{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# epitopepredict advanced analyses\n",
    "\n",
    "### References:\n",
    "* Paul, S. et al., 2015. Development and validation of a broad scheme for prediction of HLA class II restricted T cell epitopes. Journal of Immunological Methods, 422, pp.28–34. Available at: http://dx.doi.org/10.1016/j.jim.2015.03.022.\n",
    "* Terry, F.E. et al., 2014. Time for T? Immunoinformatics addresses vaccine design for neglected tropical and emerging infectious diseases. Expert review of vaccines, 9, pp.1–15. Available at: http://www.ncbi.nlm.nih.gov/pubmed/25193104.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "pd.set_option('display.width', 100)\n",
    "pd.set_option('max_colwidth', 80)\n",
    "%matplotlib inline\n",
    "import matplotlib as mpl\n",
    "import seaborn as sns\n",
    "sns.set_context(\"notebook\", font_scale=1.4)\n",
    "from IPython.display import display, HTML\n",
    "\n",
    "import epitopepredict as ep\n",
    "from epitopepredict import base, sequtils, analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predictions done for 9 proteins in 6 alleles\n",
      "results saved to /home/farrell/gitprojects/epitopepredict/examples/test_iedbmhc1\n"
     ]
    }
   ],
   "source": [
    "genbankfile = '../testing/zaire-ebolavirus.gb'\n",
    "zaire = sequtils.genbank_to_dataframe(genbankfile, cds=True)\n",
    "savepath = 'test_iedbmhc1'\n",
    "Pi = ep.get_predictor('iedbmhc1')\n",
    "alleles = ep.mhc1_supertypes\n",
    "Pi.predictProteins(zaire,length=11,alleles=alleles,path=savepath,overwrite=False)\n",
    "Pi.load(path=savepath)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Binder clustering for finding regions with possible epitopes\n",
    "\n",
    "One application of immunoinformatics is to screen out likely candidate antigens from the genome for further study. To do this using epitope prediction requires filtering the many potential binders in each protein. There is no theoretical basis for doing this.\n",
    "\n",
    "**Epitope clustering** has been previously observed to be an indicator of T cell epitope regions. The `findClusters` method in the analysis module allows automatic cluster detection from a set of predicted binders from one or more proteins. It can be done for a whole genome.\n",
    "\n",
    "The result is a table of sequence regions with the number of binders and density of epitope cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "40 clusters found in 7 proteins\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>binders</th>\n",
       "      <th>clustersize</th>\n",
       "      <th>gene</th>\n",
       "      <th>peptide</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>1451</td>\n",
       "      <td>1481</td>\n",
       "      <td>7</td>\n",
       "      <td>30</td>\n",
       "      <td>L</td>\n",
       "      <td>FTTHFLTYPKIGLLYSFGAFVSYYLGNTIL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ZEBOVgp1</td>\n",
       "      <td>176</td>\n",
       "      <td>215</td>\n",
       "      <td>6</td>\n",
       "      <td>39</td>\n",
       "      <td>NP</td>\n",
       "      <td>QVHAEQGLIQYPTAWQSVGHMMVIFRLMRTNFLIKFLLI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>95</td>\n",
       "      <td>118</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>L</td>\n",
