{
 "metadata": {
  "name": "",
  "signature": "sha256:708abf61a0baa849adc231139d94b4f9cda1df4ac5cc0e8a0cc39ee79c0f3d1b"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Fasta2Slim"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This IPython notebook is intended to serve as a structured means to annotate sequences using UniProt/SwissProt database. The notebook can be easily modified to personal preferences. As developed, the notebook requires the user has the following software installed ...\n",
      "\n",
      "* IPython\n",
      "* NCBI Blast\n",
      "* SQLShare Python Client\n",
      "\n",
      "---\n"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "PLEASE COPY BEFORE USING"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "**Instructions for use.**   \n",
      "In a working directory of your choosing place query fasta file, naming as `query.fa`. Edit the cell below, providing the path to said working directory. \n",
      "\n",
      "Identify the location of the blast database you would like to use and indicate path in the cell below.\n",
      "\n",
      "Identify the location of your `sqlshare-pythonclient/tools`  and indicate path in the cell below.\n",
      "\n",
      "Change the input to the `usr` variable to reflect your SQLShare user account."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Location Variables\n",
      "wd=\"~/Desktop/test/\"\n",
      "\n",
      "db=\"/Users/sr320/data-genomic/blast/db/uniprot_sprot_r2015_01\"\n",
      "\n",
      "sqls=\"/Applications/bioinfo/sqlshare-pythonclient/tools/\"\n",
      "\n",
      "usr=\"sr320@washington.edu\"\n",
      "\n",
      "blastloc=\"/Applications/bioinfo/ncbi-blast-2.2.30/bin/\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head {wd}query.fa"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        ">comp12018_c0_seq4 len=900 path=[15693595:0-11 15661608:12-155 15693625:156-899]\r\n",
        "GAAACTTTGTCTTAATAAACTTCAGACATGTAGCCATGAGGAAATATCCTTAATCAATTT\r\n",
        "TAATTCTTATGAACTTGGACTACGCCAACTTTAAGTGCCCCAATTAGTCCATAGTATATT\r\n",
        "GGCATTGTATATTCTCTTGGTGAAGTCCGATTCACATTTTTGTGGTAAATAAATGCGTGG\r\n",
        "AGGGAAAACAGATCAAAATGAAATGGATTCGATAAAAAATTCACAATCGTGTACATTATT\r\n",
        "CATTGGCAAAATATCCAAAACTGACACAATGGTAGATTTCATTTTTGCATAAAATGGAAT\r\n",
        "ATAACAAATATAAATGGAATGGATATTTGATAGTCAGAGTTTTCACATACTGCATTTTGA\r\n",
        "GTAACATCGATGGCTAAAAGTGGTGATCACAAAGGTTGTTTATTTAGTATTGGCATCACC\r\n",
        "GTACATCAAAATTAGTCCAAACAGGTTGTTGGTGCTTGAAAAAGTTGAGAAATATTCACC\r\n",
        "ACAAGATATTTAAGATGACTCAGAAGACCAAAACGCATGCTTAAACATTGATGCTGGTGA\r\n"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#number of sequences\n",
      "!fgrep -c \">\" {wd}query.fa"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "2546\r\n"
       ]
      }
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Blast"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!{blastloc}blastx \\\n",
      "-query {wd}query.fa \\\n",
      "-db {db} \\\n",
      "-max_target_seqs 1 \\\n",
      "-max_hsps 1 \\\n",
      "-outfmt 6 \\\n",
      "-evalue 1E-05 \\\n",
      "-num_threads 6 \\\n",
      "-out {wd}blast_sprot.tab"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Number of matched sequences:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!wc -l {wd}blast_sprot.tab "
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!tr '|' \"\\t\" <{wd}blast_sprot.tab> {wd}blast_sprot_sql.tab \n",
      "!head -1 {wd}blast_sprot.tab\n",
      "!echo SQLShare ready version has Pipes converted to Tabs ....\n",
      "!head -1 {wd}blast_sprot_sql.tab "
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Joining in SQL Share"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!python {sqls}singleupload.py \\\n",
      "-d _blast_sprot \\\n",
      "{wd}blast_sprot_sql.tab "
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!python {sqls}fetchdata.py \\\n",
      "-s \"SELECT Column1, term, GOSlim_bin, aspect, ProteinName FROM [{usr}].[_blast_sprot]md left join [samwhite@washington.edu].[UniprotProtNamesReviewed_yes20130610]sp on md.Column3=sp.SPID left join [sr320@washington.edu].[SPID and GO Numbers]go on md.Column3=go.SPID left join [sr320@washington.edu].[GO_to_GOslim]slim on go.GOID=slim.GO_id where aspect like 'P'\" \\\n",
      "-f tsv \\\n",
      "-o {wd}GOdescriptions.txt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head -2 {wd}GOdescriptions.txt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Plot GoSlim terms"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cd {wd}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from pandas import *\n",
      "\n",
      "gs = read_table('GOdescriptions.txt')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gs.groupby('GOSlim_bin').Column1.count().plot(kind='barh', color=list('y'))\n",
      "savefig('GOSlim.png', bbox_inches='tight')\n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}