parse_fasta_wJS_03182019.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Idea from:  \n",
    "https://stackoverflow.com/questions/19436789\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from Bio.SeqIO.FastaIO import SimpleFastaParser\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This was esp useful:  \n",
    "http://biopython.org/DIST/docs/tutorial/Tutorial.html#sec:low-level-fasta-fastq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8 records with total sequence length 13629\n"
     ]
    }
   ],
   "source": [
    "count = 0\n",
    "total_len = 0\n",
    "with open(\"short_test1.fa\") as in_handle:\n",
    "    for title, seq in SimpleFastaParser(in_handle):\n",
    "        count += 1\n",
    "        total_len += len(seq)\n",
    "print(\"%i records with total sequence length %i\" % (count, total_len))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('short_test1.fa') as fasta_file:  # Will close handle cleanly\n",
    "    titles = []\n",
    "    sequences = []\n",
    "    for title, sequence in SimpleFastaParser(fasta_file):\n",
    "        titles.append(title)\n",
    "        sequences.append(sequence)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['MH363660 A/canine/Georgia/20170606-19/2017 2017/05/25 4 (HA)',\n",
       " 'MH363665 A/canine/Georgia/20170606-19/2017 2017/05/25 8 (NS)']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titles[0:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AGCAAAAGCAGGGGATACTTTCATTAATCATGAAAACTGTTATTGCTTTAAGCTATATTTTCTGCCTGGCTTTTGGTCAGAATCTTCTAGGAAATGAAAATAATGCTGCAACACTATGCCTGGGACATCATGCAGTGCCGAACGGGACAATGGTAAAAACTATCACAGACGATCAAATTGAGGTGACCAACGCCACTGAGCTAGTCCAAAACTCCTCAACAGGGAAAATATGCAACAATCCCCACAAGATTCTTGATGGGAGGGACTGCACGCTAATAGATGCCCTACTAGGGGACCCACACTGTGACGTCTTCCAAAATGAGACATGGGACCTTTTTGTGGAACGAAGCAATGCTTTTAGCAATTGTTACCCTTATGATGTACCAGACTATGCATCCCTCCGATCCATAGTTGCATCATCAGGCACATTGGAGTTCATCACTGAAGGTTTCACTTGGGCAGGAGTAACTCAAAATGGAGGAAGCGGTGCTTGTAAAAGGGGACCTGCTAATAGTTTCTTCAGTAGATTGAATTGGTTAACTAAATCAGGAAATACATATCCAGTGTTGAATGTGACTATGCCAAACAACAACAATTTCGACAAATTATACATCTGGGGAGTTCATCACCCAAGCACTGATCAAGAACAAACCAGCCTGTATATTCAGGCCTCAGGAAGAGTCACAGTCTCTACCAGGAGAAGCCAACAGACCATAATCCCAAACATTGGATCTAGACCCTTGGTAAGGGGCCAATCTGGCAGAATAAGCGTATATTGGACAATAGTCAAACCTGGAGACATACTGGTAATAAACAGTAATGGAAACCTAATCGCTCCTCGAGGATACTTCAAAATGCACATTGGGAAAAGCTCAATAATGAGATCAGATGCACCTATTGACACCTGCATTTCCGAATGTATCACCCCGAACGGGAGCATCCCCAATGAAAAGCCCTTCCAAAATGTAAACAAGATCACATACGGAGCATGTCCCAAATATGTTAAGCAAAACACCTTGAAACTGGCAACAGGAATGCGGAATGTCCCTGAAAGGCAAACCAGAGGCCTGTTCGGCGCAATAGCAGGCTTCATAGAAAATGGATGGGAAGGGATGGTAGACGGTTGGTATGGCTTCAGACACCAAAATTCCGAAGGTACAGGACAAGCAGCAGACCTTAAAAGCACTCAGGCAGCCATTGACCAGATTAATGGGAAATTGAACAGAGTGATTGAAAAAACGAATGAAAAGTTCCATCAAATTGAAAAGGAGTTTTCCGAAGTAGAAGGGAGGATTCAAGACCTTGAAAGATACGTTGAAGACACAAAAATAGATCTTTGGTCTTACAATGCCGAGCTTCTTGTTGCCTTAGAAAACCAGAACACAATTGATTTAACTGATTCAGAAATGAACAAATTGTTTGAAAAGACTAGGAGGCAATTGAGGGAAAATGCTGAAGACATGGGCAATGGCTGCTTCAAAATCTACCACAAGTGTGACAATGCTTGCATAGAATCGATTAGAAACGGAACTTATGACCATAACATATATAGAGATGAGGCAGTGAACAATCGGTTCCAGATCAAAGGTGTTGAGCTAAAGTCTGGATACAAAGACTGGATCTTGTGGATTTCCTTTGCCATATCATGCTTTTTGCTTTGTGTTGTCTTGCTGGGTTTCATTATGTGGGCCTGCCAGAGAGGCAACATTAGGTGCAACATTTGCATTTGAGTGTACTAATAATTAAAAACACCCTTGTTTCTACT',\n",
