Notebook_ExtendedData_Fig7.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1c72f6ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import bioframe as bf\n",
    "import cooltools\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "plt.rcParams['pdf.fonttype'] = 42\n",
    "plt.rcParams['svg.fonttype'] = 'none'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c281a76",
   "metadata": {},
   "source": [
    "<h3> CTCF occupancy per IPG in HCT116 and H1-hESCs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "99ad64ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "conditions = ['H1', 'HCT']\n",
    "\n",
    "CTCF_paths = {\n",
    "    'H1': 'H1_CTCF_r1_ENCFF692RPA.bed.gz', \n",
    "    'HCT': 'HCT116_CTCF_r1r2_ENCFF463FGL.bed.gz', \n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "9cf5a795",
   "metadata": {},
   "outputs": [
    {
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       "<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>signalValue</th>\n",
       "      <th>pValue</th>\n",
       "      <th>qValue</th>\n",
       "      <th>peak</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr17</td>\n",
       "      <td>36148893</td>\n",
       "      <td>36149387</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>653.62460</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>5.11483</td>\n",
       "      <td>254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr10</td>\n",
       "      <td>100433702</td>\n",
       "      <td>100434245</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>591.45045</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>5.11483</td>\n",
       "      <td>263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr16</td>\n",
       "      <td>86563726</td>\n",
       "      <td>86564257</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>590.14796</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>5.11483</td>\n",
       "      <td>252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr17</td>\n",
       "      <td>80575271</td>\n",
       "      <td>80575754</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>589.18857</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>5.11483</td>\n",
       "      <td>249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr17</td>\n",
       "      <td>50200429</td>\n",
       "      <td>50201075</td>\n",
       "      <td>.</td>\n",
       "      <td>1000</td>\n",
       "      <td>.</td>\n",
       "      <td>582.07648</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>5.11483</td>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   chrom      start        end name  score strand  signalValue  pValue  \\\n",
       "0  chr17   36148893   36149387    .   1000      .    653.62460    -1.0   \n",
       "1  chr10  100433702  100434245    .   1000      .    591.45045    -1.0   \n",
       "2  chr16   86563726   86564257    .   1000      .    590.14796    -1.0   \n",
       "3  chr17   80575271   80575754    .   1000      .    589.18857    -1.0   \n",
       "4  chr17   50200429   50201075    .   1000      .    582.07648    -1.0   \n",
       "\n",
       "    qValue  peak  \n",
       "0  5.11483   254  \n",
       "1  5.11483   263  \n",
       "2  5.11483   252  \n",
       "3  5.11483   249  \n",
       "4  5.11483   325  "
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ctcf = {\n",
    "    cond: pd.read_table(\n",
    "        path, \n",
    "        sep='\\t', \n",
    "        header=None,\n",
    "        names=['chrom', 'start', 'end', 'name', 'score', 'strand', 'signalValue', 'pValue', 'qValue', 'peak']\n",
    "    ) for cond, path in CTCF_paths.items()\n",
    "}\n",
    "\n",
    "ctcf['HCT'].head()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "22056b22",
   "metadata": {},
   "outputs": [
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       "  <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>color</th>\n",
       "      <th>length</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>chr1</td>\n",
       "      <td>75750000</td>\n",
       "      <td>75800000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>chr1</td>\n",
       "      <td>75800000</td>\n",
       "      <td>76700000</td>\n",
       "      <td>B0</td>\n",
       "      <td>#5ebd3e</td>\n",
       "      <td>900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>chr1</td>\n",
       "      <td>76700000</td>\n",
       "      <td>76800000</td>\n",
       "      <td>B1</td>\n",
       "      <td>#009cdf</td>\n",
       "      <td>100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>chr1</td>\n",
       "      <td>76800000</td>\n",
       "      <td>77650000</td>\n",
       "      <td>B0</td>\n",
       "      <td>#5ebd3e</td>\n",
       "      <td>850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>chr1</td>\n",
       "      <td>77650000</td>\n",
