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server.R
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vals <- reactiveValues(count=0)
## Uploading file's size requirement (<30MB)
options(shiny.maxRequestSize = 30*1024^2)
## Start shiny server
shinyServer(function(input, output, session) {
pdf(NULL)
isolate(vals$count <- vals$count + 1)
#########################################################################################################
#undefined columns selected
#######################################################################################################################
#########################################################################################################
observe({
chFileFormat <- input$Fileformat
if (chFileFormat == ""){
output$a1<- renderUI({
isolate(
actionButton("stop", label = "Check Input Files"))
})
observeEvent(input$stop,{
shinyalert("Warning!", "Please Select one Option from above", type = "error")
})
}
else if (chFileFormat == "1"){
output$a1<- renderUI({
isolate(
actionButton("dataSubmit", label = "Check Input Files"))
})
observeEvent(input$dataSubmit,{
withProgress(message = "Checking your data, please wait",
{
##### UpLoding ##################################################################################################################
values <- reactiveValues()
file_to_read <- input$file1
file_to_read2 <- input$file2
if (is.null(file_to_read ) & is.null(file_to_read2)) {
queryMagic <- function() {
print(paste(" Please upload your files first"))
return("Data")
}
output$console2 <- renderPrint({
logText()
return(print(values[["log"]]))
})
logText <- reactive({
values[["log"]] <- capture.output(data <- queryMagic())
})
return()
}
else if (!is.null(file_to_read ) & !is.null(file_to_read2)) {
UploadData <- reactiveValues(
mainfile = read.delim(file=file_to_read$datapath,sep=input$Sep1, header=TRUE))
Uploadtable <- reactiveValues(
labelfile = read.delim(file=file_to_read2$datapath,sep=input$Sep1, header=TRUE)
)
if (length(colnames( UploadData$mainfile)) < 4 || length(colnames(Uploadtable$labelfile))> 3) {
queryMagic <- function() {
if(input$dataSubmit)
print(paste("Wrong File Uploaded: Input 1 should be your Main file and Input 2 should be your Labels table"))
return("Data")
}
output$console2 <- renderPrint({
logText()
return(print(values[["log"]]))
})
logText <- reactive({
values[["log"]] <- capture.output(data <- queryMagic())
})
output$b1<- renderUI({
if(input$dataSubmit)
isolate(
actionButton("wait", label = "Continue to Submit"))
})
output$error <- renderText({
if(input$dataSubmit)
isolate({
paste("If there is any error or Input summary table seems wrong, please make sure: 1)You have uploaded correct files with correct format (CSV (Comma delimited)/ txt (Tab delimited)).
2) You have picked correct file Separators.")
})
})
}
else if (length(colnames( UploadData$mainfile)) > 4 && length(colnames(Uploadtable$labelfile))< 4) {
queryMagic <- function() {
print(paste(" Correct input Uploaded"))
return("Data")
}
output$console2 <- renderPrint({
logText()
return(print(values[["log"]]))
})
logText <- reactive({
values[["log"]] <- capture.output(data <- queryMagic())
})
if(input$dataSubmit)
isolate({
output$b<- renderUI({
actionButton("dataPCA", label = " Continue to Submit")
})
output$b1<- renderUI({
})
output$error <- renderText({
if(input$dataSubmit)
isolate({
})
})
})
}
}
######## Summary ##############################################################################################################
output$Title <- renderText({
if(input$dataSubmit)
isolate({
no.samples <- length(colnames(UploadData$mainfile))-2
paste("This cohort contains ", as.character(no.samples)," Samples:", sep="")
})
})
######################################################################################################################
output$Info <- renderText({
if(input$dataSubmit)
isolate({
