notebooks/Notebook.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "93be1e01-bcb9-43a5-b55d-3343f4267619",
   "metadata": {},
   "outputs": [],
   "source": [
    "import urllib\n",
    "import gzip\n",
    "from io import BytesIO\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.gridspec as gridspec\n",
    "\n",
    "from gtfparse import read_gtf\n",
    "import pyBigWig\n",
    "\n",
    "import raesymatto.visualizations\n",
    "\n",
    "%matplotlib inline\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "mpl.rcParams.update({'axes.linewidth': 0.25,\n",
    "                     'xtick.major.size': 2,\n",
    "                     'xtick.major.width': 0.25,\n",
    "                     'ytick.major.size': 2,\n",
    "                     'ytick.major.width': 0.25,\n",
    "                     'pdf.fonttype': 42,\n",
    "                     'font.size': 7,\n",
    "                     'font.sans-serif': 'Arial'})\n",
    "\n",
    "%config InlineBackend.figure_format = 'retina'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e38a59d-1c3a-4edb-9896-67e02907ddc8",
   "metadata": {},
   "source": [
    "### Read data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3f5663bc-1a8d-4864-aec7-06245151db2a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/Caskroom/miniforge/base/envs/python39/lib/python3.9/site-packages/gtfparse/read_gtf.py:151: FutureWarning: The error_bad_lines argument has been deprecated and will be removed in a future version.\n",
      "\n",
      "\n",
      "  result = parse_gtf(\n",
      "/opt/homebrew/Caskroom/miniforge/base/envs/python39/lib/python3.9/site-packages/gtfparse/read_gtf.py:151: FutureWarning: The warn_bad_lines argument has been deprecated and will be removed in a future version.\n",
      "\n",
      "\n",
      "  result = parse_gtf(\n",
      "INFO:root:Extracted GTF attributes: ['gene_id', 'transcript_id', 'gene_name', 'exon_number', 'exon_id']\n"
     ]
    }
   ],
   "source": [
    "# conservation (bigWig)\n",
    "cons_bw = pyBigWig.open('https://hgdownload.soe.ucsc.edu/goldenPath/mm10/phyloP60way/mm10.60way.phyloP60way.bw')\n",
    "\n",
    "# ATAC-seq (bigWig)\n",
    "wt_imm_bw = pyBigWig.open('https://ftp.ncbi.nlm.nih.gov/geo/samples/GSM4486nnn/GSM4486874/suppl/GSM4486874%5FWT%5FImCD4%5FATAC%5FCPM%5FRep1%2Ebw')\n",
    "thpok_ko_bw = pyBigWig.open('https://ftp.ncbi.nlm.nih.gov/geo/samples/GSM4486nnn/GSM4486877/suppl/GSM4486877%5FKO%5FImCD4%5FATAC%5FCPM%5FRep1%2Ebw')\n",
    "\n",
    "# GATA3 motifs (BED)\n",
    "gata3_bed = pd.read_csv('http://expdata.cmmt.ubc.ca/JASPAR/downloads/UCSC_tracks/2022/mm10/MA0037.4.tsv.gz',sep='\\t',compression='gzip',header=None)\n",
    "\n",
    "# GATA3 binding sites (BED)\n",
