Commit 7e82168f authored by Stevenn Volant's avatar Stevenn Volant
Browse files

modif diag plot + sere

parent 6d48df24
......@@ -260,7 +260,6 @@ CheckCountsTable <- function(counts)
Interaction = input$Interaction2
alltmp = c(InterVar,Interaction)
design = as.formula(paste("~", paste0(alltmp, collapse= "+")))
return(design)
}
......@@ -292,7 +291,7 @@ CheckCountsTable <- function(counts)
if(input$DiagPlot=="barplotNul") res = barPlotNul(input,counts, group = group, col=colors)
if(input$DiagPlot=="densityPlot") res = densityPlotTot(input,counts, group = group, col=colors)
if(input$DiagPlot=="MajTax") res = majTaxPlot(input,counts, group = group, col=colors)
if(input$DiagPlot=="SERE") res = SEREplot(input,counts)
#if(input$DiagPlot=="SERE") res = SEREplot(input,counts)
#if(input$DiagPlot=="Sfactors") diagSFactors(input,dds,frame=1)
if(input$DiagPlot=="SfactorsVStot") res = diagSFactors(input,dds,normFactors,CT_noNorm,frame=2)
if(input$DiagPlot=="pcaPlot") res = PCAPlot_meta(input,dds, group, type.trans = input$TransType, col = colors)
......@@ -343,6 +342,8 @@ CheckCountsTable <- function(counts)
HCPlot <- function (input,dds,group,type.trans,col = c("lightblue", "orange", "MediumVioletRed", "SpringGreen"))
{
res = NULL
## Get the counts
counts = as.data.frame(round(counts(dds, normalized = TRUE)))
if (type.trans == "VST") counts.trans <- assay(varianceStabilizingTransformation(dds))
......@@ -353,27 +354,29 @@ CheckCountsTable <- function(counts)
nb = length(unique((group)))
## Get the dendrogram
hc <- hclust(dist(t(counts.trans)), method = "ward.D")
if(input$DistClust!="sere") dist = vegdist(t(counts), method = input$DistClust)
if(input$DistClust=="sere") dist = as.dist(SEREcoef(counts))
hc <- hclust(dist, method = "ward.D")
dend = as.dendrogram(hc)
## Get the type of dendrogram
type <- switch(input$typeHculst,
"fan"="fan",
"hori"= "hori")
type <- input$typeHculst
dend <- set(dend, "labels_cex", input$cexLabelDiag)
if(input$colorHC) labels_colors(dend)<-rainbow(nb)[as.integer(as.factor(group))][order.dendrogram(dend)]
if(type=="hori")
{
par(mar = c(8,4,4,2))
plot(dend, main = "Cluster dendrogram")
par(cex=input$cexTitleDiag,mar = c(0.3,2,0.3,2))
res = plot(dend, main = "Cluster dendrogram",xlab = paste(input$DistClust,"distance, Ward criterion",sep=" "),cex=input$cexLabelDiag)
}
if(type!="hori")
{
par(mar = c(0.3,2,0.3,2))
circlize_dendrogram(dend, labels_track_height = 0.2, dend_track_height = .3, main = "Cluster dendrogram")
par(cex=input$cexTitleDiag,mar = c(0.3,2,0.3,2))
res = circlize_dendrogram(dend, labels_track_height = NULL, dend_track_height = .3, main = "Cluster dendrogram",xlab = paste(input$DistClust,"distance, Ward criterion",sep=" "))
}
return(res)
}
......@@ -428,7 +431,7 @@ CheckCountsTable <- function(counts)
barplotTot <- function(input,counts, group, cex.names = 1, col = c("lightblue","orange", "MediumVioletRed", "SpringGreen"))
{
ncol1 <- ncol(group) == 1
par(cex=input$cexLabelDiag,mar=c(12,5,4,5))
par(cex=input$cexTitleDiag,mar=c(6,6,4,5))
barplot(colSums(counts), cex.names = cex.names, main = "Total mapped read count per sample", ylab = "Total mapped read count",
ylim = c(0, max(colSums(counts)) * 1.2), density = if (ncol1) {NULL}
else {15},
......@@ -448,7 +451,7 @@ CheckCountsTable <- function(counts)
percentage.allNull <- (nrow(counts) - nrow(removeNulCounts(counts))) * 100/nrow(counts)