paste(as.character( (Uploadtable$labelfile)[,1]), collapse=", " )
})
})
#####################################################################################################################
output$t1 <- renderText({
if(input$dataSubmit)
isolate({
paste(as.character(colnames(Uploadtable$labelfile)[2]),sep=""," Label:")
})
})
#####################################################################################################################
output$t2 <- renderText({
if(input$dataSubmit)
isolate({
paste(as.character(levels(as.factor((Uploadtable$labelfile)[,2]))), collapse=", ")
})
})
#######################################################################################################################
output$Summary <- renderTable({
if(input$dataSubmit)
isolate({
no.samples <- length(colnames(UploadData$mainfile))-2
no.gene <- dim(UploadData$mainfile)[1]
res.summary <- rbind(no.samples, no.gene)
rownames(res.summary) <- c("Samples", "Gene_ID")
colnames(res.summary) <- "Number"
res.summary
})
},digits=0,rownames = TRUE, align="lc")
#})
#################################################################################################################
# }
})
})
##############PCA 2D PLOT ####################################################
##PCA###
data <- reactiveValues()
observeEvent(input$dataPCA,{
withProgress(message = "Preparing PCA & MDS Plots, please wait",
{
file_to_read=input$file1
f6<- read.delim(file_to_read$datapath,sep=input$Sep1, header=T)
names(f6)[1] <- "ID"
names(f6)[2] <- "symbol"
head(f6)
dim(f6)
# remove rows with zero value
f7 <- column_to_rownames(f6, var = "ID")[-1]
f7 <- f7[rowSums(f7 != 0)>0,]
#### attaching gene symbol to the file
f8 <- rownames_to_column(f7, var="ID")
exp <- join(f8[,1,drop=F], f6, by="ID", type="inner")
data$exp<-exp
file_to_read2=input$file2
table <- read.delim(file_to_read2$datapath,sep=input$Sep1, header=T)
names(table)[1] <- " Types"
names(table)[2] <- "Samples"
names(table)[3] <- "Labels"
rownames(exp) <- exp[,1]
exp <- exp[,-c(1,2)]
exp.scale <- t(scale(t(exp), scale = F))
pc <- prcomp(exp.scale, scale. = F, center = F)
percentage <- round(pc$sdev / sum(pc$sdev) * 100, 2)
pc$rotation
pcr <- data.frame(pc$rotation[,1:3], Group = table[,1] )
data$pp <-data.frame(pc$rotation[,1:3], Group = table[,1] )
data$percentage <- paste( colnames(pcr), "(", paste( as.character(percentage), "%", ")", sep="") )
pcr1 <- data.matrix(pc$rotation[,1:3])
pcr2 <- data.frame(pc$rotation[,1:3], Group = table[,1] )
pcr$label<- table[,3]
data$label<- table[,3]
data$gr<-(table[,1])
data$plot<-pcr1[,1:3]
data$plot3<-pcr2[,1:3]
data$table<-table
A <- table[,1]
B = factor(A)
B7=(levels(B))
data$B7<- length(B7)
data$A <-A
##############Group Selection################################
output$color1 <- renderUI({
selectInput('select','Please pick a color for all of your Groups:', as.list(B7), multiple = TRUE)
})
output$check1 <- renderUI({
selectInput ('Group1comp','Category A', as.list(B7),multiple = TRUE)
})
output$check2 <- renderUI({
selectInput ('Group2comp','Category B', as.list(B7),multiple = TRUE)
})
output$check3 <- renderUI({
selectInput ('Group3comp','Group A', as.list(B7),selected = as.list(B7[1]), multiple = FALSE)
#selectInput ('Group3comp','Group A', as.list(B7),selectize=TRUE)
})
output$check4 <- renderUI({
selectInput ('Group4comp','Group B', as.list(B7),selected = as.list(B7[2]), multiple = FALSE)
})
my_list <- list("both","row","column")
output$checkdan <- renderUI({
selectInput ('Group7comp','Choose clustering option', as.list(my_list),multiple = FALSE)
})
output$checkdanselected <- renderUI({
selectInput ('Group8comp','Choose clustering option', as.list(my_list),multiple = FALSE)
})
############## MDS Plot ##########################################
distance.matrix <- dist(scale(t(exp), scale = T,center = T ), method="euclidean")
mds.stuff <- cmdscale(distance.matrix, eig=TRUE, x.ret=TRUE)
