Nothing
inst/shiny/server.R
In SEPA: SEPA
######################################################
## SEPA ##
## Interactive User Interface ##
## Server File ##
## Author:Zhicheng Ji, Hongkai Ji ##
## Maintainer:Zhicheng Ji (zji4@jhu.edu) ##
######################################################
library(shiny)
library(grid)
library(ggplot2)
library(topGO)
library(reshape2)
library(segmented)
options(shiny.maxRequestSize=30000*1024^2)
shinyServer(function(input, output,session) {
output$showbusybar <- renderUI({
tagList(
tags$head(
tags$link(rel="stylesheet", type="text/css",href="style.css"),
tags$script(type="text/javascript", src = "busy.js")
),
div(class = "busy",
p("Calculation in progress.."),
img(src="ajaxloaderq.gif")
)
)
})
Maindata <- reactiveValues()
### Readexp ###
observe({
if (input$Readexpreadin > 0)
isolate({
FileHandle <- input$ReadexpFile
if (!is.null(FileHandle)) {
tmpdata <- read.table(FileHandle$datapath,header=T,sep=input$Readexpsep,as.is=T,blank.lines.skip=TRUE)
Maindata$rawexpr <- as.matrix(tmpdata[,-1])
row.names(Maindata$rawexpr) <- make.names(tmpdata[,1])
}
})
})
output$Readexpraddsymbolui <- renderUI({
if (input$Readexprchooseanno!="symbol")
checkboxInput("Readexpraddsymbol","Add gene symbol to row names",value=F)
})
observe({
if (!is.null(Maindata$rawexpr)) {
tmp <- Maindata$rawexpr
if (input$Readexpraddsymbol) {
if (input$Readexprchoosespecies == "Human") {
x <- org.Hs.egSYMBOL
mapped_genes <- mappedkeys(x)
eg2symbol <- unlist(as.list(x[mapped_genes]))
if (input$Readexprchooseanno == "entrez") {
row.names(tmp) <- paste0(eg2symbol[row.names(tmp)],"_",row.names(tmp))
} else if (input$Readexprchooseanno == "ensembl") {
xx <- sapply(as.list(org.Hs.egENSEMBL2EG),function(i) i[1])
ensembl2symbol <- eg2symbol[xx]
names(ensembl2symbol) <- names(xx)
tmprowname <- sapply(row.names(tmp),function(i) strsplit(i,"\\.")[[1]][1])
row.names(tmp) <- paste0(ensembl2symbol[tmprowname],"_",row.names(tmp))
} else if (input$Readexprchooseanno == "unigene") {
x <- org.Hs.egUNIGENE2EG
mapped_genes <- mappedkeys(x)
unigene2eg <- sapply(as.list(x[mapped_genes]),function(i) i[1])
unigene2symbol <- eg2symbol[unigene2eg]
names(unigene2symbol) <- names(unigene2eg)
row.names(tmp) <- paste0(unigene2symbol[row.names(tmp)],"_",row.names(tmp))
}
} else if (input$Readexprchoosespecies == "Mouse") {
x <- org.Mm.egSYMBOL
mapped_genes <- mappedkeys(x)
eg2symbol <- unlist(as.list(x[mapped_genes]))
if (input$Readexprchooseanno == "entrez") {
row.names(tmp) <- paste0(eg2symbol[row.names(tmp)],"_",row.names(tmp))
} else if (input$Readexprchooseanno == "ensembl") {
xx <- sapply(as.list(org.Mm.egENSEMBL2EG),function(i) i[1])
ensembl2symbol <- eg2symbol[xx]
names(ensembl2symbol) <- names(xx)
tmprowname <- sapply(row.names(tmp),function(i) strsplit(i,"\\.")[[1]][1])
row.names(tmp) <- paste0(ensembl2symbol[tmprowname],"_",row.names(tmp))
} else if (input$Readexprchooseanno == "unigene") {
x <- org.Mm.egUNIGENE2EG
mapped_genes <- mappedkeys(x)
unigene2eg <- sapply(as.list(x[mapped_genes]),function(i) i[1])
unigene2symbol <- eg2symbol[unigene2eg]
names(unigene2symbol) <- names(unigene2eg)
row.names(tmp) <- paste0(unigene2symbol[row.names(tmp)],"_",row.names(tmp))
}
}
}
Maindata$nametransexpr <- tmp
}
})
observe({
if (!is.null(Maindata$nametransexpr)) {
tmp <- Maindata$nametransexpr[,!colnames(Maindata$nametransexpr) %in% input$Readexpcell]
if (input$Readexplogtf) {
if (input$Readexplogbase == "2") {
tmp <- log2(tmp+as.numeric(input$Readexplogpseudocount))
} else if (input$Readexplogbase == "10") {
tmp <- log10(tmp+as.numeric(input$Readexplogpseudocount))
} else if (input$Readexplogbase == "e") {
tmp <- log(tmp+as.numeric(input$Readexplogpseudocount))
}
}
tmp <- tmp[rowSums(tmp) > 0,]
tmp <- tmp[rowSums(tmp > as.numeric(input$Readexpgeneexpcutoff)) > ncol(tmp)*as.numeric(input$Readexpgenepercentcutoff)/100,]
tmp <- tmp[apply(tmp,1,sd)/rowMeans(tmp) > as.numeric(input$Readexpgenecvcutoff),]
Maindata$expr <- tmp
}
})
observe({
if (input$Readexprchoosespecies=="Human") {
library(org.Hs.eg.db)
mapdb <- "org.Hs.eg.db"
} else {
library(org.Mm.eg.db)
mapdb <- "org.Mm.eg.db"
}
xx <- unique(unlist(annFUN.org("BP", mapping = mapdb, ID = input$Readexprchooseanno)))
genename <- row.names(Maindata$rawexpr)
if (input$Readexprchooseanno == "ensembl") {
genename <- sapply(genename,function(i) strsplit(i,"\\.")[[1]][1])
}
Maindata$genenumwithid <- length(intersect(xx,genename))
})
output$Readexpcellui <- renderUI(
selectizeInput("Readexpcell","Select cells to be removed",colnames(Maindata$rawexpr),multiple = TRUE),
)
output$Readexpshowrawtable <- renderTable(head(Maindata$expr))
output$Readexpshowsummaryui <- renderUI({
if (!is.null(Maindata$expr)) {
tagList(
h4("Summary of the gene expression profile:"),
h5(paste("The filtered dataset contains",nrow(Maindata$expr),"genes and",ncol(Maindata$expr),"cells")),
h5(paste(Maindata$genenumwithid,"genes have corresponding GO terms.")),
hr(),
h4("Head of the input file:"),
tableOutput("Readexpshowrawtable")
)
}
})
### Truetime ###
observe({
if (input$Truetimereadin > 0)
isolate({
FileHandle <- input$TruetimeFile
if (!is.null(FileHandle)) {
tmp <- read.table(FileHandle$datapath,header=T,sep=input$Truetimesep,as.is=T,blank.lines.skip=TRUE)
commoncell <- intersect(tmp[,1],colnames(Maindata$expr))
Maindata$Truetimedata <- tmp[tmp[,1] %in% commoncell,]
Maindata$Truetimeexpr <- Maindata$expr[,commoncell]
}
})
})
output$Truetimeshowtime <- renderDataTable({
Maindata$Truetimedata
})
observe({
if (!is.null(Maindata$Truetimeexpr) && !is.null(Maindata$Truetimedata) && input$Truetimerunanalysis > 0)
isolate({
tmptime <- Maindata$Truetimedata[,2]
names(tmptime) <- Maindata$Truetimedata[,1]
truetime <- factor(tmptime)
tmppattern <- rep("tmp",nrow(Maindata$Truetimeexpr))
withProgress(message = 'Calculation in Progress...', {
for (i in 1:nrow(Maindata$Truetimeexpr)) {
e <- Maindata$Truetimeexpr[i,]
ttestpval <- sapply(1:(length(levels(truetime))-1), function(i) {
sign(mean(e[truetime==levels(truetime)[i]])-mean(e[truetime==levels(truetime)[i+1]]))*t.test(e[truetime==levels(truetime)[i]],e[truetime==levels(truetime)[i+1]])$p.value
})
ttestpval <- sign(ttestpval) * p.adjust(abs(ttestpval),method="fdr")
pattern <- rep("constant",length(levels(truetime))-1)
pattern[abs(ttestpval) < as.numeric(input$Truetimepvalcutoff) & ttestpval < 0] <- "up"
pattern[abs(ttestpval) < as.numeric(input$Truetimepvalcutoff) & ttestpval > 0] <- "down"
pattern <- paste(pattern,collapse = "_")
tmppattern[i] <- pattern
incProgress(1/nrow(Maindata$Truetimeexpr), detail = paste("Calculating Pattern for Gene", i))
}
})
names(tmppattern) <- row.names(Maindata$Truetimeexpr)
Maindata$Truetimeoripattern <- tmppattern
})
})
observe({
if (!is.null(Maindata$Truetimeoripattern)) {
if (!input$Truetimeignoreconst && !input$Truetimesimplify) {
Maindata$Truetimepattern <- Maindata$Truetimeoripattern
} else {
Maindata$Truetimepattern <- sapply(Maindata$Truetimeoripattern, function(pattern) {
pattern <- strsplit(pattern,"_")[[1]]
if (input$Truetimeignoreconst)
pattern <- pattern[pattern!="constant"]
if (input$Truetimesimplify)
pattern <- rle(pattern)$values
paste(pattern,collapse = "_")
})
}
Maindata$Truetimenoconstantname <- names(Maindata$Truetimepattern)[grepl("up",Maindata$Truetimepattern) | grepl("down",Maindata$Truetimepattern)]
}
})
output$Truetimepatternsummary <- renderDataTable({
if (!is.null(Maindata$Truetimepattern)) {
tmp <- data.frame(table(Maindata$Truetimepattern))
colnames(tmp) <- c("Pattern","Number")
tmp <- tmp[tmp$Pattern!="",]
tmp
}
})
output$Truetimepatternsummarysave <- downloadHandler(
filename = function() { "Pattern Summary.csv" },
content = function(file) {
tmp <- data.frame(table(Maindata$Truetimepattern))
colnames(tmp) <- c("Pattern","Number")
tmp <- tmp[tmp$Pattern!="",]
write.csv(tmp,file=file,quote=F,row.names=F)
}
)
output$TruetimepatternsummaryGeneselectui <- renderUI({
if (!is.null(Maindata$Truetimepattern))
tagList(
checkboxInput("TruetimepatternsummaryGeneselectlistall","List Genes for all Pattern",value=T),
conditionalPanel(condition = "input.TruetimepatternsummaryGeneselectlistall==0",
selectInput("TruetimepatternsummaryGeneselect","Select Pattern",sort(unique(Maindata$Truetimepattern)),multiple = T)
)
)
})
output$TruetimepatternsummaryGene <- renderDataTable({
if (!is.null(input$TruetimepatternsummaryGeneselectlistall)) {
if (input$TruetimepatternsummaryGeneselectlistall) {
tmp <- Maindata$Truetimepattern
} else {
tmp <- Maindata$Truetimepattern[Maindata$Truetimepattern %in% input$TruetimepatternsummaryGeneselect]
}
data.frame(Gene=names(tmp),Pattern=tmp)
}
})
output$TruetimepatternsummaryGenesave <- downloadHandler(
filename = function() { "Gene List.csv" },
content = function(file) {
if (input$TruetimepatternsummaryGeneselectlistall) {
tmp <- Maindata$Truetimepattern
} else {
tmp <- Maindata$Truetimepattern[Maindata$Truetimepattern %in% input$TruetimepatternsummaryGeneselect]
}
tmp <- data.frame(Gene=names(tmp),Pattern=tmp)
write.csv(tmp,file=file,quote=F,row.names=F)
}
)
output$Truetimeselectgeneui <- renderUI(
selectizeInput("Truetimeselectgene","Select genes of interest",Maindata$Truetimenoconstantname,multiple = TRUE)
)
output$Truetimevisualize <- renderPlot({
if (!is.null(Maindata$Truetimedata) && !is.null(input$Truetimeselectgene)) {
tmptime <- Maindata$Truetimedata[,2]
names(tmptime) <- Maindata$Truetimedata[,1]
truetime <- factor(tmptime)
tmp <- data.frame(time=rep(levels(truetime),length(input$Truetimeselectgene)),expmean=0,Gene=rep(input$Truetimeselectgene,each=length(levels(truetime))))