ncol1 <- ncol(group) == 1
par(cex=input$cexLabelDiag,mar=c(12,5,4,5))
par(cex=input$cexTitleDiag,mar=c(6,6,4,5))
barplot(percentage, las = 2, col = col[as.integer(group[,1])],
density = if (ncol1) {NULL}
......@@ -471,7 +474,7 @@ CheckCountsTable <- function(counts)
counts <- removeNulCounts(counts)
ncol1 <- ncol(group) == 1
par(cex=input$cexLabelDiag,mar=c(8,5,4,5))
par(cex=input$cexTitleDiag,mar=c(8,5,4,5))
plot(density(log2(counts[, 1] + 1)), las = 1, lwd = 2, main = "Density of counts distribution",
xlab = expression(log[2] ~ (raw ~ count + 1)),
ylim = c(0, max(apply(counts, 2, function(x) {max(density(log2(x + 1))$y)})) * 1.05),
......@@ -514,7 +517,7 @@ CheckCountsTable <- function(counts)
maj <- apply(p, 2, max)
seqname <- rownames(p)[apply(p, 2, which.max)]
ncol1 <- ncol(group) == 1
par(cex=input$cexTitleDiag,mar=c(6,6,4,5))
x <- barplot(maj, col = col[as.integer(group[, 1])], main = "Proportion of mapped reads from\nmost expressed sequence",
ylim = c(0, max(maj) * 1.2), cex.main = 1,
cex.names = cex.names, las = 2, ylab = "Proportion of mapped reads",
......@@ -532,14 +535,13 @@ CheckCountsTable <- function(counts)
## plot SERE Coefs
SEREplot<-function(input,counts)
{
sere = SEREcoef(counts)
print(sere)
hc <- hclust(as.dist(sere), method = "ward.D")
plot(hc, las = 2, hang = -1, xlab = "SERE distance, Ward criterion",main = "Cluster dendrogram\non SERE values")
}
# SEREplot<-function(input,counts)
# {
# sere = SEREcoef(counts)
# hc <- hclust(as.dist(sere), method = "ward.D")
# plot(hc, las = 2, hang = -1, xlab = "SERE distance, Ward criterion",main = "Cluster dendrogram\non SERE values")
#
# }
## Get the SERE COEF
......@@ -604,9 +606,11 @@ CheckCountsTable <- function(counts)
if(frame==2)
{
plot(normFactors, colSums(counts), pch = 19, las = 1,
par(cex=input$cexTitleDiag,mar=c(6,6,4,5))
plot(normFactors, colSums(counts), pch = 19, las = 1,cex = ifelse(input$addLabelSFact,0,input$cexLabelDiag),
ylab = "Total number of reads", xlab = "Size factors",
main = "Diagnostic: size factors vs total number of reads")
if(input$addLabelSFact) text(normFactors,colSums(counts),labels = samples,cex=input$cexLabelDiag)
abline(lm(colSums(counts) ~ normFactors + 0), lty = 2, col = "grey")
}
}
......@@ -653,14 +657,14 @@ CheckCountsTable <- function(counts)
counts.norm = counts.norm[,ind_kept]
## Get the distance
dist.counts.norm = vegdist(t(counts.norm), method = input$DistPCOA)
if(input$DistClust!="sere") dist.counts.norm = vegdist(t(counts.norm), method = input$DistClust)
if(input$DistClust=="sere") dist.counts.norm = as.dist(SEREcoef(counts.norm))
## Do PCoA
pco.counts.norm = dudi.pco(d = dist.counts.norm, scannf = FALSE,nf=3)
## Get eigen values
eigen=(pco.counts.norm$eig/sum(pco.counts.norm$eig))*100
print(eigen)
## xlim and ylim of the plot
min = min(pco.counts.norm$li)
......@@ -686,9 +690,10 @@ CheckCountsTable <- function(counts)
# to reactivate
#pco.counts.norm$li = pco.counts.norm$li[ind_kept,]
if (plot == "pcoa"){
par(cex=input$cexTitleDiag,mar=c(6,6,4,5))
## Plot axis, label and circles
plot(pco.counts.norm$li[1:2], xlab=paste("PC1 : ",round(eigen[1],1),"%") , ylab=paste("PC2 : ",round(eigen[2],1),"%"),
xlim=c(min+0.25*min,max+0.25*max), ylim=c(min-0.1,max+0.1), cex.axis=1, cex.lab=1,lwd=2, type="n")
xlim=c(min+0.25*min,max+0.25*max), ylim=c(min-0.1,max+0.1), cex.axis=1, cex.lab=1,lwd=2, type="n",main='Principal Coordinates Analysis ')
