notebooks/ClusterFinderLabelledContigCheck.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ClusterFinder Reference genomes reconstruction\n",
    "\n",
    "This notebook validates the 10 genomes we obtained from NCBI based on the ClusterFinder supplementary table. \n",
    "\n",
    "We check that the gene locations from the supplementary table match locations in the GenBank files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from Bio import SeqIO\n",
    "from Bio.SeqFeature import FeatureLocation\n",
    "import pandas as pd\n",
    "from Bio import Entrez\n",
    "import seaborn as sns\n",
    "\n",
    "def get_features_of_type(sequence, feature_type):\n",
    "    return [feature for feature in sequence.features if feature.type == feature_type]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_reference_gene_location(gene_csv_row):\n",
    "    start = gene_csv_row['gene start'] - 1\n",
    "    end = gene_csv_row['gene stop']\n",
    "    strand = 1 if gene_csv_row['gene strand'] == '+' else (-1 if gene_csv_row['gene strand'] == '-' else None)\n",
    "    return FeatureLocation(start, end, strand)\n",
    "\n",
    "def feature_locus_matches(feature, reference_locus):\n",
    "     return feature.qualifiers.get('locus_tag',[None])[0] == reference_locus"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading reference cluster gene locations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NCBI ID</th>\n",
       "      <th>Genome ID</th>\n",
       "      <th>contig id</th>\n",
       "      <th>NPL start</th>\n",
       "      <th>NPL stop</th>\n",
       "      <th>NPL strand</th>\n",
       "      <th>gene id</th>\n",
       "      <th>gene locus</th>\n",
       "      <th>gene name</th>\n",
       "      <th>gene start</th>\n",
       "      <th>gene stop</th>\n",
       "      <th>gene strand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>KK037166.1</td>\n",
       "      <td>Kutzneria_sp_744</td>\n",
       "      <td>7,00E+15</td>\n",
       "      <td>28901</td>\n",
       "      <td>43059</td>\n",
       "      <td>+</td>\n",
       "      <td>7,00E+15</td>\n",
       "      <td>KUTG_00017</td>\n",
       "      <td>lysine 2,3-aminomutase</td>\n",
       "      <td>28901</td>\n",
       "      <td>30310</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>KK037166.1</td>\n",
       "      <td>Kutzneria_sp_744</td>\n",
       "      <td>7,00E+15</td>\n",
       "      <td>28901</td>\n",
       "      <td>43059</td>\n",
       "      <td>+</td>\n",
       "      <td>7,00E+15</td>\n",
       "      <td>KUTG_00018</td>\n",
       "      <td>alcohol dehydrogenase, zinc-containing</td>\n",
       "      <td>30404</td>\n",
       "      <td>31462</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>KK037166.1</td>\n",
       "      <td>Kutzneria_sp_744</td>\n",
       "      <td>7,00E+15</td>\n",
       "      <td>28901</td>\n",
       "      <td>43059</td>\n",
       "      <td>+</td>\n",
       "      <td>7,00E+15</td>\n",
       "      <td>KUTG_00019</td>\n",
       "      <td>amidohydrolase 3</td>\n",
       "      <td>31459</td>\n",
       "      <td>33072</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>KK037166.1</td>\n",
       "      <td>Kutzneria_sp_744</td>\n",
       "      <td>7,00E+15</td>\n",
       "      <td>28901</td>\n",
       "      <td>43059</td>\n",
       "      <td>+</td>\n",
       "      <td>7,00E+15</td>\n",
       "      <td>KUTG_00020</td>\n",
       "      <td>beta-lysine 5,6-aminomutase</td>\n",
       "      <td>33069</td>\n",
       "      <td>34637</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>KK037166.1</td>\n",
       "      <td>Kutzneria_sp_744</td>\n",
       "      <td>7,00E+15</td>\n",
       "      <td>28901</td>\n",
       "      <td>43059</td>\n",
       "      <td>+</td>\n",
       "      <td>7,00E+15</td>\n",
       "      <td>KUTG_00021</td>\n",
       "      <td>beta-lysine 5,6-aminomutase</td>\n",
       "      <td>34634</td>\n",
       "      <td>35383</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      NCBI ID         Genome ID contig id  NPL start  NPL stop NPL strand  \\\n",
       "0  KK037166.1  Kutzneria_sp_744  7,00E+15      28901     43059          +   \n",
       "1  KK037166.1  Kutzneria_sp_744  7,00E+15      28901     43059          +   \n",
       "2  KK037166.1  Kutzneria_sp_744  7,00E+15      28901     43059          +   \n",
       "3  KK037166.1  Kutzneria_sp_744  7,00E+15      28901     43059          +   \n",