       "      <td>77700000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>50000</td>\n",
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      "text/plain": [
       "    chrom     start       end name    color  length\n",
       "100  chr1  75750000  75800000   A2  #f78200   50000\n",
       "101  chr1  75800000  76700000   B0  #5ebd3e  900000\n",
       "102  chr1  76700000  76800000   B1  #009cdf  100000\n",
       "103  chr1  76800000  77650000   B0  #5ebd3e  850000\n",
       "104  chr1  77650000  77700000   A2  #f78200   50000"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Load IPGs\n",
    "hct_path = '/net/levsha/share/nezar/heterochrom2019/eigs_norm3/clusters_final'\n",
    "hct116_cluster = pd.read_table(f'{hct_path}/HCT116_Unsynchronized.hg38.50000.clusters.E1-E9.eignorm_sqrt.chr1-22.kmeans8_5.compressed.tsv', \n",
    "                          sep='\\t',)\n",
    "hct116_cluster['name'] = hct116_cluster['name'].apply(\n",
    "    {'A1': 'A1', \n",
    "     'A0': 'A2', \n",
    "     'B0': 'B0', \n",
    "     'B1': 'B1', \n",
    "     'B2': 'B4'}.get\n",
    ")\n",
    "hct116_cluster['length'] = hct116_cluster['end'] - hct116_cluster['start']\n",
    "hct116_cluster[100:105]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "3cc5e947",
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
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       "      <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",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>267933</td>\n",
       "      <td>268083</td>\n",
       "      <td>id-2</td>\n",
       "      <td>0</td>\n",
       "      <td>+</td>\n",
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       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>586087</td>\n",
       "      <td>586237</td>\n",
       "      <td>id-3</td>\n",
       "      <td>0</td>\n",
       "      <td>+</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>778825</td>\n",
       "      <td>778975</td>\n",
       "      <td>id-4</td>\n",
       "      <td>0</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>850485</td>\n",
       "      <td>850635</td>\n",
       "      <td>id-5</td>\n",
       "      <td>0</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>858078</td>\n",
       "      <td>858228</td>\n",
       "      <td>id-6</td>\n",
       "      <td>0</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109282</th>\n",
       "      <td>chrY</td>\n",
       "      <td>56838961</td>\n",
       "      <td>56839111</td>\n",
       "      <td>id-109338</td>\n",
       "      <td>0</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109283</th>\n",
       "      <td>chrY</td>\n",
       "      <td>56839441</td>\n",
       "      <td>56839591</td>\n",
       "      <td>id-109339</td>\n",
       "      <td>0</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109284</th>\n",
       "      <td>chrY</td>\n",
       "      <td>56842347</td>\n",
       "      <td>56842497</td>\n",
       "      <td>id-109340</td>\n",
       "      <td>0</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109285</th>\n",
       "      <td>chrY</td>\n",
       "      <td>56843607</td>\n",
       "      <td>56843757</td>\n",
       "      <td>id-109341</td>\n",
       "      <td>0</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109286</th>\n",
       "      <td>chrY</td>\n",
       "      <td>56855793</td>\n",
       "      <td>56855943</td>\n",
       "      <td>id-109342</td>\n",
       "      <td>0</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>109287 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom     start       end       name  score strand\n",
       "0       chr1    267933    268083       id-2      0      +\n",
       "1       chr1    586087    586237       id-3      0      +\n",
       "2       chr1    778825    778975       id-4      0      +\n",
       "3       chr1    850485    850635       id-5      0      -\n",
       "4       chr1    858078    858228       id-6      0      +\n",
       "...      ...       ...       ...        ...    ...    ...\n",
       "109282  chrY  56838961  56839111  id-109338      0      +\n",
       "109283  chrY  56839441  56839591  id-109339      0      +\n",
       "109284  chrY  56842347  56842497  id-109340      0      +\n",
       "109285  chrY  56843607  56843757  id-109341      0      +\n",
       "109286  chrY  56855793  56855943  id-109342      0      +\n",
       "\n",
       "[109287 rows x 6 columns]"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#List of all known CTCF peaks in various cell types\n",
    "ctcf_maurano = pd.read_table('/net/levsha/share/spracklin/HCT116_hic/bedfiles/CTCF_hg38_liftover_maurano_masterlist.bed',\n",
    "                           header=0,\n",
    "                           sep='\\t',\n",
    "                           names=['chrom','start','end','name','score','strand'])\n",