## calculate the percentage of variation that each MDS axis accounts for...
data$mds.var.per <- round(mds.stuff$eig/sum(mds.stuff$eig)*100, 1)
#print(data$mds.var.per)
mds.values <- mds.stuff$points
data$mds.data <- data.frame(Sample=rownames(mds.values),
X=mds.values[,1],
Y=mds.values[,2], Group = table[,1] )
###############################################################################
shinyalert("Done!", "Please go to Data analysis section", type = "success")
}) #progress bar
}) # End submit
#############Colour ###########################################################
gg_fill_hue <- function(n) {
hues = seq(15, 375, length = n + 1)
hcl(h = hues, l = 65, c = 100)[1:n]
}
output$platter <- renderUI({
lev <- sort(unique(input$select))
cols <- gg_fill_hue(length(lev))
lapply(seq_along(lev), function(i) {
colourInput(inputId = paste0("col", lev[i]),
label = paste0("Choose colour for ", lev[i]),
value = cols[i]
)
})
})
##############PCA 2D PLOT #####################################################
observe({
chp <- input$optionp
chlab <- input$optionlab
textpca <- as.numeric(input$label_pca)
pointpca <- as.numeric(input$point_pca)
widthpca <- reactive ({ input$plot_widthpca })
heightpca <- reactive ({ input$plot_heightpca})
if (chp == "1"){
output$PCAPlot2D <- renderPlot(width = widthpca, height = heightpca,{
cols <- paste0("c(", paste0("input$col", sort(input$select), collapse = ", "), ")")
cols <- eval(parse(text = cols))
req(length(cols) == length(input$select))
if (length(cols) == data$B7){
if (chlab == "1"){
sp <- ggplot(data$pp, aes(PC1, PC2,label = data$label,fill = Group))+ geom_point(aes(col = Group),size=pointpca)
p <- sp+ scale_color_manual(values = cols)+
geom_text(size= textpca,position = position_nudge(y = -0.05))+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(data$percentage[1]) + ylab(data$percentage[2])}
else if (chlab == "2"){
sp <- ggplot(data$pp, aes(PC1, PC2, fill = Group)) +geom_point(aes(col = Group),size=pointpca)
p <-sp + scale_color_manual(values = cols)+
theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(data$percentage[1]) + ylab(data$percentage[2])}
vals$p<-p
print(p)
vals$cols<-cols
}
else{
if (chlab == "1"){
p <-ggplot(data$pp, aes(PC1, PC2, label = data$label, fill = Group))+geom_point(aes(col = Group),size=pointpca)+geom_text(size= textpca,position = position_nudge(y = -0.05))+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(data$percentage[1]) + ylab(data$percentage[2])}
else if (chlab == "2"){
p <-ggplot(data$pp, aes(PC1, PC2, color = Group))+geom_point(aes(col = Group),size=pointpca)+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(data$percentage[1]) + ylab(data$percentage[2])}
vals$p<-p
print(p)
}
})
}# Chp=1
else if (chp == "2"){
output$PCAPlot2D <- renderPlot(width = widthpca, height = heightpca,{
cols <- paste0("c(", paste0("input$col", sort(input$select), collapse = ", "), ")")
cols <- eval(parse(text = cols))
req(length(cols) == length(input$select))
if (length(cols) == data$B7){
if (chlab == "1"){
sp<- ggplot(data$pp, aes(PC1, PC3,label = data$label, fill = Group)) +
geom_point(aes(col = Group),size=pointpca)
p <- sp+ scale_color_manual(values = vals$cols)+
geom_text(size= textpca,position = position_nudge(y = -0.05))+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(data$percentage[1]) + ylab(data$percentage[3])}
else if (chlab == "2"){
sp<- ggplot(data$pp, aes(PC1, PC3, fill = Group)) +
geom_point(aes(col = Group),size=pointpca)
p <- sp+ scale_color_manual(values = vals$cols)+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(data$percentage[1]) + ylab(data$percentage[3])}
vals$p<-p
print(p)
}
else{
