app.R

# Load packages --------
library(shiny)
library(shinythemes)
library(Seurat)
library(dplyr)
library(sctransform)
library(ggplot2)
library(viridis)
library(stringr)
library(plotly)
library(BiocManager)
library(shinydashboard)
library(shinyjs)
library(DT)          
library(RColorBrewer) 
library(MAST)     
library(data.table)
library(clusterProfiler)
library(org.Hs.eg.db) 
library(tools)
library(PANTHER.db)


### ----------------------------- User interface -----------------------------------------------------

## HEADER --------
useShinyjs()
header <- dashboardHeader(tags$li(class="dropdown",
                                  conditionalPanel(condition="input.tabs == 'visu_item'",
                                                   tags$p(style="color:white;font-size:25px;margin-right:20px","- Visualization -")), 
                                  conditionalPanel(condition="input.tabs == 'heatmap_item'",
                                                   tags$p(style="color:white;font-size:25px;margin-right:20px","- HeatMap -")),
                                  conditionalPanel(condition="input.tabs == 'genes_item'",
                                                   tags$p(style="color:white;font-size:25px;margin-right:20px","- Genes -")),
                                  conditionalPanel(condition="input.tabs == 'compare_item'",
                                                   tags$p(style="color:white;font-size:25px;margin-right:20px","- Compare -")),
                                  conditionalPanel(condition="input.tabs == 'pipeline_item'",
                                                   tags$p(style="color:white;font-size:25px;margin-right:20px","- Pipeline -")),
                                  tags$head(HTML("<link rel='icon' href='min.png'>"))
))
anchor <- tags$a(tags$img(src='logo.png', height='30', width='20'),'Shiny SChnurR', style="color: white")
header$children[[2]]$children <- tags$div(tags$head(tags$style(HTML(".name { background-color:  transparent } .content-wrapper, .right-side {background-color: white}"))),anchor)    
header[["children"]][[2]][["children"]][["name"]] <- "Shiny SChnurR"

## SIDEBAR --------
sidebar <- dashboardSidebar(
  tags$style(type="text/css",
             ".shiny-output-error { visibility: hidden; }",
             ".shiny-output-error:before { visibility: hidden; }"
  ),
  br(),
  # Menu -------
  sidebarMenu(id="tabs",
              menuItem("Visualization", tabName="visu_item", icon=icon("area-chart"), selected = TRUE),
              menuItem("HeatMap", tabName = "heatmap_item", icon=icon("fas fa-align-justify")),
              menuItem("Genes", tabName = "genes_item", icon=icon("dna")),
              menuItem("Compare", tabName="compare_item", icon = icon("table")),
              menuItem("Pipeline", tabName="pipeline_item", icon = icon("fas fa-bezier-curve")),
              menuItem("About", tabName = "about_item", icon = icon("far fa-id-card"))
  ),
  br(),
  # Genes Panel --------
  conditionalPanel(condition="input.tabs=='genes_item'",align="center",
                   fluidRow(
                     column(1),
                     column(10, h4(align="center", "Control Panel"),
                            div(actionLink("help2", "", icon = icon("far fa-question-circle")), align="center"),
                            verbatimTextOutput(outputId = "no_file2"), 
                            conditionalPanel(condition= "output.fileUploaded",align="center",
                                             uiOutput("fchoice4"), br(),
                                             uiOutput("group"), br(),
                                             radioButtons("gographtype", label="Choose a graph type :", choices=c("Dotplot"="dplot", "Barplot"="bplot", "Emapplot" = "eplot")), br(),
                                             radioButtons("ontology", label="Choose an ontology :", choices=c("Biological Process"="BP", "Molecular Function"="MF", "Cellular Component" = "CC")), br(),
                                             br(), actionButton("gogo", icon = icon("far fa-arrow-alt-circle-right"), label="Do Gene Ontology")
                            )
                     )
                   )
  ),
  # About Panel --------
  conditionalPanel(condition="input.tabs=='about_item'",
                   fluidRow(
                     column(1),
                     column(10, tags$img(src='logo.png', height='300', width='175')
                     )
                   )
  ),
  # Compare Panel --------
  conditionalPanel(condition="input.tabs=='compare_item'", align="center",
                   fluidRow(
                     column(1),
                     column(10, h4(align="center", "Control Panel"),
                            div(actionLink("help3", "", icon = icon("far fa-question-circle")), align="center"),
                            verbatimTextOutput(outputId = "no_file3"),
                            conditionalPanel(condition= "output.fileUploaded",align="center",
                                             radioButtons(inputId="choice_compare", label= "Compare :", c("Factors" = "f_compare", "Features" = "features_compare"), selected = "f_compare"),
                                             conditionalPanel(condition = "input.choice_compare == 'features_compare'",
                                                              uiOutput("featurechoice2"),
                                                              conditionalPanel(condition ="input.featuresel2 == 'g2'",
                                                                               selectizeInput(inputId="genes2", label="Choose a gene :", choices ="")),
                                                              conditionalPanel(condition ="input.featuresel2 == 'd2'",
                                                                               uiOutput("nchoice2"))),
                                             radioButtons(inputId="graph_compare", label= "Choose the graph mode :", c("t-SNE" = "tsne", "UMAP" = "umap")),
                                             sliderInput(inputId="ptsize_compare", label="Point size :", min=0.1, max=2, step=0.1, value = 0.6, ticks = FALSE),
                                             conditionalPanel(condition = "input.choice_compare == 'f_compare'",
                                                              checkboxInput(inputId="show_clusters_compare", label="Clusters information", value=FALSE)
                                             ),
                                             radioButtons("ontology2", label="Choose an ontology :", choices=c("Biological Process"="BP", "Molecular Function"="MF", "Cellular Component" = "CC"))
                            )
                     )
                   )
  ),
  # HeatMap Panel --------
  conditionalPanel(condition="input.tabs=='heatmap_item'", align="center",
                   fluidRow(
                     column(1),
                     column(10, h4(align="center", "Control Panel"),
                            div(actionLink("help4", "", icon = icon("far fa-question-circle")), align="center"),
                            verbatimTextOutput(outputId = "no_file4"),
                            conditionalPanel(condition= "output.fileUploaded",align="center",
                                             uiOutput("fchoice3"), br(),
                                             uiOutput("heat_numb"), br(),
                                             actionButton("goheatmap", icon = icon("far fa-arrow-alt-circle-right"), label="Do HeatMap")
                            )
                     )
                   )
  ),
  # Visu Panel --------
  conditionalPanel(condition="input.tabs=='visu_item'",
                   fluidRow(
                     column(1),
                     column(10,
                            h4(align="center", "Control Panel"), 
                            div(actionLink("help1", "", icon = icon("far fa-question-circle")), align="center"),
                            fileInput(inputId="file1", label="Upload your *.rds file :", accept = ".rds", placeholder=""),
                            uiOutput("selectfile"),
                            conditionalPanel(condition= "output.fileUploaded", align="center",
                                             radioButtons(inputId="graph", label= "Choose the graph mode :", c("t-SNE" = "tsne", "UMAP" = "umap")),
                                             checkboxInput(inputId="show_clusters", label="Clusters information", value=FALSE),
                                             # checkboxInput(inputId="show_gene", label="Gene information", value=FALSE),
                                             sliderInput(inputId="ptsize", label="Point size :", min=0.1, max=2, step=0.1, value = 0.6, ticks = FALSE)
                            )
                     )
                   )
  )
)