tmp$expmean <- as.vector(sapply(input$Truetimeselectgene, function(gene) {
e <- Maindata$Truetimeexpr[gene,Maindata$Truetimedata[,1]]
sapply(1:length(levels(truetime)), function(i) {
mean(e[truetime==levels(truetime)[i]])
})
}))
ggplot(data = tmp, aes(x=time, y=expmean, colour=Gene)) +
geom_line(aes(group=Gene)) +
geom_point(size=4) +
xlab("Experiment Time") +
ylab("Expression Values") +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(size=17,color='black'),
axis.text.y = element_text(size=17,color='black'),
axis.title.x = element_text(size=20,vjust=-1),
axis.title.y = element_text(size=20,vjust=1),
strip.text.y = element_text(size=17,color='black'),
legend.text = element_text(size=15),
legend.title = element_text(size=15),
legend.position = "right"
)
}
})
output$Truetimevisualizesave <- downloadHandler(
filename = function() { "Pattern.pdf" },
content = function(file) {
if (!is.null(Maindata$Truetimedata) && !is.null(input$Truetimeselectgene)) {
pdf(file,width=14,height=7)
tmptime <- Maindata$Truetimedata[,2]
names(tmptime) <- Maindata$Truetimedata[,1]
truetime <- factor(tmptime)
tmp <- data.frame(time=rep(levels(truetime),length(input$Truetimeselectgene)),expmean=0,Gene=rep(input$Truetimeselectgene,each=length(levels(truetime))))
tmp$expmean <- as.vector(sapply(input$Truetimeselectgene, function(gene) {
e <- Maindata$Truetimeexpr[gene,Maindata$Truetimedata[,1]]
sapply(1:length(levels(truetime)), function(i) {
mean(e[truetime==levels(truetime)[i]])
})
}))
tmp <- ggplot(data = tmp, aes(x=time, y=expmean, colour=Gene)) +
geom_line(aes(group=Gene)) +
geom_point(size=4) +
xlab("Experiment Time") +
ylab("Expression Values") +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(size=17,color='black'),
axis.text.y = element_text(size=17,color='black'),
axis.title.x = element_text(size=20,vjust=-1),
axis.title.y = element_text(size=20,vjust=1),
strip.text.y = element_text(size=17,color='black'),
legend.text = element_text(size=15),
legend.title = element_text(size=15),
legend.position = "right"
)
print(tmp)
dev.off()
}
}
)
output$Truetimevisualizetable <- renderDataTable({
if (!is.null(input$Truetimeselectgene)) {
data.frame(Gene=input$Truetimeselectgene,Pattern=Maindata$Truetimepattern[input$Truetimeselectgene])
}
})
output$Truetimevisualizetablesave <- downloadHandler(
filename = function() { "Gene Pattern.csv" },
content = function(file) {
tmp <- data.frame(Gene=input$Truetimeselectgene,Pattern=Maindata$Truetimepattern[input$Truetimeselectgene])
write.csv(tmp,file=file,quote=F,row.names=F)
}
)
output$TruetimeGOanalysisselectui <- renderUI({
if (!is.null(Maindata$Truetimepattern))
selectInput("TruetimeGOanalysisselect","Select pattern of interest",sort(unique(Maindata$Truetimepattern)),multiple = T)
})
observe({
if (input$TruetimeGOanalysisrunbutton > 0) {
isolate({
if (!is.null(input$TruetimeGOanalysisselect) && Maindata$genenumwithid > 0) {
withProgress(message = 'Performing GO analysis...', {
if (input$Readexprchoosespecies=="Human") {
mapdb <- "org.Hs.eg.db"
} else {
mapdb <- "org.Mm.eg.db"
}
allgene <- row.names(Maindata$rawexpr)
if (input$Readexprchooseanno == "ensembl") {
allgene <- sapply(allgene,function(i) strsplit(i,"\\.")[[1]][1])
}
inputgene <- allgene[Maindata$Truetimepattern %in% input$TruetimeGOanalysisselect]
geneList <- factor(as.integer(allgene %in% inputgene))
names(geneList) <- allgene
Maindata$TruetimeGOdata <- new("topGOdata", ontology = "BP", allGenes = geneList,geneSel=function(a) {a},annot = annFUN.org, mapping = mapdb, ID = input$Readexprchooseanno)
Maindata$TruetimeGOresultFisher <- runTest(Maindata$TruetimeGOdata, algorithm = "classic", statistic = "fisher")
})
}
})
}
})
output$TruetimeGOanalysisresult <- renderDataTable({
if (!is.null(Maindata$TruetimeGOresultFisher)) {
tmp <- GenTable(Maindata$TruetimeGOdata, classicFisher = Maindata$TruetimeGOresultFisher, topNodes = as.numeric(input$TruetimeGOanalysistermnum),orderBy="classicFisher")
tmp
}
})
output$TruetimeGOanalysisresultsave <- downloadHandler(
filename = function() { "GO Analysis.csv" },
content = function(file) {
if (!is.null(Maindata$TruetimeGOresultFisher)) {
tmp <- GenTable(Maindata$TruetimeGOdata, classicFisher = Maindata$TruetimeGOresultFisher, topNodes = as.numeric(input$TruetimeGOanalysistermnum),orderBy="classicFisher")
tmp$Term <- gsub(","," ",tmp$Term)
write.csv(tmp,file=file,quote=F,row.names=F)
}
}
)
### Pseudotime ###
observe({
if (input$Pseudotimereadin > 0)
isolate({
FileHandle <- input$PseudotimeFile
if (!is.null(FileHandle)) {
tmp <- read.table(FileHandle$datapath,header=T,sep=input$Pseudotimesep,as.is=T,blank.lines.skip=TRUE)
pseudotime <- tmp[,2]
names(pseudotime) <- tmp[,1]
commoncell <- intersect(tmp[,1],colnames(Maindata$expr))
Maindata$Pseudotimedata <- pseudotime[commoncell]
Maindata$Pseudotimeexpr <- Maindata$expr[,commoncell]
}
})
})
output$Pseudotimeshowtime <- renderDataTable({
data.frame(Cell=names(Maindata$Pseudotimedata),Time=Maindata$Pseudotimedata)
})
observe({
if (!is.null(Maindata$Pseudotimeexpr) && !is.null(Maindata$Pseudotimedata) && input$Pseudotimerunanalysis > 0)
isolate({
pseudotime <- Maindata$Pseudotimedata
expr <- Maindata$Pseudotimeexpr
gap <- as.numeric(input$Pseudotimegapvalue)
fastRSS <- function(X, y) {
XtX <- crossprod(X)
ch <- chol(XtX)
V <- chol2inv(ch)
sum(drop(X %*% V %*% crossprod(X, y)-y)^2)
}
x <- pseudotime
breakpoint <- rowMeans(cbind(pseudotime[-1],pseudotime[-length(pseudotime)]))
breakpoint <- breakpoint[gap:(length(breakpoint)-gap+1)]
spmat <- t(sapply(breakpoint,function(i) {
ifelse(x > i,x - i,0)
}))
# genes that are constantly zero
expr <- expr[,names(pseudotime)]
zerogene <- row.names(expr)[rowSums(expr) == 0]
fitexpr <- expr <- expr[rowSums(expr) > 0,]
# use davies test to identify whether there is a transition point
withProgress(message = 'Determining existence of transition points...', {
daviespval <- apply(expr,1,function(y) {
tmpy <- y[(gap+1):(length(y)-gap)]
tmpx <-x[(gap+1):(length(y)-gap)]
if (sum(tmpy) > 0) {
fit <- lm(tmpy~tmpx)
davies.test(fit,~tmpx)$p.value
} else {
1
}
})
})
daviespval[is.na(daviespval)] <- 1
daviespval <- p.adjust(daviespval,method="fdr")
notransgene <- names(daviespval)[daviespval >= 0.05]
transgene <- names(daviespval)[daviespval < 0.05]
withProgress(message = 'Predicting starting positions...', {
transpos <- sapply(transgene,function(gene) {
y <- expr[gene,]
RSS1 <- sapply(1:length(breakpoint),function(i) {
fastRSS(cbind(1,x,spmat[i,]),y)
})
which.min(RSS1)
})
})
pattern <- data.frame(pattern=rep("constant",length(transgene)),transpoint=rep(0,length(transgene)),LCI=rep(0,length(transgene)),UCI=rep(0,length(transgene)),stringsAsFactors = F)
row.names(pattern) <- transgene
withProgress(message = 'Calculating transition points...', {
for (i in 1:length(transgene)) {
set.seed(1234)
y <- expr[transgene[i],]
fit <- lm(y~x)
o.seg1 <- tryCatch(segmented(fit,seg.Z=~x,psi=breakpoint[transpos[i]]),error=function(e) {})
if (is.null(o.seg1)) {
suppressWarnings(o.seg1 <- segmented(fit,seg.Z=~x,psi=breakpoint[transpos[i]],control = seg.control(n.boot=0,it.max=1)))
}
if (o.seg1$psi[2] <= x[gap] || o.seg1$psi[2] >= x[length(x)-gap+1]) {
notransgene <- c(notransgene,transgene[i])
} else {
slopecol <- rep("constant",2)
for (j in 1:2) {
if (slope(o.seg1)$x[j,4] * slope(o.seg1)$x[j,5] > 0) {
if (slope(o.seg1)$x[j,4] > 0) {
slopecol[j] <- "up"
} else {
slopecol[j] <- "down"
}
}
}
if ((input$Pseudotimesimplify && slopecol[1] == slopecol[2]) || (input$Pseudotimeignoreconst && (slopecol[1]=="constant" || slopecol[2]=="constant"))) {
notransgene <- c(notransgene,transgene[i])
} else {
pattern[i,1] <- paste0(slopecol,collapse = "_")
pattern[i,2] <- confint(o.seg1)$x[1]
pattern[i,3] <- confint(o.seg1)$x[2]
pattern[i,4] <- confint(o.seg1)$x[3]
fitexpr[transgene[i],] <- fitted(o.seg1)
}
}
incProgress(1/length(transgene), detail = paste("Calculating transition point for gene", i))
}
})
pattern <- pattern[pattern[,1]!="constant",]
pattern <- pattern[order(pattern$pattern,pattern$transpoint),]
tmp <- pattern[,1]
pattern <- pattern[,-1]
pattern <- split(pattern,tmp)
notranspval <- sapply(notransgene,function(i) {
set.seed(1234)
y <- expr[i,]
fit <- lm(y~x)
fitexpr[i,] <<- fitted(fit)
sign(summary(fit)[[4]][2,1])*summary(fit)[[4]][2,4]
})
notranspval <- sign(notranspval) * p.adjust(abs(notranspval),method = "fdr")
upgene <- notranspval[notranspval > 0 & abs(notranspval) < 0.05]
downgene <- notranspval[notranspval < 0 & abs(notranspval) < 0.05]
constantgene <- notranspval[abs(notranspval) >= 0.05]
pattern$up <- sort(upgene)
pattern$down <- sort(abs(downgene))
if (!input$Pseudotimeignoreconst)
pattern$constant <- sort(abs(constantgene))
Maindata$Pseudotimefitexpr <- fitexpr
Maindata$Pseudotimepattern <- pattern
tmp <- NULL
for (name in names(Maindata$Pseudotimepattern)) {
if (typeof(Maindata$Pseudotimepattern[[name]]) == "list") {
tmppattern <- rep(name,length(row.names(Maindata$Pseudotimepattern[[name]])))
names(tmppattern) <- row.names(Maindata$Pseudotimepattern[[name]])
tmp <- c(tmp,tmppattern)
} else {
tmppattern <- rep(name,length(names(Maindata$Pseudotimepattern[[name]])))
names(tmppattern) <- names(Maindata$Pseudotimepattern[[name]])
tmp <- c(tmp,tmppattern)
}
}
Maindata$Pseudotimepatternsimple <- tmp
})
})
output$Pseudotimepatternsummary <- renderDataTable({
if (!is.null(Maindata$Pseudotimepatternsimple)) {
tmp <- data.frame(table(Maindata$Pseudotimepatternsimple))
colnames(tmp) <- c("Pattern","Number")
