iDigBio GenBank Investigation Wrap-Up.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's start out by searching iDigBio for all of the records that have an \"associatedSequences\" field."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "22161\n"
     ]
    }
   ],
   "source": [
    "import idigbio\n",
    "\n",
    "api = idigbio.json()\n",
    "seq_query = {\"data.dwc:associatedSequences\": {\n",
    "            \"type\":\"exists\"\n",
    "            }\n",
    "        }\n",
    "seq_count = api.count_records(rq=seq_query)\n",
    "print seq_count"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It looks like only 22,161 records (out of 29,342,343 total records) have an entry for the \"associatedSequences\" field.\n",
    "\n",
    "Now let's try and grab all of the entries so that we can start checking out counts and formats."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import csv\n",
    "\n",
    "PAGE_SIZE = 1000\n",
    "fields = [\"data.dwc:associatedSequences\", \"recordset\"]\n",
    "seq_query = {\"data.dwc:associatedSequences\": {\n",
    "            \"type\":\"exists\"\n",
    "            }\n",
    "        }\n",
    "\n",
    "with open('idigbio_seqs_and_recordsets.tsv', 'wb') as outfile:\n",
    "    tsvwriter = csv.writer(outfile, delimiter=\"\\t\")\n",
    "    for offset in xrange(0,seq_count, PAGE_SIZE):\n",
    "        seq_records = api.search_records(rq = seq_query, \n",
    "                                         limit=PAGE_SIZE, offset=offset, \n",
    "                                         fields=fields, fields_exclude=[])\n",
    "        for seq_record in seq_records['items']:\n",
    "            tsvwriter.writerow([seq_record['uuid'], \n",
    "                                seq_record['indexTerms']['recordset'], \n",
    "                                seq_record['data']['dwc:associatedSequences']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                            recordset uuid  \\\n",
      "specimen uuid                                                                \n",
      "661df25d-8663-4dd2-a9fb-12941e55efe6  fcbcb214-cd62-4453-af56-b4b49161a261   \n",
      "1b5e679a-ced4-45f7-83c6-d81ba72b6ea6  fcbcb214-cd62-4453-af56-b4b49161a261   \n",
      "c6a0379d-6919-4624-a54f-0bf1c7e82318  fcbcb214-cd62-4453-af56-b4b49161a261   \n",
      "01eb3840-f246-49aa-93ca-71400df1a044  fcbcb214-cd62-4453-af56-b4b49161a261   \n",
      "ac37322c-276d-4fbc-80d8-680510a17d8c  fcbcb214-cd62-4453-af56-b4b49161a261   \n",
      "\n",
      "                                                               associatedSequence field  \n",
      "specimen uuid                                                                            \n",
      "661df25d-8663-4dd2-a9fb-12941e55efe6  http://www.ncbi.nlm.nih.gov/nuccore/JN042326; ...  \n",
      "1b5e679a-ced4-45f7-83c6-d81ba72b6ea6         http://www.ncbi.nlm.nih.gov/nuccore/U65280  \n",
      "c6a0379d-6919-4624-a54f-0bf1c7e82318       http://www.ncbi.nlm.nih.gov/nuccore/GQ175238  \n",
      "01eb3840-f246-49aa-93ca-71400df1a044         http://www.ncbi.nlm.nih.gov/nuccore/U65270  \n",
      "ac37322c-276d-4fbc-80d8-680510a17d8c       http://www.ncbi.nlm.nih.gov/nuccore/GQ175236  \n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "columns = [\"specimen uuid\", \"recordset uuid\",\"associatedSequence field\"]\n",
    "idigbio_sequences = pd.read_csv('idigbio_seqs_and_recordsets.tsv', names=columns, sep=\"\\t\", index_col=0)\n",
    "print idigbio_sequences.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "def pull_out_gb_accessions_and_count(seq_string):\n",
    "    pattern = re.compile(\"[a-zA-Z]{1,2}\\-?_?\\d{5,6}\")\n",
    "    matching_accessions = re.findall(pattern, seq_string)\n",
    "    if len(matching_accessions) > 0:\n",
    "        gb_accs = \"|\".join(matching_accessions)\n",