    "gata3_bs_bed = pd.read_csv('https://ftp.ncbi.nlm.nih.gov/geo/samples/GSM2931nnn/GSM2931810/suppl/GSM2931810%5FTh2%5FGATA3%5Fpeaks%2E0%2EFNG%2Egenes%2Etxt%2Egz',\n",
    "                           compression='gzip',sep='\\t',comment='#',header=None,usecols=(0,1,2,3,7),names=(0,1,2,3,4))\n",
    "\n",
    "# Gene definitions (GTF)\n",
    "with urllib.request.urlopen('https://hgdownload.soe.ucsc.edu/goldenPath/mm10/bigZips/genes/mm10.refGene.gtf.gz') as f:\n",
    "    genes_gtf = read_gtf(BytesIO(gzip.decompress(f.read())))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e80fc35-b46d-40fa-a0e5-c2411f691e48",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Define the region of interest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "21189416-616f-42dd-811b-3de025bd43a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "chromosome,start,end = 'chr3',89373714,89397292"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd436631-0008-4fc7-96ef-0fd03a9a5369",
   "metadata": {},
   "source": [
    "### Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5f78ee6f-6898-4447-a5ef-df8f8078093f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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98MAD2rVrl+6++25J0quvvtrne+655x5dcsklkqRnnnlG3/zmN/XII4/oxhtv1Jlnnqn/+q//kiRt3rxZV111ld56662U9z/44IO699579dJLL2n69Om9zqOmpkaXXnqpvvvd7+qqq65SIBDQFVdcofvvv1+nnXaaJOl3v/udPvGJT+jJJ588rGUAAACAMdLSosaGhgGDH2OM6uvqVOD3J5p3HRKLx3Wgrk7LRrucwGTW1aXm6uo+X960dq2OuvBCuVw0nJnI4vG49u3bpz179sjlcumYY45xXmtra+sZ/AxGOCzl5k7a4Ic1dhTs2bNHl156qU466STdeeedvY7T2tqq/Px8NTc3a+vWrfqnf/on57WVK1fq8ssv1yOPPOIM+8Mf/qAf/vCHevHFF/sMfaqrq3XBBRfoBz/4ga666ipJ0lNPPaVzzz3XCX0k6dOf/rSam5tV0UsVRgAAAExAXq/i/XTsnKyrs1MNNTUy8XjKRYrhcdRAv+JPP62mfjpxbq+u1sEtW8awRBiKtrY2GWP06quvauPGjWpqalIgEEgZp6OjQ+Fw+P0B4bDU2TnwxBsbJUmmvn4kizxmqPEzCoLBoB599FHFYjHNmzfPCX+++tWv6u6775bb7dasWbN0zz33aP/+/Vq8eHGPaSxatEhVVVVauHChXn/9ddXU1Ki1tVXRaLTP+V5zzTXKzc1V46GVUlKf01+4cKEzfQAAAExwxvTa4WxvYvG4YvF4j6DHtLePQsGA9FC5YYPat23rfzuLxRT3+YY+cTuAtazhFQ4D8nq9euihh7Rw4ULV1NQ44U5nt1CnR/8+Xm8i/BlIc7M0bZrie/bI7/crNzd3pIo+Jgh+RsFxxx2nrKwsSZLH8/4iTm7qZYvFYqqqquoxjT179jhV0mbOnKkXXnhB999/v66//no988wzvVYv/M1vfqPp06frrLPO0qpVq7Rs2TLNnj1b7777bo9x9+7dm9JHEAAAACau5uZmlTc0DOk91S+9pHAw+P6ApJuDAFK9/rvfKdDSMuB4e/bu1YKzzhraxBsaEk+Oon+gUeH3+/Xiiy9KUo9WLfv379fZZ5+trq4uFRcXa1f3x7YPttP7aFSqr1csFtP+/ft13HHHpb4ej0utrVJp6XA/xqiiqdcosIaQ5M6ZM0eLFy/WT3/6U2fYhg0b9MQTT+gjH/mIJOmoo45Sdna2vvjFLyozM1P/8R//0eu0jjvuOM2dO1c/+MEP9NGPflSBQEBXXnmlXnjhhZTw5/7771dpaakWLVo0zE+II4ExRl1dXQqHw2oY4okmAAAYWb5t2xSNxYb0nk0bNiiY9Njivp5wAxzpwuGwYt2aBPWlaetW+YZa66e8XHr7bamyMhEAYUS98cYbKa1eksViMZWXl2vTpk166aWXdDC5KV88PriOnW2NjVI8rm3vvqsDe/bo4DPPOM3E4o8/rnf++ldFIhFV99NP1Hihxs8E8Pvf/15f+cpXdNppp8ntdqukpESPPvqoiouLe4z7m9/8RieeeKLOPvtsnXfeeb1O75prrtGzzz6rm2++Wb/97W/1xBNP6JZbblFLS4ui0aiOP/54Pfjgg6P8qTDZNTY2qrKyUps3b9bMmTN1+eWXj3eRAAA4YpnBNEUYwPYDB3TcwKMd8To7O5Wfn6/Ozs5ez8eRfiorKxUeZB9aXr9fr7/+ui644IKU1h09tLQkfurqpN27E8Oef166/nppkjUTmsii0WhqmNOLzs5O7d+/v2ermZYWaaghXjyuzt279dKWLcrx+XRWc7OyS0rkqazUrp07NbuyUlvWrtW8z352iJ9kdFmToVfqO++80/TVSTKA0bFu3Tpt2rRJ8XhcHo9Hl1xyiWbNmjXexQJ6tb52fZ+vnTTrpDEsCQCMjopf/lIvvP76YU2jMDdXH//ud6UZM0aoVOmlvr5e+/fvV2VlpZYtW6bt27frvPPO05w5c8a7aBhlb7/8srb87neDq43jckknnKCFK1bovPPO6zv8efPNRODTPVA6/njp9NMPv9BQPB5XeXm51qxZ0/PFUCjxOytLLperZ41HY6TD3KfasjMyVJybq/quLmWXlKi4sFBX/Nu/jci0ezGsjqJo6gWgh5aWFjU0NDg7yGg06oRAAAD0p62tTbFDF08vvvhin9XvMQRer2oGuKM9GCYeTzRV8PsTF6WBQKLfCigej2v9+vXatm2bvF6v1q1bp0AgoGeffVatra3jXTyMsGg0qvakzs6rtmwZfBOseFzauVMVu3frmWee6Xu88nIn9LE7XN904ICCg2xShoFVVVUlmlX5fNLevYkaPH5/Yr9WUyOtWycFAr1fw7S1jVg5gpGI6js6pHhcwZYWtXZ2pqxfEwHBD4AUb7/9tp555hnV1NSkDD948KDefvvtcSoVAGAyeO+99/TQQw+psbFR1dXVqqiocDrcxGHwetUyiE5nB2KkxMXR9u3Stm3Spk3S+r5rTB5JduzY0ePcR0oEQvWT9PHN6F04HNbDDz/sdPLb3Nw89D57AgGpoUF1dXVq7qtz4KSwoamrS7954w29W1GhbS+9JO3fnwiFmpqkl16Skjthx6C1tLSosrIy0alybW0ibGtoSOzfDh5MhHlNTb2/eRT74Qn7/aoqLx+16Q8HwQ+AFAcPHpTf708crDo7Ewe2Qwejbdu2qaOjY5xLCPTtYM1Bbd+xXZOhGTOQjvyHOhJ+7bXX1NraKmOM/H6/amtrnUfrYoh8PmnbNo3EXs0Yk3h0sd3fyNatMps3v98k4giSfD7T3t6uN+0aUL0cP6jxnF7WrVunjo4O7dy5U62trfL5fIoOJ3jp7JTica1bt67na+XlTg2ipq4uvb53r3NusqGyUjufekqNDz+s8DPPSPv2STt3HpHb4XD5Oju1b9cu7d2zJ3GdYtfKi0SkAwecDpclJWoA9aav4SMhEFBjL0/uHk8EPwAcsVhMUbvKd22ttGePtGOHtGtX4uDl96t8gqXXOLLV1tam/N/V2aXOjk7t3r1bAapSA2OitrZW+/fv14EDB9R2qOp8Z2enDhw4IClx0fzkk09q79692rp1q3bs2DGexZ18QiF1bt+uzhHYpwUiEdU3NEh+v97ev1/+cFgPr1+v8r/+dQQKOnm0trbq9aS+PZzHP1dVJWpDdQsBeqsJhMlp79692rZtmyQpEomotrY2EewN5wm2LS1SZaUOVFWpvLxcdXV1kqRAIKD2117T7ro6tfp8emX3brV1q1G0cfNmvfjii9pfWanK5mYF33xTam/XI488okgkovr6+vfPyeHYuXOn2ltbtfevf9VLjz6qzs2bE09K6+/GdHNzSu0rSYnaPqMc6JoJ1kSUp3oBcNTW1qqzszPR5rW9PbWX+3fekVwuxU85ZdzKByQzxmjdunW64oorFDdxNTY2avfu3Yq3tqi+tU2eiy7UUcevHO9i4ghh92kTi8WUmZk5zqUZO+3t7Xrttdfkdrt79GdgXwTZ1q1bp4yMDJWWluqYY44Zw1JOYpGIfI2Neq28XMFBPnGoP/F4XL5wWG/u26dtNTUqb2hQMBLRmy+9pHh2to7+u7/r+dSbNBMOh52mPfX19SouLk40+ampSfR/JCWa4SxdKrndkqTq6modOHBAc+fOHceSYyTY4bRCISkrS5s3b9a0adN6rek1KA0NMn6/XrUslZSUaMHs2WrfuFHNmzbJFwppVlGR2nupWeI9FC6uOXRD9SOrVil7+3a1t7Xpz3/+swKBgM455xzl5eUpIyND06ZNk2X10aev1yu99550wglSYaGz3qabvXv36vXXX1d2c7OCO3ZIWVlSODzwdxePJ56slpubuLbJyCD4AXBkCwQCiR1hZWXPFw/ddYhHInr77bd1Ok8jwDgzxqixsVHbt29XdUe1NmzckLhLW1UtE49p7zvvqHjWbImH0WGUBYNBrVmzRrFYTMccc4zmz58/3kUaE9FoVE1NTerq6up7pOZmaepUybIUDAYVDAaVk5OjaDTa/2OQkdifvfiiQnv2qG4Em1nvqK1V6NAx3Q6TwuGw1jz5pFwdHTr6Ix+R0vgR5qFQSO+++678fr+2bt2qeCymrv37E81tbPZ6W1YmuVwyxujAgQOaNm2asrKyxq/wOGx733gjUau9vl5avlw+SRVbtiQChOGIRBI3Sw8cUFtrq9r27Uv0L3PIwUF2ILy7vl7v/u1vioXD8p9wghQK6bXXXnNeLyoq0urVq1VUVKSuri6VlZUlAo/q6kRfXQ0NiZr6F18speExKBwOJ2p5V1craF+nDKVpXEfH+9t4dvaohz6S1NzRoW3btum4444b9XkNBkdcAI7y8vK+O0A7ZOszzyijqEiLZs3StHnzxqhkQE979