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server.R
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server <- function(input, output, session) {
#use_python("/opt/conda39/envs/pyscenic/bin/python") #environment containing phate
source("global.R", local=TRUE)
source("addPeak2GeneLinks_shiny.R")
options(shiny.maxRequestSize=100*1024^3) # 2GB limit in the online version
session$sendCustomMessage("handler_disableTabs", "sidebarMenu") # disable all tab panels (except Data Input) until files are uploaded
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " GENE REGULATORY NETWORK\nANALYSIS", " UTILITY OPTIONS")) #enable GRN tab only for RNA
hideTab(inputId="grnTabPanel", target="scATAC-seq", session = session)
hideAllLoaders() # helper function (in global.R) that initially hides all loaders
metaD <- reactiveValues(my_project_name="-", all_lin="0")
#------------------Upload tab--------------------------------
observeEvent(input$uploadCountMatrixConfirm, {
if(!is.null(proj_default) | !is.null(seurat_object))
{
showModal(modal_confirm)
}
else
{
session$sendCustomMessage("handler_disableTabs", "sidebarMenu")
session$sendCustomMessage("handler_disableAllButtons", "uploadCountMatrixConfirm")
tryCatch({
showModal(modalDialog(div('Data upload in progress. Please wait...', style='color:#ffffff; background-color:#222d32;'), footer = NULL, style = 'font-size:20px; text-align:center;position:absolute;')) #position:absolute;top:50%;left:50%
# Create the user directory for the input and output of the analysis
metaD$my_project_name <- input$uploadCountMatrixprojectID
minimum_cells <<- input$uploadCountMatrixminCells
minimum_features <<- input$uploadCountMatrixminFeatures
organism <<- input$uploadCountMatrixRadioSpecies
userId <- session$token
user_dir <<- paste0("./usr_temp/", userId, metaD$my_project_name, gsub(pattern = "[ ]|[:]", replacement = "_", x = paste0("_", Sys.time())))
dir.create(user_dir)
file.copy(from = input$countMatrix$datapath, to = paste0(user_dir, "/countMatrix.txt"), overwrite = TRUE)
testMatrix <- read.table(paste0(user_dir, "/countMatrix.txt"))
seurat_object <<- CreateSeuratObject(counts = testMatrix, project = metaD$my_project_name, min.cells = as.numeric(minimum_cells), min.features = as.numeric(minimum_features))
init_seurat_object <<- CreateSeuratObject(counts = testMatrix, project = metaD$my_project_name, min.cells = as.numeric(minimum_cells), min.features = as.numeric(minimum_features))
if(organism == "mouse")
{
seurat_object[["percent.mt"]] <<- PercentageFeatureSet(seurat_object, pattern = "^mt-")
init_seurat_object[["percent.mt"]] <<- PercentageFeatureSet(init_seurat_object, pattern = "^mt-")
}
else
{
seurat_object[["percent.mt"]] <<- PercentageFeatureSet(seurat_object, pattern = "^MT-")
init_seurat_object[["percent.mt"]] <<- PercentageFeatureSet(init_seurat_object, pattern = "^MT-")
}
updateMetadata()
updateSelInpColor()
updateGeneSearchFP()
updateQC_choices()
updateMaxHVGs()
updatePCs_selection(10)
updateUtilitiesAssays()
disableTabsATAC()
#update signature text area
if(organism == "human")
updateTextAreaInput(session, inputId="findMarkersSignatureMembers", placeholder = "PRG4\nTSPAN15\nCOL22A1\nHTRA4")
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " QUALITY CONTROL", " DATA NORMALIZATION\n& SCALING"))
}, error = function(e) {
print(paste("Error : ", e))
session$sendCustomMessage("handler_alert", "Data Input error. Please, refer to the help pages for input format.")
}, finally = { # with or without error
removeModal()
Sys.sleep(1) # giving some time for rendering, for smoother transition
session$sendCustomMessage("handler_enableAllButtons", "uploadCountMatrixConfirm")
})
}
})
observeEvent(input$upload10xExampleRNACountMatrixConfirm, {
if(!is.null(proj_default) | !is.null(seurat_object))
{
showModal(modal_confirm)
}
else
{
session$sendCustomMessage("handler_disableTabs", "sidebarMenu")
session$sendCustomMessage("handler_disableAllButtons", "upload10xExampleRNACountMatrixConfirm")
tryCatch({
showModal(modalDialog(div('Data upload in progress. Please wait...', style='color:#ffffff; background-color:#222d32;'), footer = NULL, style = 'font-size:20px; text-align:center;position:absolute;')) #position:absolute;top:50%;left:50%
# Create the user directory for the input and output of the analysis
metaD$my_project_name <- input$uploadCountMatrixprojectID
minimum_cells <<- input$uploadCountMatrixminCells
minimum_features <<- input$uploadCountMatrixminFeatures
organism <<- "human"
userId <- session$token
user_dir <<- paste0("./usr_temp/", userId, metaD$my_project_name, gsub(pattern = "[ ]|[:]", replacement = "_", x = paste0("_", Sys.time())))
dir.create(user_dir)
testMatrix <- read.table("exampleRNA_matrix/exampleMatrix.txt")
seurat_object <<- CreateSeuratObject(counts = testMatrix, project = metaD$my_project_name, min.cells = as.numeric(minimum_cells), min.features = as.numeric(minimum_features))
init_seurat_object <<- CreateSeuratObject(counts = testMatrix, project = metaD$my_project_name, min.cells = as.numeric(minimum_cells), min.features = as.numeric(minimum_features))
seurat_object[["percent.mt"]] <<- PercentageFeatureSet(seurat_object, pattern = "^MT-")
init_seurat_object[["percent.mt"]] <<- PercentageFeatureSet(init_seurat_object, pattern = "^MT-")
updateMetadata()
updateSelInpColor()
updateGeneSearchFP()
updateQC_choices()
updateMaxHVGs()
updatePCs_selection(10)
updateUtilitiesAssays()
disableTabsATAC()
#update signature text area
if(organism == "human")
updateTextAreaInput(session, inputId="findMarkersSignatureMembers", placeholder = "PRG4\nTSPAN15\nCOL22A1\nHTRA4")
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " QUALITY CONTROL", " DATA NORMALIZATION\n& SCALING"))
}, error = function(e) {
print(paste("Error : ", e))
session$sendCustomMessage("handler_alert", "Data Input error. Please, refer to the help pages for input format.")