    "ctcf_maurano"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "38fc015b",
   "metadata": {},
   "outputs": [
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       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
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       "      <td>chr1</td>\n",
       "      <td>850000</td>\n",
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       "      <td>#e23838</td>\n",
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       "      <td>55</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1750000</td>\n",
       "      <td>2450000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>700000</td>\n",
       "      <td>41</td>\n",
       "      <td>32</td>\n",
       "      <td>93</td>\n",
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       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>2800000</td>\n",
       "      <td>3800000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>1000000</td>\n",
       "      <td>45</td>\n",
       "      <td>42</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3800000</td>\n",
       "      <td>4350000</td>\n",
       "      <td>B1</td>\n",
       "      <td>#009cdf</td>\n",
       "      <td>550000</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4350000</td>\n",
       "      <td>5350000</td>\n",
       "      <td>B4</td>\n",
       "      <td>#973999</td>\n",
       "      <td>1000000</td>\n",
       "      <td>29</td>\n",
       "      <td>8</td>\n",
       "      <td>23</td>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4179</th>\n",
       "      <td>chr22</td>\n",
       "      <td>47450000</td>\n",
       "      <td>49050000</td>\n",
       "      <td>B1</td>\n",
       "      <td>#009cdf</td>\n",
       "      <td>1600000</td>\n",
       "      <td>42</td>\n",
       "      <td>24</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4180</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49050000</td>\n",
       "      <td>49150000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>100000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4181</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49150000</td>\n",
       "      <td>49250000</td>\n",
       "      <td>B1</td>\n",
       "      <td>#009cdf</td>\n",
       "      <td>100000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4182</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49250000</td>\n",
       "      <td>49800000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>550000</td>\n",
       "      <td>16</td>\n",
       "      <td>14</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4183</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49800000</td>\n",
       "      <td>50750000</td>\n",
       "      <td>A1</td>\n",
       "      <td>#e23838</td>\n",
       "      <td>950000</td>\n",
       "      <td>58</td>\n",
       "      <td>56</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4184 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      chrom     start       end name    color   length  count_H1  count_HCT  \\\n",
       "0      chr1    850000   1700000   A1  #e23838   850000        59         55   \n",
       "1      chr1   1750000   2450000   A2  #f78200   700000        41         32   \n",
       "2      chr1   2800000   3800000   A2  #f78200  1000000        45         42   \n",
       "3      chr1   3800000   4350000   B1  #009cdf   550000        12          9   \n",
       "4      chr1   4350000   5350000   B4  #973999  1000000        29          8   \n",
       "...     ...       ...       ...  ...      ...      ...       ...        ...   \n",
       "4179  chr22  47450000  49050000   B1  #009cdf  1600000        42         24   \n",
       "4180  chr22  49050000  49150000   A2  #f78200   100000         0          0   \n",
       "4181  chr22  49150000  49250000   B1  #009cdf   100000         1          1   \n",
       "4182  chr22  49250000  49800000   A2  #f78200   550000        16         14   \n",
       "4183  chr22  49800000  50750000   A1  #e23838   950000        58         56   \n",
       "\n",
       "      count_maurano  \n",
       "0                99  \n",
       "1                93  \n",
       "2                83  \n",
       "3                27  \n",
       "4                23  \n",
       "...             ...  \n",
       "4179             47  \n",
       "4180              0  \n",
       "4181              3  \n",
       "4182             21  \n",
       "4183             93  \n",
       "\n",
       "[4184 rows x 9 columns]"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# overlap CTCF bedfile with IPGs\n",
    "ov = bf.count_overlaps(hct116_cluster, ctcf['H1'], suffixes=('','_')).rename(columns={\n",
    "    'count': 'count_H1'\n",
    "})\n",
    "ov = bf.count_overlaps(ov, ctcf['HCT'], suffixes=('','_')).rename(columns={\n",
    "    'count': 'count_HCT'\n",