       " 'AGCAAAAGCAGGGTGACAAAAACATAATGGACTCCAACACTGTGTCAAGCTTTCAGGTAGACTGCTTTCTTTGGCATGTCCGCAAACGATTTGCAGACCAAGAACTGGGTGATGCCCCATTCCTTGATCGGCTTCGCCGAGATCAGAAGTCCCTAAGAGGAAGAGGCAGCACCCTTGGTCTGGACATTGAAACAGCTACTCGTATAGGAAAACAGATAGTGGAGTGGATTCTGGAGGAAGAATCCGATAAGGCACTTAAAATGACCATTGCTTCAGTCCCAGTTTCATGCTACCTAACTGATATGACACTTGAAGAAATGTCAAGAGACTGGTTCATGCTCATGCCAAAGCAAAAAGTAGCAGGGTCCCTTTGCATCAAAATGGACCAGGCAATAATGGATAAAAACATCACATTGAAAGCAAACTTCAGTGTGATTTTTGAGCGACTGGAAACTCTAATACTACTTAGAGCTTTCACAAACGAAGGAGCAATTGTGGGAGAAATTTCACCATTACCTTCTCTTCCAGGACATACTGATAAGGATGTCAAAAATGCAATTGGGATCCTCATCGGAGGGCTTGAATGGAATGATAACACAGTTCGAGTCTCTGAAATTCTACAGAGATTCGCTTGGAGAAGCAGTGATGAGAATGGGAGATCTTCACTCCCTCCAAAGTAGAAACGGAAAATGGCGAGAACAATTAAGTCAGAAATTTGAGGAAATAAGGTGGCTAATCGAAGAAGTACGGCATAGATTAAAGATTACGGAAAACAGCTTTGAACAAATAACATTTATGCAAGCCTTACAACTATTGCTTGAGGTAGAGCAAGAGATAAGAACTTTCTCGTTTCAGCTTATTTAATGATAAAAAACACCCTTGTTTCTACT']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sequences[0:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = pd.DataFrame(list(zip(titles, sequences)), columns=['titles','sequences'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>titles</th>\n",
       "      <th>sequences</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MH363660 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGGGATACTTTCATTAATCATGAAAACTGTTATTGC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MH363665 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGGTGACAAAAACATAATGGACTCCAACACTGTGTC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MH363670 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGAGTAAAAATGAACCCAAATCAAAAGATAATAGCA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MH363671 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGTCAAATATATTCAATATGGAAAGAATAAAAGAAT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MH363685 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGGTAGATAATCACTCACTGAGTGACATCAACGTCA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>MH363689 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGTACTGATCCAAAATGGAAGACTTTGTGAGACAAT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MH363690 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGTAGATATTGAAAGATGAGTCTTCTAACCGAGGTC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MH363696 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGCAAACCATTTGAATGGATGTCAATCCGACTTTAC...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              titles  \\\n",
       "0  MH363660 A/canine/Georgia/20170606-19/2017 201...   \n",
       "1  MH363665 A/canine/Georgia/20170606-19/2017 201...   \n",
       "2  MH363670 A/canine/Georgia/20170606-19/2017 201...   \n",
       "3  MH363671 A/canine/Georgia/20170606-19/2017 201...   \n",
       "4  MH363685 A/canine/Georgia/20170606-19/2017 201...   \n",
       "5  MH363689 A/canine/Georgia/20170606-19/2017 201...   \n",
       "6  MH363690 A/canine/Georgia/20170606-19/2017 201...   \n",
       "7  MH363696 A/canine/Georgia/20170606-19/2017 201...   \n",
       "\n",
       "                                           sequences  \n",
       "0  AGCAAAAGCAGGGGATACTTTCATTAATCATGAAAACTGTTATTGC...  \n",
       "1  AGCAAAAGCAGGGTGACAAAAACATAATGGACTCCAACACTGTGTC...  \n",
       "2  AGCAAAAGCAGGAGTAAAAATGAACCCAAATCAAAAGATAATAGCA...  \n",
       "3  AGCAAAAGCAGGTCAAATATATTCAATATGGAAAGAATAAAAGAAT...  \n",
       "4  AGCAAAAGCAGGGTAGATAATCACTCACTGAGTGACATCAACGTCA...  \n",
       "5  AGCAAAAGCAGGTACTGATCCAAAATGGAAGACTTTGTGAGACAAT...  \n",
       "6  AGCAAAAGCAGGTAGATATTGAAAGATGAGTCTTCTAACCGAGGTC...  \n",
       "7  AGCAAAAGCAGGCAAACCATTTGAATGGATGTCAATCCGACTTTAC...  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('canine_flu_test.fa') as fasta_file: \n",
    "    ct_titles = []\n",
    "    ct_sequences = []\n",
    "    for title, sequence in SimpleFastaParser(fasta_file):\n",
    "        ct_titles.append(title)\n",
