1</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_2</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_3</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_4</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_5</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_354</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_355</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_356</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_357</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samp_358</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>358 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         phenotype\n",
       "Samp_1           1\n",
       "Samp_2           2\n",
       "Samp_3           1\n",
       "Samp_4           3\n",
       "Samp_5           2\n",
       "...            ...\n",
       "Samp_354         1\n",
       "Samp_355         1\n",
       "Samp_356         2\n",
       "Samp_357         1\n",
       "Samp_358         1\n",
       "\n",
       "[358 rows x 1 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "phenotype\n",
       "0     38\n",
       "1    158\n",
       "2    141\n",
       "3     21\n",
       "Name: count, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(phenotype)\n",
    "display(count_values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing the variance distribution and feature variance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-03-07 12:31:51,166 - bioneuralnet.metrics.plot - INFO - Computed variances for each feature.\n",
      "2025-03-07 12:31:51,209 - bioneuralnet.metrics.plot - INFO - Variance distribution plot generated.\n"
     ]
    },
    {
     "data": {
      "image/png": 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uMbRU3WGXGhuu6MEHHyyGzllhhRWK18fXAw88cI4hlWL4nrXXXrvUrl27esNPxRBBjQ2709hwWDfffHNpyJAhpeWWW67UqVOnYjio2YcAChdeeGExtFF1dXVpyy23LI0cOXKOdc6tbQ0N2fTZZ5+VTjjhhOJ9tm/fvrTGGmuULrjggnpDDoVYz1FHHTVHmxobpmt2H3/8cenQQw8tdevWrdiv6667boNDds3vcFjftGy8v9i3vXv3LrYb299iiy1Kv/nNb4ohr2pce+21xXuPfdu3b9+ibQ0NZfXaa68VwzTF5xTP1X3v999/fzGEVmynT58+xfBfjQ2H1dC+rNlP8VzPnj2LzyOO3/79+5euvvrq0ryKoaliiKjYzt///vc5nn/yySdL3/rWt4r3EJ/7SSedVAyhFcvHMVljfo7lOF7OOeec4jOJfRhDzo0YMWKOY65mOKw4xmZXdyizGq+88kpp7733Li211FKljh07Fvv11FNPne99dtVVVxWfWwzDFe1bffXVSyeeeGJp8uTJ87xfIUdV8U+5wzMAAHwTNa4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALLQ6m9AELdk/OCDD4oBmZv7tpYAACy4GJ017rgYN0KpeyvtNhdcI7T27Nmz3M0AAOAbxG2/486ObTa41tz6LnbEkksuWe7mAAAwmylTphQdjd90y+JWH1xrygMitAquAACV65vKOl2cBQBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALLQrtwNoOWNHTs2TZgwod68bt26pV69epWtTQAA30RwbYOhtU/ftdK0L7+oN79jp85p9GujhFcAoGIJrm1M9LRGaO26++DUvmvPYt6MiePSxBEXFs8JrgBApRJc26gIrdXde5e7GQAA88zFWQAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyUNbg+thjj6U99tgjrbDCCqmqqirdeeedjS7705/+tFjm4osvbtE2AgBQGcoaXD///PO0/vrrpyuuuGKuy91xxx3pmWeeKQIuAABtU7tybnyXXXYpprl5//330zHHHJPuu+++tNtuu7VY2wAAqCxlDa7fZNasWemHP/xhOvHEE9M666wzT6+ZPn16MdWYMmXKQmwhAAAtpaIvzjrvvPNSu3bt0rHHHjvPrxk6dGjq0qVL7dSzZ8+F2kYAANp4cH3++efTJZdckq6//vrioqx5NWTIkDR58uTaady4cQu1nQAAtPHg+vjjj6fx48enXr16Fb2uMb377rtp8ODBaZVVVmn0ddXV1WnJJZesNwEAkL+KrXGN2tYddtih3ryddtqpmH/ooYeWrV0AALTB4Dp16tQ0ZsyY2sdvv/12evHFF9MyyyxT9LR27dq13vLt27dP3bt3T3369ClDawEAaLPBdeTIkWm77barfTxo0KDi68CBA4vaVgAAqIjguu2226ZSqTTPy7/zzjsLtT0AAFSuir04CwAA6hJcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAtlDa6PPfZY2mOPPdIKK6yQqqqq0p133ln73IwZM9LJJ5+c1l133bTYYosVyxx88MHpgw8+KGeTAQBoi8H1888/T+uvv3664oor5njuiy++SC+88EI69dRTi6+33357Gj16dPre975XlrYCAFBe7cq58V122aWYGtKlS5f0wAMP1Jt3+eWXp8022yyNHTs29erVq4VaCQBAauvBdX5Nnjy5KClYaqmlGl1m+vTpxVRjypQpLdQ6AAAWpmwuzpo2bVpR83rggQemJZdcstHlhg4dWvTW1kw9e/Zs0XYCANCGg2tcqLXffvulUqmUrrzyyrkuO2TIkKJntmYaN25ci7UTAIA2XCpQE1rffffd9NBDD821tzVUV1cXEwAArUu7HELrG2+8kR5++OHUtWvXcjcJAIC2GFynTp2axowZU/v47bffTi+++GJaZpllUo8ePdK+++5bDIU1YsSINHPmzPTRRx8Vy8XzHTp0KGPLAQBoU8F15MiRabvttqt9PGjQoOLrwIED0xlnnJHuvvvu4vEGG2xQ73XR+7rtttu2cGsBAGizwTXCZ1xw1Zi5PQcAQNuSxagCAAAguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIQlmD62OPPZb22GOPtMIKK6Sqqqp055131nu+VCql0047LfXo0SN16tQp7bDDDumNN94oW3sBAGijwfXzzz9P66+/frriiisafP78889Pl156aRo2bFj65z//mRZbbLG00047pWnTprV4WwEAKK925dz4LrvsUkwNid7Wiy++OP3yl79Me+65ZzHvxhtvTMsvv3zRM3vAAQe0cGsBACiniq1xffvtt9NHH31UlAfU6NKlS9p8883T008/3ejrpk+fnqZMmVJvAgAgfxUbXCO0huhhrSse1zzXkKFDhxYBt2bq2bPnQm8rAABtOLg21ZAhQ9LkyZNrp3HjxpW7SQAAtObg2r179+Lrxx9/XG9+PK55riHV1dVpySWXrDcBAJC/ig2uq666ahFQH3zwwdp5Ua8aowt8+9vfLmvbAABoY6MKTJ06NY0ZM6beBVkvvvhiWmaZZVKvXr3S8ccfn84+++y0xhprFEH21FNPLcZ83WuvvcrZbAAA2lpwHTlyZNpuu+1qHw8aNKj4OnDgwHT99denk046qRjr9Sc/+Un6z3/+k7baaqt07733po4dO5ax1QAAtLnguu222xbjtTYm7qb1q1/9qpgAAGjbKrbGFQAA6hJcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAstCt3A2j9xo4dmyZMmFBvXrdu3VKvXr3K1iYAoI0E17feeiutttpqzd8aWmVo7dN3rTTtyy/qze/YqXMa/doo4RUAWLjBtXfv3mmbbbZJhx9+eNp3331Tx44dm7Ia2oDoaY3Q2nX3wal9157FvBkTx6WJIy4snhNcAYCFWuP6wgsvpPXWWy8NGjQode/ePR1xxBHp2WefbcqqaCMitFZ3711MNQEWAGChB9cNNtggXXLJJemDDz5I1113Xfrwww/TVlttlfr165cuuuii9MknnzRltQAAsHBGFWjXrl3aZ5990p/+9Kd03nnnpTFjxqSf//znqWfPnunggw8uAi0AAJQ9uI4cOTIdeeSRqUePHkVPa4TWN998Mz3wwANFb+yee+7ZLI0EAIAmXZwVIXX48OFp9OjRadddd0033nhj8XWRRf43B6+66qrp+uuvT6usskpztxcAgDaqScH1yiuvTIcddlg65JBDit7Whiy33HLp2muvXdD2AQBA04PrG2+88Y3LdOjQIQ0cOLApqwcAgOapcY0ygbgga3Yx74YbbmjKKgEAoPmD69ChQ4tbdjZUHnDOOec0ZZUAAND8wTVu4xkXYM1u5ZVXLp4DAICKCK7Rs/ryyy/PMf+ll15KXbt2bY52AQDAggfXAw88MB177LHp4YcfTjNnziymhx56KB133HHpgAMOaMoqAQCg+UcVOOuss9I777yT+vfvX9w9K8yaNau4W5YaVwAAKia4xlBXt956axFgozygU6dOad111y1qXAEAoGKCa40111yzmAAAoCKDa9S0xi1dH3zwwTR+/PiiTKCuqHcFAICyB9e4CCuC62677Zb69euXqqqqmrVRAADQLMH1lltuSbfddlvaddddm/JyAABomeGw4uKs3r17N+WlAADQcsF18ODB6ZJLLkmlUqlpWwUAgJYoFXjiiSeKmw/cc889aZ111knt27ev9/ztt9/elNUCAEDzBtellloq7b333k15KQAAtFxwHT58eNO2BgAALVnjGr7++uv0j3/8I1111VXps88+K+Z98MEHaerUqam5xHixp556alp11VWLu3Otvvrqxd261NYCALQ9Tepxfffdd9POO++cxo4dm6ZPn56++93vpiWWWCKdd955xeNhw4Y1S+NifVdeeWW64YYbilrakSNHpkMPPTR16dIlHXvssc2yDQAAWnGPa9yAYJNNNkmTJk0qekJrRN1r3E2ruTz11FNpzz33LG50sMoqq6R999037bjjjunZZ59ttm0AANCKe1wff/zxIlTGeK51Rbh8//33m6ttaYsttkhXX311ev3119Oaa66