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server.R
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shinyServer(function(input, output,session) {
hide(id = "loading-content", anim = TRUE, animType = "fade",time=1.5)
hide(id = "loading-content-bar", anim = TRUE, animType = "fade",time=1.5)
### ###
#### LOAD FILES ####
### ###
## Create base for contrast
rand = floor(runif(1,0,1e9))
namesfile = tempfile(pattern = "BaseContrast", tmpdir = tempdir(), fileext = "")
file.create(namesfile,showWarnings=FALSE)
target = NULL
taxo = NULL
proxy = dataTableProxy('DataTaxo')
## JSON name for masque
curdir = getwd()
json_name = tempfile(pattern = "file", tmpdir = paste(curdir,"www","masque","todo",sep= .Platform$file.sep), fileext = ".json")
## Pass for MASQUE
pass = gsub("file","",basename(file_path_sans_ext(json_name)))
## Popup messages
observe(if(input$AddRegScatter) info("By adding the regression line, you will lose interactivity."))
## Reactive target
values <- reactiveValues(TargetWorking = target, TaxoWorking = taxo, labeled=NULL,fastq_names_only=NULL,R1fastQ=NULL,R2fastQ=NULL,
json_name=json_name,num=0,pass=pass,login_email = NULL,is.valid =NULL,
biom_masque = NULL,tree_masque=NULL, masque_key = NULL, count_table_masque = NULL,
rdp_annot_masque = NULL, rdp_thres_masque = NULL,
paths_fastq_tmp=NULL,curdir=curdir, error_progress=FALSE, visTarget=FALSE, colors_diag=NULL)
## Counts file
dataInputCounts <-reactive({
data = NULL
inFile <- input$fileCounts
if (is.null(inFile) && is.null(values$count_table_masque)) return(NULL)
#if (is.null(inFile)) return(NULL)
if (!is.null(values$count_table_masque) && file.exists(values$count_table_masque)){
tryCatch(read.csv(values$count_table_masque,sep="\t",header=TRUE,check.names=FALSE)->data,
#messageId="ErrorCounts",
error=function(e) sendSweetAlert(session,
title = "Oops",
text=paste("The count file can not be read in SHAMAN.\n \n",e),type ="error"))
}
else{
tryCatch(read.csv(inFile$datapath,sep=input$sepcount,header=TRUE,check.names=FALSE)->data,
#messageId="ErrorCounts",
error=function(e) sendSweetAlert(session,
title = "Oops",
text=paste("Your file can not be read in SHAMAN.\n \n",e),type ="error"))
}
#print(data)
if(!is.null(data)){
colnames(data) = gsub("-",".",colnames(data))
## Rownames
if(!TRUE%in%duplicated(data[,1])) rownames(data)=data[,1];data=data[,-1]
try(round(data, 0)->data, silent=T)
}
#print(data)
return(as.data.frame(data))
})
## Taxo File
dataInputTaxo <-reactive({
inFile <- input$fileTaxo
values$TaxoWorking = NULL
if (is.null(inFile) && is.null(values$rdp_annot_masque)) return(NULL)
#if (is.null(inFile)) return(NULL)
if(input$TypeTaxo=="Table" && !is.null(inFile))
{
tryCatch(read.csv(inFile$datapath,sep=input$septaxo,header=TRUE)->data,
#messageId="ErrorTaxo",
error=function(e) sendSweetAlert(session,
title = "Oops",
text=paste("Your file can not be read in SHAMAN.\n \n",e),type ="error"))
## Rownames
if(!is.null(data))
{
if(!TRUE%in%duplicated(data[,1])){
DataNames=data[,1]
colNames=colnames(data)[-1]
data=as.matrix(data[,-1])
rownames(data)=DataNames
colnames(data) = colNames
}
}
}
if(input$TypeTaxo=="RDP" && !is.null(inFile) || !is.null(values$rdp_annot_masque))
{
if (!is.null(values$rdp_annot_masque) && file.exists(values$rdp_annot_masque)){
tryCatch(read_rdp(values$rdp_annot_masque,values$rdp_thres_masque)->data,
#messageId="ErrorRDP",
error=function(e) sendSweetAlert(session,
title = "Oops",
text=paste("The annotation file can not be read in SHAMAN.\n \n",e),type ="error"))
}
else{
tryCatch(read_rdp(inFile$datapath,input$RDP_th)->data,
#messageId="ErrorRDP",
error=function(e) sendSweetAlert(session,
title = "Oops",
text=paste("Your file can not be read in SHAMAN.\n \n",e),type ="error"))
}
}
## Add NA
data=as.matrix(data)
indNa = which(data=="")
data[indNa]=NA
#print(data)
return(as.data.frame(data))
})
## BIOM File
dataInputEpi2me <-reactive({
data = NULL
inFile <- input$fileEpi2me
if (!is.null(inFile) && is.null(values$biom_masque)){
tryCatch(read.csv(inFile$datapath,sep=input$sepepi2me,header=TRUE)->data,
#messageId="ErrorBiom1",
error=function(e) sendSweetAlert(session,
title = "Oops",
text=paste("Your file can not be read in SHAMAN.\n \n",e),type ="error"))
if(FALSE %in% c(c("accuracy", "barcode", "lineage") %in% colnames(data))){
data = NULL
sendSweetAlert(session, title = "Missing data",
text="Shaman looks for accuracy, barcode and lineage colnames in Epi2me files\n \n",type ="error")
}
}
return(data)
})
## BIOM File
dataInputBiom <-reactive({
data = NULL
inFile <- input$fileBiom
if (!is.null(inFile) && is.null(values$biom_masque)){
tryCatch(read_biom(inFile$datapath)->data,
#messageId="ErrorBiom1",
error=function(e) sendSweetAlert(session,
title = "Oops",
text=paste("Your file can not be read in SHAMAN.\n \n",e),type ="error"))
}
if (!is.null(values$biom_masque) && file.exists(values$biom_masque)){
tryCatch(read_biom(values$biom_masque)->data,
#messageId="ErrorBiom2",
error=function(e) sendSweetAlert(session,
title = "Oops",
text=paste("Your file can not be read in SHAMAN.\n \n",e),type ="error"))
}
return(data)
})
observeEvent(input$fileCounts,{
values$count_table_masque=NULL;
})
observeEvent(input$fileTaxo,{
values$rdp_annot_masque=NULL;
values$rdp_thres_masque=NULL;
})
observeEvent(input$fileBiom,{
values$biom_masque=NULL;
})
## Unifrac File (tree)
dataInputTree <-reactive({
data = NULL
{inFile <- input$fileTree
values$tree_masque}
if (!is.null(inFile) && is.null(values$tree_masque)) {
try(read.tree(inFile$datapath)->data, silent=T)
CheckTree = CheckTreeFile(data)
data = CheckTree$tree
try(readLines(inFile$datapath)->treeseq, silent=T)
return(list(data=data, Error=CheckTree$Error, Warning=CheckTree$Warning, treeseq=treeseq))
}
if (!is.null(values$tree_masque) && file.exists(values$tree_masque)) {
try(read.tree(values$tree_masque)->data, silent=T)
CheckTree = CheckTreeFile(data)
data = CheckTree$tree
try(readLines(values$tree_masque)->treeseq, silent=T)
return(list(data=data, Error=CheckTree$Error, Warning=CheckTree$Warning, treeseq=treeseq))
}
})
observeEvent(input$fileTree,{
values$tree_masque=NULL;
})
# Infobox Tree (Unifrac)
output$InfoTreePhylo_box <- renderInfoBox({
{input$fileTree
values$tree_masque}
tree_tmp = isolate(dataInputTree())
tree = tree_tmp$data
res = infoBox(h6(strong("Phylogenetic tree")), subtitle = h6(strong("Load the phylogenetic tree (optional)")) ,color = "light-blue",width=NULL,fill=TRUE, icon = icon("upload"))
if(!is.null(tree)){
#if(!is.null(isolate(input$fileTree))){
res = infoBox(h6(strong("Phylogenetic tree")), subtitle = h6("The phylogenetic has been loaded") ,color = "green",width=NULL,fill=TRUE, icon = icon("thumbs-o-up"))
if(!is.null(tree_tmp$Warning)){
res = infoBox(h6(strong("Phylogenetic tree")), subtitle = h6(tree_tmp$Warning) ,color = "orange",width=NULL,fill=TRUE, icon = icon("warning"))
}
if(!is.null(tree_tmp$Error)){
res = infoBox(h6(strong("Phylogenetic tree")), subtitle = h6(tree_tmp$Error),color = "red",width=NULL,fill=TRUE, icon = icon("thumbs-o-down"))
}
#}
}
return(res)
})
observe({
val <- input$annotationKingdomthreshold
# Control the value, min, max, and step.
# Step size is 2 when input value is even; 1 when value is odd.
updateSliderInput(session, "annotationPhylumthreshold", value = input$annotationPhylumthreshold,
min = val, max = 1, step = 0.005)
})
observe({
val <- input$annotationPhylumthreshold[2]
# Control the value, min, max, and step.
# Step size is 2 when input value is even; 1 when value is odd.
updateSliderInput(session, "annotationClassthreshold", value = input$annotationClassthreshold,
min = val, max = 1, step = 0.005)
})
observe({
val <- input$annotationClassthreshold[2]
# Control the value, min, max, and step.
# Step size is 2 when input value is even; 1 when value is odd.
updateSliderInput(session, "annotationOrderthreshold", value = input$annotationOrderthreshold,
min = val, max = 1, step = 0.005)
})
observe({
val <- input$annotationOrderthreshold[2]
# Control the value, min, max, and step.
# Step size is 2 when input value is even; 1 when value is odd.
updateSliderInput(session, "annotationFamilythreshold", value = input$annotationFamilythreshold,
min = val, max = 1, step = 0.005)
})
observe({
val <- input$annotationFamilythreshold[2]
# Control the value, min, max, and step.
# Step size is 2 when input value is even; 1 when value is odd.
updateSliderInput(session, "annotationGenusthreshold", value = input$annotationGenusthreshold,
min = val, max = 1, step = 0.005)
})
observe({
val <- input$annotationGenusthreshold[2]
# Control the value, min, max, and step.
# Step size is 2 when input value is even; 1 when value is odd.
updateSliderInput(session, "annotationSpeciethreshold", value = input$annotationSpeciethreshold,
min = val, max = 1, step = 0.005)
})
## Input data
dataInput <-reactive({
data = NULL
check = NULL
percent = NULL
Taxo = values$TaxoWorking
Counts = NULL
inputData = NULL
target = NULL
if(input$FileFormat=="fileCounts")
{
Counts = dataInputCounts()
if(!input$NoTaxoFile && is.null(Taxo)) Taxo = dataInputTaxo()
if(!is.null(Counts) && input$NoTaxoFile) {Taxo = data.frame(rownames(Counts),row.names = rownames(Counts));names(Taxo)=NA}
if(!is.null(Counts) && !is.null(Taxo))
{
tmp = GetDataFromCT(Counts,Taxo, ifelse(input$TypeTable=="MGS" && input$FileFormat!="fileBiom", TRUE, FALSE))
data = list(counts=tmp$counts,taxo=tmp$taxo, taxo_biom=tmp$taxo_biom)
## Remove row with only O
# data[["counts"]] = data[["counts"]][rowSums(data[["counts"]])>1,]
check = list(CheckCounts=tmp$CheckCounts,CheckTaxo=tmp$CheckTaxo,CheckPercent=tmp$CheckPercent)
percent = tmp$Percent
}
}
if(input$FileFormat=="fileEpi2me")
{
tmpEpi2me = dataInputEpi2me()
if(!is.null(tmpEpi2me) && is.null(data))
{
tmpEpi2me = tmpEpi2me[which(tmpEpi2me$accuracy >= as.numeric(input$Epi2me_th) & !is.na(tmpEpi2me$barcode) ),]
# remove missing levels
tmpEpi2me = droplevels(tmpEpi2me)
#tmp = plyr::count(tmpEpi2me,c("barcode", "phylum", "class", "order", "family", "genus", "species"))
tmp = plyr::count(tmpEpi2me,c("barcode", "lineage"))
#tmp$ids = paste(tmp$genus, tmp$species, sep="|")
#tmp$index = paste0("Seq_",match(tmp$ids, unique(tmp$ids)))
tmp$index = paste0("Seq_",match(tmp$lineage, unique(tmp$lineage)))
Counts = as.data.frame.matrix(t(xtabs(freq~.,tmp[,c("freq", "barcode","index")])))
#Taxo = unique(tmp[,c("index", "phylum", "class", "order", "family", "genus", "species")])
Taxotmp = unique(tmp[,c("index", "lineage")])
Taxo = stringr::str_split_fixed(Taxotmp$lineage, ";", 7)
Taxo[Taxo == ""] =NA
colnames(Taxo) = c("Kingdom", "Phylum", "Class", "Order", "Family", "Genus", "Specie")
rownames(Taxo) = Taxotmp$index
names(Taxo) = c("Kingdom", "Phylum", "Class", "Order", "Family", "Genus", "Specie")
#rownames(Taxo) = Taxo$index
#Taxo= Taxo[,c("genus","species")]
#names(Taxo)=c("Genus","Specie")
if(!is.null(Counts) && !is.null(Taxo))
{
tmp = GetDataFromCT(Counts,Taxo, FALSE)
# print(tmp)
data = list(counts=tmp$counts,taxo=tmp$taxo, taxo_biom=tmp$taxo_biom)
## Remove row with only O
# data[["counts"]] = data[["counts"]][rowSums(data[["counts"]])>1,]
check = list(CheckCounts=tmp$CheckCounts,CheckTaxo=tmp$CheckTaxo,CheckPercent=tmp$CheckPercent)
# print(check)
percent = tmp$Percent
}
## Remove row with only O
# data[["counts"]] = data[["counts"]][rowSums(data[["counts"]])>1,]
}
}
if(input$FileFormat=="fileBiom")
{
tmpBIOM = dataInputBiom()
if(!is.null(tmpBIOM) && is.null(data))
{
tmp = GetDataFromBIOM(tmpBIOM)
if(!is.null(Taxo)){
data = list(counts=tmp$counts,taxo=Taxo, target=tmp$target, taxo_biom=tmp$taxo_biom)
tmp_check = CheckTaxoTable(Taxo,tmp$counts)
tmp_annot = PercentAnnot(tmp$counts,Taxo)
check = list(CheckCounts=tmp_check$CheckCounts,CheckTaxo=tmp_check$CheckTaxo,Percent=tmp_annot$Percent,CheckPercent=tmp_annot$Error)
percent = tmp_annot$Percent
}
else{
data = list(counts=tmp$counts,taxo=tmp$taxo, target=tmp$target, taxo_biom=tmp$taxo_biom)
## Remove row with only O
# data[["counts"]] = data[["counts"]][rowSums(data[["counts"]])>1,]
check = list(CheckCounts=tmp$CheckCounts,CheckTaxo=tmp$CheckTaxo,CheckPercent=tmp$CheckPercent)
percent = tmp$Percent}
#if(!is.null(data$target)) values$TargetWorking = data$target
}
}
# if(input$FileFormat=="fileRData")
# {
# inFile <- input$fileRData
# load(inFile)
# if(!is.null(inputData)){
# data = inputData$data
# check = inputData$check
# percent = inputData$percent
# }
# }
return(list(data=data,check=check,percent=percent))
})
## Size factor file (optional)
dataSizeFactors <-reactive({
inFile <- input$fileSizeFactors
if (is.null(inFile)) return(NULL)
tryCatch(read.csv(inFile$datapath,sep=input$sepsize,header=TRUE)->data,
#messageId="ErrorSizeFactor",
error=function(e) sendSweetAlert(session,
title = "Oops",
text=paste("Your file can not be read in SHAMAN.\n \n",e),type ="error"))
return(as.data.frame(data))
})
## Size factor file (optional)
SizeFactors_fromFile <-reactive({
Error = NULL
Check = TRUE
data = dataSizeFactors()
normFactors = dataMergeCounts()$normFactors
if(!is.null(data)){
## Check the format
tmp = as.numeric(data)
names(tmp) = colnames(data)
if(length(tmp)!=length(normFactors)){Error = "The number of samples is not the same than in the target file, size factors will be estimated"; Check = FALSE}
if(!identical(names(tmp),names(normFactors))){Error = "The names are not the same or in the same order than in the target file, size factors will be estimated"; Check = FALSE}
if(Check) normFactors = tmp
}
return(list(Check = Check,Error = Error,normFactors=normFactors))
})
## Merge counts data
dataMergeCounts <-reactive({
input$RunDESeq
counts = NULL
CheckTarget = FALSE
normFactors = NULL
CT_noNorm = NULL
CT_Norm = NULL
ChTM = NULL
ChMC = NULL
data = isolate(dataInput()$data)
target = isolate(values$TargetWorking)
labeled= isolate(values$labeled)
taxo = isolate(input$TaxoSelect)
withProgress(
if(!is.null(data$counts) && !is.null(data$taxo) && nrow(data$counts)>0 && nrow(data$taxo)>0 && !is.null(taxo) && taxo!="..." && !is.null(target))
{
design = GetDesign(isolate(input),target)
ChTM = CheckTargetModel(input,target,labeled,data$counts)$Error
if(!is.null(design) && is.null(ChTM))
{
tmp = isolate(GetCountsMerge(input,data,taxo,target,design))
#ChMC = tmp$Error
#if (!is.null(ChMC))
#{
counts = tmp$counts
## Filtering the counts
if(isolate(input$AddFilter) && !is.null(isolate(input$SliderThSamp)) && !is.null(isolate(input$SliderThAb)))
{
ind.filter =Filtered_feature(counts,isolate(input$SliderThSamp),isolate(input$SliderThAb))$ind
counts = counts[-ind.filter,]
}
CheckTarget = tmp$CheckTarget
#target = tmp$target
#labeled = tmp$labeled
normFactors = tmp$normFactors
## OTU table, norm and no norm
CT_noNorm = tmp$CT_noNorm
CT_Norm = tmp$CT_Norm
#}
}
}
,message="Merging the counts ...")
return(list(counts=counts,CheckTarget=CheckTarget,normFactors=normFactors,CT_noNorm=CT_noNorm, CT_Norm=CT_Norm, Error = ChMC))
#return(list(counts=counts,target=target,labeled=labeled,normFactors=normFactors,CT_noNorm=CT_noNorm))
})
# Infobox Error counts
output$InfoErrorCounts <- renderInfoBox({
tmp = dataInput()
data = tmp$data
check = tmp$check
cond = (!is.null(data$counts) && nrow(data$counts)>0)
res =infoBox(h6(strong("Count table")), subtitle = h6("Load the count table") ,color = "light-blue",width=NULL,fill=TRUE, icon = icon("upload"))
if(cond)
{
if(!is.null(check$CheckCounts$Warning)) res = infoBox(h6(strong("Count table")), subtitle = h6(check$CheckCounts$Warning), icon = icon("warning"),color = "orange",width=NULL,fill=TRUE)
if(!is.null(check$CheckCounts$Error)) res = infoBox(h6(strong("Count table")), subtitle = h6(check$CheckCounts$Error), icon = icon("thumbs-o-down"),color = "red",width=NULL,fill=TRUE)
if(is.null(check$CheckCounts$Error) && is.null(check$CheckCounts$Warning)) res = infoBox(h6(strong("Count table")), subtitle = h6(paste("Format of the count table seems to be OK")), icon = icon("thumbs-o-up"),color = "green",width=NULL,fill=TRUE)
}
return(res)
})
# Infobox Error counts
output$InfoErrorTaxo <- renderInfoBox({
tmp = dataInput()
data = tmp$data
check = tmp$check
cond = (!is.null(data$taxo) && nrow(data$taxo)>0)
res = infoBox(h6(strong("Taxonomy table")), subtitle = h6("Load the taxonomy table") ,color = "light-blue",width=NULL,fill=TRUE, icon = icon("upload"))
if(cond)
{
if(!is.null(check$CheckTaxo$Warning)) res = infoBox(h6(strong("Taxonomy table")), subtitle = h6(check$CheckTaxo$Warning), icon = icon("warning"),color = "orange",width=NULL,fill=TRUE)
if(!is.null(check$CheckTaxo$Error)) res = infoBox(h6(strong("Taxonomy table")), subtitle = h6(check$CheckTaxo$Error), icon = icon("thumbs-o-down"),color = "red",width=NULL,fill=TRUE)
if(is.null(check$CheckTaxo$Error) && is.null(check$CheckTaxo$Warning)) res = infoBox(h6(strong("Taxonomy table")), subtitle = h6(paste("Format of the taxonomy table seems to be OK")), icon = icon("thumbs-o-up"),color = "green",width=NULL,fill=TRUE)
}
if(input$NoTaxoFile && input$FileFormat=="fileCounts") res = infoBox(h6(strong("Taxonomy table")), subtitle = h6("No taxonomy table has been uploaded, the analysis can only be done at the OTU/gene level"), icon = icon("warning"),color = "orange",width=NULL,fill=TRUE)
return(res)
})
# Infobox Error counts
output$valueErrorPercent <- renderInfoBox({
{values$TaxoWorking
tmp = dataInput()}
data = tmp$data
if(!is.null(values$TaxoWorking)) tmp = dataInput()
check = tmp$check
cond = (!is.null(data$counts) && nrow(data$counts)>0 && !is.null(data$taxo) && nrow(data$taxo)>0)
res = shinydashboardshaman::valueBox(paste0(0, "%"),h6(strong("Annotated features")), color = "light-blue",width=NULL,icon = icon("list"))
if(cond)
{
percent = round(100*tmp$percent,2)
if(percent==0) res = shinydashboardshaman::valueBox(paste0(percent, "%"),h6(strong("Annotated features")), color = "red",width=NULL,icon = icon("list"))
if(percent!=0) res = shinydashboardshaman::valueBox(paste0(percent, "%"),h6(strong("Annotated features")), color = "green",width=NULL,icon = icon("list"))
}
return(res)
})
####### Filtering the counts (sliders)
output$ThAb <- renderUI({
input$AddFilter
res = NULL
counts = isolate(dataMergeCounts()$counts)
tot = rowSums(counts)
#save(counts,tot,file="testFilter.RData")
withProgress({tmp = SelectThreshAb(counts,lambda=max(round(sum(counts)/nrow(counts)*0.05),min(tot)+1),graph=FALSE)},message="Loading...")
res = sliderInput("SliderThAb","Threshold on the total abundance (in log)",min=0,max=round(max(log(tot+1)),1),value = log(tmp+1))
return(res)
})
output$ThSamp <- renderUI({
input$AddFilter
res = NULL
counts = isolate(dataMergeCounts()$counts)
counts.bin = as.matrix(counts)
counts.bin[which(counts>0)] = 1
nbSampByFeat = rowSums(counts.bin)
## Default value
val = round(max(nbSampByFeat)*0.2)
res = sliderInput("SliderThSamp","Threshold on the minimal number of samples",min=0,max=max(nbSampByFeat),value = val)
return(res)
})
## Plot for the filtering step$
# plot_filter(counts,th.samp,th.abund,type="Scatter")
output$Plot_ThAb <- renderPlot({
counts = dataMergeCounts()$counts
## output of plot_filter is ggplot class
plot_filter(counts,input$SliderThSamp,input$SliderThAb,type="Abundance")
})
output$Plot_ThSamp <- renderPlot({
counts = dataMergeCounts()$counts
## output of plot_filter is ggplot class
plot_filter(counts,input$SliderThSamp,input$SliderThAb,type="Samples")
})
output$Plot_Scatter_Filter <- renderScatterD3({
counts = dataMergeCounts()$counts
## output of plot_filter is ggplot class
plot_filter(counts,input$SliderThSamp,input$SliderThAb,type="Scatter")
})
### ###
##
## DYNAMIC MENU ####
##
### ###
output$dymMenu <- renderMenu({
tmp = dataInput()
data = tmp$data
check = tmp$check
## Check error in the counts and taxonomy table
CheckOK = (is.null(check$CheckCounts$Error) && is.null(check$CheckTaxo$Error) && is.null(check$CheckPercent))
if(!is.null(data$counts) && !is.null(data$taxo) && nrow(data$counts)>0 && nrow(data$taxo)>0 && CheckOK)
{
sidebarMenu(id = "side",
menuItem("Statistical analysis",
menuSubItem("Run differential analysis",tabName="RunDiff"),
menuSubItem("Diagnostic plots",tabName="DiagPlotTab"),
menuSubItem("Tables",tabName="TableDiff"),
icon = icon("bar-chart-o"), tabName = "AnaStat"
),
menuItem("Visualization",icon = icon("area-chart"),
menuSubItem("Global views",tabName="GlobVisu"),
menuSubItem("Comparison plots",tabName="CompPlot"),
tabName = "Visu")
#menuItem("Perspective plots", icon = icon("pie-chart"), tabName = "Krona")
)
} else{ sidebarMenu(id = "side",NULL)}
})
### ###
##
## DATA TABLE ####
##
### ###
## Counts Table
output$DataCounts <- DT::renderDataTable(
dataInput()$data$counts,
options = list(lengthMenu = list(c(10, 50, -1), c('10', '50', 'All')),
pageLength = 10,scrollX=TRUE, processing=FALSE
))
## Counts Table
output$DataUpSet<- DT::renderDataTable({
resDiff = ResDiffAnal()
BaseContrast = read.table(namesfile,header=TRUE)
datatable(Plot_UpSet(input,BaseContrast, resDiff, ContrastListDebounce)$table,
options = list(lengthMenu = list(c(10, 50, -1), c('10', '50', 'All')),
pageLength = 10,scrollX=TRUE, processing=FALSE)
)
})
## Counts Table
output$DataVenn<- DT::renderDataTable({
SelContrast = ContrastListVennDebounce()
#SelContrast = input$ContrastList_table_FC
resDiff = ResDiffAnal()
#BaseContrast = read.table(namesfile,header=TRUE)
datatable(GetData_venn(input,SelContrast,read.table(namesfile,header=TRUE),resDiff)$df.tot,
options = list(lengthMenu = list(c(10, 50, -1), c('10', '50', 'All')),
pageLength = 10,scrollX=TRUE, processing=FALSE)
)
})
# output$DataVenn<- DT::renderDataTable(#{
# #SelContrast = input$ContrastList_table_FC
# #resDiff = ResDiffAnal()
# #BaseContrast = read.table(namesfile,header=TRUE)
# GetData_venn(input,input$ContrastList_table_FC,read.table(namesfile,header=TRUE),ResDiffAnal())$df.tot,
# #}
# options = list(lengthMenu = list(c(10, 50, -1), c('10', '50', 'All')),
# pageLength = 10,scrollX=TRUE, processing=FALSE
# ))
## Taxonomy table
output$DataTaxo <- DT::renderDataTable(
dataInput()$data$taxo,
editable=T,
options = list(lengthMenu = list(c(10, 50, -1), c('10', '50', 'All')),
pageLength = 10,scrollX=TRUE, processing=FALSE)
)
observeEvent(input$DataTaxo_cell_edit, {
info = input$DataTaxo_cell_edit
str(info)
i = info$row
j = info$col
v = info$value
tmp=as.matrix(dataInput()$data$taxo)
tmp[i,j] = v
values$TaxoWorking = as.data.frame(tmp)
replaceData(proxy, values$TaxoWorking, resetPaging = FALSE)
})
## Tab box for data visualisation
output$TabBoxData <- renderUI({
tree = dataInputTree()$data
data=dataInput()$data
res=NULL
if(!is.null(tree))
{
res = tabBox(width = NULL, selected = "Count table",
tabPanel("Count table",DT::dataTableOutput("DataCounts"),
downloadButton('ExportRawCounts', 'Export count table file')),
tabPanel("Taxonomy",DT::dataTableOutput("DataTaxo"),
actionButton("deleteTaxo", "Delete annotation"),
downloadButton('ExportTaxo', 'Export taxonomy file')),
tabPanel("Summary",h5(strong("Percentage of annotation")),htmlOutput("SummaryView"),
br(),h5(strong("Number of features by level:")),plotOutput("SummaryViewBarplot",width = 1200,height=500)),
tabPanel("Phylogeny", PhyloTreeMetaROutput('PhyloTreeMetaR'),
downloadButton('ExportPhylo', 'Export phylogeny file'))
)
}
else
{
res = tabBox(width = NULL,selected = "Count table",
tabPanel("Count table",DT::dataTableOutput("DataCounts"),
downloadButton('ExportRawCounts', 'Export count table file')),
tabPanel("Taxonomy",DT::dataTableOutput("DataTaxo"),
actionButton("deleteTaxo", "Delete annotation"),
downloadButton('ExportTaxo', 'Export taxonomy file')),
tabPanel("Summary",h5(strong("Percentage of annotation")),htmlOutput("SummaryView"),
br(),h5(strong("Number of features by level:")),plotOutput("SummaryViewBarplot",width = 1200,height=500))
)
}
return(res)
})
observe({
data=dataInput()$data
if(!is.null(data$counts) && !is.null(data$taxo) && nrow(data$counts)>0 && nrow(data$taxo)>0)
{
showElement("tabboxdata_col",anim=TRUE)
} else hideElement("tabboxdata_col",anim=TRUE)
})
output$PhyloTreeMetaR <- renderPhyloTreeMetaR({
PhyloTreeMetaR(dataInputTree()$treeseq,NULL)
})
output$SummaryView <- renderGvis({
tmp = dataInput()
data = tmp$data
taxo = data$taxo
counts = data$counts
check = tmp$check
cond = (!is.null(data$counts) && nrow(data$counts)>0 && !is.null(data$taxo) && nrow(data$taxo)>0 && is.null(check$CheckTaxo$Error) && is.null(check$CheckCounts$Error))
res = NULL
if(cond)
{
taxo = rbind(taxo,rep(NA,ncol(taxo)))
#tmpPercent = round(apply(is.na(taxo),2,table)["FALSE",]/(nrow(taxo)-1)*100,2)
tmp = apply(is.na(taxo),2,table)
if (class(tmp) == "list") {
tmp2 = sapply(tmp, function (x) {if (! "FALSE" %in% names(x)) {x["FALSE"] = 0} ; return(x["FALSE"])})
}
else
{
tmp2 = tmp["FALSE",]
}
tmpPercent = round(tmp2/(nrow(taxo)-1)*100,2)
df <- data.frame(Label = colnames(taxo),Value = tmpPercent)
# res = gvisGauge(df,options=list(min=0, max=100, greenFrom=80,
# greenTo=100, yellowFrom=60, yellowTo=80,
# redFrom=0, redTo=60, width=1200, height=300))
res = gvisGauge(df,options=list(min=0, max=100, greenFrom=80,
greenTo=100, yellowFrom=60, yellowTo=80,
redFrom=0, redTo=60, width=800, height=200))
}
return(res)
})
output$SummaryViewBarplot <- renderPlot({
tmp = dataInput()
data = tmp$data
taxo = data$taxo
counts = data$counts
check = tmp$check
cond = (!is.null(data$counts) && nrow(data$counts)>0 && !is.null(data$taxo) && nrow(data$taxo)>0 && is.null(check$CheckTaxo$Error) && is.null(check$CheckCounts$Error))
res = NULL
if(cond)
{
colors=rep(c("#1f77b4","#aec7e8","#ff7f0e","#ffbb78", "#2ca02c","#98df8a","#d62728","#ff9896","#9467bd","#c5b0d5","#8c564b",
"#c49c94","#e377c2","#f7b6d2","#7f7f7f", "#c7c7c7","#bcbd22","#dbdb8d","#17becf","#9edae5"),ceiling(ncol(taxo)/20))
tmp = apply(taxo,2,unique)
nbfeatures = as.numeric(lapply(tmp,length)) -as.numeric(lapply(lapply(tmp,is.na),any))
df <- data.frame(Label = colnames(taxo),Count = nbfeatures)
df$Label = factor(df$Label,levels =colnames(taxo) )
res = ggplot(df,aes(x=Label,y=Count,fill=Label))+geom_bar(stat="identity")
res = res + theme_bw() + xlab("Taxonomy") + scale_fill_manual(values=colors) + guides(fill=FALSE)
}
return(res)
})
### ###
##
## TARGET FILE ####
### ###
observe({
counts = dataInput()$data$counts
data = dataInput()$data$target
if(!is.null(data) && !is.null(counts))
{
names = colnames(data)
## Keep only the row which are in the count table
ind = which(rownames(data)%in%colnames(counts))
data = as.data.frame(data[ind,])
colnames(data) = names
## Replace "-" by "."
if(ncol(data)>1 && nrow(data)>1){
ind_num = which(sapply(as.data.frame(data[,-1]),is.numeric)) + 1
if(length(ind_num)>0){
data_tmp =cbind( as.data.frame(apply(as.data.frame(data[,-ind_num]),2,gsub,pattern = "-",replacement = ".")),data[,ind_num])
#data_tmp =cbind( as.data.frame(as.data.frame(data[,-ind_num])),data[,ind_num])
colnames(data_tmp) = c(colnames(data)[-ind_num],colnames(data)[ind_num])
data = data_tmp
}
if(length(ind_num)==0){data = as.data.frame(apply(data,2,gsub,pattern = "-",replacement = "."))}
}
values$TargetWorking = data
values$labeled = length(ind)/length(colnames(counts))*100.0
}
})
## Load target file
observe({
inFile <- input$fileTarget
#values$TargetWorking = NULL
counts = dataInput()$data$counts
labeled = 0
data = NULL
if (is.null(inFile)) return(NULL)
## Read the data
try(read.csv(inFile$datapath,sep=input$septarget,header=TRUE)->data,silent=TRUE)
if(!is.null(data))
{
data = as.data.frame(data)
names = colnames(data)
## Change the rownames
if(!TRUE%in%duplicated(data[,1])) rownames(data)=gsub(pattern = "-",replacement = ".",as.character(data[,1]))
## Keep only the row which are in the count table
ind = which(rownames(data)%in%colnames(counts))
data = as.data.frame(data[ind,])
colnames(data) = names
## Replace "-" by "."
if(ncol(data)>1 && nrow(data)>1){
ind_num = which(sapply(as.data.frame(data[,-1]),is.numeric)) + 1
if(length(ind_num)>0){
data_tmp =cbind( as.data.frame(apply(as.data.frame(data[,-ind_num]),2,gsub,pattern = "-",replacement = ".")),data[,ind_num])
#data_tmp =cbind( as.data.frame(as.data.frame(data[,-ind_num])),data[,ind_num])
colnames(data_tmp) = c(colnames(data)[-ind_num],colnames(data)[ind_num])
data = data_tmp
}
if(length(ind_num)==0){data = as.data.frame(apply(data,2,gsub,pattern = "-",replacement = "."))}
}
values$TargetWorking = as.data.frame(data)
values$visTarget = FALSE
# ind_sel = Target_selection()
# if(length(ind))
# target = as.data.frame(apply(target,2,gsub,pattern = "-",replacement = "."))
#ord = order(rownames(data))
#data = data[ord,]
### A SUqPPRIMER
#rownamQes(data) <- colnames(counts)
# Percent annotated
# print(ind)
# print(colnames(counts))
# print(rownames(data))
values$labeled = length(ind)/length(colnames(counts))*100.0
}
# return(list(target = target, labeled=labeled))
})
### ###
##
## MASQUE ####
##
### ###
observeEvent(input$dir,{
inFiles <- input$dir
if (!is.null(inFiles)){
# values$fastq_names_only = unique(paste(values$fastq_names_only,inFiles$name))
values$paths_fastq_tmp = rbind(isolate(values$paths_fastq_tmp),inFiles)
values$fastq_names_only = isolate(unique(values$paths_fastq_tmp[,"name"]))
}
})
## Create a fasta file containing the contaminant
CreateFasta <- reactive({
seq = NULL
tmp = tempdir()
fastaName = paste(tmp,paste(basename(file_path_sans_ext(json_name)),"_contaminant.fasta",sep=""),sep = .Platform$file.sep)
if(!file.exists(fastaName)) file.create(fastaName,showWarnings=FALSE)
if(input$PairedOrNot=="y"){seq =paste("\n>Seq1\n",input$R1primer,"\n \n",">Seq2\n",input$R2primer,sep="")}
if(input$PairedOrNot=="n"){seq =paste("\n>Seq1\n",input$primerSingle, sep="")}
if(!is.null(seq)){
known_adaptators=">poly-A
AAAAAAAAAAAAAAAAAAAA
>poly-C
CCCCCCCCCCCCCCCCCCCC
>poly-G
GGGGGGGGGGGGGGGGGGGG
>poly-T
TTTTTTTTTTTTTTTTTTTT
>Adapter 1
GATCGGAAGAGCTCGTATGCCGTCTTCTGCTTG
>Adapter 2
ACACTCTTTCCCTACACGACGCTCTTCCGATCT
>PCR Primer 1
AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCT
>PCR Primer 2
CAAGCAGAAGACGGCATACGAGCTCTTCCGATCT
>Genomic DNA Sequencing Primer
ACACTCTTTCCCTACACGACGCTCTTCCGATCT
>PCR Primer 1
AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCT
>PCR Primer 2
CAAGCAGAAGACGGCATACGAGCTCTTCCGATCT"
seq = paste(known_adaptators, seq, sep="")
write(seq, file=fastaName)
}
})
## Action with submit button
MasqueSubmit <- eventReactive(input$submit,{
galaxyAlertfile=paste(values$curdir,"www","galaxy_pasteur_alert.txt",sep= .Platform$file.sep)
galaxyAlert = NULL
#activate check_mail
CMP = CheckMasque(input, values,check_mail = TRUE)
Error = CMP$Error
isJSONalreadyExist = file.exists(paste(values$curdir,"www","masque","doing",basename(json_name),sep= .Platform$file.sep))
if(is.null(Error) && !isJSONalreadyExist)
{
CreateFasta()
values$num = 1
tmp = tempdir()
# home <- normalizePath("~")
home <- ""
# path_glob = file.path(home, paste(unlist(dir()$path[-1]), collapse = .Platform$file.sep))
## Paired-end
if(input$PairedOrNot=="y"){
cmp = 0
nfiles = length(values$R1fastQ)+length(values$R2fastQ)
withProgress(message = 'Uploading files...', value = 0, {
pathToR1 = paste(tmp,"Masque_files_R1",sep=.Platform$file.sep)
pathToR2 = paste(tmp,"Masque_files_R2",sep=.Platform$file.sep)
if(dir.exists(pathToR1)){file.remove(list.files(pathToR1,full.names =TRUE))} else dir.create(pathToR1)
if(dir.exists(pathToR2)){file.remove(list.files(pathToR2,full.names =TRUE))} else dir.create(pathToR2)
for(i in values$R1fastQ){
ind=which(i==values$paths_fastq_tmp[,"name"])[1]
file.rename(from=values$paths_fastq_tmp[,"datapath"][ind], to=paste(tmp,"Masque_files_R1",i,sep= .Platform$file.sep))
cmp = cmp +1
incProgress(cmp/nfiles, detail = "Forward fastq files...")