    "})\n",
    "ov = bf.count_overlaps(ov, ctcf_maurano, suffixes=('','_')).rename(columns={\n",
    "    'count': 'count_maurano'\n",
    "})\n",
    "\n",
    "ov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "210b27d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        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>color</th>\n",
       "      <th>length</th>\n",
       "      <th>count_H1</th>\n",
       "      <th>count_HCT</th>\n",
       "      <th>count_maurano</th>\n",
       "      <th>H1_occupied</th>\n",
       "      <th>HCT116_occupied</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>850000</td>\n",
       "      <td>1700000</td>\n",
       "      <td>A1</td>\n",
       "      <td>#e23838</td>\n",
       "      <td>850000</td>\n",
       "      <td>59</td>\n",
       "      <td>55</td>\n",
       "      <td>99</td>\n",
       "      <td>0.595960</td>\n",
       "      <td>0.555556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1750000</td>\n",
       "      <td>2450000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>700000</td>\n",
       "      <td>41</td>\n",
       "      <td>32</td>\n",
       "      <td>93</td>\n",
       "      <td>0.440860</td>\n",
       "      <td>0.344086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>2800000</td>\n",
       "      <td>3800000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>1000000</td>\n",
       "      <td>45</td>\n",
       "      <td>42</td>\n",
       "      <td>83</td>\n",
       "      <td>0.542169</td>\n",
       "      <td>0.506024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3800000</td>\n",
       "      <td>4350000</td>\n",
       "      <td>B1</td>\n",
       "      <td>#009cdf</td>\n",
       "      <td>550000</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>27</td>\n",
       "      <td>0.444444</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4350000</td>\n",
       "      <td>5350000</td>\n",
       "      <td>B4</td>\n",
       "      <td>#973999</td>\n",
       "      <td>1000000</td>\n",
       "      <td>29</td>\n",
       "      <td>8</td>\n",
       "      <td>23</td>\n",
       "      <td>1.260870</td>\n",
       "      <td>0.347826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4179</th>\n",
       "      <td>chr22</td>\n",
       "      <td>47450000</td>\n",
       "      <td>49050000</td>\n",
       "      <td>B1</td>\n",
       "      <td>#009cdf</td>\n",
       "      <td>1600000</td>\n",
       "      <td>42</td>\n",
       "      <td>24</td>\n",
       "      <td>47</td>\n",
       "      <td>0.893617</td>\n",
       "      <td>0.510638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4180</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49050000</td>\n",
       "      <td>49150000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>100000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4181</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49150000</td>\n",
       "      <td>49250000</td>\n",
       "      <td>B1</td>\n",
       "      <td>#009cdf</td>\n",
       "      <td>100000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4182</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49250000</td>\n",
       "      <td>49800000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>550000</td>\n",
       "      <td>16</td>\n",
       "      <td>14</td>\n",
       "      <td>21</td>\n",
       "      <td>0.761905</td>\n",
       "      <td>0.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4183</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49800000</td>\n",
       "      <td>50750000</td>\n",
       "      <td>A1</td>\n",
       "      <td>#e23838</td>\n",
       "      <td>950000</td>\n",
       "      <td>58</td>\n",
       "      <td>56</td>\n",
       "      <td>93</td>\n",
       "      <td>0.623656</td>\n",
       "      <td>0.602151</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4184 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      chrom     start       end name    color   length  count_H1  count_HCT  \\\n",
       "0      chr1    850000   1700000   A1  #e23838   850000        59         55   \n",
       "1      chr1   1750000   2450000   A2  #f78200   700000        41         32   \n",
       "2      chr1   2800000   3800000   A2  #f78200  1000000        45         42   \n",
       "3      chr1   3800000   4350000   B1  #009cdf   550000        12          9   \n",
       "4      chr1   4350000   5350000   B4  #973999  1000000        29          8   \n",
       "...     ...       ...       ...  ...      ...      ...       ...        ...   \n",
       "4179  chr22  47450000  49050000   B1  #009cdf  1600000        42         24   \n",
       "4180  chr22  49050000  49150000   A2  #f78200   100000         0          0   \n",
       "4181  chr22  49150000  49250000   B1  #009cdf   100000         1          1   \n",