## BODY --------
body <- dashboardBody(
  tabItems(
    
    # Visualize Item --------
    tabItem(tabName="visu_item", align="center", 
            conditionalPanel(condition="output.fileUploaded", 
                             br(),
                             htmlOutput(outputId = "information"),
                             br(),
                             uiOutput(outputId = "clusters_infos"),
                             verbatimTextOutput(outputId = "select_infos"),  
                             br(),
                             fluidRow(column(align="center", width = 6, plotlyOutput("plot_factors", width="575", height="500"), uiOutput("fchoice"),downloadButton("dlleftplot", label="")),
                                      column(align="center", width = 6, plotlyOutput("plot_numerics", width="500", height="500"),uiOutput("featurechoice"), uiOutput("nchoice"), 
                                             conditionalPanel(condition ="input.featuresel == 'g'", selectizeInput(inputId="genes", label="Choose a gene :", choices ="")),downloadButton("dlrightplot", label=""))#  br(), verbatimTextOutput(outputId="genes_analyse"))
                             ), 
                             hr(),
                             br(),
                             dataTableOutput("markers_table"),
                             uiOutput(align="left","dlmarkbutton_visu")
                             
            )         
    ),
    
    # HeatMap Item --------
    tabItem(tabName="heatmap_item", align="center",
            conditionalPanel(condition= "output.fileUploaded",
                             br(), br(),
                             plotOutput("heatmap", height = 850),
                             br(), 
                             uiOutput(align="left","dlheat")
                             
            )
    ),
    # Genes Item --------
    tabItem(tabName="genes_item", align="left",
            conditionalPanel(condition= "output.fileUploaded",
                             br(), br(),
                             fluidRow(column(align="center", width = 6, plotOutput("goplot", height = 600),uiOutput(align="left","dlgenegraph")),
                                      column(align="center", width = 6, dataTableOutput("dtgenes"),uiOutput(align="left","dlgenedt"))),
                             br(), hr(),
                             br(),
                             dataTableOutput("dtonto"),
                             uiOutput(align="left","dlontodt")
            )
    ),
    