uxRPB7XG6+/rqrYASkaS7TrjidqXvjr6rTlzTd08fEXj3NJke7Wrl2b6FxSksvl0syZM4+IWj81NTW9920hJfpKaWxMbJPz50tJNSUaGxv16KOPas6cOdxE6E08Lr38suLV1Xr03XdVnJs7opPvM0SKRPTmmjWadtZZKk7j4Gf37t2JvqjC4UQTr337EiFAzxETHWGvWiXl5GjHjh3q7OzUJZdcMvaFxmHz+XzKy8uT8XoTwY+U+N4LChIh62Cf6NWbeFyqqEjUtOmrVs4Atic3Xd+5U+rqkpYtk0pKJCX6pFqzZo3KiotVW1mpC888U6GnntKm6mpNLyxUcU6Olkyfngh/5s0bdjkmqg0bNmjXjh2JmnnDkdwB9xh1pO1rb1f1/v065phjJkRNSoIfAIrFYorFYoo3Nw/c0VlNjSI1NXr5T3/SqquuUktLi3JycnTssccqIyNjbAqMI97OnTsT/TOUlydOtOZ5Egf15JoHkYji+/aPXyGR9uw+GCq3b080kS0tVdW6ddo7d66WL1/ed7X8SSoej2vXrl0qKytTWVmZduzY0bO2j8+X2C5drvf7XKiuTgl+pEQfK62trTrppJM4dnT33HNq2rFDb+zbp2avV81e75jNOhyNqvy993Tq0qVjNs+xFI/HE49+DoUStTLy8xM3vPq6+x+LJZ56tmqV4rm5am1tld/vV+4Ih3EYwMGD0owZUn+1BDs6Et0SXHRRj5f8Xq/WvfWWPnD++YonBywtLYmfkfo+Dyc8SmY3EaquloqKEvtTSW319WrbtUtqbdW2cFh7t26VMUb1nZ2Kx+NqDwR0iiSVliaafU1y4XBY9fX1qq+vV/nOnYk+R0egyeuY8Xp18I03FLn44glRU5DgB4BaWlpUU1Oj1paWQbdx7tq3T6+//rrTr8X06dM1c+bM0Swm4Ni8eXPiZL2+PnFCFImkhj6HhLo65d2zR/lLloxDKZHOurq69OabbyrQ3Kz4jh2JwKO9XfJ6tfaBB5Rx8cVacv75413MwxaLxdTR0aHq6mpVVVWpoaFB06dP19KlS50neDl8vsSJeffHIsdiiQ5zjzoq0SdDkgceeECnn366li9fTtMvSdq1S++uWaNd9fUj0qfPcNTs3q3W1lZNmTJlXOY/Urxer95991198IMfdIZFo1E1NzYm7vj7fD3X1d7E44kbC/Pmyev1yuv1EvyMtZdfTvwuK5MuvbTn69FoIqDrowN038GD2v344+raulX+5Kc92Ubz6U6Ho6ND2rJFysxMrLPhcOKcJxjUnqQa+vZT57YcPKhMt1vHGSP3gQOJZTVJ96s1NTV66qmnEv/EYtLWralP6posurp0cPNmLT711PEuyeQIfpqamobcFry1tVV5eXkTIl0DJopgMKjm5mbt2bNH55xzjjZv3qyysjJVVFQkOjZsaRn0tEw0qlhVVWInvGSJnn/+eZ1yyil02IkxEa+qSjQhkRIn5R3tvY4XikTUXlfXZ/DT3NyslpYW+Xw+LVu2jJN5DNqaNWvUfPBgosNI++LRrkpeW6uqV15ROD9fx5x66qSu+fPGG28kjg9JGhoa1ND9CTitrSn9WvTQ0pK4cDn++ETHmocYY/TWW28pHA5r9uzZ2rx5s6ZPn66VK1f2utzSuW+gzq1btePBB7WtpmZcHx/eVF2trX/6k879whecmgbjKh6XIhEFjdHLL7+smTNnarakafPnS32EU+FwWA8//LBCoZDcbrfOPfdcSdKWLVsS6+pQLyDr6xPNZ5TopPy4445TW1ubqqurtXLlSs1L56bv8XgicMjOHt77g8FEgFFSkthX+v2J5b98eR+ziyscDitbSjTDmztXrR0dKvR45AmFEsf+7p1sh8OJZnmS9NZb0hlnOC95vV4dOHhQamtT7SD725lQhrCuxuJxvVNRocauLp3s96tk1y5pgvQvMxTGmEToE4kkmr1lZ0/O0EeSOjv10s9+psXNzYlaWLPGr+PJSXHkbG9v17Zt23TCCSc4j7Xr76Df1dWlJ598UsYYfepTn5rUJ1zASHrzzTdVUVGhWCzmVLO3LEv59jYylM4jQ6HEUy8kKT9foVmz9PZrrykajWrhwoUqKCgY+Q8ASKp66il5t28fdMd81e++qznnnJMyrKOjQy+88II8Ho8aa2qkri5t3LBBN3zucxwzkhhjtG/fPi1cuFDuNH1KyHB0dHSosa5O2rEj8TSVXuyvrNT+3/1O+2pqdNSyZZMuFDfGaOPGjYm+3wbDvujqTyAgbdwoTZsmLViQ8tKGDRu0YcMGGWNUVVWluXPnaurUqSnl6erqch4JX1ZWpilTpigUCumUU06Z9KFtMBDQk//7v/JOhMeGx2KK79uX6EvD65WOPnp8nhIUjUr19QqvX6+31q9Xzmmn6eDOnTq4bp3eKy/X5StXauYHPiD10k9UXV2dQoc6frX7g1uxYoW2bdmS6N+lvw7JexMOJzrQnTtXByUdPHjQeam1tVXHHnusjjvuOGeeRUVFw/3UI6e+PtFJdzCo4Pbtis6bp+zsbHlKS/vv/8V+0EdpqZSRoU3PPKPqXbt00SWXKNuyEqFLKNRjG3Y0NCQ6xq6pkXJzVbl5s7yvv65Gj0fzCgp01FFHqaO2VlYwKH91taafdJIsSWbKFL335pvKnjJFO156Secdc4yKKisVyczUkxs2KMPt1snz52v+iy8qc/p0ac6cRBhXXPx+0ygp0TfT8cdLeXlSNKoN992nXRO1Rs8oqWhultvl0plvvKHsRYtGrinbGNm+fXuilk9VVaIm7WQXjWrL22/r+JoamcJCWRdfPC4d6E+K4EdKpOutra1avHixmpqadPLJJzuvRaNRlZeXa/78+dq9e7e2bt3q7HjLy8u1NE3bKQNDEQwGVVNT4zTNajlUu8cEg+rcsiVx8OyjiuyAKiul6mpFLUtvt7SofNYsXXPDDQoEAnK73crIyOBiGiNi3bPPqu7pp4f0NIbqmhqd2NCgnNJSye1WMBjUGy++qNba2sTJYmWlFI0qtmSJXnjhBV3US/8AR6JYLObU9sjMzNQnP/nJI6LD4sHw1dUp8uabztMO+9TZqfrnnlNrfb0aGxu1cuVKlRzqqHMi6uzsVHNzszIzM7Vp06bEE1QGEgwmajoN5ok48XhifHu68+Y5NUpMt2bGFRUVmjp1qiKRiN544w1VVlYqEokoLy9PoVBIBw8edC6+Dxw4oEsuuUSlpaVD+rwTRUdHhza8/vrECH0OqWlr05b/+R8dP2dOoqnJsceObc2BDRvU9vrr2t/YqPVVVYlhlZUp+/6nt27Vp4qKlDFrllMbx9fernavV1X2e5SoQbJn+3btefbZxDY7nAvJeDxR42DHjvcDB7db6uhQqKhIGzZsUE1NjQKBgILBoD7+8Y8re7g1ZAYrEkk04wkEEtuUXcZoVMrNldmxQ5u3b1e7ZammtlYyRlkejz7y9a/L1UcNpVhTk5r+9jeFWlp0sK1NDV6vWrq6ZIzR/+7bpwuWLdMCOzhavjwRuiXfjG9tlZ5+Wpo5U6axUbvb2vTm9u2KHgpeKt1u1dfWan9Tk3LWr1ebz6fZL76o8048UWvLy1Xp9ycCp/JyvVdV5fRvFY5GFYxE9Mru3TolFNLxoZDcBw8mgoHLLpOefVaS5A+HZYXDyjnUTDISDGrXnj2j+CVMXHsbG1Xf2alrXC5l3nhjr+OEw2G5XK4JV4uytbU1cTOhe83SSezdykq1+nwKx2JaaYymf/zjY14Gq/uBdiK67rrrzLnnnitFIrIiEZXFYjr5Yx9TQUGBQqGQs7P1eDxO4GNbsGCBTj/9dBUWFo5T6YHxZ4zRK6+8or27dyd2oqFQIkmPxRLVbke640iXS9OmT5e3q0sZJ52kUz74QS1avHhk54EjQjwed56E0F5fr0e+8x1Fe7lTW5XVdzPF+aGpys7I0NX/+q96o7xcbXV16nj77UR/VtHo+xcShYVyH3+8lq1YoVNOOeWIDDkqKioUDAZVXl6urq6ulD5cMjMzdfHFFw+qL69YLJZ2NYTsJoH79u3T3o0bZTZsGPybS0ul5ctVXFKiK6+8csyaodvbTzgclsfj6fOpIi0tLXrppZfUfuiCeO7cuTpgN6W0+5mxm2cZk7joi0QSw5qaElXxhyMjI3EBHQ4nahEkXXx4PB6tWrVKPp8vcfd3AMsWLdJZ552XeFBBPC6/36+8vDxVVVWpublZhYWFKigo0PxhPObYGKN4PK7t27fL6/WqqKhIy5Ytk2VZI/Kklueee05Vr776fvPVCeTMxYuVm5mpBVOnylVcnLjYX7asR19NhyMSiaR08N3a0qJ999+v8vJy+QZ4XHNxbq5WH3usmvPyVHzuudr0l7/ooJRYlzo7E+uq15sIJEay+VxeXuJ3IJAIxerqEnfwDzXjyMnJUVk4rFNOPlnZs2YpZ+pUWZY1cjfBOjsTYUcw2OcTit7ev19bkmom2T59/fXK6uPJZH/95jcVq69XRx83ArMzMnTu0UfrQFubSvPzNeuUU1R40kmJWnySdOCA4k89JcuytKexUa/u3j2oj5Pp8SgSi/UIgPuSm5mpaYWF+uDSpfJccIH0yisyxui57duVnZGh048/Xtmf+IRC+/frd//+74OaZrrKzczUeV/4gmYn9TETj8e1c+dOrV+/3mk+6/F4NGfOHJ155pl9B0Ht7VJXl2I7d8p88INyuVwj+rSqPXv2aOvWrWqurZXefnvEpjsRnX3SSfKceKKqa2tVNnu2VnzgA0NZlsPakYx68GNZVpak/5b0UUkhST8wxtwzlGlc9+EPm3OXLElcrHq9iR74V6x4v9ppPN5vG+SMjAwVFRUpJydH8+bNk8fjUX5+vmbPnj3szwVMZKFQKOXCwuv16o+/+520bt349IZ/0kk6++KLJ11TB4yPWCymvXv3KhQKadeuXTr//PP1xtq18m7bJm8fF5gDBT+SVDZ7tpqbmmT6q5lQWCgdc4wyPR6dYweWDQ2Jk/lwOHGR63Il7q7OmiWlS4fmfr/e2bxZ+yoq5O0tCA6HE01B3W4tOflknbhggYrnzVNYiWOs3SRswYIFqq+v1wsvvKATTjhBxx57bFr0tbd9wwa9tW5d4mkw9fWJ0HwoNSQtK3HOsmiRFp91lqZPn66FCxdq06ZNOvroo+X1erVw4cJ+JxEOh7Xl3Xflr6hQSWmpVpxxRp9VxYPBoDZt2qSqqiqVlJSosrJSRx11lBobG7VkyRKtWLFC5eXl8ng8OnjwoJpqatTV2wV2PJ7oUDMjQ8rJSRw/OjoS/S0Eg4ltIRAYmQtqtzvRcWtmZkpNoB683sRPTk7iPY2NiRsYliXPsccqalnyeDyKRqPKyspSJBJx+svJyMjQ3Llz1dTUpA996EMD3hQ0xsjn8+nFF1+Uz+eTL6kjYI/Ho6lTp+rEE0+Ux+PRjBkzep60x+OJ736Ai/1fff3riZoLE1h+drZKcnN15uLFKpo6NfGkoXPOSfwepG3btqmurk5lZWWaNm2aqqqqFI1GtWfPHp111llqaWlRU2OjAuXliZrIg2QHKvGMjMS1wng6+ujE+jh3rrRhg6ZkZMibkaHcM85QcVmZPvCBDySaGVuWlk2frkXJHb5Go4l1u6Mj8ZTA7OzEMWnGjNTtoapKeuklKRpVKBJRKBqV2+VSU1dXojaOpA3V1VpXWdlrEY+ZNUuFp5yieccco/wpU7TuzTc1NRZTW1eXNr3yypA/8smLF2vVP/+zYoWFMpWVev0Xv1CG261d9fWj3ldVdkaGPnnqqYobo+d37FDtofD6jMWLteILX9CO117T2iefHNUyTAZnfeADip1xhg5WVmp6WZl27N2rgL3vtp9EFg5LeXk69thjNW3aNC1ZsiQR9NvBaVWVtGuXwtGo/rJ+vYIzZ2rWySerKC9PbX6/VixZovmZmdLixYn3BYNSVpZCoZBC0Wiv+1tjjCKRiOrr69Xe3q6tb74pX0ND4iluw22FMEm4XK73t4/8fJWdeaYK/H6VLlqkjNmz5W1s1LJVq/pqNjphg58fSzpP0mckzZH0B0mfN8b8abDTuG71anPunDmpA7OzEz92kl9SkujgLTc3kYJ3dCRW5OnTE6/Zd3Y9HsnjkbupSbmLF2vp0qVasWIFjxKdLGprE3dV8vISJ4YeT+JO4+7diSrIRx89aXuvTxaNRuVyudTU1KTS0tKUO+fdO7aMxWLOXce2tjbV1tZq/4YNml1Sory5c1U8Y4Z2btig8ldeeb96/VhzuTRv0SLNOP98TZk/X/PmzVNzc7NcLpcsv18lc+YkDirNzYmL7MxM6aSTxvS7NMYoEAgoOzt7RO9eYGDt7e1au3atlixZosLCQlVWVmrr1q2JF5uaEifyyc1DejGY4GdQXK73n57hcmlmcbGOnT5dM6dPV5bHo7DPp+zk48Xs2Yrm50vLl8tj3/GcwKLRqHbu3KlYLKbc3Fx1NjQouH69/NXVqpQSfTYkN08IBhPH2D17Ehf9LpfkcsljjOJ5eYovWaJpCxeqtLRUO3bskNvtVlZWllNTaNGiRbrgggvG4ZOOgHhcMkaN1dV68kc/UrSjY+CmXQNxu6UTT0zpb8GuWbZo0SKddNJJyrNrEkiKhEJa/9hj2vvmm/LHYonzm1hMmR6PPrBkiXKXLVPZ/Plyz5gh69B5UjQa1fPPP6+DFRWJ+blciXMg+wlGsZgyp05V2OtNnFjbTziaOjURJOXmJobNmpVoWpP05JgxU1SUqFGSn58oj8eTKFN7e+rTd1yunqFTZmbiPcYk/i4rS3y2buFLbm6usrKyVFhYqFNPPbVHE7x169Zp+/btPWqS92XF8uXK8XpVmJentspKTQ+HletyKcPjUf5pp8mqrU2cl1pW4vhWXCy/36+9e/fq7XuGdD90XE0rLNRlxx2nTI8ncd59zTV9juv1elVRUaH9+/f37Azc1tEhHTigzJIShfPzE33LTMYOeG29rZNSYh3OyFDmkiUKG5O4iPb5tPyyy3TW6tWKr1snj/1kQEnRWEwe+9yvtFTxc86RNzNT2ZL233+/oh0dqu3oUF1Hh0JJN/QKc3JUkpurg21tig0QusyYMkXTSkq0Zd++w/zILi0uK1NNNCpPKKTOka5FPoArVq6UPxzWi91uDF1w3HFqjsW0abg1EtNISUmJQsuXy9/Vlbhumj8/sY+1+/GSEvvMVauca+njzzhDDa+/rtmdnSrNz9fU/HztrKvT/uZmddqhTFZW4rhoWVJmpubn5Gj54sUqnTpVzQcOyCor0ztbtqjV41HZMcdoxbnn6qijjpIk1W/dqp1796puyxa5AwF1tLUlwqfJ9Lj20eDxJPYj4bBc2dm64tZbNa3njfOJF/xYlpUnqVnS5caYFw8N+4akS4wxZw92Or0GP33PtOfjqHNy3k8NLSvRNre2NhEKBYOaM22apoXDyikq0vITTpBPUobbrexVqxILPjd3WE81iMfjckUi8tfXK8vrVai0VDnTpvWo5mmMUTAYlM/n05QpU5wEMB6Py+v1qrq6Wu5AQMtLSuSaMiVxInQowOqXMYkL6aKixMlPr6Mkqi+73W61t7crMzOzZweJXm/ipDA3t0fnYIOtzt/reMYkqjWXliZ2GoeS4Fg0ql2/+Y3cU6cqJzdXMbdbBdGoyjyexElo8iQyM2UOVXF1uVyKz5ol1+rViWBoEvYp4/P51NbWpq1r18ofj6tlxw5lZWdralGRpuTkKNjaqiq/Xycff7yy5s+Xp6REW7duVTgcVkZGhhrr6xNPTtm3L7HztCy5MjMVj0RGtorzcE2frqylS7Vg3jzt3bhRsZoaqbNTJyxZokWlpaqtq1O736/czEzNmD5dcz79acV9PrnKyhInSfF44kKmq0sqKEhs211diUcENzUl1nX7ADTIzqX9fr9qamq0f/9+VVVVOXdxly9frqNLShLrZV81Fny+xL6luDgtAsexZozRCy+8oAMHDjh9TzlaWt5/SscgjlMjFvz0weVyaVpBgdr8fs09dIF44ty52tfUpM0HD8oUFGjKwoW64OyzVZiXJ7lcqqiqUuHJJ2v7tm1avHSpZsyYMfbNn+JxmUhETXv26M3HH5c3O1v+rKzEMvX7E8u3e6eXU6YkaniUlCTuuvV3Ep+dndjfdnUltk1jEu89+minKcSCBQt0/vnnKxgMqqurSzNmzBhc2e3vfQj7cvucpt/mFIdqL/lff125p58uU1cnzZkjyxhp3z7F8/OligpVVVVpX1OTquvrFe2jKcWwZGcnjqUZGYllm5WVGDZ/vrKyspQVCChYX6/CeFztLS1O3xi9sSxLORkZKs7L06ySEk2dM0c74nEd2LXr/c767XOYoV5M93Y+NVm5XInlvGJFr08mKi0tVXFxsfLy8uRyubR//3519Pewg0jk/T5VCgoS639dXY9g0LIsGWO0oLRUU/PylJuZKcuy1BIIqCIWUyQSUcSuTTeJHD9njuo7OzUlN1cnXn218k46SeFD55LuhgbVVFTo9R075HO5UpvudHUlllFOTuL7qKuTKirer3FwhCo5tK/My8xUJBZTQXa26jo6NDUvT1Py8lSan6/X9u1TrKBAWZGIApP16UajJCczU4FeavLOmzJF4VhM9ZNs+xo1bnfiuNzf+pORkdintbamXj+rWw2VAXjcbkV72a6z8vO15JRTVLFhgzKiUbX7/elznBklK447Tmd87WvdB0/I4OdMSWsl5RpjgoeGrZb03KFhg9rTDyn4OUz2ipqdkaH5c+Zofk6OfIWFKsjIkO9QSOQuKFDutGmJE9tD1azj8bgaGxtVXVmp2qoqHVNWpreee05TolE1NjXJSJLLpYJZs7Ty+OO17KijpHnz1OJ2a+2aNWqor5csS5lutxYffbQq33tPgaqqxEZ6qGp1cW6ujps1S1Pz8zX96KPfr2I9fXri5KO0VF0dHWry+1W/Z49KW1s1v6REWfn5ktst//Llii1cqJodO1SzebOycnMlv1+79u1TztKl8kejcnd0KNvl0rTSUoVqarQ8P1+58biKc3PV4vWq7JxzVJefr4qGBrV3dqqpqUnFxcVaVlqq5ro6NdTUqCAe19SSEkUXLVJQUn1NjUxtrU4/9liVZGUpy+NRfkGB1NSkcHW13C6X2iIR+aZM0abNm9XW2alIUnVq29HTp2thaamqWlrUHggoHI0qGo87d0VKcnPV5vfL43LpqPnzFV++XH6/X7nZ2Tp61Srl21XHI5FEDYKCgsTOz+9XrK1N/rY25S1YoLaGBk2xLFlZWYlE3K6iv3174iQlM1Pxri41ZmXJn5WlhoYG+fPzFYxElDdlikw8rqnFxXLV12vq/PmaMn++sgoKEndxDnW4lxygxSMRVe7dq8Z331XlwYOJFL26OjHf/k6G8vISIWBmZuLzZGYmPttE7wjN7U58tkHcOZ9VXCx/OKxZpaXyxOPKz8pSZzAoY4xmFhVp7pQpisRiyvJ45LbD2YyM908si4qk005L/B8OJw4usZjU2qrG/HzVhcN6b906xe3X7TvgXV3yBIPKjkZ19LRpyi0r0+zjj1fRccfJ19WlQE2NKrZsUWN5uTLdbq2cP1/uk09WW1GRpi1YoGy3W5nZ2Yn5uVyJALatTWbqVDU2NCggqdnvl8sYRaNRTZk2TdnZ2Zo+fXpa1j4Mh8PKzMyUt7NT0UhEmzZvVn1jozIktTQ2Jtbfrq7Eham9Hic/oWMQRjv4GayC7GwV5eTIHw6r1d6Pud3SrFmaNmVKohPSWEwzlyxR3ONRe2urpk6bpkggoIjPp8LCQlmhkDrb2pQ7d66mFhQoq6ND4fp6Fcdiyjcm0ZeCvT/LylJo/36FIxH5wmFFXC5N7+qSLEsN7e2q27lT++vr3787N1bc7sS2WFoq+f3KmD5dVl6ewh6Ppvv9mlJUpOZoVDmFhXK7XCqMRjV98WK5m5rU5fXqqJkzlVlXJwUC8mdnq8LtVlVTkzyZmeqKRHTMCSdo6tSpCnd2qnzPHgViMZUcfbQisZh8Pp8WL1wot8ulRUuWaMf69VIopKjXq/aqKmU3NSnQ1qY9DQ2aU1KizmBQcWNUlJOjUCTi9G0RGY+LUbf7iL8IHlX2TYHZs9/fPweDieDePuZmZLx/cZSdnXgtMzPxOxRK3C0PBg+/9leayDy0fKIul1yxmFyRiML2DZhZsxI3W93uxHmNHZYBAAYlJzNT559zjqadcII8HR2J8+O/+7sJGfxcLemXxpjSpGHLJe2QNMsYUzeY6Xzuwx82l69YMUqlHDpL0tSCAikrS/nz58sViyns9+ug3SnfIE6wc7OylJ2TI29+vsJdXYm7PVlZ7590DDANl2UpLztbUwsK5LIsxY1Rp9+vrkAg5WTV7XKprLBQ/lBIXYGAhvttZ3k8iQP5IXaQ5ejrQG6P0+31nEN3vQKhkHNHbDTz3uzMTJ2+bJlUUKD6+np1tbUpIDlPIfEGgwpHo86yzMnMVCQaVVlxsWKWpfzCQsnvV2Furlq7utTU2dnr3QVlZLyfXB9aXi7L0vRp06RwWL5gUN5wWFOnT1dBRoYyPR7VNTaqY6iPFYWkxLI1xijT49HMKVMUikSUlZGhTr9fvmBQWYfuhMficQXCYWV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\n",
      "text/plain": [
       "<Figure size 576x288 with 7 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 287,
       "width": 575
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "fig.set_size_inches((8,4))\n",
    "gs = gridspec.GridSpec(7,1,height_ratios=(1,0.5,0.5,0.25,0.25,0.25,1))\n",
    "\n",
    "# visualize region information and scale bar\n",
    "ax = fig.add_subplot(gs[0,0])\n",