# Set different shapes
if(input$labelPCOA == "Group"){
if(!is.null(cval)){
......@@ -698,7 +703,7 @@ CheckCountsTable <- function(counts)
s.class(dfxy = pco.counts.norm$li, fac = group, col = col, label = levels(group),
add.plot = TRUE, cpoint = 0, cell=input$cexcircle, clabel=input$cexLabelDiag, cstar = input$cexstar)
}else s.class(dfxy = pco.counts.norm$li, fac = group, col = col, label = levels(group),
add.plot = TRUE, cpoint = input$cexpoint, cell=input$cexcircle, clabel=input$cexLabelDiag, cstar = input$cexstar)
add.plot = TRUE, cpoint = input$cexTitleDiag, cell=input$cexcircle, clabel=input$cexLabelDiag, cstar = input$cexstar)
}
else{
s.label(pco.counts.norm$li, clabel = input$cexLabelDiag,boxes=FALSE, add.plot = TRUE)
......@@ -729,15 +734,15 @@ CheckCountsTable <- function(counts)
prp <- round(prp, 2)
ncol1 <- ncol(group) == 1
par(mfrow = c(1, 2))
abs = range(pca$x[, 1])
abs = abs(abs[2] - abs[1])/25
ord = range(pca$x[, 2])
ord = abs(ord[2] - ord[1])/25
par(mar=c(8,5,4,5))
plot(pca$x[, 1], pca$x[, 2], las = 1, cex = 2, col = col[as.integer(group[,1])],
par(mfrow = c(1, 2),cex=input$cexTitleDiag,mar=c(6,6,4,5))
plot(pca$x[, 1], pca$x[, 2], las = 1, cex = cex=input$cexTitleDiag, col = col[as.integer(group[,1])],
pch = if (ncol1) {16}
else {c(16:18, 25)[as.integer(group[, 2])]},
xlab = paste0("PC1 (", prp[1], "%)"),
......@@ -745,12 +750,12 @@ CheckCountsTable <- function(counts)
main = "Principal Component Analysis",
)
abline(h = 0, v = 0, lty = 2, col = "lightgray")
text(pca$x[, 1] - ifelse(pca$x[, 1] > 0, abs, -abs), pca$x[,2] - ifelse(pca$x[, 2] > 0, ord, -ord), colnames(counts.trans), col = col[as.integer(group[, 1])])
text(pca$x[, 1] - ifelse(pca$x[, 1] > 0, abs, -abs), pca$x[,2] - ifelse(pca$x[, 2] > 0, ord, -ord), colnames(counts.trans), col = col[as.integer(group[, 1])],cex=input$cexLabelDiag)
abs = range(pca$x[, 1])
abs = abs(abs[2] - abs[1])/25
ord = range(pca$x[, 3])
ord = abs(ord[2] - ord[1])/25
plot(pca$x[, 1], pca$x[, 3], las = 1, cex = 2, col = col[as.integer(group[, 1])],
plot(pca$x[, 1], pca$x[, 3], las = 1, cex = cex=input$cexTitleDiag, col = col[as.integer(group[, 1])],
pch = if (ncol1) {16}
else {c(16:18, 25)[as.integer(group[, 2])]},
xlab = paste0("PC1 (", prp[1], "%)"),
......@@ -1269,7 +1274,7 @@ CheckCountsTable <- function(counts)
dispGeneEst = mcols(dds)$dispGeneEst, dispFit = mcols(dds)$dispFit,
dispMAP = mcols(dds)$dispMAP, dispersion = mcols(dds)$dispersion,
betaConv = mcols(dds)$betaConv, maxCooks = mcols(dds)$maxCooks)
if (is.null(cooksCutoff)) {
if (is.null(cooksCutoff)){
m <- nrow(attr(dds, "modelMatrix"))
p <- ncol(attr(dds, "modelMatrix"))
cooksCutoff <- qf(0.99, p, m - p)
......@@ -1283,11 +1288,11 @@ CheckCountsTable <- function(counts)
down.name <- down.name[order(down.name$padj), ]
name <- gsub(" ", "", name)
# keep <- c("FC", "log2FoldChange", "padj")
keep <- c("Id","baseMean","FC","log2FoldChange","padj")
# complete.complete[, paste(name, keep, sep = ".")] <- complete.name[, keep]
}
#return(list(complete=complete.name,up=up.name,down=down.name))
return(list(complete=complete.name[,c("Id","baseMean","FC","log2FoldChange","padj")],up=up.name[,c("Id","baseMean","FC","log2FoldChange","padj")],down=down.name[,c("Id","baseMean","FC","log2FoldChange","padj")]))
return(list(complete=complete.name[,keep],up=up.name[,keep],down=down.name[,keep]))
}
......