       "4182  chr22  49250000  49800000   A2  #f78200   550000        16         14   \n",
       "4183  chr22  49800000  50750000   A1  #e23838   950000        58         56   \n",
       "\n",
       "      count_maurano  H1_occupied  HCT116_occupied  \n",
       "0                99     0.595960         0.555556  \n",
       "1                93     0.440860         0.344086  \n",
       "2                83     0.542169         0.506024  \n",
       "3                27     0.444444         0.333333  \n",
       "4                23     1.260870         0.347826  \n",
       "...             ...          ...              ...  \n",
       "4179             47     0.893617         0.510638  \n",
       "4180              0          NaN              NaN  \n",
       "4181              3     0.333333         0.333333  \n",
       "4182             21     0.761905         0.666667  \n",
       "4183             93     0.623656         0.602151  \n",
       "\n",
       "[4184 rows x 11 columns]"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ov['H1_occupied'] = ov['count_H1'] / ov['count_maurano']\n",
    "ov['HCT116_occupied'] = ov['count_HCT'] / ov['count_maurano']\n",
    "\n",
    "ov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "88c9022f",
   "metadata": {},
   "outputs": [],
   "source": [
    "ov_ctcf = ov\n",
    "ov_ctcf.to_excel(excel_writer='sourcedata_ED_fig7.xlsx', sheet_name='7e_ctcf', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "da768de8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>variable</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>850000</td>\n",
       "      <td>1700000</td>\n",
       "      <td>A1</td>\n",
       "      <td>HCT116_occupied</td>\n",
       "      <td>0.555556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1750000</td>\n",
       "      <td>2450000</td>\n",
       "      <td>A2</td>\n",
       "      <td>HCT116_occupied</td>\n",
       "      <td>0.344086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>2800000</td>\n",
       "      <td>3800000</td>\n",
       "      <td>A2</td>\n",
       "      <td>HCT116_occupied</td>\n",
       "      <td>0.506024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3800000</td>\n",
       "      <td>4350000</td>\n",
       "      <td>B1</td>\n",
       "      <td>HCT116_occupied</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4350000</td>\n",
       "      <td>5350000</td>\n",
       "      <td>B4</td>\n",
       "      <td>HCT116_occupied</td>\n",
       "      <td>0.347826</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>8362</th>\n",
       "      <td>chr22</td>\n",
       "      <td>43750000</td>\n",
       "      <td>47450000</td>\n",
       "      <td>A2</td>\n",
       "      <td>H1_occupied</td>\n",
       "      <td>0.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8363</th>\n",
       "      <td>chr22</td>\n",
       "      <td>47450000</td>\n",
       "      <td>49050000</td>\n",
       "      <td>B1</td>\n",
       "      <td>H1_occupied</td>\n",
       "      <td>0.893617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8365</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49150000</td>\n",
       "      <td>49250000</td>\n",
       "      <td>B1</td>\n",
       "      <td>H1_occupied</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8366</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49250000</td>\n",
       "      <td>49800000</td>\n",
       "      <td>A2</td>\n",
       "      <td>H1_occupied</td>\n",
       "      <td>0.761905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8367</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49800000</td>\n",
       "      <td>50750000</td>\n",
       "      <td>A1</td>\n",
       "      <td>H1_occupied</td>\n",
       "      <td>0.623656</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7796 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      chrom     start       end name         variable     value\n",
       "0      chr1    850000   1700000   A1  HCT116_occupied  0.555556\n",
       "1      chr1   1750000   2450000   A2  HCT116_occupied  0.344086\n",
       "2      chr1   2800000   3800000   A2  HCT116_occupied  0.506024\n",
       "3      chr1   3800000   4350000   B1  HCT116_occupied  0.333333\n",
       "4      chr1   4350000   5350000   B4  HCT116_occupied  0.347826\n",
       "...     ...       ...       ...  ...              ...       ...\n",
       "8362  chr22  43750000  47450000   A2      H1_occupied  0.600000\n",
       "8363  chr22  47450000  49050000   B1      H1_occupied  0.893617\n",
       "8365  chr22  49150000  49250000   B1      H1_occupied  0.333333\n",
       "8366  chr22  49250000  49800000   A2      H1_occupied  0.761905\n",
       "8367  chr22  49800000  50750000   A1      H1_occupied  0.623656\n",
       "\n",