    "        ct_sequences.append(sequence)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "caninet = pd.DataFrame(list(zip(ct_titles, ct_sequences)), columns=['titles','sequences'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>titles</th>\n",
       "      <th>sequences</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MH363660 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGGGATACTTTCATTAATCATGAAAACTGTTATTGC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MH363665 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGGTGACAAAAACATAATGGACTCCAACACTGTGTC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MH363670 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGAGTAAAAATGAACCCAAATCAAAAGATAATAGCA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MH363671 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGTCAAATATATTCAATATGGAAAGAATAAAAGAAT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MH363685 A/canine/Georgia/20170606-19/2017 201...</td>\n",
       "      <td>AGCAAAAGCAGGGTAGATAATCACTCACTGAGTGACATCAACGTCA...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              titles  \\\n",
       "0  MH363660 A/canine/Georgia/20170606-19/2017 201...   \n",
       "1  MH363665 A/canine/Georgia/20170606-19/2017 201...   \n",
       "2  MH363670 A/canine/Georgia/20170606-19/2017 201...   \n",
       "3  MH363671 A/canine/Georgia/20170606-19/2017 201...   \n",
       "4  MH363685 A/canine/Georgia/20170606-19/2017 201...   \n",
       "\n",
       "                                           sequences  \n",
       "0  AGCAAAAGCAGGGGATACTTTCATTAATCATGAAAACTGTTATTGC...  \n",
       "1  AGCAAAAGCAGGGTGACAAAAACATAATGGACTCCAACACTGTGTC...  \n",
       "2  AGCAAAAGCAGGAGTAAAAATGAACCCAAATCAAAAGATAATAGCA...  \n",
       "3  AGCAAAAGCAGGTCAAATATATTCAATATGGAAAGAATAAAAGAAT...  \n",
       "4  AGCAAAAGCAGGGTAGATAATCACTCACTGAGTGACATCAACGTCA...  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "caninet.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>titles</th>\n",
       "      <th>sequences</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1235</th>\n",
       "      <td>MH266395 A/canine/South Carolina/132956/2017 2...</td>\n",
       "      <td>AGCAAAAGCAGGGTAGATAATCACTCACTGAGTGACATCAACGTCA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1236</th>\n",
       "      <td>MH266396 A/canine/South Carolina/132956/2017 2...</td>\n",
       "      <td>AGCAAAAGCAGGGTGACAAAAACATAATGGACTCCAACACTGTGTC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1237</th>\n",
       "      <td>MH266397 A/canine/South Carolina/132956/2017 2...</td>\n",
       "      <td>AGCAAAAGCAGGTACTGATCCAAAATGGAAGACTTTGTGAGACAAT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1238</th>\n",
       "      <td>MH266398 A/canine/South Carolina/132956/2017 2...</td>\n",
       "      <td>AGCGAAAGCAGGCAAACCATTTGAATGGATGTCAATCCGACTTTAC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1239</th>\n",
       "      <td>MH266399 A/canine/South Carolina/132956/2017 2...</td>\n",
       "      <td>AGCGAAAGCAGGTCAAATATATTCAATATGGAAAGAATAAAAGAAT...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 titles  \\\n",
       "1235  MH266395 A/canine/South Carolina/132956/2017 2...   \n",
       "1236  MH266396 A/canine/South Carolina/132956/2017 2...   \n",
       "1237  MH266397 A/canine/South Carolina/132956/2017 2...   \n",
       "1238  MH266398 A/canine/South Carolina/132956/2017 2...   \n",
       "1239  MH266399 A/canine/South Carolina/132956/2017 2...   \n",
       "\n",
       "                                              sequences  \n",
       "1235  AGCAAAAGCAGGGTAGATAATCACTCACTGAGTGACATCAACGTCA...  \n",