......@@ -3,7 +3,6 @@ if (!require(rNVD3)) {
install.packages('rNVD3')
library(rNVD3)
}
library(plotly)
if (!require(psych)) {
install.packages('psych')
library(psych)
......@@ -152,6 +151,7 @@ shinyServer(function(input, output,session) {
## Merge counts data
dataMergeCounts <-reactive({
input$RunDESeq
counts = NULL
CheckTarget = FALSE
......@@ -159,7 +159,6 @@ shinyServer(function(input, output,session) {
CT_noNorm = NULL
data = dataInput()$data
target = dataInputTarget()
taxo = input$TaxoSelect
if(!is.null(data$counts) && !is.null(data$taxo) && nrow(data$counts)>0 && nrow(data$taxo)>0 && !is.null(taxo) && taxo!="..." && !is.null(target))
......@@ -420,7 +419,7 @@ shinyServer(function(input, output,session) {
))
## Box for target visualisation
## Box for merged counts
output$BoxCountsMerge <- renderUI({
counts = dataMergeCounts()$counts
......@@ -562,7 +561,9 @@ shinyServer(function(input, output,session) {
names = resultsNames(dds)
BaseContrast(input,names,namesfile)
tmp = read.table(namesfile,header=TRUE)
filesize = file.info(namesfile)[,"size"]
if(is.na(filesize)){filesize=0}
if(filesize!=0) tmp = read.table(namesfile,header=TRUE)
Contrast = colnames(as.matrix(tmp))
updateSelectInput(session, "ContrastList","Contrasts",Contrast)
updateSelectInput(session, "ContrastList_table","Contrasts",Contrast)
......@@ -891,19 +892,21 @@ shinyServer(function(input, output,session) {
resDiff = isolate(ResDiffAnal())
Plot_diag(input,resDiff)
})
},height = reactive(input$heightDiag))
output$PlotpcoaEigen <- renderPlot({
resDiff = ResDiffAnal()
Plot_diag_pcoaEigen(input,resDiff)
})
},height = 400)
output$PlotEigen <- renderPlot({
resDiff = ResDiffAnal()
Plot_diag_Eigen(input,resDiff)
})
},height = 400)
SizeFactor_table <-reactive({
res = ResDiffAnal()
......@@ -967,12 +970,17 @@ output$exportPDFVisu <- downloadHandler(
filename <- function() { paste("test",'meta16S.ps',sep="_")},
content <- function(file) {
resDiff = ResDiffAnal()
BaseContrast = read.table(namesfile,header=TRUE)
#ggsave(filename = filename, Plot_Visu_Heatmap_FC(input,BaseContrast,resDiff),width = input$widthHeat, height = input$heightHeat)
postscript(file, width = input$widthHeat, height = input$heightHeat)
if(input$HeatMapType=="Counts") Plot_Visu_Heatmap(input,resDiff)
if(input$HeatMapType=="Log2FC") Plot_Visu_Heatmap_FC(input,BaseContrast,resDiff)
filesize = file.info(namesfile)[,"size"]
if(is.na(filesize)){filesize=0}
if(filesize!=0)
{
BaseContrast = read.table(namesfile,header=TRUE)
#ggsave(filename = filename, Plot_Visu_Heatmap_FC(input,BaseContrast,resDiff),width = input$widthHeat, height = input$heightHeat)
postscript(file, width = input$widthHeat, height = input$heightHeat)