}, finally = { # with or without error
removeModal()
Sys.sleep(1) # giving some time for rendering for smoother transition
session$sendCustomMessage("handler_enableAllButtons", "upload10xExampleRNACountMatrixConfirm")
})
}
})
observeEvent(input$upload10xRNAConfirm, {
if(!is.null(proj_default) | !is.null(seurat_object))
{
showModal(modal_confirm)
}
else
{
session$sendCustomMessage("handler_disableTabs", "sidebarMenu")
session$sendCustomMessage("handler_disableAllButtons", "upload10xRNAConfirm")
tryCatch({
showModal(modalDialog(div('Data upload in progress. Please wait...', style='color:#ffffff; background-color:#222d32;'), footer = NULL, style = 'font-size:20px; text-align:center;position:absolute;')) #position:absolute;top:50%;left:50%
metaD$my_project_name <- input$upload10xRNAprojectID
minimum_cells <<- input$upload10xRNAminCells
minimum_features <<- input$upload10xRNAminFeatures
organism <<- input$upload10xRNARadioSpecies
userId <- session$token
user_dir <<- paste0("./usr_temp/", userId, metaD$my_project_name, gsub(pattern = "[ ]|[:]", replacement = "_", x = paste0("_", Sys.time())))
dir.create(user_dir)
file.copy(from = input$matrix$datapath, to = paste0(user_dir, "/matrix.mtx.gz"), overwrite = TRUE) #,input$matrix$name
file.copy(from = input$barcodes$datapath, to = paste0(user_dir, "/barcodes.tsv.gz"), overwrite = TRUE) #, input$barcodes$name
file.copy(from = input$genes$datapath, to = paste0(user_dir, "/features.tsv.gz"), overwrite = TRUE) #, input$genes$name
seurat_data <- Read10X(user_dir)
seurat_object <<- CreateSeuratObject(counts = seurat_data, project = metaD$my_project_name, min.cells = as.numeric(minimum_cells), min.features = as.numeric(minimum_features))
init_seurat_object <<- CreateSeuratObject(counts = seurat_data, project = metaD$my_project_name, min.cells = as.numeric(minimum_cells), min.features = as.numeric(minimum_features))
if(organism == "mouse")
{
seurat_object[["percent.mt"]] <<- PercentageFeatureSet(seurat_object, pattern = "^mt-")
init_seurat_object[["percent.mt"]] <<- PercentageFeatureSet(init_seurat_object, pattern = "^mt-")
}
else
{
seurat_object[["percent.mt"]] <<- PercentageFeatureSet(seurat_object, pattern = "^MT-")
init_seurat_object[["percent.mt"]] <<- PercentageFeatureSet(init_seurat_object, pattern = "^MT-")
}
updateMetadata()
updateSelInpColor()
updateGeneSearchFP()
updateQC_choices()
updateMaxHVGs()
updatePCs_selection(10)
updateUtilitiesAssays()
disableTabsATAC()
#update signature text area
if(organism == "human")
updateTextAreaInput(session, inputId="findMarkersSignatureMembers", placeholder = "PRG4\nTSPAN15\nCOL22A1\nHTRA4")
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " QUALITY CONTROL", " DATA NORMALIZATION\n& SCALING"))
}, error = function(e) {
print(paste("Error : ", e))
session$sendCustomMessage("handler_alert", "Data Input error. Please, refer to the help pages for input format.")