       "      <td>CQQFLDEIIKYTMQDALFLKYYL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>1962</td>\n",
       "      <td>1987</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "      <td>L</td>\n",
       "      <td>VFLSDTEGMLWLNDNLAPFFATGYL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ZEBOVgp5</td>\n",
       "      <td>224</td>\n",
       "      <td>249</td>\n",
       "      <td>4</td>\n",
       "      <td>25</td>\n",
       "      <td>VP30</td>\n",
       "      <td>ALWQQWDRQSLIMFITAFLNIALQL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ZEBOVgp4.2</td>\n",
       "      <td>15</td>\n",
       "      <td>35</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>GP</td>\n",
       "      <td>RTSFFLWVIILFQRTFSIPL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>139</td>\n",
       "      <td>158</td>\n",
       "      <td>3</td>\n",
       "      <td>19</td>\n",
       "      <td>L</td>\n",
       "      <td>IQGNEFLHQMFFWYDLAIL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ZEBOVgp1</td>\n",
       "      <td>142</td>\n",
       "      <td>160</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>NP</td>\n",
       "      <td>TEANAGQFLSFASLFLPK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>ZEBOVgp4.2</td>\n",
       "      <td>225</td>\n",
       "      <td>252</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>GP</td>\n",
       "      <td>GTNETEYLFEVDNLTYVQLESRFTPQF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>ZEBOVgp3</td>\n",
       "      <td>165</td>\n",
       "      <td>186</td>\n",
       "      <td>3</td>\n",
       "      <td>21</td>\n",
       "      <td>VP40</td>\n",
       "      <td>VQLPQYFTFDLTALKLITQPL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>1625</td>\n",
       "      <td>1642</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>L</td>\n",
       "      <td>YTCKSTASNFFHASLAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>393</td>\n",
       "      <td>419</td>\n",
       "      <td>3</td>\n",
       "      <td>26</td>\n",
       "      <td>L</td>\n",
       "      <td>TVLKALRPIVIFETYCVFKYSIAKHY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>1521</td>\n",
       "      <td>1533</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>L</td>\n",
       "      <td>RLMSIDPHFSIY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>295</td>\n",
       "      <td>312</td>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>L</td>\n",
       "      <td>KFLEPLCLAKIQLCSKY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>1547</td>\n",
       "      <td>1562</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>L</td>\n",
       "      <td>RLFLRTSISSFLTFV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>1795</td>\n",
       "      <td>1816</td>\n",
       "      <td>2</td>\n",
       "      <td>21</td>\n",
       "      <td>L</td>\n",
       "      <td>SVIDTTVYCRFTGIVSSMHYK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>1074</td>\n",
       "      <td>1088</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>L</td>\n",
       "      <td>RKITLQRWSLWFSY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>941</td>\n",
       "      <td>953</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>L</td>\n",
       "      <td>MIEMDDLFLPLI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>901</td>\n",