    "raesymatto.visualizations.draw_region_information(ax,chromosome,start,end,fontsize=10)\n",
    "\n",
    "# visualize two bigwig files\n",
    "ax = fig.add_subplot(gs[1,0])\n",
    "raesymatto.visualizations.draw_bw(ax,chromosome,start,end,wt_imm_bw,ymin=0,ymax=20,\n",
    "                                  label='WT',kwargs={'lw':0,'fc':'red','alpha':0.4})\n",
    "raesymatto.visualizations.draw_bw(ax,chromosome,start,end,thpok_ko_bw,ymin=0,ymax=20,\n",
    "                                  label='ThPOK KO',kwargs={'lw':0,'fc':'black','alpha':0.4})\n",
    "\n",
    "# add a legend\n",
    "ax.legend(loc='upper left',frameon=False,fontsize=5)\n",
    "\n",
    "# add a shaded rectangle to show a region of interest\n",
    "ax.add_patch(mpl.patches.Rectangle((89382182,0),89382343-89382182,20,\n",
    "                                          color='green',alpha=0.2,lw=0))\n",
    "\n",
    "# visualize some artificial looping data\n",
    "ax = fig.add_subplot(gs[2,0])\n",
    "# create some example looping data\n",
    "loops_bed = pd.DataFrame([['chr3',89363900,89388500],\n",
    "                          ['chr3',89373900,89374900],\n",
    "                          ['chr3',89376900,89379900],\n",
    "                          ['chr3',89374200,89394000]])\n",
    "raesymatto.visualizations.draw_loops(ax,chromosome,start,end,loops_bed,frame=False,flip=True,\n",
    "                                     kwargs={'lw':2,'ec':'gray','fc':'none','alpha':0.5})\n",
    "\n",
    "# visualize some \"flat\" BED rectangles (score defines the color)\n",
    "ax = fig.add_subplot(gs[3,0])\n",
    "raesymatto.visualizations.draw_bed(ax,chromosome,start,end,gata3_bed,frame=False,\n",
    "                                   scores=True,kwargs={'lw':0})\n",
    "\n",
    "# visualize some BED rectangles (score defines the height)\n",
    "ax = fig.add_subplot(gs[4,0])\n",
    "raesymatto.visualizations.draw_boxes(ax,chromosome,start,end,gata3_bs_bed,\n",
    "                                     kwargs={'lw':0,'fc':'gray'})\n",
    "\n",
    "# visualize conservation data\n",
    "ax = fig.add_subplot(gs[5,0])\n",
    "raesymatto.visualizations.draw_bw(ax,chromosome,start,end,cons_bw,ymin=-5,ymax=5,\n",
    "                                  xspine=0,kwargs={'lw':0,'fc':'gray'})\n",
    "\n",
    "# visualize gene models\n",
    "ax = fig.add_subplot(gs[6,0])\n",
    "raesymatto.visualizations.draw_gene_models(ax,chromosome,start,end,genes_gtf,min_height=10,\n",
    "                                           fontsize=7,frame=False)\n",
    "\n",
    "fig.set_tight_layout(True)\n",
    "# fig.savefig('output.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5ea40451-ab02-49cb-aeb6-16ad0a2c44e6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}