       "4  KK037166.1  Kutzneria_sp_744  7,00E+15      28901     43059          +   \n",
       "\n",
       "    gene id  gene locus                               gene name  gene start  \\\n",
       "0  7,00E+15  KUTG_00017                  lysine 2,3-aminomutase       28901   \n",
       "1  7,00E+15  KUTG_00018  alcohol dehydrogenase, zinc-containing       30404   \n",
       "2  7,00E+15  KUTG_00019                        amidohydrolase 3       31459   \n",
       "3  7,00E+15  KUTG_00020             beta-lysine 5,6-aminomutase       33069   \n",
       "4  7,00E+15  KUTG_00021             beta-lysine 5,6-aminomutase       34634   \n",
       "\n",
       "   gene stop gene strand  \n",
       "0      30310           -  \n",
       "1      31462           +  \n",
       "2      33072           +  \n",
       "3      34637           +  \n",
       "4      35383           +  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reference_genes = pd.read_csv('../data/clusterfinder/labelled/CF_labelled_genes_orig.csv', sep=';')\n",
    "reference_genes.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Genes with no sequence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "421 genes don't have a sequence!\n"
     ]
    },
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>missing genes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Genome ID</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Micromonospora_M42_V1</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StrRos_NRRL11379_V1</th>\n",
       "      <td>420</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                       missing genes\n",
       "Genome ID                           \n",
       "Micromonospora_M42_V1              1\n",
       "StrRos_NRRL11379_V1              420"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "no_sequence_genes = reference_genes[reference_genes['NCBI ID'] == '?']\n",
    "no_sequence_counts = no_sequence_genes.groupby('Genome ID')['gene locus'].count()\n",
    "print('{} genes don\\'t have a sequence!'.format(len(no_sequence_genes)))\n",
    "pd.DataFrame({'missing genes':no_sequence_counts})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['KK037166.1', 'GG657738.1', 'KK037233.1', 'DS999642.1',\n",
       "       'DS999641.1', 'DS999645.1', 'GG657754.1', 'CM000950.1',\n",
       "       'GG657747.1', 'GG657746.1', 'GG657751.1', 'GG657750.1',\n",
       "       'GG657752.1'], dtype=object)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reference_ids = reference_genes[reference_genes['NCBI ID'] != '?']['NCBI ID'].unique()\n",
    "reference_ids"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Validating that reference genes are found in our sequences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def validate_genome(record, record_reference_genes):\n",
    "    print('Validating {}'.format(record.id))\n",
    "    record_genes = get_features_of_type(record, 'gene')\n",
    "    record_cds = get_features_of_type(record, 'CDS')\n",
    "    validation = []\n",
    "    record_length = len(record.seq)\n",
    "    min_location = record_length\n",
    "    max_location = -1\n",
    "    prev_gene_index = None\n",
    "    prev_cluster_start = None\n",
    "    for i, reference_gene in record_reference_genes.iterrows():\n",
    "        reference_gene_location = get_reference_gene_location(reference_gene)\n",
    "        reference_gene_locus = reference_gene['gene locus']\n",
    "        reference_cluster_start = reference_gene['NPL start']\n",
    "        gene_matches_locus = [f for f in record_genes if feature_locus_matches(f, reference_gene_locus)]\n",
    "        cds_matches_locus = [f for f in record_cds if feature_locus_matches(f, reference_gene_locus)]\n",
    "        gene_matches_location = [f for f in gene_matches_locus if reference_gene_location == f.location]\n",
    "        cds_matches_location = [f for f in cds_matches_locus if reference_gene_location == f.location]\n",
    "        validation.append({\n",
    "            'gene_locus_not_found':not gene_matches_locus, \n",
    "            'cds_locus_not_found':not cds_matches_locus, \n",
    "            'gene_location_correct': bool(gene_matches_location), \n",
    "            'cds_location_correct': bool(cds_matches_location)\n",
    "        })\n",
    "        if not cds_matches_locus:\n",
    "            print('No CDS found for gene locus {}'.format(reference_gene_locus))\n",
    "        if gene_matches_locus:\n",
    "            gene_match = gene_matches_locus[0]\n",
