{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c6c7a2e3",
   "metadata": {},
   "source": [
    "# ChIP-seq Data Exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dc0140e1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-02-04T23:55:46.123413Z",
     "start_time": "2026-02-04T23:54:53.952692Z"
    },
    "execution": {
     "iopub.execute_input": "2025-12-01T21:16:09.430673Z",
     "iopub.status.busy": "2025-12-01T21:16:09.429885Z",
     "iopub.status.idle": "2025-12-01T21:16:26.775825Z",
     "shell.execute_reply": "2025-12-01T21:16:26.773113Z",
     "shell.execute_reply.started": "2025-12-01T21:16:09.430648Z"
    }
   },
   "outputs": [],
   "source": [
    "import glob\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pybedtools\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "from matplotlib_venn import venn2, venn3\n",
    "# import pyranges as pr\n",
    "# import gseapy as gp\n",
    "import pyBigWig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "54f2e6f9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-02-04T23:55:46.135283Z",
     "start_time": "2026-02-04T23:55:46.129483Z"
    }
   },
   "outputs": [],
   "source": [
    "base_path = '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "21262a90",
   "metadata": {},
   "outputs": [],
   "source": [
    "composite_fusion_dataset_pairs = {\n",
    "    'Reh_RUNX1_B': 'Reh_HPA',\n",
    "    'Reh_DMSO_RUNX1': 'Reh_DMSO_HPA',\n",
    "    'Nalm6_RUNX1': 'Nalm6_ETV6-RUNX1_V5_B',\n",
    "    'REH_RUNX1_rep1': 'REH_ETV6-RUNX1_rep1',\n",
    "    'REH_RUNX1_rep2': 'REH_ETV6-RUNX1_rep2',\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3e84d327",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_directories = {\n",
    "    'Reh_HPA': '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Wray_et_al/Reh_HPA/',\n",
    "    'Reh_DMSO_HPA': '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Wray_et_al/Reh_DMSO_HPA/',\n",
    "    'Nalm6_ETV6-RUNX1_V5_B': '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Wray_et_al/Nalm6_ETV6-RUNX1_V5_B/',\n",
    "    'REH_ETV6-RUNX1_rep1': '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Jakobczyk_et_al/REH_ETV6-RUNX1_rep1/',\n",
    "    'REH_ETV6-RUNX1_rep2': '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Jakobczyk_et_al/REH_ETV6-RUNX1_rep2/',\n",
    "    'Reh_RUNX1_B': '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Wray_et_al/Reh_RUNX1_B/',\n",
    "    'Reh_DMSO_RUNX1': '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Wray_et_al/Reh_DMSO_RUNX1/',\n",
    "    'Nalm6_RUNX1': '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Wray_et_al/Nalm6_RUNX1/',\n",
    "    'REH_RUNX1_rep1': '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Jakobczyk_et_al/REH_RUNX1_rep1/',\n",
    "    'REH_RUNX1_rep2': '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Jakobczyk_et_al/REH_RUNX1_rep2/',\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f1a8a3ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x400 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=1, ncols=len(composite_fusion_dataset_pairs),\n",
    "                         figsize=(25, 4))\n",
    "i = 0\n",
    "for composite, fusion in composite_fusion_dataset_pairs.items():\n",
    "    composite_dir = dataset_directories[composite]\n",
    "    composite_peaks = pybedtools.BedTool(composite_dir + 'idr_peaks/idr_thresholded_peaks.narrowPeak')\n",
    "    composite_signal_path = glob.glob(composite_dir + '*.plus.bw')[0]\n",
    "    composite_signal = pyBigWig.open(composite_signal_path)\n",
    "\n",
    "    fusion_dir = dataset_directories[fusion]\n",
    "    fusion_peaks = pybedtools.BedTool(fusion_dir + 'idr_peaks/idr_thresholded_peaks.narrowPeak')\n",
    "    fusion_signal_path = glob.glob(fusion_dir + '*.plus.bw')[0]\n",
    "    fusion_signal = pyBigWig.open(fusion_signal_path)\n",
    "\n",
    "    composite_fusion_peaks_intersection = composite_peaks.intersect(fusion_peaks).to_dataframe()\n",
    "    \n",
    "    # Calculate sum of counts in each peak\n",
    "    composite_counts_per_peak = []\n",
    "    fusion_counts_per_peak = []\n",
    "    for _, peak in composite_fusion_peaks_intersection.iterrows():\n",
    "        try:\n",
    "            chrom, start, end = peak[\"chrom\"], int(peak[\"start\"]), int(peak[\"end\"])\n",
    "            # Subset composite bigwig file and sum counts at each peak\n",
    "            composite_vals = np.array(composite_signal.values(chrom, start, end), dtype=np.float32) \n",
    "            composite_vals = np.nan_to_num(composite_vals, nan=0.0)\n",
    "            composite_counts_per_peak.append(composite_vals.sum())\n",
    "            # Subset fusion bigwig file and sum counts at each peak \n",
    "            fusion_vals = np.array(fusion_signal.values(chrom, start, end), dtype=np.float32) \n",
    "            fusion_vals = np.nan_to_num(fusion_vals, nan=0.0)\n",
    "            fusion_counts_per_peak.append(fusion_vals.sum())\n",
    "        except:\n",
    "            continue\n",
    "    \n",
    "    ax = axes[i]\n",
    "    corr = np.corrcoef(composite_counts_per_peak, fusion_counts_per_peak)[0, 1]\n",
    "    ax.scatter(composite_counts_per_peak, fusion_counts_per_peak, s=4)\n",
    "    ax.axline((0, 0), slope=1, color='gray', linestyle='--')\n",
    "    ax.set_xlabel(f'{composite} (composite)', fontsize=13)\n",
    "    ax.set_ylabel(f'{fusion} (fusion)', fontsize=13)\n",
    "    ax.set_title(f'Correlation: {corr:.2f}', fontsize=13)\n",
    "\n",
    "    i += 1\n",
    "\n",
    "plt.suptitle('Composite vs fusion signal in peaks', y=1.1, fontsize=14)\n",
    "plt.subplots_adjust(wspace=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1431673a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x400 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=1, ncols=len(composite_fusion_dataset_pairs),\n",
    "                         figsize=(25, 4))\n",
    "i = 0\n",
    "for composite, fusion in composite_fusion_dataset_pairs.items():\n",
    "    composite_dir = dataset_directories[composite]\n",
    "    composite_non_peaks = pybedtools.BedTool(composite_dir + 'idr_peaks/gc_negatives.bed')\n",
    "    composite_signal_path = glob.glob(composite_dir + '*.plus.bw')[0]\n",
    "    composite_signal = pyBigWig.open(composite_signal_path)\n",
    "\n",
    "    fusion_dir = dataset_directories[fusion]\n",
    "    fusion_non_peaks = pybedtools.BedTool(fusion_dir + 'idr_peaks/gc_negatives.bed')\n",
    "    fusion_signal_path = glob.glob(fusion_dir + '*.plus.bw')[0]\n",
    "    fusion_signal = pyBigWig.open(fusion_signal_path)\n",
    "\n",
    "    composite_fusion_non_peaks_intersection = composite_non_peaks.intersect(fusion_non_peaks).to_dataframe()\n",
    "    \n",
    "    # Store sum of counts in each non-peak\n",
    "    composite_counts_per_non_peak = []\n",
    "    fusion_counts_per_non_peak = []\n",
    "\n",
    "    for _, non_peak in composite_fusion_non_peaks_intersection.iterrows():\n",
    "        try:\n",
    "            chrom, start, end = non_peak[\"chrom\"], int(non_peak[\"start\"]), int(non_peak[\"end\"])\n",
    "            # Subset composite bigwig file and sum counts at each peak\n",
    "            composite_vals = np.array(composite_signal.values(chrom, start, end), dtype=np.float32) \n",
    "            composite_vals = np.nan_to_num(composite_vals, nan=0.0)\n",
    "            composite_counts_per_non_peak.append(composite_vals.sum())\n",
    "            # Subset fusion bigwig file and sum counts at each peak \n",
    "            fusion_vals = np.array(fusion_signal.values(chrom, start, end), dtype=np.float32) \n",
    "            fusion_vals = np.nan_to_num(fusion_vals, nan=0.0)\n",
    "            fusion_counts_per_non_peak.append(fusion_vals.sum())\n",
    "        except:\n",
    "            continue\n",
    "    \n",
    "    ax = axes[i]\n",
    "    corr = np.corrcoef(composite_counts_per_non_peak, fusion_counts_per_non_peak)[0, 1]\n",
    "    ax.scatter(composite_counts_per_non_peak, fusion_counts_per_non_peak, s=4)\n",
    "    ax.axline((0, 0), slope=1, color='gray', linestyle='--')\n",
    "    ax.set_xlabel(f'{composite} signal (composite)', fontsize=12)\n",
    "    ax.set_ylabel(f'{fusion} signal (fusion)', fontsize=12)\n",
    "    ax.set_title(f'{composite} vs {fusion}\\n(Correlation: {corr:.2f})', fontsize=12)\n",
    "\n",
    "    i += 1\n",
    "\n",
    "plt.suptitle('Composite vs fusion signal in non-peaks', y=1.1, fontsize=14)\n",
    "plt.subplots_adjust(wspace=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0fbaebbe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pyBigWig.bigWigFile at 0x7fe64c7b6ea0>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "composite_dir = '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Wray_et_al/Reh_RUNX1_B/'\n",
    "composite_peaks = pybedtools.BedTool(composite_dir + 'idr_peaks/idr_thresholded_peaks.narrowPeak')\n",
    "composite_signal_path = glob.glob(composite_dir + '*.plus.bw')[0]\n",
    "composite_signal = pyBigWig.open(composite_signal_path)\n",
    "composite_signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8a837e1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pyBigWig.bigWigFile at 0x7fe64c7b65d0>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fusion_dir = '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Wray_et_al/Reh_HPA/'\n",
    "fusion_peaks = pybedtools.BedTool(fusion_dir + 'idr_peaks/idr_thresholded_peaks.narrowPeak')\n",
    "fusion_signal_path = glob.glob(fusion_dir + '*.plus.bw')[0]\n",
    "fusion_signal = pyBigWig.open(fusion_signal_path)\n",
    "fusion_signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2aec33ac",
   "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>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>strand</th>\n",
       "      <th>thickStart</th>\n",
       "      <th>thickEnd</th>\n",
       "      <th>itemRgb</th>\n",
       "      <th>blockCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr7</td>\n",
       "      <td>92133644</td>\n",
       "      <td>92134072</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>149.4910</td>\n",
       "      <td>-1</td>\n",
       "      <td>218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr21</td>\n",
       "      <td>45287805</td>\n",
       "      <td>45288250</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>147.6020</td>\n",
       "      <td>-1</td>\n",
       "      <td>289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr11</td>\n",
       "      <td>125887508</td>\n",
       "      <td>125887835</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>147.3560</td>\n",
       "      <td>-1</td>\n",
       "      <td>374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr16</td>\n",
       "      <td>12322809</td>\n",
       "      <td>12323299</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>127.4260</td>\n",
       "      <td>-1</td>\n",
       "      <td>397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr16</td>\n",
       "      <td>89917807</td>\n",
       "      <td>89918259</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>115.2560</td>\n",
       "      <td>-1</td>\n",
       "      <td>298</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>chr14</td>\n",
       "      <td>22071142</td>\n",
       "      <td>22071315</td>\n",
       "      <td>.</td>\n",
       "      <td>627</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>12.1738</td>\n",
       "      <td>-1</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>chr19</td>\n",
       "      <td>58347071</td>\n",
       "      <td>58347354</td>\n",
       "      <td>.</td>\n",
       "      <td>607</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>11.6521</td>\n",
       "      <td>-1</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>chr21</td>\n",
       "      <td>42496164</td>\n",
       "      <td>42496382</td>\n",
       "      <td>.</td>\n",
       "      <td>555</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>11.5812</td>\n",
       "      <td>-1</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>chr4</td>\n",
       "      <td>8602835</td>\n",
       "      <td>8603273</td>\n",
       "      <td>.</td>\n",
       "      <td>559</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>11.4197</td>\n",
       "      <td>-1</td>\n",
       "      <td>148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408</th>\n",
       "      <td>chr1</td>\n",
       "      <td>57737020</td>\n",
       "      <td>57737339</td>\n",
       "      <td>.</td>\n",
       "      <td>544</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>11.3007</td>\n",
       "      <td>-1</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>409 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     chrom      start        end name  score strand  thickStart  thickEnd  \\\n",
       "0     chr7   92133644   92134072    .   1000      .          -1  149.4910   \n",
       "1    chr21   45287805   45288250    .   1000      .          -1  147.6020   \n",
       "2    chr11  125887508  125887835    .   1000      .          -1  147.3560   \n",
       "3    chr16   12322809   12323299    .   1000      .          -1  127.4260   \n",
       "4    chr16   89917807   89918259    .   1000      .          -1  115.2560   \n",
       "..     ...        ...        ...  ...    ...    ...         ...       ...   \n",
       "404  chr14   22071142   22071315    .    627      .          -1   12.1738   \n",
       "405  chr19   58347071   58347354    .    607      .          -1   11.6521   \n",
       "406  chr21   42496164   42496382    .    555      .          -1   11.5812   \n",
       "407   chr4    8602835    8603273    .    559      .          -1   11.4197   \n",
       "408   chr1   57737020   57737339    .    544      .          -1   11.3007   \n",
       "\n",
       "     itemRgb  blockCount  \n",
       "0         -1         218  \n",
       "1         -1         289  \n",
       "2         -1         374  \n",
       "3         -1         397  \n",
       "4         -1         298  \n",
       "..       ...         ...  \n",
       "404       -1          81  \n",
       "405       -1         127  \n",
       "406       -1          91  \n",
       "407       -1         148  \n",
       "408       -1          94  \n",
       "\n",
       "[409 rows x 10 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "composite_fusion_peaks_intersection = composite_peaks.intersect(fusion_peaks).to_dataframe()\n",
    "composite_fusion_peaks_intersection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2adc1bff",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Store sum of counts in each peak\n",
    "composite_counts_per_peak = []\n",
    "fusion_counts_per_peak = []\n",
    "\n",
    "for _, peak in composite_fusion_peaks_intersection.iterrows():\n",
    "    chrom, start, end = peak[\"chrom\"], int(peak[\"start\"]), int(peak[\"end\"])\n",
    "    # Subset composite bigwig file and sum counts at each peak\n",
    "    composite_vals = np.array(composite_signal.values(chrom, start, end), dtype=np.float32) \n",
    "    composite_vals = np.nan_to_num(composite_vals, nan=0.0)\n",
    "    composite_counts_per_peak.append(composite_vals.sum())\n",
    "    # Subset fusion bigwig file and sum counts at each peak \n",
    "    fusion_vals = np.array(fusion_signal.values(chrom, start, end), dtype=np.float32) \n",
    "    fusion_vals = np.nan_to_num(fusion_vals, nan=0.0)\n",
    "    fusion_counts_per_peak.append(fusion_vals.sum())\n",
    "\n",
    "corr = np.corrcoef(composite_counts_per_peak, fusion_counts_per_peak)[0, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "388b4469",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Composite vs fusion signal at peaks \\nCorrelation: 0.58')"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5, 5))\n",
    "plt.scatter(composite_counts_per_peak, fusion_counts_per_peak, s=4)\n",
    "plt.axline((0, 0), slope=1, color='gray', linestyle='--')\n",
    "plt.xlabel('Composite signal')\n",
    "plt.ylabel('Fusion signal')\n",
    "plt.title(f'Composite vs fusion signal at peaks \\nCorrelation: {corr:.2f}', fontsize=11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cfeb4dae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pyBigWig.bigWigFile at 0x7fe6195972d0>"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "composite_dir = '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Wray_et_al/Reh_RUNX1_B/'\n",
    "composite_non_peaks = pybedtools.BedTool(composite_dir + 'idr_peaks/gc_negatives.bed')\n",
    "composite_signal_path = glob.glob(composite_dir + '*.plus.bw')[0]\n",
    "composite_signal = pyBigWig.open(composite_signal_path)\n",
    "composite_signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40a8125f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pyBigWig.bigWigFile at 0x7fe629bfa810>"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fusion_dir = '/users/shouvikm/data/Cell_Lines_Ped_Leukemia/Reh/Wray_et_al/Reh_HPA/'\n",
    "fusion_non_peaks = pybedtools.BedTool(fusion_dir + 'idr_peaks/gc_negatives.bed')\n",
    "fusion_signal_path = glob.glob(fusion_dir + '*.plus.bw')[0]\n",
    "fusion_signal = pyBigWig.open(fusion_signal_path)\n",
    "fusion_signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d8b69619",
   "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>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>strand</th>\n",
       "      <th>thickStart</th>\n",
       "      <th>thickEnd</th>\n",
       "      <th>itemRgb</th>\n",
       "      <th>blockCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr22</td>\n",
       "      <td>48263000</td>\n",
       "      <td>48264114</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr19</td>\n",
       "      <td>314000</td>\n",
       "      <td>314114</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr11</td>\n",
       "      <td>117733000</td>\n",
       "      <td>117735114</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr15</td>\n",
       "      <td>77817000</td>\n",
       "      <td>77817114</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr20</td>\n",
       "      <td>44037000</td>\n",
       "      <td>44037114</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1057</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2781</th>\n",
       "      <td>chr21</td>\n",
       "      <td>44242000</td>\n",
       "      <td>44243114</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2782</th>\n",
       "      <td>chr21</td>\n",
       "      <td>44427000</td>\n",
       "      <td>44427114</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2783</th>\n",
       "      <td>chr21</td>\n",
       "      <td>44425000</td>\n",
       "      <td>44425114</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2784</th>\n",
       "      <td>chr21</td>\n",
       "      <td>46097000</td>\n",
       "      <td>46097114</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2785</th>\n",
       "      <td>chr21</td>\n",
       "      <td>46095000</td>\n",
       "      <td>46096114</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2786 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      chrom      start        end name  score strand  thickStart  thickEnd  \\\n",
       "0     chr22   48263000   48264114    .      0      .           0         0   \n",
       "1     chr19     314000     314114    .      0      .           0         0   \n",
       "2     chr11  117733000  117735114    .      0      .           0         0   \n",
       "3     chr15   77817000   77817114    .      0      .           0         0   \n",
       "4     chr20   44037000   44037114    .      0      .           0         0   \n",
       "...     ...        ...        ...  ...    ...    ...         ...       ...   \n",
       "2781  chr21   44242000   44243114    .      0      .           0         0   \n",
       "2782  chr21   44427000   44427114    .      0      .           0         0   \n",
       "2783  chr21   44425000   44425114    .      0      .           0         0   \n",
       "2784  chr21   46097000   46097114    .      0      .           0         0   \n",
       "2785  chr21   46095000   46096114    .      0      .           0         0   \n",
       "\n",
       "      itemRgb  blockCount  \n",
       "0           0        1057  \n",
       "1           0        1057  \n",
       "2           0        1057  \n",
       "3           0        1057  \n",
       "4           0        1057  \n",
       "...       ...         ...  \n",
       "2781        0        1057  \n",
       "2782        0        1057  \n",
       "2783        0        1057  \n",
       "2784        0        1057  \n",
       "2785        0        1057  \n",
       "\n",
       "[2786 rows x 10 columns]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "composite_fusion_non_peaks_intersection = composite_non_peaks.intersect(fusion_non_peaks).to_dataframe()\n",
    "composite_fusion_non_peaks_intersection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0fd106a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Store sum of counts in each non-peak\n",
    "composite_counts_per_non_peak = []\n",
    "fusion_counts_per_non_peak = []\n",
    "\n",
    "for _, non_peak in composite_fusion_non_peaks_intersection.iterrows():\n",
    "    chrom, start, end = non_peak[\"chrom\"], int(non_peak[\"start\"]), int(non_peak[\"end\"])\n",
    "    # Subset composite bigwig file and sum counts at each peak\n",
    "    composite_vals = np.array(composite_signal.values(chrom, start, end), dtype=np.float32) \n",
    "    composite_vals = np.nan_to_num(composite_vals, nan=0.0)\n",
    "    composite_counts_per_non_peak.append(composite_vals.sum())\n",
    "    # Subset fusion bigwig file and sum counts at each peak \n",
    "    fusion_vals = np.array(fusion_signal.values(chrom, start, end), dtype=np.float32) \n",
    "    fusion_vals = np.nan_to_num(fusion_vals, nan=0.0)\n",
    "    fusion_counts_per_non_peak.append(fusion_vals.sum())\n",
    "\n",