    # Compare Item --------
    tabItem(tabName="compare_item", align="center", 
            br(),
            uiOutput(outputId="compare_helptext"),
            verbatimTextOutput(outputId = "select_infos_compare"),  
            uiOutput(outputId = "clusters_infos_compare"),
            br(),
            conditionalPanel(condition="output.fileUploaded",
                             fluidRow(column(align="center", width = 2, plotOutput(outputId="miniplot_compare", width="225px", height="225px"), br(), plotOutput(outputId="miniplot_compare2", width="225px", height="225px"), uiOutput("fchoice2"), div(actionLink("add", "", icon = icon("far fa-plus-square")), align="center"), uiOutput("addf")),
                                      column(align="center", width = 5, plotlyOutput("plot1_compare", width="450px", height="450px"), br(), uiOutput("plot1_library"), br(), uiOutput("addg1"), br(), downloadButton("dl_compare1", label=""), downloadButton("dl_comparebarcodes1", label="Export barcodes")),
                                      column(align="center", width = 5, plotlyOutput("plot2_compare", width="450px", height="450px"), br(), uiOutput("plot2_library"), br(), uiOutput("addg2"), br(), downloadButton("dl_compare2", label=""), downloadButton("dl_comparebarcodes2", label="Export barcodes"))
                             ),
                             hr(),
                             br(), 
                             uiOutput(align="left","markbutton"), uiOutput(align="left","dlmarkbutton_compare"), br(), 
                             dataTableOutput("markers_compare"),
                             hr(),
                             br(),
                             uiOutput(align="left","ontobutton"),
                             fluidRow(column(align="center",width=6, column(align="center", width=2, uiOutput("topgenes1"),br(), uiOutput(align="center","dlontobutton_compare1") ) , column(align="center", width=10, br(), dataTableOutput("onto_compare1"))),
                                      column(align="center",width=6, column(align="center", width=10, br(), dataTableOutput("onto_compare2")), column(align="align", width=2, uiOutput("topgenes2"),br(), uiOutput(align="align","dlontobutton_compare2") )))
                             )
    ),
    # Pipeline Item --------
    tabItem(tabName="pipeline_item", align="center", 
            br(),
            helpText("Here you can find the pipeline used."),
            br(),
            img(src = "pipe.png", height = 700, width = 400)
    ),
    # About Item --------
    tabItem(tabName="about_item", align="center", h3(strong("Shiny SChnurR")), br(), br(), br(),
            strong("Centre de Recherche en Cancérologie et Immunologie Nantes-Angers"), br(),
            p("UMR1232, CNRS ERL6001"), 
            p("Equipe 11 'Oncogénomique intégrative de la genèse et de la progression du Myélome Multiple'"), 
            p("IRS-UN"), 
            p("8 Quai Moncousu"), 
            p("44007 Nantes"), br(),
            img(src = "crcina.png", height = 180, width = 400, align="center"),
            br(), hr(), br(),  p(em("Development Team : Jean-Baptiste ALBERGE, Jonathan CRUARD, Mathias BAGUENEAU"), br(), em("Beta-test : Benjamin DELAUNE")),
            br(), p(strong("Git repository :"),a(href="https://gitlab.univ-nantes.fr/MathBgn/myelome", "Shiny SChnurR"), br(), em("A complete tutorial is available at this adress."))
    )
  )
)            

## PAGE --------
ui <- dashboardPage(
  header,
  sidebar,
  body
)


### ----------------------------- Server logic -----------------------------------------------------

server <- function(input, output, session) {
  options(shiny.maxRequestSize = 2500*1024^2)
  
  ## Upload and gestion of files --------
  filedata <- reactiveValues()
  observe ({
    if (!is.null(input$file1)) {
      infile <- input$file1
      if (is.null(infile)) {return (NULL)}
      filedata$data <- readRDS(infile$datapath)
      filedata$name <- input$file1$name
    } else {
      req(input$file)
      filedata$data <- withProgress(readRDS(paste0("./data/",input$file)), message = "Uploading file...", value=1)
      filedata$name <- input$file
    }
    genesList <- filedata$data@assays$SCT@data@Dimnames[1]
    updateSelectizeInput(session, "genes", choices = genesList[[1]], selected = "IGKC")
    updateSelectizeInput(session, "genes2", choices = genesList[[1]], selected = "IGKC")
    return(filedata$data)
    return(filedata$name)
  })
  output$fileUploaded <- reactive({
    return(!is.null(filedata$data))
  })
  outputOptions(output, 'fileUploaded', suspendWhenHidden=FALSE)
  
  ## Select File --
  output$selectfile <- renderUI ({
    req(is.null(input$file1))
    selectInput(inputId="file", label="Or choose a file :", choices = c("",list.files(path = "./data",full.names = FALSE,recursive = FALSE)))
  })
  
  ## Creating a usefull object for filedata (readable & writable) and assay gestion --------
  wrfile <- reactive ({
    req(filedata$data)
    wrdata <- filedata$data
    if (!is.null(wrdata@assays$SCT)) {
      DefaultAssay(wrdata) <- "SCT"
    } else {
      DefaultAssay(wrdata) <- "RNA"
    }
    return (wrdata)
  })
  
  
  ## Graphs & one table Generations --------
  markersData <- reactive ({
    mD <- wrfile()@misc$markers[[input$fsel]]
    # setDT(mD, keep.rownames = TRUE)[]
    return(mD)
  })
  
  factorsplotData <- reactive ({ # Left Graph Visu page
    scalex <- scale_x_continuous(limits = c(min(wrfile()@reductions[[input$graph]]@cell.embeddings[,1]), max(wrfile()@reductions[[input$graph]]@cell.embeddings[,1])))
    scaley <- scale_y_continuous(limits = c(min(wrfile()@reductions[[input$graph]]@cell.embeddings[,1]), max(wrfile()@reductions[[input$graph]]@cell.embeddings[,1])))
    withProgress(DimPlot(object = wrfile(), label=FALSE, pt.size = input$ptsize, reduction=input$graph, group.by = input$fsel), message = "Plot Generation", value=1) + NoLegend() + theme_bw()+ theme(panel.grid.major=element_blank(),plot.title = element_text(size=18),panel.grid.minor=element_blank(),plot.background=element_blank()) + NoAxes() + ggtitle(paste(file_path_sans_ext(filedata$name),"-", input$fsel)) + scalex + scaley 
  })
  