tmp
}
})
output$Pseudotimepatternsummarysave <- downloadHandler(
filename = function() { "Pattern Summary.csv" },
content = function(file) {
if (!is.null(Maindata$Pseudotimepatternsimple)) {
tmp <- data.frame(table(Maindata$Pseudotimepatternsimple))
colnames(tmp) <- c("Pattern","Number")
write.csv(tmp,file=file,quote=F,row.names=F)
}
}
)
output$PseudotimepatternsummaryGeneselectui <- renderUI(
if (!is.null(Maindata$Pseudotimepattern))
tagList(
checkboxInput("PseudotimepatternsummaryGeneselectlistall","List Genes for all Pattern",value=T),
conditionalPanel(condition = "input.PseudotimepatternsummaryGeneselectlistall==0",
selectInput("PseudotimepatternsummaryGeneselect","Select Pattern",names(Maindata$Pseudotimepattern),multiple = T)
)
)
)
output$PseudotimepatternsummaryGene <- renderDataTable({
if (!is.null(input$PseudotimepatternsummaryGeneselectlistall)) {
if (input$PseudotimepatternsummaryGeneselectlistall) {
tmp <- Maindata$Pseudotimepatternsimple
data.frame(Gene=names(tmp),Pattern=tmp)
} else if (sum(!grepl("_",input$PseudotimepatternsummaryGeneselect)) > 0) {
tmp <- Maindata$Pseudotimepatternsimple[Maindata$Pseudotimepatternsimple %in% input$PseudotimepatternsummaryGeneselect]
data.frame(Gene=names(tmp),Pattern=tmp)
} else {
allres <- NULL
for (i in input$PseudotimepatternsummaryGeneselect) {
tmp <- cbind(row.names(Maindata$Pseudotimepattern[[i]]),i,Maindata$Pseudotimepattern[[i]])
colnames(tmp) <- c("Gene","Pattern","Transition","LCI","UCI")
allres <- rbind(allres,tmp)
}
allres
}
}
})
output$PseudotimepatternsummaryGenesave <- downloadHandler(
filename = function() { "Gene List.csv" },
content = function(file) {
if (input$PseudotimepatternsummaryGeneselectlistall) {
tmp <- Maindata$Pseudotimepatternsimple
tmp <- data.frame(Gene=names(tmp),Pattern=tmp)
} else if (sum(!grepl("_",input$PseudotimepatternsummaryGeneselect)) > 0) {
tmp <- Maindata$Pseudotimepatternsimple[Maindata$Pseudotimepatternsimple %in% input$PseudotimepatternsummaryGeneselect]
tmp <- data.frame(Gene=names(tmp),Pattern=tmp)
} else {
allres <- NULL
for (i in input$PseudotimepatternsummaryGeneselect) {
tmp <- cbind(row.names(Maindata$Pseudotimepattern[[i]]),i,Maindata$Pseudotimepattern[[i]])
colnames(tmp) <- c("Gene","Pattern","Transition","LCI","UCI")
allres <- rbind(allres,tmp)
}
tmp <- allres
}
write.csv(tmp,file=file,quote=F,row.names=F)
}
)
observe({
tmp <- Maindata$Pseudotimepatternsimple
Maindata$Pseudotimenoconstantname <- names(tmp)[grepl("up",tmp) | grepl("down",tmp)]
})
output$Pseudotimeselectgeneui <- renderUI(
selectizeInput("Pseudotimeselectgene","Select genes of interest",Maindata$Pseudotimenoconstantname,multiple = TRUE)
)
Pseudotimeplotfunc <- function(pattern,expr,fitexpr,pseudotime,gap,gene,showtrue=F) {
findgene <- function(gene) {
findres <- sapply(names(pattern), function(pat) {
if (grepl("_",pat)) {
gene %in% row.names(pattern[[pat]])
} else {
gene %in% names(pattern[[pat]])
}
})
names(which(findres))
}
genename <- gene
x <- sort(pseudotime)
gene <- sapply(gene, findgene)
if (length(gene) == 1) {
if (grepl("_",gene)) {
transinfo <- pattern[[gene]][names(gene),]
transmean <- transinfo[1,1]
} else {
transinfo <- pattern[[gene]][names(gene)]
}
y <- expr[names(gene),names(x)]
fity <- fitexpr[names(gene),names(x)]
p <- qplot(x,y,data=data.frame(x=x,y=y),size=3)
gene <- gsub("constant","black",gene)
gene <- gsub("up","green",gene)
gene <- gsub("down","red",gene)
gene <- strsplit(gene,"_")[[1]]
if (length(gene)==1) {
p <- p + geom_line(aes(x=x,y=y),data=data.frame(x=x,y=fity),col=gene,size=2)
} else {
transpointy <- (fity[2]-fity[1])/(x[2]-x[1])*(transmean-x[1])+fity[1]
p <- p + geom_line(aes(x=x,y=y),data=data.frame(x=c(x[x<transmean],transmean),y=c(fity[x<transmean],transpointy)),col=gene[1],size=2)
p <- p + geom_line(aes(x=x,y=y),data=data.frame(x=c(transmean,x[x>transmean]),y=c(transpointy,fity[x>transmean])),col=gene[2],size=2)
ypos <- ifelse(max(y) > 0, 1.1 * max(y), 0.9 * max(y))
p <- p + geom_point(aes(x=transmean,y=ypos),col="blue",size=5) + geom_segment(aes(x=transinfo[1,2],xend=transinfo[1,3],y=ypos,yend=ypos),col="blue",size=2)
}
p + xlab("Pseudo-time") +
ylab("Gene Expression") +
ggtitle(genename) +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(size=17,color='black'),
axis.text.y = element_text(size=17,color='black'),
axis.title.x = element_text(size=20),
axis.title.y = element_text(size=20),
strip.text.y = element_text(size=17,color='black'),
plot.title = element_text(size = 25),
legend.position = "none")
} else {
if (!showtrue) {
geneexpr <- fitexpr[names(gene),names(x)]
} else {
geneexpr <- expr[names(gene),names(x)]
}
colnames(geneexpr) <- NULL
geneexpr <- geneexpr[rev(row.names(geneexpr)),]
linesegmat <- NULL
for (g in 1:length(gene)) {
if (grepl("_",gene[g])) {
tmp <- unlist(pattern[[gene[g]]][names(gene[g]),])
tmp <- sapply(tmp,function(j) which.min(abs(j-x)))
linesegmat <- rbind(linesegmat,c(tmp,g))
}
}
linesegmat[,4] <- length(gene) + 1 - linesegmat[,4]
geneexpr <- t(apply(geneexpr,1,scale))
geneexpr <- melt(geneexpr)
p <- ggplot(data=geneexpr, aes(x=Var2, y=Var1)) + geom_tile(aes(fill = value)) + scale_fill_gradient2(low = "blue",high = "red",mid="white") +
geom_segment(aes(x=x,xend=xend,y=y,yend=yend),data=data.frame(x=linesegmat[,2],xend=linesegmat[,3],y=linesegmat[,4],yend=linesegmat[,4])) +
geom_point(aes(x=x,y=y),data=data.frame(x=linesegmat[,1],y=linesegmat[,4]))
p + xlab("Cell") +
ylab("Predicted Expression") +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(size=17,color='black'),
axis.text.y = element_text(size=17,color='black'),
axis.title.x = element_text(size=20,vjust=-1),
axis.title.y = element_text(size=20,vjust=1),
strip.text.y = element_text(size=17,color='black'),
legend.text = element_text(size=15),
legend.title = element_text(size=15),
legend.position = "right"
)
}
}
output$Pseudotimevisualize <- renderPlot({
if (!is.null(Maindata$Pseudotimedata) && !is.null(input$Pseudotimeselectgene)) {
pseudotime <- Maindata$Pseudotimedata
Pseudotimeplotfunc(Maindata$Pseudotimepattern,Maindata$Pseudotimeexpr,Maindata$Pseudotimefitexpr,pseudotime,as.numeric(input$Pseudotimegapvalue),input$Pseudotimeselectgene,showtrue=input$Pseudotimegeneexpressionshowtrue)
}
})
output$Pseudotimevisualizeui <- renderUI({
plotOutput("Pseudotimevisualize",width=700,height=ifelse(length(input$Pseudotimeselectgene)==1,700,400))
})
output$Pseudotimevisualizesave <- downloadHandler(
filename = function() { "Pattern.pdf" },
content = function(file) {
if (!is.null(Maindata$Pseudotimedata) && !is.null(input$Pseudotimeselectgene)) {
pdf(file)
pseudotime <- Maindata$Pseudotimedata
Pseudotimeplotfunc(Maindata$Pseudotimepattern,Maindata$Pseudotimeexpr,Maindata$Pseudotimefitexpr,pseudotime,as.numeric(input$Pseudotimegapvalue),input$Pseudotimeselectgene,showtrue=F)
dev.off()
}
}
)
output$Pseudotimevisualizetable <- renderDataTable({
if (!is.null(input$Pseudotimeselectgene)) {
data.frame(Gene=input$Pseudotimeselectgene,Pattern=Maindata$Pseudotimepatternsimple[input$Pseudotimeselectgene])
}
})
output$Pseudotimevisualizetablesave <- downloadHandler(
filename = function() { "Gene Pattern.csv" },
content = function(file) {
tmp <- data.frame(Gene=input$Pseudotimeselectgene,Pattern=Maindata$Pseudotimepatternsimple[input$Pseudotimeselectgene])
write.csv(tmp,file=file,quote=F,row.names=F)
}
)
output$PseudotimeGOanalysisselectui <- renderUI({
if (!is.null(Maindata$Pseudotimepatternsimple))
selectInput("PseudotimeGOanalysisselect","Select pattern of interest",sort(unique(Maindata$Pseudotimepatternsimple)),multiple = T)
})
observe({
if (input$PseudotimeGOanalysisrunbutton > 0) {
isolate({
if (!is.null(input$PseudotimeGOanalysisselect) && Maindata$genenumwithid > 0) {
withProgress(message = 'Performing GO analysis...', value = 0, {
if (input$Readexprchoosespecies=="Human") {
mapdb <- "org.Hs.eg.db"
} else {
mapdb <- "org.Mm.eg.db"
}
allgene <- row.names(Maindata$rawexpr)
if (input$Readexprchooseanno == "ensembl") {
allgene <- sapply(allgene,function(i) strsplit(i,"\\.")[[1]][1])
}
inputgene <- allgene[Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisselect]
geneList <- factor(as.integer(allgene %in% inputgene))
names(geneList) <- allgene
Maindata$PseudotimeGOdata <- new("topGOdata", ontology = "BP", allGenes = geneList,geneSel=function(a) {a},annot = annFUN.org, mapping = mapdb, ID = input$Readexprchooseanno)
Maindata$PseudotimeGOresultFisher <- runTest(Maindata$PseudotimeGOdata, algorithm = "classic", statistic = "fisher")
})
}
})
}
})
output$PseudotimeGOanalysisresult <- renderDataTable({
if (!is.null(Maindata$PseudotimeGOresultFisher)) {
tmp <- GenTable(Maindata$PseudotimeGOdata, classicFisher = Maindata$PseudotimeGOresultFisher, topNodes = as.numeric(input$PseudotimeGOanalysistermnum),orderBy="classicFisher")
tmp
}
})
output$PseudotimeGOanalysisresultsave <- downloadHandler(
filename = function() { "GO Analysis.csv" },
content = function(file) {
if (!is.null(Maindata$PseudotimeGOresultFisher)) {
tmp <- GenTable(Maindata$PseudotimeGOdata, classicFisher = Maindata$PseudotimeGOresultFisher, topNodes = as.numeric(input$PseudotimeGOanalysistermnum),orderBy="classicFisher")
tmp$Term <- gsub(","," ",tmp$Term)
write.csv(tmp,file=file,quote=F,row.names=F)
}
}
)
output$PseudotimeGOanalysisTimeselectui <- renderUI({
if (!is.null(Maindata$Pseudotimepatternsimple)) {
tmp <- sort(unique(Maindata$Pseudotimepatternsimple))
tmp <- tmp[grep("_",tmp)]
if (length(tmp) == 0) {
strong("There is no pattern with transition point!")
} else {
selectInput("PseudotimeGOanalysisTimeselect","Select pattern of interest",tmp,multiple = T)
}
}
})
output$PseudotimeGOanalysisTimewinsizesliderui <- renderUI({
if (!is.null(input$PseudotimeGOanalysisTimeselect)) {
tagList(
helpText("Select window size (how many genes to be included in each GO analsysis). Notice that the results of GO analyses are not robust if too few genes and included."),
sliderInput("PseudotimeGOanalysisTimewinsizeslider","Select window size",min=1,max=sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect),step=1,value=ifelse(sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect) > 50,50,ceiling(sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect)/2)))
)
}
})
output$PseudotimeGOanalysisTimestepsliderui <- renderUI({
if (!is.null(input$PseudotimeGOanalysisTimewinsizeslider))
sliderInput("PseudotimeGOanalysisTimestepslider","Select moving step",min=1,max=sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect)-1,step=1,value=ifelse(sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect)-1 > 25,25,ceiling((sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect)-1)/2)))
})
observe({
if (input$PseudotimeGOanalysisTimerunbutton > 0) {
isolate({
if (!is.null(input$PseudotimeGOanalysisTimeselect) && Maindata$genenumwithid > 0) {
GOanalysis <- function(inputgene,allgene,identifier="ENSEMBL",species="Human") {
if (species == "Human") {
mapdb <- "org.Hs.eg.db"
} else if (species == "Mouse") {
mapdb <- "org.Mm.eg.db"
}
geneList <- factor(as.integer(allgene %in% inputgene))
names(geneList) <- allgene
GOdata <- new("topGOdata", ontology = "BP", allGenes = geneList,geneSel=function(a) {a},annot = annFUN.org, mapping = mapdb, ID = identifier)
resultFisher <- runTest(GOdata, algorithm = "classic", statistic = "fisher")
list(resultFisher=resultFisher,GOdata=GOdata)
}
allres <- NULL
for (i in input$PseudotimeGOanalysisTimeselect) {
tmp <- data.frame(row.names(Maindata$Pseudotimepattern[[i]]),i,Maindata$Pseudotimepattern[[i]],stringsAsFactors = F)
colnames(tmp) <- c("Gene","Pattern","Transition","LCI","UCI")
allres <- rbind(allres,tmp)
}
genelist <- allres[order(allres$Transition),1]
if (input$Readexprchooseanno!="symbol" && input$Readexpraddsymbol)
genelist <- sapply(genelist,function(i) strsplit(i,"_")[[1]][2])
allgene <- row.names(Maindata$rawexpr)
if (input$Readexprchooseanno == "ensembl") {
allgene <- sapply(allgene,function(i) strsplit(i,"\\.")[[1]][1])
genelist <- sapply(genelist,function(i) strsplit(i,"\\.")[[1]][1])
}
withProgress(message = 'Calculation in Progress...', value = 0, {
genenum <- sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect)
windowsize <- as.numeric(input$PseudotimeGOanalysisTimewinsizeslider)
movesize <- as.numeric(input$PseudotimeGOanalysisTimestepslider)
maxwinnum <- ceiling((genenum-windowsize)/movesize) + 1
res <- list()
for (i in 1:maxwinnum) {
if (i==maxwinnum) {
startid <- genenum-windowsize+1
endid <- genenum
} else {
startid <- 1+movesize*(i-1)
endid <- movesize*(i-1)+windowsize
}
res[[paste0(startid,"-",endid)]] <- GOanalysis(genelist[startid:endid],allgene,identifier=input$Readexprchooseanno,species=input$Readexprchoosespecies)
incProgress(1/maxwinnum, detail = paste("Performing GO analysis for Window", i))
}
Maindata$PseudotimewindowGOres <- res
})
}
})
}
})
observe({
res <- list()
for (name in names(Maindata$PseudotimewindowGOres)) {
res[[name]] <- GenTable(Maindata$PseudotimewindowGOres[[name]][["GOdata"]], classicFisher = Maindata$PseudotimewindowGOres[[name]][["resultFisher"]], topNodes = as.numeric(input$PseudotimeGOanalysisTimetermnum),orderBy="classicFisher")
}
Maindata$PseudotimewindowGOtable <- res
})
output$PseudotimeGOanalysisTimeselectresultwindowui <- renderUI({
selectInput("PseudotimeGOanalysisTimeselectresultwindow","Select window",names(Maindata$PseudotimewindowGOtable))
})
output$PseudotimeGOanalysisTimeshowresultwindow <- renderDataTable({
if (!is.null(input$PseudotimeGOanalysisTimeselectresultwindow))
Maindata$PseudotimewindowGOtable[[input$PseudotimeGOanalysisTimeselectresultwindow]]
})
output$PseudotimeGOanalysisTimeshowresultwindowsave <- downloadHandler(
filename = function() { "GO Analysis.csv" },
content = function(file) {
if (!is.null(input$PseudotimeGOanalysisTimeselectresultwindow))
write.csv(Maindata$PseudotimewindowGOtable[[input$PseudotimeGOanalysisTimeselectresultwindow]],file=file,quote=F,row.names=F)
}
)
output$PseudotimeGOanalysisTimeselectresulttimetrendselectmethodui <- renderUI({
if (input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=='Specific') {
selectInput("PseudotimeGOanalysisTimeselectresulttimetrendspecific","Select GO term",unique(as.vector(sapply(Maindata$PseudotimewindowGOtable,function(i) i[,1]))),multiple = T)
} else {
sliderInput("PseudotimeGOanalysisTimeselectresulttimetrendtop","Select Number of Top GO Terms",1,as.numeric(input$PseudotimeGOanalysisTimetermnum),1,1)
}
})
output$PseudotimeGOanalysisTimeshowresulttimetrend <- renderPlot({
if (!is.null(Maindata$PseudotimewindowGOtable) && ((input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=="Specific" && !is.null(input$PseudotimeGOanalysisTimeselectresulttimetrendspecific)) || (input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=="Top" && !is.null(input$PseudotimeGOanalysisTimeselectresulttimetrendtop)))) {
GOres <- Maindata$PseudotimewindowGOtable
termnum <- as.numeric(input$PseudotimeGOanalysisTimetermnum)
if (input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=="Specific") {
GOterm <- input$PseudotimeGOanalysisTimeselectresulttimetrendspecific
} else {
GOterm <- unique(as.vector(sapply(GOres,function(i) i[1:as.numeric(input$PseudotimeGOanalysisTimeselectresulttimetrendtop),1])))
}
GOdes <- NULL
for (i in GOres) {
GOdes <- rbind(GOdes,as.matrix(i[,1:2]))
}
GOdes <- unique(GOdes)
rankres <- sapply(GOterm,function(term) {
sapply(GOres,function(i) {
tmp <- which(i[,1]==term)
if (length(tmp) == 0)
tmp <- termnum + 1
tmp
})
})
rankres <- melt(rankres,id="V1")
maxrank <- max(rankres$value)
if (maxrank < termnum + 1) {
tmpyset <- scale_y_reverse()
} else {
tickpos <- round(seq(0,maxrank,maxrank/5))
tickpos <- tickpos[tickpos < termnum + 1]
tmpyset <- scale_y_reverse(lim=c(termnum + 1,1),breaks=c(tickpos,(termnum+1)),labels=c(tickpos,paste(">",termnum)))
}
colnames(rankres)[2] <- "GOTerm"
rankres[,2] <- paste0(rankres[,2],"\n",sapply(rankres[,2], function(i) GOdes[GOdes[,1]==i,2]))
if (input$PseudotimeGOanalysisTimeselectresulttimetrendshowheatmap) {
p <- ggplot(data=rankres, aes(x=Var1, y=GOTerm)) + geom_tile(aes(fill = value), colour = "white") + scale_fill_gradient2(low = "blue",high = "red",mid="white")
} else {
p <- ggplot(data = rankres, aes(x=Var1, y=value, colour=GOTerm)) +
geom_line(aes(group=GOTerm)) + tmpyset +
geom_point(size=4)
}
p + xlab("Interval") +
ylab("Rank") +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(size=17,color='black'),
axis.text.y = element_text(size=17,color='black'),
axis.title.x = element_text(size=20,vjust=-1),
axis.title.y = element_text(size=20,vjust=1),
strip.text.y = element_text(size=17,color='black'),
legend.text = element_text(size=15),
legend.title = element_text(size=15),
legend.position = "right",
legend.key.width=unit(3,"line"),legend.key.height=unit(3,"line")
)
}
})
output$PseudotimeGOanalysisTimeshowresultwindowplotsave <- downloadHandler(
filename = function() { "GO pattern.pdf" },
content = function(file) {
if (!is.null(Maindata$PseudotimewindowGOtable) && ((input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=="Specific" && !is.null(input$PseudotimeGOanalysisTimeselectresulttimetrendspecific)) || (input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=="Top" && !is.null(input$PseudotimeGOanalysisTimeselectresulttimetrendtop)))) {
pdf(file,width=14,height=7)
GOres <- Maindata$PseudotimewindowGOtable
termnum <- as.numeric(input$PseudotimeGOanalysisTimetermnum)
if (input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=="Specific") {
GOterm <- input$PseudotimeGOanalysisTimeselectresulttimetrendspecific
} else {
GOterm <- unique(as.vector(sapply(GOres,function(i) i[1:as.numeric(input$PseudotimeGOanalysisTimeselectresulttimetrendtop),1])))
}
GOdes <- NULL
for (i in GOres) {
GOdes <- rbind(GOdes,as.matrix(i[,1:2]))
}
GOdes <- unique(GOdes)
rankres <- sapply(GOterm,function(term) {
sapply(GOres,function(i) {
tmp <- which(i[,1]==term)
if (length(tmp) == 0)
tmp <- termnum + 1
tmp
})
})
rankres <- melt(rankres,id="V1")
maxrank <- max(rankres$value)
if (maxrank < termnum + 1) {
tmpyset <- scale_y_reverse()
} else {
tickpos <- round(seq(0,maxrank,maxrank/5))
tickpos <- tickpos[tickpos < termnum + 1]
tmpyset <- scale_y_reverse(lim=c(termnum + 1,1),breaks=c(tickpos,(termnum+1)),labels=c(tickpos,paste(">",termnum)))
}
colnames(rankres)[2] <- "GOTerm"
rankres[,2] <- paste0(rankres[,2],"\n",sapply(rankres[,2], function(i) GOdes[GOdes[,1]==i,2]))
if (input$PseudotimeGOanalysisTimeselectresulttimetrendshowheatmap) {
p <- ggplot(data=rankres, aes(x=Var1, y=GOTerm)) + geom_tile(aes(fill = value), colour = "white") + scale_fill_gradient2(low = "blue",high = "red",mid="white")
} else {
p <- ggplot(data = rankres, aes(x=Var1, y=value, colour=GOTerm)) +
geom_line(aes(group=GOTerm)) + tmpyset +
geom_point(size=4)
}
p <- p + xlab("Interval") +
ylab("Rank") +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(size=17,color='black'),
axis.text.y = element_text(size=17,color='black'),
axis.title.x = element_text(size=20,vjust=-1),
axis.title.y = element_text(size=20,vjust=1),
strip.text.y = element_text(size=17,color='black'),
legend.text = element_text(size=15),
legend.title = element_text(size=15),
legend.position = "right",
legend.key.width=unit(3,"line"),legend.key.height=unit(3,"line")
)
print(p)
}
dev.off()
}
)
### Comparison ###
observe({
if (is.null(Maindata$Comparisonrawdata))
Maindata$Comparisonrawdata <- list()
})
output$Comparisonlistnameui <- renderUI({
if (!is.null(Maindata$Comparisonrawdata))
textInput("Comparisonlistname","List Name",paste0("List",length(Maindata$Comparisonrawdata) + 1))
})
observe({
if (input$Comparisonreadin > 0)
isolate({
FileHandle <- input$ComparisonFile
if (!is.null(FileHandle)) {
Maindata$Comparisonrawdata[[input$Comparisonlistname]] <- read.csv(FileHandle$datapath,header=T,as.is=T,blank.lines.skip=TRUE)
}
})
})
observe({
if (!input$Comparisonsimplify && !input$Comparisonignoreconst) {
Maindata$Comparisondata <- Maindata$Comparisonrawdata
} else {
Maindata$Comparisondata <- lapply(Maindata$Comparisonrawdata, function(i) {
i[,2] <- sapply(i[,2], function(pattern) {
pattern <- strsplit(pattern,"_")[[1]]
if (input$Comparisonignoreconst)
pattern <- pattern[pattern!="constant"]
if (input$Comparisonsimplify)
pattern <- rle(pattern)$values
if (length(pattern) == 0) {
"NA"
} else {
paste(pattern,collapse = "_")
}
})
i
})
}
})
output$Comparisonchoosefileui <- renderUI({
selectInput("Comparisonchoosefile","Choose file to display",names(Maindata$Comparisonrawdata),names(Maindata$Comparisonrawdata)[length(Maindata$Comparisonrawdata)])
})
output$Comparisonshowfile <- renderDataTable({
if (!is.null(input$Comparisonchoosefile))
Maindata$Comparisondata[[input$Comparisonchoosefile]]
})
observe({
if (length(Maindata$Comparisondata) > 1) {
tmp <- Reduce(function(x, y) merge(x, y, by="Gene"), Maindata$Comparisondata)
colnames(tmp) <- c("Gene",names(Maindata$Comparisondata))
Maindata$Comparisonsumdata <- tmp
}
})
output$Comparisonshowcomparisonresults <- renderDataTable({
if (!is.null(Maindata$Comparisonsumdata)) {
if (input$Comparisononlyshowdifferentgene=="diffpattern") {
Maindata$Comparisonsumdata[apply(Maindata$Comparisonsumdata[,-1],1,function(x) length(unique(x))) > 1,]
} else if (input$Comparisononlyshowdifferentgene=="samepattern") {
Maindata$Comparisonsumdata[apply(Maindata$Comparisonsumdata[,-1],1,function(x) length(unique(x))) == 1,]
} else {
Maindata$Comparisonsumdata
}
}
})
})
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SEPA documentation built on May 6, 2019, 2:42 a.m.