       "[7796 rows x 6 columns]"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Create tidy dataframe for seaborn\n",
    "df_melt = pd.melt(ov, id_vars=['chrom','start','end','name'], value_vars=['HCT116_occupied','H1_occupied'])\n",
    "df_melt.replace([np.inf, -np.inf], np.nan, inplace=True) #divide by 0 errors\n",
    "df_melt.dropna(inplace=True) \n",
    "df_melt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "7183864a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.barplot(x=\"name\", y='value', data=df_nan, hue='variable', order=['A1','A2','B0','B1','B4'])\n",
    "#ax = sns.stripplot(size=1, x=\"name\", y='value', data=df_melt, hue='variable', dodge=True, order=['A1','A0','B0','B1','B2'])\n",
    "plt.savefig('Density_CTCF_h1_hct.pdf')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6dc5ae5",
   "metadata": {},
   "source": [
    "<h2> Insulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "657f616d",
   "metadata": {},
   "outputs": [],
   "source": [
    "conditions = ['H1', 'HCT']\n",
    "boun_paths = {\n",
    "    'H1': 'H1-hESC.boundaries.4DNFIGDQ72ID.bed.gz', \n",
    "    'HCT': 'HCT116.boundaries.4DNFIBKY9EG9.bed.gz', \n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "50401c20",
   "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>strength</th>\n",
       "      <th>ins_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>910000</td>\n",
       "      <td>915000</td>\n",
       "      <td>Strong</td>\n",
       "      <td>1.025563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1065000</td>\n",
       "      <td>1070000</td>\n",
       "      <td>Weak</td>\n",
       "      <td>0.204139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1315000</td>\n",
       "      <td>1320000</td>\n",
       "      <td>Strong</td>\n",
       "      <td>0.586819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1630000</td>\n",
       "      <td>1635000</td>\n",
       "      <td>Strong</td>\n",
       "      <td>0.891663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1770000</td>\n",
       "      <td>1775000</td>\n",
       "      <td>Weak</td>\n",
       "      <td>0.434202</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  chrom    start      end strength  ins_score\n",
       "0  chr1   910000   915000   Strong   1.025563\n",
       "1  chr1  1065000  1070000     Weak   0.204139\n",
       "2  chr1  1315000  1320000   Strong   0.586819\n",
       "3  chr1  1630000  1635000   Strong   0.891663\n",
       "4  chr1  1770000  1775000     Weak   0.434202"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boun = {\n",
    "    cond: pd.read_table(\n",
    "        path, \n",
    "        sep='\\t', \n",
    "        header=None,\n",
    "        names=['chrom', 'start','end','strength','ins_score']\n",
    "    ) for cond, path in boun_paths.items()\n",
    "}\n",
    "\n",
    "boun['H1'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "1e1dd3dd",
   "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>strength</th>\n",
       "      <th>ins_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1095000</td>\n",
       "      <td>1100000</td>\n",
       "      <td>Strong</td>\n",
       "      <td>0.612423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1275000</td>\n",
       "      <td>1280000</td>\n",
       "      <td>Weak</td>\n",
       "      <td>0.384464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1620000</td>\n",
       "      <td>1625000</td>\n",
       "      <td>Weak</td>\n",
       "      <td>0.375042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1755000</td>\n",
       "      <td>1760000</td>\n",
       "      <td>Strong</td>\n",
       "      <td>0.519699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1910000</td>\n",
       "      <td>1915000</td>\n",
       "      <td>Strong</td>\n",
       "      <td>1.314856</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  chrom    start      end strength  ins_score\n",
       "0  chr1  1095000  1100000   Strong   0.612423\n",
       "1  chr1  1275000  1280000     Weak   0.384464\n",
       "2  chr1  1620000  1625000     Weak   0.375042\n",
       "3  chr1  1755000  1760000   Strong   0.519699\n",
       "4  chr1  1910000  1915000   Strong   1.314856"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boun['HCT'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "093000f4",
   "metadata": {},
   "source": [
    "<h4> Calculate density of insulating loci (per Mb) for each domain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "4a18e66e",
   "metadata": {},
   "outputs": [],
   "source": [
    "ov = bf.count_overlaps(hct116_cluster, boun['H1'], suffixes=('','_')).rename(columns={\n",
    "    'count': 'count_H1'\n",
    "})\n",
    "ov = bf.count_overlaps(ov, boun['HCT'], suffixes=('','_')).rename(columns={\n",
    "    'count': 'count_HCT'\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "c46b4fd8",