    "corr = np.corrcoef(composite_counts_per_non_peak, fusion_counts_per_non_peak)[0, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aa4f8fc8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Composite vs fusion signal in non-peaks \\nCorrelation: 0.80')"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5, 5))\n",
    "plt.scatter(composite_counts_per_non_peak, fusion_counts_per_non_peak, s=4)\n",
    "plt.axline((0, 0), slope=1, color='gray', linestyle='--')\n",
    "plt.xlabel('Composite signal')\n",
    "plt.ylabel('Fusion signal')\n",
    "plt.title(f'Composite vs fusion signal in non-peaks \\nCorrelation: {corr:.2f}', fontsize=11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d5328082",
   "metadata": {},
   "outputs": [],
   "source": [
    "bias_corrected_prediction_directories = {\n",
    "    'Reh_HPA': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/Reh_HPA/',\n",
    "    'Reh_DMSO_HPA': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/Reh_DMSO_HPA/',\n",
    "    'Nalm6_ETV6-RUNX1_V5_B': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/Nalm6_ETV6-RUNX1_V5_B/',\n",
    "    'REH_ETV6-RUNX1_rep1': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/REH_ETV6-RUNX1_rep1/',\n",
    "    'REH_ETV6-RUNX1_rep2': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/REH_ETV6-RUNX1_rep2/',\n",
    "    'Reh_RUNX1_B': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/Reh_RUNX1_B/',\n",
    "    'Reh_DMSO_RUNX1': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/Reh_DMSO_RUNX1/',\n",
    "    'Nalm6_RUNX1': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/Nalm6_RUNX1/',\n",
    "    'REH_RUNX1_rep1': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/REH_RUNX1_rep1/',\n",
    "    'REH_RUNX1_rep2': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/REH_RUNX1_rep2/',\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b06edbd3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x400 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=1, ncols=len(composite_fusion_dataset_pairs),\n",
    "                         figsize=(25, 4))\n",
    "i = 0\n",
    "for composite, fusion in composite_fusion_dataset_pairs.items():\n",
    "    composite_data_dir = dataset_directories[composite]\n",
    "    composite_prediction_dir = bias_corrected_prediction_directories[composite]\n",
    "    composite_peaks = pybedtools.BedTool(composite_data_dir + 'idr_peaks/idr_thresholded_peaks.narrowPeak')\n",
    "    composite_pred_signal_path = composite_prediction_dir + 'predictions_plus_avg.bw'\n",
    "    composite_pred_signal = pyBigWig.open(composite_pred_signal_path)\n",
    "\n",
    "    fusion_data_dir = dataset_directories[fusion]\n",
    "    fusion_prediction_dir = bias_corrected_prediction_directories[fusion]\n",
    "    fusion_peaks = pybedtools.BedTool(fusion_data_dir + 'idr_peaks/idr_thresholded_peaks.narrowPeak')\n",
    "    fusion_pred_signal_path = fusion_prediction_dir + 'predictions_plus_avg.bw'\n",
    "    fusion_pred_signal = pyBigWig.open(fusion_pred_signal_path)\n",
    "\n",
    "    composite_fusion_peaks_intersection = composite_peaks.intersect(fusion_peaks).to_dataframe()\n",
    "\n",
    "    # Store sum of predicted counts in each peak\n",
    "    composite_pred_counts_per_peak = []\n",
    "    fusion_pred_counts_per_peak = []\n",
    "    for _, peak in composite_fusion_peaks_intersection.iterrows():\n",
    "        try:\n",
    "            chrom, start, end = peak[\"chrom\"], int(peak[\"start\"]), int(peak[\"end\"])\n",
    "            # Subset composite bigwig file and sum counts at each peak\n",
    "            composite_vals = np.array(composite_pred_signal.values(chrom, start, end), dtype=np.float32) \n",
    "            composite_vals = np.nan_to_num(composite_vals, nan=0.0)\n",
    "            composite_pred_counts_per_peak.append(composite_vals.sum())\n",
    "            # Subset fusion bigwig file and sum counts at each peak\n",
    "            fusion_vals = np.array(fusion_pred_signal.values(chrom, start, end), dtype=np.float32) \n",
    "            fusion_vals = np.nan_to_num(fusion_vals, nan=0.0)\n",
    "            fusion_pred_counts_per_peak.append(fusion_vals.sum())\n",
    "        except:\n",
    "            continue\n",
    "\n",
    "    ax = axes[i]\n",
    "    corr = np.corrcoef(composite_pred_counts_per_peak, fusion_pred_counts_per_peak)[0, 1]\n",
    "    ax.scatter(composite_pred_counts_per_peak, fusion_pred_counts_per_peak, s=4)\n",
    "    ax.axline((0, 0), slope=1, color='gray', linestyle='--')\n",
    "    ax.set_xlabel(f'{composite} (composite)', fontsize=13)\n",
    "    ax.set_ylabel(f'{fusion} (fusion)', fontsize=13)\n",
    "    ax.set_title(f'Correlation: {corr:.2f}', fontsize=13)\n",
    "\n",
    "    i += 1\n",
    "\n",
    "plt.suptitle('Composite vs fusion predicted signal in peaks', y=1.1, fontsize=14)\n",
    "plt.subplots_adjust(wspace=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cd9afbf7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pyBigWig.bigWigFile at 0x7fc5cb77d570>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "composite = 'Reh_RUNX1_B'\n",
    "composite_data_dir = dataset_directories[composite]\n",
    "composite_prediction_dir = bias_corrected_prediction_directories[composite]\n",
    "composite_peaks = pybedtools.BedTool(composite_data_dir + 'idr_peaks/idr_thresholded_peaks.narrowPeak')\n",
    "composite_pred_signal_path = composite_prediction_dir + 'predictions_plus_avg.bw'\n",
    "composite_pred_signal = pyBigWig.open(composite_pred_signal_path)\n",
    "composite_pred_signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d7742cab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pyBigWig.bigWigFile at 0x7fc61c6ff240>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fusion = 'Reh_HPA'\n",
    "fusion_data_dir = dataset_directories[fusion]\n",
    "fusion_prediction_dir = bias_corrected_prediction_directories[fusion]\n",
    "fusion_peaks = pybedtools.BedTool(fusion_data_dir + 'idr_peaks/idr_thresholded_peaks.narrowPeak')\n",
    "fusion_pred_signal_path = fusion_prediction_dir + 'predictions_plus_avg.bw'\n",
    "fusion_pred_signal = pyBigWig.open(fusion_pred_signal_path)\n",
    "fusion_pred_signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "042eb9b8",
   "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>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>strand</th>\n",
       "      <th>thickStart</th>\n",
       "      <th>thickEnd</th>\n",
       "      <th>itemRgb</th>\n",
       "      <th>blockCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr7</td>\n",
       "      <td>92133644</td>\n",
       "      <td>92134072</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>149.4910</td>\n",
       "      <td>-1</td>\n",
       "      <td>218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr21</td>\n",
       "      <td>45287805</td>\n",
       "      <td>45288250</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>147.6020</td>\n",
       "      <td>-1</td>\n",
       "      <td>289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr11</td>\n",
       "      <td>125887508</td>\n",
       "      <td>125887835</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>147.3560</td>\n",
       "      <td>-1</td>\n",
       "      <td>374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr16</td>\n",
       "      <td>12322809</td>\n",
       "      <td>12323299</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>127.4260</td>\n",
       "      <td>-1</td>\n",
       "      <td>397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr16</td>\n",
       "      <td>89917807</td>\n",
       "      <td>89918259</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>115.2560</td>\n",
       "      <td>-1</td>\n",
       "      <td>298</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>chr14</td>\n",
       "      <td>22071142</td>\n",
       "      <td>22071315</td>\n",
       "      <td>.</td>\n",
       "      <td>627</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>12.1738</td>\n",
       "      <td>-1</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>chr19</td>\n",
       "      <td>58347071</td>\n",
       "      <td>58347354</td>\n",
       "      <td>.</td>\n",
       "      <td>607</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>11.6521</td>\n",
       "      <td>-1</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>chr21</td>\n",
       "      <td>42496164</td>\n",
       "      <td>42496382</td>\n",
       "      <td>.</td>\n",
       "      <td>555</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>11.5812</td>\n",
       "      <td>-1</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>chr4</td>\n",
       "      <td>8602835</td>\n",
       "      <td>8603273</td>\n",
       "      <td>.</td>\n",
       "      <td>559</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>11.4197</td>\n",
       "      <td>-1</td>\n",
       "      <td>148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408</th>\n",
       "      <td>chr1</td>\n",
       "      <td>57737020</td>\n",
       "      <td>57737339</td>\n",
       "      <td>.</td>\n",
       "      <td>544</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>11.3007</td>\n",
       "      <td>-1</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>409 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     chrom      start        end name  score strand  thickStart  thickEnd  \\\n",
       "0     chr7   92133644   92134072    .   1000      .          -1  149.4910   \n",
       "1    chr21   45287805   45288250    .   1000      .          -1  147.6020   \n",
       "2    chr11  125887508  125887835    .   1000      .          -1  147.3560   \n",
       "3    chr16   12322809   12323299    .   1000      .          -1  127.4260   \n",
       "4    chr16   89917807   89918259    .   1000      .          -1  115.2560   \n",
       "..     ...        ...        ...  ...    ...    ...         ...       ...   \n",
       "404  chr14   22071142   22071315    .    627      .          -1   12.1738   \n",
       "405  chr19   58347071   58347354    .    607      .          -1   11.6521   \n",
       "406  chr21   42496164   42496382    .    555      .          -1   11.5812   \n",
       "407   chr4    8602835    8603273    .    559      .          -1   11.4197   \n",
       "408   chr1   57737020   57737339    .    544      .          -1   11.3007   \n",
       "\n",
       "     itemRgb  blockCount  \n",
       "0         -1         218  \n",
       "1         -1         289  \n",
       "2         -1         374  \n",
       "3         -1         397  \n",
       "4         -1         298  \n",
       "..       ...         ...  \n",
       "404       -1          81  \n",
       "405       -1         127  \n",
       "406       -1          91  \n",
       "407       -1         148  \n",
       "408       -1          94  \n",
       "\n",
       "[409 rows x 10 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "composite_fusion_peaks_intersection = composite_peaks.intersect(fusion_peaks).to_dataframe()\n",
    "composite_fusion_peaks_intersection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a9bff1cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Store sum of predicted counts in each peak\n",
    "composite_pred_counts_per_peak = []\n",
    "fusion_pred_counts_per_peak = []\n",
    "\n",
    "for _, peak in composite_fusion_peaks_intersection.iterrows():\n",
    "    chrom, start, end = peak[\"chrom\"], int(peak[\"start\"]), int(peak[\"end\"])\n",
    "    # Subset composite bigwig file and sum counts at each peak\n",
    "    composite_vals = np.array(composite_pred_signal.values(chrom, start, end), dtype=np.float32) \n",
    "    composite_vals = np.nan_to_num(composite_vals, nan=0.0)\n",
    "    composite_pred_counts_per_peak.append(composite_vals.sum())\n",
    "    # Subset fusion bigwig file and sum counts at each peak\n",
    "    fusion_vals = np.array(fusion_pred_signal.values(chrom, start, end), dtype=np.float32) \n",
    "    fusion_vals = np.nan_to_num(fusion_vals, nan=0.0)\n",
    "    fusion_pred_counts_per_peak.append(fusion_vals.sum())\n",
    "\n",
    "corr = np.corrcoef(composite_pred_counts_per_peak, fusion_pred_counts_per_peak)[0, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e5aa865a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Composite vs fusion predicted signal at peaks \\nCorrelation: 0.67')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5, 5))\n",
    "plt.scatter(composite_pred_counts_per_peak, fusion_pred_counts_per_peak, s=4)\n",
    "plt.axline((0, 0), slope=1, color='gray', linestyle='--')\n",
    "plt.xlabel('Composite predicted signal')\n",
    "plt.ylabel('Fusion predicted signal')\n",
    "plt.title(f'Composite vs fusion predicted signal at peaks \\nCorrelation: {corr:.2f}', fontsize=11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "96389387",
   "metadata": {},
   "outputs": [],
   "source": [
    "deconvolved_native_prediction_directories = {\n",
    "    'Reh_RUNX1_B': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/Reh_RUNX1_B_native/',\n",
    "    'Reh_DMSO_RUNX1': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/Reh_DMSO_RUNX1_native/',\n",
    "    'Nalm6_RUNX1': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/Nalm6_RUNX1_native/',\n",
    "    'REH_RUNX1_rep1': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/REH_RUNX1_rep1_native/',\n",
    "    'REH_RUNX1_rep2': '/users/shouvikm/BPNet/fusion_deconvolution_V3/predictions/REH_RUNX1_rep2_native/',\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "282ca2d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x400 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=1, ncols=len(composite_fusion_dataset_pairs),\n",
    "                         figsize=(25, 4))\n",
    "i = 0\n",
    "for native, fusion in composite_fusion_dataset_pairs.items():\n",
    "    native_data_dir = dataset_directories[native]\n",
    "    native_prediction_dir = deconvolved_native_prediction_directories[native]\n",
    "    native_peaks = pybedtools.BedTool(native_data_dir + 'idr_peaks/idr_thresholded_peaks.narrowPeak')\n",
    "    native_pred_signal_path = native_prediction_dir + 'predictions_plus_avg.bw'\n",
    "    native_pred_signal = pyBigWig.open(native_pred_signal_path)\n",
    "\n",
    "    fusion_data_dir = dataset_directories[fusion]\n",
    "    fusion_prediction_dir = bias_corrected_prediction_directories[fusion]\n",
    "    fusion_peaks = pybedtools.BedTool(fusion_data_dir + 'idr_peaks/idr_thresholded_peaks.narrowPeak')\n",
    "    fusion_pred_signal_path = fusion_prediction_dir + 'predictions_plus_avg.bw'\n",
    "    fusion_pred_signal = pyBigWig.open(fusion_pred_signal_path)\n",
    "\n",
    "    native_fusion_peaks_intersection = native_peaks.intersect(fusion_peaks).to_dataframe()\n",
    "\n",
    "    # Store sum of predicted counts in each peak\n",
    "    native_pred_counts_per_peak = []\n",
    "    fusion_pred_counts_per_peak = []\n",
    "    for _, peak in native_fusion_peaks_intersection.iterrows():\n",
    "        try:\n",
    "            chrom, start, end = peak[\"chrom\"], int(peak[\"start\"]), int(peak[\"end\"])\n",
    "            # Subset native bigwig file and sum counts at each peak\n",
    "            native_vals = np.array(native_pred_signal.values(chrom, start, end), dtype=np.float32) \n",
    "            native_vals = np.nan_to_num(native_vals, nan=0.0)\n",
    "            native_pred_counts_per_peak.append(native_vals.sum())\n",
    "            # Subset fusion bigwig file and sum counts at each peak\n",
    "            fusion_vals = np.array(fusion_pred_signal.values(chrom, start, end), dtype=np.float32) \n",
    "            fusion_vals = np.nan_to_num(fusion_vals, nan=0.0)\n",
    "            fusion_pred_counts_per_peak.append(fusion_vals.sum())\n",
    "        except:\n",
    "            continue\n",
    "\n",
    "    ax = axes[i]\n",
    "    corr = np.corrcoef(native_pred_counts_per_peak, fusion_pred_counts_per_peak)[0, 1]\n",
    "    ax.scatter(native_pred_counts_per_peak, fusion_pred_counts_per_peak, s=4)\n",
    "    ax.axline((0, 0), slope=1, color='gray', linestyle='--')\n",
    "    ax.set_xlabel(f'{native} (native)', fontsize=13)\n",
    "    ax.set_ylabel(f'{fusion} (fusion)', fontsize=13)\n",
    "    ax.set_title(f'Correlation: {corr:.2f}', fontsize=13)\n",
    "\n",
    "    i += 1\n",
    "\n",
    "plt.suptitle('Native vs fusion predicted signal in peaks', y=1.1, fontsize=14)\n",
    "plt.subplots_adjust(wspace=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3c463d27",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pyBigWig.bigWigFile at 0x7fc5b233e3f0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "native = 'Reh_RUNX1_B'\n",
    "native_data_dir = dataset_directories[native]\n",
    "native_prediction_dir = deconvolved_native_prediction_directories[native]\n",
    "native_peaks = pybedtools.BedTool(native_data_dir + 'idr_peaks/idr_thresholded_peaks.narrowPeak')\n",
    "native_pred_signal_path = native_prediction_dir + 'predictions_plus_avg.bw'\n",
    "native_pred_signal = pyBigWig.open(native_pred_signal_path)\n",
    "native_pred_signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "287d850d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pyBigWig.bigWigFile at 0x7fc5cb77dd80>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fusion = 'Reh_HPA'\n",
    "fusion_data_dir = dataset_directories[fusion]\n",
    "fusion_prediction_dir = bias_corrected_prediction_directories[fusion]\n",
    "fusion_peaks = pybedtools.BedTool(fusion_data_dir + 'idr_peaks/idr_thresholded_peaks.narrowPeak')\n",
    "fusion_pred_signal_path = fusion_prediction_dir + 'predictions_plus_avg.bw'\n",
    "fusion_pred_signal = pyBigWig.open(fusion_pred_signal_path)\n",
    "fusion_pred_signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1c8cbe91",
   "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>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>strand</th>\n",
       "      <th>thickStart</th>\n",
       "      <th>thickEnd</th>\n",
       "      <th>itemRgb</th>\n",
       "      <th>blockCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr7</td>\n",
       "      <td>92133644</td>\n",
       "      <td>92134072</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>149.4910</td>\n",
       "      <td>-1</td>\n",
       "      <td>218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr21</td>\n",
       "      <td>45287805</td>\n",
       "      <td>45288250</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>147.6020</td>\n",
       "      <td>-1</td>\n",
       "      <td>289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr11</td>\n",
       "      <td>125887508</td>\n",
       "      <td>125887835</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>147.3560</td>\n",
       "      <td>-1</td>\n",
       "      <td>374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr16</td>\n",
       "      <td>12322809</td>\n",
       "      <td>12323299</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>127.4260</td>\n",
       "      <td>-1</td>\n",
       "      <td>397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr16</td>\n",
       "      <td>89917807</td>\n",
       "      <td>89918259</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>115.2560</td>\n",
       "      <td>-1</td>\n",
       "      <td>298</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>chr14</td>\n",
       "      <td>22071142</td>\n",
       "      <td>22071315</td>\n",
       "      <td>.</td>\n",
       "      <td>627</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>12.1738</td>\n",
       "      <td>-1</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>chr19</td>\n",
       "      <td>58347071</td>\n",
       "      <td>58347354</td>\n",
       "      <td>.</td>\n",
       "      <td>607</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>11.6521</td>\n",
       "      <td>-1</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>chr21</td>\n",
       "      <td>42496164</td>\n",
       "      <td>42496382</td>\n",
       "      <td>.</td>\n",
       "      <td>555</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>11.5812</td>\n",
       "      <td>-1</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>chr4</td>\n",
       "      <td>8602835</td>\n",
       "      <td>8603273</td>\n",
       "      <td>.</td>\n",
       "      <td>559</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>11.4197</td>\n",
       "      <td>-1</td>\n",
       "      <td>148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408</th>\n",
       "      <td>chr1</td>\n",
       "      <td>57737020</td>\n",
       "      <td>57737339</td>\n",
       "      <td>.</td>\n",
       "      <td>544</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>11.3007</td>\n",
       "      <td>-1</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>409 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     chrom      start        end name  score strand  thickStart  thickEnd  \\\n",
       "0     chr7   92133644   92134072    .   1000      .          -1  149.4910   \n",
       "1    chr21   45287805   45288250    .   1000      .          -1  147.6020   \n",
       "2    chr11  125887508  125887835    .   1000      .          -1  147.3560   \n",
       "3    chr16   12322809   12323299    .   1000      .          -1  127.4260   \n",
       "4    chr16   89917807   89918259    .   1000      .          -1  115.2560   \n",
       "..     ...        ...        ...  ...    ...    ...         ...       ...   \n",
       "404  chr14   22071142   22071315    .    627      .          -1   12.1738   \n",
       "405  chr19   58347071   58347354    .    607      .          -1   11.6521   \n",
       "406  chr21   42496164   42496382    .    555      .          -1   11.5812   \n",
       "407   chr4    8602835    8603273    .    559      .          -1   11.4197   \n",
       "408   chr1   57737020   57737339    .    544      .          -1   11.3007   \n",
       "\n",
       "     itemRgb  blockCount  \n",
       "0         -1         218  \n",
       "1         -1         289  \n",
       "2         -1         374  \n",
       "3         -1         397  \n",
       "4         -1         298  \n",
       "..       ...         ...  \n",
       "404       -1          81  \n",
       "405       -1         127  \n",
       "406       -1          91  \n",
       "407       -1         148  \n",
       "408       -1          94  \n",
       "\n",
       "[409 rows x 10 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "native_fusion_peaks_intersection = native_peaks.intersect(fusion_peaks).to_dataframe()\n",
    "native_fusion_peaks_intersection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6a8f5af9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Store sum of predicted counts in each peak\n",
    "native_pred_counts_per_peak = []\n",
    "fusion_pred_counts_per_peak = []\n",
    "\n",
    "for _, peak in native_fusion_peaks_intersection.iterrows():\n",
    "    chrom, start, end = peak[\"chrom\"], int(peak[\"start\"]), int(peak[\"end\"])\n",
    "    # Subset composite bigwig file and sum counts at each peak\n",
    "    native_vals = np.array(native_pred_signal.values(chrom, start, end), dtype=np.float32) \n",
    "    native_vals = np.nan_to_num(native_vals, nan=0.0)\n",
    "    native_pred_counts_per_peak.append(native_vals.sum())\n",
    "    # Subset fusion bigwig file and sum counts at each peak\n",
    "    fusion_vals = np.array(fusion_pred_signal.values(chrom, start, end), dtype=np.float32) \n",
    "    fusion_vals = np.nan_to_num(fusion_vals, nan=0.0)\n",
    "    fusion_pred_counts_per_peak.append(fusion_vals.sum())\n",
    "\n",
    "corr = np.corrcoef(native_pred_counts_per_peak, fusion_pred_counts_per_peak)[0, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "11bbd05b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Native vs fusion predicted signal at peaks \\nCorrelation: 0.63')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5, 5))\n",
    "plt.scatter(native_pred_counts_per_peak, fusion_pred_counts_per_peak, s=4)\n",
    "plt.axline((0, 0), slope=1, color='gray', linestyle='--')\n",
    "plt.xlabel('Native predicted signal')\n",
    "plt.ylabel('Fusion predicted signal')\n",
    "plt.title(f'Native vs fusion predicted signal at peaks \\nCorrelation: {corr:.2f}', fontsize=11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc8f8679",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f66da187",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6655c706",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11b95aee",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "a2432085",
   "metadata": {},
   "source": [
    "#### Reh_HPA vs Reh_PAS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "12141465",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:05.456365Z",
     "start_time": "2026-01-08T03:16:03.699489Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "824"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reh_hpa_peaks = pybedtools.BedTool(base_path + 'Wray_et_al/Reh_HPA/idr_peaks/idr_thresholded_peaks')\n",
    "reh_hpa_peaks.count()\n",
    "# reh_hpa_peaks.to_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cae14563",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:06.467230Z",
     "start_time": "2026-01-08T03:16:06.378491Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "747"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reh_pas_peaks = pybedtools.BedTool(base_path + 'Wray_et_al/Reh_PAS/idr_peaks/idr_thresholded_peaks')\n",
    "reh_pas_peaks.count()\n",
    "# reh_pas_peaks.to_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "eb4669c3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:07.134486Z",
     "start_time": "2026-01-08T03:16:07.074135Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "549"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersection = reh_hpa_peaks.intersect(reh_pas_peaks)\n",
    "intersection.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3d14c6fc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:07.671127Z",
     "start_time": "2026-01-08T03:16:07.497044Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1022"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "union = reh_hpa_peaks.cat(reh_pas_peaks, postmerge=True)\n",
    "union.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a4ba62c3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:09.618578Z",
     "start_time": "2026-01-08T03:16:09.575679Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5371819960861057"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersection_over_union = intersection.count() / union.count()\n",
    "intersection_over_union"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "85cb192d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:16.720297Z",
     "start_time": "2026-01-08T03:16:16.708009Z"
    }
   },
   "outputs": [],
   "source": [
    "intersection_df = intersection.to_dataframe(names=range(20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4da99d11",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:17.119024Z",
     "start_time": "2026-01-08T03:16:17.090420Z"
    }
   },
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>chr7</td>\n",
       "      <td>50410132</td>\n",
       "      <td>50410608</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>25.6079</td>\n",
       "      <td>-1</td>\n",
       "      <td>230</td>\n",
       "      <td>2.71</td>\n",
       "      <td>3.31</td>\n",
       "      <td>50410132</td>\n",
       "      <td>50410664</td>\n",
       "      <td>37.36</td>\n",
       "      <td>238</td>\n",
       "      <td>50410211</td>\n",
       "      <td>50410598</td>\n",
       "      <td>25.6079</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       0         1         2  3     4  5   6        7   8    9     10    11  \\\n",
       "189  chr7  50410132  50410608  .  1000  .  -1  25.6079  -1  230  2.71  3.31   \n",
       "\n",
       "           12        13     14   15        16        17       18   19  \n",
       "189  50410132  50410664  37.36  238  50410211  50410598  25.6079  144  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Peak near IKZF1\n",
    "intersection_df[((intersection_df[0] == 'chr7') & \n",
    "                 (intersection_df[1] >= 50385591) & \n",
    "                 (intersection_df[2] <= 50415221))]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6c00603",
   "metadata": {},
   "source": [
    "#### Reh_HPA vs Nalm6_ETV6-RUNX1_V5_B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e41c4d95",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:13.936483Z",
     "start_time": "2026-01-08T03:16:13.733316Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4951"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nalm_etv6_runx1_peaks = pybedtools.BedTool(\n",
    "    base_path + 'Wray_et_al/Nalm6_ETV6-RUNX1_V5_B/idr_peaks/idr_thresholded_peaks'\n",
    ")\n",
    "nalm_etv6_runx1_peaks.count()\n",
    "# nalm_etv6_runx1_peaks.to_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a023ce98",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:14.508158Z",
     "start_time": "2026-01-08T03:16:14.446360Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "515"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersection = reh_hpa_peaks.intersect(nalm_etv6_runx1_peaks)\n",
    "intersection.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0bf454e1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:15.177189Z",
     "start_time": "2026-01-08T03:16:14.920110Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5260"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "union = reh_hpa_peaks.cat(nalm_etv6_runx1_peaks, postmerge=True)\n",
    "union.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "254aff84",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:15.406531Z",
     "start_time": "2026-01-08T03:16:15.329007Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0979087452471483"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersection_over_union = intersection.count() / union.count()\n",
    "intersection_over_union"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5de52662",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:16.720297Z",
     "start_time": "2026-01-08T03:16:16.708009Z"
    }
   },
   "outputs": [],
   "source": [
    "intersection_df = intersection.to_dataframe(names=range(20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0d8ced7a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:17.119024Z",
     "start_time": "2026-01-08T03:16:17.090420Z"
    }
   },
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>chr7</td>\n",
       "      <td>50410178</td>\n",
       "      <td>50410664</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>25.6079</td>\n",
       "      <td>-1</td>\n",
       "      <td>230</td>\n",
       "      <td>2.71</td>\n",
       "      <td>3.31</td>\n",
       "      <td>50410132</td>\n",
       "      <td>50410664</td>\n",
       "      <td>37.36</td>\n",
       "      <td>238</td>\n",
       "      <td>50410211</td>\n",
       "      <td>50410598</td>\n",
       "      <td>25.6079</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       0         1         2  3     4  5   6        7   8    9     10    11  \\\n",
       "166  chr7  50410178  50410664  .  1000  .  -1  25.6079  -1  230  2.71  3.31   \n",
       "\n",
       "           12        13     14   15        16        17       18   19  \n",
       "166  50410132  50410664  37.36  238  50410211  50410598  25.6079  144  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Peak near IKZF1\n",
    "intersection_df[((intersection_df[0] == 'chr7') & \n",
    "                 (intersection_df[1] >= 50385591) & \n",
    "                 (intersection_df[2] <= 50415221))]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6f8532c",
   "metadata": {},
   "source": [
    "#### Nalm6_RUNX1 vs Nalm6_ETV6-RUNX1_V5_B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d36ce3c0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:18.126889Z",
     "start_time": "2026-01-08T03:16:18.018351Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8242"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nalm_runx1_peaks = pybedtools.BedTool(\n",
    "    base_path + 'Wray_et_al/Nalm6_RUNX1/idr_peaks/idr_thresholded_peaks'\n",
    ")\n",
    "nalm_runx1_peaks.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5c111de0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:18.665857Z",
     "start_time": "2026-01-08T03:16:18.521320Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3142"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersection = nalm_runx1_peaks.intersect(nalm_etv6_runx1_peaks)\n",
    "intersection.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "93f53aeb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:21.480311Z",
     "start_time": "2026-01-08T03:16:21.043044Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10050"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "union = nalm_runx1_peaks.cat(nalm_etv6_runx1_peaks, postmerge=True)\n",
    "union.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d1ff8799",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:21.606962Z",
     "start_time": "2026-01-08T03:16:21.483276Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.312636815920398"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersection_over_union = intersection.count() / union.count()\n",
    "intersection_over_union"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8b283ef3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:22.830959Z",
     "start_time": "2026-01-08T03:16:22.802463Z"
    }
   },
   "outputs": [],
   "source": [
    "intersection_df = intersection.to_dataframe(names=range(20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "fabf9ed0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:23.370938Z",
     "start_time": "2026-01-08T03:16:23.343279Z"
    }
   },
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2026</th>\n",
       "      <td>chr7</td>\n",
       "      <td>50410178</td>\n",
       "      <td>50410566</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>20.3199</td>\n",
       "      <td>-1</td>\n",
       "      <td>216</td>\n",
       "      <td>1.92</td>\n",
       "      <td>2.57</td>\n",
       "      <td>50410126</td>\n",
       "      <td>50410535</td>\n",
       "      <td>20.3199</td>\n",
       "      <td>216</td>\n",
       "      <td>50410181</td>\n",
       "      <td>50410566</td>\n",
       "      <td>23.7865</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        0         1         2  3     4  5   6        7   8    9     10    11  \\\n",
       "2026  chr7  50410178  50410566  .  1000  .  -1  20.3199  -1  216  1.92  2.57   \n",
       "\n",
       "            12        13       14   15        16        17       18   19  \n",
       "2026  50410126  50410535  20.3199  216  50410181  50410566  23.7865  162  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Peak near IKZF1\n",
    "intersection_df[((intersection_df[0] == 'chr7') & \n",
    "                 (intersection_df[1] >= 50385591) & \n",
    "                 (intersection_df[2] <= 50415221))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "64739965",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:16:24.681209Z",
     "start_time": "2026-01-08T03:16:24.654520Z"
    }
   },
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>chr22</td>\n",
       "      <td>22244222</td>\n",
       "      <td>22244992</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>-1</td>\n",
       "      <td>47.495</td>\n",
       "      <td>-1</td>\n",
       "      <td>313</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.98</td>\n",
       "      <td>22244222</td>\n",
       "      <td>22244992</td>\n",
       "      <td>47.495</td>\n",
       "      <td>283</td>\n",
       "      <td>22244333</td>\n",
       "      <td>22244850</td>\n",
       "      <td>67.3195</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        0         1         2  3     4  5   6       7   8    9     10    11  \\\n",
       "552  chr22  22244222  22244992  .  1000  .  -1  47.495  -1  313  4.39  4.98   \n",
       "\n",
       "           12        13      14   15        16        17       18   19  \n",
       "552  22244222  22244992  47.495  283  22244333  22244850  67.3195  232  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Peak near VPREB1\n",
    "intersection_df[((intersection_df[0] == 'chr22') & \n",
    "                 (intersection_df[1] >= 22243690) & \n",
    "                 (intersection_df[2] <= 22246610))]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34b6a5d9",
   "metadata": {},
   "source": [
    "#### Peak overlap across all datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8207640c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:17:31.751375Z",
     "start_time": "2026-01-08T03:16:26.744340Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n",
      "5\n",
      "6\n",
      "7\n",
      "8\n",
      "9\n",
      "10\n",
      "11\n",
      "12\n",
      "13\n",
      "14\n"
     ]
    }
   ],
   "source": [
    "datasets = ['Reh_HPA', 'Reh_PAS', 'Reh_DMSO_HPA', 'REH_ETV6-RUNX1_rep1', \n",
    "            'REH_ETV6-RUNX1_rep2', 'Reh_ETV6_Atlas', 'Nalm6_ETV6-RUNX1_V5_B', \n",
    "            'Reh_RUNX1_B', 'Reh_DMSO_RUNX1', 'REH_RUNX1_rep1', 'REH_RUNX1_rep2', \n",
    "            'Nalm6_RUNX1', 'ETV6_HA_IP', 'Reh_ETV6-WT', 'Reh_ERG']\n",
    "\n",
    "peak_overlap_matrix = np.zeros((len(datasets), len(datasets)))\n",
    "for i, dataset_1 in enumerate(datasets):\n",
    "    print(i)\n",
    "    dataset_1_peaks_path = glob.glob(base_path + f'*/{dataset_1}/idr_peaks/idr_thresholded_peaks')[0]\n",
    "    dataset_1_peaks = pybedtools.BedTool(dataset_1_peaks_path)\n",
    "    for j, dataset_2 in enumerate(datasets):\n",
    "        dataset_2_peaks_path = glob.glob(base_path + f'*/{dataset_2}/idr_peaks/idr_thresholded_peaks')[0]\n",
    "        dataset_2_peaks = pybedtools.BedTool(dataset_2_peaks_path)\n",
    "        intersection = dataset_1_peaks.intersect(dataset_2_peaks)\n",
    "        union = dataset_1_peaks.cat(dataset_2_peaks, postmerge=True)\n",
    "        intersection_over_union = intersection.count() / union.count()\n",
    "        peak_overlap_matrix[i, j] = intersection_over_union"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "08cd9d7e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:17:36.517374Z",
     "start_time": "2026-01-08T03:17:36.478513Z"
    }
   },
   "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>Reh_HPA</th>\n",
       "      <th>Reh_PAS</th>\n",
       "      <th>Reh_DMSO_HPA</th>\n",
       "      <th>REH_ETV6-RUNX1_rep1</th>\n",
       "      <th>REH_ETV6-RUNX1_rep2</th>\n",
       "      <th>Reh_ETV6_Atlas</th>\n",
       "      <th>Nalm6_ETV6-RUNX1_V5_B</th>\n",
       "      <th>Reh_RUNX1_B</th>\n",
       "      <th>Reh_DMSO_RUNX1</th>\n",
       "      <th>REH_RUNX1_rep1</th>\n",
       "      <th>REH_RUNX1_rep2</th>\n",
       "      <th>Nalm6_RUNX1</th>\n",
       "      <th>ETV6_HA_IP</th>\n",
       "      <th>Reh_ETV6-WT</th>\n",
       "      <th>Reh_ERG</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Reh_HPA</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.537182</td>\n",
       "      <td>0.289848</td>\n",
       "      <td>0.399831</td>\n",
       "      <td>0.163943</td>\n",
       "      <td>0.155886</td>\n",
       "      <td>0.097909</td>\n",
       "      <td>0.063966</td>\n",
       "      <td>0.169953</td>\n",
       "      <td>0.350718</td>\n",
       "      <td>0.176133</td>\n",
       "      <td>0.065085</td>\n",
       "      <td>0.070837</td>\n",
       "      <td>0.046181</td>\n",
       "      <td>0.054372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reh_PAS</th>\n",
       "      <td>0.537182</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.347959</td>\n",
       "      <td>0.472948</td>\n",
       "      <td>0.189745</td>\n",
       "      <td>0.179747</td>\n",
       "      <td>0.107914</td>\n",
       "      <td>0.062895</td>\n",
       "      <td>0.188008</td>\n",
       "      <td>0.410891</td>\n",
       "      <td>0.206659</td>\n",
       "      <td>0.064921</td>\n",
       "      <td>0.076238</td>\n",
       "      <td>0.049274</td>\n",
       "      <td>0.056338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reh_DMSO_HPA</th>\n",
       "      <td>0.289848</td>\n",
       "      <td>0.347959</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.346667</td>\n",
       "      <td>0.389818</td>\n",
       "      <td>0.311564</td>\n",
       "      <td>0.241342</td>\n",
       "      <td>0.127291</td>\n",
       "      <td>0.133007</td>\n",
       "      <td>0.320702</td>\n",
       "      <td>0.382990</td>\n",
       "      <td>0.134400</td>\n",
       "      <td>0.042930</td>\n",
       "      <td>0.054405</td>\n",
       "      <td>0.057579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REH_ETV6-RUNX1_rep1</th>\n",
       "      <td>0.399831</td>\n",
       "      <td>0.472948</td>\n",
       "      <td>0.346667</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.219405</td>\n",
       "      <td>0.193584</td>\n",
       "      <td>0.115548</td>\n",
       "      <td>0.063388</td>\n",
       "      <td>0.158965</td>\n",
       "      <td>0.571804</td>\n",
       "      <td>0.244471</td>\n",
       "      <td>0.070552</td>\n",
       "      <td>0.072278</td>\n",
       "      <td>0.048211</td>\n",
       "      <td>0.047555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REH_ETV6-RUNX1_rep2</th>\n",
       "      <td>0.163943</td>\n",
       "      <td>0.189745</td>\n",
       "      <td>0.389818</td>\n",
       "      <td>0.219405</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.324116</td>\n",
       "      <td>0.265817</td>\n",
       "      <td>0.124677</td>\n",
       "      <td>0.073836</td>\n",
       "      <td>0.247262</td>\n",
       "      <td>0.611828</td>\n",
       "      <td>0.186742</td>\n",
       "      <td>0.029319</td>\n",
       "      <td>0.053187</td>\n",
       "      <td>0.054211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reh_ETV6_Atlas</th>\n",
       "      <td>0.155886</td>\n",
       "      <td>0.179747</td>\n",
       "      <td>0.311564</td>\n",
       "      <td>0.193584</td>\n",
       "      <td>0.324116</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.192051</td>\n",
       "      <td>0.094774</td>\n",
       "      <td>0.064081</td>\n",
       "      <td>0.196744</td>\n",
       "      <td>0.300135</td>\n",
       "      <td>0.136731</td>\n",
       "      <td>0.035548</td>\n",
       "      <td>0.069097</td>\n",
       "      <td>0.072822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nalm6_ETV6-RUNX1_V5_B</th>\n",
       "      <td>0.097909</td>\n",
       "      <td>0.107914</td>\n",
       "      <td>0.241342</td>\n",
       "      <td>0.115548</td>\n",
       "      <td>0.265817</td>\n",
       "      <td>0.192051</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.174133</td>\n",
       "      <td>0.057885</td>\n",
       "      <td>0.115008</td>\n",
       "      <td>0.233988</td>\n",
       "      <td>0.312637</td>\n",
       "      <td>0.016718</td>\n",
       "      <td>0.030220</td>\n",
       "      <td>0.045013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reh_RUNX1_B</th>\n",
       "      <td>0.063966</td>\n",
       "      <td>0.062895</td>\n",
       "      <td>0.127291</td>\n",
       "      <td>0.063388</td>\n",
       "      <td>0.124677</td>\n",
       "      <td>0.094774</td>\n",
       "      <td>0.174133</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.054530</td>\n",
       "      <td>0.065051</td>\n",
       "      <td>0.121697</td>\n",
       "      <td>0.185182</td>\n",
       "      <td>0.008780</td>\n",
       "      <td>0.016099</td>\n",
       "      <td>0.028312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reh_DMSO_RUNX1</th>\n",
       "      <td>0.169953</td>\n",
       "      <td>0.188008</td>\n",
       "      <td>0.133007</td>\n",
       "      <td>0.158965</td>\n",
       "      <td>0.073836</td>\n",
       "      <td>0.064081</td>\n",
       "      <td>0.057885</td>\n",