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######################################################
## SEPA ##
## Interactive User Interface ##
## Server File ##
## Author:Zhicheng Ji, Hongkai Ji ##
## Maintainer:Zhicheng Ji (zji4@jhu.edu) ##
######################################################
library(shiny)
library(grid)
library(ggplot2)
library(topGO)
library(reshape2)
library(segmented)
options(shiny.maxRequestSize=30000*1024^2)
shinyServer(function(input, output,session) {
output$showbusybar <- renderUI({
tagList(
tags$head(
tags$link(rel="stylesheet", type="text/css",href="style.css"),
tags$script(type="text/javascript", src = "busy.js")
),
div(class = "busy",
p("Calculation in progress.."),
img(src="ajaxloaderq.gif")
)
)
})
Maindata <- reactiveValues()
### Readexp ###
observe({
if (input$Readexpreadin > 0)
isolate({
FileHandle <- input$ReadexpFile
if (!is.null(FileHandle)) {
tmpdata <- read.table(FileHandle$datapath,header=T,sep=input$Readexpsep,as.is=T,blank.lines.skip=TRUE)
Maindata$rawexpr <- as.matrix(tmpdata[,-1])
row.names(Maindata$rawexpr) <- make.names(tmpdata[,1])
}
})
})
output$Readexpraddsymbolui <- renderUI({
if (input$Readexprchooseanno!="symbol")
checkboxInput("Readexpraddsymbol","Add gene symbol to row names",value=F)
})
observe({
if (!is.null(Maindata$rawexpr)) {
tmp <- Maindata$rawexpr
if (input$Readexpraddsymbol) {
if (input$Readexprchoosespecies == "Human") {
x <- org.Hs.egSYMBOL
mapped_genes <- mappedkeys(x)
eg2symbol <- unlist(as.list(x[mapped_genes]))
if (input$Readexprchooseanno == "entrez") {
row.names(tmp) <- paste0(eg2symbol[row.names(tmp)],"_",row.names(tmp))
} else if (input$Readexprchooseanno == "ensembl") {
xx <- sapply(as.list(org.Hs.egENSEMBL2EG),function(i) i[1])
ensembl2symbol <- eg2symbol[xx]
names(ensembl2symbol) <- names(xx)
tmprowname <- sapply(row.names(tmp),function(i) strsplit(i,"\\.")[[1]][1])
row.names(tmp) <- paste0(ensembl2symbol[tmprowname],"_",row.names(tmp))
} else if (input$Readexprchooseanno == "unigene") {
x <- org.Hs.egUNIGENE2EG
mapped_genes <- mappedkeys(x)
unigene2eg <- sapply(as.list(x[mapped_genes]),function(i) i[1])
unigene2symbol <- eg2symbol[unigene2eg]
names(unigene2symbol) <- names(unigene2eg)
row.names(tmp) <- paste0(unigene2symbol[row.names(tmp)],"_",row.names(tmp))
}
} else if (input$Readexprchoosespecies == "Mouse") {
x <- org.Mm.egSYMBOL
mapped_genes <- mappedkeys(x)
eg2symbol <- unlist(as.list(x[mapped_genes]))
if (input$Readexprchooseanno == "entrez") {
row.names(tmp) <- paste0(eg2symbol[row.names(tmp)],"_",row.names(tmp))
} else if (input$Readexprchooseanno == "ensembl") {
xx <- sapply(as.list(org.Mm.egENSEMBL2EG),function(i) i[1])
ensembl2symbol <- eg2symbol[xx]
names(ensembl2symbol) <- names(xx)
tmprowname <- sapply(row.names(tmp),function(i) strsplit(i,"\\.")[[1]][1])
row.names(tmp) <- paste0(ensembl2symbol[tmprowname],"_",row.names(tmp))
} else if (input$Readexprchooseanno == "unigene") {
x <- org.Mm.egUNIGENE2EG
mapped_genes <- mappedkeys(x)
unigene2eg <- sapply(as.list(x[mapped_genes]),function(i) i[1])
unigene2symbol <- eg2symbol[unigene2eg]
names(unigene2symbol) <- names(unigene2eg)
row.names(tmp) <- paste0(unigene2symbol[row.names(tmp)],"_",row.names(tmp))
}
}
}
Maindata$nametransexpr <- tmp
}
})
observe({
if (!is.null(Maindata$nametransexpr)) {
tmp <- Maindata$nametransexpr[,!colnames(Maindata$nametransexpr) %in% input$Readexpcell]
if (input$Readexplogtf) {
if (input$Readexplogbase == "2") {
tmp <- log2(tmp+as.numeric(input$Readexplogpseudocount))
} else if (input$Readexplogbase == "10") {
tmp <- log10(tmp+as.numeric(input$Readexplogpseudocount))
} else if (input$Readexplogbase == "e") {
tmp <- log(tmp+as.numeric(input$Readexplogpseudocount))
}
}
tmp <- tmp[rowSums(tmp) > 0,]
tmp <- tmp[rowSums(tmp > as.numeric(input$Readexpgeneexpcutoff)) > ncol(tmp)*as.numeric(input$Readexpgenepercentcutoff)/100,]
tmp <- tmp[apply(tmp,1,sd)/rowMeans(tmp) > as.numeric(input$Readexpgenecvcutoff),]
Maindata$expr <- tmp
}
})
observe({
if (input$Readexprchoosespecies=="Human") {
library(org.Hs.eg.db)
mapdb <- "org.Hs.eg.db"
} else {
library(org.Mm.eg.db)
mapdb <- "org.Mm.eg.db"
}
xx <- unique(unlist(annFUN.org("BP", mapping = mapdb, ID = input$Readexprchooseanno)))
genename <- row.names(Maindata$rawexpr)
if (input$Readexprchooseanno == "ensembl") {
genename <- sapply(genename,function(i) strsplit(i,"\\.")[[1]][1])
}
Maindata$genenumwithid <- length(intersect(xx,genename))
})
output$Readexpcellui <- renderUI(
selectizeInput("Readexpcell","Select cells to be removed",colnames(Maindata$rawexpr),multiple = TRUE),
)
output$Readexpshowrawtable <- renderTable(head(Maindata$expr))
output$Readexpshowsummaryui <- renderUI({
if (!is.null(Maindata$expr)) {
tagList(
h4("Summary of the gene expression profile:"),
h5(paste("The filtered dataset contains",nrow(Maindata$expr),"genes and",ncol(Maindata$expr),"cells")),
h5(paste(Maindata$genenumwithid,"genes have corresponding GO terms.")),
hr(),
h4("Head of the input file:"),
tableOutput("Readexpshowrawtable")
)
}
})
### Truetime ###
observe({
if (input$Truetimereadin > 0)
isolate({
FileHandle <- input$TruetimeFile
if (!is.null(FileHandle)) {
tmp <- read.table(FileHandle$datapath,header=T,sep=input$Truetimesep,as.is=T,blank.lines.skip=TRUE)
commoncell <- intersect(tmp[,1],colnames(Maindata$expr))
Maindata$Truetimedata <- tmp[tmp[,1] %in% commoncell,]
Maindata$Truetimeexpr <- Maindata$expr[,commoncell]
}
})
})
output$Truetimeshowtime <- renderDataTable({
Maindata$Truetimedata
})
observe({
if (!is.null(Maindata$Truetimeexpr) && !is.null(Maindata$Truetimedata) && input$Truetimerunanalysis > 0)
isolate({
tmptime <- Maindata$Truetimedata[,2]
names(tmptime) <- Maindata$Truetimedata[,1]
truetime <- factor(tmptime)
tmppattern <- rep("tmp",nrow(Maindata$Truetimeexpr))
withProgress(message = 'Calculation in Progress...', {
for (i in 1:nrow(Maindata$Truetimeexpr)) {
e <- Maindata$Truetimeexpr[i,]
ttestpval <- sapply(1:(length(levels(truetime))-1), function(i) {
sign(mean(e[truetime==levels(truetime)[i]])-mean(e[truetime==levels(truetime)[i+1]]))*t.test(e[truetime==levels(truetime)[i]],e[truetime==levels(truetime)[i+1]])$p.value
})
ttestpval <- sign(ttestpval) * p.adjust(abs(ttestpval),method="fdr")
pattern <- rep("constant",length(levels(truetime))-1)
pattern[abs(ttestpval) < as.numeric(input$Truetimepvalcutoff) & ttestpval < 0] <- "up"
pattern[abs(ttestpval) < as.numeric(input$Truetimepvalcutoff) & ttestpval > 0] <- "down"
pattern <- paste(pattern,collapse = "_")
tmppattern[i] <- pattern
incProgress(1/nrow(Maindata$Truetimeexpr), detail = paste("Calculating Pattern for Gene", i))
}
})
names(tmppattern) <- row.names(Maindata$Truetimeexpr)
Maindata$Truetimeoripattern <- tmppattern
})
})
observe({
if (!is.null(Maindata$Truetimeoripattern)) {
if (!input$Truetimeignoreconst && !input$Truetimesimplify) {
Maindata$Truetimepattern <- Maindata$Truetimeoripattern
} else {
Maindata$Truetimepattern <- sapply(Maindata$Truetimeoripattern, function(pattern) {
pattern <- strsplit(pattern,"_")[[1]]
if (input$Truetimeignoreconst)
pattern <- pattern[pattern!="constant"]
if (input$Truetimesimplify)
pattern <- rle(pattern)$values
paste(pattern,collapse = "_")
})
}
Maindata$Truetimenoconstantname <- names(Maindata$Truetimepattern)[grepl("up",Maindata$Truetimepattern) | grepl("down",Maindata$Truetimepattern)]
}
})
output$Truetimepatternsummary <- renderDataTable({
if (!is.null(Maindata$Truetimepattern)) {
tmp <- data.frame(table(Maindata$Truetimepattern))
colnames(tmp) <- c("Pattern","Number")
tmp <- tmp[tmp$Pattern!="",]
tmp
}
})
output$Truetimepatternsummarysave <- downloadHandler(
filename = function() { "Pattern Summary.csv" },
content = function(file) {
tmp <- data.frame(table(Maindata$Truetimepattern))
colnames(tmp) <- c("Pattern","Number")
tmp <- tmp[tmp$Pattern!="",]
write.csv(tmp,file=file,quote=F,row.names=F)
}
)
output$TruetimepatternsummaryGeneselectui <- renderUI({
if (!is.null(Maindata$Truetimepattern))
tagList(
checkboxInput("TruetimepatternsummaryGeneselectlistall","List Genes for all Pattern",value=T),
conditionalPanel(condition = "input.TruetimepatternsummaryGeneselectlistall==0",
selectInput("TruetimepatternsummaryGeneselect","Select Pattern",sort(unique(Maindata$Truetimepattern)),multiple = T)
)
)
})
output$TruetimepatternsummaryGene <- renderDataTable({
if (!is.null(input$TruetimepatternsummaryGeneselectlistall)) {
if (input$TruetimepatternsummaryGeneselectlistall) {
tmp <- Maindata$Truetimepattern
} else {
tmp <- Maindata$Truetimepattern[Maindata$Truetimepattern %in% input$TruetimepatternsummaryGeneselect]
}
data.frame(Gene=names(tmp),Pattern=tmp)
}
})
output$TruetimepatternsummaryGenesave <- downloadHandler(
filename = function() { "Gene List.csv" },
content = function(file) {
if (input$TruetimepatternsummaryGeneselectlistall) {
tmp <- Maindata$Truetimepattern
} else {
tmp <- Maindata$Truetimepattern[Maindata$Truetimepattern %in% input$TruetimepatternsummaryGeneselect]
}
tmp <- data.frame(Gene=names(tmp),Pattern=tmp)
write.csv(tmp,file=file,quote=F,row.names=F)
}
)
output$Truetimeselectgeneui <- renderUI(
selectizeInput("Truetimeselectgene","Select genes of interest",Maindata$Truetimenoconstantname,multiple = TRUE)
)
output$Truetimevisualize <- renderPlot({
if (!is.null(Maindata$Truetimedata) && !is.null(input$Truetimeselectgene)) {
tmptime <- Maindata$Truetimedata[,2]
names(tmptime) <- Maindata$Truetimedata[,1]
truetime <- factor(tmptime)
tmp <- data.frame(time=rep(levels(truetime),length(input$Truetimeselectgene)),expmean=0,Gene=rep(input$Truetimeselectgene,each=length(levels(truetime))))
