#Begin by activating the InterMineR library:
library(InterMineR)

listMines()

humanMine <- listMines()["HumanMine"] #select humanmine
humanMine #print out the value to see what's inside

im <- initInterMine(mine=humanMine)

# First, we'll retrieve the widgets available from HumanMine. This will tell us what types of enrichment are available.

humanWidgets <- getWidgets(im)

# Print out the widgets so we can see what there is

humanWidgets


# We'll put the widget list in a data frame, so it's easy to filter.
humanWidgetsDataFrame <- as.data.frame(humanWidgets)

# Now let's ask the data frame to give us a subset of the widgets.
subset(humanWidgetsDataFrame, widgetType == 'enrichment' & targets == 'Gene')

# We're using the widget `go_enrichment_for_gene` against the list name 
# `PL_GenomicsEngland_GenePanel:Genetic_Epilepsy_Syndromes`
#
#Syntax: 
#
# GO_enrichResult = doEnrichment(
#   im = YOUR_CHOSEN_INTERMINE_HERE
#   genelist = LIST_NAME_SAVE_ON_YOUR_CHOSEN_INTERMINE,
#   widget = "go_enrichment_for_gene"
#   organism = "Homo sapiens" # optional if results from more than one organism are retrieved
# )

GOEnrichmentResult = doEnrichment(
  im = im,
  genelist = "PL_GenomicsEngland_GenePanel:Genetic_Epilepsy_Syndromes",
  widget = "go_enrichment_for_gene"
)

# Print the results 
GOEnrichmentResult

# We'll be using the setQuery method here
# 
# Syntax: 
# setQuery( 
#  select = c("VIEW.NAME1", "VIEW.NAME2", .... ),
#  where = setConstraints(
#    paths = c("CONSTRAINT.PATH.A", "CONSTRAINT.PATH.B"),
#    operators = c("CONSTRAINT.OPERATOR.A", "CONSTRAINT.OPERATOR.B"),
#    values = list("CONSTRAINT.VALUE.A","CONSTRAINT.VALUE.B")
#  )
#)
queryEpilepsy <- setQuery(
  # Choose which columns of data we'd like to see
  select = c("Gene.primaryIdentifier"),
  where = setConstraints(
      paths = c("Gene"),
      operators = c("IN"),
      values = list("PL_GenomicsEngland_GenePanel:Genetic_Epilepsy_Syndromes"))
)

queryEpilepsyResults <- runQuery(im, queryEpilepsy)
queryEpilepsyResults

# load GeneAnswers package
library(GeneAnswers)

# convert InterMineR Gene Ontology Enrichment analysis results to GeneAnswers object
queryEpilepsyForGeneAnswers = convertToGeneAnswers(
  
  # Pass the enrichment results we ran earlier to GeneAnswers:
  enrichmentResult = GOEnrichmentResult,
  
  # Pass in our original list of gene IDs 
  geneInput = data.frame(GeneID = queryEpilepsyResults, 
                         stringsAsFactors = FALSE),
  
  # in our example we use Gene.primaryIdentifier values
  geneInputType = "Gene.primaryIdentifier",
    
  # The type of enrichment widget we ran
  # in our example we use Gene Ontology (GO) terms:
  categoryType = "GO"  
)

summary(queryEpilepsyForGeneAnswers)

geneAnswersConceptNet(queryEpilepsyForGeneAnswers, 
                      colorValueColumn=NULL,
                      centroidSize='correctedPvalue', 
                      output='fixed',
                      geneSymbol = TRUE)

geneAnswersConceptRelation(queryEpilepsyForGeneAnswers,
                           directed=TRUE, 
                           output="fixed",
                           netMode='connection') 

buildNet(getGeneInput(queryEpilepsyForGeneAnswers)[,1],
         idType='GeneInteraction', 
         layers=3,
         output="fixed",
         filterGraphIDs=getGeneInput(queryEpilepsyForGeneAnswers)[,1],
         filterLayer=2, 
         netMode='connection')

geneAnswersHeatmap(queryEpilepsyForGeneAnswers, 
                   catTerm=TRUE, 
                   geneSymbol=TRUE,
                   cex.axis = 0.75)