       "1236  AGCAAAAGCAGGGTGACAAAAACATAATGGACTCCAACACTGTGTC...  \n",
       "1237  AGCAAAAGCAGGTACTGATCCAAAATGGAAGACTTTGTGAGACAAT...  \n",
       "1238  AGCGAAAGCAGGCAAACCATTTGAATGGATGTCAATCCGACTTTAC...  \n",
       "1239  AGCGAAAGCAGGTCAAATATATTCAATATGGAAAGAATAAAAGAAT...  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "caninet.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('influenza.fna') as fasta_file: \n",
    "    cgi_titles = []\n",
    "    cgi_sequences = []\n",
    "    for title, sequence in SimpleFastaParser(fasta_file):\n",
    "        cgi_titles.append(title)\n",
    "        cgi_sequences.append(sequence)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "influenza_na = pd.DataFrame(list(zip(cgi_titles, cgi_sequences)), columns=['titles','sequences'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>titles</th>\n",
       "      <th>sequences</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gi|58576|gb|X52226|Influenza A virus (A/FPV/Ro...</td>\n",
       "      <td>AGCAAAAGCAGGAGTTCAAAATGAATCCAAATCAGAAAATAATAAC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gi|59292|gb|X53029|Influenza A virus (A/USSR/9...</td>\n",
       "      <td>AGCAAAAGCAGGTAGATGTTGAAAGATGAGTCTTCTAACCGAGGTC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>gi|59294|gb|X59778|Influenza A virus (A/NIB/4/...</td>\n",
       "      <td>GGATCCTGTTATGTGCATTTACAGCTACAGATGCAGACACAATATG...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>gi|59296|gb|X66320|Influenza A virus (A/Chile/...</td>\n",
       "      <td>ACACCAAATGGAACGAAAATCAGAACCCTAGAATGTTTTTGGCCAT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gi|60457|gb|X08088|Influenza A virus (A/WSN/33...</td>\n",
       "      <td>ATGAGTCTTCTAACCGAGGTCGAAACGTACGTTCTCTCTATCGTCC...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              titles  \\\n",
       "0  gi|58576|gb|X52226|Influenza A virus (A/FPV/Ro...   \n",
       "1  gi|59292|gb|X53029|Influenza A virus (A/USSR/9...   \n",
       "2  gi|59294|gb|X59778|Influenza A virus (A/NIB/4/...   \n",
       "3  gi|59296|gb|X66320|Influenza A virus (A/Chile/...   \n",
       "4  gi|60457|gb|X08088|Influenza A virus (A/WSN/33...   \n",
       "\n",
       "                                           sequences  \n",
       "0  AGCAAAAGCAGGAGTTCAAAATGAATCCAAATCAGAAAATAATAAC...  \n",
       "1  AGCAAAAGCAGGTAGATGTTGAAAGATGAGTCTTCTAACCGAGGTC...  \n",
       "2  GGATCCTGTTATGTGCATTTACAGCTACAGATGCAGACACAATATG...  \n",
       "3  ACACCAAATGGAACGAAAATCAGAACCCTAGAATGTTTTTGGCCAT...  \n",
       "4  ATGAGTCTTCTAACCGAGGTCGAAACGTACGTTCTCTCTATCGTCC...  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "influenza_na.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>titles</th>\n",
       "      <th>sequences</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>655759</th>\n",
       "      <td>gi|1509579658|gb|LC430968|Influenza A virus (A...</td>\n",
       "      <td>AGCAAAAGCAGGGGAAAATAAAAGCAACCGAGATGAAGGCAATACT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>655760</th>\n",
       "      <td>gi|1509579660|gb|LC430969|Influenza A virus (A...</td>\n",
       "      <td>AGCAATAGCAGGGTAGATAATCACTCAATGAGTGACATCGAAATCA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>655761</th>\n",
       "      <td>gi|1509579662|gb|LC430970|Influenza A virus (A...</td>\n",
       "      <td>AGCGAAAGCAGGAGTTTAAAATGAATACAAATCAAAGAATAATAAC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>655762</th>\n",
       "      <td>gi|1509579664|gb|LC430971|Influenza A virus (A...</td>\n",
       "      <td>AGCAAAAGCAGGTAGATGTTTAAAGATGAGCCTTCTAACCGAGGTC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>655763</th>\n",
