1.04_WorkingWithSequencingReads.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2015-07-14 11:22:35--  http://d28rh4a8wq0iu5.cloudfront.net/ads1/data/SRR835775_1.first1000.fastq\n",
      "Resolving d28rh4a8wq0iu5.cloudfront.net... 54.192.54.164, 54.192.54.222, 54.192.55.189, ...\n",
      "Connecting to d28rh4a8wq0iu5.cloudfront.net|54.192.54.164|:80... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 224786 (220K) [application/octet-stream]\n",
      "Saving to: 'SRR835775_1.first1000.fastq'\n",
      "\n",
      "SRR835775_1.first10 100%[=====================>] 219.52K  1.03MB/s   in 0.2s   \n",
      "\n",
      "2015-07-14 11:22:36 (1.03 MB/s) - 'SRR835775_1.first1000.fastq' saved [224786/224786]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget http://d28rh4a8wq0iu5.cloudfront.net/ads1/data/SRR835775_1.first1000.fastq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def readFastq(filename):\n",
    "    sequences = []\n",
    "    qualities = []\n",
    "    with open(filename) as fh:\n",
    "        while True:\n",
    "            fh.readline() # skip name line\n",
    "            seq = fh.readline().rstrip() # read base sequence\n",
    "            fh.readline() # skip placeholder line\n",
    "            qual = fh.readline().rstrip() #base quality line\n",
    "            if len(seq) == 0:\n",
    "                break\n",
    "            sequences.append(seq)\n",
    "            qualities.append(qual)\n",
    "    return sequences, qualities\n",
    "seqs, quals = readFastq('SRR835775_1.first1000.fastq')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def phred33ToQ(qual):\n",
    "    return ord(qual) - 33"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 0, 6178, 0, 0, 54, 108, 574, 345, 83, 193, 124, 79, 165, 49, 236, 184, 327, 514, 238, 531, 254, 313, 798, 992, 888, 1396, 1488, 993, 1752, 3387, 4487, 3248, 5476, 8375, 11814, 4243, 7827, 6579, 8179, 9349, 8180, 0, 0, 0, 0, 0, 0, 0, 0]\n"
     ]
    }
   ],
   "source": [
    "def createHist(qualityStrings):\n",
    "    # Create a histogram of quality scores\n",
    "    hist = [0]*50\n",
    "    for read in qualityStrings:\n",
    "        for phred in read:\n",
    "            q = phred33ToQ(phred)\n",
    "            hist[q] += 1\n",
    "    return hist\n",
    "h = createHist(quals)\n",
    "print(h)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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TSr5vI14CuwHXEMysJonpwD7AkyVfol4N4WDg6co1EyaZm4wacCCYWT2dzEGA+qOMmvUf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\nzMwyB4KZmQEOBDMzyxwIZmYGwP8HaRAVJVJ//3sAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x107312908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the histogram\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(range(len(h)), h)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}