if (chlab == "1"){
p <-ggplot(data$pp, aes(PC1, PC3, label = data$label, fill = Group))+geom_point(aes(col = Group),size=pointpca)+geom_text(size= textpca,position = position_nudge(y = -0.05))+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(data$percentage[1]) + ylab(data$percentage[3])}
else if (chlab == "2"){
p <-ggplot(data$pp, aes(PC1, PC3, color = Group))+geom_point(aes(col = Group),size=pointpca)+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(data$percentage[1]) + ylab(data$percentage[3])}
vals$p<-p
print(p)
}
})
}#Chp=2
else if (chp == "3"){
output$PCAPlot2D <- renderPlot(width = widthpca, height = heightpca,{
cols <- paste0("c(", paste0("input$col", sort(input$select), collapse = ", "), ")")
cols <- eval(parse(text = cols))
req(length(cols) == length(input$select))
if (length(cols) == data$B7){
if (chlab == "1"){
sp<- ggplot(data$pp, aes(PC2, PC3,label = data$label, fill = Group)) +
geom_point(aes(col = Group),size=pointpca)
p <- sp + scale_color_manual(values = vals$cols) +
geom_text(size= textpca,position = position_nudge(y = -0.05))+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(data$percentage[2]) + ylab(data$percentage[3])}
else if (chlab == "2"){
sp<- ggplot(data$pp, aes(PC2, PC3, fill = Group)) +
geom_point(aes(col = Group),size=pointpca)
p <- sp + scale_color_manual(values = vals$cols) +theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(data$percentage[2]) + ylab(data$percentage[3])
}
vals$p<-p
print(p)
}
else{
if (chlab == "1"){
p <-ggplot(data$pp, aes(PC2, PC3, label = data$label, fill = Group))+geom_point(aes(col = Group),size=pointpca)+geom_text(size= textpca,position = position_nudge(y = -0.05))+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(data$percentage[2]) + ylab(data$percentage[3])}
else if (chlab == "2"){
p <-ggplot(data$pp, aes(PC2, PC3, color = Group))+geom_point(aes(col = Group),size=pointpca)+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(data$percentage[2]) + ylab(data$percentage[3]) }
vals$p<-p
print(p)
}
})
}#Chp=3
}) # end observe
###########################################################################################################
####### MDS PLOT
observe({
chmds <- input$optlab
textmds<- as.numeric(input$label_mds)
pointmds<- as.numeric(input$point_mds)
widthmds <- reactive ({ input$plot_widthmds })
heightmds <- reactive ({ input$plot_heightmds})
output$MDSPlot <- renderPlot(width = widthmds, height = heightmds,{
cols <- paste0("c(", paste0("input$col", sort(input$select), collapse = ", "), ")")
cols <- eval(parse(text = cols))
req(length(cols) == length(input$select))
if (length(cols) == data$B7){
if (chmds == "1"){
g<- ggplot(data$mds.data, aes(x=X, y=Y, label = data$label, fill = Group)) +
geom_point(aes(col = Group),size=pointmds)
s <- g + scale_color_manual(values = vals$cols) +
geom_text(size= textmds,position = position_nudge(y = +5))+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(paste("MDS1 - ", data$mds.var.per[1], "%", sep="")) +ylab(paste("MDS2 - ", data$mds.var.per[2], "%", sep="")) }
else if (chmds == "2"){
g<- ggplot(data$mds.data, aes(x=X, y=Y, fill = Group)) +
geom_point(aes(col = Group),size=pointmds)
s<- g + scale_color_manual(values = vals$cols) +theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(paste("MDS1 - ", data$mds.var.per[1], "%", sep="")) +ylab(paste("MDS2 - ", data$mds.var.per[2], "%", sep="")) }
vals$s<-s
print(s)
}
else{
if (chmds == "1"){
s <-ggplot( data$mds.data, aes(x=X, y=Y, label = data$label, fill = Group))+geom_point(aes(col = Group),size=pointmds)+geom_text(size= textmds,nudge_y = +5)+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(paste("MDS1 - ", data$mds.var.per[1], "%", sep="")) +ylab(paste("MDS2 - ", data$mds.var.per[2], "%", sep="")) }