       "      <td>gi|1509579667|gb|LC430972|Influenza A virus (A...</td>\n",
       "      <td>AGCAAAAGCAGGGTGACAAAGACATAATGGACTCCAACACTGTGTC...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   titles  \\\n",
       "655759  gi|1509579658|gb|LC430968|Influenza A virus (A...   \n",
       "655760  gi|1509579660|gb|LC430969|Influenza A virus (A...   \n",
       "655761  gi|1509579662|gb|LC430970|Influenza A virus (A...   \n",
       "655762  gi|1509579664|gb|LC430971|Influenza A virus (A...   \n",
       "655763  gi|1509579667|gb|LC430972|Influenza A virus (A...   \n",
       "\n",
       "                                                sequences  \n",
       "655759  AGCAAAAGCAGGGGAAAATAAAAGCAACCGAGATGAAGGCAATACT...  \n",
       "655760  AGCAATAGCAGGGTAGATAATCACTCAATGAGTGACATCGAAATCA...  \n",
       "655761  AGCGAAAGCAGGAGTTTAAAATGAATACAAATCAAAGAATAATAAC...  \n",
       "655762  AGCAAAAGCAGGTAGATGTTTAAAGATGAGCCTTCTAACCGAGGTC...  \n",
       "655763  AGCAAAAGCAGGGTGACAAAGACATAATGGACTCCAACACTGTGTC...  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "influenza_na.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(655764, 2)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "influenza_na.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "uniflna = influenza_na.drop_duplicates('sequences')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>titles</th>\n",
       "      <th>sequences</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gi|58576|gb|X52226|Influenza A virus (A/FPV/Ro...</td>\n",
       "      <td>AGCAAAAGCAGGAGTTCAAAATGAATCCAAATCAGAAAATAATAAC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gi|59292|gb|X53029|Influenza A virus (A/USSR/9...</td>\n",
       "      <td>AGCAAAAGCAGGTAGATGTTGAAAGATGAGTCTTCTAACCGAGGTC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>gi|59294|gb|X59778|Influenza A virus (A/NIB/4/...</td>\n",
       "      <td>GGATCCTGTTATGTGCATTTACAGCTACAGATGCAGACACAATATG...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>gi|59296|gb|X66320|Influenza A virus (A/Chile/...</td>\n",
       "      <td>ACACCAAATGGAACGAAAATCAGAACCCTAGAATGTTTTTGGCCAT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gi|60457|gb|X08088|Influenza A virus (A/WSN/33...</td>\n",
       "      <td>ATGAGTCTTCTAACCGAGGTCGAAACGTACGTTCTCTCTATCGTCC...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              titles  \\\n",
       "0  gi|58576|gb|X52226|Influenza A virus (A/FPV/Ro...   \n",
       "1  gi|59292|gb|X53029|Influenza A virus (A/USSR/9...   \n",
       "2  gi|59294|gb|X59778|Influenza A virus (A/NIB/4/...   \n",
       "3  gi|59296|gb|X66320|Influenza A virus (A/Chile/...   \n",
       "4  gi|60457|gb|X08088|Influenza A virus (A/WSN/33...   \n",
       "\n",
       "                                           sequences  \n",
       "0  AGCAAAAGCAGGAGTTCAAAATGAATCCAAATCAGAAAATAATAAC...  \n",
       "1  AGCAAAAGCAGGTAGATGTTGAAAGATGAGTCTTCTAACCGAGGTC...  \n",
       "2  GGATCCTGTTATGTGCATTTACAGCTACAGATGCAGACACAATATG...  \n",
       "3  ACACCAAATGGAACGAAAATCAGAACCCTAGAATGTTTTTGGCCAT...  \n",
