## ----, echo=TRUE, eval=TRUE----------------------------------------------
# Unpack files
location <- tempdir()
unzip(system.file('extdata', 'Mycoplasma.zip', package='FindMyFriends'),
      exdir=location)
genomeFiles <- list.files(location, full.names=TRUE, pattern='*.fasta')

## ----, echo=TRUE, eval=TRUE----------------------------------------------
library(FindMyFriends)
library(igraph) # some return values are igraph objects

mycoPan <- pangenome(genomeFiles[1:9], 
                     translated=TRUE, 
                     geneLocation='prodigal', 
                     lowMem=FALSE)
mycoPan

## ----, echo=TRUE, eval=TRUE----------------------------------------------
head(geneLocation(mycoPan))

## ----, echo=TRUE, eval=TRUE----------------------------------------------
orgMeta <- data.frame(Species = c("hyopneumoniae", "hyopneumoniae", 
                                  "hyopneumoniae", "pneumoniae", 
                                  "pneumoniae", "hyopneumoniae", 
                                  "hyopneumoniae", "hyopneumoniae", 
                                  "pneumoniae"))

mycoPan <- addOrgInfo(mycoPan, orgMeta)
head(orgInfo(mycoPan))

## ----, echo=TRUE, eval=TRUE----------------------------------------------
genes(mycoPan)
genes(mycoPan, split = 'organism')

## ----, echo=TRUE, eval=TRUE----------------------------------------------
# Query current defaults
head(defaults(mycoPan))

# Set a new default
defaults(mycoPan)$lowerLimit <- 0.6

## ----, echo=TRUE, eval=TRUE----------------------------------------------
mycoSim <- kmerSimilarity(mycoPan, lowerLimit=0.8, rescale=FALSE)

## ----, eval=TRUE, echo=TRUE----------------------------------------------
mycoPan <- graphGrouping(mycoPan, mycoSim)
mycoPan

## ----, eval=TRUE, echo=TRUE----------------------------------------------
mycoPan <- gpcGrouping(mycoPan, lowerLimit=0.5)
mycoPan

## ----, echo=TRUE, eval=TRUE----------------------------------------------
# Compute grouping based on hierarchical clustering - only for illustrative
# purpose. Not advisable.
distMat <- as.matrix(1/mycoSim-1)
distMat[is.infinite(distMat)] <- 1e5
htree <- hclust(as.dist(distMat), method='ward.D2')
members <- cutree(htree, k=2000)

# Add membership manually
mycoPanMan <- manualGrouping(mycoPan, members)
mycoPanMan

## ----, echo=TRUE, eval=TRUE----------------------------------------------
mycoPan <- neighborhoodSplit(mycoPan, lowerLimit=0.75)
mycoPan

## ----, echo=TRUE, eval=TRUE----------------------------------------------
mycoPan <- kmerLink(mycoPan, lowerLimit=0.8)

genes(mycoPan, split='paralogue')[[1]]

mycoPan
collapseParalogues(mycoPan, combineInfo='largest')

## ----, echo=TRUE, eval=TRUE----------------------------------------------
# Remove a gene by raw index
removeGene(mycoPan, ind=60)

# Remove the first organism by index
removeGene(mycoPan, organism=1)
# or by name
name <- orgNames(mycoPan)[1]
removeGene(mycoPan, organism=name)

# Remove the second member of the first gene group
removeGene(mycoPan, group=1, ind=2)

## ----, echo=TRUE, eval=TRUE----------------------------------------------
# Get the pangenome matrix as an ExpressionSet object
as(mycoPan, 'ExpressionSet')
# or as a regular matrix
as(mycoPan, 'matrix')[1:6, ]

# Get all genes split into gene groups
genes(mycoPan, split='group')

## ----, echo=TRUE, eval=TRUE----------------------------------------------
groupStat(mycoPan)[[1]]

head(orgStat(mycoPan))

## ----, echo=TRUE, eval=TRUE, fig.height=18, fig.width=9, fig.align='center'----
plotStat(mycoPan, color='Species', type='qual', palette=6)

## ----, echo=TRUE, eval=TRUE, fig.height=6, fig.width=9, fig.align='center'----
plotEvolution(mycoPan)

## ----, echo=TRUE, eval=TRUE, fig.height=9, fig.width=9, fig.align='center'----
# Pangenome matrix similarity
plotSimilarity(mycoPan)
# Kmer similarity
plotSimilarity(mycoPan, type='kmer', kmerSize=5)
# No ordering
plotSimilarity(mycoPan, ordering='none')

## ----, echo=TRUE, eval=TRUE, fig.width=9, fig.height=9, fig.align='center'----
plotTree(mycoPan, clust='ward.D2', dist='minkowski')
plotTree(mycoPan, type='kmer', kmerSize=5, clust='ward.D2', 
         dist='cosine', circular=TRUE, info='Species') + 
    ggplot2::scale_color_brewer(type='qual', palette=6)

## ----, echo=TRUE, eval=TRUE----------------------------------------------
library(igraph)
getNeighborhood(mycoPan, group=15, vicinity=5)

## ----, echo=TRUE, eval=TRUE, fig.align='center', fig.height=9, fig.width=9----
plotNeighborhood(mycoPan, group=15, vicinity=5)

## ----, echo=TRUE, eval=TRUE----------------------------------------------
panchromosome <- pcGraph(mycoPan)
plot(panchromosome, 
     layout=layout.drl(panchromosome, options = igraph.drl.coarsen),
     vertex.shape='none',
     vertex.label=NA)

## ----, echo=TRUE, eval=TRUE----------------------------------------------
localVar <- variableRegions(mycoPan, flankSize=6)
localVar[[1]]
plot(localVar[[1]]$graph)

## ----, echo=TRUE, eval=TRUE----------------------------------------------
sessionInfo()