   "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>color</th>\n",
       "      <th>length</th>\n",
       "      <th>count_H1</th>\n",
       "      <th>count_HCT</th>\n",
       "      <th>density_H1</th>\n",
       "      <th>density_HCT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>850000</td>\n",
       "      <td>1700000</td>\n",
       "      <td>A1</td>\n",
       "      <td>#e23838</td>\n",
       "      <td>850000</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4.705882</td>\n",
       "      <td>3.529412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1750000</td>\n",
       "      <td>2450000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>700000</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>7.142857</td>\n",
       "      <td>5.714286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>2800000</td>\n",
       "      <td>3800000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>1000000</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3800000</td>\n",
       "      <td>4350000</td>\n",
       "      <td>B1</td>\n",
       "      <td>#009cdf</td>\n",
       "      <td>550000</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3.636364</td>\n",
       "      <td>3.636364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4350000</td>\n",
       "      <td>5350000</td>\n",
       "      <td>B4</td>\n",
       "      <td>#973999</td>\n",
       "      <td>1000000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.000000</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>4179</th>\n",
       "      <td>chr22</td>\n",
       "      <td>47450000</td>\n",
       "      <td>49050000</td>\n",
       "      <td>B1</td>\n",
       "      <td>#009cdf</td>\n",
       "      <td>1600000</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>3.750000</td>\n",
       "      <td>1.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4180</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49050000</td>\n",
       "      <td>49150000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>100000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4181</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49150000</td>\n",
       "      <td>49250000</td>\n",
       "      <td>B1</td>\n",
       "      <td>#009cdf</td>\n",
       "      <td>100000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4182</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49250000</td>\n",
       "      <td>49800000</td>\n",
       "      <td>A2</td>\n",
       "      <td>#f78200</td>\n",
       "      <td>550000</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3.636364</td>\n",
       "      <td>3.636364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4183</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49800000</td>\n",
       "      <td>50750000</td>\n",
       "      <td>A1</td>\n",
       "      <td>#e23838</td>\n",
       "      <td>950000</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>6.315789</td>\n",
       "      <td>4.210526</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4184 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      chrom     start       end name    color   length  count_H1  count_HCT  \\\n",
       "0      chr1    850000   1700000   A1  #e23838   850000         4          3   \n",
       "1      chr1   1750000   2450000   A2  #f78200   700000         5          4   \n",
       "2      chr1   2800000   3800000   A2  #f78200  1000000         2          2   \n",
       "3      chr1   3800000   4350000   B1  #009cdf   550000         2          2   \n",
       "4      chr1   4350000   5350000   B4  #973999  1000000         5          0   \n",
       "...     ...       ...       ...  ...      ...      ...       ...        ...   \n",
       "4179  chr22  47450000  49050000   B1  #009cdf  1600000         6          2   \n",
       "4180  chr22  49050000  49150000   A2  #f78200   100000         0          0   \n",
       "4181  chr22  49150000  49250000   B1  #009cdf   100000         0          0   \n",
       "4182  chr22  49250000  49800000   A2  #f78200   550000         2          2   \n",
       "4183  chr22  49800000  50750000   A1  #e23838   950000         6          4   \n",
       "\n",
       "      density_H1  density_HCT  \n",
       "0       4.705882     3.529412  \n",
       "1       7.142857     5.714286  \n",
       "2       2.000000     2.000000  \n",
       "3       3.636364     3.636364  \n",
       "4       5.000000     0.000000  \n",
       "...          ...          ...  \n",
       "4179    3.750000     1.250000  \n",
       "4180    0.000000     0.000000  \n",
       "4181    0.000000     0.000000  \n",
       "4182    3.636364     3.636364  \n",
       "4183    6.315789     4.210526  \n",
       "\n",
       "[4184 rows x 10 columns]"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ov['density_H1'] = ov['count_H1'] / (ov['length']) * 1_000_000\n",
