chromosome_band_ideogram/ideogram.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, sys, warnings\n",
    "\n",
    "import numpy  as np\n",
    "import pandas as pd\n",
    "\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import matplotlib as mpl\n",
    "mpl.rcParams['svg.fonttype'] = 'none'\n",
    "\n",
    "sns.set_context(context='poster')\n",
    "\n",
    "bigsize   = 20\n",
    "midsize   = 18\n",
    "smallsize = 14\n",
    "hugesize  = 24\n",
    "\n",
    "from matplotlib.path    import Path\n",
    "from matplotlib.colors  import to_hex\n",
    "from matplotlib.patches import Polygon, PathPatch, Rectangle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Download data\n",
    "\n",
    "### Download from [UCSC Genome Browser](http://genome.ucsc.edu) @ 2020.03.17\n",
    "\n",
    "Tools (Table Browser) -> hg38 -> Mapping and Sequencing -> Chromosome Band (Ideogram)\n",
    "\n",
    "or\n",
    "\n",
    "From UCSC database [Links](http://hgdownload.soe.ucsc.edu/goldenPath/hg38/database/cytoBand.txt.gz)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load table\n",
    "ideo = pd.read_csv('cytoBand.txt.gz',sep='\\t',names=['chrom','chromStart','chromEnd','name','gieStain']).set_index('chrom')\n",
    "# Get chromosomes\n",
    "chrMain = sorted(ideo.index[ideo.index.str.contains(r'^chr\\d+$')].unique().tolist(), key=lambda x: int(x.strip('^chr'))) + ['chrX','chrY']\n",
    "# Clean table\n",
    "ideo = ideo.loc[chrMain]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Karyotype colors From [CIRCOS](http://circos.ca)\n",
    "\n",
    "gpos100 = 0,0,0\n",
    "gpos    = 0,0,0\n",
    "gpos75  = 130,130,130\n",
    "gpos66  = 160,160,160\n",
    "gpos50  = 200,200,200\n",
    "gpos33  = 210,210,210\n",
    "gpos25  = 200,200,200\n",
    "gvar    = 220,220,220\n",
    "gneg    = 255,255,255\n",
    "acen    = 217,47,39\n",
    "stalk   = 100,127,164\n",
    "\n",
    "# Map color to name\n",
    "color_dict = dict( \n",
    "    zip(\n",
    "        ideo['gieStain'].unique(),                # Stain results\n",
    "        list(                                     # Get hex color\n",
    "            map(\n",
    "                to_hex,                           # Convert to hex color\n",
    "                np.array(\n",
    "                    list(                         # Get RGB colors ([0,255])\n",
    "                    map(eval,                     # Convert to RGB colors ([0,255])\n",
    "                        ideo['gieStain'].unique() # Stain results\n",
    "                       )\n",
    "                    )\n",
    "                )/255                             # Convert to RGB colors ([0,1])\n",
    "               )\n",
    "            )\n",
    "       )\n",
    ")\n",
    "\n",
    "# Plot code\n",
    "codes = [\n",
    "    Path.MOVETO,\n",
    "    Path.LINETO,\n",
    "    Path.LINETO,\n",
    "    Path.CURVE4,\n",
    "    Path.CURVE4,\n",
    "    Path.CURVE4,\n",
    "    Path.CLOSEPOLY,\n",
    "]\n",
    "\n",
    "# Plot factor\n",
    "chrom_factor = 2.5e8\n",
    "round_factor = 0.005\n",
    "space_factor = 0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12,12))\n",
    "\n",
    "for n,chrom in enumerate(chrMain):\n",
    "    midpoint = n-1+space_factor/2\n",
    "    tag_acen = 1\n",
    "\n",
    "    ax.text( -0.025, midpoint, chrom, ha='right',va='center',fontsize=smallsize)\n",
    "\n",
    "    for idx, row in ideo.loc[chrom].reset_index().iterrows():\n",
    "        start    = row['chromStart']/chrom_factor\n",
    "        end      = row['chromEnd']  /chrom_factor\n",
    "        gieStain = row['gieStain']\n",
    "\n",
    "        # Start\n",
    "        if idx == 0:\n",
    "            v1 = [\n",
    "                ( end, n-1+space_factor ),\n",
    "                ( end, n-1 ),\n",
    "                ( start, n-1 ),\n",
    "                ( start-round_factor, n-1 ),\n",
    "                ( start-round_factor, n-1+space_factor),\n",
    "                ( start, n-1+space_factor ),\n",
    "                ( end, n-1+space_factor ),\n",
    "            ]\n",
    "            p = PathPatch(Path(v1, codes), facecolor = color_dict[gieStain], edgecolor='black', lw=2)\n",
    "            ax.add_patch(p)\n",
    "        # End\n",
    "        elif idx == ideo.loc[chrom].shape[0]-1:\n",
    "            v2 = [\n",
    "                ( start, n-1),\n",
    "                ( start, n-1+space_factor),\n",
    "                ( end, n-1+space_factor),\n",
    "                ( end+round_factor, n-1+space_factor),\n",
    "                ( end+round_factor, n-1),\n",
    "                ( end, n-1),\n",
    "                ( start, n-1),\n",
    "            ]\n",
    "            p = PathPatch(Path(v2, codes), facecolor = color_dict[gieStain], edgecolor='black', lw=2)\n",
    "            ax.add_patch(p)\n",
    "        # Centromere\n",
    "        elif gieStain == 'acen':\n",
    "            if tag_acen == 1:\n",
    "                triangle = [\n",
    "                    (start,n-1),\n",
    "                    (start,n-1+space_factor),\n",
    "                    (end, midpoint)\n",
    "                ]\n",
    "                tag_acen = 0\n",
    "            elif tag_acen == 0:\n",
    "                triangle = [\n",
    "                    (end,n-1),\n",
    "                    (end,n-1+space_factor),\n",
    "                    (start, midpoint)\n",
    "                ]\n",
    "                tag_acen = -1\n",
    "            else:\n",
    "                print ('Bug at acen!')\n",
    "                continue\n",
    "            p = Polygon(triangle, facecolor = color_dict[gieStain], edgecolor='black', lw=2)\n",
    "            ax.add_patch(p)\n",
    "        else:\n",
    "            p = Rectangle((start,n-1), end-start, height=space_factor, facecolor = color_dict[gieStain], edgecolor='black', lw=2)\n",
    "            ax.add_patch(p)\n",
    "#         break\n",
    "#     break\n",
    "\n",
    "ax.set_xlim(-0.1,1+0.1)\n",
    "ax.set_ylim(24,-2)\n",
    "ax.set_title('Human genome (hg38) ideogram', fontsize=bigsize)\n",
    "ax.axis('off')\n",
    "\n",
    "fig.savefig('ideogram_hg38.svg', transparent=True, bbox_inches='tight')\n",
    "fig.savefig('ideogram_hg38.png', transparent=True, bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}