  numericsplotData <- reactive ({ # Right Graph Visu page
    scalex <- scale_x_continuous(limits = c(min(wrfile()@reductions[[input$graph]]@cell.embeddings[,1]), max(wrfile()@reductions[[input$graph]]@cell.embeddings[,1])))
    scaley <- scale_y_continuous(limits = c(min(wrfile()@reductions[[input$graph]]@cell.embeddings[,1]), max(wrfile()@reductions[[input$graph]]@cell.embeddings[,1])))
    if (input$featuresel =="d") {
      # withProgress(FeaturePlot(object = wrfile(), cols=c("lightgrey",plasma(ceiling(max(eval(parse(text=paste0("wrfile()@meta.data$",input$nsel))))))), pt.size = input$ptsize, features = input$nsel, reduction = input$graph), message = "Plot Generation", value=1) + theme_bw()+  NoAxes() + ggtitle(paste(filedata$name,"- Feature Plot -", input$nsel)) + scalex + scaley  #+ aes(text=Cells(wrfile())) 
      withProgress(FeaturePlot(object = wrfile(), cols=c("lightgrey",plasma(200)), pt.size = input$ptsize, features = input$nsel, reduction = input$graph), message = "Plot Generation", value=1) + theme_bw() + NoLegend() + theme(panel.grid.major=element_blank(),plot.title = element_text(size=18),panel.grid.minor=element_blank(),plot.background=element_blank()) +  NoAxes() + ggtitle(paste(file_path_sans_ext(filedata$name),"-", input$nsel)) + scalex + scaley 
      
    } else if (input$featuresel =="g") {
      withProgress(FeaturePlot(object = wrfile(), cols=c("lightgrey",plasma(200)), pt.size = input$ptsize, features = input$genes, reduction = input$graph), message = "Plot Generation", value=1) + theme_bw() + NoLegend() + theme(panel.grid.major=element_blank(),plot.title = element_text(size=18),panel.grid.minor=element_blank(),plot.background=element_blank()) +   NoAxes() + ggtitle(paste(file_path_sans_ext(filedata$name),"-", input$genes)) + scalex + scaley  
      
    }
  })
  
  
  miniplot_compareData <- reactive ({ # Mini Graph 1 Compare page
    withProgress(DimPlot(object = wrfile(), label=TRUE, pt.size = input$ptsize_compare, legend="none", reduction=input$graph_compare, group.by = input$fsel2), message = "Plot Generation", value=1)  + theme_bw() + theme(panel.grid.major=element_blank(),plot.title = element_text(size=12),panel.grid.minor=element_blank(),plot.background=element_blank()) + NoAxes() + NoLegend()
  })
  
  miniplot_compare2Data <- reactive ({ # Mini Graph 2 Compare page
    if (input$choice_compare == "features_compare") {
      if (input$featuresel2 =="d2") {
        withProgress(FeaturePlot(object = wrfile(),   cols=c("lightgrey",plasma(200)), pt.size = input$ptsize_compare, features = input$nsel2, reduction = input$graph_compare), message = "Plot Generation", value=1) + theme_bw()+ NoLegend() + NoAxes() + theme(panel.grid.major=element_blank(),plot.title = element_text(size=12),panel.grid.minor=element_blank(),plot.background=element_blank())
      } else if (input$featuresel2 =="g2") {
        withProgress(FeaturePlot(object = wrfile(),   cols=c("lightgrey",plasma(200)), pt.size = input$ptsize_compare, features = input$genes2, reduction = input$graph_compare), message = "Plot Generation", value=1) + theme_bw()+ NoLegend() + NoAxes() + theme(panel.grid.major=element_blank(),plot.title = element_text(size=12),panel.grid.minor=element_blank(),plot.background=element_blank())
      }      
    }
  })
  
  cells_to_plot1 <- reactive({ # Data for Compare Left Graph
    if (input$add %% 2 != 0) {
      subset1 <- SubsetData(object = wrfile(), cells=rownames(wrfile()@meta.data)[which(eval(parse(text=paste0("wrfile()@meta.data$",input$fsel2))) %in% input$library1_compare)] )
      selectedCells <- SubsetData(object = subset1, cells=rownames(subset1@meta.data)[which(eval(parse(text=paste0("subset1@meta.data$",input$add_factor))) %in% input$add_group1)])
    } else {
      selectedCells <- SubsetData(object = wrfile(), cells=rownames(wrfile()@meta.data)[which(eval(parse(text=paste0("wrfile()@meta.data$",input$fsel2))) %in% input$library1_compare)] )                                        
    } 
  return(selectedCells)
  })
  