    "        return gb_accs, len(matching_accessions)\n",
    "    return np.nan, 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "idigbio_sequences['extracted_accessions'], idigbio_sequences['sequence_count'] = \\\n",
    "    zip(*idigbio_sequences['associatedSequence field'].map(pull_out_gb_accessions_and_count))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                            recordset uuid  \\\n",
      "specimen uuid                                                                \n",
      "661df25d-8663-4dd2-a9fb-12941e55efe6  fcbcb214-cd62-4453-af56-b4b49161a261   \n",
      "1b5e679a-ced4-45f7-83c6-d81ba72b6ea6  fcbcb214-cd62-4453-af56-b4b49161a261   \n",
      "c6a0379d-6919-4624-a54f-0bf1c7e82318  fcbcb214-cd62-4453-af56-b4b49161a261   \n",
      "01eb3840-f246-49aa-93ca-71400df1a044  fcbcb214-cd62-4453-af56-b4b49161a261   \n",
      "ac37322c-276d-4fbc-80d8-680510a17d8c  fcbcb214-cd62-4453-af56-b4b49161a261   \n",
      "\n",
      "                                                               associatedSequence field  \\\n",
      "specimen uuid                                                                             \n",
      "661df25d-8663-4dd2-a9fb-12941e55efe6  http://www.ncbi.nlm.nih.gov/nuccore/JN042326; ...   \n",
      "1b5e679a-ced4-45f7-83c6-d81ba72b6ea6         http://www.ncbi.nlm.nih.gov/nuccore/U65280   \n",
      "c6a0379d-6919-4624-a54f-0bf1c7e82318       http://www.ncbi.nlm.nih.gov/nuccore/GQ175238   \n",
      "01eb3840-f246-49aa-93ca-71400df1a044         http://www.ncbi.nlm.nih.gov/nuccore/U65270   \n",
      "ac37322c-276d-4fbc-80d8-680510a17d8c       http://www.ncbi.nlm.nih.gov/nuccore/GQ175236   \n",
      "\n",
      "                                                                   extracted_accessions  \\\n",
      "specimen uuid                                                                             \n",
      "661df25d-8663-4dd2-a9fb-12941e55efe6  JN042326|JN042327|JN042415|JN042723|JN042724|J...   \n",
      "1b5e679a-ced4-45f7-83c6-d81ba72b6ea6                                             U65280   \n",
      "c6a0379d-6919-4624-a54f-0bf1c7e82318                                           GQ175238   \n",
      "01eb3840-f246-49aa-93ca-71400df1a044                                             U65270   \n",
      "ac37322c-276d-4fbc-80d8-680510a17d8c                                           GQ175236   \n",
      "\n",
      "                                      sequence_count  \n",
      "specimen uuid                                         \n",
      "661df25d-8663-4dd2-a9fb-12941e55efe6               9  \n",
      "1b5e679a-ced4-45f7-83c6-d81ba72b6ea6               1  \n",
      "c6a0379d-6919-4624-a54f-0bf1c7e82318               1  \n",
      "01eb3840-f246-49aa-93ca-71400df1a044               1  \n",
      "ac37322c-276d-4fbc-80d8-680510a17d8c               1  \n"
     ]
    }
   ],
   "source": [
    "print idigbio_sequences.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "34185\n"
     ]
    }
   ],
   "source": [
    "print idigbio_sequences['sequence_count'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x108992b10>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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iRAMAAACGCNEAAACAIUI0AAAAYIgQDQAAABgiRAMAAACGCNEAAACAIUI0AAAAYIgQDQAA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\nAIYI0QAAAICh/wdIVqEe1jYQvwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1087b6e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "plt.rcParams['figure.figsize'] = 12, 5\n",
    "\n",
    "plt.style.use('ggplot')\n",
    "\n",
    "vc = idigbio_sequences['sequence_count'].value_counts()\n",
    "vc = vc.sort_index()\n",
    "\n",
    "vc.plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "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": "2.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}