else if (chmds == "2"){
s <-ggplot( data$mds.data, aes(x=X, y=Y, fill= Group))+geom_point(aes(col = Group),size=pointmds)+theme_bw(base_size = 14)+
theme(plot.title = element_text(hjust = 0.5), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())+ xlab(paste("MDS1 - ", data$mds.var.per[1], "%", sep="")) +ylab(paste("MDS2 - ", data$mds.var.per[2], "%", sep="")) }
vals$s<-s
print(s)
}
})
})
################ 3D PLOT #####################################################################
output$PCAPlot <- renderPlotly({
withProgress(message = "Preparing PCA3D, please wait",
{
get_colors <- function(groups, group.col = palette()){
groups <- data$gr
ngrps <- length(levels(groups))
if(ngrps > length(group.col))
group.col <- rep(group.col, ngrps)
color <- group.col[as.numeric(groups)]
names(color) <- as.vector(groups)
return(color)
}
gr<-data$gr
n <- data$plot3
s=get_colors(gr)
m<-as.factor(s)
cols <- paste0("c(", paste0("input$col", sort(input$select), collapse = ", "), ")")
print(cols)
cols <- eval(parse(text = cols))
req(length(cols) == length(input$select))
if (length(cols) == data$B7){
fig <- plot_ly(n, x = ~PC1, y = ~PC2, z = ~PC3, color = ~gr, colors = vals$cols,text = rownames(n))
fig <- fig %>% add_markers()
chs3d <- input$option3d
if (chs3d == "1"){
fig <- fig %>% layout(scene = list(xaxis = list(title = 'PC1'),
yaxis = list(title = 'PC2'),
zaxis = list(title = 'PC3'),
camera = list(eye = list(x = 1.5, y = 1.5, z = 0.1))))
fig <- fig %>% layout(autosize = T)
fig <- fig %>% config(
toImageButtonOptions= list(filename = 'PCA3DPlot'))
fig <- fig %>% layout(scene = list(xaxis = list(title = 'PC1'),
yaxis = list(title = 'PC2'),
zaxis = list(title = 'PC3')
))
}
else if (chs3d == "2"){
fig <- plot_ly(n, x = ~PC1, y = ~PC2, z = ~PC3, color = ~gr, colors = vals$cols,text = rownames(n))
fig <- fig %>% add_markers()
fig <- fig %>% layout(scene = list(xaxis = list(title = 'PC1'),
yaxis = list(title = 'PC2'),
zaxis = list(title = 'PC3'),
camera = list(eye = list(x = 1.5, y = 1.5, z = 0.1))))
fig <- fig %>% layout(autosize = T)
fig <- fig %>% config(
toImageButtonOptions= list(format = "svg",filename = 'PCA3DPlot'))
fig <- fig %>% layout(scene = list(xaxis = list(title = 'PC1'),
yaxis = list(title = 'PC2'),
zaxis = list(title = 'PC3')
))
}
}
else
{
fig <- plot_ly(n, x = ~PC1, y = ~PC2, z = ~PC3, color = ~gr, colors= c("#F8766D","#00BFC4","#7CAE00", "#C77CFF", "#009E73",
"#7CAE00", "#C77CFF", "#D55E00", "#00BFC4"),text = rownames(n))
fig <- fig %>% add_markers()
chs3d <- input$option3d
if (chs3d == "1"){
fig <- fig %>% layout(scene = list(xaxis = list(title = 'PC1'),
yaxis = list(title = 'PC2'),
zaxis = list(title = 'PC3'),
camera = list(eye = list(x = 1.5, y = 1.5, z = 0.1))))
fig <- fig %>% layout(autosize = T)
fig <- fig %>% config(
toImageButtonOptions= list(filename = 'PCA3DPlot'))
fig <- fig %>% layout(scene = list(xaxis = list(title = 'PC1'),
yaxis = list(title = 'PC2'),
zaxis = list(title = 'PC3')
))
}
else if (chs3d == "2"){
fig <- plot_ly(n, x = ~PC1, y = ~PC2, z = ~PC3, color = ~gr, colors= c("#F8766D","#00BFC4","#7CAE00", "#C77CFF", "#009E73",
"#7CAE00", "#C77CFF", "#D55E00", "#00BFC4"),text = rownames(n))
fig <- fig %>% add_markers()
fig <- fig %>% layout(scene = list(xaxis = list(title = 'PC1'),
yaxis = list(title = 'PC2'),
zaxis = list(title = 'PC3'),
camera = list(eye = list(x = 1.5, y = 1.5, z = 0.1))))
fig <- fig %>% layout(autosize = T)
fig <- fig %>% config(
toImageButtonOptions= list(format = "svg",filename = 'PCA3DPlot'))
fig <- fig %>% layout(scene = list(xaxis = list(title = 'PC1'),