  plot1_compareData <- reactive ({ # Left Graph Compare page
    scalex <- scale_x_continuous(limits = c(min(wrfile()@reductions[[input$graph_compare]]@cell.embeddings[,1]), max(wrfile()@reductions[[input$graph_compare]]@cell.embeddings[,1])))
    scaley <- scale_y_continuous(limits = c(min(wrfile()@reductions[[input$graph_compare]]@cell.embeddings[,1]), max(wrfile()@reductions[[input$graph_compare]]@cell.embeddings[,1])))
    if (input$choice_compare == "f_compare") {
      withProgress(DimPlot(object = wrfile(), cells=rownames(cells_to_plot1()@meta.data), label=FALSE, pt.size = input$ptsize_compare, reduction=input$graph_compare, group.by = input$fsel2), message = "Plot Generation", value=1) + NoLegend() + theme_bw() + NoAxes() + ggtitle(paste(file_path_sans_ext(filedata$name),"-",input$fsel2)) + scalex + scaley+ theme(panel.grid.major=element_blank(),plot.title = element_text(size=18),panel.grid.minor=element_blank(),plot.background=element_blank())
    } else {
      if (input$featuresel2 =="d2") {
        withProgress(FeaturePlot(object = wrfile(), cells=rownames(cells_to_plot1()@meta.data), cols=c("lightgrey",plasma(200)), pt.size = input$ptsize_compare, features = input$nsel2, reduction = input$graph_compare), message = "Plot Generation", value=1) + theme_bw()+ NoLegend() + NoAxes() + ggtitle(paste(file_path_sans_ext(filedata$name),"-", input$nsel2))+ theme(panel.grid.major=element_blank(),plot.title = element_text(size=18),panel.grid.minor=element_blank(),plot.background=element_blank()) + scalex + scaley 
      } else if (input$featuresel2 =="g2") {
        withProgress(FeaturePlot(object = wrfile(), cells=rownames(cells_to_plot1()@meta.data), cols=c("lightgrey",plasma(200)), pt.size = input$ptsize_compare, features = input$genes2, reduction = input$graph_compare), message = "Plot Generation", value=1) + theme_bw()+ NoLegend() + NoAxes() + ggtitle(paste(file_path_sans_ext(filedata$name),"-", input$genes2))+ theme(panel.grid.major=element_blank(),plot.title = element_text(size=18),panel.grid.minor=element_blank(),plot.background=element_blank()) +scalex + scaley  
      }      
    }
  })
  
  
  cells_to_plot2 <- reactive({ # Data for Compare Right Graph
    if (input$add %% 2 != 0) {
      subset2 <- SubsetData(object = wrfile(), cells=rownames(wrfile()@meta.data)[which(eval(parse(text=paste0("wrfile()@meta.data$",input$fsel2))) %in% input$library2_compare)] )
      selectedCells2 <- SubsetData(object = subset2, cells=rownames(subset2@meta.data)[which(eval(parse(text=paste0("subset2@meta.data$",input$add_factor))) %in% input$add_group2)])
    } else {
      selectedCells2 <- SubsetData(object = wrfile(), cells=rownames(wrfile()@meta.data)[which(eval(parse(text=paste0("wrfile()@meta.data$",input$fsel2))) %in% input$library2_compare)] )                                        
    }
    return(selectedCells2)
  })
  
  plot2_compareData <- reactive ({ # Right Graph Compare page
    #  df.colors <- data.frame(class=unique(eval(parse(text=paste0("wrfile()@meta.data$",input$fsel2)))), color="viridis"(length(unique(eval(parse(text=paste0("wrfile()@meta.data$",input$fsel2)))))))
    scalex <- scale_x_continuous(limits = c(min(wrfile()@reductions[[input$graph_compare]]@cell.embeddings[,1]), max(wrfile()@reductions[[input$graph_compare]]@cell.embeddings[,1])))
    scaley <- scale_y_continuous(limits = c(min(wrfile()@reductions[[input$graph_compare]]@cell.embeddings[,1]), max(wrfile()@reductions[[input$graph_compare]]@cell.embeddings[,1])))
    
    if (input$choice_compare == "f_compare") {
      withProgress(DimPlot(object = wrfile(), cells=rownames(cells_to_plot2()@meta.data), pt.size = input$ptsize_compare, reduction=input$graph_compare, group.by = input$fsel2), message = "Plot Generation", value=1) + NoLegend() + theme_bw() + NoAxes() + ggtitle(paste(file_path_sans_ext(filedata$name),"-", input$fsel2))+ theme(panel.grid.major=element_blank(),plot.title = element_text(size=18),panel.grid.minor=element_blank(),plot.background=element_blank()) + scalex + scaley
      # cols = df.colors[df.colors$class==input$library2_compare, "color"],
    } else {
      if (input$featuresel2 =="d2") {
        withProgress(FeaturePlot(object = wrfile(), cells=rownames(cells_to_plot2()@meta.data), cols=c("lightgrey",plasma(200)), pt.size = input$ptsize_compare, features = input$nsel2, reduction = input$graph_compare), message = "Plot Generation", value=1) + theme_bw() + NoLegend() + NoAxes() + ggtitle(paste(file_path_sans_ext(filedata$name),"-", input$nsel2))+ theme(panel.grid.major=element_blank(),plot.title = element_text(size=18),panel.grid.minor=element_blank(),plot.background=element_blank()) + scalex + scaley   
      } else if (input$featuresel2 =="g2") {
        withProgress(FeaturePlot(object = wrfile(), cells=rownames(cells_to_plot2()@meta.data), cols=c("lightgrey",plasma(200)), pt.size = input$ptsize_compare, features = input$genes2, reduction = input$graph_compare), message = "Plot Generation", value=1) + theme_bw() + NoLegend() + NoAxes() + ggtitle(paste(file_path_sans_ext(filedata$name),"-", input$genes2))+ theme(panel.grid.major=element_blank(),plot.title = element_text(size=18),panel.grid.minor=element_blank(),plot.background=element_blank()) + scalex + scaley 
      }    
    }
  })
  