       "      <td>914</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>L</td>\n",
       "      <td>ALAVPQVLGGLSF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>ZEBOVgp7</td>\n",
       "      <td>858</td>\n",
       "      <td>874</td>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "      <td>L</td>\n",
       "      <td>ITAAFHTFFSVRILQY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          name  start   end  binders  clustersize  gene                                  peptide\n",
       "0     ZEBOVgp7   1451  1481        7           30     L           FTTHFLTYPKIGLLYSFGAFVSYYLGNTIL\n",
       "1     ZEBOVgp1    176   215        6           39    NP  QVHAEQGLIQYPTAWQSVGHMMVIFRLMRTNFLIKFLLI\n",
       "2     ZEBOVgp7     95   118        5           23     L                  CQQFLDEIIKYTMQDALFLKYYL\n",
       "3     ZEBOVgp7   1962  1987        5           25     L                VFLSDTEGMLWLNDNLAPFFATGYL\n",
       "4     ZEBOVgp5    224   249        4           25  VP30                ALWQQWDRQSLIMFITAFLNIALQL\n",
       "5   ZEBOVgp4.2     15    35        4           20    GP                     RTSFFLWVIILFQRTFSIPL\n",
       "6     ZEBOVgp7    139   158        3           19     L                      IQGNEFLHQMFFWYDLAIL\n",
       "7     ZEBOVgp1    142   160        3           18    NP                       TEANAGQFLSFASLFLPK\n",
       "8   ZEBOVgp4.2    225   252        3           27    GP              GTNETEYLFEVDNLTYVQLESRFTPQF\n",
       "9     ZEBOVgp3    165   186        3           21  VP40                    VQLPQYFTFDLTALKLITQPL\n",
       "10    ZEBOVgp7   1625  1642        3           17     L                        YTCKSTASNFFHASLAY\n",
       "11    ZEBOVgp7    393   419        3           26     L               TVLKALRPIVIFETYCVFKYSIAKHY\n",
       "12    ZEBOVgp7   1521  1533        2           12     L                             RLMSIDPHFSIY\n",
       "13    ZEBOVgp7    295   312        2           17     L                        KFLEPLCLAKIQLCSKY\n",
       "14    ZEBOVgp7   1547  1562        2           15     L                          RLFLRTSISSFLTFV\n",
       "15    ZEBOVgp7   1795  1816        2           21     L                    SVIDTTVYCRFTGIVSSMHYK\n",
       "16    ZEBOVgp7   1074  1088        2           14     L                           RKITLQRWSLWFSY\n",
       "17    ZEBOVgp7    941   953        2           12     L                             MIEMDDLFLPLI\n",
       "18    ZEBOVgp7    901   914        2           13     L                            ALAVPQVLGGLSF\n",
       "19    ZEBOVgp7    858   874        2           16     L                         ITAAFHTFFSVRILQY"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#find clusters of binders in these results\n",
    "pb = Pi.promiscuousBinders(cutoff=5,n=2)\n",
    "cl = analysis.find_clusters(pb, dist=10, min_size=3, genome=zaire)\n",
    "display(cl[:20])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## plot regions on sequence \n",
    "We can use this to see where our clusters are in the sequence, for exmaple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "name = 'ZEBOVgp6'\n",
    "#ep.plotting.plot_multiple([Pi], name, regions=cl, n=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## overlaps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/farrell/gitprojects/epitopepredict/epitopepredict/base.py:826: FutureWarning: convert_objects is deprecated.  Use the data-type specific converters pd.to_datetime, pd.to_timedelta and pd.to_numeric.\n",