tmp$expmean <- as.vector(sapply(input$Truetimeselectgene, function(gene) {
e <- Maindata$Truetimeexpr[gene,Maindata$Truetimedata[,1]]
sapply(1:length(levels(truetime)), function(i) {
mean(e[truetime==levels(truetime)[i]])
})
}))
ggplot(data = tmp, aes(x=time, y=expmean, colour=Gene)) +
geom_line(aes(group=Gene)) +
geom_point(size=4) +
xlab("Experiment Time") +
ylab("Expression Values") +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(size=17,color='black'),
axis.text.y = element_text(size=17,color='black'),
axis.title.x = element_text(size=20,vjust=-1),
axis.title.y = element_text(size=20,vjust=1),
strip.text.y = element_text(size=17,color='black'),
legend.text = element_text(size=15),
legend.title = element_text(size=15),
legend.position = "right"
)
}
})
output$Truetimevisualizesave <- downloadHandler(
filename = function() { "Pattern.pdf" },
content = function(file) {
if (!is.null(Maindata$Truetimedata) && !is.null(input$Truetimeselectgene)) {
pdf(file,width=14,height=7)
tmptime <- Maindata$Truetimedata[,2]
names(tmptime) <- Maindata$Truetimedata[,1]
truetime <- factor(tmptime)
tmp <- data.frame(time=rep(levels(truetime),length(input$Truetimeselectgene)),expmean=0,Gene=rep(input$Truetimeselectgene,each=length(levels(truetime))))
tmp$expmean <- as.vector(sapply(input$Truetimeselectgene, function(gene) {
e <- Maindata$Truetimeexpr[gene,Maindata$Truetimedata[,1]]
sapply(1:length(levels(truetime)), function(i) {
mean(e[truetime==levels(truetime)[i]])
})
}))
tmp <- ggplot(data = tmp, aes(x=time, y=expmean, colour=Gene)) +
geom_line(aes(group=Gene)) +
geom_point(size=4) +
xlab("Experiment Time") +
ylab("Expression Values") +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(size=17,color='black'),
axis.text.y = element_text(size=17,color='black'),
axis.title.x = element_text(size=20,vjust=-1),
axis.title.y = element_text(size=20,vjust=1),
strip.text.y = element_text(size=17,color='black'),
legend.text = element_text(size=15),
legend.title = element_text(size=15),
legend.position = "right"
)
print(tmp)
dev.off()
}
}
)
output$Truetimevisualizetable <- renderDataTable({
if (!is.null(input$Truetimeselectgene)) {
data.frame(Gene=input$Truetimeselectgene,Pattern=Maindata$Truetimepattern[input$Truetimeselectgene])
}
})
output$Truetimevisualizetablesave <- downloadHandler(
filename = function() { "Gene Pattern.csv" },
content = function(file) {
tmp <- data.frame(Gene=input$Truetimeselectgene,Pattern=Maindata$Truetimepattern[input$Truetimeselectgene])
write.csv(tmp,file=file,quote=F,row.names=F)
}
)
output$TruetimeGOanalysisselectui <- renderUI({
if (!is.null(Maindata$Truetimepattern))
selectInput("TruetimeGOanalysisselect","Select pattern of interest",sort(unique(Maindata$Truetimepattern)),multiple = T)
})
observe({
if (input$TruetimeGOanalysisrunbutton > 0) {
isolate({
if (!is.null(input$TruetimeGOanalysisselect) && Maindata$genenumwithid > 0) {
withProgress(message = 'Performing GO analysis...', {
if (input$Readexprchoosespecies=="Human") {
mapdb <- "org.Hs.eg.db"
} else {
mapdb <- "org.Mm.eg.db"
}
allgene <- row.names(Maindata$rawexpr)
if (input$Readexprchooseanno == "ensembl") {
allgene <- sapply(allgene,function(i) strsplit(i,"\\.")[[1]][1])
}
inputgene <- allgene[Maindata$Truetimepattern %in% input$TruetimeGOanalysisselect]
geneList <- factor(as.integer(allgene %in% inputgene))
names(geneList) <- allgene
Maindata$TruetimeGOdata <- new("topGOdata", ontology = "BP", allGenes = geneList,geneSel=function(a) {a},annot = annFUN.org, mapping = mapdb, ID = input$Readexprchooseanno)
Maindata$TruetimeGOresultFisher <- runTest(Maindata$TruetimeGOdata, algorithm = "classic", statistic = "fisher")
})
}
})
}
})
output$TruetimeGOanalysisresult <- renderDataTable({
if (!is.null(Maindata$TruetimeGOresultFisher)) {
tmp <- GenTable(Maindata$TruetimeGOdata, classicFisher = Maindata$TruetimeGOresultFisher, topNodes = as.numeric(input$TruetimeGOanalysistermnum),orderBy="classicFisher")
tmp
}
})
output$TruetimeGOanalysisresultsave <- downloadHandler(
filename = function() { "GO Analysis.csv" },
content = function(file) {
if (!is.null(Maindata$TruetimeGOresultFisher)) {
tmp <- GenTable(Maindata$TruetimeGOdata, classicFisher = Maindata$TruetimeGOresultFisher, topNodes = as.numeric(input$TruetimeGOanalysistermnum),orderBy="classicFisher")
tmp$Term <- gsub(","," ",tmp$Term)
write.csv(tmp,file=file,quote=F,row.names=F)
}
}
)
### Pseudotime ###
observe({
if (input$Pseudotimereadin > 0)
isolate({
FileHandle <- input$PseudotimeFile
if (!is.null(FileHandle)) {
tmp <- read.table(FileHandle$datapath,header=T,sep=input$Pseudotimesep,as.is=T,blank.lines.skip=TRUE)
pseudotime <- tmp[,2]
names(pseudotime) <- tmp[,1]
commoncell <- intersect(tmp[,1],colnames(Maindata$expr))
Maindata$Pseudotimedata <- pseudotime[commoncell]
Maindata$Pseudotimeexpr <- Maindata$expr[,commoncell]
}
})
})
output$Pseudotimeshowtime <- renderDataTable({
data.frame(Cell=names(Maindata$Pseudotimedata),Time=Maindata$Pseudotimedata)
})
observe({
if (!is.null(Maindata$Pseudotimeexpr) && !is.null(Maindata$Pseudotimedata) && input$Pseudotimerunanalysis > 0)
isolate({
pseudotime <- Maindata$Pseudotimedata
expr <- Maindata$Pseudotimeexpr
gap <- as.numeric(input$Pseudotimegapvalue)
fastRSS <- function(X, y) {
XtX <- crossprod(X)
ch <- chol(XtX)
V <- chol2inv(ch)
sum(drop(X %*% V %*% crossprod(X, y)-y)^2)
}
x <- pseudotime
breakpoint <- rowMeans(cbind(pseudotime[-1],pseudotime[-length(pseudotime)]))
breakpoint <- breakpoint[gap:(length(breakpoint)-gap+1)]
spmat <- t(sapply(breakpoint,function(i) {
ifelse(x > i,x - i,0)
}))
# genes that are constantly zero
expr <- expr[,names(pseudotime)]
zerogene <- row.names(expr)[rowSums(expr) == 0]
fitexpr <- expr <- expr[rowSums(expr) > 0,]
# use davies test to identify whether there is a transition point
withProgress(message = 'Determining existence of transition points...', {
daviespval <- apply(expr,1,function(y) {
tmpy <- y[(gap+1):(length(y)-gap)]
tmpx <-x[(gap+1):(length(y)-gap)]
if (sum(tmpy) > 0) {
fit <- lm(tmpy~tmpx)
davies.test(fit,~tmpx)$p.value
} else {
1
}
})
})
daviespval[is.na(daviespval)] <- 1
daviespval <- p.adjust(daviespval,method="fdr")
notransgene <- names(daviespval)[daviespval >= 0.05]
transgene <- names(daviespval)[daviespval < 0.05]
withProgress(message = 'Predicting starting positions...', {
transpos <- sapply(transgene,function(gene) {
y <- expr[gene,]
RSS1 <- sapply(1:length(breakpoint),function(i) {
fastRSS(cbind(1,x,spmat[i,]),y)
})
which.min(RSS1)
})
})
pattern <- data.frame(pattern=rep("constant",length(transgene)),transpoint=rep(0,length(transgene)),LCI=rep(0,length(transgene)),UCI=rep(0,length(transgene)),stringsAsFactors = F)
row.names(pattern) <- transgene
withProgress(message = 'Calculating transition points...', {
for (i in 1:length(transgene)) {
set.seed(1234)
y <- expr[transgene[i],]
fit <- lm(y~x)
o.seg1 <- tryCatch(segmented(fit,seg.Z=~x,psi=breakpoint[transpos[i]]),error=function(e) {})
if (is.null(o.seg1)) {
suppressWarnings(o.seg1 <- segmented(fit,seg.Z=~x,psi=breakpoint[transpos[i]],control = seg.control(n.boot=0,it.max=1)))
}
if (o.seg1$psi[2] <= x[gap] || o.seg1$psi[2] >= x[length(x)-gap+1]) {
notransgene <- c(notransgene,transgene[i])
} else {
slopecol <- rep("constant",2)
for (j in 1:2) {
if (slope(o.seg1)$x[j,4] * slope(o.seg1)$x[j,5] > 0) {
if (slope(o.seg1)$x[j,4] > 0) {
slopecol[j] <- "up"
} else {
slopecol[j] <- "down"
}
}
}
if ((input$Pseudotimesimplify && slopecol[1] == slopecol[2]) || (input$Pseudotimeignoreconst && (slopecol[1]=="constant" || slopecol[2]=="constant"))) {
notransgene <- c(notransgene,transgene[i])
} else {
pattern[i,1] <- paste0(slopecol,collapse = "_")
pattern[i,2] <- confint(o.seg1)$x[1]
pattern[i,3] <- confint(o.seg1)$x[2]
pattern[i,4] <- confint(o.seg1)$x[3]
fitexpr[transgene[i],] <- fitted(o.seg1)
}
}
incProgress(1/length(transgene), detail = paste("Calculating transition point for gene", i))
}
})
pattern <- pattern[pattern[,1]!="constant",]
pattern <- pattern[order(pattern$pattern,pattern$transpoint),]
tmp <- pattern[,1]
pattern <- pattern[,-1]
pattern <- split(pattern,tmp)
notranspval <- sapply(notransgene,function(i) {
set.seed(1234)
y <- expr[i,]
fit <- lm(y~x)
fitexpr[i,] <<- fitted(fit)
sign(summary(fit)[[4]][2,1])*summary(fit)[[4]][2,4]
})
notranspval <- sign(notranspval) * p.adjust(abs(notranspval),method = "fdr")
upgene <- notranspval[notranspval > 0 & abs(notranspval) < 0.05]
downgene <- notranspval[notranspval < 0 & abs(notranspval) < 0.05]
constantgene <- notranspval[abs(notranspval) >= 0.05]
pattern$up <- sort(upgene)
pattern$down <- sort(abs(downgene))
if (!input$Pseudotimeignoreconst)
pattern$constant <- sort(abs(constantgene))
Maindata$Pseudotimefitexpr <- fitexpr
Maindata$Pseudotimepattern <- pattern
tmp <- NULL
for (name in names(Maindata$Pseudotimepattern)) {
if (typeof(Maindata$Pseudotimepattern[[name]]) == "list") {
tmppattern <- rep(name,length(row.names(Maindata$Pseudotimepattern[[name]])))
names(tmppattern) <- row.names(Maindata$Pseudotimepattern[[name]])
tmp <- c(tmp,tmppattern)
} else {
tmppattern <- rep(name,length(names(Maindata$Pseudotimepattern[[name]])))
names(tmppattern) <- names(Maindata$Pseudotimepattern[[name]])
tmp <- c(tmp,tmppattern)
}
}
Maindata$Pseudotimepatternsimple <- tmp
})
})
output$Pseudotimepatternsummary <- renderDataTable({
if (!is.null(Maindata$Pseudotimepatternsimple)) {
tmp <- data.frame(table(Maindata$Pseudotimepatternsimple))
colnames(tmp) <- c("Pattern","Number")