  ## Graphs & Tables Outputs --------
  output$plot_factors <-renderPlotly ({
    req(wrfile())
    ggplotly(factorsplotData(),tooltip = c("colour","text")) %>% config(displaylogo = F,  modeBarButtonsToRemove = c('resetScale2d', 'toggleSpikelines', 'toImage', 'hoverCompareCartesian','hoverClosestCartesian'))
  })
  
  output$plot_numerics <-renderPlotly ({
    req(wrfile())
    ggplotly(numericsplotData(),tooltip = "none") %>% config(displaylogo = F,  modeBarButtonsToRemove = c('resetScale2d', 'toggleSpikelines', 'toImage', 'hoverCompareCartesian','hoverClosestCartesian'))
  })
  
  output$markers_table <- renderDataTable ({
    req(wrfile())
    req(markersData() != "")
    datatable(markersData()[c(7,6,3,4,2,1,5)], rownames = FALSE, filter="top", caption = paste("Table : All significant markers for the factor :", input$fsel ,"| Test used : MAST" ))  %>% formatRound(columns=c(3,4,5), digits=3) %>% formatSignif(columns=c(7,6), digits=3)
  })
  
  output$miniplot_compare <- renderPlot({
    req(wrfile())
    plot(miniplot_compareData())
  })
  
  output$miniplot_compare2 <- renderPlot({
    req(wrfile())
    plot(miniplot_compare2Data())
  })
  
  output$plot1_compare <- renderPlotly ({
    req(wrfile())
    if (input$choice_compare == "features_compare") {
      ggplotly(plot1_compareData(),tooltip ="none") %>% config(displaylogo = F, modeBarButtonsToRemove = c('resetScale2d', 'toggleSpikelines', 'toImage', 'hoverCompareCartesian','hoverClosestCartesian'))
    } else {
      ggplotly(plot1_compareData(),tooltip = c("colour","x","y")) %>% config(displaylogo = F, modeBarButtonsToRemove = c('resetScale2d', 'toggleSpikelines', 'toImage', 'hoverCompareCartesian','hoverClosestCartesian'))
    }
  })
  
  output$plot2_compare <- renderPlotly ({
    req(wrfile())
    if (input$choice_compare == "features_compare") {
      ggplotly(plot2_compareData(),tooltip ="none") %>% config(displaylogo = F, modeBarButtonsToRemove = c('resetScale2d', 'toggleSpikelines', 'toImage', 'hoverCompareCartesian','hoverClosestCartesian'))
    } else {
      ggplotly(plot2_compareData(),tooltip = c("colour","x","y")) %>% config(displaylogo = F, modeBarButtonsToRemove = c('resetScale2d', 'toggleSpikelines', 'toImage', 'hoverCompareCartesian','hoverClosestCartesian'))
    }
  })
  
  ## Heatmap Generation & Output --------
  output$heat_numb <- renderUI ({
    sliderInput("top_number", label="Choose the number of top genes :", min=1, max=5, step=1, value=3)
  })
  heatmapData <- reactive ({
    req(input$goheatmap)
    if (is.null(wrfile()@misc$markers[[input$fsel3]])) { 
      showModal(modalDialog("The markers may have not been calculated for this factor yet.", title=strong("Warning !"), easyClose=TRUE, footer = NULL )) 
    } else {
      topgenes <- wrfile()@misc$markers[[input$fsel3]] %>% group_by(cluster) %>% top_n(n = input$top_number, wt = avg_logFC)
      datascale <- withProgress(ScaleData(object = wrfile(), features = topgenes$gene), message = "Scaling data...", value=1)
      withProgress(DoHeatmap(object = datascale, features = topgenes$gene, group.by=input$fsel3), message = "HeatMap Generation", value=1) + NoLegend() + ggtitle(paste(file_path_sans_ext(filedata$name),"- HeatMap -", input$fsel3,"- top",input$top_number,"genes")) + theme(plot.title = element_text(size=20))
    }
  }) 
  output$heatmap <-renderPlot ({
    req(wrfile())
    heatmapData()
  })
  