if(input$HeatMapType=="Counts") Plot_Visu_Heatmap(input,resDiff)
if(input$HeatMapType=="Log2FC") Plot_Visu_Heatmap_FC(input,BaseContrast,resDiff)
dev.off()
}
}
)
......@@ -991,24 +999,29 @@ output$exportPDFVisu <- downloadHandler(
output$exportVisu <- downloadHandler(
filename <- function() { paste(input$PlotVisuSelect,paste('meta16S',input$Exp_format_Visu,sep="."),sep="_") },
content <- function(file) {
BaseContrast = read.table(namesfile,header=TRUE)
taxo = input$TaxoSelect
if(input$Exp_format_Visu=="png") png(file, width = input$widthVisuExport, height = input$heightVisuExport)
if(input$Exp_format_Visu=="pdf") pdf(file, width = input$widthVisuExport/96, height = input$heightVisuExport/96)
if(input$Exp_format_Visu=="eps") postscript(file, width = input$widthVisuExport/96, height = input$heightVisuExport/96)
if(input$Exp_format_Visu=="svg") svg(file, width = input$widthVisuExport/96, height = input$heightVisuExport/96)
if(input$PlotVisuSelect=="Barplot") print(Plot_Visu_Barplot(input,ResDiffAnal())$gg)
if(input$PlotVisuSelect=="Heatmap"){
if(input$HeatMapType=="Counts") print(Plot_Visu_Heatmap(input,ResDiffAnal(),export=TRUE))
if(input$HeatMapType=="Log2FC") print(Plot_Visu_Heatmap_FC(input,BaseContrast,ResDiffAnal(),export=TRUE))
}
if(input$PlotVisuSelect=="Boxplot") print(Plot_Visu_Boxplot(input,ResDiffAnal()))
if(input$PlotVisuSelect=="Diversity") print(Plot_Visu_Diversity(input,ResDiffAnal(),type="point"))
if(input$PlotVisuSelect=="Rarefaction") print( Plot_Visu_Rarefaction(input,ResDiffAnal(),ranges$x,ranges$y,ylab=taxo))
dev.off()
filesize = file.info(namesfile)[,"size"]
if(is.na(filesize)){filesize=0}
if(filesize!=0)
{
BaseContrast = read.table(namesfile,header=TRUE)
taxo = input$TaxoSelect
if(input$Exp_format_Visu=="png") png(file, width = input$widthVisuExport, height = input$heightVisuExport)
if(input$Exp_format_Visu=="pdf") pdf(file, width = input$widthVisuExport/96, height = input$heightVisuExport/96)
if(input$Exp_format_Visu=="eps") postscript(file, width = input$widthVisuExport/96, height = input$heightVisuExport/96)
if(input$Exp_format_Visu=="svg") svg(file, width = input$widthVisuExport/96, height = input$heightVisuExport/96)
if(input$PlotVisuSelect=="Barplot") print(Plot_Visu_Barplot(input,ResDiffAnal())$gg)
if(input$PlotVisuSelect=="Heatmap"){
if(input$HeatMapType=="Counts") print(Plot_Visu_Heatmap(input,ResDiffAnal(),export=TRUE))
if(input$HeatMapType=="Log2FC") print(Plot_Visu_Heatmap_FC(input,BaseContrast,ResDiffAnal(),export=TRUE))
}
if(input$PlotVisuSelect=="Boxplot") print(Plot_Visu_Boxplot(input,ResDiffAnal()))
if(input$PlotVisuSelect=="Diversity") print(Plot_Visu_Diversity(input,ResDiffAnal(),type="point"))