tmp
}
})
output$Pseudotimepatternsummarysave <- downloadHandler(
filename = function() { "Pattern Summary.csv" },
content = function(file) {
if (!is.null(Maindata$Pseudotimepatternsimple)) {
tmp <- data.frame(table(Maindata$Pseudotimepatternsimple))
colnames(tmp) <- c("Pattern","Number")
write.csv(tmp,file=file,quote=F,row.names=F)
}
}
)
output$PseudotimepatternsummaryGeneselectui <- renderUI(
if (!is.null(Maindata$Pseudotimepattern))
tagList(
checkboxInput("PseudotimepatternsummaryGeneselectlistall","List Genes for all Pattern",value=T),
conditionalPanel(condition = "input.PseudotimepatternsummaryGeneselectlistall==0",
selectInput("PseudotimepatternsummaryGeneselect","Select Pattern",names(Maindata$Pseudotimepattern),multiple = T)
)
)
)
output$PseudotimepatternsummaryGene <- renderDataTable({
if (!is.null(input$PseudotimepatternsummaryGeneselectlistall)) {
if (input$PseudotimepatternsummaryGeneselectlistall) {
tmp <- Maindata$Pseudotimepatternsimple
data.frame(Gene=names(tmp),Pattern=tmp)
} else if (sum(!grepl("_",input$PseudotimepatternsummaryGeneselect)) > 0) {
tmp <- Maindata$Pseudotimepatternsimple[Maindata$Pseudotimepatternsimple %in% input$PseudotimepatternsummaryGeneselect]
data.frame(Gene=names(tmp),Pattern=tmp)
} else {
allres <- NULL
for (i in input$PseudotimepatternsummaryGeneselect) {
tmp <- cbind(row.names(Maindata$Pseudotimepattern[[i]]),i,Maindata$Pseudotimepattern[[i]])
colnames(tmp) <- c("Gene","Pattern","Transition","LCI","UCI")
allres <- rbind(allres,tmp)
}
allres
}
}
})
output$PseudotimepatternsummaryGenesave <- downloadHandler(
filename = function() { "Gene List.csv" },
content = function(file) {
if (input$PseudotimepatternsummaryGeneselectlistall) {
tmp <- Maindata$Pseudotimepatternsimple
tmp <- data.frame(Gene=names(tmp),Pattern=tmp)
} else if (sum(!grepl("_",input$PseudotimepatternsummaryGeneselect)) > 0) {
tmp <- Maindata$Pseudotimepatternsimple[Maindata$Pseudotimepatternsimple %in% input$PseudotimepatternsummaryGeneselect]
tmp <- data.frame(Gene=names(tmp),Pattern=tmp)
} else {
allres <- NULL
for (i in input$PseudotimepatternsummaryGeneselect) {
tmp <- cbind(row.names(Maindata$Pseudotimepattern[[i]]),i,Maindata$Pseudotimepattern[[i]])
colnames(tmp) <- c("Gene","Pattern","Transition","LCI","UCI")
allres <- rbind(allres,tmp)
}
tmp <- allres
}
write.csv(tmp,file=file,quote=F,row.names=F)
}
)
observe({
tmp <- Maindata$Pseudotimepatternsimple
Maindata$Pseudotimenoconstantname <- names(tmp)[grepl("up",tmp) | grepl("down",tmp)]
})
output$Pseudotimeselectgeneui <- renderUI(
selectizeInput("Pseudotimeselectgene","Select genes of interest",Maindata$Pseudotimenoconstantname,multiple = TRUE)
)
Pseudotimeplotfunc <- function(pattern,expr,fitexpr,pseudotime,gap,gene,showtrue=F) {
findgene <- function(gene) {
findres <- sapply(names(pattern), function(pat) {
if (grepl("_",pat)) {
gene %in% row.names(pattern[[pat]])
} else {
gene %in% names(pattern[[pat]])
}
})
names(which(findres))
}
genename <- gene
x <- sort(pseudotime)
gene <- sapply(gene, findgene)
if (length(gene) == 1) {
if (grepl("_",gene)) {
transinfo <- pattern[[gene]][names(gene),]
transmean <- transinfo[1,1]
} else {
transinfo <- pattern[[gene]][names(gene)]
}
y <- expr[names(gene),names(x)]
fity <- fitexpr[names(gene),names(x)]
p <- qplot(x,y,data=data.frame(x=x,y=y),size=3)
gene <- gsub("constant","black",gene)
gene <- gsub("up","green",gene)
gene <- gsub("down","red",gene)
gene <- strsplit(gene,"_")[[1]]
if (length(gene)==1) {
p <- p + geom_line(aes(x=x,y=y),data=data.frame(x=x,y=fity),col=gene,size=2)
} else {
transpointy <- (fity[2]-fity[1])/(x[2]-x[1])*(transmean-x[1])+fity[1]
p <- p + geom_line(aes(x=x,y=y),data=data.frame(x=c(x[x<transmean],transmean),y=c(fity[x<transmean],transpointy)),col=gene[1],size=2)
p <- p + geom_line(aes(x=x,y=y),data=data.frame(x=c(transmean,x[x>transmean]),y=c(transpointy,fity[x>transmean])),col=gene[2],size=2)
ypos <- ifelse(max(y) > 0, 1.1 * max(y), 0.9 * max(y))
p <- p + geom_point(aes(x=transmean,y=ypos),col="blue",size=5) + geom_segment(aes(x=transinfo[1,2],xend=transinfo[1,3],y=ypos,yend=ypos),col="blue",size=2)
}
p + xlab("Pseudo-time") +
ylab("Gene Expression") +
ggtitle(genename) +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(size=17,color='black'),
axis.text.y = element_text(size=17,color='black'),
axis.title.x = element_text(size=20),
axis.title.y = element_text(size=20),
strip.text.y = element_text(size=17,color='black'),
plot.title = element_text(size = 25),
legend.position = "none")
} else {
if (!showtrue) {
geneexpr <- fitexpr[names(gene),names(x)]
} else {
geneexpr <- expr[names(gene),names(x)]
}
colnames(geneexpr) <- NULL
geneexpr <- geneexpr[rev(row.names(geneexpr)),]
linesegmat <- NULL
for (g in 1:length(gene)) {
if (grepl("_",gene[g])) {
tmp <- unlist(pattern[[gene[g]]][names(gene[g]),])
tmp <- sapply(tmp,function(j) which.min(abs(j-x)))
linesegmat <- rbind(linesegmat,c(tmp,g))
}
}
linesegmat[,4] <- length(gene) + 1 - linesegmat[,4]
geneexpr <- t(apply(geneexpr,1,scale))
geneexpr <- melt(geneexpr)
p <- ggplot(data=geneexpr, aes(x=Var2, y=Var1)) + geom_tile(aes(fill = value)) + scale_fill_gradient2(low = "blue",high = "red",mid="white") +
geom_segment(aes(x=x,xend=xend,y=y,yend=yend),data=data.frame(x=linesegmat[,2],xend=linesegmat[,3],y=linesegmat[,4],yend=linesegmat[,4])) +
geom_point(aes(x=x,y=y),data=data.frame(x=linesegmat[,1],y=linesegmat[,4]))
p + xlab("Cell") +
ylab("Predicted Expression") +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(size=17,color='black'),
axis.text.y = element_text(size=17,color='black'),
axis.title.x = element_text(size=20,vjust=-1),
axis.title.y = element_text(size=20,vjust=1),
strip.text.y = element_text(size=17,color='black'),
legend.text = element_text(size=15),
legend.title = element_text(size=15),
legend.position = "right"
)
}
}
output$Pseudotimevisualize <- renderPlot({
if (!is.null(Maindata$Pseudotimedata) && !is.null(input$Pseudotimeselectgene)) {
pseudotime <- Maindata$Pseudotimedata
Pseudotimeplotfunc(Maindata$Pseudotimepattern,Maindata$Pseudotimeexpr,Maindata$Pseudotimefitexpr,pseudotime,as.numeric(input$Pseudotimegapvalue),input$Pseudotimeselectgene,showtrue=input$Pseudotimegeneexpressionshowtrue)
}
})
output$Pseudotimevisualizeui <- renderUI({
plotOutput("Pseudotimevisualize",width=700,height=ifelse(length(input$Pseudotimeselectgene)==1,700,400))
})
output$Pseudotimevisualizesave <- downloadHandler(
filename = function() { "Pattern.pdf" },
content = function(file) {
if (!is.null(Maindata$Pseudotimedata) && !is.null(input$Pseudotimeselectgene)) {
pdf(file)
pseudotime <- Maindata$Pseudotimedata
Pseudotimeplotfunc(Maindata$Pseudotimepattern,Maindata$Pseudotimeexpr,Maindata$Pseudotimefitexpr,pseudotime,as.numeric(input$Pseudotimegapvalue),input$Pseudotimeselectgene,showtrue=F)
dev.off()
}
}
)
output$Pseudotimevisualizetable <- renderDataTable({
if (!is.null(input$Pseudotimeselectgene)) {
data.frame(Gene=input$Pseudotimeselectgene,Pattern=Maindata$Pseudotimepatternsimple[input$Pseudotimeselectgene])
}
})
output$Pseudotimevisualizetablesave <- downloadHandler(
filename = function() { "Gene Pattern.csv" },
content = function(file) {
tmp <- data.frame(Gene=input$Pseudotimeselectgene,Pattern=Maindata$Pseudotimepatternsimple[input$Pseudotimeselectgene])
write.csv(tmp,file=file,quote=F,row.names=F)
}
)
output$PseudotimeGOanalysisselectui <- renderUI({
if (!is.null(Maindata$Pseudotimepatternsimple))
selectInput("PseudotimeGOanalysisselect","Select pattern of interest",sort(unique(Maindata$Pseudotimepatternsimple)),multiple = T)
})
observe({
if (input$PseudotimeGOanalysisrunbutton > 0) {
isolate({
if (!is.null(input$PseudotimeGOanalysisselect) && Maindata$genenumwithid > 0) {
withProgress(message = 'Performing GO analysis...', value = 0, {
if (input$Readexprchoosespecies=="Human") {
mapdb <- "org.Hs.eg.db"
} else {
mapdb <- "org.Mm.eg.db"
}
allgene <- row.names(Maindata$rawexpr)
if (input$Readexprchooseanno == "ensembl") {
allgene <- sapply(allgene,function(i) strsplit(i,"\\.")[[1]][1])
}
inputgene <- allgene[Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisselect]
geneList <- factor(as.integer(allgene %in% inputgene))
names(geneList) <- allgene
Maindata$PseudotimeGOdata <- new("topGOdata", ontology = "BP", allGenes = geneList,geneSel=function(a) {a},annot = annFUN.org, mapping = mapdb, ID = input$Readexprchooseanno)
Maindata$PseudotimeGOresultFisher <- runTest(Maindata$PseudotimeGOdata, algorithm = "classic", statistic = "fisher")
})
}
})
}
})
output$PseudotimeGOanalysisresult <- renderDataTable({
if (!is.null(Maindata$PseudotimeGOresultFisher)) {
tmp <- GenTable(Maindata$PseudotimeGOdata, classicFisher = Maindata$PseudotimeGOresultFisher, topNodes = as.numeric(input$PseudotimeGOanalysistermnum),orderBy="classicFisher")
tmp
}
})
output$PseudotimeGOanalysisresultsave <- downloadHandler(
filename = function() { "GO Analysis.csv" },
content = function(file) {
if (!is.null(Maindata$PseudotimeGOresultFisher)) {
tmp <- GenTable(Maindata$PseudotimeGOdata, classicFisher = Maindata$PseudotimeGOresultFisher, topNodes = as.numeric(input$PseudotimeGOanalysistermnum),orderBy="classicFisher")
tmp$Term <- gsub(","," ",tmp$Term)
write.csv(tmp,file=file,quote=F,row.names=F)
}
}
)
output$PseudotimeGOanalysisTimeselectui <- renderUI({
if (!is.null(Maindata$Pseudotimepatternsimple)) {
tmp <- sort(unique(Maindata$Pseudotimepatternsimple))
tmp <- tmp[grep("_",tmp)]
if (length(tmp) == 0) {
strong("There is no pattern with transition point!")