ZXnrppWJEg4suuqjR10SPb0w1pkyZkipZ9FpPmDBhjvndunVLvXr1SpXYvkppGwDQtjQpuM6aNauoP53de++9V5QMNJdTTjmlCJ59+/ZNiy66aLHNX//61+mggw5q9DVDhw5NZ555ZspBhMI+fddK0778Yo7nOnbqnEa/NqqsAbGx9lVC2wCAtqdJwTVO11988cVFb2ioqqoqLso6/fTTm/U2sHFb2T/+8Y/ppptuKmpcX3zxxXT88cenFVZYIQ0cOLDB1wwZMiQNGjSo9nEE3549e6ZKFD2ZEQq77j44te/6f22cMXFcmjjiwuL5cobDhtpXKW0DANqeJgXXCy+8MO20005p7bXXTtOmTUs/+MEP0htvvFGcQr755pubrXEnnnhi0et6wAEHFI/XXXfd4sKw6FVtLLhWV1cXU04iFFZ3r9xb6FZ6+wCAtqFJwXWllVYq6k1vueWW9PLLLxe9rYcffnhxCr/uxVoL6osvvkiLLFL/+rEoGYhSBQAA2pZ2TX5hu3ZpwIABaWHaY489iprWOCUdpQL/7//9v+LCrMMOO2yhbhcAgFYSXG+88ca5Pn/wwQen5nDZZZcVNyA48sgj0/jx44va1iOOOCKddtppzbJ+AABaeXCNcVzrmjFjRnFaP4bH6ty5c7MF1xihIC4CiwkAgLatSTcgiBsP1J2ixnX06NFpq622ataLswAAYIGCa0PWWGONdO65587RGwsAABUVXGsu2Prggw+ac5UAAND0Gte777673uNSqZQ+/PDDdPnll6ctt9yyKasEAIDmD6577bVXvcdx56xll102bb/99sXNCQAAoCKCqxsAAACQdY0rAABUVI/roEGD5nnZuNMVAACUJbjGrVdjihsP9OnTp5j3+uuvp0UXXTRttNFG9WpfAQCgbMF1jz32KO5qdcMNN6Sll166mBc3Ijj00EPT1ltvnQYPHtwsjQMAgAWqcY2RA4YOHVobWkP8/+yzzzaqAAAAlRNcp0yZkj755JM55se8zz77rDnaBQAACx5c995776Is4Pbbb0/vvfdeMf3lL39Jhx9+eNpnn32askoAAGj+Gtdhw4aln//85+kHP/hBcYFWsaJ27YrgesEFFzRllQAA0PzBtXPnzul3v/tdEVLffPPNYt7qq6+eFltssaasDgAAFu4NCD788MNiWmONNYrQWiqVFmR1AADQvMF14sSJqX///mnNNddMu+66axFeQ5QKGAoLAICKCa4nnHBCat++fRo7dmxRNlBj//33T/fee29ztg8AAJpe43r//fen++67L6200kr15kfJwLvvvtuUVQIAQPP3uH7++ef1elprfPrpp6m6uropqwQAgOYPrnFb1xtvvLH2cVVVVZo1a1Y6//zz03bbbdeUVQIAQPOXCkRAjYuzRo4cmb766qt00kknpVdffbXocX3yySebskoaMGrUqDnmdevWLfXq1avevKg1njBhwjwtCwDQpoJrv3790uuvv54uv/zytMQSS6SpU6cWd8w66qijUo8ePZq/lW3MzKmTohs7DRgwYI7nOnbqnEa/Nqo2kEZo7dN3rTTtyy++cVkAgDYVXONOWTvvvHNx96xf/OIXC6dVbdys6VNTKpVS190Hp/Zde9bOnzFxXJo44sKid7UmjMb/I7TOy7IAAG0quMYwWC+//PLCaQ31RBCt7t672ZcFAGgzF2fFKexrr722+VsDAADNWeP69ddfp+uuuy794x//SBtvvHFxu9e6LrrooqasFgAAmie4vvXWW2mVVVZJr7zyStpoo42KeXGRVl0xNBYAAJQ1uMadsT788MP08MMP197i9dJLL03LL798szcMAACaXONaKpXqPb7nnnuKu2gBAEBFXpzVWJAFAICKCK5Rvzp7DauaVgAAKq7GNXpYDznkkFRdXV08njZtWvrpT386x6gCt99+e/O2EgCANm++guvAgQPrPW7olqQAAFD24Dp8+PCF0ggAAFioF2cBAEBLEVwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkIWKD67vv/9+GjBgQOratWvq1KlTWnfdddPIkSPL3SwAAFpYu1TBJk2alLbccsu03XbbpXvuuSctu+yy6Y033khLL710uZsGAEALq+jget5556WePXum4cOH185bddVVy9omAADKo6KD691335122mmn9P3vfz89+uijacUVV0xHHnlk+vGPf9zoa6ZPn15MNaZMmdJCrW1bRo0aNce8bt26pV69epWlPQBA61fRwfWtt95KV155ZRo0aFD67//+7/Tcc8+lY489NnXo0CENHDiwwdcMHTo0nXnmmS3e1rZi5tRJKVVVFXXHs+vYqXMa/doo4RUAaHvBddasWWmTTTZJ55xzTvF4ww03TK+88koaNmxYo8F1yJAhRdCt2+Ma5QY0j1nTp6ZUKqWuuw9O7bv+336dMXFcmjjiwjRhwgTBFQBoe8G1R48eae211643b6211kp/+ctfGn1NdXV1MbFwRWit7t673M0AANqQih4OK0YUGD16dL15r7/+elp55ZXL1iYAAMqjooPrCSeckJ555pmiVGDMmDHppptuSldffXU66qijyt00AABaWEUH10033TTdcccd6eabb079+vVLZ511Vrr44ovTQQcdVO6mAQDQwiq6xjXsvvvuxQQAQNtW0T2uAABQQ3AFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAW2pW7ASxco0aNmutjAIBcCK6t1Mypk1KqqkoDBgwod1MAAJqF4NpKzZo+NaVSKXXdfXBq37Vn7fwv3xqZJj/+h7K2DQCgKQTXVi5Ca3X33rWPZ0wcV9b2AAA0lYuzAADIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGQhq+B67rnnpqqqqnT88ceXuykAALSwbILrc889l6666qq03nrrlbspAACUQRbBderUqemggw5K11xzTVp66aXL3RwAAMqgXcrAUUcdlXbbbbe0ww47pLPPPnuuy06fPr2YakyZMiW1NqNGjWrw/8253qauuznWAQCQZXC95ZZb0gsvvFCUCsyLoUOHpjPPPDO1RjOnTkqpqioNGDCg4ta7sNoGAJBFcB03blw67rjj0gMPPJA6duw4T68ZMmRIGjRoUL0e1549e6bWYNb0qSmVSqnr7oNT+67/+56+fGtkmvz4H5p9vfO77uZYBwBAtsH1+eefT+PHj08bbbRR7byZM2emxx57LF1++eVFScCiiy5a7zXV1dXF1JpFMKzu3rv4/4yJ4xbKepu67uZYBwBAdsG1f//+6V//+le9eYceemjq27dvOvnkk+cIrQAAtF4VHVyXWGKJ1K9fv3rzFltssdS1a9c55gMA0LplMRwWAABUdI9rQx555JFyNwEAgDLQ4woAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC+3K3YC2ZOzYsWnChAm1j0eNGlXW9gAA5ERwbcHQ2qfvWmnal1+UuykAAFkSXFtI9LRGaO26++DUvmvPYt6Xb41Mkx//Q7mbBgCQBcG1hUVore7eu/j/jInjyt0cAIBsuDgLAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYqOrgOHTo0bbrppmmJJZZIyy23XNprr73S6NGjy90sAADKoKKD66OPPpqOOuqo9Mwzz6QHHnggzZgxI+24447p888/L3fTAABoYe1SBbv33nvrPb7++uuLntfnn38+fec73ylbuwAAaHkVHVxnN3ny5OLrMsss0+gy06dPL6YaU6ZMSS1t7NixacKECfXmjRo1qsXbUeka2ifx2VVXV88xv1u3bqlXr16pnBr6XCulbQDQFmQTXGfNmpWOP/74tOWWW6Z+/frNtS72zDPPTOUMN336rpWmfflF2dpQ6WZOnZRSVVUaMGDAnE9WLZJSadYcszt26pxGvzaqbAFxbp9rudsGAG1FNsE1al1feeWV9MQTT8x1uSFDhqRBgwbV63Ht2bNnainRIxfhpuvug1P7rv+33S/fGpkmP/6HFmtHJZs1fWpKpVKj+2j2+TMmjksTR1xY7NtyhcPGPtdKaBsAtBVZBNejjz46jRgxIj322GNppZVWmuuycZq5oVPNLS3CTXX33vUCDvO2j2afX0kquW0A0NpVdHAtlUrpmGOOSXfccUd65JFH0qqrrlruJgEAUCbtKr084Kabbkp33XVXMZbrRx99VMzv0qVL6tSpU7mbBwBAC6rocVyvvPLKYiSBbbfdNvXo0aN2uvXWW8vdNAAAWljFlwoAAEDF97gCAEANwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFloV+4GwLwaNWpUvcfdunVLvXr1SpXYtvlt39ixY9OECRPmmD99+vRUXV3d5PXO7/Zaep+2dDsq5X1XyntpaB057ovW9l6gEn4WVOr3kOBKxZs5dVJKVVVpwIAB9eZ37NQ5jX5tVFm/qRpr2/y0L35g9Om7Vpr25RdzPlm1SEqlWU1ab1O215L7tKXbUSnvu1LeS2PryG1ftLb3ApXys6BSv4cEVyrerOlTUyqVUtfdB6f2XXsW82ZMHJcmjriw+AuxnN9QDbVtftsXy8QPjNnX8eVbI9Pkx//Q7O+7se219D5t6XZUyvuulPfS0Dpy3Bet7b1AJfwsqOTvIcGVbMQ3VHX33qm1tm32dcQPjeZa97xsr1xauh2V8r4r9bjLWWt6LzA/2rehnwUuzgIAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsZBFcr7jiirTKKqukjh07ps033zw9++yz5W4SAAAtrOKD66233poGDRqUTj/99PTCCy+k9ddfP+20005p/Pjx5W4aAAAtqOKD60UXXZR+/OMfp0MPPTStvfbaadiwYalz587puuuuK3fTAABoQe1SBfvqq6/S888/n4YMGVI7b5FFFkk77LBDevrppxt8zfTp04upxuTJk4uvU6ZMaYEWpzR16tT/bcdHY9Ksr6bVzp8xcdwc8xuaN7/zW3odFdPmT98rvsbxUbPP6x4js2bNmu2TaXj+vC47evTo+WtzI+1raHvzs+7meN+Nbm8+2jy/8+frfS+kdlTK+26OdTTHe2loHS39fdVc62iO91LJn/fCXEeObW6OdeTY5obmj15IPwvqriNe3xIZqmYbpVJp7guWKtj7778frS899dRT9eafeOKJpc0226zB15x++unFa0wmk8lkMplMKatp3Lhxc82GFd3j2hTROxs1sTXiL4tPP/00de3aNVVVVX1j2u/Zs2caN25cWnLJJVugtW2T/bzw2cctw35uGfbzwmcftwz7uXHR0/rZZ5+lFVZYId9SgW7duqVFF100ffzxx/Xmx+Pu3bs3+Jrq6upiqmuppZaar+3GweSAWvjs54XPPm4Z9nPLsJ8XPvu4ZdjPDevSpUvK+uKsDh06pI033jg9+OCD9XpQ4/G3v/3tsrYNAICWVdE9riFO+w8cODBtsskmabPNNksXX3xx+vzzz4tRBgAAaDsqPrjuv//+6ZNPPkmnnXZa+uijj9IGG2yQ7r333rT88ss3+7aixCDGi5291IDmZT8vfPZxy7CfW4b9vPDZxy3Dfl5wVXGFVjOsBwAAFqqKrnEFAIAagisAAFkQXAEAyILgCgBAFgTX/98VV1yRVlllldSxY8e0+eabp2effbbcTWp1HnvssbTHHnsUd8WIu5jdeeed5W5SqzN06NC06aabpiWWWCItt9xyaa+99qq9DzXN58orr0zrrbde7SDiMa70PffcU+5mtWrnnntu8XPj+OOPL3dTWpUzzjij2K91p759+5a7Wa3S+++/nwYMGFDcybNTp05p3XXXTSNHjix3s7IjuKaUbr311mK82Bii4oUXXkjrr79+2mmnndL48ePL3bRWJcbfjX0bfySwcDz66KPpqKOOSs8880x64IEH0owZM9KOO+5Y7Huaz0orrVQEqeeff774xbP99tunPffcM7366qvlblqr9Nxzz6Wrrrqq+GOB5rfOOuukDz/8sHZ64oknyt2kVmfSpElpyy23TO3bty/+yP33v/+dLrzwwrT00kuXu2nZMRxWSkUPa/RSXX755bV354p7CR9zzDHplFNOKXfzWqX4q/6OO+4oegRZeGIM5Oh5jUD7ne98p9zNadWWWWaZdMEFF6TDDz+83E1pVaZOnZo22mij9Lvf/S6dffbZxVjecSMamq/HNc5+vfjii+VuSqsWWeLJJ59Mjz/+eLmbkr023+P61VdfFb0mO+ywQ+28RRZZpHj89NNPl7VtsKAmT55cG6pYOGbOnJluueWWolfbraibX5xB2G233er9jKZ5vfHGG0UJ12qrrZYOOuigNHbs2HI3qdW5++67izuAfv/73y86EzbccMN0zTXXlLtZWWrzwXXChAnFL57Z78QVj+NOXZCrOHMQ9YBxeqpfv37lbk6r869//SstvvjixR1wfvrTnxZnENZee+1yN6tViT8IonwrardZeGccr7/++uKOlFG7/fbbb6ett946ffbZZ+VuWqvy1ltvFft3jTXWSPfdd1/62c9+lo499th0ww03lLtp2an4W74CTe+peuWVV9SrLSR9+vQpTq9Gr/af//znNHDgwKIkQ3htHuPGjUvHHXdcUasdF82ycOyyyy61/48a4giyK6+8crrtttuUvTRzR0L0uJ5zzjnF4+hxjZ/Pw4YNK352MO/afI9rt27d0qKLLpo+/vjjevPjcffu3cvWLlgQRx99dBoxYkR6+OGHiwuJaH4dOnRIvXv3ThtvvHHRIxgXHl5yySXlblarESVccYFs1Le2a9eumOIPg0svvbT4f5wpo/kttdRSac0110xjxowpd1NalR49eszxR+1aa62lLKMJ2nxwjV8+8YvnwQcfrPeXUTxWr0Zu4lrLCK1x2vqhhx5Kq666armb1GbEz43p06eXuxmtRv/+/YtyjOjVrpmixypqMOP/0eHAwrkY7s033yyCFs0nSrZmH5rw9ddfL3q3mT9KBVIqhsKKrvr4objZZpsVV6zGhRaHHnpouZvWqsQPxLp/xUctVfwCiguHevXqVda2tabygJtuuindddddxViuNXXaXbp0KcYNpHkMGTKkOMUax23UAsY+f+SRR4raNZpHHL+z12YvtthixRiYarabz89//vNifO0IUB988EExLGT8UXDggQeWu2mtygknnJC22GKLolRgv/32K8aKv/rqq4uJ+RTDYVEqXXbZZaVevXqVOnToUNpss81KzzzzTLmb1Oo8/PDDMfTaHNPAgQPL3bRWo6H9G9Pw4cPL3bRW5bDDDiutvPLKxc+LZZddttS/f//S/fffX+5mtXrbbLNN6bjjjit3M1qV/fffv9SjR4/iWF5xxRWLx2PGjCl3s1qlv/71r6V+/fqVqqurS3379i1dffXV5W5SlozjCgBAFtp8jSsAAHkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrQIWqqqpKd955Z7mbAVAxBFeABRD3ed95550bfO7xxx8vwufLL7/cpHV/+OGHaZdddlnAFgK0HoIrwAI4/PDD0wMPPJDee++9OZ4bPnx42mSTTdJ66603X+v86quviq/du3dP1dXVzdZWgNwJrgALYPfdd0/LLrtsuv766+vNnzp1avrTn/6U9tprr3TggQemFVdcMXXu3Dmtu+666eabb6637LbbbpuOPvrodPzxx6du3bqlnXbaqcFSgZNPPjmtueaaxXpWW221dOqpp6YZM2bUPn/GGWekDTbYIP3+979Pq6yySurSpUs64IAD0meffVa7zKxZs9L555+fevfuXYTiXr16pV//+te1z48bNy7tt99+aamllkrLLLNM2nPPPdM777yzUPYdwPwSXAEWQLt27dLBBx9cBNdSqVQ7P0LrzJkz04ABA9LGG2+c/va3v6VXXnkl/eQnP0k//OEP07PPPltvPTfccEPq0KFDevLJJ9OwYcMa3NYSSyxRbOff//53uuSSS9I111yTfvvb39Zb5s033yzC7ogRI4rp0UcfTeeee27t80OGDCkeR+iN9dx0001p+eWXL56LEByhObYTZQ7RlsUXX7wohajpBQYoqxIAC2TUqFGRWEsPP/xw7bytt966NGDAgAaX32233UqDBw+ufbzNNtuUNtxwwzmWi3XecccdjW73ggsuKG288ca1j08//fRS586dS1OmTKmdd+KJJ5Y233zz4v8xv7q6unTNNdc0uL7f//73pT59+pRmzZpVO2/69OmlTp06le6777657AGAltGuvLEZIH99+/ZNW2yxRbruuuuK0/5jxowpeix/9atfFb2u55xzTrrtttvS+++/X/RcTp8+vTjdX1f0yn6TW2+9NV166aVFr2qUInz99ddpySWXrLdMlAhEj2mNHj16pPHjxxf/HzVqVLHt/v37N7j+l156qWh73deHadOmFdsEKDfBFaCZLtI65phj0hVXXFFclLX66qunbbbZJp133nnFaf2LL764qG9dbLHFilrW2U+9x/y5efrpp9NBBx2UzjzzzOJ0ftSv3nLLLenCCy+st1z79u3rPY462ahrDZ06dZrrNiIMR4D+4x//OMdzUccLUG6CK0AziAuajjvuuKJm9MYbb0w/+9nPitAYdaJxgVPUuoYIka+//npae+2152v9Tz31VFp55ZXTL37xi9p577777nytY4011ijC64MPPph+9KMfzfH8RhttVPTqLrfccnP05AJUAhdnATSDuIhp//33Ly5+ivFXDznkkNqwGMNlRfCMU/VHHHFE+vjjj+d7/bGesWPHFr2scdo+SgbuuOOO+VpHx44di5EJTjrppCJcx3qeeeaZdO211xbPR49ujGoQQTtKHd5+++30yCOPpGOPPbbB4b4AWprgCtCM5QKTJk0qTuWvsMIKxbxf/vKXRU9mzIv61xibNYbIml/f+9730gknnFAMmxVDXkUQjpEB5le8ZvDgwem0005La621VhG2a2pgo+72scceK4bI2meffYrn4z1FjaseWKASVMUVWuVuBAAAfBM9rgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAKQf/HwFmFHDmrmgyAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bioneuralnet.metrics import plot_variance_distribution\n",
    "\n",
    "fig = plot_variance_distribution(omics2, bins=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-03-07 12:31:51,338 - bioneuralnet.metrics.plot - INFO - Computed variances for each feature for index plot.\n",
      "2025-03-07 12:31:51,348 - bioneuralnet.metrics.plot - INFO - Variance vs. feature index plot generated.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bioneuralnet.metrics import plot_variance_by_feature\n",
    "\n",
    "fig2 = plot_variance_by_feature(omics2.iloc[:, 0:20])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bioneuralnet.downstream_task import DPMON\n",
    "\n",
    "dpmon = DPMON(\n",
    "    adjacency_matrix=global_network,\n",
    "    omics_list=[omics1, omics2],\n",
    "    phenotype_data=phenotype,\n",
    "    clinical_data=clinical,\n",
    "    model=\"GAT\",\n",
    "    layer_num=4,\n",
    "    num_epochs=100,\n",
    "    lr=1e-3,\n",
    "    weight_decay=1e-4,\n",
    "    tune=False,\n",
    "    gpu=False,\n",
    "    output_dir=\"dpmon_output\"\n",
    ")\n",
    "predictions = dpmon.run()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DPMON Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>Actual</th>\n",
       "      <th>Predicted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>353</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>355</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>357</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>358 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Actual  Predicted\n",
       "0        1          1\n",
       "1        2          2\n",
       "2        1          1\n",
       "3        3          3\n",
       "4        2          2\n",
       "..     ...        ...\n",
       "353      1          1\n",
       "354      1          2\n",
       "355      2          2\n",
       "356      1          1\n",
       "357      1          1\n",
       "\n",
       "[358 rows x 2 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(predictions[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\ramos\\Desktop\\GitHub\\BioNeuralNet\\.venv\\lib\\site-packages\\sklearn\\base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
      "  return fit_method(estimator, *args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bioneuralnet.metrics import evaluate_rf\n",
    "\n",
    "X_raw = merged_omics.values\n",
    "y_global = phenotype.values\n",
    "rf_accuracy = evaluate_rf(X_raw, y_global, n=100, mode=\"classification\")\n",
    "\n",
    "plot_performance(predictions[1], rf_accuracy, \"Raw Omics, vs DPMON Omics\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clustering with CorrelatedLouvain and HybridLouvain\n",