if(input$PlotVisuSelect=="Rarefaction") print( Plot_Visu_Rarefaction(input,ResDiffAnal(),ranges$x,ranges$y,ylab=taxo))
dev.off()
}
}
)
......@@ -1182,12 +1195,17 @@ output$RunButton <- renderUI({
output$heatmap <- renderD3heatmap({
resDiff = ResDiffAnal()
BaseContrast = read.table(namesfile,header=TRUE)
filesize = file.info(namesfile)[,"size"]
if(is.na(filesize)){filesize=0}
resplot = NULL
if(!is.null(resDiff$dds))
{
if(input$HeatMapType=="Counts") resplot = Plot_Visu_Heatmap(input,resDiff)
if(input$HeatMapType=="Log2FC") resplot = Plot_Visu_Heatmap_FC(input,BaseContrast,resDiff)
if(input$HeatMapType=="Log2FC" && filesize!=0)
{
BaseContrast = read.table(namesfile,header=TRUE)
resplot = Plot_Visu_Heatmap_FC(input,BaseContrast,resDiff)
}
}
return(resplot)
},env=new.env())
......@@ -1265,7 +1283,6 @@ output$RunButton <- renderUI({
taxo = input$TaxoSelect
resDiff = ResDiffAnal()
res = NULL
BaseContrast = read.table(namesfile,header=TRUE)
if(!is.null(data$counts) && !is.null(data$taxo) && nrow(data$counts)>0 && nrow(data$taxo)>0 && !is.null(taxo) && taxo!="...")
{
......@@ -1278,13 +1295,18 @@ output$RunButton <- renderUI({
if(input$SelectSpecifTaxo=='Most') res = selectizeInput("selectTaxoPlot",h6(strong(paste("Select the",input$TaxoSelect, "to plot"))),Available_taxo, selected = selTaxo,multiple = TRUE)
if(input$SelectSpecifTaxo=="Diff")
{
SelContrast = input$ContrastList_table_Visu
padj = Get_log2FC_padj(input,BaseContrast,resDiff, info = NULL)$padj
cont = which(colnames(padj)%in%SelContrast)
padj = padj[,cont]
selTaxo = names(padj[which(padj<=input$AlphaVal)])
res = selectizeInput("selectTaxoPlot",h6(strong(paste("Select the",input$TaxoSelect, "to plot"))),Available_taxo, selected = selTaxo,multiple = TRUE,options = list(minItems = 2))
filesize = file.info(namesfile)[,"size"]
if(is.na(filesize)){filesize=0}
if(filesize!=0)
{
BaseContrast = read.table(namesfile,header=TRUE)
SelContrast = input$ContrastList_table_Visu
padj = Get_log2FC_padj(input,BaseContrast,resDiff, info = NULL)$padj
cont = which(colnames(padj)%in%SelContrast)
padj = padj[,cont]
selTaxo = names(padj[which(padj<=input$AlphaVal)])
res = selectizeInput("selectTaxoPlot",h6(strong(paste("Select the",input$TaxoSelect, "to plot"))),Available_taxo, selected = selTaxo,multiple = TRUE,options = list(minItems = 2))
}
}
if(input$SelectSpecifTaxo=="All") res = selectizeInput("selectTaxoPlot",h6(strong(paste("Select the",input$TaxoSelect, "to plot"))),Available_taxo, selected = Available_taxo,multiple = TRUE)
}
......
......@@ -69,7 +69,7 @@ the differential analysis and mutiple visualization.",style = "font-family: 'tim
Resulting p-values are adjusted according to the Benjamini and Hochberg procedure [Benjamini and Hochberg 1995].
