library(shiny)

library(ape)

source("plotTree.R")

shinyServer( function(input, output, session) {

# An event observer for changes to INFO CSV file

observeEvent(input$info_file,

{

# read the CSV file and get the column names.

# re-reading this file repeatedly is inefficient

df = read.table(input$info_file$datapath, header=TRUE, sep=',')

# build a list of values, this is what is required by update methods

info_cols = list()

for (v in colnames(df)) {

info_cols[v] = v

}

# update the two input widgets using the column names

updateSelectInput(session, inputId='colour_tips_by', choices=c('(none)',info_cols[-1]))

updateSelectInput(session, inputId='print_column', choices=c(info_cols[-1]))

# switch on the meta data plotting option

updateCheckboxInput(session, inputId='info_data', value=TRUE)

}

)

# An event observer for changes to HEATMAP file

observeEvent(input$heatmap,

{

# switch on the heatmap plotting option

updateCheckboxInput(session, inputId='chk_heatmap', value=TRUE)

}

)

# An event observer for changes to BAR DATA file

observeEvent(input$barData,

{

# switch on the heatmap plotting option

updateCheckboxInput(session, inputId='chk_barplot', value=TRUE)

}

)

# An event observer for changes to BLOCKS file

observeEvent(input$blockFile,

{

# switch on the heatmap plotting option

updateCheckboxInput(session, inputId='chk_blocks', value=TRUE)

}

)

# An event observer for changes to SNPs file

observeEvent(input$snpFile,

{

# switch on the heatmap plotting option

updateCheckboxInput(session, inputId='chk_snps', value=TRUE)

}

)

output$Tree <- renderPlot({

input$drawButton == 0

### ALL VARIABLES PULLED FROM 'input' GO INSIDE HERE

isolate ( {

l<-input$Layout

t<-input$Tree

i<-input$Info

o<-input$Other

d<-input$Data

treeFile <- input$tree$datapath

# tree plotting options

label_tips <- input$label_tips

tree_line_width <- as.integer(input$tree_line_width)

branch_colour <- input$branch_colour

tipLabelSize <- as.integer(input$tipLabelSize)

offset <- as.integer(input$offset)

# metadata variables

infoFile <- input$info_file$datapath

tip_size <- input$tip_size

colour_tips_by <- input$colour_tips_by

if (colour_tips_by == '(none)') {colour_tips_by <- NULL}

ancestral <- input$ancestral

pie_size <- input$pie_size

legend <- input$legend

legend_pos <- input$legend_pos

print_column <- input$print_column

print_metadata <- input$print_metadata

if (!print_metadata) { print_column <- NA }

# heatmap variables

heatmapFile <- input$heatmap$datapath

cluster <- input$clustering

heatmapDecimalPlaces <- as.integer(input$heatmapDecimalPlaces)

colLabelCex <- as.integer(input$colLabelCex)

vlines_heatmap_col <-input$vlines_heatmap_col

vlines_heatmap <- input$vlines_heatmap

# heatColoursSpecify <- input$heatColoursSpecify

# if (heatColoursSpecify) {

# heatmap_colours <- input$heatmap_colour_vector

# }

# else {

heatmap_colours <- colorRampPalette(c(input$start_col,input$middle_col,input$end_col),space="rgb")(as.integer(input$heatmap_breaks))

# }

# barplot variables

barDataFile <- input$barData$datapath

barDataCol <- input$barDataCol

# block plot variables

blockFile <- input$blockFile$datapath

block_colour <- input$block_colour

blwd <- input$blwd

genome_size <- input$genome_size

snpFile <- input$snpFile$datapath

snp_colour <- input$snp_colour

# Layout/spacing

tree_width <- as.numeric(input$tree_width)

info_width <- as.numeric(input$info_width)

heatmap_width <- as.numeric(input$heatmap_width)

bar_width <- as.numeric(input$bar_width)

genome_width <- as.numeric(input$genome_width)

main_height <- as.numeric(input$main_height)

label_height <- as.numeric(input$label_height)

edge_width <- as.numeric(input$edge_width)

# TRACK DATA TYPES TO PLOT

chk_heatmap <- input$chk_heatmap

info_data <- input$info_data

chk_barplot <- input$chk_barplot

chk_blocks <- input$chk_blocks

chk_snps <- input$chk_snps

if (is.null(treeFile)) { return(NULL) }

if (!info_data) { infoFile <- NULL }

else { infoFile <- infoFile }

if (!chk_heatmap) { heatmapFile <- NULL }

else { heatmapFile <- heatmapFile }

if (!chk_barplot) { barDataFile <- NULL }

else { barDataFile <- barDataFile }

if (!chk_blocks) { blockFile <- NULL }

else { blockFile <- blockFile }

if (!chk_snps) { snpFile <- NULL }

else { snpFile <- snpFile }

}) # end isolate

### PLOT THE TREE

# main plotting function

doPlotTree <-function() {

# underlying call to plotTree(), drawn to screen and to file

plotTree(tree=treeFile,

tip.labels=label_tips, tipLabelSize=tipLabelSize, offset=offset,

lwd=tree_line_width, edge.color=branch_colour,

infoFile=infoFile, infoCols=print_column,

colourNodesBy=colour_tips_by, tip.colour.cex=tip_size,

ancestral.reconstruction=ancestral, pie.cex=pie_size,

legend=legend, legend.pos=legend_pos,

heatmapData=heatmapFile, cluster=cluster,

heatmap.colours=heatmap_colours,

heatmapDecimalPlaces=heatmapDecimalPlaces, colLabelCex=colLabelCex,

vlines.heatmap=vlines_heatmap, vlines.heatmap.col=vlines_heatmap_col,

barData=barDataFile, barDataCol=barDataCol,

blockFile=blockFile, block_colour=block_colour, blwd=blwd,

genome_size=genome_size,

snpFile=snpFile, snp_colour=snp_colour,

treeWidth=tree_width, infoWidth=info_width, dataWidth=heatmap_width,

barDataWidth=bar_width, blockPlotWidth=genome_width,

mainHeight=main_height, labelHeight=label_height, edgeWidth=edge_width

)

}

doPlotTree()

}) # end render plot

}) # shinyServer