yaxis = list(title = 'PC2'),
zaxis = list(title = 'PC3')
))
}
}
}) #progress bar
})# ENd Plotly
###############Downloads PCA2D ###########################################################
# print(input$plot_widthpca*4)
observe({
chs <- input$optionchs
if (chs == "1"){
output$PlotDownloadPCA2D <- downloadHandler(
filename = function(){paste("PCAPlot",'.png',sep='')},
content = function(file){
device <- function(..., width, height) grDevices::png(..., width =input$plot_widthpca*4, height =input$plot_heightpca*4, res = 350, units = "px")
ggsave(file, plot = (vals$p) , device = device)
})
}
else if (chs == "2"){
output$PlotDownloadPCA2D <- downloadHandler(
filename = function(){paste("PCAPlot",'.svg',sep='')},
content = function(file) {
device <- function(..., width, height) grDevices::svg(..., width =round(input$plot_widthpca*4/300), height =round(input$plot_heightpca*4/300))
ggsave(file, plot = (vals$p) , device = device)
})
}
})
########### Donwload MDS ###############################################################################
observe({
chd <- input$optchs
if (chd== "1"){
output$PlotDownloadMDS2D <- downloadHandler(
filename = function(){paste("MDSPlot",'.png',sep='')},
content = function(file){
device <- function(..., width, height) grDevices::png(..., width =input$plot_widthmds*4, height =input$plot_heightmds*4, res = 350, units = "px")
ggsave(file, plot = (vals$s) , device = device)
})
}
else if (chd == "2"){
output$PlotDownloadMDS2D <- downloadHandler(
filename = function(){paste("MDSPlot",'.svg',sep='')},
content = function(file) {
device <- function(..., width, height) grDevices::svg(..., width =round(input$plot_widthmds*4/300), height =round(input$plot_heightmds*4/300))
ggsave(file, plot = (vals$p) , device = device)
})
}
})# End MDS
######################################################################################################
###############################################################################################################
####CRIS classifier
datacris <- reactiveValues()
observeEvent(input$CRISAnalysis,{
withProgress(message = "Preparing CRIS Classifier Table and Plot, please wait",
{
Collapsed_data <- datar$Coll
head(Collapsed_data)
########## Mouse data############################################
chcris <- input$optionCRIS
if (chcris == "Mouse"){
####### Get the normalized data from the first part
Collapsed_cris <- Collapsed_data[,-c(1,2)]
col_name8<- paste(datar$n1, sep="")
col_name9<-paste(datar$n2, sep="")
names(Collapsed_cris)[1:length(datar$n1)]<-col_name8
names(Collapsed_cris)[length(datar$n1)+1:length(datar$n2)]<-col_name9
expcris <- data.matrix(Collapsed_cris)
# adjust matrix before classification
mat_exp_adj <- ematAdjust(expcris)
datacris$mat_exp_adj<-mat_exp_adj
load("CRIS_template_mouse.RData")
NTP_CRIS <- ntp(emat=mat_exp_adj,CIRS_template, seed=367707,doPlot =F)
NTP_CRIS <- tibble::rownames_to_column(NTP_CRIS,var = "ID")
crisl <-(length(colnames(NTP_CRIS)))
output$CRIS<- DT::renderDataTable({NTP_CRIS},
extensions = 'FixedColumns',
options = list(pageLength = 20, autoWidth = FALSE,
scrollX = TRUE,
scrollCollapse = TRUE,
lengthMenu = c(20, 50, 100),
columnDefs = list(list(targets = c(3:crisl), searchable = FALSE))),
editable = FALSE)
output$TableDownloadCRIS<- downloadHandler(
filename = function(){paste("MOUSE_DATA_NTP_CRIS_results",'.csv')},
content = function(file){
write.csv(NTP_CRIS, file, sep = ",", quote = F)
})
observe({
widthcris <- reactive ({ input$plot_widthcris})
heightcris<- reactive ({ input$plot_heightcris})
output$CRIS_Plot<- renderPlot(width = widthcris, height = heightcris,{