    "            if not cds_matches_locus:\n",
    "                print(' Gene: ', gene_match.qualifiers)\n",
    "                \n",
    "            # Use gene index to check if we have a consecutive sequence of genes (except when going from one cluster to another)\n",
    "            gene_index = [gi for gi,f in enumerate(record_genes) if feature_locus_matches(f, reference_gene_locus)][0]\n",
    "            if reference_cluster_start == prev_cluster_start and gene_index != prev_gene_index + 1:\n",
    "                print('Additional unexpected genes found before {} (index {} -> {}) at cluster start {}'.format(reference_gene_locus, prev_gene_index, gene_index, reference_cluster_start))\n",
    "            \n",
    "            # Calculate min and max cluster gene location to see how much of the sequence is covered by the reference genes\n",
    "            min_location = min(gene_match.location.start, min_location)\n",
    "            max_location = max(gene_match.location.end, max_location)\n",
    "            prev_gene_index = gene_index\n",
    "        prev_cluster_start = reference_cluster_start\n",
    "           \n",
    "    result = pd.DataFrame(validation).sum().to_dict()\n",
    "    result['location correct'] = min(result['gene_location_correct'], result['cds_location_correct']) / len(validation)\n",
    "    result['ID'] = record.id\n",
    "    result['genome'] = record_reference_genes.iloc[0]['Genome ID']\n",
    "    result['sequence length'] = record_length\n",
    "    result['total genes'] = len(record_genes)\n",
    "    result['reference genes'] = len(record_reference_genes)\n",
    "    result['first location'] = min_location / record_length\n",
    "    result['last location'] = max_location / record_length\n",
    "    result['covered'] = (max_location - min_location) / record_length\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CM000950.1\n",
      "Validating CM000950.1\n",
      "No CDS found for gene locus SSDG_00035\n",
      " Gene:  OrderedDict([('locus_tag', ['SSDG_00035']), ('note', ['ABC transporter; frameshift'])])\n",
      "No CDS found for gene locus SSDG_00089\n",
      " Gene:  OrderedDict([('locus_tag', ['SSDG_00089']), ('note', ['squalene/phytoene dehydrogenase; frameshift'])])\n",
      "No CDS found for gene locus SSDG_04325\n",
      " Gene:  OrderedDict([('locus_tag', ['SSDG_04325']), ('note', ['AMP-dependent synthetase and ligase; frameshift'])])\n",
      "No CDS found for gene locus SSDG_06129\n",
      " Gene:  OrderedDict([('locus_tag', ['SSDG_06129']), ('note', ['transferase; frameshift'])])\n",
      "No CDS found for gene locus SSDG_06352\n",
      " Gene:  OrderedDict([('locus_tag', ['SSDG_06352']), ('note', ['predicted protein; frameshift'])])\n",
      "No CDS found for gene locus SSDG_00185\n",
      " Gene:  OrderedDict([('locus_tag', ['SSDG_00185']), ('note', ['glycosyl transferase; frameshift'])])\n",
      "No CDS found for gene locus SSDG_06509\n",
      " Gene:  OrderedDict([('locus_tag', ['SSDG_06509']), ('note', ['beta keto-acyl synthase; frameshift'])])\n",
      "No CDS found for gene locus SSDG_07501\n",
      " Gene:  OrderedDict([('locus_tag', ['SSDG_07501']), ('note', ['acyltransferase; frameshift'])])\n",
      "No CDS found for gene locus SSDG_07518\n",
      " Gene:  OrderedDict([('locus_tag', ['SSDG_07518']), ('note', ['predicted protein; frameshift'])])\n",
      "No CDS found for gene locus SSDG_07538\n",
      " Gene:  OrderedDict([('locus_tag', ['SSDG_07538']), ('note', ['pristinamycin I synthase 3 and 4; frameshift'])])\n",
      "DS999641.1\n",
      "Validating DS999641.1\n",
      "DS999642.1\n",
      "Validating DS999642.1\n",
      "DS999645.1\n",
      "Validating DS999645.1\n",
      "GG657738.1\n",
      "Validating GG657738.1\n",
      "GG657746.1\n",
      "Validating GG657746.1\n",
      "GG657747.1\n",
      "Validating GG657747.1\n",
      "GG657750.1\n",
      "Validating GG657750.1\n",
      "GG657751.1\n",
      "Validating GG657751.1\n",
      "GG657752.1\n",
      "Validating GG657752.1\n",
      "GG657754.1\n",
      "Validating GG657754.1\n",
      "KK037166.1\n",
      "Validating KK037166.1\n",
      "KK037233.1\n",
      "Validating KK037233.1\n"
     ]
    },
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cds_location_correct</th>\n",
       "      <th>cds_locus_not_found</th>\n",
       "      <th>covered</th>\n",
       "      <th>first location</th>\n",
       "      <th>gene_location_correct</th>\n",
       "      <th>gene_locus_not_found</th>\n",
       "      <th>genome</th>\n",
       "      <th>last location</th>\n",
       "      <th>location correct</th>\n",
       "      <th>reference genes</th>\n",
       "      <th>sequence length</th>\n",
       "      <th>total genes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CM000950.1</th>\n",
       "      <td>300</td>\n",
       "      <td>10</td>\n",
       "      <td>0.972233</td>\n",
       "      <td>0.010094</td>\n",
       "      <td>310</td>\n",
       "      <td>0</td>\n",
       "      <td>Strept_priATCC25486_V1</td>\n",
       "      <td>0.982327</td>\n",
       "      <td>0.884956</td>\n",
       "      <td>339</td>\n",
       "      <td>8133379</td>\n",
       "      <td>7077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DS999641.1</th>\n",
       "      <td>281</td>\n",
       "      <td>0</td>\n",
       "      <td>0.983626</td>\n",
       "      <td>0.008382</td>\n",
       "      <td>290</td>\n",
       "      <td>0</td>\n",
       "      <td>S.ghanaensis_ATCC14672_V1</td>\n",
       "      <td>0.992008</td>\n",
       "      <td>0.939799</td>\n",
       "      <td>299</td>\n",
       "      <td>8265412</td>\n",
       "      <td>7729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DS999642.1</th>\n",
       "      <td>93</td>\n",
       "      <td>0</td>\n",
       "      <td>0.873147</td>\n",
       "      <td>0.107535</td>\n",
       "      <td>93</td>\n",
       "      <td>0</td>\n",
       "      <td>S.ghanaensis_ATCC14672_V1</td>\n",
       "      <td>0.980682</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>93</td>\n",
       "      <td>231283</td>\n",
       "      <td>211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DS999645.1</th>\n",
       "      <td>264</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999363</td>\n",
       "      <td>0.000624</td>\n",
       "      <td>275</td>\n",
       "      <td>0</td>\n",
       "      <td>StrAlb_J1074_V3</td>\n",
       "      <td>0.999988</td>\n",
       "      <td>0.901024</td>\n",
       "      <td>293</td>\n",
       "      <td>6813830</td>\n",
       "      <td>5955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657738.1</th>\n",
       "      <td>462</td>\n",
       "      <td>0</td>\n",
       "      <td>0.944454</td>\n",
       "      <td>0.048209</td>\n",
       "      <td>483</td>\n",
       "      <td>0</td>\n",
       "      <td>Micro_carb_varATCC39149</td>\n",
       "      <td>0.992663</td>\n",
       "      <td>0.925852</td>\n",
       "      <td>499</td>\n",
       "      <td>6798591</td>\n",
       "      <td>5662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657746.1</th>\n",
       "      <td>266</td>\n",
       "      <td>0</td>\n",
       "      <td>0.932882</td>\n",
       "      <td>0.004900</td>\n",
       "      <td>269</td>\n",
       "      <td>0</td>\n",
       "      <td>Strept_sp_AA4</td>\n",
       "      <td>0.937782</td>\n",
       "      <td>0.988848</td>\n",
       "      <td>269</td>\n",
       "      <td>8475969</td>\n",
       "      <td>7789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657747.1</th>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>0.557014</td>\n",
       "      <td>0.343816</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>Strept_sp_AA4</td>\n",
       "      <td>0.900830</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>39</td>\n",
       "      <td>327015</td>\n",
       "      <td>327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657750.1</th>\n",
       "      <td>212</td>\n",
       "      <td>0</td>\n",
       "      <td>0.945454</td>\n",
       "      <td>0.046865</td>\n",
       "      <td>219</td>\n",
       "      <td>0</td>\n",
       "      <td>Strept_sp_C</td>\n",
       "      <td>0.992320</td>\n",
       "      <td>0.909871</td>\n",
       "      <td>233</td>\n",
       "      <td>7450102</td>\n",
       "      <td>6740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657751.1</th>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "      <td>0.691226</td>\n",
       "      <td>0.302906</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "      <td>Strept_sp_C</td>\n",
       "      <td>0.994132</td>\n",
       "      <td>0.955556</td>\n",
       "      <td>45</td>\n",
       "      <td>625386</td>\n",
       "      <td>616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657752.1</th>\n",
       "      <td>117</td>\n",
       "      <td>0</td>\n",
       "      <td>0.925985</td>\n",
       "      <td>0.045375</td>\n",
       "      <td>121</td>\n",
       "      <td>0</td>\n",
       "      <td>Strept_sp_C</td>\n",
       "      <td>0.971360</td>\n",
       "      <td>0.893130</td>\n",
       "      <td>131</td>\n",
       "      <td>366789</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657754.1</th>\n",
       "      <td>576</td>\n",
       "      <td>0</td>\n",
       "      <td>0.984583</td>\n",
       "      <td>0.007089</td>\n",
       "      <td>602</td>\n",
       "      <td>0</td>\n",
       "      <td>Strept_hygr_ATCC53653</td>\n",
       "      <td>0.991673</td>\n",
       "      <td>0.902821</td>\n",
       "      <td>638</td>\n",
       "      <td>10901646</td>\n",
       "      <td>9146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KK037166.1</th>\n",
       "      <td>498</td>\n",
       "      <td>0</td>\n",
       "      <td>0.992181</td>\n",
       "      <td>0.002481</td>\n",
       "      <td>518</td>\n",
       "      <td>0</td>\n",
       "      <td>Kutzneria_sp_744</td>\n",
       "      <td>0.994663</td>\n",
       "      <td>0.922222</td>\n",
       "      <td>540</td>\n",
       "      <td>11646492</td>\n",
       "      <td>10254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KK037233.1</th>\n",
       "      <td>300</td>\n",
       "      <td>0</td>\n",
       "      <td>0.996487</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>321</td>\n",
       "      <td>0</td>\n",
       "      <td>Micromonospora_M42_V1</td>\n",
       "      <td>0.996507</td>\n",
       "      <td>0.824176</td>\n",
       "      <td>364</td>\n",
       "      <td>6703188</td>\n",
       "      <td>6092</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            cds_location_correct  cds_locus_not_found   covered  \\\n",
       "ID                                                                \n",
       "CM000950.1                   300                   10  0.972233   \n",
       "DS999641.1                   281                    0  0.983626   \n",
       "DS999642.1                    93                    0  0.873147   \n",
       "DS999645.1                   264                    0  0.999363   \n",
       "GG657738.1                   462                    0  0.944454   \n",
       "GG657746.1                   266                    0  0.932882   \n",
       "GG657747.1                    39                    0  0.557014   \n",
       "GG657750.1                   212                    0  0.945454   \n",
       "GG657751.1                    43                    0  0.691226   \n",
       "GG657752.1                   117                    0  0.925985   \n",
       "GG657754.1                   576                    0  0.984583   \n",
       "KK037166.1                   498                    0  0.992181   \n",
       "KK037233.1                   300                    0  0.996487   \n",
       "\n",
       "            first location  gene_location_correct  gene_locus_not_found  \\\n",
       "ID                                                                        \n",
       "CM000950.1        0.010094                    310                     0   \n",
       "DS999641.1        0.008382                    290                     0   \n",
       "DS999642.1        0.107535                     93                     0   \n",
       "DS999645.1        0.000624                    275                     0   \n",
       "GG657738.1        0.048209                    483                     0   \n",
       "GG657746.1        0.004900                    269                     0   \n",
       "GG657747.1        0.343816                     39                     0   \n",
       "GG657750.1        0.046865                    219                     0   \n",
       "GG657751.1        0.302906                     43                     0   \n",
       "GG657752.1        0.045375                    121                     0   \n",
       "GG657754.1        0.007089                    602                     0   \n",
       "KK037166.1        0.002481                    518                     0   \n",
       "KK037233.1        0.000020                    321                     0   \n",
       "\n",
       "                               genome  last location  location correct  \\\n",
       "ID                                                                       \n",
       "CM000950.1     Strept_priATCC25486_V1       0.982327          0.884956   \n",
       "DS999641.1  S.ghanaensis_ATCC14672_V1       0.992008          0.939799   \n",
       "DS999642.1  S.ghanaensis_ATCC14672_V1       0.980682          1.000000   \n",
       "DS999645.1            StrAlb_J1074_V3       0.999988          0.901024   \n",
       "GG657738.1    Micro_carb_varATCC39149       0.992663          0.925852   \n",
       "GG657746.1              Strept_sp_AA4       0.937782          0.988848   \n",
       "GG657747.1              Strept_sp_AA4       0.900830          1.000000   \n",
       "GG657750.1                Strept_sp_C       0.992320          0.909871   \n",
       "GG657751.1                Strept_sp_C       0.994132          0.955556   \n",
       "GG657752.1                Strept_sp_C       0.971360          0.893130   \n",
       "GG657754.1      Strept_hygr_ATCC53653       0.991673          0.902821   \n",
       "KK037166.1           Kutzneria_sp_744       0.994663          0.922222   \n",
       "KK037233.1      Micromonospora_M42_V1       0.996507          0.824176   \n",
       "\n",
       "            reference genes  sequence length  total genes  \n",
       "ID                                                         \n",
       "CM000950.1              339          8133379         7077  \n",
       "DS999641.1              299          8265412         7729  \n",
       "DS999642.1               93           231283          211  \n",
       "DS999645.1              293          6813830         5955  \n",
       "GG657738.1              499          6798591         5662  \n",
       "GG657746.1              269          8475969         7789  \n",
       "GG657747.1               39           327015          327  \n",
       "GG657750.1              233          7450102         6740  \n",
       "GG657751.1               45           625386          616  \n",
       "GG657752.1              131           366789          232  \n",
       "GG657754.1              638         10901646         9146  \n",
       "KK037166.1              540         11646492        10254  \n",
       "KK037233.1              364          6703188         6092  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "validations = []\n",
    "reference_gene_groups = reference_genes.groupby('NCBI ID')\n",
    "records = SeqIO.parse('../data/clusterfinder/labelled/CF_labelled_contigs.gbk', 'genbank')\n",
    "for record in records:\n",
    "    ncbi_id = record.id\n",
    "    print(ncbi_id)\n",
    "    record_reference_genes = reference_gene_groups.get_group(ncbi_id)\n",
    "    validations.append(validate_genome(record, record_reference_genes))\n",
    "validations = pd.DataFrame(validations)\n",
    "validations.set_index('ID', inplace=True)\n",
    "validations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9267887842574284"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "validations['location correct'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.07321121574257161"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 - validations['location correct'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>genome</th>\n",
       "      <th>first location</th>\n",
       "      <th>last location</th>\n",
       "      <th>covered</th>\n",
       "      <th>location correct</th>\n",
       "      <th>reference genes</th>\n",
       "      <th>total genes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CM000950.1</th>\n",
       "      <td>Strept_priATCC25486_V1</td>\n",
       "      <td>0.010094</td>\n",
       "      <td>0.982327</td>\n",
       "      <td>0.972233</td>\n",
       "      <td>0.884956</td>\n",
       "      <td>339</td>\n",
       "      <td>7077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DS999641.1</th>\n",
       "      <td>S.ghanaensis_ATCC14672_V1</td>\n",
       "      <td>0.008382</td>\n",
       "      <td>0.992008</td>\n",
       "      <td>0.983626</td>\n",
       "      <td>0.939799</td>\n",
       "      <td>299</td>\n",
       "      <td>7729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DS999642.1</th>\n",
       "      <td>S.ghanaensis_ATCC14672_V1</td>\n",
       "      <td>0.107535</td>\n",
       "      <td>0.980682</td>\n",
       "      <td>0.873147</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>93</td>\n",
       "      <td>211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DS999645.1</th>\n",
       "      <td>StrAlb_J1074_V3</td>\n",
       "      <td>0.000624</td>\n",
       "      <td>0.999988</td>\n",
       "      <td>0.999363</td>\n",
       "      <td>0.901024</td>\n",
       "      <td>293</td>\n",
       "      <td>5955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657738.1</th>\n",
       "      <td>Micro_carb_varATCC39149</td>\n",
       "      <td>0.048209</td>\n",
       "      <td>0.992663</td>\n",
       "      <td>0.944454</td>\n",
       "      <td>0.925852</td>\n",
       "      <td>499</td>\n",
       "      <td>5662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657746.1</th>\n",
       "      <td>Strept_sp_AA4</td>\n",
       "      <td>0.004900</td>\n",
       "      <td>0.937782</td>\n",
       "      <td>0.932882</td>\n",
       "      <td>0.988848</td>\n",
       "      <td>269</td>\n",
       "      <td>7789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657747.1</th>\n",
       "      <td>Strept_sp_AA4</td>\n",
       "      <td>0.343816</td>\n",
       "      <td>0.900830</td>\n",
       "      <td>0.557014</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>39</td>\n",
       "      <td>327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657750.1</th>\n",
       "      <td>Strept_sp_C</td>\n",
       "      <td>0.046865</td>\n",
       "      <td>0.992320</td>\n",
       "      <td>0.945454</td>\n",
       "      <td>0.909871</td>\n",
       "      <td>233</td>\n",
       "      <td>6740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657751.1</th>\n",
       "      <td>Strept_sp_C</td>\n",
       "      <td>0.302906</td>\n",
       "      <td>0.994132</td>\n",
       "      <td>0.691226</td>\n",
       "      <td>0.955556</td>\n",
       "      <td>45</td>\n",
       "      <td>616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657752.1</th>\n",
       "      <td>Strept_sp_C</td>\n",
       "      <td>0.045375</td>\n",
       "      <td>0.971360</td>\n",
       "      <td>0.925985</td>\n",
       "      <td>0.893130</td>\n",
       "      <td>131</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GG657754.1</th>\n",
       "      <td>Strept_hygr_ATCC53653</td>\n",
       "      <td>0.007089</td>\n",
       "      <td>0.991673</td>\n",
       "      <td>0.984583</td>\n",
       "      <td>0.902821</td>\n",
       "      <td>638</td>\n",
       "      <td>9146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KK037166.1</th>\n",
       "      <td>Kutzneria_sp_744</td>\n",
       "      <td>0.002481</td>\n",
       "      <td>0.994663</td>\n",
       "      <td>0.992181</td>\n",
       "      <td>0.922222</td>\n",
       "      <td>540</td>\n",
       "      <td>10254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KK037233.1</th>\n",
       "      <td>Micromonospora_M42_V1</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.996507</td>\n",
       "      <td>0.996487</td>\n",
       "      <td>0.824176</td>\n",
       "      <td>364</td>\n",
       "      <td>6092</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               genome  first location  last location  \\\n",
       "ID                                                                     \n",
       "CM000950.1     Strept_priATCC25486_V1        0.010094       0.982327   \n",
       "DS999641.1  S.ghanaensis_ATCC14672_V1        0.008382       0.992008   \n",
       "DS999642.1  S.ghanaensis_ATCC14672_V1        0.107535       0.980682   \n",
       "DS999645.1            StrAlb_J1074_V3        0.000624       0.999988   \n",
       "GG657738.1    Micro_carb_varATCC39149        0.048209       0.992663   \n",
       "GG657746.1              Strept_sp_AA4        0.004900       0.937782   \n",
       "GG657747.1              Strept_sp_AA4        0.343816       0.900830   \n",
       "GG657750.1                Strept_sp_C        0.046865       0.992320   \n",
       "GG657751.1                Strept_sp_C        0.302906       0.994132   \n",
       "GG657752.1                Strept_sp_C        0.045375       0.971360   \n",
       "GG657754.1      Strept_hygr_ATCC53653        0.007089       0.991673   \n",
       "KK037166.1           Kutzneria_sp_744        0.002481       0.994663   \n",
       "KK037233.1      Micromonospora_M42_V1        0.000020       0.996507   \n",
       "\n",
       "             covered  location correct  reference genes  total genes  \n",
       "ID                                                                    \n",
       "CM000950.1  0.972233          0.884956              339         7077  \n",
       "DS999641.1  0.983626          0.939799              299         7729  \n",
       "DS999642.1  0.873147          1.000000               93          211  \n",
       "DS999645.1  0.999363          0.901024              293         5955  \n",