    "ov['density_HCT'] = ov['count_HCT'] / (ov['length']) * 1_000_000\n",
    "ov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "6f088437",
   "metadata": {},
   "outputs": [],
   "source": [
    "ov.to_excel('sourcedata_ED_fig7.xlsx', sheet_name='7e', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "c9ecfa38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>variable</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1</td>\n",
       "      <td>850000</td>\n",
       "      <td>1700000</td>\n",
       "      <td>A1</td>\n",
       "      <td>density_HCT</td>\n",
       "      <td>3.529412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1</td>\n",
       "      <td>1750000</td>\n",
       "      <td>2450000</td>\n",
       "      <td>A2</td>\n",
       "      <td>density_HCT</td>\n",
       "      <td>5.714286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1</td>\n",
       "      <td>2800000</td>\n",
       "      <td>3800000</td>\n",
       "      <td>A2</td>\n",
       "      <td>density_HCT</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr1</td>\n",
       "      <td>3800000</td>\n",
       "      <td>4350000</td>\n",
       "      <td>B1</td>\n",
       "      <td>density_HCT</td>\n",
       "      <td>3.636364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>4350000</td>\n",
       "      <td>5350000</td>\n",
       "      <td>B4</td>\n",
       "      <td>density_HCT</td>\n",
       "      <td>0.000000</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>8363</th>\n",
       "      <td>chr22</td>\n",
       "      <td>47450000</td>\n",
       "      <td>49050000</td>\n",
       "      <td>B1</td>\n",
       "      <td>density_H1</td>\n",
       "      <td>3.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8364</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49050000</td>\n",
       "      <td>49150000</td>\n",
       "      <td>A2</td>\n",
       "      <td>density_H1</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8365</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49150000</td>\n",
       "      <td>49250000</td>\n",
       "      <td>B1</td>\n",
       "      <td>density_H1</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8366</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49250000</td>\n",
       "      <td>49800000</td>\n",
       "      <td>A2</td>\n",
       "      <td>density_H1</td>\n",
       "      <td>3.636364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8367</th>\n",
       "      <td>chr22</td>\n",
       "      <td>49800000</td>\n",
       "      <td>50750000</td>\n",
       "      <td>A1</td>\n",
       "      <td>density_H1</td>\n",
       "      <td>6.315789</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8368 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      chrom     start       end name     variable     value\n",
       "0      chr1    850000   1700000   A1  density_HCT  3.529412\n",
       "1      chr1   1750000   2450000   A2  density_HCT  5.714286\n",
       "2      chr1   2800000   3800000   A2  density_HCT  2.000000\n",
       "3      chr1   3800000   4350000   B1  density_HCT  3.636364\n",
       "4      chr1   4350000   5350000   B4  density_HCT  0.000000\n",
       "...     ...       ...       ...  ...          ...       ...\n",
       "8363  chr22  47450000  49050000   B1   density_H1  3.750000\n",
       "8364  chr22  49050000  49150000   A2   density_H1  0.000000\n",
       "8365  chr22  49150000  49250000   B1   density_H1  0.000000\n",
       "8366  chr22  49250000  49800000   A2   density_H1  3.636364\n",
       "8367  chr22  49800000  50750000   A1   density_H1  6.315789\n",
       "\n",
       "[8368 rows x 6 columns]"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ov_melt = pd.melt(\n",
    "    ov, \n",
    "    id_vars=['chrom','start','end','name'], \n",
    "    value_vars=['density_HCT','density_H1']\n",
    ")\n",
    "ov_melt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "ef06bd61",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.barplot(x=\"name\", y='value', data=ov_melt, hue='variable', order=['A1','A2','B0','B1','B4'])\n",
    "\n",
    "plt.savefig('Density_ins_h1_hct.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "9ba306cd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name\n",
       "A1     310.0\n",
       "A2    1448.0\n",
       "B0     711.0\n",
       "B1    1333.0\n",
       "B4     382.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ov_melt.groupby('name').size() / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "69b14698",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4184.0"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ov_melt.groupby('name').size().sum() / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bdb54e1a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3dd80154",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}