NTP_CRIS <- ntp(emat=mat_exp_adj,CIRS_template, seed=367707,doPlot = TRUE)
})
})
observe({
chdcris <- input$optioncris
if ( chdcris == "1"){
output$PlotDownloadCRIS<- downloadHandler(
file = "CRIS-Plot.png" , # variable with filename
content = function(file) {
png(file = file)
load("CRIS_template_mouse.RData")
NTP_CRIS <- ntp(emat=datacris$mat_exp_adj,CIRS_template, seed=367707,doPlot = TRUE)
dev.off()
})
} else if ( chdcris == "2"){
output$PlotDownloadCRIS <- downloadHandler(
file = "CRIS-Plot.svg" , # variable with filename
content = function(file) {
svg(file = file)
load("CRIS_template_mouse.RData")
NTP_CRIS <- ntp(emat=datacris$mat_exp_adj,CIRS_template, seed=367707,doPlot = TRUE)
dev.off()
})
}
})
}
#############################################################################################
else if (chcris == "Human"){
####### Get the normalized data from the first part
Collapsed_cris <- Collapsed_data[,-c(1,2)]
col_name8<- paste(datar$n1, sep="")
col_name9<-paste(datar$n2, sep="")
names(Collapsed_cris)[1:length(datar$n1)]<-col_name8
names(Collapsed_cris)[length(datar$n1)+1:length(datar$n2)]<-col_name9
expcris <- data.matrix(Collapsed_cris)
# adjust matrix before classification
exp_adj <- ematAdjust(expcris)
datacris$exp_adj<-exp_adj
load("Human.CRIS.template.RData")
NTP_CRIS <- ntp(emat=exp_adj, Human.CRIS.template, seed=367707,doPlot =F)
NTP_CRIS <- tibble::rownames_to_column(NTP_CRIS,var = "ID")
crisl <-(length(colnames(NTP_CRIS)))
output$CRIS<- DT::renderDataTable({NTP_CRIS},
extensions = 'FixedColumns',
options = list(pageLength = 20, autoWidth = FALSE,
scrollX = TRUE,
scrollCollapse = TRUE,
lengthMenu = c(20, 50, 100),
columnDefs = list(list(targets = c(3:crisl), searchable = FALSE))),
editable = FALSE)
output$TableDownloadCRIS<- downloadHandler(
filename = function(){paste("human_DATA_NTP_CMS_results",'.csv')},
content = function(file){
write.csv(NTP_CRIS, file, sep = ",", quote = F)
})
observe({
widthcris <- reactive ({ input$plot_widthcris})
heightcris<- reactive ({ input$plot_heightcris})
output$CRIS_Plot<- renderPlot(width = widthcris, height = heightcris,{
NTP_CRIS <- ntp(emat=exp_adj, Human.CRIS.template, seed=367707,doPlot = TRUE)
})
})
observe({
chdcris <- input$optioncris
if ( chdcris == "1"){
output$PlotDownloadCRIS<- downloadHandler(
file = "CRIS-Plot.png" , # variable with filename
content = function(file) {
png(file = file)
load("Human.CRIS.template.RData")
NTP_CRIS <- ntp(emat= datacris$exp_adj, Human.CRIS.template, seed=367707,doPlot = TRUE)
dev.off()
})
} else if ( chdcris == "2"){
output$PlotDownloadCRIS <- downloadHandler(
file = "CRIS-Plot.svg" , # variable with filename
content = function(file) {
svg(file = file)
load("Human.CRIS.template.RData")
NTP_CRIS <- ntp(emat= datacris$exp_adj, Human.CRIS.template, seed=367707,doPlot = TRUE)
dev.off()
})
}
})
}
})
})
#########################################################################################################################
#Classifier_CMS
datacms <- reactiveValues()
observeEvent(input$CMSAnalysis,{
withProgress(message = "Preparing CMS Classifier Table and Plot, please wait",
{
Collapsed_data <- datar$Coll
head(Collapsed_data)
########## Mouse data############################################
chcms <- input$optionCMS
if (chcms == "Mouse"){
####### Get the normalized data from the first part
Collapsed_cms <- Collapsed_data[,-c(1,2)]
col_name8<- paste(datar$n1, sep="")
col_name9<-paste(datar$n2, sep="")
names(Collapsed_cms)[1:length(datar$n1)]<-col_name8
names(Collapsed_cms)[length(datar$n1)+1:length(datar$n2)]<-col_name9
expcms <- data.matrix(Collapsed_cms)
# adjust matrix before classification
mat_exp_adj <- ematAdjust(expcms)