       "GG657738.1  0.944454          0.925852              499         5662  \n",
       "GG657746.1  0.932882          0.988848              269         7789  \n",
       "GG657747.1  0.557014          1.000000               39          327  \n",
       "GG657750.1  0.945454          0.909871              233         6740  \n",
       "GG657751.1  0.691226          0.955556               45          616  \n",
       "GG657752.1  0.925985          0.893130              131          232  \n",
       "GG657754.1  0.984583          0.902821              638         9146  \n",
       "KK037166.1  0.992181          0.922222              540        10254  \n",
       "KK037233.1  0.996487          0.824176              364         6092  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "validations[['genome','first location','last location','covered','location correct','reference genes','total genes']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cluster genes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>contig_id</th>\n",
       "      <th>contig_source</th>\n",
       "      <th>cluster_id</th>\n",
       "      <th>cluster_strand</th>\n",
       "      <th>locus_tag</th>\n",
       "      <th>gene_label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>KK037166.1</td>\n",
       "      <td>Kutzneria_sp_744</td>\n",
       "      <td>Kutzneria_sp_744_28901-43059</td>\n",
       "      <td>+</td>\n",
       "      <td>KUTG_00017</td>\n",
       "      <td>lysine 2,3-aminomutase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>KK037166.1</td>\n",
       "      <td>Kutzneria_sp_744</td>\n",
       "      <td>Kutzneria_sp_744_28901-43059</td>\n",
       "      <td>+</td>\n",
       "      <td>KUTG_00018</td>\n",
       "      <td>alcohol dehydrogenase, zinc-containing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>KK037166.1</td>\n",
       "      <td>Kutzneria_sp_744</td>\n",
       "      <td>Kutzneria_sp_744_28901-43059</td>\n",
       "      <td>+</td>\n",
       "      <td>KUTG_00019</td>\n",
       "      <td>amidohydrolase 3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>KK037166.1</td>\n",
       "      <td>Kutzneria_sp_744</td>\n",
       "      <td>Kutzneria_sp_744_28901-43059</td>\n",
       "      <td>+</td>\n",
       "      <td>KUTG_00020</td>\n",
       "      <td>beta-lysine 5,6-aminomutase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>KK037166.1</td>\n",
       "      <td>Kutzneria_sp_744</td>\n",
       "      <td>Kutzneria_sp_744_28901-43059</td>\n",
       "      <td>+</td>\n",
       "      <td>KUTG_00021</td>\n",
       "      <td>beta-lysine 5,6-aminomutase</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    contig_id     contig_source                    cluster_id cluster_strand  \\\n",
       "0  KK037166.1  Kutzneria_sp_744  Kutzneria_sp_744_28901-43059              +   \n",
       "1  KK037166.1  Kutzneria_sp_744  Kutzneria_sp_744_28901-43059              +   \n",
       "2  KK037166.1  Kutzneria_sp_744  Kutzneria_sp_744_28901-43059              +   \n",
       "3  KK037166.1  Kutzneria_sp_744  Kutzneria_sp_744_28901-43059              +   \n",
       "4  KK037166.1  Kutzneria_sp_744  Kutzneria_sp_744_28901-43059              +   \n",
       "\n",
       "    locus_tag                              gene_label  \n",
       "0  KUTG_00017                  lysine 2,3-aminomutase  \n",
       "1  KUTG_00018  alcohol dehydrogenase, zinc-containing  \n",
       "2  KUTG_00019                        amidohydrolase 3  \n",
       "3  KUTG_00020             beta-lysine 5,6-aminomutase  \n",
       "4  KUTG_00021             beta-lysine 5,6-aminomutase  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genes = pd.read_csv('../data/clusterfinder/labelled/CF_labelled_genes.csv', sep=';')\n",
    "genes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1124631d0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b972dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cluster_counts = genes.groupby('contig_id')['cluster_id'].nunique()\n",
    "cluster_counts.sort_values().plot.barh()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1124f9358>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112414668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gene_counts = genes.groupby('cluster_id')['locus_tag'].count()\n",
    "gene_counts.hist(bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "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": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}