}, finally = { # with or without error
removeModal()
Sys.sleep(1) # giving some time for rendering for smoother transition
session$sendCustomMessage("handler_enableAllButtons", "upload10xRNAConfirm")
})
}
})
observeEvent(input$upload10xExampleRNA10xFilesConfirm, {
if(!is.null(proj_default) | !is.null(seurat_object))
{
showModal(modal_confirm)
}
else
{
session$sendCustomMessage("handler_disableTabs", "sidebarMenu") # disable all tab panels (except Data Input) until files are uploaded
session$sendCustomMessage("handler_disableAllButtons", "upload10xExampleRNA10xFilesConfirm")
tryCatch({
showModal(modalDialog(div('Data upload in progress. Please wait...', style='color:#ffffff; background-color:#222d32;'), footer = NULL, style = 'font-size:20px; text-align:center;position:absolute;')) #position:absolute;top:50%;left:50%
metaD$my_project_name <- "PBMC3k"
minimum_cells <<- 3
minimum_features <<- 200
organism <<- "human"
userId <- session$token
user_dir <<- paste0("./usr_temp/", userId, metaD$my_project_name, gsub(pattern = "[ ]|[:]", replacement = "_", x = paste0("_", Sys.time())))
dir.create(user_dir)
seurat_data <- Read10X("exampleRNA_10xFiles/")
seurat_object <<- CreateSeuratObject(counts = seurat_data, project = metaD$my_project_name, min.cells = as.numeric(minimum_cells), min.features = as.numeric(minimum_features))
init_seurat_object <<- CreateSeuratObject(counts = seurat_data, project = metaD$my_project_name, min.cells = as.numeric(minimum_cells), min.features = as.numeric(minimum_features))
seurat_object[["percent.mt"]] <<- PercentageFeatureSet(seurat_object, pattern = "^MT-")
init_seurat_object[["percent.mt"]] <<- PercentageFeatureSet(init_seurat_object, pattern = "^MT-") #as.double(sprintf("%.3f", as.double([email protected]$percent.mt)))
[email protected]$percent.mt <<- as.double([email protected]$percent.mt)
[email protected]$percent.mt <<- as.double([email protected]$percent.mt)
updateMetadata()
updateSelInpColor()
updateGeneSearchFP()
updateQC_choices()
updateMaxHVGs()
updatePCs_selection(10)
updateUtilitiesAssays()
disableTabsATAC()
#update signature text area
if(organism == "human")
updateTextAreaInput(session, inputId="findMarkersSignatureMembers", placeholder = "PRG4\nTSPAN15\nCOL22A1\nHTRA4")
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " QUALITY CONTROL", " DATA NORMALIZATION\n& SCALING"))
}, error = function(e) {
print(paste("Error : ", e))
session$sendCustomMessage("handler_alert", "Data Input error. Please, refer to the help pages for input format.")
}, finally = { # with or without error
removeModal()
Sys.sleep(1) # giving some time for rendering for smoother transition
session$sendCustomMessage("handler_enableAllButtons", "upload10xExampleRNA10xFilesConfirm")
})
}
})
observeEvent(input$uploadSeuratRdsConfirm, {
if(!is.null(proj_default) | !is.null(seurat_object))
{
showModal(modal_confirm)
}
else
{
session$sendCustomMessage("handler_disableAllButtons", "uploadSeuratRdsConfirm")
tryCatch({
showModal(modalDialog(div('Data upload in progress. Please wait...', style='color:#ffffff; background-color:#222d32;'), footer = NULL, style = 'font-size:20px; text-align:center;position:absolute;')) #position:absolute;top:50%;left:50%
#seurat_object <<- readRDS(input$uploadRdsFile$datapath)
#init_seurat_object <<- readRDS(input$uploadRdsFile$datapath)
userId <- session$token
user_dir <<- paste0("./usr_temp/", userId, gsub(pattern = "[ ]|[:]", replacement = "_", x = paste0("_", Sys.time())))
dir.create(user_dir)
file.copy(from = input$uploadRdsFile$datapath, to = paste0(user_dir, "/init_seurat_object.RDS"), overwrite = TRUE)
seurat_object <<- readRDS(paste0(user_dir, "/init_seurat_object.RDS"))
init_seurat_object <<- readRDS(paste0(user_dir, "/init_seurat_object.RDS"))
organism <<- input$uploadRdsRadioSpecies
print(seurat_object)
print(init_seurat_object)
#checking slots and enabling tabs
if(is.null([email protected]))
print("Metadata table is missing")
else
{
disableTabsATAC()
updateMetadata()
updateSelInpColor()
updateGeneSearchFP()
updateQC_choices()
updateMaxHVGs()
updatePCs_selection(10)
updateUtilitiesAssays()
updateRegressOut()
#CHECK percent.mt
if(is.null([email protected]$percent.mt))
{
#calculate percent.mt and enable
if(organism == "mouse")
{
seurat_object[["percent.mt"]] <<- PercentageFeatureSet(seurat_object, pattern = "^mt-")
init_seurat_object[["percent.mt"]] <<- PercentageFeatureSet(init_seurat_object, pattern = "^mt-")
}
else
{
seurat_object[["percent.mt"]] <<- PercentageFeatureSet(seurat_object, pattern = "^MT-")
init_seurat_object[["percent.mt"]] <<- PercentageFeatureSet(init_seurat_object, pattern = "^MT-")
}
}
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " UTILITY OPTIONS", " QUALITY CONTROL", " GENE REGULATORY NETWORK\nANALYSIS"))
#CHECK @data, VariableFeatures, @scale.data
if( !is.null(seurat_object@assays$RNA@data) & length(VariableFeatures(seurat_object)) != 0 & !is.null(seurat_object@[email protected]) )
{
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " DATA NORMALIZATION\n& SCALING"))
shinyjs::show("hvgScatter_loader")
#plot highly variable genes
#--Rendering
output$hvgScatter <- renderPlotly({ # tooltip
plot1 <- VariableFeaturePlot(seurat_object)
varplot <- plot1$data
varplot$gene <- rownames(varplot)
varplot$colors[varplot$colors == "yes"] <- paste0("Highly Variable genes(", length(VariableFeatures(seurat_object)), ")")
varplot$colors[varplot$colors == "no"] <- paste0("Not Variable genes(", length(rownames(seurat_object)) - length(VariableFeatures(seurat_object)), ")")
print("before method")
print(seurat_object@commands$FindVariableFeatures.RNA$selection.method)
if(seurat_object@commands$FindVariableFeatures.RNA$selection.method == "vst"){
p <- ggplot(varplot, aes(x=log10(mean), y=variance.standardized, color=colors, text = paste0("log10(mean expression): ", log10(mean),
"\nstandardized variance: ", variance.standardized,
"\ngene: ", gene)
)) +
geom_point() +
theme_bw() +
scale_color_manual(
values = c("red", "black")
)+
labs(x="Average Expression", y="Standardized Variance", color="")
} else {
p <- ggplot(varplot, aes(x=mean, y=dispersion, color=colors, text = paste0("mean expression: ", mean,
"\ndispersion: ", dispersion,
"\ngene: ", gene)
)) +
geom_point() +
theme_bw() +
scale_color_manual(
values = c("red", "black")
)+
labs(x="Average Expression", y="Dispersion", color="")
}
gp <- plotly::ggplotly(p, tooltip = "text")
gp
})
output$hvgTop10Stats <- renderPrint(
{
top10hvgs <- head(VariableFeatures(seurat_object), 10)
cat("\nTop10 varibale features:", c(top10hvgs[1:10]))
})
#--End Rendering
}
#CHECK @reductions$pca and other dimensionality reductions
if( !is.null(seurat_object@reductions$pca) )
{
#print 2 plots
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " PCA/LSI", " ADDITIONAL DIMENSIONALITY\nREDUCTION METHODS", " FEATURE INSPECTION"))
shinyjs::show("elbowPlotPCA_loader")
shinyjs::show("PCAscatter_loader")
#--Rendering
output$elbowPlotPCA <- renderPlotly(
{
plot1 <- ElbowPlot(seurat_object, ndims = ncol(seurat_object@reductions$pca))
plot1_data <- plot1$data
colnames(plot1_data)[1] <- "PC"
colnames(plot1_data)[2] <- "SD"
p <- ggplot(plot1_data, aes(x=PC, y=SD))+
geom_point() +
theme_bw() +
labs(x="PC", y="Standard Deviation")
gp <- plotly::ggplotly(p, tooltip = c("x", "y"))
print(gp)
}
)
output$PCAscatter <- renderPlotly(
{
#prepare metadata
meta <- [email protected]
meta$Cell_id <- rownames(meta)
meta <- meta[, ]#meta[, c('Cell_id', 'seurat_clusters', 'orig.ident')]
reduc_data <- data.frame()
#prepare colors
cols = colorRampPalette(brewer.pal(12, "Paired"))(1)
#umap data frame
seurat_object_reduc <- as.data.frame(seurat_object@[email protected])
seurat_object_reduc <- seurat_object_reduc[, c(1:ncol(seurat_object_reduc))]
seurat_object_reduc$Cell_id <- rownames(seurat_object_reduc)
reduc_data <- left_join(seurat_object_reduc, meta)
p <- ggplot(data=reduc_data, aes_string(x="PC_1", y="PC_2", fill="orig.ident")) +
geom_point(size=2, shape=19, stroke=0)+
scale_fill_manual(values = cols)+
scale_size()+
theme_bw() +
theme(axis.text.x = element_text(face = "bold", color = "black", size = 25, angle = 0),
axis.text.y = element_text(face = "bold", color = "black", size = 25, angle = 0),
axis.title.y = element_text(face = "bold", color = "black", size = 25),
axis.title.x = element_text(face = "bold", color = "black", size = 25),
legend.text = element_text(face = "bold", color = "black", size = 9),
legend.title = element_text(face = "bold", color = "black", size = 9),
legend.position="right",
title = element_text(face = "bold", color = "black", size = 25, angle = 0)) +
labs(x="PC 1", y="PC 2", title = "", fill="Color")
print(plotly::ggplotly(p))
}
)
#--End rendering
#CHECK $seurat@reductions
updateUmapTypeChoices(names(seurat_object@reductions))
}
#CHECK $seurat_clusters
if( !is.null([email protected]$seurat_clusters) )
{
updateInputLRclusters()
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " CLUSTERING", " MARKERS' IDENTIFICATION", " CELL CYCLE PHASE ANALYSIS", " DOUBLETS' DETECTION",
" LIGAND - RECEPTOR\nANALYSIS"))
#--print cluster table
updateClusterTab()
#--
if(!is.null(seurat_object@reductions$umap))
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " TRAJECTORY ANALYSIS"))
}
#CHECK Seurat@misc$markers
if( !is.null(seurat_object@misc$markers) )
{
seurat_object@misc$markers <- seurat_object@misc$markers[, c(7, 6, 1:5)]
output$findMarkersTable <- renderDataTable(seurat_object@misc$markers, options = list(pageLength = 20), filter = 'top', rownames = FALSE)
markers_logFCBase <<- colnames(seurat_object@misc$markers)[grep(pattern = "avg_log", x = colnames(seurat_object@misc$markers))]
export_markerGenes_RNA <<- seurat_object@misc$markers
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " FUNCTIONAL/MOTIF\nENRICHMENT ANALYSIS"))
}
}
}, error = function(e) {
print(paste("Error : ", e))
session$sendCustomMessage("handler_alert", "Data Input error. Please, refer to the help pages for input format.")
}, finally = { # with or without error
removeModal()
Sys.sleep(1) # giving some time for rendering for smoother transition
session$sendCustomMessage("handler_enableAllButtons", "uploadSeuratRdsConfirm")
}
)
}
})
observeEvent(input$upload10xATACConfirm, {
if(!is.null(proj_default) | !is.null(seurat_object))
{
showModal(modal_confirm)
}
else
{
session$sendCustomMessage("handler_disableTabs", "sidebarMenu") # disable all tab panels (except Data Input) until files are uploaded
session$sendCustomMessage("handler_disableAllButtons", "upload10xATACConfirm")
tryCatch({
showModal(modalDialog(div('Data upload in progress. Please wait...', style='color:#ffffff; background-color:#222d32;'), footer = NULL, style = 'font-size:20px; text-align:center;position:absolute;')) #position:absolute;top:50%;left:50%
#user dir creation
projectNameATAC <<- input$uploadATACprojectID
userId <- session$token
user_dir <<- paste0("./usr_temp/", userId, projectNameATAC, gsub(pattern = "[ ]|[:]", replacement = "_", x = paste0("_", Sys.time())))
dir.create(user_dir)
file.copy(from = input$uploadATACArrow$datapath, to = paste0(user_dir, "/arrowFile.arrow"), overwrite = TRUE)
dir.create(paste0(user_dir, "/default"))
#select genome version and organism
addArchRGenome(input$upload10xATACRadioSpecies)
if(length(grep("mm", input$upload10xATACRadioSpecies)) == 1)
{
organism <<- "mouse"
}
else
{
organism <<- "human"
}
addArchRThreads(threads = as.numeric(input$upload10xATACThreads))
########################################
######### Create Arch Project ##########
########################################
proj_default <<- ArchRProject(
ArrowFiles = paste0(user_dir, "/arrowFile.arrow"),
outputDirectory = paste0(user_dir, "/default"),
copyArrows = FALSE #This is recommended so that if you modify the Arrow files you have an original copy for later usage.
)
saveArchRProject(proj_default)
print("Project saved")
updateMetadataATAC()
addArchRThreads(threads = as.numeric(as.numeric(input$upload10xATACThreads)))
updateSelectizeInput(session, "visualizeTracksGene", choices = unique(proj_default@geneAnnotation$genes$symbol), server = T)
disableTabsRNA()
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " QUALITY CONTROL"))
}, error = function(e) {
print(paste("Error : ", e))
session$sendCustomMessage("handler_alert", "Data Input error. Please, refer to the help pages for input format.")
}, finally = { # with or without error
removeModal()
Sys.sleep(1) # giving some time for rendering for smoother transition
session$sendCustomMessage("handler_enableAllButtons", "upload10xATACConfirm")
})
}
})
observeEvent(input$upload10xExampleATACConfirm, {
if(!is.null(proj_default) | !is.null(seurat_object))
{
showModal(modal_confirm)
}
else
{
session$sendCustomMessage("handler_disableTabs", "sidebarMenu") # disable all tab panels (except Data Input) until files are uploaded
session$sendCustomMessage("handler_disableAllButtons", "upload10xExampleATACConfirm")
tryCatch({
showModal(modalDialog(div('Data upload in progress. Please wait...', style='color:#ffffff; background-color:#222d32;'), footer = NULL, style = 'font-size:20px; text-align:center;position:absolute;')) #position:absolute;top:50%;left:50%
#user dir creation
projectNameATAC <<- "example"
userId <- session$token
user_dir <<- paste0("./usr_temp/", userId, projectNameATAC, gsub(pattern = "[ ]|[:]", replacement = "_", x = paste0("_", Sys.time())))
dir.create(user_dir)
dir.create(paste0(user_dir, "/default"))
#select genome version and organism
addArchRGenome("hg19")
#set number of threads
addArchRThreads(threads = as.numeric(input$upload10xATACThreads))
########################################
######### Create Arch Project ##########
########################################
proj_default <<- ArchRProject(
ArrowFiles = "exampleATAC/arrowFile.arrow",
outputDirectory = paste0(user_dir, "/default"),
copyArrows = FALSE #This is recommended so that if you modify the Arrow files you have an original copy for later usage.
)
saveArchRProject(proj_default)
print("Project saved")
updateMetadataATAC()
addArchRThreads(threads = as.numeric(input$upload10xATACThreads))
updateSelectizeInput(session, "visualizeTracksGene", choices = unique(proj_default@geneAnnotation$genes$symbol), server = T)
disableTabsRNA()
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " QUALITY CONTROL"))
}, error = function(e) {
print(paste("Error : ", e))
session$sendCustomMessage("handler_alert", "Data Input error. Please, refer to the help pages for input format.")
}, finally = { # with or without error
removeModal()
Sys.sleep(1) # giving some time for rendering for smoother transition
session$sendCustomMessage("handler_enableAllButtons", "upload10xExampleATACConfirm")
})
}
})
output$uploadMetadataExport <- downloadHandler(
filename = function() {
paste("metadataTableATAC-", Sys.Date(), ".txt", sep="")
},
content = function(file) {
write.table(export_metadata_ATAC, file, sep = "\t", quote = F, row.names = F)
})
output$uploadMetadataExportRNA <- downloadHandler(
filename = function() {
paste("metadataTableRNA-", Sys.Date(), ".txt", sep="")
},
content = function(file) {
write.table(export_metadata_RNA, file, sep = "\t", quote = F, row.names = F)
})
#------------------Utilities------------------------------------------
#save rna object as rds file
output$utilitiesConfirmExport1 <- downloadHandler(
filename = function() {
paste("processed_seurat_object-", Sys.Date(), ".RDS", sep="")
},
content = function(file) {
saveRDS(seurat_object, file)
})
output$utilitiesConfirmExport2 <- downloadHandler(
filename = function() {
paste("processed_seurat_object-", Sys.Date(), ".RDS", sep="")
},
content = function(file) {
saveRDS(seurat_object, file)
})
output$utilitiesConfirmExport <- downloadHandler(
filename = function() {
paste("processed_seurat_object-", Sys.Date(), ".RDS", sep="")
},
content = function(file) {
saveRDS(seurat_object, file)
})
#rename-merge-delete clusters
observeEvent(input$utilitiesConfirmRename, {
if(!identical(seurat_object, NULL) & input$utilitiesRenameOldName != "-" & input$utilitiesRenameNewName != "")
{
showModal(modal_confirm_utilities_rename)
}
})
observeEvent(input$utilitiesConfirmDelete, {
if(!identical(seurat_object, NULL) & input$utilitiesDeleteCluster != "-")
{
showModal(modal_confirm_utilities_delete)
}
})
#change active clusters
observeEvent(input$utilitiesConfirmChangeCluster, {
tryCatch({
seurat_object$seurat_clusters <<- [email protected][, input$utilitiesActiveClusters]
Idents(seurat_object) <<- seurat_object$seurat_clusters
updateInputLRclusters()
updateMetadata()
updateClusterTab()
shinyalert(title = "Active clustering column changed succesfully!", type = "success")
}, error = function(e) {
print(paste("Error : ", e))
shinyalert(title = "There was an error with changing the clustering column.", type = "error")
}, finally = {
})
})
#change active assay
observeEvent(input$utilitiesConfirmChangeAssay, {
tryCatch({
DefaultAssay(seurat_object) <<- input$utilitiesActiveAssay
updateGeneSearchFP()
shinyalert(title = "Default assay was changed succesfully!", type = "success")
}, error = function(e) {
print(paste("Error : ", e))
shinyalert(title = "There was an error with changing the default assay.", type = "error")
}, finally = {
})
#print("def assay")
#print(DefaultAssay(seurat_object))
})
observeEvent(input$utilitiesPlotCommands, {
if(!is.null(seurat_object))
{
if(length(seurat_object@commands) > 0)
{
output$history <- renderPrint(
{
for(i in 1:length(seurat_object@commands))
{
print(seurat_object@commands[[i]])
print("-------------------------------------------------------------")
}
})
}
else
{
Sys.sleep(1)
shinyalert("Error. No command history was found.", type = "error")
}
}
else
{
Sys.sleep(1)
shinyalert("Error. No project is loaded.", type = "error")
}
})
#------------------Quality Control tab--------------------------------
observeEvent(input$qcDisplay, {
start.time <- Sys.time()
print(paste0("!!!!-----DisplayQC_start-----", start.time))
session$sendCustomMessage("handler_disableAllButtons", "qcDisplay")
tryCatch({
if (identical(init_seurat_object, NULL)) session$sendCustomMessage("handler_alert", "Please, upload some data via the DATA INPUT tab first.")
else{
shinyjs::show("nFeatureViolin_loader")
shinyjs::show("totalCountsViolin_loader")
shinyjs::show("mitoViolin_loader")
shinyjs::show("genesCounts_loader")
shinyjs::show("mtCounts_loader")
showModal(modalDialog(div('Quality control in progress. This operation may take a few minutes for large datasets. Please wait...', style='color:#ffffff; background-color:#222d32;'),
footer = NULL, style = 'font-size:20px; text-align:center;position:absolute;')) #position:absolute;top:50%;left:50%
output$nFeatureViolin <- renderPlotly(
{
p <- VlnPlot(init_seurat_object, features = c("nFeature_RNA"), pt.size = 0, group.by = "orig.ident",
cols = colorRampPalette(brewer.pal(12, "Paired"))(length(unique([email protected][, 'orig.ident'])))) +
theme_bw() +
geom_hline(yintercept=c(as.numeric(input$minUniqueGenes), as.numeric(input$maxUniqueGenes)), linetype="dashed", color = "red", size=1) +
theme(
plot.title = element_blank(),
axis.title.x = element_blank(),
legend.position = "none") +
labs(title = "", y="Genes detected/cell")
p_temp <- VlnPlot(init_seurat_object, features = c("nFeature_RNA"), pt.size = 0, group.by = "orig.ident",
cols = colorRampPalette(brewer.pal(12, "Paired"))(length(unique([email protected][, 'orig.ident'])))) +
theme_bw() +
geom_hline(yintercept=c(as.numeric(input$minUniqueGenes), as.numeric(input$maxUniqueGenes)), linetype="dashed", color = "red", size=1) +
theme(
plot.title = element_blank(),
axis.title.x = element_blank(),
legend.position = "none") +
labs(title = "", y="Genes detected/cell")
plotly::ggplotly(p + ylim(min(init_seurat_object$nFeature_RNA)-1, max(init_seurat_object$nFeature_RNA)+2), tooltip = c("x", "y"))
}
)
output$totalCountsViolin <- renderPlotly(
{
p <- VlnPlot(init_seurat_object, features = c("nCount_RNA"), pt.size = 0, group.by = "orig.ident",
cols = colorRampPalette(brewer.pal(12, "Paired"))(length(unique([email protected][, 'orig.ident'])))) +
theme_bw() +
theme(
plot.title = element_blank(),
axis.title.x = element_blank(),
legend.position = "none")+
labs(title = "", y="Total counts/cell")
plotly::ggplotly(p, tooltip = c("x", "y"))
}
)
output$mitoViolin <- renderPlotly(
{
p <- VlnPlot(init_seurat_object, features = c("percent.mt"), pt.size = 0, group.by = "orig.ident",
cols = colorRampPalette(brewer.pal(12, "Paired"))(length(unique([email protected][, 'orig.ident'])))) +
theme_bw() +
#scale_y_continuous(labels = number_format(accuracy = 0.001)) +
geom_hline(yintercept= as.numeric(input$maxMtReads), linetype="dashed", color = "red", size=1) +
theme(
plot.title = element_blank(),
axis.title.x = element_blank(),
legend.position = "none")+
labs(title = "", y="% of reads mapped to mitochonrial genome/cell")
plotly::ggplotly(p, tooltip = c("x", "y")) #%>%
#layout(yaxis = list(hoverformat = ".2f"))
}
)
output$mtCounts <- renderPlotly(
{
p <- FeatureScatter(init_seurat_object, feature1 = "nCount_RNA", feature2 = "percent.mt", group.by = "orig.ident", raster = F,
cols = colorRampPalette(brewer.pal(12, "Paired"))(length(unique([email protected][, 'orig.ident']))))
gp <- plotly::ggplotly(p)
print(gp)
}
)
output$genesCounts <- renderPlotly(
{
p <- FeatureScatter(init_seurat_object, feature1 = "nCount_RNA", feature2 = "nFeature_RNA", group.by = "orig.ident", raster = F,
cols = colorRampPalette(brewer.pal(12, "Paired"))(length(unique([email protected][, 'orig.ident']))))
gp <- plotly::ggplotly(p)
print(gp)
}
)
output$cellStats <- renderPrint(
{
cat(paste0("Total number of cells: ", nrow([email protected])))
}
)
}
}, error = function(e) {
print(paste("Error : ", e))
session$sendCustomMessage("handler_alert", "The selected Quality Control arguments cannot produce meaningful visualizations.")
}, finally = {
removeModal()
end.time <- Sys.time()
time.taken <- as.numeric (end.time - start.time, units = "mins")
print(paste0("!!!!-----DisplayQC_end_Mins_taken-----", time.taken))
Sys.sleep(1)
session$sendCustomMessage("handler_enableAllButtons", "qcDisplay")
})
})
observeEvent(input$qcConfirm, {
start.time <- Sys.time()
print(paste0("!!!!-----QCFiltering_start-----", start.time))
session$sendCustomMessage("handler_disableAllButtons", "qcConfirm")
tryCatch({
if (identical(seurat_object, NULL)) session$sendCustomMessage("handler_alert", "Please, upload some data via the DATA INPUT tab first.")
else{
updateTabsetPanel(session, inputId = "qc_tabs_rna", selected = "Post-filtering plots")
showModal(modalDialog(div('Analysis in Progress. This operation may take several minutes, please wait...', style='color:#ffffff; background-color:#222d32;'), footer = NULL, style = 'font-size:20px; text-align:center;position:absolute;')) #position:absolute;top:50%;left:50%
shinyjs::show("filteredNFeatureViolin_loader")
shinyjs::show("filteredTotalCountsViolin_loader")
shinyjs::show("filteredMitoViolin_loader")
shinyjs::show("filteredGenesCounts_loader")
shinyjs::show("filteredMtCounts_loader")
qc_minFeatures <<- input$minUniqueGenes
qc_maxFeatures <<- input$maxUniqueGenes
qc_maxMtPercent <<- input$maxMtReads
seurat_object <<- subset(init_seurat_object, subset = nFeature_RNA > as.numeric(qc_minFeatures) & nFeature_RNA < as.numeric(qc_maxFeatures) & percent.mt < as.double(qc_maxMtPercent)) #filter object
output$filteredNFeatureViolin <- renderPlotly(
{
p <- VlnPlot(seurat_object, features = c("nFeature_RNA"), pt.size = 0, group.by = input$qcColorBy,
cols = colorRampPalette(brewer.pal(12, "Paired"))(length(unique([email protected][, input$qcColorBy])))) +
theme_bw() +
theme(
plot.title = element_blank(),
axis.title.x = element_blank(),
legend.position = "none") +
labs(title = "", y="Genes detected/cell")
plotly::ggplotly(p, tooltip = c("x", "y"))
}
)
output$filteredTotalCountsViolin <- renderPlotly(
{
p <- VlnPlot(seurat_object, features = c("nCount_RNA"), pt.size = 0, group.by = input$qcColorBy,
cols = colorRampPalette(brewer.pal(12, "Paired"))(length(unique([email protected][, input$qcColorBy])))) +
theme_bw() +
theme(
plot.title = element_blank(),
axis.title.x = element_blank(),
legend.position = "none")+
labs(title = "", y="Total counts/cell")
plotly::ggplotly(p, tooltip = c("x", "y"))
}
)
output$filteredMitoViolin <- renderPlotly(
{
p <- VlnPlot(seurat_object, features = c("percent.mt"), pt.size = 0, group.by = input$qcColorBy,
cols = colorRampPalette(brewer.pal(12, "Paired"))(length(unique([email protected][, input$qcColorBy])))) +
theme_bw() +
theme(
plot.title = element_blank(),
axis.title.x = element_blank(),
legend.position = "none")+
labs(title = "", y="% of reads mapped to mitochonrial genome/cell")
plotly::ggplotly(p, tooltip = c("x", "y"))
}
)
output$filteredMtCounts <- renderPlotly(
{
p <- FeatureScatter(seurat_object, feature1 = "nCount_RNA", feature2 = "percent.mt", group.by = input$qcColorBy, raster = F,
cols = colorRampPalette(brewer.pal(12, "Paired"))(length(unique([email protected][, input$qcColorBy]))))
gp <- plotly::ggplotly(p)
print(gp)
}
)
output$filteredGenesCounts <- renderPlotly(
{
p <- FeatureScatter(seurat_object, feature1 = "nCount_RNA", feature2 = "nFeature_RNA", group.by = input$qcColorBy, raster = F,
cols = colorRampPalette(brewer.pal(12, "Paired"))(length(unique([email protected][, input$qcColorBy]))))
gp <- plotly::ggplotly(p)
print(gp)
}
)
output$filteredCellStats <- renderPrint(
{
cat(paste0("\nTotal number of cells after filtering: ", nrow([email protected])))
}
)
updateSelInpColor()
session$sendCustomMessage("handler_disableTabs", "sidebarMenu")
updateMetadata()
cleanAllPlots(F) # fromDataInput -> FALSE
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " QUALITY CONTROL", " DATA NORMALIZATION\n& SCALING"))
}
}, error = function(e) {
print(paste("Error : ", e))
session$sendCustomMessage("handler_alert", "The selected Quality Control arguments cannot produce meaningful visualizations.")
}, finally = {
end.time <- Sys.time()
time.taken <- as.numeric (end.time - start.time, units = "mins")
print(paste0("!!!!-----QCfilter_end_Mins_taken-----", time.taken))
removeModal()
Sys.sleep(1)
session$sendCustomMessage("handler_enableAllButtons", "qcConfirm")
})
})
#ATAC qc
observeEvent(input$qcDisplayATAC, {
start.time <- Sys.time()
print(paste0("!!!!-----DisplayQC_start-----", start.time))
session$sendCustomMessage("handler_disableAllButtons", "qcDisplayATAC")
tryCatch({
if (identical(proj_default, NULL)) session$sendCustomMessage("handler_alert", "Please, upload some data via the DATA INPUT tab first.")
else{
showModal(modalDialog(div('Quality control metrics are prepared. Rendering mighr take several minutes for large datasets. Please wait...', style='color:#ffffff; background-color:#222d32;'), footer = NULL, style = 'font-size:20px; text-align:center;position:absolute;')) #position:absolute;top:50%;left:50%
shinyjs::show("TSS_plot_loader")
shinyjs::show("nFrag_plot_loader")
shinyjs::show("TSS_nFrag_plot_loader")
#TSS plot
p1 <- plotGroups(
ArchRProj = proj_default,
colorBy = "cellColData",
name = "TSSEnrichment",
plotAs = "violin",
alpha = 0.4,
addBoxPlot = TRUE
)
output$TSS_plot <- renderPlotly( expr = ggplot(p1$data, aes(x=x, y=y, fill=x)) + geom_violin() + theme_bw() + labs(y="TSS Enrichment"))
#nFrags plot
p2 <- plotGroups(
ArchRProj = proj_default,
colorBy = "cellColData",
name = "log10(nFrags)",
plotAs = "ridges"
)
output$nFrag_plot <- renderPlot( expr = ggplot(p2$data, aes(y=x, x=y, fill=x)) + geom_density_ridges() + theme_bw() + scale_y_discrete(expand = c(0, 0)) + labs(x="log10(nFrags)"),
width = 500, height = 500
)
#nFrags-TSS plot
df <- getCellColData(proj_default, select = c("log10(nFrags)", "TSSEnrichment"))
p4 <- ggPoint(
x = df[,1],
y = df[,2],
#size = 3,
#baseSize=30,
#legendSize=5,
#dpi=1200,
colorDensity = TRUE,
continuousSet = "sambaNight",
xlabel = "Log10 Unique Fragments",
ylabel = "TSS Enrichment",
xlim = c(log10(500), quantile(df[,1], probs = 0.99)),
ylim = c(0, quantile(df[,2], probs = 0.99))
) + geom_hline(yintercept = 4, lty = "dashed") + geom_vline(xintercept = 3, lty = "dashed")
output$TSS_nFrag_plot <- renderPlotly( expr = ggplotly(p4))
#cells
output$CellStatsATAC <- renderPrint(
{
cat(paste0("\nTotal number of cells after soft filtering: ", nrow(getCellColData(proj_default))))
}
)
session$sendCustomMessage("handler_enableTabs", c("sidebarMenu", " QUALITY CONTROL", " PCA/LSI"))
}
}, error = function(e) {
print(paste("Error : ", e))
session$sendCustomMessage("handler_alert", "The selected Quality Control arguments cannot produce meaningful visualizations.")
}, finally = {
end.time <- Sys.time()
time.taken <- as.numeric (end.time - start.time, units = "mins")
print(paste0("!!!!-----DisplayQC_end_Mins_taken-----", time.taken))
removeModal()
Sys.sleep(1)
session$sendCustomMessage("handler_enableAllButtons", "qcDisplayATAC")
})
})
#------------------Normalization tab--------------------------------
observeEvent(input$normalizeConfirm, {
start.time <- Sys.time()
print(paste0("!!!!-----Scaling_start-----", start.time))
session$sendCustomMessage("handler_log", " ### Starting normalization procedure ###")
session$sendCustomMessage("handler_disableAllButtons", "normalizeConfirm")
tryCatch({
if (identical(seurat_object, NULL)) session$sendCustomMessage("handler_alert", "Please, upload some data via the DATA INPUT tab first.")
else{
shinyjs::show("hvgScatter_loader")
showModal(modalDialog(div('Normalization and scaling in progress. This operation will be dramatically slowed down if all genes are selected.