} else {
selectInput("PseudotimeGOanalysisTimeselect","Select pattern of interest",tmp,multiple = T)
}
}
})
output$PseudotimeGOanalysisTimewinsizesliderui <- renderUI({
if (!is.null(input$PseudotimeGOanalysisTimeselect)) {
tagList(
helpText("Select window size (how many genes to be included in each GO analsysis). Notice that the results of GO analyses are not robust if too few genes and included."),
sliderInput("PseudotimeGOanalysisTimewinsizeslider","Select window size",min=1,max=sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect),step=1,value=ifelse(sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect) > 50,50,ceiling(sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect)/2)))
)
}
})
output$PseudotimeGOanalysisTimestepsliderui <- renderUI({
if (!is.null(input$PseudotimeGOanalysisTimewinsizeslider))
sliderInput("PseudotimeGOanalysisTimestepslider","Select moving step",min=1,max=sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect)-1,step=1,value=ifelse(sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect)-1 > 25,25,ceiling((sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect)-1)/2)))
})
observe({
if (input$PseudotimeGOanalysisTimerunbutton > 0) {
isolate({
if (!is.null(input$PseudotimeGOanalysisTimeselect) && Maindata$genenumwithid > 0) {
GOanalysis <- function(inputgene,allgene,identifier="ENSEMBL",species="Human") {
if (species == "Human") {
mapdb <- "org.Hs.eg.db"
} else if (species == "Mouse") {
mapdb <- "org.Mm.eg.db"
}
geneList <- factor(as.integer(allgene %in% inputgene))
names(geneList) <- allgene
GOdata <- new("topGOdata", ontology = "BP", allGenes = geneList,geneSel=function(a) {a},annot = annFUN.org, mapping = mapdb, ID = identifier)
resultFisher <- runTest(GOdata, algorithm = "classic", statistic = "fisher")
list(resultFisher=resultFisher,GOdata=GOdata)
}
allres <- NULL
for (i in input$PseudotimeGOanalysisTimeselect) {
tmp <- data.frame(row.names(Maindata$Pseudotimepattern[[i]]),i,Maindata$Pseudotimepattern[[i]],stringsAsFactors = F)
colnames(tmp) <- c("Gene","Pattern","Transition","LCI","UCI")
allres <- rbind(allres,tmp)
}
genelist <- allres[order(allres$Transition),1]
if (input$Readexprchooseanno!="symbol" && input$Readexpraddsymbol)
genelist <- sapply(genelist,function(i) strsplit(i,"_")[[1]][2])
allgene <- row.names(Maindata$rawexpr)
if (input$Readexprchooseanno == "ensembl") {
allgene <- sapply(allgene,function(i) strsplit(i,"\\.")[[1]][1])
genelist <- sapply(genelist,function(i) strsplit(i,"\\.")[[1]][1])
}
withProgress(message = 'Calculation in Progress...', value = 0, {
genenum <- sum(Maindata$Pseudotimepatternsimple %in% input$PseudotimeGOanalysisTimeselect)
windowsize <- as.numeric(input$PseudotimeGOanalysisTimewinsizeslider)
movesize <- as.numeric(input$PseudotimeGOanalysisTimestepslider)
maxwinnum <- ceiling((genenum-windowsize)/movesize) + 1
res <- list()
for (i in 1:maxwinnum) {
if (i==maxwinnum) {
startid <- genenum-windowsize+1
endid <- genenum
} else {
startid <- 1+movesize*(i-1)
endid <- movesize*(i-1)+windowsize
}
res[[paste0(startid,"-",endid)]] <- GOanalysis(genelist[startid:endid],allgene,identifier=input$Readexprchooseanno,species=input$Readexprchoosespecies)
incProgress(1/maxwinnum, detail = paste("Performing GO analysis for Window", i))
}
Maindata$PseudotimewindowGOres <- res
})
}
})
}
})
observe({
res <- list()
for (name in names(Maindata$PseudotimewindowGOres)) {
res[[name]] <- GenTable(Maindata$PseudotimewindowGOres[[name]][["GOdata"]], classicFisher = Maindata$PseudotimewindowGOres[[name]][["resultFisher"]], topNodes = as.numeric(input$PseudotimeGOanalysisTimetermnum),orderBy="classicFisher")
}
Maindata$PseudotimewindowGOtable <- res
})
output$PseudotimeGOanalysisTimeselectresultwindowui <- renderUI({
selectInput("PseudotimeGOanalysisTimeselectresultwindow","Select window",names(Maindata$PseudotimewindowGOtable))
})
output$PseudotimeGOanalysisTimeshowresultwindow <- renderDataTable({
if (!is.null(input$PseudotimeGOanalysisTimeselectresultwindow))
Maindata$PseudotimewindowGOtable[[input$PseudotimeGOanalysisTimeselectresultwindow]]
})
output$PseudotimeGOanalysisTimeshowresultwindowsave <- downloadHandler(
filename = function() { "GO Analysis.csv" },
content = function(file) {
if (!is.null(input$PseudotimeGOanalysisTimeselectresultwindow))
write.csv(Maindata$PseudotimewindowGOtable[[input$PseudotimeGOanalysisTimeselectresultwindow]],file=file,quote=F,row.names=F)
}
)
output$PseudotimeGOanalysisTimeselectresulttimetrendselectmethodui <- renderUI({
if (input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=='Specific') {
selectInput("PseudotimeGOanalysisTimeselectresulttimetrendspecific","Select GO term",unique(as.vector(sapply(Maindata$PseudotimewindowGOtable,function(i) i[,1]))),multiple = T)
} else {
sliderInput("PseudotimeGOanalysisTimeselectresulttimetrendtop","Select Number of Top GO Terms",1,as.numeric(input$PseudotimeGOanalysisTimetermnum),1,1)
}
})
output$PseudotimeGOanalysisTimeshowresulttimetrend <- renderPlot({
if (!is.null(Maindata$PseudotimewindowGOtable) && ((input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=="Specific" && !is.null(input$PseudotimeGOanalysisTimeselectresulttimetrendspecific)) || (input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=="Top" && !is.null(input$PseudotimeGOanalysisTimeselectresulttimetrendtop)))) {
GOres <- Maindata$PseudotimewindowGOtable
termnum <- as.numeric(input$PseudotimeGOanalysisTimetermnum)
if (input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=="Specific") {
GOterm <- input$PseudotimeGOanalysisTimeselectresulttimetrendspecific
} else {
GOterm <- unique(as.vector(sapply(GOres,function(i) i[1:as.numeric(input$PseudotimeGOanalysisTimeselectresulttimetrendtop),1])))
}
GOdes <- NULL
for (i in GOres) {
GOdes <- rbind(GOdes,as.matrix(i[,1:2]))
}
GOdes <- unique(GOdes)
rankres <- sapply(GOterm,function(term) {
sapply(GOres,function(i) {
tmp <- which(i[,1]==term)
if (length(tmp) == 0)
tmp <- termnum + 1
tmp
})
})
rankres <- melt(rankres,id="V1")
maxrank <- max(rankres$value)
if (maxrank < termnum + 1) {
tmpyset <- scale_y_reverse()
} else {
tickpos <- round(seq(0,maxrank,maxrank/5))
tickpos <- tickpos[tickpos < termnum + 1]
tmpyset <- scale_y_reverse(lim=c(termnum + 1,1),breaks=c(tickpos,(termnum+1)),labels=c(tickpos,paste(">",termnum)))
}
colnames(rankres)[2] <- "GOTerm"
rankres[,2] <- paste0(rankres[,2],"\n",sapply(rankres[,2], function(i) GOdes[GOdes[,1]==i,2]))
if (input$PseudotimeGOanalysisTimeselectresulttimetrendshowheatmap) {
p <- ggplot(data=rankres, aes(x=Var1, y=GOTerm)) + geom_tile(aes(fill = value), colour = "white") + scale_fill_gradient2(low = "blue",high = "red",mid="white")
} else {
p <- ggplot(data = rankres, aes(x=Var1, y=value, colour=GOTerm)) +
geom_line(aes(group=GOTerm)) + tmpyset +
geom_point(size=4)
}
p + xlab("Interval") +
ylab("Rank") +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(size=17,color='black'),
axis.text.y = element_text(size=17,color='black'),
axis.title.x = element_text(size=20,vjust=-1),
axis.title.y = element_text(size=20,vjust=1),
strip.text.y = element_text(size=17,color='black'),
legend.text = element_text(size=15),
legend.title = element_text(size=15),
legend.position = "right",
legend.key.width=unit(3,"line"),legend.key.height=unit(3,"line")
)
}
})
output$PseudotimeGOanalysisTimeshowresultwindowplotsave <- downloadHandler(
filename = function() { "GO pattern.pdf" },
content = function(file) {
if (!is.null(Maindata$PseudotimewindowGOtable) && ((input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=="Specific" && !is.null(input$PseudotimeGOanalysisTimeselectresulttimetrendspecific)) || (input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=="Top" && !is.null(input$PseudotimeGOanalysisTimeselectresulttimetrendtop)))) {
pdf(file,width=14,height=7)
GOres <- Maindata$PseudotimewindowGOtable
termnum <- as.numeric(input$PseudotimeGOanalysisTimetermnum)
if (input$PseudotimeGOanalysisTimeselectresulttimetrendselectmethod=="Specific") {
GOterm <- input$PseudotimeGOanalysisTimeselectresulttimetrendspecific
} else {
GOterm <- unique(as.vector(sapply(GOres,function(i) i[1:as.numeric(input$PseudotimeGOanalysisTimeselectresulttimetrendtop),1])))
}
GOdes <- NULL
for (i in GOres) {
GOdes <- rbind(GOdes,as.matrix(i[,1:2]))
}
GOdes <- unique(GOdes)
rankres <- sapply(GOterm,function(term) {
sapply(GOres,function(i) {
tmp <- which(i[,1]==term)
if (length(tmp) == 0)
tmp <- termnum + 1
tmp
})
})
rankres <- melt(rankres,id="V1")
maxrank <- max(rankres$value)
if (maxrank < termnum + 1) {
tmpyset <- scale_y_reverse()
} else {
tickpos <- round(seq(0,maxrank,maxrank/5))
tickpos <- tickpos[tickpos < termnum + 1]
tmpyset <- scale_y_reverse(lim=c(termnum + 1,1),breaks=c(tickpos,(termnum+1)),labels=c(tickpos,paste(">",termnum)))
}
colnames(rankres)[2] <- "GOTerm"
rankres[,2] <- paste0(rankres[,2],"\n",sapply(rankres[,2], function(i) GOdes[GOdes[,1]==i,2]))
if (input$PseudotimeGOanalysisTimeselectresulttimetrendshowheatmap) {
p <- ggplot(data=rankres, aes(x=Var1, y=GOTerm)) + geom_tile(aes(fill = value), colour = "white") + scale_fill_gradient2(low = "blue",high = "red",mid="white")
} else {
p <- ggplot(data = rankres, aes(x=Var1, y=value, colour=GOTerm)) +
geom_line(aes(group=GOTerm)) + tmpyset +
geom_point(size=4)
}
p <- p + xlab("Interval") +
ylab("Rank") +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(size=17,color='black'),
axis.text.y = element_text(size=17,color='black'),
axis.title.x = element_text(size=20,vjust=-1),
axis.title.y = element_text(size=20,vjust=1),
strip.text.y = element_text(size=17,color='black'),
legend.text = element_text(size=15),
legend.title = element_text(size=15),
legend.position = "right",
legend.key.width=unit(3,"line"),legend.key.height=unit(3,"line")
)
print(p)
}
dev.off()
}
)
### Comparison ###
observe({
if (is.null(Maindata$Comparisonrawdata))
Maindata$Comparisonrawdata <- list()
})
output$Comparisonlistnameui <- renderUI({
if (!is.null(Maindata$Comparisonrawdata))
textInput("Comparisonlistname","List Name",paste0("List",length(Maindata$Comparisonrawdata) + 1))
})
observe({
if (input$Comparisonreadin > 0)
isolate({
FileHandle <- input$ComparisonFile
if (!is.null(FileHandle)) {
Maindata$Comparisonrawdata[[input$Comparisonlistname]] <- read.csv(FileHandle$datapath,header=T,as.is=T,blank.lines.skip=TRUE)
}
})
})
observe({
if (!input$Comparisonsimplify && !input$Comparisonignoreconst) {
Maindata$Comparisondata <- Maindata$Comparisonrawdata
} else {
Maindata$Comparisondata <- lapply(Maindata$Comparisonrawdata, function(i) {
i[,2] <- sapply(i[,2], function(pattern) {
pattern <- strsplit(pattern,"_")[[1]]
if (input$Comparisonignoreconst)
pattern <- pattern[pattern!="constant"]
if (input$Comparisonsimplify)
pattern <- rle(pattern)$values
if (length(pattern) == 0) {
"NA"
} else {
paste(pattern,collapse = "_")
}
})
i
})
}
})
output$Comparisonchoosefileui <- renderUI({
selectInput("Comparisonchoosefile","Choose file to display",names(Maindata$Comparisonrawdata),names(Maindata$Comparisonrawdata)[length(Maindata$Comparisonrawdata)])
})
output$Comparisonshowfile <- renderDataTable({
if (!is.null(input$Comparisonchoosefile))
Maindata$Comparisondata[[input$Comparisonchoosefile]]
})
observe({
if (length(Maindata$Comparisondata) > 1) {
tmp <- Reduce(function(x, y) merge(x, y, by="Gene"), Maindata$Comparisondata)
colnames(tmp) <- c("Gene",names(Maindata$Comparisondata))
Maindata$Comparisonsumdata <- tmp
}
})
output$Comparisonshowcomparisonresults <- renderDataTable({
if (!is.null(Maindata$Comparisonsumdata)) {
if (input$Comparisononlyshowdifferentgene=="diffpattern") {
Maindata$Comparisonsumdata[apply(Maindata$Comparisonsumdata[,-1],1,function(x) length(unique(x))) > 1,]
} else if (input$Comparisononlyshowdifferentgene=="samepattern") {
Maindata$Comparisonsumdata[apply(Maindata$Comparisonsumdata[,-1],1,function(x) length(unique(x))) == 1,]
} else {
Maindata$Comparisonsumdata
}
}
})
})
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