       "      <td>0.054530</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.158996</td>\n",
       "      <td>0.084140</td>\n",
       "      <td>0.043101</td>\n",
       "      <td>0.049587</td>\n",
       "      <td>0.017223</td>\n",
       "      <td>0.034390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REH_RUNX1_rep1</th>\n",
       "      <td>0.350718</td>\n",
       "      <td>0.410891</td>\n",
       "      <td>0.320702</td>\n",
       "      <td>0.571804</td>\n",
       "      <td>0.247262</td>\n",
       "      <td>0.196744</td>\n",
       "      <td>0.115008</td>\n",
       "      <td>0.065051</td>\n",
       "      <td>0.158996</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.281439</td>\n",
       "      <td>0.078374</td>\n",
       "      <td>0.065413</td>\n",
       "      <td>0.048979</td>\n",
       "      <td>0.048024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REH_RUNX1_rep2</th>\n",
       "      <td>0.176133</td>\n",
       "      <td>0.206659</td>\n",
       "      <td>0.382990</td>\n",
       "      <td>0.244471</td>\n",
       "      <td>0.611828</td>\n",
       "      <td>0.300135</td>\n",
       "      <td>0.233988</td>\n",
       "      <td>0.121697</td>\n",
       "      <td>0.084140</td>\n",
       "      <td>0.281439</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.176386</td>\n",
       "      <td>0.029027</td>\n",
       "      <td>0.050152</td>\n",
       "      <td>0.049868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nalm6_RUNX1</th>\n",
       "      <td>0.065085</td>\n",
       "      <td>0.064921</td>\n",
       "      <td>0.134400</td>\n",
       "      <td>0.070552</td>\n",
       "      <td>0.186742</td>\n",
       "      <td>0.136731</td>\n",
       "      <td>0.312637</td>\n",
       "      <td>0.185182</td>\n",
       "      <td>0.043101</td>\n",
       "      <td>0.078374</td>\n",
       "      <td>0.176386</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.009528</td>\n",
       "      <td>0.021418</td>\n",
       "      <td>0.037806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ETV6_HA_IP</th>\n",
       "      <td>0.070837</td>\n",
       "      <td>0.076238</td>\n",
       "      <td>0.042930</td>\n",
       "      <td>0.072278</td>\n",
       "      <td>0.029319</td>\n",
       "      <td>0.035548</td>\n",
       "      <td>0.016718</td>\n",
       "      <td>0.008780</td>\n",
       "      <td>0.049587</td>\n",
       "      <td>0.065413</td>\n",
       "      <td>0.029027</td>\n",
       "      <td>0.009528</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.085297</td>\n",
       "      <td>0.149002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reh_ETV6-WT</th>\n",
       "      <td>0.046181</td>\n",
       "      <td>0.049274</td>\n",
       "      <td>0.054405</td>\n",
       "      <td>0.048211</td>\n",
       "      <td>0.053187</td>\n",
       "      <td>0.069097</td>\n",
       "      <td>0.030220</td>\n",
       "      <td>0.016099</td>\n",
       "      <td>0.017223</td>\n",
       "      <td>0.048979</td>\n",
       "      <td>0.050152</td>\n",
       "      <td>0.021418</td>\n",
       "      <td>0.085297</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.181013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reh_ERG</th>\n",
       "      <td>0.054372</td>\n",
       "      <td>0.056338</td>\n",
       "      <td>0.057579</td>\n",
       "      <td>0.047555</td>\n",
       "      <td>0.054211</td>\n",
       "      <td>0.072822</td>\n",
       "      <td>0.045013</td>\n",
       "      <td>0.028312</td>\n",
       "      <td>0.034390</td>\n",
       "      <td>0.048024</td>\n",
       "      <td>0.049868</td>\n",
       "      <td>0.037806</td>\n",
       "      <td>0.149002</td>\n",
       "      <td>0.181013</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Reh_HPA   Reh_PAS  Reh_DMSO_HPA  REH_ETV6-RUNX1_rep1  \\\n",
       "Reh_HPA                1.000000  0.537182      0.289848             0.399831   \n",
       "Reh_PAS                0.537182  1.000000      0.347959             0.472948   \n",
       "Reh_DMSO_HPA           0.289848  0.347959      1.000000             0.346667   \n",
       "REH_ETV6-RUNX1_rep1    0.399831  0.472948      0.346667             1.000000   \n",
       "REH_ETV6-RUNX1_rep2    0.163943  0.189745      0.389818             0.219405   \n",
       "Reh_ETV6_Atlas         0.155886  0.179747      0.311564             0.193584   \n",
       "Nalm6_ETV6-RUNX1_V5_B  0.097909  0.107914      0.241342             0.115548   \n",
       "Reh_RUNX1_B            0.063966  0.062895      0.127291             0.063388   \n",
       "Reh_DMSO_RUNX1         0.169953  0.188008      0.133007             0.158965   \n",
       "REH_RUNX1_rep1         0.350718  0.410891      0.320702             0.571804   \n",
       "REH_RUNX1_rep2         0.176133  0.206659      0.382990             0.244471   \n",
       "Nalm6_RUNX1            0.065085  0.064921      0.134400             0.070552   \n",
       "ETV6_HA_IP             0.070837  0.076238      0.042930             0.072278   \n",
       "Reh_ETV6-WT            0.046181  0.049274      0.054405             0.048211   \n",
       "Reh_ERG                0.054372  0.056338      0.057579             0.047555   \n",
       "\n",
       "                       REH_ETV6-RUNX1_rep2  Reh_ETV6_Atlas  \\\n",
       "Reh_HPA                           0.163943        0.155886   \n",
       "Reh_PAS                           0.189745        0.179747   \n",
       "Reh_DMSO_HPA                      0.389818        0.311564   \n",
       "REH_ETV6-RUNX1_rep1               0.219405        0.193584   \n",
       "REH_ETV6-RUNX1_rep2               1.000000        0.324116   \n",
       "Reh_ETV6_Atlas                    0.324116        1.000000   \n",
       "Nalm6_ETV6-RUNX1_V5_B             0.265817        0.192051   \n",
       "Reh_RUNX1_B                       0.124677        0.094774   \n",
       "Reh_DMSO_RUNX1                    0.073836        0.064081   \n",
       "REH_RUNX1_rep1                    0.247262        0.196744   \n",
       "REH_RUNX1_rep2                    0.611828        0.300135   \n",
       "Nalm6_RUNX1                       0.186742        0.136731   \n",
       "ETV6_HA_IP                        0.029319        0.035548   \n",
       "Reh_ETV6-WT                       0.053187        0.069097   \n",
       "Reh_ERG                           0.054211        0.072822   \n",
       "\n",
       "                       Nalm6_ETV6-RUNX1_V5_B  Reh_RUNX1_B  Reh_DMSO_RUNX1  \\\n",
       "Reh_HPA                             0.097909     0.063966        0.169953   \n",
       "Reh_PAS                             0.107914     0.062895        0.188008   \n",
       "Reh_DMSO_HPA                        0.241342     0.127291        0.133007   \n",
       "REH_ETV6-RUNX1_rep1                 0.115548     0.063388        0.158965   \n",
       "REH_ETV6-RUNX1_rep2                 0.265817     0.124677        0.073836   \n",
       "Reh_ETV6_Atlas                      0.192051     0.094774        0.064081   \n",
       "Nalm6_ETV6-RUNX1_V5_B               1.000000     0.174133        0.057885   \n",
       "Reh_RUNX1_B                         0.174133     1.000000        0.054530   \n",
       "Reh_DMSO_RUNX1                      0.057885     0.054530        1.000000   \n",
       "REH_RUNX1_rep1                      0.115008     0.065051        0.158996   \n",
       "REH_RUNX1_rep2                      0.233988     0.121697        0.084140   \n",
       "Nalm6_RUNX1                         0.312637     0.185182        0.043101   \n",
       "ETV6_HA_IP                          0.016718     0.008780        0.049587   \n",
       "Reh_ETV6-WT                         0.030220     0.016099        0.017223   \n",
       "Reh_ERG                             0.045013     0.028312        0.034390   \n",
       "\n",
       "                       REH_RUNX1_rep1  REH_RUNX1_rep2  Nalm6_RUNX1  \\\n",
       "Reh_HPA                      0.350718        0.176133     0.065085   \n",
       "Reh_PAS                      0.410891        0.206659     0.064921   \n",
       "Reh_DMSO_HPA                 0.320702        0.382990     0.134400   \n",
       "REH_ETV6-RUNX1_rep1          0.571804        0.244471     0.070552   \n",
       "REH_ETV6-RUNX1_rep2          0.247262        0.611828     0.186742   \n",
       "Reh_ETV6_Atlas               0.196744        0.300135     0.136731   \n",
       "Nalm6_ETV6-RUNX1_V5_B        0.115008        0.233988     0.312637   \n",
       "Reh_RUNX1_B                  0.065051        0.121697     0.185182   \n",
       "Reh_DMSO_RUNX1               0.158996        0.084140     0.043101   \n",
       "REH_RUNX1_rep1               1.000000        0.281439     0.078374   \n",
       "REH_RUNX1_rep2               0.281439        1.000000     0.176386   \n",
       "Nalm6_RUNX1                  0.078374        0.176386     1.000000   \n",
       "ETV6_HA_IP                   0.065413        0.029027     0.009528   \n",
       "Reh_ETV6-WT                  0.048979        0.050152     0.021418   \n",
       "Reh_ERG                      0.048024        0.049868     0.037806   \n",
       "\n",
       "                       ETV6_HA_IP  Reh_ETV6-WT   Reh_ERG  \n",
       "Reh_HPA                  0.070837     0.046181  0.054372  \n",
       "Reh_PAS                  0.076238     0.049274  0.056338  \n",
       "Reh_DMSO_HPA             0.042930     0.054405  0.057579  \n",
       "REH_ETV6-RUNX1_rep1      0.072278     0.048211  0.047555  \n",
       "REH_ETV6-RUNX1_rep2      0.029319     0.053187  0.054211  \n",
       "Reh_ETV6_Atlas           0.035548     0.069097  0.072822  \n",
       "Nalm6_ETV6-RUNX1_V5_B    0.016718     0.030220  0.045013  \n",
       "Reh_RUNX1_B              0.008780     0.016099  0.028312  \n",
       "Reh_DMSO_RUNX1           0.049587     0.017223  0.034390  \n",
       "REH_RUNX1_rep1           0.065413     0.048979  0.048024  \n",
       "REH_RUNX1_rep2           0.029027     0.050152  0.049868  \n",
       "Nalm6_RUNX1              0.009528     0.021418  0.037806  \n",
       "ETV6_HA_IP               1.000000     0.085297  0.149002  \n",
       "Reh_ETV6-WT              0.085297     1.000000  0.181013  \n",
       "Reh_ERG                  0.149002     0.181013  1.000000  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "peak_overlap_df = pd.DataFrame(peak_overlap_matrix, index=datasets, columns=datasets)\n",
    "peak_overlap_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "23e584a3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:19:17.461430Z",
     "start_time": "2026-01-08T03:19:17.455014Z"
    }
   },
   "outputs": [],
   "source": [
    "sns.set(font_scale=1.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "cd96f591",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:21:32.337323Z",
     "start_time": "2026-01-08T03:21:31.864335Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.05, 'Peak set overlap (intersection over union) between ETV6-RUNX1 ChIP datasets')"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 792x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(11, 9))\n",
    "sns.heatmap(peak_overlap_df, cmap='Blues', annot=True, fmt=\".1f\")\n",
    "plt.title('Peak set overlap (intersection over union) between ETV6-RUNX1 ChIP datasets', \n",
    "          fontsize=15, y=1.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "1b70ff51",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:21:38.356009Z",
     "start_time": "2026-01-08T03:21:37.877412Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.05, 'Peak set overlap (intersection over union) between ETV6-RUNX1 ChIP datasets')"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 792x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(11, 9))\n",
    "sns.heatmap(peak_overlap_df, cmap='Blues', vmax=0.5,\n",
    "            annot=True, fmt=\".1f\")\n",
    "plt.title('Peak set overlap (intersection over union) between ETV6-RUNX1 ChIP datasets', \n",
    "          fontsize=15, y=1.05)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b020d1b",
   "metadata": {},
   "source": [
    "#### Differential analysis: Nalm6_RUNX1 vs Nalm6_ETV6-RUNX1_V5_B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "06ff0053",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:21:53.257453Z",
     "start_time": "2026-01-08T03:21:53.148449Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8242"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nalm_runx1_peaks = pybedtools.BedTool(\n",
    "    base_path + 'Wray_et_al/Nalm6_RUNX1/idr_peaks/idr_thresholded_peaks'\n",
    ")\n",
    "nalm_runx1_peaks.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "b8a6cd71",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:22:05.147579Z",
     "start_time": "2026-01-08T03:22:05.053821Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4951"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nalm_etv6_runx1_peaks = pybedtools.BedTool(\n",
    "    base_path + 'Wray_et_al/Nalm6_ETV6-RUNX1_V5_B/idr_peaks/idr_thresholded_peaks'\n",
    ")\n",
    "nalm_etv6_runx1_peaks.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "8fc78ac7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:22:05.687363Z",
     "start_time": "2026-01-08T03:22:05.537842Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3142"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersection = nalm_runx1_peaks.intersect(nalm_etv6_runx1_peaks)\n",
    "intersection.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "08ec88e4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:22:06.543474Z",
     "start_time": "2026-01-08T03:22:06.098010Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10050"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "union = nalm_runx1_peaks.cat(nalm_etv6_runx1_peaks, postmerge=True)\n",
    "union.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "40abb6f0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:23:22.737591Z",
     "start_time": "2026-01-08T03:23:22.412033Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Overlap between ChIP-seq peaks')"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 8))\n",
    "sns.set(font_scale=1)\n",
    "venn2(subsets=(nalm_runx1_peaks.count() - intersection.count(), \n",
    "               nalm_etv6_runx1_peaks.count() - intersection.count(), \n",
    "               intersection.count()), \n",
    "      set_labels = ('Nalm6_RUNX1', 'Nalm6_ETV6-RUNX1_V5_B'))\n",
    "plt.title('Overlap between ChIP-seq peaks', fontsize=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "845c0d9a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:23:32.133903Z",
     "start_time": "2026-01-08T03:23:31.947248Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5131"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nalm_runx1_only_peaks = nalm_runx1_peaks.subtract(nalm_etv6_runx1_peaks, A=True)\n",
    "nalm_runx1_only_peaks.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "ec48c94f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:23:35.636961Z",
     "start_time": "2026-01-08T03:23:35.530304Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3142"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersection.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "67aac0c5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:23:36.213817Z",
     "start_time": "2026-01-08T03:23:36.095292Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1830"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nalm_etv6_runx1_only_peaks = nalm_etv6_runx1_peaks.subtract(nalm_runx1_peaks, A=True)\n",
    "nalm_etv6_runx1_only_peaks.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "9670cd3e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:29:18.392360Z",
     "start_time": "2026-01-08T03:28:33.851723Z"
    }
   },
   "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>Chromosome</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Strand</th>\n",
       "      <th>gene_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>65418</td>\n",
       "      <td>71585</td>\n",
       "      <td>+</td>\n",
       "      <td>OR4F5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>923922</td>\n",
       "      <td>944575</td>\n",
       "      <td>+</td>\n",
       "      <td>SAMD11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>960583</td>\n",
       "      <td>965719</td>\n",
       "      <td>+</td>\n",
       "      <td>KLHL17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>966481</td>\n",
       "      <td>975865</td>\n",
       "      <td>+</td>\n",
       "      <td>PLEKHN1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1001137</td>\n",
       "      <td>1014540</td>\n",
       "      <td>+</td>\n",
       "      <td>ISG15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20091</th>\n",
       "      <td>chrY</td>\n",
       "      <td>22168541</td>\n",
       "      <td>22182982</td>\n",
       "      <td>-</td>\n",
       "      <td>RBMY1F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20092</th>\n",
       "      <td>chrY</td>\n",
       "      <td>23129354</td>\n",
       "      <td>23199010</td>\n",
       "      <td>-</td>\n",
       "      <td>DAZ1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20093</th>\n",
       "      <td>chrY</td>\n",
       "      <td>24045228</td>\n",
       "      <td>24048019</td>\n",
       "      <td>-</td>\n",
       "      <td>CDY1B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20094</th>\n",
       "      <td>chrY</td>\n",
       "      <td>24763068</td>\n",
       "      <td>24813492</td>\n",
       "      <td>-</td>\n",
       "      <td>DAZ3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20095</th>\n",
       "      <td>chrY</td>\n",
       "      <td>25030900</td>\n",
       "      <td>25062548</td>\n",
       "      <td>-</td>\n",
       "      <td>BPY2C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20096 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "+--------------+-----------+-----------+--------------+-------------+\n",
       "| Chromosome   | Start     | End       | Strand       | gene_name   |\n",
       "| (category)   | (int64)   | (int64)   | (category)   | (object)    |\n",
       "|--------------+-----------+-----------+--------------+-------------|\n",
       "| chr1         | 65418     | 71585     | +            | OR4F5       |\n",
       "| chr1         | 923922    | 944575    | +            | SAMD11      |\n",
       "| chr1         | 960583    | 965719    | +            | KLHL17      |\n",
       "| chr1         | 966481    | 975865    | +            | PLEKHN1     |\n",
       "| ...          | ...       | ...       | ...          | ...         |\n",
       "| chrY         | 23129354  | 23199010  | -            | DAZ1        |\n",
       "| chrY         | 24045228  | 24048019  | -            | CDY1B       |\n",
       "| chrY         | 24763068  | 24813492  | -            | DAZ3        |\n",
       "| chrY         | 25030900  | 25062548  | -            | BPY2C       |\n",
       "+--------------+-----------+-----------+--------------+-------------+\n",
       "Stranded PyRanges object has 20,096 rows and 5 columns from 25 chromosomes.\n",
       "For printing, the PyRanges was sorted on Chromosome and Strand."
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_genes = pr.read_gtf('/users/shouvikm/data/Cell_Lines_Ped_Leukemia/gencode.v48.annotation.gtf.gz')\n",
    "all_genes = all_genes[(all_genes.Feature == 'gene') & (all_genes.gene_type == 'protein_coding')]\n",
    "all_genes = all_genes[[\"Chromosome\", \"Start\", \"End\", \"gene_name\"]]\n",
    "all_genes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "5cf82502",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:33:32.698786Z",
     "start_time": "2026-01-08T03:33:32.593388Z"
    }
   },
   "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>Chromosome</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>9426269</td>\n",
       "      <td>9426964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>228141302</td>\n",
       "      <td>228142346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>30748384</td>\n",
       "      <td>30749025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>226407640</td>\n",
       "      <td>226408276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>31431733</td>\n",
       "      <td>31432258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1825</th>\n",
       "      <td>chrX</td>\n",
       "      <td>1466940</td>\n",
       "      <td>1467200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1826</th>\n",
       "      <td>chrX</td>\n",
       "      <td>1249681</td>\n",
       "      <td>1249939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1827</th>\n",
       "      <td>chrX</td>\n",
       "      <td>153985406</td>\n",
       "      <td>153985769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1828</th>\n",
       "      <td>chrX</td>\n",
       "      <td>155026773</td>\n",
       "      <td>155027143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1829</th>\n",
       "      <td>chrX</td>\n",
       "      <td>154342460</td>\n",
       "      <td>154342978</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1830 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "+--------------+-----------+-----------+\n",
       "| Chromosome   | Start     | End       |\n",
       "| (category)   | (int64)   | (int64)   |\n",
       "|--------------+-----------+-----------|\n",
       "| chr1         | 9426269   | 9426964   |\n",
       "| chr1         | 228141302 | 228142346 |\n",
       "| chr1         | 30748384  | 30749025  |\n",
       "| chr1         | 226407640 | 226408276 |\n",
       "| ...          | ...       | ...       |\n",
       "| chrX         | 1249681   | 1249939   |\n",
       "| chrX         | 153985406 | 153985769 |\n",
       "| chrX         | 155026773 | 155027143 |\n",
       "| chrX         | 154342460 | 154342978 |\n",
       "+--------------+-----------+-----------+\n",
       "Unstranded PyRanges object has 1,830 rows and 3 columns from 26 chromosomes.\n",
       "For printing, the PyRanges was sorted on Chromosome."