      "  df = df.convert_objects(convert_numeric=True)\n",
      "/home/farrell/gitprojects/epitopepredict/epitopepredict/analysis.py:165: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  df[label] = df.apply(lambda r: overlap(r,found),axis=1)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predictions done for 9 proteins in 7 alleles\n",
      "results saved to /home/farrell/gitprojects/epitopepredict/examples/test_netmhciipan\n",
      "17 with overlapping binders\n",
      "        name  start  end  binders  clustersize  gene                peptide  mhc2_ovlp\n",
      "28  ZEBOVgp6    142  158        2           16  VP24       EQLSLKMLSLIRSNIL          2\n",
      "29  ZEBOVgp6     86  107        2           21  VP24  IESPLWALRVILAAGIQDQLI          0\n",
      "30  ZEBOVgp6     68   80        2           12  VP24           WSMTRNLFPHLF          0\n"
     ]
    },
    {
     "data": {
      "image/png": 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NDUNpbBxTkryqsX75TJgwngULXuk5Yi81Nzdz8MGTS55vKekzvrVS3betrcsZ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\n6/tUqoHe3nzjclWuHG2TJgz4fgfbo48+QldX16Dtv6kpzbJlvwNg3Lh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j98MgjOzo7u8h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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc9fd4d5b10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Pn = ep.get_predictor('netmhciipan')\n",
    "savepath2='test_netmhciipan'\n",
    "alleles2 = ep.mhc2_supertypes\n",
    "Pn.predictProteins(zaire,length=11,alleles=alleles2,path=savepath2,overwrite=False)\n",
    "Pn.load(path=savepath2)\n",
    "\n",
    "cl = analysis.get_overlaps(cl,Pn.promiscuousBinders(n=2,cutoff=5),label='mhc2_ovlp')\n",
    "\n",
    "#plot both sets of binders and overlay region of cluster in previous data\n",
    "ax = ep.plot_tracks([Pi,Pn],name=name,legend=True,figsize=(14,4),n=2)\n",
    "r = cl[cl.name==name]\n",
    "print r\n",
    "coords = (list(r.start),list(r.end-r.start))\n",
    "coords = zip(*coords)\n",
    "ep.plot_regions(coords, ax, color='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## conservation analysis\n",
    "Conservation of epitopes may be important across strains or species."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25 non-redundant sequences retrieved\n"
     ]
    },
    {
     "data": {
      "image/png": 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sBkkLAUhqA24BDgBOw4shrwjch8cTbdZEx4Xwciz9Je2QtXs4a1N7zcXYFYLt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\nO/Ph6SfWMKa538yGm/uL7iSnfLCatWxi2sKWTOJWcrsMf14TfldS69aXu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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc9f91151d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "reload(ep.base)\n",
    "reload(analysis)\n",
    "reload(sequtils)\n",
    "\n",
    "name = 'ZEBOVgp2'\n",
    "proteinseq = zaire[zaire.locus_tag==name].translation.iloc[0]\n",
    "#print proteinseq\n",
    "#print pb\n",
    "seqs = pb.peptide\n",
    "\n",
    "#provide a list of seqs (e.g. strains)\n",
    "filename='ebola_VP35.fa'\n",
    "r = sequtils.fetch_protein_sequences('Filovirus[Orgn] AND VP35[Gene]', filename=filename)\n",
