1.07_NaiveExactMatching-MatchingRealReads.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2015-07-14 11:55:06--  http://d28rh4a8wq0iu5.cloudfront.net/ads1/data/phix.fa\n",
      "Resolving d28rh4a8wq0iu5.cloudfront.net... 54.230.53.87, 54.192.54.164, 54.192.54.222, ...\n",
      "Connecting to d28rh4a8wq0iu5.cloudfront.net|54.230.53.87|:80... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 5528 (5.4K) [application/octet-stream]\n",
      "Saving to: 'phix.fa'\n",
      "\n",
      "phix.fa             100%[=====================>]   5.40K  --.-KB/s   in 0.003s \n",
      "\n",
      "2015-07-14 11:55:07 (1.60 MB/s) - 'phix.fa' saved [5528/5528]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget http://d28rh4a8wq0iu5.cloudfront.net/ads1/data/phix.fa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "def readGenome(filename):\n",
    "    genome = ''\n",
    "    with open(filename, 'r') as f:\n",
    "        for line in f:\n",
    "            # ignore header line with genome information\n",
    "            if not line[0] == '>':\n",
    "                genome += line.rstrip()\n",
    "    return genome"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "genome = readGenome('phix.fa')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def naive(p, t):\n",
    "    occurrences = []\n",
    "    for i in range(len(t) - len(p) + 1):\n",
    "        match = True\n",
    "        for j in range(len(p)):\n",
    "            if t[i+j] != p[j]:\n",
    "                match = False\n",
    "                break\n",
    "        if match:\n",
    "            occurrences.append(i)\n",
    "    return occurrences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 5, 9]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = 'AGCTTAGATAGC'\n",
    "p = 'AG'\n",
    "naive(p, t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "def generateReads(genome, numReads, readLen):\n",
    "    ''' Generate reads from random positions in the given genome. '''\n",
    "    reads = []\n",
    "    for _ in range(numReads):\n",
    "        start = random.randint(0, len(genome)-readLen) - 1\n",
    "        reads.append(genome[start : start+readLen])\n",
    "    return reads"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 / 100 reads matched the genome exactly!\n"
     ]
    }
   ],
   "source": [
    "# Generate 100 reads of length 100\n",
    "reads = generateReads(genome, 100, 100)\n",
    "\n",
    "# Count how many reads match the genome exactly\n",
    "numMatched = 0\n",
    "for r in reads:\n",
    "    matches = naive(r, genome)\n",
    "    if len(matches) > 0:\n",
    "        numMatched += 1\n",
    "print('%d / %d reads matched the genome exactly!' % (numMatched, len(reads)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "--2023-10-20 11:54:08--  http://d28rh4a8wq0iu5.cloudfront.net/ads1/data/ERR266411_1.first1000.fastq\n",
      "Resolving d28rh4a8wq0iu5.cloudfront.net (d28rh4a8wq0iu5.cloudfront.net)... 18.67.194.17, 18.67.194.183, 18.67.194.59, ...\n",
      "Connecting to d28rh4a8wq0iu5.cloudfront.net (d28rh4a8wq0iu5.cloudfront.net)|18.67.194.17|:80... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 254384 (248K) [audio/mpeg]\n",
      "Saving to: 'ERR266411_1.first1000.fastq'\n",
      "\n",
      "     0K .......... .......... .......... .......... .......... 20% 2.19M 0s\n",
      "    50K .......... .......... .......... .......... .......... 40% 6.26M 0s\n",
      "   100K .......... .......... .......... .......... .......... 60% 5.36M 0s\n",
      "   150K .......... .......... .......... .......... .......... 80%  185K 0s\n",
      "   200K .......... .......... .......... .......... ........  100% 8.15M=0.3s\n",
      "\n",
      "2023-10-20 11:54:09 (788 KB/s) - 'ERR266411_1.first1000.fastq' saved [254384/254384]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget http://d28rh4a8wq0iu5.cloudfront.net/ads1/data/ERR266411_1.first1000.fastq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def readFastq(filename):\n",
    "    sequences = []\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",
    "            fh.readline() # skip base quality line\n",
    "            if len(seq) == 0:\n",
    "                break\n",
    "            sequences.append(seq)\n",
    "    return sequences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({'T': 30531, 'A': 28426, 'C': 21890, 'G': 19147, 'N': 6})"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import collections\n",
    "phix_reads = readFastq('ERR266411_1.first1000.fastq')\n",
    "count = collections.Counter()\n",
    "for read in phix_reads:\n",
    "    count.update(read)\n",
    "count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7 / 1000 reads matched the genome exactly!\n"
     ]
    }
   ],
   "source": [
    "numMatched = 0\n",
    "n = 0\n",
    "for r in phix_reads:\n",
    "    matches = naive(r, genome)\n",
    "    n += 1\n",
    "    if len(matches) > 0:\n",
    "        numMatched += 1\n",
    "print('%d / %d reads matched the genome exactly!' % (numMatched, n))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "459 / 1000 reads matched the genome exactly!\n"
     ]
    }
   ],
   "source": [
    "# Now let's try matching just the first 30 bases of each read\n",
    "numMatched = 0\n",
    "n = 0\n",
    "for r in phix_reads:\n",
    "    r = r[:30]  # just taking the first 30 bases\n",
    "    matches = naive(r, genome)\n",
    "    n += 1\n",
    "    if len(matches) > 0:\n",
    "        numMatched += 1\n",
    "print('%d / %d reads matched the genome exactly!' % (numMatched, n))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def reverseComplement(s):\n",
    "    complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A', 'N': 'N'}\n",
    "    t = ''\n",
    "    for base in s:\n",
    "        t = complement[base] + t\n",
    "    return t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "932 / 1000 reads matched the genome exactly!\n"
     ]
    }
   ],
   "source": [
    "numMatched = 0\n",
    "n = 0\n",
    "for r in phix_reads:\n",
    "    r = r[:30]  # just taking the first 30 bases\n",
    "    matches = naive(r, genome)\n",
    "    matches.extend(naive(reverseComplement(r), genome))\n",
    "    n += 1\n",
    "    if len(matches) > 0:\n",
    "        numMatched += 1\n",
    "print('%d / %d reads matched the genome exactly!' % (numMatched, n))"
   ]
  }
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