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nalm_etv6_runx1_only_peaks_df = nalm_etv6_runx1_only_peaks.to_dataframe(names=range(20))\n",
    "nalm_etv6_runx1_only_peaks_df = nalm_etv6_runx1_only_peaks_df[[0, 1, 2]]\n",
    "nalm_etv6_runx1_only_peaks_df.columns = ['Chromosome', 'Start', 'End']\n",
    "nalm_etv6_runx1_only_peaks = pr.PyRanges(nalm_etv6_runx1_only_peaks_df)\n",
    "nalm_etv6_runx1_only_peaks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "2451773a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T03:44:05.178328Z",
     "start_time": "2026-01-08T03:44:04.464415Z"
    }
   },
   "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>Chromosome</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Strand</th>\n",
       "      <th>gene_name</th>\n",
       "      <th>Distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>228141302</td>\n",
       "      <td>228142346</td>\n",
       "      <td>+</td>\n",
       "      <td>GUK1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>31431733</td>\n",
       "      <td>31432258</td>\n",
       "      <td>+</td>\n",
       "      <td>SERINC2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>9715864</td>\n",
       "      <td>9716297</td>\n",
       "      <td>+</td>\n",
       "      <td>PIK3CD</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>202247863</td>\n",
       "      <td>202248627</td>\n",
       "      <td>+</td>\n",
       "      <td>LGR6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>2227317</td>\n",
       "      <td>2227961</td>\n",
       "      <td>+</td>\n",
       "      <td>SKI</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1822</th>\n",
       "      <td>chrX</td>\n",
       "      <td>40013433</td>\n",
       "      <td>40013827</td>\n",
       "      <td>-</td>\n",
       "      <td>BCOR</td>\n",
       "      <td>35988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1823</th>\n",
       "      <td>chrX</td>\n",
       "      <td>47513148</td>\n",
       "      <td>47513490</td>\n",
       "      <td>-</td>\n",
       "      <td>ZNF41</td>\n",
       "      <td>29927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1824</th>\n",
       "      <td>chrX</td>\n",
       "      <td>69293830</td>\n",
       "      <td>69294563</td>\n",
       "      <td>-</td>\n",
       "      <td>PJA1</td>\n",
       "      <td>128310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1825</th>\n",
       "      <td>chrX</td>\n",
       "      <td>120498033</td>\n",
       "      <td>120498322</td>\n",
       "      <td>-</td>\n",
       "      <td>CUL4B</td>\n",
       "      <td>7598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1826</th>\n",
       "      <td>chrX</td>\n",
       "      <td>154342460</td>\n",
       "      <td>154342978</td>\n",
       "      <td>-</td>\n",
       "      <td>FLNA</td>\n",
       "      <td>5546</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1827 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "+--------------+-----------+-----------+--------------+-------------+-------+\n",
       "| Chromosome   | Start     | End       | Strand       | gene_name   | +1    |\n",
       "| (category)   | (int64)   | (int64)   | (category)   | (object)    | ...   |\n",
       "|--------------+-----------+-----------+--------------+-------------+-------|\n",
       "| chr1         | 228141302 | 228142346 | +            | GUK1        | ...   |\n",
       "| chr1         | 31431733  | 31432258  | +            | SERINC2     | ...   |\n",
       "| chr1         | 9715864   | 9716297   | +            | PIK3CD      | ...   |\n",
       "| chr1         | 202247863 | 202248627 | +            | LGR6        | ...   |\n",
       "| ...          | ...       | ...       | ...          | ...         | ...   |\n",
       "| chrX         | 47513148  | 47513490  | -            | ZNF41       | ...   |\n",
       "| chrX         | 69293830  | 69294563  | -            | PJA1        | ...   |\n",
       "| chrX         | 120498033 | 120498322 | -            | CUL4B       | ...   |\n",
       "| chrX         | 154342460 | 154342978 | -            | FLNA        | ...   |\n",
       "+--------------+-----------+-----------+--------------+-------------+-------+\n",
       "Stranded PyRanges object has 1,827 rows and 6 columns from 23 chromosomes.\n",
       "For printing, the PyRanges was sorted on Chromosome and Strand.\n",
       "1 hidden columns: Distance"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nalm_etv6_runx1_only_peaks = nalm_etv6_runx1_only_peaks.nearest(all_genes)\n",
    "nalm_etv6_runx1_only_peaks = nalm_etv6_runx1_only_peaks[['Chromosome', 'Start', 'End', 'gene_name', 'Distance']]\n",
    "nalm_etv6_runx1_only_peaks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "dcabc438",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T04:15:33.437192Z",
     "start_time": "2026-01-08T04:15:32.953228Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ARCHS4_Cell-lines',\n",
       " 'ARCHS4_IDG_Coexp',\n",
       " 'ARCHS4_Kinases_Coexp',\n",
       " 'ARCHS4_TFs_Coexp',\n",
       " 'ARCHS4_Tissues',\n",
       " 'Achilles_fitness_decrease',\n",
       " 'Achilles_fitness_increase',\n",
       " 'Aging_Perturbations_from_GEO_down',\n",
       " 'Aging_Perturbations_from_GEO_up',\n",
       " 'Allen_Brain_Atlas_10x_scRNA_2021',\n",
       " 'Allen_Brain_Atlas_down',\n",
       " 'Allen_Brain_Atlas_up',\n",
       " 'Azimuth_2023',\n",
       " 'Azimuth_Cell_Types_2021',\n",
       " 'BioCarta_2013',\n",
       " 'BioCarta_2015',\n",
       " 'BioCarta_2016',\n",
       " 'BioPlanet_2019',\n",
       " 'BioPlex_2017',\n",
       " 'CCLE_Proteomics_2020',\n",
       " 'CM4AI_U2OS_Protein_Localization_Assemblies',\n",
       " 'COMPARTMENTS_Curated_2025',\n",
       " 'COMPARTMENTS_Experimental_2025',\n",
       " 'CORUM',\n",
       " 'COVID-19_Related_Gene_Sets',\n",
       " 'COVID-19_Related_Gene_Sets_2021',\n",
       " 'Cancer_Cell_Line_Encyclopedia',\n",
       " 'CellMarker_2024',\n",
       " 'CellMarker_Augmented_2021',\n",
       " 'ChEA_2013',\n",
       " 'ChEA_2015',\n",
       " 'ChEA_2016',\n",
       " 'ChEA_2022',\n",
       " 'Chromosome_Location',\n",
       " 'Chromosome_Location_hg19',\n",
       " 'ClinVar_2019',\n",
       " 'ClinVar_2025',\n",
       " 'DGIdb_Drug_Targets_2024',\n",
       " 'DSigDB',\n",
       " 'Data_Acquisition_Method_Most_Popular_Genes',\n",
       " 'DepMap_CRISPR_GeneDependency_CellLines_2023',\n",
       " 'DepMap_WG_CRISPR_Screens_Broad_CellLines_2019',\n",
       " 'DepMap_WG_CRISPR_Screens_Sanger_CellLines_2019',\n",
       " 'Descartes_Cell_Types_and_Tissue_2021',\n",
       " 'Diabetes_Perturbations_GEO_2022',\n",
       " 'DisGeNET',\n",
       " 'Disease_Perturbations_from_GEO_down',\n",
       " 'Disease_Perturbations_from_GEO_up',\n",
       " 'Disease_Signatures_from_GEO_down_2014',\n",
       " 'Disease_Signatures_from_GEO_up_2014',\n",
       " 'DrugMatrix',\n",
       " 'Drug_Perturbations_from_GEO_2014',\n",
       " 'Drug_Perturbations_from_GEO_down',\n",
       " 'Drug_Perturbations_from_GEO_up',\n",
       " 'ENCODE_Histone_Modifications_2013',\n",
       " 'ENCODE_Histone_Modifications_2015',\n",
       " 'ENCODE_TF_ChIP-seq_2014',\n",
       " 'ENCODE_TF_ChIP-seq_2015',\n",
       " 'ENCODE_and_ChEA_Consensus_TFs_from_ChIP-X',\n",
       " 'ESCAPE',\n",
       " 'Elsevier_Pathway_Collection',\n",
       " 'Enrichr_Libraries_Most_Popular_Genes',\n",
       " 'Enrichr_Submissions_TF-Gene_Coocurrence',\n",
       " 'Enrichr_Users_Contributed_Lists_2020',\n",
       " 'Epigenomics_Roadmap_HM_ChIP-seq',\n",
       " 'FANTOM6_lncRNA_KD_DEGs',\n",
       " 'GO_Biological_Process_2021',\n",
       " 'GO_Biological_Process_2023',\n",
       " 'GO_Biological_Process_2025',\n",
       " 'GO_Cellular_Component_2021',\n",
       " 'GO_Cellular_Component_2023',\n",
       " 'GO_Cellular_Component_2025',\n",
       " 'GO_Molecular_Function_2021',\n",
       " 'GO_Molecular_Function_2023',\n",
       " 'GO_Molecular_Function_2025',\n",
       " 'GTEx_Aging_Signatures_2021',\n",
       " 'GTEx_Tissue_Expression_Down',\n",
       " 'GTEx_Tissue_Expression_Up',\n",
       " 'GTEx_Tissues_V8_2023',\n",
       " 'GWAS_Catalog_2019',\n",
       " 'GWAS_Catalog_2023',\n",
       " 'GWAS_Catalog_2025',\n",
       " 'GeDiPNet_2023',\n",
       " 'GeneSigDB',\n",
       " 'Gene_Perturbations_from_GEO_down',\n",
       " 'Gene_Perturbations_from_GEO_up',\n",
       " 'Genes_Associated_with_NIH_Grants',\n",
       " 'Genome_Browser_PWMs',\n",
       " 'GlyGen_Glycosylated_Proteins_2022',\n",
       " 'HDSigDB_Human_2021',\n",
       " 'HDSigDB_Mouse_2021',\n",
       " 'HMDB_Metabolites',\n",
       " 'HMS_LINCS_KinomeScan',\n",
       " 'HomoloGene',\n",
       " 'HuBMAP_ASCT_plus_B_augmented_w_RNAseq_Coexpression',\n",
       " 'HuBMAP_ASCTplusB_augmented_2022',\n",
       " 'HumanCyc_2015',\n",
       " 'HumanCyc_2016',\n",
       " 'Human_Gene_Atlas',\n",
       " 'Human_Phenotype_Ontology',\n",
       " 'IDG_Drug_Targets_2022',\n",
       " 'InterPro_Domains_2019',\n",
       " 'JASPAR_PWM_Human_2025',\n",
       " 'JASPAR_PWM_Mouse_2025',\n",
       " 'Jensen_COMPARTMENTS',\n",
       " 'Jensen_DISEASES',\n",
       " 'Jensen_DISEASES_Curated_2025',\n",
       " 'Jensen_DISEASES_Experimental_2025',\n",
       " 'Jensen_TISSUES',\n",
       " 'KEA_2013',\n",
       " 'KEA_2015',\n",
       " 'KEGG_2013',\n",
       " 'KEGG_2015',\n",
       " 'KEGG_2016',\n",
       " 'KEGG_2019_Human',\n",
       " 'KEGG_2019_Mouse',\n",
       " 'KEGG_2021_Human',\n",
       " 'KOMP2_Mouse_Phenotypes_2022',\n",
       " 'Kinase_Perturbations_from_GEO_down',\n",
       " 'Kinase_Perturbations_from_GEO_up',\n",
       " 'L1000_Kinase_and_GPCR_Perturbations_down',\n",
       " 'L1000_Kinase_and_GPCR_Perturbations_up',\n",
       " 'LINCS_L1000_CRISPR_KO_Consensus_Sigs',\n",
       " 'LINCS_L1000_Chem_Pert_Consensus_Sigs',\n",
       " 'LINCS_L1000_Chem_Pert_down',\n",
       " 'LINCS_L1000_Chem_Pert_up',\n",
       " 'LINCS_L1000_Ligand_Perturbations_down',\n",
       " 'LINCS_L1000_Ligand_Perturbations_up',\n",
       " 'Ligand_Perturbations_from_GEO_down',\n",
       " 'Ligand_Perturbations_from_GEO_up',\n",
       " 'MAGMA_Drugs_and_Diseases',\n",
       " 'MAGNET_2023',\n",
       " 'MCF7_Perturbations_from_GEO_down',\n",
       " 'MCF7_Perturbations_from_GEO_up',\n",
       " 'MGI_Mammalian_Phenotype_Level_4_2021',\n",
       " 'MGI_Mammalian_Phenotype_Level_4_2024',\n",
       " 'MSigDB_Computational',\n",
       " 'MSigDB_Hallmark_2020',\n",
       " 'MSigDB_Oncogenic_Signatures',\n",
       " 'Metabolomics_Workbench_Metabolites_2022',\n",
       " 'Microbe_Perturbations_from_GEO_down',\n",
       " 'Microbe_Perturbations_from_GEO_up',\n",
       " 'MoTrPAC_2023',\n",
       " 'Mouse_Gene_Atlas',\n",
       " 'NCI-60_Cancer_Cell_Lines',\n",
       " 'NCI-Nature_2016',\n",
       " 'NIBR_DRUGseq_2025_down',\n",
       " 'NIBR_DRUGseq_2025_up',\n",
       " 'NURSA_Human_Endogenous_Complexome',\n",
       " 'OMIM_Disease',\n",
       " 'OMIM_Expanded',\n",
       " 'Old_CMAP_down',\n",
       " 'Old_CMAP_up',\n",
       " 'Orphanet_Augmented_2021',\n",
       " 'PFOCR_Pathways_2023',\n",
       " 'PPI_Hub_Proteins',\n",
       " 'PanglaoDB_Augmented_2021',\n",
       " 'Panther_2015',\n",
       " 'Panther_2016',\n",
       " 'PerturbAtlas',\n",
       " 'PerturbAtlas_MouseGenePerturbationSigs',\n",
       " 'PerturbSeq_ReplogleK562',\n",
       " 'PerturbSeq_ReplogleRPE1',\n",
       " 'Pfam_Domains_2019',\n",
       " 'Pfam_InterPro_Domains',\n",
       " 'PheWeb_2019',\n",
       " 'PhenGenI_Association_2021',\n",
       " 'Phosphatase_Substrates_from_DEPOD',\n",
       " 'ProteomicsDB_2020',\n",
       " 'Proteomics_Drug_Atlas_2023',\n",
       " 'RNA-Seq_Disease_Gene_and_Drug_Signatures_from_GEO',\n",
       " 'Rare_Diseases_AutoRIF_ARCHS4_Predictions',\n",
       " 'Rare_Diseases_AutoRIF_Gene_Lists',\n",
       " 'Rare_Diseases_GeneRIF_ARCHS4_Predictions',\n",
       " 'Rare_Diseases_GeneRIF_Gene_Lists',\n",
       " 'Reactome_2022',\n",
       " 'Reactome_Pathways_2024',\n",
       " 'RummaGEO_DrugPerturbations_2025',\n",
       " 'RummaGEO_GenePerturbations_2025',\n",
       " 'Rummagene_kinases',\n",
       " 'Rummagene_signatures',\n",
       " 'Rummagene_transcription_factors',\n",
       " 'SILAC_Phosphoproteomics',\n",
       " 'Sciplex_Drug_Perturbation_Signatures_2025',\n",
       " 'SubCell_BarCode',\n",
       " 'SynGO_2022',\n",
       " 'SynGO_2024',\n",
       " 'SysMyo_Muscle_Gene_Sets',\n",
       " 'TF-LOF_Expression_from_GEO',\n",
       " 'TF_Perturbations_Followed_by_Expression',\n",
       " 'TG_GATES_2020',\n",
       " 'TISSUES_Curated_2025',\n",
       " 'TISSUES_Experimental_2025',\n",
       " 'TRANSFAC_and_JASPAR_PWMs',\n",
       " 'TRRUST_Transcription_Factors_2019',\n",
       " 'Table_Mining_of_CRISPR_Studies',\n",
       " 'Tabula_Muris',\n",
       " 'Tabula_Sapiens',\n",
       " 'TargetScan_microRNA',\n",
       " 'TargetScan_microRNA_2017',\n",
       " 'The_Kinase_Library_2023',\n",
       " 'The_Kinase_Library_2024',\n",
       " 'Tissue_Protein_Expression_from_Human_Proteome_Map',\n",
       " 'Tissue_Protein_Expression_from_ProteomicsDB',\n",
       " 'Transcription_Factor_PPIs',\n",
       " 'UK_Biobank_GWAS_v1',\n",
       " 'Virus-Host_PPI_P-HIPSTer_2020',\n",
       " 'VirusMINT',\n",
       " 'Virus_Perturbations_from_GEO_down',\n",
       " 'Virus_Perturbations_from_GEO_up',\n",
       " 'WikiPathway_2021_Human',\n",
       " 'WikiPathway_2023_Human',\n",
       " 'WikiPathways_2013',\n",
       " 'WikiPathways_2015',\n",
       " 'WikiPathways_2016',\n",
       " 'WikiPathways_2019_Human',\n",
       " 'WikiPathways_2019_Mouse',\n",
       " 'WikiPathways_2024_Human',\n",
       " 'WikiPathways_2024_Mouse',\n",
       " 'dbGaP',\n",
       " 'huMAP',\n",
       " 'lncHUB_lncRNA_Co-Expression',\n",
       " 'miRTarBase_2017']"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gp.get_library_name(organism='Human')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "430710d0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T04:29:31.667104Z",
     "start_time": "2026-01-08T04:29:22.672606Z"
    }
   },
   "outputs": [],
   "source": [
    "enr = gp.enrichr(gene_list=nalm_etv6_runx1_only_peaks.gene_name,\n",
    "#                  background=all_genes.gene_name,\n",
    "                 gene_sets=['MSigDB_Hallmark_2020', 'MSigDB_Oncogenic_Signatures', 'KEGG_2021_Human'],\n",
    "                 organism='human')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "d9854fd9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T04:31:21.764711Z",
     "start_time": "2026-01-08T04:31:21.739852Z"
    },
    "scrolled": false
   },
   "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>Gene_set</th>\n",
       "      <th>Term</th>\n",
       "      <th>Overlap</th>\n",
       "      <th>P-value</th>\n",
       "      <th>Adjusted P-value</th>\n",
       "      <th>Old P-value</th>\n",
       "      <th>Old Adjusted P-value</th>\n",
       "      <th>Odds Ratio</th>\n",
       "      <th>Combined Score</th>\n",
       "      <th>Genes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>TGF-beta Signaling</td>\n",
       "      <td>15/54</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000179</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.048486</td>\n",
       "      <td>63.313462</td>\n",
       "      <td>BCAR3;KLF10;TGFB1;SMAD3;NOG;LTBP2;SMAD7;PPP1CA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>IL-2/STAT5 Signaling</td>\n",
       "      <td>32/199</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>0.000311</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.528242</td>\n",
       "      <td>28.553858</td>\n",
       "      <td>ITIH5;PHTF2;AHNAK;CD81;CTSZ;SLC2A3;AHR;IKZF2;H...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>UV Response Dn</td>\n",
       "      <td>25/144</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.000441</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.765257</td>\n",
       "      <td>28.876162</td>\n",
       "      <td>INSIG1;CACNA1A;PIK3CD;PRDM2;LTBP1;KALRN;RXRA;M...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>Estrogen Response Early</td>\n",
       "      <td>31/200</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>0.000441</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.418253</td>\n",
       "      <td>24.791574</td>\n",
       "      <td>SCARB1;B4GALT1;RHOBTB3;SLC2A1;ASB13;SLC1A4;NAD...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>TNF-alpha Signaling via NF-kB</td>\n",
       "      <td>30/200</td>\n",
       "      <td>0.000087</td>\n",
       "      <td>0.000869</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.324687</td>\n",
       "      <td>21.738491</td>\n",
       "      <td>CDKN1A;CEBPB;B4GALT1;SLC2A3;SOCS3;ZFP36;PHLDA1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>p53 Pathway</td>\n",
       "      <td>26/200</td>\n",
       "      <td>0.002177</td>\n",
       "      <td>0.018144</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.962367</td>\n",
       "      <td>12.028692</td>\n",
       "      <td>CYFIP2;CDKN1A;NOTCH1;CD82;CD81;PDGFA;TGFA;ACVR...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>KRAS Signaling Up</td>\n",
       "      <td>24/200</td>\n",
       "      <td>0.008569</td>\n",
       "      <td>0.061209</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.788084</td>\n",
       "      <td>8.510505</td>\n",
       "      <td>RABGAP1L;FCER1G;MAP3K1;ITGB2;IGF2;LIF;LAPTM5;E...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>Myogenesis</td>\n",
       "      <td>23/200</td>\n",
       "      <td>0.015959</td>\n",
       "      <td>0.088661</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.702593</td>\n",
       "      <td>7.044873</td>\n",
       "      <td>TEAD4;MYOM1;CDKN1A;NOTCH1;TGFB1;GADD45B;DAPK2;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>Apical Junction</td>\n",
       "      <td>23/200</td>\n",
       "      <td>0.015959</td>\n",
       "      <td>0.088661</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.702593</td>\n",
       "      <td>7.044873</td>\n",
       "      <td>VASP;CAP1;B4GALT1;SYK;INSIG1;LAMA3;TNFRSF11B;A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>Reactive Oxygen Species Pathway</td>\n",
       "      <td>8/49</td>\n",
       "      <td>0.021639</td>\n",
       "      <td>0.094870</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.548273</td>\n",
       "      <td>9.768208</td>\n",
       "      <td>ABCC1;SBNO2;TXNRD2;PRDX1;MBP;MPO;PFKP;SOD1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Gene_set                             Term Overlap   P-value  \\\n",
       "0  MSigDB_Hallmark_2020               TGF-beta Signaling   15/54  0.000004   \n",
       "1  MSigDB_Hallmark_2020             IL-2/STAT5 Signaling  32/199  0.000012   \n",
       "2  MSigDB_Hallmark_2020                   UV Response Dn  25/144  0.000029   \n",
       "3  MSigDB_Hallmark_2020          Estrogen Response Early  31/200  0.000035   \n",
       "4  MSigDB_Hallmark_2020    TNF-alpha Signaling via NF-kB  30/200  0.000087   \n",
       "5  MSigDB_Hallmark_2020                      p53 Pathway  26/200  0.002177   \n",
       "6  MSigDB_Hallmark_2020                KRAS Signaling Up  24/200  0.008569   \n",
       "7  MSigDB_Hallmark_2020                       Myogenesis  23/200  0.015959   \n",
       "8  MSigDB_Hallmark_2020                  Apical Junction  23/200  0.015959   \n",
       "9  MSigDB_Hallmark_2020  Reactive Oxygen Species Pathway    8/49  0.021639   \n",
       "\n",
       "   Adjusted P-value  Old P-value  Old Adjusted P-value  Odds Ratio  \\\n",
       "0          0.000179            0                     0    5.048486   \n",
       "1          0.000311            0                     0    2.528242   \n",
       "2          0.000441            0                     0    2.765257   \n",
       "3          0.000441            0                     0    2.418253   \n",
       "4          0.000869            0                     0    2.324687   \n",
       "5          0.018144            0                     0    1.962367   \n",
       "6          0.061209            0                     0    1.788084   \n",
       "7          0.088661            0                     0    1.702593   \n",
       "8          0.088661            0                     0    1.702593   \n",
       "9          0.094870            0                     0    2.548273   \n",
       "\n",
       "   Combined Score                                              Genes  \n",
       "0       63.313462  BCAR3;KLF10;TGFB1;SMAD3;NOG;LTBP2;SMAD7;PPP1CA...  \n",
       "1       28.553858  ITIH5;PHTF2;AHNAK;CD81;CTSZ;SLC2A3;AHR;IKZF2;H...  \n",
       "2       28.876162  INSIG1;CACNA1A;PIK3CD;PRDM2;LTBP1;KALRN;RXRA;M...  \n",
       "3       24.791574  SCARB1;B4GALT1;RHOBTB3;SLC2A1;ASB13;SLC1A4;NAD...  \n",
       "4       21.738491  CDKN1A;CEBPB;B4GALT1;SLC2A3;SOCS3;ZFP36;PHLDA1...  \n",
       "5       12.028692  CYFIP2;CDKN1A;NOTCH1;CD82;CD81;PDGFA;TGFA;ACVR...  \n",
       "6        8.510505  RABGAP1L;FCER1G;MAP3K1;ITGB2;IGF2;LIF;LAPTM5;E...  \n",
       "7        7.044873  TEAD4;MYOM1;CDKN1A;NOTCH1;TGFB1;GADD45B;DAPK2;...  \n",
       "8        7.044873  VASP;CAP1;B4GALT1;SYK;INSIG1;LAMA3;TNFRSF11B;A...  \n",
       "9        9.768208         ABCC1;SBNO2;TXNRD2;PRDX1;MBP;MPO;PFKP;SOD1  "
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "enr.results[enr.results['Gene_set'] == 'MSigDB_Hallmark_2020'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "a32c99b2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T04:31:31.188734Z",
     "start_time": "2026-01-08T04:31:31.162209Z"
    },
    "scrolled": false
   },
   "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>Gene_set</th>\n",
       "      <th>Term</th>\n",
       "      <th>Overlap</th>\n",
       "      <th>P-value</th>\n",
       "      <th>Adjusted P-value</th>\n",
       "      <th>Old P-value</th>\n",
       "      <th>Old Adjusted P-value</th>\n",
       "      <th>Odds Ratio</th>\n",
       "      <th>Combined Score</th>\n",
       "      <th>Genes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>CAMP UP.V1 DN</td>\n",
       "      <td>33/200</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.000982</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.609120</td>\n",
       "      <td>31.732627</td>\n",
       "      <td>RERE;STXBP1;INSIG1;SLC2A3;ASAP2;BZW1;DEDD2;ZFP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>MEK UP.V1 UP</td>\n",
       "      <td>30/196</td>\n",
       "      <td>0.000059</td>\n",
       "      <td>0.005593</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.381221</td>\n",
       "      <td>23.168223</td>\n",
       "      <td>GALNT12;PTPRU;PPP1R13B;EPAS1;LRP5;AGAP1;TNFRSF...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>LTE2 UP.V1 UP</td>\n",
       "      <td>25/190</td>\n",
       "      <td>0.002220</td>\n",
       "      <td>0.096335</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.989366</td>\n",
       "      <td>12.155228</td>\n",
       "      <td>GALNT12;CYFIP2;CALML5;EPAS1;ECI2;TNFRSF11B;FAM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>ESC V6.5 UP EARLY.V1 UP</td>\n",
       "      <td>23/170</td>\n",
       "      <td>0.002275</td>\n",
       "      <td>0.096335</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.053404</td>\n",
       "      <td>12.496231</td>\n",
       "      <td>KLF13;WNT3A;CHD7;LEF1;NRL;MLLT1;ARAP1;ARID3B;T...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>IL2 UP.V1 UP</td>\n",
       "      <td>25/192</td>\n",
       "      <td>0.002562</td>\n",
       "      <td>0.096335</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.965328</td>\n",
       "      <td>11.726962</td>\n",
       "      <td>DGKG;MEGF6;FLT1;SLC2A3;AHR;HK2;SOCS2;PIM1;PAK6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>PDGF ERK DN.V1 DN</td>\n",
       "      <td>20/149</td>\n",
       "      <td>0.004646</td>\n",
       "      <td>0.097090</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.032363</td>\n",
       "      <td>10.917523</td>\n",
       "      <td>KLF10;CEBPB;FAM89B;DUSP1;LY86;TBCC;FBXL18;LTBP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>ERB2 UP.V1 UP</td>\n",
       "      <td>24/191</td>\n",
       "      <td>0.004872</td>\n",
       "      <td>0.097090</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.885370</td>\n",
       "      <td>10.038079</td>\n",
       "      <td>GALNT12;CSGALNACT1;CAST;VASP;SH3GLB2;BNIP3L;PT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>CRX NRL DN.V1 UP</td>\n",
       "      <td>19/140</td>\n",
       "      <td>0.005060</td>\n",
       "      <td>0.097090</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.057828</td>\n",
       "      <td>10.878373</td>\n",
       "      <td>B4GALT1;PLEKHA2;SYTL1;RFX2;NRL;MYO7A;PDIA5;ZFP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>STK33 DN</td>\n",
       "      <td>33/289</td>\n",
       "      <td>0.005087</td>\n",
       "      <td>0.097090</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.693813</td>\n",
       "      <td>8.945023</td>\n",
       "      <td>CYFIP2;GALNT12;FBLN7;VKORC1L1;NLRC3;PIK3CB;AFF...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>TGFB UP.V1 UP</td>\n",
       "      <td>24/192</td>\n",
       "      <td>0.005202</td>\n",
       "      <td>0.097090</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.874045</td>\n",
       "      <td>9.854962</td>\n",
       "      <td>KLF10;MLXIP;TLE3;EPHA4;GADD45B;LIF;TFEB;JMJD1C...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Gene_set                     Term Overlap   P-value  \\\n",
       "50  MSigDB_Oncogenic_Signatures            CAMP UP.V1 DN  33/200  0.000005   \n",
       "51  MSigDB_Oncogenic_Signatures             MEK UP.V1 UP  30/196  0.000059   \n",
       "52  MSigDB_Oncogenic_Signatures            LTE2 UP.V1 UP  25/190  0.002220   \n",
       "53  MSigDB_Oncogenic_Signatures  ESC V6.5 UP EARLY.V1 UP  23/170  0.002275   \n",
       "54  MSigDB_Oncogenic_Signatures             IL2 UP.V1 UP  25/192  0.002562   \n",
       "55  MSigDB_Oncogenic_Signatures        PDGF ERK DN.V1 DN  20/149  0.004646   \n",
       "56  MSigDB_Oncogenic_Signatures            ERB2 UP.V1 UP  24/191  0.004872   \n",
       "57  MSigDB_Oncogenic_Signatures         CRX NRL DN.V1 UP  19/140  0.005060   \n",
       "58  MSigDB_Oncogenic_Signatures                 STK33 DN  33/289  0.005087   \n",
       "59  MSigDB_Oncogenic_Signatures            TGFB UP.V1 UP  24/192  0.005202   \n",
       "\n",
       "    Adjusted P-value  Old P-value  Old Adjusted P-value  Odds Ratio  \\\n",
       "50          0.000982            0                     0    2.609120   \n",
       "51          0.005593            0                     0    2.381221   \n",
       "52          0.096335            0                     0    1.989366   \n",
       "53          0.096335            0                     0    2.053404   \n",
       "54          0.096335            0                     0    1.965328   \n",
       "55          0.097090            0                     0    2.032363   \n",
       "56          0.097090            0                     0    1.885370   \n",
       "57          0.097090            0                     0    2.057828   \n",
       "58          0.097090            0                     0    1.693813   \n",
       "59          0.097090            0                     0    1.874045   \n",
       "\n",
       "    Combined Score                                              Genes  \n",
       "50       31.732627  RERE;STXBP1;INSIG1;SLC2A3;ASAP2;BZW1;DEDD2;ZFP...  \n",
       "51       23.168223  GALNT12;PTPRU;PPP1R13B;EPAS1;LRP5;AGAP1;TNFRSF...  \n",
       "52       12.155228  GALNT12;CYFIP2;CALML5;EPAS1;ECI2;TNFRSF11B;FAM...  \n",
       "53       12.496231  KLF13;WNT3A;CHD7;LEF1;NRL;MLLT1;ARAP1;ARID3B;T...  \n",
       "54       11.726962  DGKG;MEGF6;FLT1;SLC2A3;AHR;HK2;SOCS2;PIM1;PAK6...  \n",
       "55       10.917523  KLF10;CEBPB;FAM89B;DUSP1;LY86;TBCC;FBXL18;LTBP...  \n",
       "56       10.038079  GALNT12;CSGALNACT1;CAST;VASP;SH3GLB2;BNIP3L;PT...  \n",
       "57       10.878373  B4GALT1;PLEKHA2;SYTL1;RFX2;NRL;MYO7A;PDIA5;ZFP...  \n",
       "58        8.945023  CYFIP2;GALNT12;FBLN7;VKORC1L1;NLRC3;PIK3CB;AFF...  \n",
       "59        9.854962  KLF10;MLXIP;TLE3;EPHA4;GADD45B;LIF;TFEB;JMJD1C...  "
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "enr.results[enr.results['Gene_set'] == 'MSigDB_Oncogenic_Signatures'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "814b3d8b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T04:31:52.974801Z",
     "start_time": "2026-01-08T04:31:52.948567Z"
    },
    "scrolled": false
   },
   "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>Gene_set</th>\n",
       "      <th>Term</th>\n",
       "      <th>Overlap</th>\n",
       "      <th>P-value</th>\n",
       "      <th>Adjusted P-value</th>\n",
       "      <th>Old P-value</th>\n",
       "      <th>Old Adjusted P-value</th>\n",
       "      <th>Odds Ratio</th>\n",
       "      <th>Combined Score</th>\n",
       "      <th>Genes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Pathways in cancer</td>\n",
       "      <td>77/531</td>\n",
       "      <td>1.837772e-09</td>\n",
       "      <td>4.829619e-07</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.276331</td>\n",
       "      <td>45.787733</td>\n",
       "      <td>GSK3B;CDKN1A;SPI1;CALML5;SLC2A1;PIK3CD;FZD10;P...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Hippo signaling pathway</td>\n",
       "      <td>35/163</td>\n",
       "      <td>3.187868e-09</td>\n",
       "      <td>4.829619e-07</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.623243</td>\n",
       "      <td>70.884819</td>\n",
       "      <td>GSK3B;YWHAB;ITGB2;LEF1;FZD10;PRKCZ;ACTB;SAV1;N...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Colorectal cancer</td>\n",
       "      <td>22/86</td>\n",
       "      <td>1.023860e-07</td>\n",
       "      <td>1.034099e-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.528448</td>\n",
       "      <td>72.883170</td>\n",
       "      <td>SMAD2;GSK3B;TCF7L2;CDKN1A;MAP2K2;RALB;SMAD3;TG...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Hepatocellular carcinoma</td>\n",
       "      <td>32/168</td>\n",
       "      <td>2.836262e-07</td>\n",
       "      <td>2.148469e-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.109762</td>\n",
       "      <td>46.881551</td>\n",
       "      <td>GSK3B;CDKN1A;SMARCD2;SMARCB1;LEF1;LRP5;TGFA;PI...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Gastric cancer</td>\n",
       "      <td>28/149</td>\n",
       "      <td>2.038094e-06</td>\n",
       "      <td>1.057834e-04</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.052097</td>\n",
       "      <td>39.993145</td>\n",
       "      <td>GSK3B;CDKN1A;LEF1;LRP5;PIK3CD;FZD10;PIK3CB;FGF...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Transcriptional misregulation in cancer</td>\n",
       "      <td>33/192</td>\n",
       "      <td>2.094720e-06</td>\n",
       "      <td>1.057834e-04</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.741588</td>\n",
       "      <td>35.849252</td>\n",
       "      <td>CDKN1A;CEBPB;SPI1;SLC45A3;FLT1;DOT1L;JMJD1C;PD...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Breast cancer</td>\n",
       "      <td>27/147</td>\n",
       "      <td>4.835016e-06</td>\n",
       "      <td>2.092871e-04</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.965661</td>\n",
       "      <td>36.298578</td>\n",
       "      <td>GSK3B;CDKN1A;NOTCH1;LEF1;LRP5;PIK3CD;FZD10;PIK...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Endometrial cancer</td>\n",
       "      <td>15/58</td>\n",
       "      <td>9.378029e-06</td>\n",
       "      <td>3.551929e-04</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.577871</td>\n",
       "      <td>52.998655</td>\n",
       "      <td>GSK3B;TCF7L2;CDKN1A;MAP2K2;GADD45B;PDPK1;LEF1;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Glycosaminoglycan biosynthesis</td>\n",
       "      <td>14/53</td>\n",
       "      <td>1.423206e-05</td>\n",
       "      <td>4.569391e-04</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.708585</td>\n",
       "      <td>52.547874</td>\n",
       "      <td>CSGALNACT1;B4GALT1;CHPF2;CSGALNACT2;XYLT1;HS6S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Cellular senescence</td>\n",
       "      <td>27/156</td>\n",
       "      <td>1.508050e-05</td>\n",
       "      <td>4.569391e-04</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.757409</td>\n",
       "      <td>30.613049</td>\n",
       "      <td>CDKN1A;CALML5;TRAF3IP2;ITPR1;ITPR2;PIK3CD;ITPR...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Gene_set                                     Term Overlap  \\\n",
       "238  KEGG_2021_Human                       Pathways in cancer  77/531   \n",
       "239  KEGG_2021_Human                  Hippo signaling pathway  35/163   \n",
       "240  KEGG_2021_Human                        Colorectal cancer   22/86   \n",
       "241  KEGG_2021_Human                 Hepatocellular carcinoma  32/168   \n",
       "242  KEGG_2021_Human                           Gastric cancer  28/149   \n",
       "243  KEGG_2021_Human  Transcriptional misregulation in cancer  33/192   \n",
       "244  KEGG_2021_Human                            Breast cancer  27/147   \n",
       "245  KEGG_2021_Human                       Endometrial cancer   15/58   \n",
       "246  KEGG_2021_Human           Glycosaminoglycan biosynthesis   14/53   \n",
       "247  KEGG_2021_Human                      Cellular senescence  27/156   \n",
       "\n",
       "          P-value  Adjusted P-value  Old P-value  Old Adjusted P-value  \\\n",
       "238  1.837772e-09      4.829619e-07            0                     0   \n",
       "239  3.187868e-09      4.829619e-07            0                     0   \n",
       "240  1.023860e-07      1.034099e-05            0                     0   \n",
       "241  2.836262e-07      2.148469e-05            0                     0   \n",
       "242  2.038094e-06      1.057834e-04            0                     0   \n",
       "243  2.094720e-06      1.057834e-04            0                     0   \n",
       "244  4.835016e-06      2.092871e-04            0                     0   \n",
       "245  9.378029e-06      3.551929e-04            0                     0   \n",
       "246  1.423206e-05      4.569391e-04            0                     0   \n",
       "247  1.508050e-05      4.569391e-04            0                     0   \n",
       "\n",
       "     Odds Ratio  Combined Score  \\\n",
       "238    2.276331       45.787733   \n",
       "239    3.623243       70.884819   \n",
       "240    4.528448       72.883170   \n",
       "241    3.109762       46.881551   \n",
       "242    3.052097       39.993145   \n",
       "243    2.741588       35.849252   \n",
       "244    2.965661       36.298578   \n",
       "245    4.577871       52.998655   \n",
       "246    4.708585       52.547874   \n",
       "247    2.757409       30.613049   \n",
       "\n",
       "                                                 Genes  \n",
       "238  GSK3B;CDKN1A;SPI1;CALML5;SLC2A1;PIK3CD;FZD10;P...  \n",
       "239  GSK3B;YWHAB;ITGB2;LEF1;FZD10;PRKCZ;ACTB;SAV1;N...  \n",
       "240  SMAD2;GSK3B;TCF7L2;CDKN1A;MAP2K2;RALB;SMAD3;TG...  \n",
       "241  GSK3B;CDKN1A;SMARCD2;SMARCB1;LEF1;LRP5;TGFA;PI...  \n",
       "242  GSK3B;CDKN1A;LEF1;LRP5;PIK3CD;FZD10;PIK3CB;FGF...  \n",
       "243  CDKN1A;CEBPB;SPI1;SLC45A3;FLT1;DOT1L;JMJD1C;PD...  \n",
       "244  GSK3B;CDKN1A;NOTCH1;LEF1;LRP5;PIK3CD;FZD10;PIK...  \n",
       "245  GSK3B;TCF7L2;CDKN1A;MAP2K2;GADD45B;PDPK1;LEF1;...  \n",
       "246  CSGALNACT1;B4GALT1;CHPF2;CSGALNACT2;XYLT1;HS6S...  \n",
       "247  CDKN1A;CALML5;TRAF3IP2;ITPR1;ITPR2;PIK3CD;ITPR...  "
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "enr.results[enr.results['Gene_set'] == 'KEGG_2021_Human'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "40a82ebf",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T06:23:39.344948Z",
     "start_time": "2026-01-08T06:23:39.220407Z"
    }
   },
   "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>Chromosome</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>2028172</td>\n",
       "      <td>2028624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>22712349</td>\n",
       "      <td>22712836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>35268574</td>\n",
       "      <td>35269106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>182616062</td>\n",
       "      <td>182616637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>111203696</td>\n",
       "      <td>111204456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5126</th>\n",
       "      <td>chrX</td>\n",
       "      <td>135521416</td>\n",
       "      <td>135521718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5127</th>\n",
       "      <td>chrY</td>\n",
       "      <td>2841376</td>\n",
       "      <td>2841678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5128</th>\n",
       "      <td>chrY</td>\n",
       "      <td>12536863</td>\n",
       "      <td>12537462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5129</th>\n",
       "      <td>chrY</td>\n",
       "      <td>6909010</td>\n",
       "      <td>6909481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5130</th>\n",
       "      <td>chrY</td>\n",
       "      <td>7703472</td>\n",
       "      <td>7703877</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5131 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "+--------------+-----------+-----------+\n",
       "| Chromosome   | Start     | End       |\n",
       "| (category)   | (int64)   | (int64)   |\n",
       "|--------------+-----------+-----------|\n",
       "| chr1         | 2028172   | 2028624   |\n",
       "| chr1         | 22712349  | 22712836  |\n",
       "| chr1         | 35268574  | 35269106  |\n",
       "| chr1         | 182616062 | 182616637 |\n",
       "| ...          | ...       | ...       |\n",
       "| chrY         | 2841376   | 2841678   |\n",
       "| chrY         | 12536863  | 12537462  |\n",
       "| chrY         | 6909010   | 6909481   |\n",
       "| chrY         | 7703472   | 7703877   |\n",
       "+--------------+-----------+-----------+\n",
       "Unstranded PyRanges object has 5,131 rows and 3 columns from 37 chromosomes.\n",
       "For printing, the PyRanges was sorted on Chromosome."
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nalm_runx1_only_peaks_df = nalm_runx1_only_peaks.to_dataframe(names=range(20))\n",
    "nalm_runx1_only_peaks_df = nalm_runx1_only_peaks_df[[0, 1, 2]]\n",
    "nalm_runx1_only_peaks_df.columns = ['Chromosome', 'Start', 'End']\n",
    "nalm_runx1_only_peaks = pr.PyRanges(nalm_runx1_only_peaks_df)\n",
    "nalm_runx1_only_peaks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "798c8b95",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T06:23:55.030221Z",
     "start_time": "2026-01-08T06:23:54.584167Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "join: Strand data from other will be added as strand data to self.\n",
      "If this is undesired use the flag apply_strand_suffix=False.\n",
      "To turn off the warning set apply_strand_suffix to True or False.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Chromosome</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Strand</th>\n",
       "      <th>gene_name</th>\n",
       "      <th>Distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>2028172</td>\n",
       "      <td>2028624</td>\n",
       "      <td>+</td>\n",
       "      <td>GABRD</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>22712349</td>\n",
       "      <td>22712836</td>\n",
       "      <td>+</td>\n",
       "      <td>EPHB2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>35268574</td>\n",
       "      <td>35269106</td>\n",
       "      <td>+</td>\n",
       "      <td>ZMYM4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>41003634</td>\n",
       "      <td>41004019</td>\n",
       "      <td>+</td>\n",
       "      <td>CTPS1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>202484037</td>\n",
       "      <td>202484461</td>\n",
       "      <td>+</td>\n",
       "      <td>PPP1R12B</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5107</th>\n",
       "      <td>chrX</td>\n",
       "      <td>154004356</td>\n",
       "      <td>154004647</td>\n",
       "      <td>-</td>\n",
       "      <td>IRAK1</td>\n",
       "      <td>5859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5108</th>\n",
       "      <td>chrY</td>\n",
       "      <td>2841376</td>\n",
       "      <td>2841678</td>\n",
       "      <td>+</td>\n",
       "      <td>RPS4Y1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5109</th>\n",
       "      <td>chrY</td>\n",
       "      <td>7703472</td>\n",
       "      <td>7703877</td>\n",
       "      <td>+</td>\n",
       "      <td>TBL1Y</td>\n",
       "      <td>601503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5110</th>\n",
       "      <td>chrY</td>\n",
       "      <td>12536863</td>\n",
       "      <td>12537462</td>\n",
       "      <td>+</td>\n",
       "      <td>USP9Y</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5111</th>\n",
       "      <td>chrY</td>\n",
       "      <td>6909010</td>\n",
       "      <td>6909481</td>\n",
       "      <td>-</td>\n",
       "      <td>AMELY</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5112 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "+--------------+-----------+-----------+--------------+-------------+-------+\n",
       "| Chromosome   | Start     | End       | Strand       | gene_name   | +1    |\n",
       "| (category)   | (int64)   | (int64)   | (category)   | (object)    | ...   |\n",
       "|--------------+-----------+-----------+--------------+-------------+-------|\n",
       "| chr1         | 2028172   | 2028624   | +            | GABRD       | ...   |\n",
       "| chr1         | 22712349  | 22712836  | +            | EPHB2       | ...   |\n",
       "| chr1         | 35268574  | 35269106  | +            | ZMYM4       | ...   |\n",
       "| chr1         | 41003634  | 41004019  | +            | CTPS1       | ...   |\n",
       "| ...          | ...       | ...       | ...          | ...         | ...   |\n",
       "| chrY         | 2841376   | 2841678   | +            | RPS4Y1      | ...   |\n",
       "| chrY         | 7703472   | 7703877   | +            | TBL1Y       | ...   |\n",
       "| chrY         | 12536863  | 12537462  | +            | USP9Y       | ...   |\n",
       "| chrY         | 6909010   | 6909481   | -            | AMELY       | ...   |\n",
       "+--------------+-----------+-----------+--------------+-------------+-------+\n",
       "Stranded PyRanges object has 5,112 rows and 6 columns from 24 chromosomes.\n",
       "For printing, the PyRanges was sorted on Chromosome and Strand.\n",
       "1 hidden columns: Distance"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nalm_runx1_only_peaks = nalm_runx1_only_peaks.nearest(all_genes)\n",
    "nalm_runx1_only_peaks = nalm_runx1_only_peaks[['Chromosome', 'Start', 'End', 'gene_name', 'Distance']]\n",
    "nalm_runx1_only_peaks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "3212b5c5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T06:33:53.028513Z",
     "start_time": "2026-01-08T06:33:21.659540Z"
    }
   },
   "outputs": [],
   "source": [
    "enr = gp.enrichr(gene_list=nalm_runx1_only_peaks.gene_name,\n",
    "#                  background=all_genes.gene_name,\n",
    "                 gene_sets=['MSigDB_Hallmark_2020', 'MSigDB_Oncogenic_Signatures', 'KEGG_2021_Human', \n",
    "                            'ENCODE_TF_ChIP-seq_2015'],\n",
    "                 organism='human')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "47bed35e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T06:33:53.052884Z",
     "start_time": "2026-01-08T06:33:53.031991Z"
    },
    "scrolled": false
   },
   "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>Gene_set</th>\n",
       "      <th>Term</th>\n",
       "      <th>Overlap</th>\n",
       "      <th>P-value</th>\n",
       "      <th>Adjusted P-value</th>\n",
       "      <th>Old P-value</th>\n",
       "      <th>Old Adjusted P-value</th>\n",
       "      <th>Odds Ratio</th>\n",
       "      <th>Combined Score</th>\n",
       "      <th>Genes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>UV Response Dn</td>\n",
       "      <td>57/144</td>\n",
       "      <td>1.100838e-08</td>\n",
       "      <td>5.504192e-07</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.781843</td>\n",
       "      <td>50.976185</td>\n",
       "      <td>NRP1;IRS1;CITED2;CELF2;PTEN;FHL2;ICA1;PTPRM;PI...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>PI3K/AKT/mTOR  Signaling</td>\n",
       "      <td>41/105</td>\n",
       "      <td>1.827883e-06</td>\n",
       "      <td>4.569708e-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.712502</td>\n",
       "      <td>35.838526</td>\n",
       "      <td>ATF1;ARF1;RALB;CAB39;CAB39L;MAPKAP1;UBE2D3;CLT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>mTORC1 Signaling</td>\n",
       "      <td>63/200</td>\n",
       "      <td>2.120077e-05</td>\n",
       "      <td>3.533462e-04</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.949543</td>\n",
       "      <td>20.979949</td>\n",
       "      <td>ERO1A;BTG2;TFRC;GBE1;UBE2D3;ARPC5L;SLC2A1;PLOD...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>Estrogen Response Early</td>\n",
       "      <td>62/200</td>\n",
       "      <td>4.194548e-05</td>\n",
       "      <td>5.243185e-04</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.904072</td>\n",
       "      <td>19.191406</td>\n",
       "      <td>RET;LAD1;SCARB1;B4GALT1;NXT1;MAST4;FHL2;SLC2A1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>Mitotic Spindle</td>\n",
       "      <td>61/199</td>\n",
       "      <td>6.919302e-05</td>\n",
       "      <td>6.919302e-04</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.872865</td>\n",
       "      <td>17.939449</td>\n",
       "      <td>DOCK4;NUMA1;ARHGAP5;PKD2;PREX1;CAPZB;ARHGDIA;C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>Hypoxia</td>\n",
       "      <td>58/200</td>\n",
       "      <td>5.131496e-04</td>\n",
       "      <td>4.276247e-03</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.728791</td>\n",
       "      <td>13.095496</td>\n",
       "      <td>CDKN1C;ERO1A;SCARB1;BTG1;CITED2;GBE1;HDLBP;SLC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>Myc Targets V1</td>\n",
       "      <td>57/200</td>\n",
       "      <td>9.066499e-04</td>\n",
       "      <td>6.476071e-03</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.686553</td>\n",
       "      <td>11.815573</td>\n",
       "      <td>HSP90AB1;MCM7;PWP1;RRP9;PSMD7;XPO1;MYC;TXNL4A;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>IL-2/STAT5 Signaling</td>\n",
       "      <td>56/199</td>\n",
       "      <td>1.381042e-03</td>\n",
       "      <td>8.631514e-03</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.656526</td>\n",
       "      <td>10.908088</td>\n",
       "      <td>CDKN1C;NRP1;CD83;CSF2;CD81;GPR65;SLC2A3;ENO3;L...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>Hedgehog Signaling</td>\n",
       "      <td>15/36</td>\n",
       "      <td>1.597086e-03</td>\n",
       "      <td>8.872699e-03</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.011871</td>\n",
       "      <td>19.395165</td>\n",
       "      <td>NRP1;NRP2;TLE1;CRMP1;PLG;THY1;VLDLR;ETS2;CDK6;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>MSigDB_Hallmark_2020</td>\n",
       "      <td>TNF-alpha Signaling via NF-kB</td>\n",
       "      <td>54/200</td>\n",
       "      <td>4.355159e-03</td>\n",
       "      <td>1.814650e-02</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.563423</td>\n",
       "      <td>8.499384</td>\n",
       "      <td>BTG2;TNFAIP8;BTG1;CD83;CSF2;B4GALT1;RNF19B;IRS...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Gene_set                           Term Overlap       P-value  \\\n",
       "0  MSigDB_Hallmark_2020                 UV Response Dn  57/144  1.100838e-08   \n",
       "1  MSigDB_Hallmark_2020       PI3K/AKT/mTOR  Signaling  41/105  1.827883e-06   \n",
       "2  MSigDB_Hallmark_2020               mTORC1 Signaling  63/200  2.120077e-05   \n",
       "3  MSigDB_Hallmark_2020        Estrogen Response Early  62/200  4.194548e-05   \n",
       "4  MSigDB_Hallmark_2020                Mitotic Spindle  61/199  6.919302e-05   \n",
       "5  MSigDB_Hallmark_2020                        Hypoxia  58/200  5.131496e-04   \n",
       "6  MSigDB_Hallmark_2020                 Myc Targets V1  57/200  9.066499e-04   \n",
       "7  MSigDB_Hallmark_2020           IL-2/STAT5 Signaling  56/199  1.381042e-03   \n",
       "8  MSigDB_Hallmark_2020             Hedgehog Signaling   15/36  1.597086e-03   \n",
       "9  MSigDB_Hallmark_2020  TNF-alpha Signaling via NF-kB  54/200  4.355159e-03   \n",
       "\n",
       "   Adjusted P-value  Old P-value  Old Adjusted P-value  Odds Ratio  \\\n",
       "0      5.504192e-07            0                     0    2.781843   \n",
       "1      4.569708e-05            0                     0    2.712502   \n",
       "2      3.533462e-04            0                     0    1.949543   \n",
       "3      5.243185e-04            0                     0    1.904072   \n",
       "4      6.919302e-04            0                     0    1.872865   \n",
       "5      4.276247e-03            0                     0    1.728791   \n",
       "6      6.476071e-03            0                     0    1.686553   \n",
       "7      8.631514e-03            0                     0    1.656526   \n",
       "8      8.872699e-03            0                     0    3.011871   \n",
       "9      1.814650e-02            0                     0    1.563423   \n",
       "\n",
       "   Combined Score                                              Genes  \n",
       "0       50.976185  NRP1;IRS1;CITED2;CELF2;PTEN;FHL2;ICA1;PTPRM;PI...  \n",
       "1       35.838526  ATF1;ARF1;RALB;CAB39;CAB39L;MAPKAP1;UBE2D3;CLT...  \n",
       "2       20.979949  ERO1A;BTG2;TFRC;GBE1;UBE2D3;ARPC5L;SLC2A1;PLOD...  \n",
       "3       19.191406  RET;LAD1;SCARB1;B4GALT1;NXT1;MAST4;FHL2;SLC2A1...  \n",
       "4       17.939449  DOCK4;NUMA1;ARHGAP5;PKD2;PREX1;CAPZB;ARHGDIA;C...  \n",
       "5       13.095496  CDKN1C;ERO1A;SCARB1;BTG1;CITED2;GBE1;HDLBP;SLC...  \n",
       "6       11.815573  HSP90AB1;MCM7;PWP1;RRP9;PSMD7;XPO1;MYC;TXNL4A;...  \n",
       "7       10.908088  CDKN1C;NRP1;CD83;CSF2;CD81;GPR65;SLC2A3;ENO3;L...  \n",
       "8       19.395165  NRP1;NRP2;TLE1;CRMP1;PLG;THY1;VLDLR;ETS2;CDK6;...  \n",
       "9        8.499384  BTG2;TNFAIP8;BTG1;CD83;CSF2;B4GALT1;RNF19B;IRS...  "
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "enr.results[enr.results['Gene_set'] == 'MSigDB_Hallmark_2020'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "314e3308",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T06:33:53.076044Z",
     "start_time": "2026-01-08T06:33:53.055336Z"
    },
    "scrolled": false
   },
   "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>Gene_set</th>\n",
       "      <th>Term</th>\n",
       "      <th>Overlap</th>\n",
       "      <th>P-value</th>\n",
       "      <th>Adjusted P-value</th>\n",
       "      <th>Old P-value</th>\n",
       "      <th>Old Adjusted P-value</th>\n",
       "      <th>Odds Ratio</th>\n",
       "      <th>Combined Score</th>\n",
       "      <th>Genes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>CAMP UP.V1 DN</td>\n",
       "      <td>61/200</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.010227</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.859276</td>\n",
       "      <td>17.512895</td>\n",
       "      <td>RERE;CD83;ATP8A1;CELF2;SLC2A3;TMEM97;ARHGAP5;F...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>MTOR UP.N4.V1 UP</td>\n",
       "      <td>59/196</td>\n",
       "      <td>0.000157</td>\n",
       "      <td>0.010227</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.823832</td>\n",
       "      <td>15.980001</td>\n",
       "      <td>MIPEP;ITK;TRAF3IP2;GBE1;GPR65;MAST2;MSMO1;ADAR...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>TBK1.DF DN</td>\n",
       "      <td>80/287</td>\n",
       "      <td>0.000214</td>\n",
       "      <td>0.010227</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.638660</td>\n",
       "      <td>13.846041</td>\n",
       "      <td>SCARB1;SERPINE2;MTR;BACH1;RCBTB1;C12ORF43;RSRC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>RAF UP.V1 DN</td>\n",
       "      <td>58/194</td>\n",
       "      <td>0.000216</td>\n",
       "      <td>0.010227</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.805738</td>\n",
       "      <td>15.237173</td>\n",
       "      <td>DIDO1;LPGAT1;IRS1;JMJD1C;PCSK6;MYLK;IGF1R;SPIN...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>TBK1.DN.48HRS UP</td>\n",
       "      <td>19/50</td>\n",
       "      <td>0.001520</td>\n",
       "      <td>0.049714</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.585480</td>\n",
       "      <td>16.776674</td>\n",
       "      <td>DDR1;TEX10;SLC11A2;TIMM22;PTK2;MYLK;TMCO1;ARL4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>BMI1 DN MEL18 DN.V1 UP</td>\n",
       "      <td>43/145</td>\n",
       "      <td>0.001578</td>\n",
       "      <td>0.049714</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.781707</td>\n",
       "      <td>11.494589</td>\n",
       "      <td>LRRC15;NRP2;CSF2;SLC1A4;VLDLR;SLC7A11;FADS3;OG...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>CSR LATE UP.V1 DN</td>\n",
       "      <td>48/170</td>\n",
       "      <td>0.002697</td>\n",
       "      <td>0.058526</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.662954</td>\n",
       "      <td>9.837117</td>\n",
       "      <td>IDI1;BTG2;ANKRD33B;INSIG1;QPRT;IRS2;MSMO1;BACH...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>LTE2 UP.V1 DN</td>\n",
       "      <td>54/196</td>\n",
       "      <td>0.002749</td>\n",
       "      <td>0.058526</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.607865</td>\n",
       "      <td>9.480747</td>\n",
       "      <td>NRP1;LPGAT1;ATP8A2;WIPF1;LTN1;FHL2;JMJD1C;SLC7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>MEL18 DN.V1 UP</td>\n",
       "      <td>41/141</td>\n",
       "      <td>0.002974</td>\n",
       "      <td>0.058526</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.732118</td>\n",
       "      <td>10.077123</td>\n",
       "      <td>NRP1;NRP2;CSF2;CD83;SLC1A4;SLC1A5;VLDLR;SLC7A1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>MSigDB_Oncogenic_Signatures</td>\n",
       "      <td>BCAT.100 UP.V1 UP</td>\n",
       "      <td>18/49</td>\n",
       "      <td>0.003097</td>\n",
       "      <td>0.058526</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.448762</td>\n",
       "      <td>14.147569</td>\n",
       "      <td>SASH3;IRS1;BIK;GCNT1;DEFA5;DKK1;ETV5;RUNX1;GAD...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Gene_set                    Term Overlap   P-value  \\\n",
       "50  MSigDB_Oncogenic_Signatures           CAMP UP.V1 DN  61/200  0.000081   \n",
       "51  MSigDB_Oncogenic_Signatures        MTOR UP.N4.V1 UP  59/196  0.000157   \n",
       "52  MSigDB_Oncogenic_Signatures              TBK1.DF DN  80/287  0.000214   \n",
       "53  MSigDB_Oncogenic_Signatures            RAF UP.V1 DN  58/194  0.000216   \n",
       "54  MSigDB_Oncogenic_Signatures        TBK1.DN.48HRS UP   19/50  0.001520   \n",
       "55  MSigDB_Oncogenic_Signatures  BMI1 DN MEL18 DN.V1 UP  43/145  0.001578   \n",
       "56  MSigDB_Oncogenic_Signatures       CSR LATE UP.V1 DN  48/170  0.002697   \n",
       "57  MSigDB_Oncogenic_Signatures           LTE2 UP.V1 DN  54/196  0.002749   \n",
       "58  MSigDB_Oncogenic_Signatures          MEL18 DN.V1 UP  41/141  0.002974   \n",
       "59  MSigDB_Oncogenic_Signatures       BCAT.100 UP.V1 UP   18/49  0.003097   \n",
       "\n",
       "    Adjusted P-value  Old P-value  Old Adjusted P-value  Odds Ratio  \\\n",
       "50          0.010227            0                     0    1.859276   \n",
       "51          0.010227            0                     0    1.823832   \n",
       "52          0.010227            0                     0    1.638660   \n",
       "53          0.010227            0                     0    1.805738   \n",
       "54          0.049714            0                     0    2.585480   \n",
       "55          0.049714            0                     0    1.781707   \n",
       "56          0.058526            0                     0    1.662954   \n",
       "57          0.058526            0                     0    1.607865   \n",
       "58          0.058526            0                     0    1.732118   \n",
       "59          0.058526            0                     0    2.448762   \n",
       "\n",
       "    Combined Score                                              Genes  \n",
       "50       17.512895  RERE;CD83;ATP8A1;CELF2;SLC2A3;TMEM97;ARHGAP5;F...  \n",
       "51       15.980001  MIPEP;ITK;TRAF3IP2;GBE1;GPR65;MAST2;MSMO1;ADAR...  \n",
       "52       13.846041  SCARB1;SERPINE2;MTR;BACH1;RCBTB1;C12ORF43;RSRC...  \n",
       "53       15.237173  DIDO1;LPGAT1;IRS1;JMJD1C;PCSK6;MYLK;IGF1R;SPIN...  \n",
       "54       16.776674  DDR1;TEX10;SLC11A2;TIMM22;PTK2;MYLK;TMCO1;ARL4...  \n",
       "55       11.494589  LRRC15;NRP2;CSF2;SLC1A4;VLDLR;SLC7A11;FADS3;OG...  \n",
       "56        9.837117  IDI1;BTG2;ANKRD33B;INSIG1;QPRT;IRS2;MSMO1;BACH...  \n",
       "57        9.480747  NRP1;LPGAT1;ATP8A2;WIPF1;LTN1;FHL2;JMJD1C;SLC7...  \n",
       "58       10.077123  NRP1;NRP2;CSF2;CD83;SLC1A4;SLC1A5;VLDLR;SLC7A1...  \n",
       "59       14.147569  SASH3;IRS1;BIK;GCNT1;DEFA5;DKK1;ETV5;RUNX1;GAD...  "
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "enr.results[enr.results['Gene_set'] == 'MSigDB_Oncogenic_Signatures'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "cbdd2c1d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T06:33:53.104483Z",
     "start_time": "2026-01-08T06:33:53.079094Z"
    },
    "scrolled": false
   },
   "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>Gene_set</th>\n",
       "      <th>Term</th>\n",
       "      <th>Overlap</th>\n",
       "      <th>P-value</th>\n",
       "      <th>Adjusted P-value</th>\n",
       "      <th>Old P-value</th>\n",
       "      <th>Old Adjusted P-value</th>\n",
       "      <th>Odds Ratio</th>\n",
       "      <th>Combined Score</th>\n",
       "      <th>Genes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Glioma</td>\n",
       "      <td>34/75</td>\n",
       "      <td>2.258822e-07</td>\n",
       "      <td>0.000072</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.509800</td>\n",
       "      <td>53.711349</td>\n",
       "      <td>RB1;CAMK2B;CAMK2D;CALML6;PTEN;PIK3CD;PDGFA;PIK...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Non-small cell lung cancer</td>\n",
       "      <td>32/72</td>\n",
       "      <td>8.786077e-07</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.384357</td>\n",
       "      <td>47.194612</td>\n",
       "      <td>ALK;RB1;RET;PIK3CD;PIK3R3;TGFA;PIK3R1;STK4;FHI...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Endocytosis</td>\n",
       "      <td>80/252</td>\n",
       "      <td>1.262154e-06</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.976435</td>\n",
       "      <td>26.845307</td>\n",
       "      <td>ARF1;TFRC;WIPF1;ZFYVE9;SH3KBP1;CLTC;ARPC5L;SNX...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Cellular senescence</td>\n",
       "      <td>55/156</td>\n",
       "      <td>1.681110e-06</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.308928</td>\n",
       "      <td>30.699639</td>\n",
       "      <td>RB1;LIN54;MRE11;TRAF3IP2;CALML6;PTEN;PIK3CD;FO...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Human T-cell leukemia virus 1 infection</td>\n",
       "      <td>70/219</td>\n",
       "      <td>4.334565e-06</td>\n",
       "      <td>0.000275</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.993904</td>\n",
       "      <td>24.622503</td>\n",
       "      <td>RB1;NRP1;CRTC3;CSF2;CRTC1;PTEN;SLC2A1;BUB1B;PI...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Kaposi sarcoma-associated herpesvirus infection</td>\n",
       "      <td>62/193</td>\n",
       "      <td>1.247362e-05</td>\n",
       "      <td>0.000659</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.006693</td>\n",
       "      <td>22.659360</td>\n",
       "      <td>RB1;CSF2;CALML6;TRADD;PIK3CD;ICAM1;PREX1;ZFP36...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Pathways in cancer</td>\n",
       "      <td>141/531</td>\n",
       "      <td>1.756836e-05</td>\n",
       "      <td>0.000796</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.540324</td>\n",
       "      <td>16.865638</td>\n",
       "      <td>RB1;CALML6;KEAP1;ETS1;IGF1R;CCND3;FGF9;AKT2;MY...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>mTOR signaling pathway</td>\n",
       "      <td>51/154</td>\n",
       "      <td>2.862374e-05</td>\n",
       "      <td>0.001134</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.096957</td>\n",
       "      <td>21.936840</td>\n",
       "      <td>IRS1;CAB39L;PTEN;PIK3CD;IGF1R;RPTOR;DEPTOR;AKT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>FoxO signaling pathway</td>\n",
       "      <td>44/131</td>\n",
       "      <td>6.732186e-05</td>\n",
       "      <td>0.002302</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.140037</td>\n",
       "      <td>20.557254</td>\n",
       "      <td>PRKAA1;IRS1;SETD7;PTEN;FOXO6;PIK3R3;PIK3CD;PRK...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>KEGG_2021_Human</td>\n",
       "      <td>Colorectal cancer</td>\n",
       "      <td>32/86</td>\n",
       "      <td>7.261705e-05</td>\n",
       "      <td>0.002302</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.504754</td>\n",
       "      <td>23.871080</td>\n",
       "      <td>RALB;TCF7;PIK3CD;PIK3R3;TGFA;PIK3R1;BBC3;MAPK8...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Gene_set                                             Term  \\\n",
       "239  KEGG_2021_Human                                           Glioma   \n",
       "240  KEGG_2021_Human                       Non-small cell lung cancer   \n",
       "241  KEGG_2021_Human                                      Endocytosis   \n",
       "242  KEGG_2021_Human                              Cellular senescence   \n",
       "243  KEGG_2021_Human          Human T-cell leukemia virus 1 infection   \n",
       "244  KEGG_2021_Human  Kaposi sarcoma-associated herpesvirus infection   \n",
       "245  KEGG_2021_Human                               Pathways in cancer   \n",
       "246  KEGG_2021_Human                           mTOR signaling pathway   \n",
       "247  KEGG_2021_Human                           FoxO signaling pathway   \n",
       "248  KEGG_2021_Human                                Colorectal cancer   \n",
       "\n",
       "     Overlap       P-value  Adjusted P-value  Old P-value  \\\n",
       "239    34/75  2.258822e-07          0.000072            0   \n",
       "240    32/72  8.786077e-07          0.000133            0   \n",
       "241   80/252  1.262154e-06          0.000133            0   \n",
       "242   55/156  1.681110e-06          0.000133            0   \n",
       "243   70/219  4.334565e-06          0.000275            0   \n",
       "244   62/193  1.247362e-05          0.000659            0   \n",
       "245  141/531  1.756836e-05          0.000796            0   \n",
       "246   51/154  2.862374e-05          0.001134            0   \n",
       "247   44/131  6.732186e-05          0.002302            0   \n",
       "248    32/86  7.261705e-05          0.002302            0   \n",
       "\n",
       "     Old Adjusted P-value  Odds Ratio  Combined Score  \\\n",
       "239                     0    3.509800       53.711349   \n",
       "240                     0    3.384357       47.194612   \n",
       "241                     0    1.976435       26.845307   \n",
       "242                     0    2.308928       30.699639   \n",
       "243                     0    1.993904       24.622503   \n",
       "244                     0    2.006693       22.659360   \n",
       "245                     0    1.540324       16.865638   \n",
       "246                     0    2.096957       21.936840   \n",
       "247                     0    2.140037       20.557254   \n",
       "248                     0    2.504754       23.871080   \n",
       "\n",
       "                                                 Genes  \n",
       "239  RB1;CAMK2B;CAMK2D;CALML6;PTEN;PIK3CD;PDGFA;PIK...  \n",
       "240  ALK;RB1;RET;PIK3CD;PIK3R3;TGFA;PIK3R1;STK4;FHI...  \n",
       "241  ARF1;TFRC;WIPF1;ZFYVE9;SH3KBP1;CLTC;ARPC5L;SNX...  \n",
       "242  RB1;LIN54;MRE11;TRAF3IP2;CALML6;PTEN;PIK3CD;FO...  \n",
       "243  RB1;NRP1;CRTC3;CSF2;CRTC1;PTEN;SLC2A1;BUB1B;PI...  \n",
       "244  RB1;CSF2;CALML6;TRADD;PIK3CD;ICAM1;PREX1;ZFP36...  \n",
       "245  RB1;CALML6;KEAP1;ETS1;IGF1R;CCND3;FGF9;AKT2;MY...  \n",
       "246  IRS1;CAB39L;PTEN;PIK3CD;IGF1R;RPTOR;DEPTOR;AKT...  \n",
       "247  PRKAA1;IRS1;SETD7;PTEN;FOXO6;PIK3R3;PIK3CD;PRK...  \n",
       "248  RALB;TCF7;PIK3CD;PIK3R3;TGFA;PIK3R1;BBC3;MAPK8...  "
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "enr.results[enr.results['Gene_set'] == 'KEGG_2021_Human'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "f826649b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T06:33:04.067581Z",
     "start_time": "2026-01-08T06:33:04.039217Z"
    },
    "scrolled": false
   },
   "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>Gene_set</th>\n",
       "      <th>Term</th>\n",
       "      <th>P-value</th>\n",
       "      <th>Adjusted P-value</th>\n",
       "      <th>Old P-value</th>\n",
       "      <th>Old adjusted P-value</th>\n",
       "      <th>Odds Ratio</th>\n",
       "      <th>Combined Score</th>\n",
       "      <th>Genes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>556</th>\n",
       "      <td>ENCODE_TF_ChIP-seq_2015</td>\n",
       "      <td>MYC K562 hg19</td>\n",
       "      <td>8.831624e-28</td>\n",
       "      <td>7.206605e-25</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.526363</td>\n",
       "      <td>95.083310</td>\n",
       "      <td>ATF1;ZNF296;ZFYVE9;GMFG;EHMT1;TMEM97;FAM110A;P...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557</th>\n",
       "      <td>ENCODE_TF_ChIP-seq_2015</td>\n",
       "      <td>MYOD1 myocyte mm9</td>\n",
       "      <td>3.182740e-25</td>\n",
       "      <td>1.298558e-22</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.675086</td>\n",
       "      <td>94.486361</td>\n",
       "      <td>ATF1;RB1;NCKAP1;TFRC;SCT;TMEM200A;RAPH1;EHMT1;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558</th>\n",
       "      <td>ENCODE_TF_ChIP-seq_2015</td>\n",
       "      <td>MYOG myocyte mm9</td>\n",
       "      <td>5.179128e-25</td>\n",
       "      <td>1.408723e-22</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.628380</td>\n",
       "      <td>91.058997</td>\n",
       "      <td>ATF1;EHMT1;FAM110A;ALKBH2;PSMD6;AKT2;FAM110B;Z...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559</th>\n",
       "      <td>ENCODE_TF_ChIP-seq_2015</td>\n",
       "      <td>PAX5 GM12878 hg19</td>\n",
       "      <td>4.337751e-24</td>\n",
       "      <td>8.849012e-22</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.781312</td>\n",
       "      <td>95.825094</td>\n",
       "      <td>ATF1;RB1;RPL3;TFRC;RRP8;ELK3;FAM110A;ALKBH2;PS...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560</th>\n",
       "      <td>ENCODE_TF_ChIP-seq_2015</td>\n",
       "      <td>CHD1 CH12.LX mm9</td>\n",
       "      <td>7.145536e-23</td>\n",
       "      <td>1.166152e-20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.824266</td>\n",
       "      <td>93.024722</td>\n",
       "      <td>TFRC;SCT;ARPC5L;GABPB1;FAM110A;MILR1;GPR174;AL...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561</th>\n",
       "      <td>ENCODE_TF_ChIP-seq_2015</td>\n",
       "      <td>EP300 SK-N-SH hg19</td>\n",
       "      <td>2.795713e-22</td>\n",
       "      <td>3.802170e-20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.696157</td>\n",
       "      <td>84.178216</td>\n",
       "      <td>RB1;NCKAP1;TFRC;MYT1L;RAPH1;RRP8;TSEN54;PSMD9;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>562</th>\n",
       "      <td>ENCODE_TF_ChIP-seq_2015</td>\n",
       "      <td>MEF2A GM12878 hg19</td>\n",
       "      <td>3.369760e-22</td>\n",
       "      <td>3.928178e-20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.258709</td>\n",
       "      <td>111.675182</td>\n",
       "      <td>EIF4A2;RB1;ZNF296;RPL3;TFRC;SCT;ARPC5L;KEAP1;C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>563</th>\n",
       "      <td>ENCODE_TF_ChIP-seq_2015</td>\n",
       "      <td>EP300 GM12878 hg19</td>\n",
       "      <td>9.707993e-22</td>\n",
       "      <td>9.902153e-20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.518192</td>\n",
       "      <td>73.456072</td>\n",
       "      <td>ATF1;MAPKBP1;ZNF296;TFRC;GMFG;TMEM97;FAM110A;I...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>564</th>\n",
       "      <td>ENCODE_TF_ChIP-seq_2015</td>\n",
       "      <td>EGR1 GM12878 hg19</td>\n",
       "      <td>2.381467e-21</td>\n",
       "      <td>2.159197e-19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.628456</td>\n",
       "      <td>77.329804</td>\n",
       "      <td>ATF1;MAPKBP1;RPL3;TFRC;GMFG;UXS1;ARPC5L;RAPH1;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>565</th>\n",
       "      <td>ENCODE_TF_ChIP-seq_2015</td>\n",
       "      <td>TCF3 myocyte mm9</td>\n",
       "      <td>3.898045e-21</td>\n",
       "      <td>3.180805e-19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.770540</td>\n",
       "      <td>83.204434</td>\n",
       "      <td>ATF1;RB1;NCKAP1;RPL3;TMEM200A;RAPH1;ADARB1;GAB...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Gene_set                Term       P-value  \\\n",
       "556  ENCODE_TF_ChIP-seq_2015       MYC K562 hg19  8.831624e-28   \n",
       "557  ENCODE_TF_ChIP-seq_2015   MYOD1 myocyte mm9  3.182740e-25   \n",
       "558  ENCODE_TF_ChIP-seq_2015    MYOG myocyte mm9  5.179128e-25   \n",
       "559  ENCODE_TF_ChIP-seq_2015   PAX5 GM12878 hg19  4.337751e-24   \n",
       "560  ENCODE_TF_ChIP-seq_2015    CHD1 CH12.LX mm9  7.145536e-23   \n",
       "561  ENCODE_TF_ChIP-seq_2015  EP300 SK-N-SH hg19  2.795713e-22   \n",
       "562  ENCODE_TF_ChIP-seq_2015  MEF2A GM12878 hg19  3.369760e-22   \n",
       "563  ENCODE_TF_ChIP-seq_2015  EP300 GM12878 hg19  9.707993e-22   \n",
       "564  ENCODE_TF_ChIP-seq_2015   EGR1 GM12878 hg19  2.381467e-21   \n",
       "565  ENCODE_TF_ChIP-seq_2015    TCF3 myocyte mm9  3.898045e-21   \n",
       "\n",
       "     Adjusted P-value  Old P-value  Old adjusted P-value  Odds Ratio  \\\n",
       "556      7.206605e-25            0                     0    1.526363   \n",
       "557      1.298558e-22            0                     0    1.675086   \n",
       "558      1.408723e-22            0                     0    1.628380   \n",
       "559      8.849012e-22            0                     0    1.781312   \n",
       "560      1.166152e-20            0                     0    1.824266   \n",
       "561      3.802170e-20            0                     0    1.696157   \n",
       "562      3.928178e-20            0                     0    2.258709   \n",
       "563      9.902153e-20            0                     0    1.518192   \n",
       "564      2.159197e-19            0                     0    1.628456   \n",
       "565      3.180805e-19            0                     0    1.770540   \n",
       "\n",
       "     Combined Score                                              Genes  \n",
       "556       95.083310  ATF1;ZNF296;ZFYVE9;GMFG;EHMT1;TMEM97;FAM110A;P...  \n",
       "557       94.486361  ATF1;RB1;NCKAP1;TFRC;SCT;TMEM200A;RAPH1;EHMT1;...  \n",
       "558       91.058997  ATF1;EHMT1;FAM110A;ALKBH2;PSMD6;AKT2;FAM110B;Z...  \n",
       "559       95.825094  ATF1;RB1;RPL3;TFRC;RRP8;ELK3;FAM110A;ALKBH2;PS...  \n",
       "560       93.024722  TFRC;SCT;ARPC5L;GABPB1;FAM110A;MILR1;GPR174;AL...  \n",
       "561       84.178216  RB1;NCKAP1;TFRC;MYT1L;RAPH1;RRP8;TSEN54;PSMD9;...  \n",
       "562      111.675182  EIF4A2;RB1;ZNF296;RPL3;TFRC;SCT;ARPC5L;KEAP1;C...  \n",
       "563       73.456072  ATF1;MAPKBP1;ZNF296;TFRC;GMFG;TMEM97;FAM110A;I...  \n",
       "564       77.329804  ATF1;MAPKBP1;RPL3;TFRC;GMFG;UXS1;ARPC5L;RAPH1;...  \n",
       "565       83.204434  ATF1;RB1;NCKAP1;RPL3;TMEM200A;RAPH1;ADARB1;GAB...  "
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "enr.results[enr.results['Gene_set'] == 'ENCODE_TF_ChIP-seq_2015'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "04f5835a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T07:02:13.192144Z",
     "start_time": "2026-01-08T07:02:13.055067Z"
    }
   },
   "outputs": [],
   "source": [
    "nalm_etv6_runx1_only_peaks.as_df()[['Chromosome', 'Start', 'End']]\\\n",
    "    .to_csv('nalm_etv6_runx1_only_peaks.bed', sep='\\t', index=False, header=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "6207bf49",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-08T07:09:05.195650Z",
     "start_time": "2026-01-08T07:09:03.019509Z"
    }
   },
   "outputs": [],
   "source": [
    "nalm_runx1_only_peaks.as_df()[['Chromosome', 'Start', 'End']]\\\n",
    "    .to_csv('nalm_runx1_only_peaks.bed', sep='\\t', index=False, header=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3bf34599",
   "metadata": {},
   "source": [
    "#### Visualize ChIP signal across tracks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6a271322",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-02-04T23:55:46.146876Z",
     "start_time": "2026-02-04T23:55:46.138523Z"
    }
   },
   "outputs": [],
   "source": [
    "chrom, start, end = 'chr11', 47407800, 47409000\n",
    "n_bins = 50\n",
    "y_max = 30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ae0288c1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-02-04T23:55:46.868937Z",
     "start_time": "2026-02-04T23:55:46.150418Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Reh_HPA')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "reh_hpa_plus = pyBigWig.open(base_path + 'Wray_et_al/Reh_HPA/ERR5643715.plus.bw')\n",
    "reh_hpa_minus = pyBigWig.open(base_path + 'Wray_et_al/Reh_HPA/ERR5643715.minus.bw')\n",
    "\n",
    "x = np.linspace(start, end, n_bins)\n",
    "y_reh_hpa_plus = np.array(reh_hpa_plus.stats(chrom, start, end, nBins=n_bins, type=\"sum\"))\n",
    "y_reh_hpa_plus[y_reh_hpa_plus == None] = 0\n",
    "y_reh_hpa_minus = np.array(reh_hpa_minus.stats(chrom, start, end, nBins=n_bins, type=\"sum\"))\n",
    "y_reh_hpa_minus[y_reh_hpa_minus == None] = 0\n",
    "\n",
    "plt.figure(figsize=(8, 3), dpi=100)\n",
    "# plt.plot(x, y_reh_hpa_minus, color='lightblue')\n",
    "plt.fill_between(x, y_reh_hpa_minus.astype(float), color='pink')\n",
    "# plt.plot(x, y_reh_hpa_plus, color='tab:blue')\n",
    "plt.fill_between(x, y_reh_hpa_plus.astype(float), color='tab:red')\n",
    "plt.ylim([0, y_max])\n",
    "plt.title('Reh_HPA')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e612ff49",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-02-04T23:55:47.393440Z",
     "start_time": "2026-02-04T23:55:46.873385Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Reh_RUNX1_B')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "reh_runx1b_plus = pyBigWig.open(base_path + 'Wray_et_al/Reh_RUNX1_B/ERR5643726.plus.bw')\n",
    "reh_runx1b_minus = pyBigWig.open(base_path + 'Wray_et_al/Reh_RUNX1_B/ERR5643726.minus.bw')\n",
    "\n",
    "x = np.linspace(start, end, n_bins)\n",
    "y_reh_runx1b_plus = np.array(reh_runx1b_plus.stats(chrom, start, end, nBins=n_bins, type=\"sum\"))\n",
    "y_reh_runx1b_plus[y_reh_runx1b_plus == None] = 0\n",
    "y_reh_runx1b_minus = np.array(reh_runx1b_minus.stats(chrom, start, end, nBins=n_bins, type=\"sum\"))\n",
    "y_reh_runx1b_minus[y_reh_runx1b_minus == None] = 0\n",
    "\n",
    "plt.figure(figsize=(8, 3), dpi=100)\n",
    "plt.fill_between(x, y_reh_runx1b_minus.astype(float), color='lightblue')\n",
    "plt.fill_between(x, y_reh_runx1b_plus.astype(float), color='tab:blue')\n",
    "plt.ylim([0, y_max])\n",
    "plt.title('Reh_RUNX1_B')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e0102425",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-02-04T23:55:47.522900Z",
     "start_time": "2026-02-04T23:55:47.395292Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Reh_RUNX1_B - Reh_HPA')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "delta_reh_runx1b_plus_reh_hpa_plus = y_reh_runx1b_plus - y_reh_hpa_plus\n",
    "delta_reh_runx1b_minus_reh_hpa_minus = y_reh_runx1b_minus - y_reh_hpa_minus\n",
    "\n",
    "plt.figure(figsize=(8, 3), dpi=100)\n",
    "plt.fill_between(x, delta_reh_runx1b_minus_reh_hpa_minus.astype(float), color='lightgreen')\n",
    "plt.fill_between(x, delta_reh_runx1b_plus_reh_hpa_plus.astype(float), color='tab:green')\n",
    "plt.ylim([0, y_max])\n",
    "plt.title('Reh_RUNX1_B - Reh_HPA')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd1cea04",
   "metadata": {},
   "source": [
    "TODO:\n",
    "- Annotate peaks with nearest genes\n",
    "- GO enrichment\n",
    "- Differential binding\n",
    "- GSEA\n",
    "- GREAT\n",
    "- Compare fusion vs native: accessibility, expression"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "bpnet",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}