The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1.fr/ade4/"), "and plots are generated with", a("ggplot2",href="http://ggplot2.org/"), "or", a("D3.js packages",href="http://d3js.org/"), ".", style = "font-family: 'times'; font-si16pt")),
tabPanel("Authors", h3("The main contributors to Meta16s:"),
p(a("Stevenn Volant", href="mailto:stevenn.volant"), "(Initiator, coding, testing, documentation, evaluation)"),
p(a("Stevenn Volant", href="mailto:stevenn.volant@pasteur.fr"), "(Initiator, coding, testing, documentation, evaluation)"),
p(a("Amine Ghozlane",href="mailto:amine.ghozlane@pasteur.fr"), "(Coding, testing, documentation, feature suggestions)"),
p(a("Pierre Lechat",href="mailto:pierre.lechat@pasteur.fr"), "(Coding, testing, feature suggestions)"),
p(a("Marie-Agnès Dillies",href="mailto:marie-agnes.dillies@pasteur.fr"), "(Evaluation)"),
......@@ -200,9 +200,9 @@ The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1
tabItem(tabName = "DiagPlotTab",
fluidRow(
column(width=9,
box(title = "Plot", width = NULL, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= FALSE,
plotOutput("PlotDiag")
),
plotOutput("PlotDiag",height="100%"),
br(),
conditionalPanel(condition="input.DiagPlot=='SfactorsVStot'",
box(title = "Size factors", width = NULL, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= TRUE,
dataTableOutput("SizeFactTable")
......@@ -211,12 +211,12 @@ The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1
conditionalPanel(condition="input.DiagPlot=='pcaPlot'",
box(title = "Eigen values", width = 6, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= FALSE,
plotOutput("PlotEigen")
plotOutput("PlotEigen",height="100%")
)
),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot'",
box(title = "Eigen values", width = 6, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= FALSE,
plotOutput("PlotpcoaEigen")
plotOutput("PlotpcoaEigen",height="100%")
)
)
......@@ -233,11 +233,14 @@ The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1
conditionalPanel(condition="input.DiagPlot!='Sfactors' && input.DiagPlot!='SfactorsVStot' ",uiOutput("VarIntDiag")),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot'",
h5(strong("Select the modalities")),
uiOutput("ModMat"),
selectInput("DistPCOA","Distance",c("euclidean", "canberra", "bray", "kulczynski", "jaccard",
"gower", "altGower", "morisita", "horn","mountford","raup","binomial",
"chao","cao","mahalanobis"),selected="jaccard")
uiOutput("ModMat")
),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot' || input.DiagPlot=='SERE' || input.DiagPlot=='clustPlot' ",
selectInput("DistClust","Distance",c("euclidean", "SERE"="sere", "canberra", "bray", "kulczynski", "jaccard",
"gower", "altGower", "morisita", "horn","mountford","raup","binomial",
"chao","cao","mahalanobis"),selected="jaccard")
)
# conditionalPanel(condition="input.RadioPlotBi=='Nuage'",selectInput("ColorBiplot", "Couleur",choices=c("Bleue" = 'blue',"Rouge"='red',"Vert"='green', "Noir"='black'),width="50%")),
# sliderInput("TransAlphaBi", "Transparence",min=1, max=100, value=50, step=1),
# conditionalPanel(condition="input.RadioPlotBi!='Nuage'", radioButtons("SensGraphBi","Sens du graph",choices=c("Vertical"="Vert","Horizontal"="Hori"))),
......@@ -249,6 +252,8 @@ The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1
# h6(strong("Layout")),
# numericInput("NbcolSfactors", h6("Columns"),min=1,value = NA)
# ),
sliderInput("heightDiag", "Height",min=100,max=1500,value = 500,step =10),
conditionalPanel(condition="input.DiagPlot=='clustPlot'",
h6(strong("Layout")),
selectInput("typeHculst", h6("Type"),c("Horizontal"="hori","Fan"="fan")),
......@@ -261,8 +266,16 @@ The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1
sliderInput("cexstar", "Star height",min=0,max=1,value = 0.95,step =0.1)
),
sliderInput("cexLabelDiag", "Label size",min=0,max=5,value = 1,step =0.1)
# sliderInput("heightDiag", "height",min=100,max=1500,value = 500,step =10),
conditionalPanel(condition="input.DiagPlot=='SfactorsVStot'",
checkboxInput("addLabelSFact","Add label",FALSE)
),
fluidRow(
column(width=12, p(strong("Size"))),
column(width=6,sliderInput("cexTitleDiag", h6("Axis"),min=0,max=5,value = 1,step =0.1)),
conditionalPanel(condition="input.DiagPlot=='SfactorsVStot' || input.DiagPlot=='pcaPlot'",column(width=6,sliderInput("cexLabelDiag", h6("Points"),min=0,max=5,value = 1,step =0.1)))
)
# sliderInput("widthDiag", "width",min=100,max=1500,value = 1000,step =10)
......
Supports Markdown
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment