Enrichment Analysis and Visualisations.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Enrichment analysis and visualisations\n",
    "\n",
    "This is loosely adapted from one of the InterMineR vignettes\n",
    "https://bioconductor.org/packages/release/bioc/vignettes/InterMineR/inst/doc/Enrichment_Analysis_and_Visualization.html\n",
    "\n",
    "## Background\n",
    "\n",
    "The InterMine gene set enrichment tool looks for annotations to a set of genes that occur more than would be expected by chance, given a background population of annotations. The hypergeometric distribution is used to calculate a P-value for each annotation and a choice of correction methods for multiple testing (Bonferonni, Holm-Bonferonni and Benjamini Hochberg) are available (Smith et al. 2012; Kalderimis et al. 2014).\n",
    "\n",
    "InterMine provides Gene Ontology enrichment statistics as well as enrichment statistics for other annotation types including protein domains, pathways, human diseases, mammalian phenotypes and publications. The default background population is all genes in the genome with the specified annotation type. However, the background population can be changed by specifying another list. More information can be found in the [online documentation](http://intermine.readthedocs.io/en/latest/embedding/list-widgets/enrichment-widgets/).\n",
    "\n",
    "## Goal for this exercise\n",
    "\n",
    "1. Use InterMine's enrichment widgets on the HumanMine public list [PL_GenomicsEngland_GenePanel%:Genetic_Epilepsy_Syndromes](http://www.humanmine.org/humanmine/bagDetails.do?scope=all&bagName=PL_GenomicsEngland_GenePanel%3AGenetic_Epilepsy_Syndromes) to see if the list is enriched for any GO Terms.\n",
    "2. Visualise the results using the GeneAnswers class. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setup\n",
    "Let's start by initialising InterMineR and choosing which InterMine we'll be running queries against:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Begin by activating the InterMineR library:\n",
    "library(InterMineR)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We want to query human data - so let's look and see what InterMines are available: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<dl class=dl-horizontal>\n",
       "\t<dt>BMAP</dt>\n",
       "\t\t<dd>'https://bmap.jgi.doe.gov/bmapmine/'</dd>\n",
       "\t<dt>BeanMine</dt>\n",
       "\t\t<dd>'https://mines.legumeinfo.org/beanmine'</dd>\n",
       "\t<dt>BovineMine</dt>\n",
       "\t\t<dd>'http://genomes.missouri.edu/bovinemine'</dd>\n",
       "\t<dt>CHOmine</dt>\n",
       "\t\t<dd>'https://chomine.boku.ac.at/chomine'</dd>\n",
       "\t<dt>ChickpeaMine</dt>\n",
       "\t\t<dd>'https://mines.legumeinfo.org/chickpeamine'</dd>\n",
       "\t<dt>CowpeaMine</dt>\n",
       "\t\t<dd>'https://mines.legumeinfo.org/cowpeamine'</dd>\n",
       "\t<dt>FlyMine</dt>\n",
       "\t\t<dd>'http://www.flymine.org/flymine'</dd>\n",
       "\t<dt>GrapeMine</dt>\n",
       "\t\t<dd>'http://urgi.versailles.inra.fr/GrapeMine'</dd>\n",
       "\t<dt>HumanMine</dt>\n",
       "\t\t<dd>'http://www.humanmine.org/humanmine'</dd>\n",
       "\t<dt>HymenopteraMine</dt>\n",
       "\t\t<dd>'http://hymenopteragenome.org/hymenopteramine'</dd>\n",
       "\t<dt>IndigoMine</dt>\n",
       "\t\t<dd>'http://www.cbrc.kaust.edu.sa/indigo'</dd>\n",
       "\t<dt>LegumeMine</dt>\n",
       "\t\t<dd>'https://mines.legumeinfo.org/legumemine'</dd>\n",
       "\t<dt>MaizeMine</dt>\n",
       "\t\t<dd>'http://maizemine.rnet.missouri.edu:8080/maizemine'</dd>\n",
       "\t<dt>MedicMine</dt>\n",
       "\t\t<dd>'http://medicmine.jcvi.org/medicmine'</dd>\n",
       "\t<dt>MitoMiner</dt>\n",
       "\t\t<dd>'http://mitominer.mrc-mbu.cam.ac.uk/release-4.0'</dd>\n",
       "\t<dt>ModMine</dt>\n",
       "\t\t<dd>'http://intermine.modencode.org/release-33'</dd>\n",
       "\t<dt>MouseMine</dt>\n",
       "\t\t<dd>'http://www.mousemine.org/mousemine'</dd>\n",
       "\t<dt>OakMine</dt>\n",
       "\t\t<dd>'https://urgi.versailles.inra.fr/OakMine_PM1N'</dd>\n",
       "\t<dt>PeanutMine</dt>\n",
       "\t\t<dd>'https://mines.legumeinfo.org/peanutmine'</dd>\n",
       "\t<dt>PhytoMine</dt>\n",
       "\t\t<dd>'https://phytozome.jgi.doe.gov/phytomine/'</dd>\n",
       "\t<dt>PlanMine</dt>\n",
       "\t\t<dd>'http://planmine.mpi-cbg.de/planmine'</dd>\n",
       "\t<dt>RatMine</dt>\n",
       "\t\t<dd>'http://ratmine.mcw.edu/ratmine'</dd>\n",
       "\t<dt>RepetDB</dt>\n",
       "\t\t<dd>'http://urgi.versailles.inra.fr/repetdb'</dd>\n",
       "\t<dt>SoyMine</dt>\n",
       "\t\t<dd>'https://mines.legumeinfo.org/soymine'</dd>\n",
       "\t<dt>TargetMine</dt>\n",
       "\t\t<dd>'https://targetmine.mizuguchilab.org/targetmine'</dd>\n",
       "\t<dt>ThaleMine</dt>\n",
       "\t\t<dd>'https://apps.araport.org/thalemine'</dd>\n",
       "\t<dt>WheatMine</dt>\n",
       "\t\t<dd>'https://urgi.versailles.inra.fr/WheatMine'</dd>\n",
       "\t<dt>WormMine</dt>\n",
       "\t\t<dd>'http://intermine.wormbase.org/tools/wormmine/'</dd>\n",
       "\t<dt>XenMine</dt>\n",
       "\t\t<dd>'http://www.xenmine.org/xenmine'</dd>\n",
       "\t<dt>YeastMine</dt>\n",
       "\t\t<dd>'https://yeastmine.yeastgenome.org/yeastmine'</dd>\n",
       "\t<dt>ZebrafishMine</dt>\n",
       "\t\t<dd>'http://zebrafishmine.org'</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[BMAP] 'https://bmap.jgi.doe.gov/bmapmine/'\n",
       "\\item[BeanMine] 'https://mines.legumeinfo.org/beanmine'\n",
       "\\item[BovineMine] 'http://genomes.missouri.edu/bovinemine'\n",
       "\\item[CHOmine] 'https://chomine.boku.ac.at/chomine'\n",
       "\\item[ChickpeaMine] 'https://mines.legumeinfo.org/chickpeamine'\n",
       "\\item[CowpeaMine] 'https://mines.legumeinfo.org/cowpeamine'\n",
       "\\item[FlyMine] 'http://www.flymine.org/flymine'\n",
       "\\item[GrapeMine] 'http://urgi.versailles.inra.fr/GrapeMine'\n",
       "\\item[HumanMine] 'http://www.humanmine.org/humanmine'\n",
       "\\item[HymenopteraMine] 'http://hymenopteragenome.org/hymenopteramine'\n",
       "\\item[IndigoMine] 'http://www.cbrc.kaust.edu.sa/indigo'\n",
       "\\item[LegumeMine] 'https://mines.legumeinfo.org/legumemine'\n",
       "\\item[MaizeMine] 'http://maizemine.rnet.missouri.edu:8080/maizemine'\n",
       "\\item[MedicMine] 'http://medicmine.jcvi.org/medicmine'\n",
       "\\item[MitoMiner] 'http://mitominer.mrc-mbu.cam.ac.uk/release-4.0'\n",
       "\\item[ModMine] 'http://intermine.modencode.org/release-33'\n",
       "\\item[MouseMine] 'http://www.mousemine.org/mousemine'\n",
       "\\item[OakMine] 'https://urgi.versailles.inra.fr/OakMine\\_PM1N'\n",
       "\\item[PeanutMine] 'https://mines.legumeinfo.org/peanutmine'\n",
       "\\item[PhytoMine] 'https://phytozome.jgi.doe.gov/phytomine/'\n",
       "\\item[PlanMine] 'http://planmine.mpi-cbg.de/planmine'\n",
       "\\item[RatMine] 'http://ratmine.mcw.edu/ratmine'\n",
       "\\item[RepetDB] 'http://urgi.versailles.inra.fr/repetdb'\n",
       "\\item[SoyMine] 'https://mines.legumeinfo.org/soymine'\n",
       "\\item[TargetMine] 'https://targetmine.mizuguchilab.org/targetmine'\n",
       "\\item[ThaleMine] 'https://apps.araport.org/thalemine'\n",
       "\\item[WheatMine] 'https://urgi.versailles.inra.fr/WheatMine'\n",
       "\\item[WormMine] 'http://intermine.wormbase.org/tools/wormmine/'\n",
       "\\item[XenMine] 'http://www.xenmine.org/xenmine'\n",
       "\\item[YeastMine] 'https://yeastmine.yeastgenome.org/yeastmine'\n",
       "\\item[ZebrafishMine] 'http://zebrafishmine.org'\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "BMAP\n",
       ":   'https://bmap.jgi.doe.gov/bmapmine/'BeanMine\n",
       ":   'https://mines.legumeinfo.org/beanmine'BovineMine\n",
       ":   'http://genomes.missouri.edu/bovinemine'CHOmine\n",
       ":   'https://chomine.boku.ac.at/chomine'ChickpeaMine\n",
       ":   'https://mines.legumeinfo.org/chickpeamine'CowpeaMine\n",
       ":   'https://mines.legumeinfo.org/cowpeamine'FlyMine\n",
       ":   'http://www.flymine.org/flymine'GrapeMine\n",
       ":   'http://urgi.versailles.inra.fr/GrapeMine'HumanMine\n",
       ":   'http://www.humanmine.org/humanmine'HymenopteraMine\n",
       ":   'http://hymenopteragenome.org/hymenopteramine'IndigoMine\n",
       ":   'http://www.cbrc.kaust.edu.sa/indigo'LegumeMine\n",
       ":   'https://mines.legumeinfo.org/legumemine'MaizeMine\n",
       ":   'http://maizemine.rnet.missouri.edu:8080/maizemine'MedicMine\n",
       ":   'http://medicmine.jcvi.org/medicmine'MitoMiner\n",
       ":   'http://mitominer.mrc-mbu.cam.ac.uk/release-4.0'ModMine\n",
       ":   'http://intermine.modencode.org/release-33'MouseMine\n",
       ":   'http://www.mousemine.org/mousemine'OakMine\n",
       ":   'https://urgi.versailles.inra.fr/OakMine_PM1N'PeanutMine\n",
       ":   'https://mines.legumeinfo.org/peanutmine'PhytoMine\n",
       ":   'https://phytozome.jgi.doe.gov/phytomine/'PlanMine\n",
       ":   'http://planmine.mpi-cbg.de/planmine'RatMine\n",
       ":   'http://ratmine.mcw.edu/ratmine'RepetDB\n",
       ":   'http://urgi.versailles.inra.fr/repetdb'SoyMine\n",
       ":   'https://mines.legumeinfo.org/soymine'TargetMine\n",
       ":   'https://targetmine.mizuguchilab.org/targetmine'ThaleMine\n",
       ":   'https://apps.araport.org/thalemine'WheatMine\n",
       ":   'https://urgi.versailles.inra.fr/WheatMine'WormMine\n",
       ":   'http://intermine.wormbase.org/tools/wormmine/'XenMine\n",
       ":   'http://www.xenmine.org/xenmine'YeastMine\n",
       ":   'https://yeastmine.yeastgenome.org/yeastmine'ZebrafishMine\n",
       ":   'http://zebrafishmine.org'\n",
       "\n"
      ],
      "text/plain": [
       "                                               BMAP \n",
       "               \"https://bmap.jgi.doe.gov/bmapmine/\" \n",
       "                                           BeanMine \n",
       "            \"https://mines.legumeinfo.org/beanmine\" \n",
       "                                         BovineMine \n",
       "           \"http://genomes.missouri.edu/bovinemine\" \n",
       "                                            CHOmine \n",
       "               \"https://chomine.boku.ac.at/chomine\" \n",
       "                                       ChickpeaMine \n",
       "        \"https://mines.legumeinfo.org/chickpeamine\" \n",
       "                                         CowpeaMine \n",
       "          \"https://mines.legumeinfo.org/cowpeamine\" \n",
       "                                            FlyMine \n",
       "                   \"http://www.flymine.org/flymine\" \n",
       "                                          GrapeMine \n",
       "         \"http://urgi.versailles.inra.fr/GrapeMine\" \n",
       "                                          HumanMine \n",
       "               \"http://www.humanmine.org/humanmine\" \n",
       "                                    HymenopteraMine \n",
       "     \"http://hymenopteragenome.org/hymenopteramine\" \n",
       "                                         IndigoMine \n",
       "              \"http://www.cbrc.kaust.edu.sa/indigo\" \n",
       "                                         LegumeMine \n",
       "          \"https://mines.legumeinfo.org/legumemine\" \n",
       "                                          MaizeMine \n",
       "\"http://maizemine.rnet.missouri.edu:8080/maizemine\" \n",
       "                                          MedicMine \n",
       "              \"http://medicmine.jcvi.org/medicmine\" \n",
       "                                          MitoMiner \n",
       "   \"http://mitominer.mrc-mbu.cam.ac.uk/release-4.0\" \n",
       "                                            ModMine \n",
       "        \"http://intermine.modencode.org/release-33\" \n",
       "                                          MouseMine \n",
       "               \"http://www.mousemine.org/mousemine\" \n",
       "                                            OakMine \n",
       "     \"https://urgi.versailles.inra.fr/OakMine_PM1N\" \n",
       "                                         PeanutMine \n",
       "          \"https://mines.legumeinfo.org/peanutmine\" \n",
       "                                          PhytoMine \n",
       "         \"https://phytozome.jgi.doe.gov/phytomine/\" \n",
       "                                           PlanMine \n",
       "              \"http://planmine.mpi-cbg.de/planmine\" \n",
       "                                            RatMine \n",
       "                   \"http://ratmine.mcw.edu/ratmine\" \n",
       "                                            RepetDB \n",
       "           \"http://urgi.versailles.inra.fr/repetdb\" \n",
       "                                            SoyMine \n",
       "             \"https://mines.legumeinfo.org/soymine\" \n",
       "                                         TargetMine \n",
       "   \"https://targetmine.mizuguchilab.org/targetmine\" \n",
       "                                          ThaleMine \n",
       "               \"https://apps.araport.org/thalemine\" \n",
       "                                          WheatMine \n",
       "        \"https://urgi.versailles.inra.fr/WheatMine\" \n",
       "                                           WormMine \n",
       "    \"http://intermine.wormbase.org/tools/wormmine/\" \n",
       "                                            XenMine \n",
       "                   \"http://www.xenmine.org/xenmine\" \n",
       "                                          YeastMine \n",
       "      \"https://yeastmine.yeastgenome.org/yeastmine\" \n",
       "                                      ZebrafishMine \n",
       "                         \"http://zebrafishmine.org\" "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "listMines()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Okay, let's select HumanMine from this list:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<strong>HumanMine:</strong> 'http://www.humanmine.org/humanmine'"
      ],
      "text/latex": [
       "\\textbf{HumanMine:} 'http://www.humanmine.org/humanmine'"
      ],
      "text/markdown": [
       "**HumanMine:** 'http://www.humanmine.org/humanmine'"
      ],
      "text/plain": [
       "                           HumanMine \n",
       "\"http://www.humanmine.org/humanmine\" "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "humanMine <- listMines()[\"HumanMine\"] #select humanmine\n",
    "humanMine #print out the value to see what's inside"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And now we need to tell InterMineR to query HumanMine specifically:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "im <- initInterMine(mine=humanMine)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting started with Enrichment\n",
    "\n",
    "Performing enrichment analysis with InterMineR is preceded by two steps:\n",
    "\n",
    "1. Get the enrichment widget name which indicates the annotation types that you want to investigate for enrichment (e.g. Gene Ontology Terms, protein domains, KEGG and Reactome Pathways, human diseases, mammalian phenotypes and publications).\n",
    "2. Retrieve the list of bioentities of interest (Genes, Proteins, SNPs, etc.) for which the analysis will be performed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A matrix: 10 × 12 of type chr</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>startClassDisplay</th><th scope=col>enrichIdentifier</th><th scope=col>name</th><th scope=col>description</th><th scope=col>enrich</th><th scope=col>startClass</th><th scope=col>title</th><th scope=col>targets</th><th scope=col>widgetType</th><th scope=col>chartType</th><th scope=col>filters</th><th scope=col>labels</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>primaryIdentifier</td><td>GWASResults.study.publication.pubMedId                       </td><td>snp_gwas_study_enrichment       </td><td>GWAS studies enriched for SNPs in this list.                                                                                                                                                                                  </td><td>GWASResults.study.name                          </td><td>SNP    </td><td>GWAS study Enrichment for SNPs </td><td>SNP    </td><td>enrichment</td><td>NA         </td><td>NA                                                      </td><td>NA                </td></tr>\n",
       "\t<tr><td><span style=white-space:pre-wrap>NA               </span></td><td><span style=white-space:pre-wrap>NA                                                           </span></td><td>chromosome_distribution_for_snp </td><td><span style=white-space:pre-wrap>Actual: number of items in this list found on each chromosome.  Expected: given the total number of items on the chromosome and the number of items in this list, the number of items expected to be found on each chromosome.</span></td><td><span style=white-space:pre-wrap>NA                                              </span></td><td><span style=white-space:pre-wrap>SNP    </span></td><td><span style=white-space:pre-wrap>Chromosome Distribution        </span></td><td><span style=white-space:pre-wrap>SNP    </span></td><td><span style=white-space:pre-wrap>chart     </span></td><td>ColumnChart</td><td><span style=white-space:pre-wrap>organism.name=[list]                                    </span></td><td>Chromosome &amp; Count</td></tr>\n",
       "\t<tr><td>primaryIdentifier</td><td>goAnnotation.ontologyTerm.parents.identifier                 </td><td>go_enrichment_for_gene          </td><td>GO terms enriched for items in this list.                                                                                                                                                                                     </td><td>goAnnotation.ontologyTerm.parents.name          </td><td>Gene   </td><td>Gene Ontology Enrichment       </td><td>Gene   </td><td>enrichment</td><td>NA         </td><td>biological_process,cellular_component,molecular_function</td><td>NA                </td></tr>\n",
       "\t<tr><td>primaryIdentifier</td><td>publications.pubMedId                                        </td><td>publication_enrichment          </td><td>Publications enriched for genes in this list.                                                                                                                                                                                 </td><td>publications.title                              </td><td>Gene   </td><td>Publication Enrichment         </td><td>Gene   </td><td>enrichment</td><td>NA         </td><td>NA                                                      </td><td>NA                </td></tr>\n",
       "\t<tr><td><span style=white-space:pre-wrap>NA               </span></td><td><span style=white-space:pre-wrap>NA                                                           </span></td><td>chromosome_distribution_for_gene</td><td><span style=white-space:pre-wrap>Actual: number of items in this list found on each chromosome.  Expected: given the total number of items on the chromosome and the number of items in this list, the number of items expected to be found on each chromosome.</span></td><td><span style=white-space:pre-wrap>NA                                              </span></td><td><span style=white-space:pre-wrap>Gene   </span></td><td><span style=white-space:pre-wrap>Chromosome Distribution        </span></td><td><span style=white-space:pre-wrap>Gene   </span></td><td><span style=white-space:pre-wrap>chart     </span></td><td>ColumnChart</td><td><span style=white-space:pre-wrap>organism.name=[list]                                    </span></td><td>Chromosome &amp; Count</td></tr>\n",
       "\t<tr><td>primaryIdentifier</td><td>pathways.identifier                                          </td><td>pathway_enrichment              </td><td>Pathways enriched for genes in this list - data from KEGG and Reactome                                                                                                                                                        </td><td>pathways.name                                   </td><td>Gene   </td><td>Pathway Enrichment             </td><td>Gene   </td><td>enrichment</td><td>NA         </td><td>All,KEGG pathways data set,Reactome data set            </td><td>NA                </td></tr>\n",
       "\t<tr><td>primaryIdentifier</td><td>GWASResults.study.publication.pubMedId                       </td><td>snp_publication_enrichment      </td><td>Publications enriched for SNPs in this list.                                                                                                                                                                                  </td><td>GWASResults.study.publication.title             </td><td>SNP    </td><td>Publication Enrichment for SNPs</td><td>SNP    </td><td>enrichment</td><td>NA         </td><td>NA                                                      </td><td>NA                </td></tr>\n",
       "\t<tr><td>primaryIdentifier</td><td>proteins.proteinDomainRegions.proteinDomain.primaryIdentifier</td><td>prot_dom_enrichment_for_gene    </td><td>Protein Domains enriched for items in this list.                                                                                                                                                                              </td><td>proteins.proteinDomainRegions.proteinDomain.name</td><td>Gene   </td><td>Protein Domain Enrichment      </td><td>Gene   </td><td>enrichment</td><td>NA         </td><td>NA                                                      </td><td>NA                </td></tr>\n",
       "\t<tr><td>primaryIdentifier</td><td>proteinDomainRegions.proteinDomain.primaryIdentifier         </td><td>prot_dom_enrichment_for_protein </td><td>Protein Domains enriched for items in this list.                                                                                                                                                                              </td><td>proteinDomainRegions.proteinDomain.name         </td><td>Protein</td><td>Protein Domain Enrichment      </td><td>Protein</td><td>enrichment</td><td>NA         </td><td>NA                                                      </td><td>NA                </td></tr>\n",
       "\t<tr><td>NA               </td><td>NA                                                           </td><td>interactions                    </td><td>Genes (from the list or not) that interact with genes in this list.  Counts may include the same interaction more than once if observed in multiple experiments.                                                              </td><td>NA                                              </td><td>NA     </td><td>Interactions                   </td><td>Gene   </td><td>table     </td><td>NA         </td><td>NA                                                      </td><td>NA                </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 10 × 12 of type chr\n",
       "\\begin{tabular}{llllllllllll}\n",
       " startClassDisplay & enrichIdentifier & name & description & enrich & startClass & title & targets & widgetType & chartType & filters & labels\\\\\n",
       "\\hline\n",
       "\t primaryIdentifier & GWASResults.study.publication.pubMedId                        & snp\\_gwas\\_study\\_enrichment        & GWAS studies enriched for SNPs in this list.                                                                                                                                                                                   & GWASResults.study.name                           & SNP     & GWAS study Enrichment for SNPs  & SNP     & enrichment & NA          & NA                                                       & NA                \\\\\n",
       "\t NA                & NA                                                            & chromosome\\_distribution\\_for\\_snp  & Actual: number of items in this list found on each chromosome.  Expected: given the total number of items on the chromosome and the number of items in this list, the number of items expected to be found on each chromosome. & NA                                               & SNP     & Chromosome Distribution         & SNP     & chart      & ColumnChart & organism.name={[}list{]}                                     & Chromosome \\& Count\\\\\n",
       "\t primaryIdentifier & goAnnotation.ontologyTerm.parents.identifier                  & go\\_enrichment\\_for\\_gene           & GO terms enriched for items in this list.                                                                                                                                                                                      & goAnnotation.ontologyTerm.parents.name           & Gene    & Gene Ontology Enrichment        & Gene    & enrichment & NA          & biological\\_process,cellular\\_component,molecular\\_function & NA                \\\\\n",
       "\t primaryIdentifier & publications.pubMedId                                         & publication\\_enrichment           & Publications enriched for genes in this list.                                                                                                                                                                                  & publications.title                               & Gene    & Publication Enrichment          & Gene    & enrichment & NA          & NA                                                       & NA                \\\\\n",
       "\t NA                & NA                                                            & chromosome\\_distribution\\_for\\_gene & Actual: number of items in this list found on each chromosome.  Expected: given the total number of items on the chromosome and the number of items in this list, the number of items expected to be found on each chromosome. & NA                                               & Gene    & Chromosome Distribution         & Gene    & chart      & ColumnChart & organism.name={[}list{]}                                     & Chromosome \\& Count\\\\\n",
       "\t primaryIdentifier & pathways.identifier                                           & pathway\\_enrichment               & Pathways enriched for genes in this list - data from KEGG and Reactome                                                                                                                                                         & pathways.name                                    & Gene    & Pathway Enrichment              & Gene    & enrichment & NA          & All,KEGG pathways data set,Reactome data set             & NA                \\\\\n",
       "\t primaryIdentifier & GWASResults.study.publication.pubMedId                        & snp\\_publication\\_enrichment       & Publications enriched for SNPs in this list.                                                                                                                                                                                   & GWASResults.study.publication.title              & SNP     & Publication Enrichment for SNPs & SNP     & enrichment & NA          & NA                                                       & NA                \\\\\n",
       "\t primaryIdentifier & proteins.proteinDomainRegions.proteinDomain.primaryIdentifier & prot\\_dom\\_enrichment\\_for\\_gene     & Protein Domains enriched for items in this list.                                                                                                                                                                               & proteins.proteinDomainRegions.proteinDomain.name & Gene    & Protein Domain Enrichment       & Gene    & enrichment & NA          & NA                                                       & NA                \\\\\n",
       "\t primaryIdentifier & proteinDomainRegions.proteinDomain.primaryIdentifier          & prot\\_dom\\_enrichment\\_for\\_protein  & Protein Domains enriched for items in this list.                                                                                                                                                                               & proteinDomainRegions.proteinDomain.name          & Protein & Protein Domain Enrichment       & Protein & enrichment & NA          & NA                                                       & NA                \\\\\n",
       "\t NA                & NA                                                            & interactions                     & Genes (from the list or not) that interact with genes in this list.  Counts may include the same interaction more than once if observed in multiple experiments.                                                               & NA                                               & NA      & Interactions                    & Gene    & table      & NA          & NA                                                       & NA                \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 10 × 12 of type chr\n",
       "\n",
       "| startClassDisplay | enrichIdentifier | name | description | enrich | startClass | title | targets | widgetType | chartType | filters | labels |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| primaryIdentifier | GWASResults.study.publication.pubMedId                        | snp_gwas_study_enrichment        | GWAS studies enriched for SNPs in this list.                                                                                                                                                                                   | GWASResults.study.name                           | SNP     | GWAS study Enrichment for SNPs  | SNP     | enrichment | NA          | NA                                                       | NA                 |\n",
       "| NA                | NA                                                            | chromosome_distribution_for_snp  | Actual: number of items in this list found on each chromosome.  Expected: given the total number of items on the chromosome and the number of items in this list, the number of items expected to be found on each chromosome. | NA                                               | SNP     | Chromosome Distribution         | SNP     | chart      | ColumnChart | organism.name=[list]                                     | Chromosome &amp; Count |\n",
       "| primaryIdentifier | goAnnotation.ontologyTerm.parents.identifier                  | go_enrichment_for_gene           | GO terms enriched for items in this list.                                                                                                                                                                                      | goAnnotation.ontologyTerm.parents.name           | Gene    | Gene Ontology Enrichment        | Gene    | enrichment | NA          | biological_process,cellular_component,molecular_function | NA                 |\n",
       "| primaryIdentifier | publications.pubMedId                                         | publication_enrichment           | Publications enriched for genes in this list.                                                                                                                                                                                  | publications.title                               | Gene    | Publication Enrichment          | Gene    | enrichment | NA          | NA                                                       | NA                 |\n",
       "| NA                | NA                                                            | chromosome_distribution_for_gene | Actual: number of items in this list found on each chromosome.  Expected: given the total number of items on the chromosome and the number of items in this list, the number of items expected to be found on each chromosome. | NA                                               | Gene    | Chromosome Distribution         | Gene    | chart      | ColumnChart | organism.name=[list]                                     | Chromosome &amp; Count |\n",
       "| primaryIdentifier | pathways.identifier                                           | pathway_enrichment               | Pathways enriched for genes in this list - data from KEGG and Reactome                                                                                                                                                         | pathways.name                                    | Gene    | Pathway Enrichment              | Gene    | enrichment | NA          | All,KEGG pathways data set,Reactome data set             | NA                 |\n",
       "| primaryIdentifier | GWASResults.study.publication.pubMedId                        | snp_publication_enrichment       | Publications enriched for SNPs in this list.                                                                                                                                                                                   | GWASResults.study.publication.title              | SNP     | Publication Enrichment for SNPs | SNP     | enrichment | NA          | NA                                                       | NA                 |\n",
       "| primaryIdentifier | proteins.proteinDomainRegions.proteinDomain.primaryIdentifier | prot_dom_enrichment_for_gene     | Protein Domains enriched for items in this list.                                                                                                                                                                               | proteins.proteinDomainRegions.proteinDomain.name | Gene    | Protein Domain Enrichment       | Gene    | enrichment | NA          | NA                                                       | NA                 |\n",
       "| primaryIdentifier | proteinDomainRegions.proteinDomain.primaryIdentifier          | prot_dom_enrichment_for_protein  | Protein Domains enriched for items in this list.                                                                                                                                                                               | proteinDomainRegions.proteinDomain.name          | Protein | Protein Domain Enrichment       | Protein | enrichment | NA          | NA                                                       | NA                 |\n",
       "| NA                | NA                                                            | interactions                     | Genes (from the list or not) that interact with genes in this list.  Counts may include the same interaction more than once if observed in multiple experiments.                                                               | NA                                               | NA      | Interactions                    | Gene    | table      | NA          | NA                                                       | NA                 |\n",
       "\n"
      ],
      "text/plain": [
       "      startClassDisplay\n",
       " [1,] primaryIdentifier\n",
       " [2,] NA               \n",
       " [3,] primaryIdentifier\n",
       " [4,] primaryIdentifier\n",
       " [5,] NA               \n",
       " [6,] primaryIdentifier\n",
       " [7,] primaryIdentifier\n",
       " [8,] primaryIdentifier\n",
       " [9,] primaryIdentifier\n",
       "[10,] NA               \n",
       "      enrichIdentifier                                             \n",
       " [1,] GWASResults.study.publication.pubMedId                       \n",
       " [2,] NA                                                           \n",
       " [3,] goAnnotation.ontologyTerm.parents.identifier                 \n",
       " [4,] publications.pubMedId                                        \n",
       " [5,] NA                                                           \n",
       " [6,] pathways.identifier                                          \n",
       " [7,] GWASResults.study.publication.pubMedId                       \n",
       " [8,] proteins.proteinDomainRegions.proteinDomain.primaryIdentifier\n",
       " [9,] proteinDomainRegions.proteinDomain.primaryIdentifier         \n",
       "[10,] NA                                                           \n",
       "      name                            \n",
       " [1,] snp_gwas_study_enrichment       \n",
       " [2,] chromosome_distribution_for_snp \n",
       " [3,] go_enrichment_for_gene          \n",
       " [4,] publication_enrichment          \n",
       " [5,] chromosome_distribution_for_gene\n",
       " [6,] pathway_enrichment              \n",
       " [7,] snp_publication_enrichment      \n",
       " [8,] prot_dom_enrichment_for_gene    \n",
       " [9,] prot_dom_enrichment_for_protein \n",
       "[10,] interactions                    \n",
       "      description                                                                                                                                                                                                                   \n",
       " [1,] GWAS studies enriched for SNPs in this list.                                                                                                                                                                                  \n",
