SNP_Analysis_GeneCoverage.ipynb

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  "name": ""
 },
 "nbformat": 3,
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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import vcf\n",
      "from collections import defaultdict\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np\n",
      "import pandas as pd\n",
      "import seaborn as sns\n",
      "import pybedtools\n",
      "from matplotlib_venn import venn2"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#All the genome scaffold information\n",
      "from collections import defaultdict\n",
      "genome_scaf_info = defaultdict(list)\n",
      "\n",
      "genomes_order = [\"J07HWQ1\", \"J07HWQ2\", \"J07HQX50\", \"J07AB56\", \"J07AB43\", \"J07HN4\", \"J07HN6\", \"J07HX64\",\n",
      "                \"J07HX5\", \"J07HB67\", \"J07HR59\", \"A07HB70\", \"A07HR67\", \"A07HN63\", \"A07HR60\", \"J07SB\", \"G22\"]\n",
      "\n",
      "#genomes_order = [\"J07HWQ1\", \"J07HWQ2\", \"J07HQX50\", \"J07AB56\", \"J07AB43\", \"J07HN4\", \"J07HN6\", \"J07HX64\",\n",
      "#                 \"J07HX5\", \"J07HB67\", \"J07HR59\", \"A07HB70\", \"A07HR67\", \"A07HN63\", \"A07HR60\", \"J07SB\"]\n",
      "\n",
      "sample_ids = [\"Jan23\", \"Jan25\", \"Aug07\", \"Aug09\"]\n",
      "\n",
      "for line in open(\"genome_scaffold_list.txt\"):\n",
      "    if line.strip():\n",
      "        line=line.rstrip()\n",
      "        genome,scaffold = line.split(\"\\t\")\n",
      "        genome_scaf_info[genome].append(scaffold)\n",
      "\n",
      "scaffold_length = defaultdict(int)\n",
      "\n",
      "for line in open(\"scaffold_length.txt\"):\n",
      "    if line.strip():\n",
      "        line=line.rstrip()\n",
      "        scaffold,length = line.split(\"\\t\")\n",
      "        scaffold_length[scaffold] = length\n",
      "        \n",
      "genome_length = defaultdict(int)\n",
      "\n",
      "for line in open(\"genome_lengths.txt\"):\n",
      "    if line.strip():\n",
      "        line=line.rstrip()\n",
      "        genome,length=line.split(\"\\t\")\n",
      "        genome_length[genome]=length"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Genome name to JGI ID number\n",
      "name_jgi_id = {\"G22\": \"2512047006\",\n",
      "\"J07SB\": \"2513020022\",\n",
      "\"A07HR60\": \"2518645513\",\n",
      "\"A07HN63\": \"2528768014\",\n",
      "\"A07HR67\": \"2518645514\",\n",
      "\"A07HB70\": \"2518645512\",\n",
      "\"J07HR59\": \"2512875011\",\n",
      "\"J07HB67\": \"2506783034\",\n",
      "\"J07HX5\": \"2512875010\",\n",
      "\"J07HX64\": \"2502082092\",\n",
      "\"J07HN6\": \"2512875008\",\n",
      "\"J07HN4\": \"2512875007\",\n",
      "\"J07AB43\": \"2502422326\",\n",
      "\"J07AB56\": \"2502422327\",\n",
      "\"J07HQX50\": \"2512875009\",\n",
      "\"J07HWQ2\": \"2512875006\",\n",
      "\"J07HWQ1\": \"2512875005\"}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "jgi_annotation_folder = \"/home/ubuntu/LT_data/New_Reads/jgi_annotation/\"\n",
      "vcf_folder = \"/home/ubuntu/LT_data/New_Reads/Mapping/variation/separated_results/by_month/\"\n",
      "output_folder = \"/home/ubuntu/LT_data/New_Reads/Mapping/variation/separated_results/gene_snps_month/\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#run annotatebed\n",
      "for genome in genomes_order:\n",
      "    gene_coverage_output = output_folder + genome + \".genecoverage\"\n",
      "    \n",
      "    input_gff = jgi_annotation_folder + genome + \"/\" + name_jgi_id[genome] + \".gff\"\n",
      "    jan_vcf = vcf_folder + genome + \"_Jan.vcf\"\n",
      "    aug_vcf = vcf_folder + genome + \"_Aug.vcf\"\n",
      "    \n",
      "    !annotateBed -i $input_gff -files $jan_vcf $aug_vcf -both > $gene_coverage_output\n",
      "    \n",
      "    "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#read files, test J07HWQ1\n",
      "\n",
      "jan_freq_hist = []\n",
      "aug_freq_hist = []\n",
      "\n",
      "for line in open(output_folder + \"J07AB56.genecoverage\",'r'):\n",
      "    if line.strip():\n",
      "        line=line.rstrip()\n",
      "        elements = line.split(\"\\t\")\n",
      "        gene_id =  elements[8].split(\";\")[0].split(\"=\")[1]\n",
      "        jan_count,jan_freq,aug_count,aug_freq = elements[9:13]\n",
      "        \n",
      "        jan_freq_hist.append(float(jan_freq)*100)\n",
      "        aug_freq_hist.append(float(aug_freq)*100)\n",
      "        \n",
      "        "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "jan_freq_data = []\n",
      "aug_freq_data = []\n",
      "\n",
      "genome_zero_count = defaultdict()\n",
      "\n",
      "for genome in genomes_order:\n",
      "    jan = []\n",
      "    aug = []\n",
      "    \n",
      "    jan_zero = 0\n",
      "    aug_zero = 0\n",
      "    \n",
      "    for line in open(output_folder + genome + \".genecoverage\", 'r'):\n",
      "        if line.strip():\n",
      "            elements = line.split(\"\\t\")\n",
      "            gene_id =  elements[8].split(\";\")[0].split(\"=\")[1]\n",
      "            jan_count,jan_freq,aug_count,aug_freq = elements[9:13]\n",
      "            jan.append(float(jan_freq)*100)\n",
      "            aug.append(float(aug_freq)*100)\n",
      "            \n",
      "            if int(jan_count) == 0:\n",
      "                jan_zero += 1\n",
      "            if int(aug_count) == 0:\n",
      "                aug_zero += 1\n",
      "    \n",
      "    genome_zero_count[genome] = (jan_zero, aug_zero)\n",
      "    \n",
      "    jan_freq_data.append(jan)\n",
      "    aug_freq_data.append(aug)\n",
      "    \n",
      "    \n",
      "    "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Use custom parameters\n",
      "from matplotlib import rcParams\n",
      "rcParams['axes.labelsize'] = 18 #18\n",
      "rcParams['xtick.labelsize'] = 15 # 15\n",
      "rcParams['ytick.labelsize'] = 15 #15\n",
      "rcParams['legend.fontsize'] = 14 # 18\n",
      "rcParams['font.family'] = 'serif'\n",
      "rcParams['font.serif'] = ['Computer Modern Roman']\n",
      "rcParams['text.usetex'] = False\n",
      "rcParams['figure.figsize'] = 5.8,3.5"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig = plt.figure(figsize=(19,8))\n",
      "sns.boxplot(jan_freq_data,color=\"Set1\", widths=.5, names=genomes_order)\n",
      "plt.ylabel(\"% of SNPs\")\n",
      "fig.tight_layout()\n",
      "fig.savefig(\"Jan_SNP_freq_boxplot.pdf\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
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9o+4yeopz1h9M5wcAAAAgzeZobrjhuiTJokUnpdFo1FxR93PO+seL7kTdsGHD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\n2h8AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x5d0b990>"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig = plt.figure(figsize=(19,8))\n",
      "sns.boxplot(aug_freq_data,color=\"Set1\", widths=.5, names=genomes_order)\n",
      "plt.ylabel(\"% of SNPs\")\n",
      "fig.tight_layout()\n",
      "fig.savefig(\"Aug_SNP_freq_boxplot.pdf\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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H6+5E3bBhw2jUAQAAAEChrOefn3PWKkbUibp58+a4/PLLY+nSpbF58+bYc889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\nrkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x5c6cf90>"
       ]
      }
     ],
     "prompt_number": 32
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print genome_zero_count"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "defaultdict(None, {'J07SB': (261, 254), 'J07HWQ1': (1494, 1506), 'G22': (3560, 3563), 'A07HB70': (334, 328), 'J07HB67': (322, 446), 'J07AB43': (272, 357), 'J07HN6': (1962, 1975), 'J07HN4': (893, 893), 'J07AB56': (202, 351), 'J07HX64': (429, 437), 'A07HR67': (412, 408), 'J07HR59': (1337, 1298), 'A07HR60': (1419, 1390), 'J07HWQ2': (2121, 2128), 'J07HQX50': (1744, 1750), 'J07HX5': (362, 366), 'A07HN63': (1683, 1634)})\n"
       ]
      }
     ],
     "prompt_number": 100
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}