  ## Genes Page --------
  observeEvent(input$gogo, {
    if (is.null(input$group_genepage)) {
      showModal(modalDialog("You must choose at least one group to do the Gene Ontology.", title=strong("Warning !"), easyClose=TRUE, footer = NULL ))
    }
  })
  egot <- reactive({
    genes <- wrfile()@misc$markers[[input$fsel4]]$cluster == input$group_genepage
    genes <- wrfile()@misc$markers[[input$fsel4]]$gene[genes]
    genes <- bitr(genes, fromType = "SYMBOL",toType = "ENTREZID",OrgDb = org.Hs.eg.db,drop = TRUE)
    ego <- withProgress(enrichGO(gene = genes$ENTREZID, OrgDb = "org.Hs.eg.db", keyType= "ENTREZID", ont = input$ontology, readable = TRUE), value = 1, message = "Ontology in progress...")
    return(ego)
  })
  
  goplotData <- reactive ({ # Ontology Graph
    req(input$gogo)
    req(!is.null(input$group_genepage))
    if (is.null(wrfile()@misc$markers[[input$fsel4]])) { 
      showModal(modalDialog("The markers may have not been calculated for this factor yet.", title=strong("Warning !"), easyClose=TRUE, footer = NULL )) 
    } else {
      if (input$gographtype == "dplot") {
        dotplot(egot()) + ggtitle(paste(file_path_sans_ext(filedata$name),"-",input$ontology,"-",input$fsel4)) + theme(panel.grid.major=element_blank(),plot.title = element_text(size=18),panel.grid.minor=element_blank(),plot.background=element_blank())
      } else if (input$gographtype == "bplot") {
        barplot(egot(), drop=TRUE) + ggtitle(paste(file_path_sans_ext(filedata$name),"-",input$ontology,"-",input$fsel4)) + theme(panel.grid.major=element_blank(),plot.title = element_text(size=18),panel.grid.minor=element_blank(),plot.background=element_blank())
      } else {
        emapplot(egot()) + ggtitle(paste(file_path_sans_ext(filedata$name),"-",input$ontology,"-",input$fsel4)) + theme(panel.grid.major=element_blank(),plot.title = element_text(size=18),panel.grid.minor=element_blank(),plot.background=element_blank())
      }
    }
  })

  output$goplot <-renderPlot ({
    req(wrfile())
    goplotData()
  })
  
  dtgoData <- reactive ({ # Genes Table
    filegene <- wrfile()
    req(input$gogo)
    Idents(filegene) <- as.factor(paste0(eval(parse(text=paste0("filegene@meta.data$",input$fsel4)))))
    dtgenes <- data.table(filegene@misc$markers[[input$fsel4]]$gene[which(eval(parse(text=paste0("filegene@misc$markers$",input$fsel4,"$cluster"))) %in% input$group_genepage)])
    setDT(dtgenes)[]
    names(dtgenes)[1] <- "Gene"
    return(dtgenes)
  })
  output$dtgenes <-renderDataTable ({
    req(wrfile())
    req(!is.null(input$group_genepage))
    datatable(dtgoData(), filter="top", caption = paste("Table : Markers for the following group(s) : ",paste(sapply(input$group_genepage, paste, collapse=""), collapse=" + "), "and this factor : ", input$fsel4))
  })

  
  dtontoData <- reactive ({ # Ontology Table
    filegene <- wrfile()
    req(input$gogo)
    Idents(filegene) <- as.factor(paste0(eval(parse(text=paste0("filegene@meta.data$",input$fsel4)))))
    dtonto <- data.table(egot()$Description, egot()$GeneRatio, egot()$pvalue, egot()$p.adjust)[which(egot()$Count > 3)]
    colnames(dtonto) <- c("Description","Gene Ratio","P-value","FDR")
    return(dtonto)
  })
  output$dtonto <-renderDataTable ({
    req(wrfile())
    req(!is.null(input$group_genepage))
    datatable(dtontoData(), filter="top", caption = paste("Table : Gene Ontology (",input$ontology,") for the following group(s) : ",paste(sapply(input$group_genepage, paste, collapse=""), collapse=" + "), "and this factor : ", input$fsel4,"| Only takes groups with a ratio > 3/Total, p-value cutoff : 0.05")) %>% formatSignif(columns=c(3,4), digits=3)
  })
  
  ## Downloads functions --------
  output$dlmarkbutton_visu <- renderUI ({ # visualization Page
    req(markersData() != "")
    downloadButton("dlmarkers", label="")
  })
  output$dlmarkers <- downloadHandler( # visualization Page
    filename = function() {
      paste0(file_path_sans_ext(filedata$name),"_allmarkers_",input$fchoice,".csv")
    },
    content = function(file) {
      write.csv(markersData(), file)
    }
  )
  
  output$dlleftplot <- downloadHandler( # visualization Page
    filename = function() {
      paste0(file_path_sans_ext(filedata$name),"_plot_",input$fsel,"_",input$graph,".svg")
    },
    content = function(file) {
      svg(file)
      print(factorsplotData())
      dev.off()
    }
  )
  
  output$dlrightplot <- downloadHandler( # visualization Page
    filename = function() {
      if (input$featuresel =="g") {
        paste0(file_path_sans_ext(filedata$name),"_",input$genes,"_plot_",input$graph,".svg")
      } else {
        paste0(file_path_sans_ext(filedata$name),"_",input$nsel,"_plot_",input$graph,".svg")
      }
    },
    content = function(file) {
      svg(file)
      print(numericsplotData())
      dev.off()
    }
  )
  