    "#align fasta sequences\n",
    "aln = sequtils.muscle_alignment(filename)\n",
    "#sequtils.showAlignment(aln)\n",
    "alnrows = sequtils.alignment_to_dataframe(aln)\n",
    "\n",
    "#print (sequtils.formatAlignment(aln))\n",
    "#print alnrows[:25][['accession','definition','perc_ident']]\n",
    "c = analysis.epitope_conservation(seqs, alnrows=alnrows)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## use a local blast database to find orthologs and conservation of your epitopes\n",
    "Blast the protein sequence locally to get an alignment with any orthologs, then perform the analysis as above. In this case we have created a blast database of viral refseq proteins locally. Online blast is generally too slow for such an analysis, especially if we want to examine epitopes in many proteins."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running blast..\n",
      "7 hits, 7 filtered\n",
      "          expect  identity       accession                                          definition  \\\n",
      "0   0.000000e+00       260  YP_003815424.1  polymerase complex protein [Tai Forest ebolavirus]   \n",
      "1  8.425780e-175       254  YP_003815433.1       polymerase complex protein [Bundibugyo virus]   \n",
      "3  1.446050e-155       222     YP_138521.1       polymerase complex protein [Sudan ebolavirus]   \n",
      "2  5.109200e-161       219     NP_690581.1      polymerase complex protein [Reston ebolavirus]   \n",
      "4  3.717640e-106       170  YP_004928136.1      polymerase complex protein [Lloviu cuevavirus]   \n",
      "5   4.452270e-62       119  YP_009055223.1   polymerase complex protein [Marburg marburgvirus]   \n",
      "6   2.145860e-61       118  YP_001531154.1   polymerase complex protein [Marburg marburgvirus]   \n",
      "\n",
      "   perc_ident                                                                              seq  \n",
      "0   76.470588  ISTRAAAINDPSLPIRNQCTRGPELSGWISEQLMTGKIPVHEI--FNDTEPHISSGSD---CLPRPKNTAPRTRNT...  \n",
      "1   74.705882  -------------TTTGTRSCGPELSGWISEQLMTGKIPITDI--FNEIETLPSISPS---IHSKIKTPSVQTRSV...  \n",
      "3   65.294118  ------------------RHHGPEVSGWFSEQLMTGKIPLTEV--FVDVENKPSPAPI---TIISKNPKTTRKSDK...  \n",
      "2   64.411765  ---------------------GPETTGWISEQLMTGKIPVTDI--FIDIDNKPDQMEV---RLKPSSRSSTRTCTS...  \n",
      "4   50.000000  ----------------------------VTDAIMTGRLSLDTIPGFQCSAPTSRSRPTGRKCPPWEGPLIEPKTSA...  \n",
      "5   35.000000  ----------------------------VSEGLMTGKVPIDQVFGTNPLEKLYKRRKP----KGTVGLQCSPCLIS...  \n",
      "6   34.705882  ----------------------------VSEGLMTGKVPIDQVFGANPLEKLYKRRKP----KGTVGLQCSPCLMS...  \n"
     ]
    },
    {
     "data": {
      "image/png": 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sAhxabX8V5fyrN+4A1oqIv1IS/6HkaTvglsai6hGTJ7XBR4GTgZcBe1dF44dS\n/sNu1mhk7bIncAblU+PhmXlbRBxJGSHZoNHI2uMY4GzKqOltwMURsQvwNWCfJgNrkTOB04DHKB+4\nzo+I91KSqGOaDKxl9gNOouQZ52TmbyPiIMr0/3sajawHLBhXK0XEApn5WNNxtE11ZeMimflgdX9x\n4AGvtOudiHgP5YPAKZl5b0SsB8yTmefN5qkahYiYF/gY5Rx/KzNvjohtKNP/R2amb4o9EhGLAS/O\nzN9W9wP4R2be22xkY2fypL4XEdvO6vHMPGGiYmmziFhjVo9n5s9m9bikuUdELD2rxzPzjomKZTw4\nbac2+GLX/XmBF1CmPq6kFIJq7C4aYfvjwJ8pNSMag4i4GxjxE21mLjmB4bRSRFzOrM/xahMYTpvd\nzszzPNBxexCYAczXRFC9YvKkvpeZL+3eFhELA0cB1098RO2Umc+4OjciplDqyg4Dvt9IUO3z2a77\n81LO8XbDPKY50/0hYF5gaWB9oK97D00yS3XdH/pdnsZ/f+DtO07bqbUiYhngF5m5eNOxtFlEvBq4\nYLgkVr0RERsAe2XmKk3H0lZV3dOWmbl+07G0WUS8ETg5M/t6pNo+T2qzFYBnNR3EXGBxSrGtxs8t\nwBuaDqLlfgGs3nQQc4kXNx3AWDltp74XEZfw3zUMCwErMrOHi8YoIoarHVsIWIOypIjGaISi/IWA\nXSlLiWiMRihkXgjYA7hrYqNpr4gYbgp0IWBT4CcTHE7PmTypDbrXohqkFIt/lhb8J51Enu66Pwjc\nC+wOnDjx4bTScEX5/wauogVLWkwSnYXMQwaAu4EdJj6c1lq16/7Q3+XjacEyOCZPaoPFgIMy8/am\nA2m5O4HjMvNPTQfSYq+lrAFmMer4WZnSHHPI0Jv6vZ73njoROC8zpzcdyHgweVIbbAF8pekg5gK7\nY9uH8fYzyvqM1zQdSIudDWyUmdc2HUjLHQxcBpg8SZPU14FvRsQhwB8pfYf+w5GSnjkRmBYRBzL8\neZ7RSFTt8mdKMa3J0/h5HJi/6SDmAhdR1sL8UmY+2nQwvWbypDYYKkxch2fWMgw1Zpsy4RG108aU\nN/ZtRnjc8zx2vwN+EBHXUYqXuxPUWXbT16hcAPwkIs5n+HP8uSaCaqGXUIrD946I+/nv89zXDV9N\nntQGyzQdwFzi/U0HMBcYBL7XdBAt9xrgakqt5GJdj1nz1DtHVV+tZJNMSZKkGhx5Ul+KiKeBF2bm\n9IiYwayh1/1sAAAgAElEQVTXqnI6aQ5FxJ+AlTLzftddGx9VP5yvZOajI/TGGTKYmftNVFxtEhE7\nACdl5hPV7ZEMZuaxExVX20TEZcCGmfmPtq8haPKkfvUu4IHq9lpNBtJy+wKPVLddW218rEq56OFR\n/rs3TienCebcvsA5wBPV7ZEMAiZPc+5iStsHGHkh8VZw2k59LyK+BJySmTc0HUubRcQuwOmZeV/T\nsbRVRCySmf9sOo42i4h5vDJ0/EXEesCFmdndXLcVTJ7U9yLip8DbgduA0yiJ1G3NRtU+EfF7SnH+\npcApwJm+0fdWRDxBuRrsVOCHmfmvhkNqnYj4K2U5oVMz81dNx9NWEfEgZVWCMyl/Ly5tUxNSkye1\nQkQ8H9gE2IyyuOeNlP+wp9nnqXci4jWUc7w58ArK8jenAuf4Rj92EfFmyvndjHIl2I8p5/dHmflE\nk7G1RUS8l3J+1wPuA75PSaRsmtlDEfEsYG3Kud4IeAw4g3Kur2gytl4weVLrRMTzKOuA7QM8x4Lx\n8RERywPvBT4JDGTmQg2H1CoR8SZmvvEsTklQt2s2qvaIiGcDG1DO8drAPZQ3dovye6xKpNai9Ip7\nL/BAZi7VbFRjY8G4WiMiXkFpyrYp8DrgEsrok3ooIhYC3k05z++idBv3PPfebylJ03Mpbzj/02w4\n7VJ1vf5+RNwM3AJ8ovoyeeq9lYE1gXcAT9GCYnKTJ/W9iNiPMmX3auCXwHGUwua/z+p5qiciPkg5\nz2tSlhE5DdgvM29sNLAWqUZD1qckpusC/6Sc5zUy8+omY2uTiFiZco43oXTN/zGwA3Bek3G1SUSs\nSTm/GwMLAz+krI95YWY+2WRsvWDypDbYADieUt/0l6aDabH9KfUh+2fmb5oOpqXuBx4CfgBskJmX\nNxxP61S9yxanXFb/BeDszHy42aha6TzgfMq0/rmZ+VjD8fSUyZP6XmauPNJjEfHCzPzbRMbTYi9t\n09Uyk9TGwEVtvbx7kvgicEZm3t90IC23eGY+1HQQ48WCcfW9iAjgQMq03VBx+ABl5fSpmemHBPWN\niHgjw/8ur5SZOzYWWItExBJAMPw5/mJjgbVIRCwI7MzIv8t9vSapbypqg28D8wGHAAcDnwZeTvmP\n+8HmwpLqiYj9KR2w76FMLf2l+j4vZSpPYxQROwOHUc7pIOUNner2rykjUxq77wBrUIrDN6fU7i1D\nKR6f1lxYvTFP0wFIPbAy8JHM/CZwLXBDZu5OuXJmVutYSZPNjsDOmfki4G7K1UmLAz8F7mourFbZ\ni5IgLQDcC7wMeA1wHWUJF/XGOsDWmbk1cBNwSGa+mfIhd4VGI+sBkye1wZPAg9XtW4DXV7cvBFZs\nJKIWi4jlImKTiNg8Il7bdDwt83xKh3Eob+Zvzcx/UHqWbdFYVO3yIuD4qunotcD/ZOZNlA9bTov2\nzvzArdXt31M+5AIcBfT1osBg8qR2uALYPSL+H3A1sGFEDABvBB5vNLIWiYjnRsS5lD+E366+rouI\nSyNikWaja40/A0tXt29m5geBh4EXNBJR+9xL6d4O5cPWStXtv1ASK/XGTcxctP1GZi56/VxKYtXX\nrHlSG+xO6SHyJ8qnmk8ADwALYv1CLx0OLAEsl5kJ/+kyfhzwdawv64WjgdMi4gPA2cDFEXEvpbfW\nbxuNrD1OBU6IiA9RRvlOiojfUlqeuCZm7+wHnBERU4ATgZsi4nzKFOkFs3xmH3DkSX2vGnJfBjgq\nMx+hjDhtD6yemdMaDK1t3k2px8mhDdW535Vyib3GKDMPpHwY+FfVS+uTlOVDZmBy2it7A98Dnp+Z\nF1FGUI+gTCvt0mRgbZKZ5wHLAj/LzLuBVSgjUEfSglpUWxWoL0XEkqPd14WBeyMi7gHWz8xrura/\nkdKbaNFmIpM02UTEV4FTMvO6pmMZD07bqV/dRbm0uNNAx+2hS5AHmdljRGPzQ+DIiNg2M2+F//TY\nOgI4t9HI+lhEnDDafTNz2/GMpa0i4vOj3TczPzeescxFVgA+HhF3UdoUnFqNVLeCyZP6VV83WOtT\nn6LU4dwSEUOdgxcCfgR8rLGo+p/dxMffqrPfBfjvD2SaQ5m5bkQsCryHMvX86YhISs3ZqZl5R6MB\njpHTdmqNiFgLWI4y0nQLZSqp7xegnGyq9gTLAo8BOTQKJUkjqa7I/TDwWeA5mdnXMwKOPKnvRcRL\nKM3tlqNcLTMFeAVwR0SslZl/bTK+toiI31EKbU/NzO83HU9bRcSmlFG+ZSl/oxM4PDOPbTSwFqnq\n9P6XmR+2EjgiM3/WaGAtFBHLApsAm1KutPspcEqjQfWAV9upDY4E/k5ZuHbFzHwNsCSlZ843Go2s\nXY4E1gb+EBG/jIiPRsTUpoNqk4jYBTge+BnwfuB9lOUtDqsurdcYRcRmlN5wM5jZr+wp4IKI2KjJ\n2NokIr4QEb8HbqC02jgKWCIzN8jMk5qNbuyctlPfi4hHgLdk5o1d218LXJ6ZNnDsoWpR1c2qrzcD\nl1E+SZ7Z5lXUJ0JE3AFMy8wTurZvC+yTmdFMZO1RvaF/OzO/0bX9E8D2mfm6ZiJrl4j4FeXvwvcz\n856m4+k1R57UBg9SutZ2WxT49wTH0nqZeU9mHkHpifMNSjHu/wF/i4jjI+KFjQbY36ZSRkW6/Yoy\nmqqxWwo4b5jt5wEmpz2Smf+TmYcBUyJi9YhYICIWbzquXrHmSW1wKnB0ROwK/Kba9mbKJfSnNRZV\nC1UdxTevvpahTCntBJxFWT7km5Q3oTc0FWOfuw7YDti3a/v2lGVxNHY3A+tSOuZ3Wh+4c+LDaaeI\neA5l9YFNKVOkrwIOiYjFgI0zc3qD4Y2ZyZPaYF/ghZRCxCFD9Qz/20hELVRNdwRlFORIynD8/R27\n/CsijqUsMaI58ynKkizvBK6str2Z0jNn/caiapf9gB9ExFt55jneBNi6saja5+uUD1RLUTqLA+xB\nqek7DNiyobh6wpontUZEPJ/y5v4YcHtmPtxwSK0SEZ+iXGk3Ysf2iHg2MJiZj01cZO0SEcsBOzKz\nHcQtwDcz8y+NBtYiEbEGZVmh5Zh5jr/e3T1fcy4i/gasl5nXRcTDwIqZeUdErAhckpnPazjEMXHk\nSa0QEQtRhoeXo9Q53RQRp2bmE81G1iqnwrBL4wxSzvnfM/PRCY+qZTLzZmD36sPAv/0Q0HtVSwLb\nEoyvBRi+5nR+nrkaRF9y5El9LyLeQam5+QdwPeVCiJWqh9fLzBsaCq1VIuJJZl5kMvTHr/MPyJOU\nDuQ7+oY/ZyJiPkoTwZ2B51eb/wYc1H11mOZcROxAOcfLUn5vb6ac47MbDaxFIuJ4yoU82wJ3A6+l\nDNh8D7g1M7dpMLwx82o7tcGhlMLEV2Tmxpm5IWWe/cfAd5oMrGU+TGlCui6wCOVqxrWAm4DPUK66\nW5xS66A5cwSlYHxPYEXKh4D9gU9FxJebDKwtIuJLwEGUCxu2Bj4A/Bw4oWpXoN74GCUxvR94DvBb\nyvTo/cDHG4yrJxx5Ut+LiMco8+m3dm1fFrg2M5/dTGTtEhF3A+/NzCu6tr8FOD0zXxoRKwE/yczF\nGgmyz0XEP4ENMvPyru3vBE7LzOcP/0yNVkRMB3bIzPO6tm9G6eRuq40eioilKeUU81KWc7ql4ZB6\nwpontcGFwHuBL3Rt35jyiVK9sRClE3O3QcpIFMBDwHwTFlH7/JPyab3bw9izrJeGu+jhdko9jnqg\nSpqG3Ny9vd8XBjZ5Ul+KiGM67j4NTIuI9YCrKG0KVgBWA44Z5umaM2cAx0XEx4CrKXVPb6A0yjy7\nutJub2b22tIodL3JHA4cHxGfpJzjod/lwyiX2GsORERnicoBwLci4oOZeVP1+FKU6f8vNhFfS93O\nM2sihwxSfq/7+kOWyZP61bM6bj8KnFzdHuo0/lfK1WELTGRQLfdRypv7j5h5/p8EjqXU6KwFvB57\n5dTV+SYzVIg/NKU02LHt/7CH1px6ime+kQ8AN0TE49X2BarvywEHT3x4rbRU1/15KQu2T6MFSao1\nT5JqqToHL0t5Q7o9M//VcEh9LSJeNtp9M/OP4xlLW0XE20e7b2Y61T+OIuKNwMmZ+aqmYxkLkye1\nQkSsDXyCsmTImpQraP6UmU7b9UjVWHBEVe8c9UBEvI2ynMUZwMuA2+xZ1lsR8WLKOf41sHBm3ttw\nSHOFKnn6eWY+p+lYxsJpO/W9iNiaslzI4cDbgSnAA8DhEbFgtTilxu6iEbY/DvyZ8kakMYiIqZQp\nu1dTipd/TpniWCEi3pWZtzcZXxtExIKUqeZWrrk2WUTE54fZPNTM+CcTHE7P2edJbbAXsHNmfo5S\nPE6VMO1AGY1SD2TmPJ1flLqnZYHLgK80G11rHA7cRVkTbGiJm22A31GKxjV2BzNzzbWhc7wHpebJ\nc9w7q3Z9rUKpKTue8re5rznypDZ4JcNf4XUNZcFgjYPMfBq4NSL2AC7AKxt7YU1gtcx8LCIAyMyH\nImIvZi5iq7HZkLLywB87zvHtEbELcEmjkbVIZq4OEBEDmTlY3V40M//RbGS94ciT2uD3wDod94cK\n+bZj5mreGj+LM7PPk8ZmBjBcU9cXUqZHNXatXnNtsoiIxSPiQp7Zf++WiDgvIl7QVFy94siT2mBP\n4NyqoHk+YJ+IWAZ4E7BBo5G1SEScMMzmhYA1gNMnOJy2OplSq7cz5UPAwhGxFqWm7/uNRtYe5wBf\njohtq/uD1d+Lw5nZIkJj963q+3c7tq1KWYLocGCrCY+ohxx5Ut+rLi1elrLu2o8pIyFXActn5sVN\nxtYyT3d9PQXcC+wOfKTBuNrkU8AVlCm6BYFrKX21Lqoe09i1es21SWR14GOZeefQhsy8jVKHus6I\nz+oTtiqQpEkmIhYAlqbMDvwhMx9pOKTWaeuaa5NFRPwZ+GBmXti1/Z3ASZm5eDOR9YbJk6RRq6ZG\nd6a86fybsmbVwZl5XaOBSZpUqlYFOwD7UkZQAVYC9gdOzcxPNxVbLzhtJ2lUIuLjlGnRRyj1DMdX\nD/0qIrZsLDBJk9E0Sj+trwDXVV8HUv52fKa5sHrDkSdJo1INw38mM0/o2v5hYK/M7F7LSpKorq77\nd2Y+1HQsveLIk/peRBxddQ3u3v7ciDi1iZhaakFKIX63X1CaDkrSf8nMv7cpcQJbFahPRcRbKc0x\nAT4I/C4iuv9zLgusN6GBtdvhwIERsV1mPggQEc+mDM9/a1ZP1OhFxLLAGykd3J/Rd8i1GnsjIhYF\nXsPw59g1GjVbJk/qV48BB1D+8A0Ae1MaDA4ZpNTm9HVRYtMi4m5mNh0dAF4M/DUi7qSc76UozQUt\nGO+BqpP4lyhrMz7c9fAgdnEfs4jYDvgmpVlmt0HK2pjSLJk8qS9VV3ctCRARlwMbDo2GqKf2ZWby\npPG3O/CpzDyo6UBa7ADgaOBzmdmdoEqjYsG4WqGqeXoyM5+IiOUoTdiuzszLGw5NGrWI+Afw+sy8\no+lY2ioiHgFek5l3NR1Lm1WtCkZULeTetxx5Ut+LiHUoS1dsEhG3Uzo03w+8KCJ2y8zvNBpgH4uI\nyyijev+oRvhG/LSVmatNXGStdSKwa0TsObSYqnruh8CmwMFNB9Jyq3bdn5cyzf9c4LSJD6e3TJ7U\nBl8Bvgb8jNKA7V5KE8f3UPqKmDzNuYuZuYjqxTiFN95eAGwCvC8i7qJrAVsT1J6YDnyx6k32B/77\nHG877LNUS2auPtz2iDiIFuQeff8DSEAAx2XmjIh4N3B2Zg5GxDWUAmfNoczcv+P2tAZDmVvcQikY\n1/hZBDil6SDmYkdSLjD5RNOBjIXJk9rgb8AKEbEI8Frgo9X2tYA/NhZVC0TEqK/uyswdxjOWuUFn\nsqrxkZkfaDqGudy7KVdL9zWTJ7XBIcCZlEvnf5OZv4iIz1D6D/mGPjbP6