    "\n",
    "- BioNeuralNet includes internal modules for performing correlated clustering on complex networks. \n",
    "\n",
    "- These methods modify and extend the traditional community detection by integrating phenotype correlation, allowing users to extract biologically relevant, phenotype-associated modules from any network. \n",
    "\n",
    "- For more details on how this performed, please visit our `Correlated Clustering Methods` tab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bioneuralnet.clustering import CorrelatedLouvain\n",
    "import networkx as nx\n",
    "\n",
    "merged_omics = pd.concat([omics1, omics2], axis=1)\n",
    "G_network = nx.from_pandas_adjacency(global_network)\n",
    "\n",
    "louvain_instance = CorrelatedLouvain(\n",
    "    G=G_network,\n",
    "    B=merged_omics,\n",
    "    Y=phenotype,\n",
    "    tune=True\n",
    ")\n",
    "\n",
    "louvain_clusters = louvain_instance.run(as_dfs=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Number of Louvain clusters: 3'"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(f\"Number of Louvain clusters: {len(louvain_clusters)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>Cluster</th>\n",
       "      <th>Louvain Size</th>\n",
       "      <th>Louvain Correlation</th>\n",
       "      <th>SMCCNET Size</th>\n",
       "      <th>SMCCNET Correlation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Cluster_1</td>\n",
       "      <td>77</td>\n",
       "      <td>0.654809</td>\n",
       "      <td>67</td>\n",
       "      <td>0.119675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cluster_2</td>\n",
       "      <td>74</td>\n",
       "      <td>-0.130497</td>\n",
       "      <td>63</td>\n",
       "      <td>0.661981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cluster_3</td>\n",
       "      <td>8</td>\n",
       "      <td>0.046296</td>\n",
       "      <td>15</td>\n",
       "      <td>-0.050186</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Cluster  Louvain Size  Louvain Correlation  SMCCNET Size  \\\n",
       "0  Cluster_1            77             0.654809            67   \n",
       "1  Cluster_2            74            -0.130497            63   \n",
       "2  Cluster_3             8             0.046296            15   \n",
       "\n",
       "   SMCCNET Correlation  \n",
       "0             0.119675  \n",
       "1             0.661981  \n",
       "2            -0.050186  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets comapre these clusters against SmCCNet clusters\n",
    "from bioneuralnet.metrics import compare_clusters\n",
    "\n",
    "compare_clusters(louvain_clusters, smccnet_clusters, phenotype, merged_omics)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lets plot the clustered network from correlated louvain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>Omic</th>\n",