       "4  ATGAGTCTTCTAACCGAGGTCGAAACGTACGTTCTCTCTATCGTCC...  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uniflna.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(441221, 2)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uniflna.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "make random sample of sequences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/brian/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: UserWarning: This pattern has match groups. To actually get the groups, use str.extract.\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "uniflna_HA = uniflna.loc[uniflna.iloc[:,0].str.contains(r'(HA)')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(91179, 2)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uniflna_HA.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(83475)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "uniflna_HA_sub1 = uniflna_HA.sample(n=2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2000, 2)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uniflna_HA_sub1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# character kgram function, out is set\n",
    "def charkgram(text, k):\n",
    "    results=set()\n",
    "    for i in range(len(text)-k+1):\n",
    "        if text[i:i+k] not in results:\n",
    "            results.add(text[i:i+k])\n",
    "    return(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def JacSim(a,b):\n",
    "    top = len(a & b)\n",
    "    bottom = len(a | b)\n",
    "    return(top/bottom)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "import itertools as it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "idl=list(it.combinations(list(uniflna_HA_sub1.index),2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1999000"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(idl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "JSresults=[]\n",
    "for i in idl:\n",
    "    JSresults.append(JacSim(charkgram(uniflna_HA_sub1.loc[[i[0]]].sequences.values[0],5),charkgram(uniflna_HA_sub1.loc[[i[1]]].sequences.values[0],5)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(JSresults, 50, range=(0,1));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "uniflna_HA_sub2 = uniflna_HA.sample(n=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "idl2=list(it.combinations(list(uniflna_HA_sub2.index),2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "JSresults2=[]\n",
    "for i in idl2:\n",
    "    JSresults2.append(JacSim(charkgram(uniflna_HA_sub2.loc[[i[0]]].sequences.values[0],5),charkgram(uniflna_HA_sub2.loc[[i[1]]].sequences.values[0],5)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(JSresults2, 50, range=(0,1));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# k=4\n",
    "JSresults3=[]\n",
    "for i in idl2:\n",
    "    JSresults3.append(JacSim(charkgram(uniflna_HA_sub2.loc[[i[0]]].sequences.values[0],4),charkgram(uniflna_HA_sub2.loc[[i[1]]].sequences.values[0],4)))\n",
    "plt.hist(JSresults3, 50, range=(0,1));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# k=6\n",
    "JSresults4=[]\n",
    "for i in idl2:\n",
    "    JSresults4.append(JacSim(charkgram(uniflna_HA_sub2.loc[[i[0]]].sequences.values[0],6),charkgram(uniflna_HA_sub2.loc[[i[1]]].sequences.values[0],6)))\n",
    "plt.hist(JSresults4, 50, range=(0,1));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# k=7\n",
    "JSresults5=[]\n",
    "for i in idl2:\n",
    "    JSresults5.append(JacSim(charkgram(uniflna_HA_sub2.loc[[i[0]]].sequences.values[0],7),charkgram(uniflna_HA_sub2.loc[[i[1]]].sequences.values[0],7)))\n",
    "plt.hist(JSresults5, 50, range=(0,1));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(JSresults3, 50, range=(0,1), color='blue', alpha=0.25)\n",
    "plt.hist(JSresults2, 50, range=(0,1), color='red', alpha=0.25)\n",
    "plt.hist(JSresults4, 50, range=(0,1), color='green', alpha=0.25)\n",
    "plt.hist(JSresults5, 50, range=(0,1), color='orange', alpha=0.25);"
   ]
  },
  {
   "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": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}