datacms$mat_exp_adj<-mat_exp_adj
# load mouse CMS template
load("template.CMS.A.RData") # template.CMS.A
# CMS NTP and save as text file
NTP_CMS <- ntp(emat=mat_exp_adj,template.CMS.A, seed=367707,doPlot = F)
NTP_CMS <-tibble:: rownames_to_column(NTP_CMS,var = "ID")
# write.table(NTP_CMS,file=CMS_res_nm,sep='\t',row.names = FALSE)
cmsl <-(length(colnames(NTP_CMS)))
output$CMS<- DT::renderDataTable({NTP_CMS},
extensions = 'FixedColumns',
options = list(pageLength = 20, autoWidth = FALSE,
scrollX = TRUE,
scrollCollapse = TRUE,
lengthMenu = c(20, 50, 100),
columnDefs = list(list(targets = c(3:cmsl), searchable = FALSE))),
editable = FALSE)
output$TableDownloadCMS<- downloadHandler(
filename = function(){paste("MOUSE_DATA_NTP_CMS_results",'.csv')},
content = function(file){
write.csv(NTP_CMS, file, sep = ",", quote = F)
})
observe({
widthcms <- reactive ({ input$plot_widthcms})
heightcms<- reactive ({ input$plot_heightcms})
output$CMS_Plot<- renderPlot(width = widthcms, height = heightcms,{
NTP_CMS<-ntp(emat=mat_exp_adj,template.CMS.A, seed=367707,doPlot = T)
})
})
observe({
chdcms <- input$optioncms
if ( chdcms == "1"){
output$PlotDownloadCMS <- downloadHandler(
file = "CMS-Plot.png" , # variable with filename
content = function(file) {
png(file = file)
load("template.CMS.A.RData") # template
NTP_CMS <- ntp(emat=datacms$mat_exp_adj,template.CMS.A, seed=367707,doPlot = T)
dev.off()
})
} else if ( chdcms == "2"){
output$PlotDownloadCMS <- downloadHandler(
file = "CMS-Plot.svg" , # variable with filename
content = function(file) {
svg(file = file)
load("template.CMS.A.RData") # template
NTP_CMS <- ntp(emat=datacms$mat_exp_adj,template.CMS.A, seed=367707,doPlot = T)
dev.off()
})
}
})
}
#############################################################################################
else if (chcms == "Human"){
####### Get the normalized data from the first part
Collapsed_cms <- Collapsed_data[,-c(1,2)]
col_name8<- paste(datar$n1, sep="")
col_name9<-paste(datar$n2, sep="")
names(Collapsed_cms)[1:length(datar$n1)]<-col_name8
names(Collapsed_cms)[length(datar$n1)+1:length(datar$n2)]<-col_name9
expcms <- data.matrix(Collapsed_cms)
# adjust matrix before classification
exp_adj <- ematAdjust(expcms)
datacms$exp_adj<-exp_adj
load("Human.CMS.template.RData") # Human.CMS.template
# CMS NTP and save as text file
NTP_CMS <- ntp(emat=exp_adj, Human.CMS.template, seed=367707,doPlot = F)
# datacms$NTP_CMS <- NTP_CMS
NTP_CMS <- rownames_to_column(NTP_CMS,var = "ID")
# write.table(NTP_CMS,file=CMS_res_nm,sep='\t',row.names = FALSE)
cmsl <-(length(colnames(NTP_CMS)))
output$CMS<- DT::renderDataTable({NTP_CMS},
extensions = 'FixedColumns',
options = list(pageLength = 20, autoWidth = FALSE,
scrollX = TRUE,
scrollCollapse = TRUE,
lengthMenu = c(20, 50, 100),
columnDefs = list(list(targets = c(3:cmsl), searchable = FALSE))),
editable = FALSE)
output$TableDownloadCMS<- downloadHandler(
filename = function(){paste("human_DATA_NTP_CMS_results",'.csv')},
content = function(file){
write.csv(NTP_CMS, file, sep = ",", quote = F)
})
observe({
widthcms <- reactive ({ input$plot_widthcms})
heightcms<- reactive ({ input$plot_heightcms})
output$CMS_Plot<- renderPlot(width = widthcms, height = heightcms,{
NTP_CMS <- ntp(emat=exp_adj, Human.CMS.template, seed=367707,doPlot = T)
})
})
observe({
chdcms <- input$optioncms
if ( chdcms == "1"){
output$PlotDownloadCMS <- downloadHandler(
file = "CMS-Plot.png" , # variable with filename
content = function(file) {
png(file = file)
load("Human.CMS.template.RData")
NTP_CMS <- ntp(emat=datacms$exp_adj,Human.CMS.template, seed=367707,doPlot = T)
dev.off()
})
} else if ( chdcms == "2"){