       "      <th>Degree</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Gene_6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>Gene_7</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Gene_1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Mir_2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Gene_299</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Omic  Degree\n",
       "Index                  \n",
       "23       Gene_6       5\n",
       "51       Gene_7       4\n",
       "21       Gene_1       4\n",
       "16        Mir_2       3\n",
       "34     Gene_299       3"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>Omic</th>\n",
       "      <th>Degree</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Gene_464</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Gene_354</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Gene_434</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Gene_422</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Gene_260</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Omic  Degree\n",
       "Index                  \n",
       "13     Gene_464       5\n",
       "26     Gene_354       3\n",
       "23     Gene_434       3\n",
       "31     Gene_422       3\n",
       "22     Gene_260       3"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bioneuralnet.metrics import plot_network\n",
    "from bioneuralnet.metrics import louvain_to_adjacency\n",
    "\n",
    "cluster1 = louvain_clusters[0]\n",
    "cluster2 = louvain_clusters[1]\n",
    "\n",
    "# Convert Louvain clusters into adjacency matrices\n",
    "louvain_adj1 = louvain_to_adjacency(cluster1)\n",
    "louvain_adj2 = louvain_to_adjacency(cluster2)\n",
    "\n",
    "# Plot using the converted adjacency matrices\n",
    "cluster1_mapping = plot_network(louvain_adj1, weight_threshold=0.12, show_labels=True, show_edge_weights=False)\n",
    "display(cluster1_mapping.head())\n",
    "\n",
    "cluster2_mapping = plot_network(louvain_adj2, weight_threshold=0.12, show_labels=True, show_edge_weights=False)\n",
    "display(cluster2_mapping.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bioneuralnet.clustering import  HybridLouvain\n",
    "import networkx as nx\n",
    "\n",
    "merged_omics = pd.concat([omics1, omics2], axis=1)\n",
    "G_network = nx.from_pandas_adjacency(global_network)\n",
    "\n",
    "hybrid = HybridLouvain(\n",
    "    G=G_network,\n",
    "    B=merged_omics,\n",
    "    Y=phenotype,\n",
    "    k3=0.2,\n",
    "    k4=0.8,\n",
    "    max_iter=3,\n",
    "    weight=\"weight\",\n",
    "    tune=False\n",
    ")\n",
    "hybrid_result = hybrid.run()\n",
    "display(\"Number of clusters:\", len(hybrid_result))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Package Version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BioNeuralNet version: 1.0\n"
     ]
    }
   ],
   "source": [
    "import bioneuralnet\n",
    "print(\"BioNeuralNet version:\", bioneuralnet.__version__)"
   ]
  }
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