ri9AGVK6RrgasrK9CsB\n/wOc8N9PVV3VhQ87A69m5iXzA5R2ECtl5jJNxdYmEbEp8ClKL7h5gQQOz8xjGw2sRbranAxZCFgY\n2HPiI+otkyf1vcw8PCJ+DbyMsvYawKXAWzLz2hGfqNnKzG2GbkfEKcD+3aMjEfFp4O0THVtLfQdY\nA7gI2JxSWLsMsDLlw4DGKCJ2Ab5Kafp6ACVJfStwWERM8QKTnuluczJIqS+7OjNvbyak3jF5Uitk\n5lURMQ+waUScDTwI9P1/0ElmQ2C4y4vPGmG76lsH2CwzL4qIVwOHZOY1EXEwsELDsbXFnsAuXWs0\nnh0RNwL74AUmPZGZxzUdw3gyeVLfi4jFgHMoU0jPAn5Jucpu+Yh4lz1zeuZWyjTo3kMbqoT148AN\nTQXVMvNTzjPA7ykjTtcAR1HWENTYTaW0M+n2K6rGu5ozc1NrE5MntcFhlKLxtYB7qm3bUnrmHAZs\n0FBcbbMbcG5EbE5JlgYoCev/A9ZuMrAWuYnye/xd4EZKr5yjKL1x5m8wrja5DtiOMq3UaXtKwqo5\n19na5KImAxlvJk9qg7WA1TLzXxEBQPXJ51PArxuNrEUy8/KIeCXwXkofLYALgFMz8x/NRdYq+wFn\nRMQUSvJ/U0ScT1nE9oJGI2uPTwEXR8Q7gSurbW+mTIuu31hULdBVD3kVcGFmPt1UPOPJ5EltMMjw\ni3wuDjwxwbG0Wmb+ndKnReMgM8+LiGWBeTPz7ohYBXg/8HPKKKrGKDN/FRFvAD5E+RDwGKXB7maZ\n+ZdGg2uXk4CnI+JMSl+tS9vUNd+17dT3IuIw4PXAhyl1C2+jdGo+CrgoM3dtMLzWiIilKA0cV6bU\nlg10Pp6Z1oto0ouIzwEHZeajXdsXBvbLzD2aiaxdIuJZlOn8zYCNKEnqGZSR6uFqzvqKyZP6XkTM\nR1meZWfKm/og8DRwHPDxzOz7hmyTQUT8Ange8H/AQ92PZ+bxEx5UC0TEnYxy2ZvMXHqcw2mliFge\nWKK6+1NKG4juqeZXA1/JzOdMZGxzgyqRWgvYmDLt/0BmLtVsVGPjtJ3aYFXKFWD7AK+g/F7fnpn/\nbDSq9nkD8IbMvKnpQFrmgI7bL6dcvfgtZjYifT3wEeDQCY+sPabyzALmM4bZ5xHgoIkJZ66zMrAm\n8A7gKVpQTO7Ik/peRNwPvCMzvVx+HEXE9ZSRvEubjqWtIuI3wNcy8/Su7RsDX8hMez2NUTXSt3JV\nv6dxEhFrUlYk2JjSVfyHlNqnCzPzySZj6wVHntQGNwJvwV5D4+0g4NsRcQhwB/+9Gv3PGomqXZZn\n+N/jOyijUhqjoemiiJinWkx8Ccro9XVt6Hw9iZwHnA98Eji3beUTjjyp70XEWZTu1/cCdwGPdz6e\nmWs0EFbrRMSMWTw8mJlTZvG4RqFqSzAA7JiZd1fblgGOAe7NzM2ajK8NIuItwOnANsDNwLWUNdfm\nB7bMzLMaDK81ImLhzHyouv08YEpm3tdwWD3jyJPa4MbqS+MoM+dpOoa5wA7AD4C7IuIhSiK1EHAJ\nsGOTgbXI1ykrElxNafz6JLAYpSXEFyjLDWmMMvOhiNiD0lfrBQAR8QDwzczcr9HgesCRJ7VKdbnx\nlMx8sOlY2iYiZnmll8vg9E61rt1QI9IbM/OWJuNpk4h4DFg2M/9YLSj+68z8RES8DLglM4frGaea\nImI/YFdKJ/crmLkA8zTKmo1fbi66sXPkSa0QER+nfMJZorp/H3BkZn6h0cDa5XbKJfWd/Z0Gq68Z\nwHxNBNUmHQnqY5TppGdsN0HtifuBJSNigHIV2NAyLW+kLPOk3tgR+GBmntux7bcR8WfgcMDkSWpS\nROxLGX6fxjM/4ewbEU9k5lcbDK9NuvuyzEtpDTEN+OKER9NOQwlqNxPU3jkGOJtywcNtlKVadqH0\nitunycBaZiFmLnLd6VbKNGlfM3lSG+wEfCgzz+nYdnVE/An4BmDy1AOZ+cdhNv+hqmM4GfjRBIfU\nRiao4ywzPxcR1wEvA06prri7C3hvZp7XaHDtcgWwZ0TsPLS+XbVm457MXFOwb5k8qQ0WBoarCbmZ\n0hxP4+/FTQfQBiaoEyMzz4qIFwPLV4X512TmvU3H1TK7A5cB76qSVSgNX6cA6zQWVY+YPKkNfgV8\nMiJ2ycwZUHq4UP7z/qbRyFokIj4/zOaFgE2Bn0xwOHMjE9QeiIgFgWMpv7czgFcBh0TEYsDGmTm9\nyfjaIjNvrha5fh+wLKWO70fAyZn5r0aD6wGTJ7XBHpRV59eOiGuqbW8A/h8t+IQziazadX+QUjdy\nPOXyb42RCeqEOJhy6fxSzGxxsgfl9/gwYMuG4mqdzLyfck5bx+RJfS8zfx8Ry1Ga3g19wrkYODEz\nH2k0uBbJzNWbjmEuYII6/jYE1qtaFQCQmbdXReOXNBpZn4uIuxn9ItdLjnM448rkSX0pIl5L6X8z\nA6DqXOubywSJiFdSLkWeF/h+ZvZ9AehkYII6IRaga2mhyvw8sw2H6vts0wFMFJtkqi9FxNPACzvr\nEyLio8AJQ0sCaOwi4jmUpPS91aYTgSO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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc9fd3cfc50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#localdb must be present in your file system, in the case it's in a folder called db\n",
    "localdb = '../db/viral_refseq'\n",
    "blr = analysis.get_orthologs(proteinseq, db=localdb)\n",
    "alnrows, aln = analysis.align_blast_results(blr)\n",
    "alnrows.to_csv('%s_aligned.csv' %name)\n",
    "print alnrows\n",
    "#now we run the same analysis using the set of refseq orthologs\n",
    "c = analysis.epitope_conservation(seqs, alnrows=alnrows)"
   ]
  },
  {
   "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": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}