       " [2,] Actual: number of items in this list found on each chromosome.  Expected: given the total number of items on the chromosome and the number of items in this list, the number of items expected to be found on each chromosome.\n",
       " [3,] GO terms enriched for items in this list.                                                                                                                                                                                     \n",
       " [4,] Publications enriched for genes in this list.                                                                                                                                                                                 \n",
       " [5,] Actual: number of items in this list found on each chromosome.  Expected: given the total number of items on the chromosome and the number of items in this list, the number of items expected to be found on each chromosome.\n",
       " [6,] Pathways enriched for genes in this list - data from KEGG and Reactome                                                                                                                                                        \n",
       " [7,] Publications enriched for SNPs in this list.                                                                                                                                                                                  \n",
       " [8,] Protein Domains enriched for items in this list.                                                                                                                                                                              \n",
       " [9,] Protein Domains enriched for items in this list.                                                                                                                                                                              \n",
       "[10,] Genes (from the list or not) that interact with genes in this list.  Counts may include the same interaction more than once if observed in multiple experiments.                                                              \n",
       "      enrich                                           startClass\n",
       " [1,] GWASResults.study.name                           SNP       \n",
       " [2,] NA                                               SNP       \n",
       " [3,] goAnnotation.ontologyTerm.parents.name           Gene      \n",
       " [4,] publications.title                               Gene      \n",
       " [5,] NA                                               Gene      \n",
       " [6,] pathways.name                                    Gene      \n",
       " [7,] GWASResults.study.publication.title              SNP       \n",
       " [8,] proteins.proteinDomainRegions.proteinDomain.name Gene      \n",
       " [9,] proteinDomainRegions.proteinDomain.name          Protein   \n",
       "[10,] NA                                               NA        \n",
       "      title                           targets widgetType chartType  \n",
       " [1,] GWAS study Enrichment for SNPs  SNP     enrichment NA         \n",
       " [2,] Chromosome Distribution         SNP     chart      ColumnChart\n",
       " [3,] Gene Ontology Enrichment        Gene    enrichment NA         \n",
       " [4,] Publication Enrichment          Gene    enrichment NA         \n",
       " [5,] Chromosome Distribution         Gene    chart      ColumnChart\n",
       " [6,] Pathway Enrichment              Gene    enrichment NA         \n",
       " [7,] Publication Enrichment for SNPs SNP     enrichment NA         \n",
       " [8,] Protein Domain Enrichment       Gene    enrichment NA         \n",
       " [9,] Protein Domain Enrichment       Protein enrichment NA         \n",
       "[10,] Interactions                    Gene    table      NA         \n",
       "      filters                                                 \n",
       " [1,] NA                                                      \n",
       " [2,] organism.name=[list]                                    \n",
       " [3,] biological_process,cellular_component,molecular_function\n",
       " [4,] NA                                                      \n",
       " [5,] organism.name=[list]                                    \n",
       " [6,] All,KEGG pathways data set,Reactome data set            \n",
       " [7,] NA                                                      \n",
       " [8,] NA                                                      \n",
       " [9,] NA                                                      \n",
       "[10,] NA                                                      \n",
       "      labels            \n",
       " [1,] NA                \n",
       " [2,] Chromosome & Count\n",
       " [3,] NA                \n",
       " [4,] NA                \n",
       " [5,] Chromosome & Count\n",
       " [6,] NA                \n",
       " [7,] NA                \n",
       " [8,] NA                \n",
       " [9,] NA                \n",
       "[10,] NA                "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# First, we'll retrieve the widgets available from HumanMine. This will tell us what types of enrichment are available.\n",
    "\n",
    "humanWidgets <- getWidgets(im)\n",
    "\n",
    "# Print out the widgets so we can see what there is\n",
    "\n",
    "humanWidgets\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Take a look through the widgets returned, especially the columns `targets` and `widgetType`. Since we plan to enrich the gene list `PL_GenomicsEngland_GenePanel:Genetic_Epilepsy_Syndromes`, we're only interested in widgets that target `Gene`s. Similarly, we don't need to look at any widgets that aren't `enrichment` type widgets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 4 × 12</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>startClassDisplay</th><th scope=col>enrichIdentifier</th><th scope=col>name</th><th scope=col>description</th><th scope=col>enrich</th><th scope=col>startClass</th><th scope=col>title</th><th scope=col>targets</th><th scope=col>widgetType</th><th scope=col>chartType</th><th scope=col>filters</th><th scope=col>labels</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>3</th><td>primaryIdentifier</td><td>goAnnotation.ontologyTerm.parents.identifier                 </td><td>go_enrichment_for_gene      </td><td>GO terms enriched for items in this list.                             </td><td>goAnnotation.ontologyTerm.parents.name          </td><td>Gene</td><td>Gene Ontology Enrichment </td><td>Gene</td><td>enrichment</td><td>NA</td><td>biological_process,cellular_component,molecular_function</td><td>NA</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>primaryIdentifier</td><td>publications.pubMedId                                        </td><td>publication_enrichment      </td><td>Publications enriched for genes in this list.                         </td><td>publications.title                              </td><td>Gene</td><td>Publication Enrichment   </td><td>Gene</td><td>enrichment</td><td>NA</td><td>NA                                                      </td><td>NA</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>primaryIdentifier</td><td>pathways.identifier                                          </td><td>pathway_enrichment          </td><td>Pathways enriched for genes in this list - data from KEGG and Reactome</td><td>pathways.name                                   </td><td>Gene</td><td>Pathway Enrichment       </td><td>Gene</td><td>enrichment</td><td>NA</td><td>All,KEGG pathways data set,Reactome data set            </td><td>NA</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>primaryIdentifier</td><td>proteins.proteinDomainRegions.proteinDomain.primaryIdentifier</td><td>prot_dom_enrichment_for_gene</td><td>Protein Domains enriched for items in this list.                      </td><td>proteins.proteinDomainRegions.proteinDomain.name</td><td>Gene</td><td>Protein Domain Enrichment</td><td>Gene</td><td>enrichment</td><td>NA</td><td>NA                                                      </td><td>NA</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 4 × 12\n",
       "\\begin{tabular}{r|llllllllllll}\n",
       "  & startClassDisplay & enrichIdentifier & name & description & enrich & startClass & title & targets & widgetType & chartType & filters & labels\\\\\n",
       "  & <fct> & <fct> & <fct> & <fct> & <fct> & <fct> & <fct> & <fct> & <fct> & <fct> & <fct> & <fct>\\\\\n",
       "\\hline\n",
       "\t3 & primaryIdentifier & goAnnotation.ontologyTerm.parents.identifier                  & go\\_enrichment\\_for\\_gene       & GO terms enriched for items in this list.                              & goAnnotation.ontologyTerm.parents.name           & Gene & Gene Ontology Enrichment  & Gene & enrichment & NA & biological\\_process,cellular\\_component,molecular\\_function & NA\\\\\n",
       "\t4 & primaryIdentifier & publications.pubMedId                                         & publication\\_enrichment       & Publications enriched for genes in this list.                          & publications.title                               & Gene & Publication Enrichment    & Gene & enrichment & NA & NA                                                       & NA\\\\\n",
       "\t6 & primaryIdentifier & pathways.identifier                                           & pathway\\_enrichment           & Pathways enriched for genes in this list - data from KEGG and Reactome & pathways.name                                    & Gene & Pathway Enrichment        & Gene & enrichment & NA & All,KEGG pathways data set,Reactome data set             & NA\\\\\n",
       "\t8 & primaryIdentifier & proteins.proteinDomainRegions.proteinDomain.primaryIdentifier & prot\\_dom\\_enrichment\\_for\\_gene & Protein Domains enriched for items in this list.                       & proteins.proteinDomainRegions.proteinDomain.name & Gene & Protein Domain Enrichment & Gene & enrichment & NA & NA                                                       & NA\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 4 × 12\n",
       "\n",
       "| <!--/--> | startClassDisplay &lt;fct&gt; | enrichIdentifier &lt;fct&gt; | name &lt;fct&gt; | description &lt;fct&gt; | enrich &lt;fct&gt; | startClass &lt;fct&gt; | title &lt;fct&gt; | targets &lt;fct&gt; | widgetType &lt;fct&gt; | chartType &lt;fct&gt; | filters &lt;fct&gt; | labels &lt;fct&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 3 | primaryIdentifier | goAnnotation.ontologyTerm.parents.identifier                  | go_enrichment_for_gene       | GO terms enriched for items in this list.                              | goAnnotation.ontologyTerm.parents.name           | Gene | Gene Ontology Enrichment  | Gene | enrichment | NA | biological_process,cellular_component,molecular_function | NA |\n",
       "| 4 | primaryIdentifier | publications.pubMedId                                         | publication_enrichment       | Publications enriched for genes in this list.                          | publications.title                               | Gene | Publication Enrichment    | Gene | enrichment | NA | NA                                                       | NA |\n",
       "| 6 | primaryIdentifier | pathways.identifier                                           | pathway_enrichment           | Pathways enriched for genes in this list - data from KEGG and Reactome | pathways.name                                    | Gene | Pathway Enrichment        | Gene | enrichment | NA | All,KEGG pathways data set,Reactome data set             | NA |\n",
       "| 8 | primaryIdentifier | proteins.proteinDomainRegions.proteinDomain.primaryIdentifier | prot_dom_enrichment_for_gene | Protein Domains enriched for items in this list.                       | proteins.proteinDomainRegions.proteinDomain.name | Gene | Protein Domain Enrichment | Gene | enrichment | NA | NA                                                       | NA |\n",
       "\n"
      ],
      "text/plain": [
       "  startClassDisplay\n",
       "3 primaryIdentifier\n",
       "4 primaryIdentifier\n",
       "6 primaryIdentifier\n",
       "8 primaryIdentifier\n",
       "  enrichIdentifier                                             \n",
       "3 goAnnotation.ontologyTerm.parents.identifier                 \n",
       "4 publications.pubMedId                                        \n",
       "6 pathways.identifier                                          \n",
       "8 proteins.proteinDomainRegions.proteinDomain.primaryIdentifier\n",
       "  name                        \n",
       "3 go_enrichment_for_gene      \n",
       "4 publication_enrichment      \n",
       "6 pathway_enrichment          \n",
       "8 prot_dom_enrichment_for_gene\n",
       "  description                                                           \n",
       "3 GO terms enriched for items in this list.                             \n",
       "4 Publications enriched for genes in this list.                         \n",
       "6 Pathways enriched for genes in this list - data from KEGG and Reactome\n",
       "8 Protein Domains enriched for items in this list.                      \n",
       "  enrich                                           startClass\n",
       "3 goAnnotation.ontologyTerm.parents.name           Gene      \n",
       "4 publications.title                               Gene      \n",
       "6 pathways.name                                    Gene      \n",
       "8 proteins.proteinDomainRegions.proteinDomain.name Gene      \n",
       "  title                     targets widgetType chartType\n",
       "3 Gene Ontology Enrichment  Gene    enrichment NA       \n",
       "4 Publication Enrichment    Gene    enrichment NA       \n",
       "6 Pathway Enrichment        Gene    enrichment NA       \n",
       "8 Protein Domain Enrichment Gene    enrichment NA       \n",
       "  filters                                                  labels\n",
       "3 biological_process,cellular_component,molecular_function NA    \n",
       "4 NA                                                       NA    \n",
       "6 All,KEGG pathways data set,Reactome data set             NA    \n",
       "8 NA                                                       NA    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We'll put the widget list in a data frame, so it's easy to filter.\n",
    "humanWidgetsDataFrame <- as.data.frame(humanWidgets)\n",
    "\n",
    "# Now let's ask the data frame to give us a subset of the widgets.\n",
    "subset(humanWidgetsDataFrame, widgetType == 'enrichment' & targets == 'Gene')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Syntax Note: `=` vs `==`\n",
    "##### Assignment operator: `=` or `<-`\n",
    "In the code example above, we use the double equals sign `==`. This is because a single equals sign is used for *assignment*, e.g. `kittens = 5`, which would assign the value 5 to the variable `kittens`.  \n",
    "\n",
    "In R we also use `<-` for assignment, so `kittens = 5` and `kittens <- 5` do (basically) the same thing.\n",
    "\n",
    "##### Comparison operator: `==`\n",
    "The double equals, however, is used for comparison - when we say `widgetType == 'enrichment'` we're saying that the code should compare all `widgetTypes`, and only give us ones that are equal to `enrichment`. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Perform enrichment analysis\n",
    "\n",
    "Looking at the filtered list of widgets above, it looks like the widget we want to use to check for enriched GO Terms is named `go_enrichment_for_gene`. We'll use the `doEnrichment` method to get the enrichment results from HumanMine. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<dl>\n",
       "\t<dt>$data</dt>\n",
       "\t\t<dd><table>\n",
       "<caption>A data.frame: 9 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>identifier</th><th scope=col>description</th><th scope=col>pValue</th><th scope=col>count</th><th scope=col>populationAnnotationCount</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>GO:0086010</td><td>membrane depolarization during action potential</td><td>0.0029933397620292668</td><td>3</td><td>36  </td></tr>\n",
       "\t<tr><td>GO:0019226</td><td>transmission of nerve impulse                  </td><td>0.012440595908190567 </td><td>3</td><td>72  </td></tr>\n",
       "\t<tr><td>GO:0051899</td><td>membrane depolarization                        </td><td>0.013711012061119023 </td><td>3</td><td>85  </td></tr>\n",
       "\t<tr><td>GO:0019227</td><td>neuronal action potential propagation          </td><td>0.015706289435420368 </td><td>2</td><td>9   </td></tr>\n",
       "\t<tr><td>GO:0098870</td><td>action potential propagation                   </td><td>0.015706289435420368 </td><td>2</td><td>9   </td></tr>\n",
       "\t<tr><td>GO:0042391</td><td>regulation of membrane potential               </td><td>0.015721651039763786 </td><td>4</td><td>421 </td></tr>\n",
       "\t<tr><td>GO:0001508</td><td>action potential                               </td><td>0.019257259325613202 </td><td>3</td><td>126 </td></tr>\n",
       "\t<tr><td>GO:0035725</td><td>sodium ion transmembrane transport             </td><td>0.022633164613943716 </td><td>3</td><td>139 </td></tr>\n",
       "\t<tr><td>GO:0050877</td><td>nervous system process                         </td><td>0.03723962575587324  </td><td>5</td><td>1365</td></tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</dd>\n",
       "\t<dt>$populationCount</dt>\n",
       "\t\t<dd>16597</dd>\n",
       "\t<dt>$notAnalysed</dt>\n",
       "\t\t<dd>0</dd>\n",
       "\t<dt>$im</dt>\n",
       "\t\t<dd><dl>\n",
       "\t<dt>$mine</dt>\n",
       "\t\t<dd><strong>HumanMine:</strong> 'http://www.humanmine.org/humanmine'</dd>\n",
       "\t<dt>$token</dt>\n",
       "\t\t<dd>''</dd>\n",
       "</dl>\n",
       "</dd>\n",
       "\t<dt>$parameters</dt>\n",
       "\t\t<dd><dl class=dl-horizontal>\n",
       "\t<dt>genelist</dt>\n",
       "\t\t<dd>'PL_GenomicsEngland_GenePanel:Genetic_Epilepsy_Syndromes'</dd>\n",
       "\t<dt>widget</dt>\n",
       "\t\t<dd>'go_enrichment_for_gene'</dd>\n",
       "\t<dt>maxp</dt>\n",
       "\t\t<dd>'0.05'</dd>\n",
       "\t<dt>correction</dt>\n",
       "\t\t<dd>'Benjamini Hochberg'</dd>\n",
       "</dl>\n",
       "</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description}\n",
       "\\item[\\$data] A data.frame: 9 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       " identifier & description & pValue & count & populationAnnotationCount\\\\\n",
       " <chr> & <chr> & <chr> & <chr> & <chr>\\\\\n",
       "\\hline\n",
       "\t GO:0086010 & membrane depolarization during action potential & 0.0029933397620292668 & 3 & 36  \\\\\n",
       "\t GO:0019226 & transmission of nerve impulse                   & 0.012440595908190567  & 3 & 72  \\\\\n",
       "\t GO:0051899 & membrane depolarization                         & 0.013711012061119023  & 3 & 85  \\\\\n",
       "\t GO:0019227 & neuronal action potential propagation           & 0.015706289435420368  & 2 & 9   \\\\\n",
       "\t GO:0098870 & action potential propagation                    & 0.015706289435420368  & 2 & 9   \\\\\n",
       "\t GO:0042391 & regulation of membrane potential                & 0.015721651039763786  & 4 & 421 \\\\\n",
       "\t GO:0001508 & action potential                                & 0.019257259325613202  & 3 & 126 \\\\\n",
       "\t GO:0035725 & sodium ion transmembrane transport              & 0.022633164613943716  & 3 & 139 \\\\\n",
       "\t GO:0050877 & nervous system process                          & 0.03723962575587324   & 5 & 1365\\\\\n",
       "\\end{tabular}\n",
       "\n",
       "\\item[\\$populationCount] 16597\n",
       "\\item[\\$notAnalysed] 0\n",
       "\\item[\\$im] \\begin{description}\n",
       "\\item[\\$mine] \\textbf{HumanMine:} 'http://www.humanmine.org/humanmine'\n",
       "\\item[\\$token] ''\n",
       "\\end{description}\n",
       "\n",
       "\\item[\\$parameters] \\begin{description*}\n",
       "\\item[genelist] 'PL\\_GenomicsEngland\\_GenePanel:Genetic\\_Epilepsy\\_Syndromes'\n",
       "\\item[widget] 'go\\_enrichment\\_for\\_gene'\n",
       "\\item[maxp] '0.05'\n",
       "\\item[correction] 'Benjamini Hochberg'\n",
       "\\end{description*}\n",
       "\n",
       "\\end{description}\n"
      ],
      "text/markdown": [
       "$data\n",
       ":   \n",
       "A data.frame: 9 × 5\n",
       "\n",
       "| identifier &lt;chr&gt; | description &lt;chr&gt; | pValue &lt;chr&gt; | count &lt;chr&gt; | populationAnnotationCount &lt;chr&gt; |\n",
       "|---|---|---|---|---|\n",
       "| GO:0086010 | membrane depolarization during action potential | 0.0029933397620292668 | 3 | 36   |\n",
       "| GO:0019226 | transmission of nerve impulse                   | 0.012440595908190567  | 3 | 72   |\n",
       "| GO:0051899 | membrane depolarization                         | 0.013711012061119023  | 3 | 85   |\n",
       "| GO:0019227 | neuronal action potential propagation           | 0.015706289435420368  | 2 | 9    |\n",
       "| GO:0098870 | action potential propagation                    | 0.015706289435420368  | 2 | 9    |\n",
       "| GO:0042391 | regulation of membrane potential                | 0.015721651039763786  | 4 | 421  |\n",
       "| GO:0001508 | action potential                                | 0.019257259325613202  | 3 | 126  |\n",
       "| GO:0035725 | sodium ion transmembrane transport              | 0.022633164613943716  | 3 | 139  |\n",
       "| GO:0050877 | nervous system process                          | 0.03723962575587324   | 5 | 1365 |\n",
       "\n",
       "\n",
       "$populationCount\n",
       ":   16597\n",
       "$notAnalysed\n",
       ":   0\n",
       "$im\n",
       ":   $mine\n",
       ":   **HumanMine:** 'http://www.humanmine.org/humanmine'\n",
       "$token\n",
       ":   ''\n",
       "\n",
       "\n",
       "\n",
       "$parameters\n",
       ":   genelist\n",
       ":   'PL_GenomicsEngland_GenePanel:Genetic_Epilepsy_Syndromes'widget\n",
       ":   'go_enrichment_for_gene'maxp\n",
       ":   '0.05'correction\n",
       ":   'Benjamini Hochberg'\n",
       "\n",
       "\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "$data\n",
       "  identifier                                     description\n",
       "1 GO:0086010 membrane depolarization during action potential\n",
       "2 GO:0019226                   transmission of nerve impulse\n",
       "3 GO:0051899                         membrane depolarization\n",
       "4 GO:0019227           neuronal action potential propagation\n",
       "5 GO:0098870                    action potential propagation\n",
       "6 GO:0042391                regulation of membrane potential\n",
       "7 GO:0001508                                action potential\n",
       "8 GO:0035725              sodium ion transmembrane transport\n",
       "9 GO:0050877                          nervous system process\n",
       "                 pValue count populationAnnotationCount\n",
       "1 0.0029933397620292668     3                        36\n",
       "2  0.012440595908190567     3                        72\n",
       "3  0.013711012061119023     3                        85\n",
       "4  0.015706289435420368     2                         9\n",
       "5  0.015706289435420368     2                         9\n",
       "6  0.015721651039763786     4                       421\n",
       "7  0.019257259325613202     3                       126\n",
       "8  0.022633164613943716     3                       139\n",
       "9   0.03723962575587324     5                      1365\n",
       "\n",
       "$populationCount\n",
       "[1] 16597\n",
       "\n",
       "$notAnalysed\n",
       "[1] 0\n",
       "\n",
       "$im\n",
       "$im$mine\n",
       "                           HumanMine \n",
       "\"http://www.humanmine.org/humanmine\" \n",
       "\n",
       "$im$token\n",
       "[1] \"\"\n",
       "\n",
       "\n",
       "$parameters\n",
       "                                                 genelist \n",
       "\"PL_GenomicsEngland_GenePanel:Genetic_Epilepsy_Syndromes\" \n",
       "                                                   widget \n",
       "                                 \"go_enrichment_for_gene\" \n",
       "                                                     maxp \n",
       "                                                   \"0.05\" \n",
       "                                               correction \n",
       "                                     \"Benjamini Hochberg\" \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We're using the widget `go_enrichment_for_gene` against the list name \n",
    "# `PL_GenomicsEngland_GenePanel:Genetic_Epilepsy_Syndromes`\n",
    "#\n",
    "#Syntax: \n",
    "#\n",
    "# GO_enrichResult = doEnrichment(\n",
    "#   im = YOUR_CHOSEN_INTERMINE_HERE\n",
    "#   genelist = LIST_NAME_SAVE_ON_YOUR_CHOSEN_INTERMINE,\n",
    "#   widget = \"go_enrichment_for_gene\"\n",
    "#   organism = \"Homo sapiens\" # optional if results from more than one organism are retrieved\n",
    "# )\n",
    "\n",
    "GOEnrichmentResult = doEnrichment(\n",
    "  im = im,\n",
    "  genelist = \"PL_GenomicsEngland_GenePanel:Genetic_Epilepsy_Syndromes\",\n",
    "  widget = \"go_enrichment_for_gene\"\n",
    ")\n",
    "\n",
    "# Print the results \n",
    "GOEnrichmentResult"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualise it with Gene Answers \n",
    "\n",
    "    \n",
    "For the visualisation, we'll need both the enrichment results and the list of genes we originally enriched - but the list is still on the server. Let's run a query to get the primaryIdentifiers for the genes in `PL_GenomicsEngland_GenePanel:Genetic_Epilepsy_Syndromes`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 6 × 1</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>Gene.primaryIdentifier</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>2566 </td></tr>\n",
       "\t<tr><td>57094</td></tr>\n",
       "\t<tr><td>6323 </td></tr>\n",
       "\t<tr><td>6324 </td></tr>\n",
       "\t<tr><td>6335 </td></tr>\n",
       "\t<tr><td>84059</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 1\n",
       "\\begin{tabular}{r|l}\n",
       " Gene.primaryIdentifier\\\\\n",
       " <chr>\\\\\n",
       "\\hline\n",
       "\t 2566 \\\\\n",
       "\t 57094\\\\\n",
       "\t 6323 \\\\\n",
       "\t 6324 \\\\\n",
       "\t 6335 \\\\\n",
       "\t 84059\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 1\n",
       "\n",
       "| Gene.primaryIdentifier &lt;chr&gt; |\n",
       "|---|\n",
       "| 2566  |\n",
       "| 57094 |\n",
       "| 6323  |\n",
       "| 6324  |\n",
       "| 6335  |\n",
       "| 84059 |\n",
       "\n"
      ],
      "text/plain": [
       "  Gene.primaryIdentifier\n",
       "1 2566                  \n",
       "2 57094                 \n",
       "3 6323                  \n",
       "4 6324                  \n",
       "5 6335                  \n",
       "6 84059                 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We'll be using the setQuery method here\n",
    "# \n",
    "# Syntax: \n",
    "# setQuery( \n",
    "#  select = c(\"VIEW.NAME1\", \"VIEW.NAME2\", .... ),\n",
    "#  where = setConstraints(\n",
    "#    paths = c(\"CONSTRAINT.PATH.A\", \"CONSTRAINT.PATH.B\"),\n",
    "#    operators = c(\"CONSTRAINT.OPERATOR.A\", \"CONSTRAINT.OPERATOR.B\"),\n",
    "#    values = list(\"CONSTRAINT.VALUE.A\",\"CONSTRAINT.VALUE.B\")\n",
    "#  )\n",
    "#)\n",
    "queryEpilepsy <- setQuery(\n",
    "  # Choose which columns of data we'd like to see\n",
    "  select = c(\"Gene.primaryIdentifier\"),\n",
    "  where = setConstraints(\n",
    "      paths = c(\"Gene\"),\n",
    "      operators = c(\"IN\"),\n",
    "      values = list(\"PL_GenomicsEngland_GenePanel:Genetic_Epilepsy_Syndromes\"))\n",
    ")\n",
    "\n",
    "queryEpilepsyResults <- runQuery(im, queryEpilepsy)\n",
    "queryEpilepsyResults"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Format data for GeneAnswers\n",
    "\n",
    "We'll be using [GeneAnswers](https://bioconductor.org/packages/release/bioc/html/GeneAnswers.html) to generate some visualisations of the data we've just fetched, so we'll need to convert our InterMine data into a shape that GeneAnswers can read. Luckily, there's a nice method for that in InterMineR: `convertToGeneAnswers`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load GeneAnswers package\n",
    "library(GeneAnswers)\n",
    "\n",
    "# convert InterMineR Gene Ontology Enrichment analysis results to GeneAnswers object\n",
    "queryEpilepsyForGeneAnswers = convertToGeneAnswers(\n",
    "  \n",
    "  # Pass the enrichment results we ran earlier to GeneAnswers:\n",
    "  enrichmentResult = GOEnrichmentResult,\n",
    "  \n",
    "  # Pass in our original list of gene IDs \n",
    "  geneInput = data.frame(GeneID = queryEpilepsyResults, \n",
    "                         stringsAsFactors = FALSE),\n",
    "  \n",
    "  # in our example we use Gene.primaryIdentifier values\n",
    "  geneInputType = \"Gene.primaryIdentifier\",\n",
    "    \n",
    "  # The type of enrichment widget we ran\n",
    "  # in our example we use Gene Ontology (GO) terms:\n",
    "  categoryType = \"GO\"  \n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use the summary(geneAnswersObjectHere) function to see\n",
    "interesting info about our list + enrichment.... "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This GeneAnswers instance was build from GO based on hyperG test.\n",
      "Statistical information of 9 categories with p value less than 0.05 are reported. Other categories are considered as nonsignificant.\n",
      "There are 9 categories related to the given 6 genes\n",
      "\n",
      "Summary of GeneAnswers instance information:\n",
      "\n",
      "Slot: geneInput\n",
      "  Gene.primaryIdentifier\n",
      "1                   2566\n",
      "2                  57094\n",
      "3                   6323\n",
      "4                   6324\n",
      "5                   6335\n",
      "6                  84059\n",
      "\n",
      "Slot: testType\n",
      "[1] \"hyperG\"\n",
      "\n",
      "Slot: pvalueT\n",
      "[1] 0.05\n",
      "\n",
      "Slot: genesInCategory\n",
      "$`GO:0086010`\n",
      "[1] \"6323\" \"6324\" \"6335\"\n",
      "\n",
      "$`GO:0019226`\n",
      "[1] \"6323\" \"6324\" \"6335\"\n",
      "\n",
      "$`GO:0051899`\n",
      "[1] \"6323\" \"6324\" \"6335\"\n",
      "\n",
      "$`GO:0019227`\n",
      "[1] \"6323\" \"6324\"\n",
      "\n",
      "$`GO:0098870`\n",
      "[1] \"6323\" \"6324\"\n",
      "\n",
      "$`GO:0042391`\n",
      "[1] \"2566\" \"6323\" \"6324\" \"6335\"\n",
      "\n",
      "......\n",
      "\n",
      "Slot: geneExprProfile\n",
      "NULL\n",
      "\n",
      "Slot: annLib\n",
      "[1] \"org.Hs.eg.db\"\n",
      "\n",
      "Slot: categoryType\n",
      "[1] \"GO\"\n",
      "\n",
      "Slot: enrichmentInfo\n",
      "           genes in Category percent in the observed List percent in the genome\n",
      "GO:0086010                 3                    0.5000000          0.0021690667\n",
      "GO:0019226                 3                    0.5000000          0.0043381334\n",
      "GO:0051899                 3                    0.5000000          0.0051214075\n",
      "GO:0019227                 2                    0.3333333          0.0005422667\n",
      "GO:0098870                 2                    0.3333333          0.0005422667\n",
      "GO:0042391                 4                    0.6666667          0.0253660300\n",
      "           fold of overrepresents odds ratio    p value fdr p value\n",
      "GO:0086010              230.51389  460.02778 0.00299334  0.00299334\n",
      "GO:0019226              115.25694  229.51389 0.01244060  0.01244060\n",
      "GO:0051899               97.62941  194.25882 0.01371101  0.01371101\n",
      "GO:0019227              614.70370  921.55556 0.01570629  0.01570629\n",
      "GO:0098870              614.70370  921.55556 0.01570629  0.01570629\n",
      "GO:0042391               26.28187   76.84561 0.01572165  0.01572165\n",
      "......\n"
     ]
    }
   ],
   "source": [
    "summary(queryEpilepsyForGeneAnswers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### It's time for some graphs\n",
    "\n",
    "We'll start with a concept-gene network that shows which genes are associated with our given GO terms\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FHEzZvIyXF8f5YNygDA1AJjHUzNMLXD1A5BDZUHBA+oPOESCoG3ronGHoMd0YBE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AsxlpaV43vJlgGFRUDDugYzRCqURwsHBj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\nE088kZ6ebr+v1WqNRuP48VNmZmZycrKtrddLAOh0+OILlJUN6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mywXnIPq3viiSe4PfPz80d8S01NzcDAgK+v74gTsgDCw8MdNskOKiqG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",
      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "geneAnswersConceptNet(queryEpilepsyForGeneAnswers, \n",
    "                      colorValueColumn=NULL,\n",
    "                      centroidSize='correctedPvalue', \n",
    "                      output='fixed',\n",
    "                      geneSymbol = TRUE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### GO structure network\n",
    "\n",
    "We can plot the GO terms that our list is enriched for to show their relationships to one another:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"Search Tree Merge without filterGraphIDs!\"\n",
      "[1] \"Searching hubs ...\"\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: GO.db\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"The Graph without any nodes removal is not a connected one. Search 4 layer(s). Drawing network ...\"\n",
      "[1] \"Building graph structure ...\"\n",
      "[1] \"Removing NULL element ...\"\n",
      "[1] \"Removing NA ..., including NA in names of the input list\"\n",
      "[1] \"Converting to a matrix ...\"\n",
      "[1] \"For the given directed graph, the node 1 or 2 or 3 might be the root.\"\n"
     ]
    },
    {
     "data": {
      "image/png": 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veMS6rR+47p5wzfd0MVFV2YnPy7Y5W5nx9rTE5M/EpBwf6GhvMHDz5/yJDs1NTB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",
      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "geneAnswersConceptRelation(queryEpilepsyForGeneAnswers,\n",
    "                           directed=TRUE, \n",
    "                           output=\"fixed\",\n",
    "                           netMode='connection') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Gene Interaction Network\n",
    "\n",
    "In this example, GeneAnswers uses the annotation package ‘org.Hs.eg.db’, which was used previously in convertToGeneAnswers function, to retrieve gene interactions for the specified genes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"Building graph structure ...\"\n",
      "[1] \"Removing NULL element ...\"\n",
      "[1] \"Removing NA ..., including NA in names of the input list\"\n",
      "[1] \"Converting to a matrix ...\"\n",
      "[1] \"For the given undirected graph, the node 3 might be the root.\"\n"
     ]
    },
    {
     "data": {
      "image/png": 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/Ly8ldffVU55h04cODEiRMvvviij4+PjdegnW3evPnbb791c3N76qmn+vbtC6Ci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      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "buildNet(getGeneInput(queryEpilepsyForGeneAnswers)[,1],\n",
    "         idType='GeneInteraction', \n",
    "         layers=3,\n",
    "         output=\"fixed\",\n",
    "         filterGraphIDs=getGeneInput(queryEpilepsyForGeneAnswers)[,1],\n",
    "         filterLayer=2, \n",
    "         netMode='connection')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gene Interaction Network for **PL_GenomicsEngland_GenePanel:Genetic_Epilepsy_Syndromes**.   \n",
    "\n",
    "The large black dots with yellow frame stand for the six given genes. They also connect to other genes by dark-blue-purple edges. Small black dots represent the other genes from getGeneInput. Small white dots are genes that are not in the genes from getGeneInput, but interact with these genes. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Genes vs GO Term heat map\n",
    "\n",
    "Let's plot the genes which were enriched for GO terms in a heat map..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initial  value 0.000000 \n",
      "final  value 0.000000 \n",
      "converged\n",
      "initial  value 0.000000 \n",
      "final  value 0.000000 \n",
      "converged\n"
     ]
    },
    {
     "data": {
      "image/png": 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h5VsSLx703In2DKPaf5Du6A/cDm9uih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\nQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "geneAnswersHeatmap(queryEpilepsyForGeneAnswers, \n",
    "                   catTerm=TRUE, \n",
    "                   geneSymbol=TRUE,\n",
    "                   cex.axis = 0.75)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}