  
  output$dlgenegraph <- renderUI ({ # Genes Page
    req(goplotData() !="")
    downloadButton("dl_gene", label="")
  })
  output$dl_gene <- downloadHandler(
    filename = function() {
      if (input$gographtype == "dplot") {
        paste0(file_path_sans_ext(filedata$name),"_",input$ontology,"_dotplot_",input$fsel4,".png")
      } else if (input$gographtype == "bplot") {
        paste0(file_path_sans_ext(filedata$name),"_",input$ontology,"_barplot_",input$fsel4,".png")
      } else {
        paste0(file_path_sans_ext(filedata$name),"_",input$ontology,"_emapplot_",input$fsel4,".png")
      }
    },
    content = function(file) {
      png(file, width = 800, height = 600)
      print(goplotData())
      dev.off()
    }
  )
  
  output$dlgenedt <- renderUI ({ # Genes Page
    req(dtgoData() !="")
    downloadButton("dl_godt", label="")
  })
  output$dl_godt <- downloadHandler(
    filename = function() {
        paste0(file_path_sans_ext(filedata$name),"_genes_datatable_",input$fsel4,".csv")
    },
    content = function(file) {
      write.csv(dtgoData(), file)
    }
  )
  

  output$dlontodt <- renderUI ({ # Genes Page
    req(dtgoData() !="")
    downloadButton("dl_ontodt", label="")
  })
  output$dl_ontodt <- downloadHandler(
    filename = function() {
      paste0(file_path_sans_ext(filedata$name),"_onto_",input$ontology,"_datatable_",input$fsel4,".csv")
    },
    content = function(file) {
      write.csv(dtontoData(), file)
    }
  )
  
  
  
  output$dlheat <- renderUI ({ # HeatMap Page
    req(heatmapData() !="")
    downloadButton("dl_heatmap", label="")
  })
  output$dl_heatmap <- downloadHandler(
    filename = function() {
      paste0(file_path_sans_ext(filedata$name),"_heatmap_",input$fsel3,"_top",input$top_number,"genes",".png")
    },
    content = function(file) {
      png(file, width = 800, height = 600)
      print(heatmapData())
      dev.off()
    }
  )
  
  
  
  output$dl_compare1 <- downloadHandler( # Compare Page
    filename = function() {
      if (input$choice_compare == "f_compare") {
        paste0(file_path_sans_ext(filedata$name),"_plot_",input$fsel2,"_",input$graph_compare,".svg")
      } else {
        if (input$featuresel2 =="g2") {
          paste0(file_path_sans_ext(filedata$name),"_",input$genes2,"_plot_",input$graph_compare,".svg")  
        } else {
          paste0(file_path_sans_ext(filedata$name),"_",input$nsel2,"_plot_",input$graph_compare,".svg")  
          }
      }
    },
    content = function(file) {
      svg(file)
      print(plot1_compareData())
      dev.off()        
    }                
  )
  
  output$dl_compare2 <- downloadHandler( # Compare Page
    filename = function() {
      if (input$choice_compare == "f_compare") {
        paste0(file_path_sans_ext(filedata$name),"_plot_",input$fsel2,"_",input$graph_compare,".svg")
      } else {
        if (input$featuresel2 =="g2") {
          paste0(file_path_sans_ext(filedata$name),"_",input$genes2,"_plot_",input$graph_compare,".svg")  
        } else {
          paste0(file_path_sans_ext(filedata$name),"_",input$nsel2,"_plot_",input$graph_compare,".svg")  
        }
      }
    },
    content = function(file) {
      svg(file)
      print(plot2_compareData())
      dev.off()
    }
  )
  
  output$dl_comparebarcodes1 <- downloadHandler( # Compare Page
    filename = function() {
      paste0(file_path_sans_ext(filedata$name),"_selectedbarcodes.csv")
    },
    content = function(file) {
      write.csv(cbar1Data(), file)
    }
  )
  
  output$dl_comparebarcodes2 <- downloadHandler( # Compare Page
    filename = function() {
      paste0(file_path_sans_ext(filedata$name),"_selectedbarcodes.csv")
    },
    content = function(file) {
      write.csv(cbar2Data(), file)
    }
  )

  ## Information Visualize text --------
  output$information  <- renderUI({
    req(wrfile())
    az <- paste(strong("Filename :"), filedata$name)
    er <- paste(strong("Genes number :"), length(wrfile()@assays$SCT@data@Dimnames[[1]]), " | ",strong("Cells number :"), length(wrfile()@assays$SCT@data@Dimnames[[2]]), " | ",strong("Median genes/cell :"), median(wrfile()@meta.data$nFeature_SCT))
    ty <- paste(strong("Assay used :"), wrfile()@active.assay)
    HTML(paste(az,er,ty, sep='</br>'))
  })
  
  
  ## No file texts --------
  output$no_file2  <- renderText({
    req(input$file =="")
    req(is.null(input$file1))
    print("Please upload or \n choose a file")
  }) 
  output$no_file3  <- renderText({
    req(input$file =="")
    req(is.null(input$file1))
    print("Please upload or \n choose a file")
  })
  output$no_file4  <- renderText({
    req(input$file =="")
    req(is.null(input$file1))
    print("Please upload or \n choose a file")
  })
  
  
  ## Clusters + selection information text in visualization page --------
  output$clusters_infos <- renderTable({ 
    req(input$fsel != "")
    req(input$show_clusters == "TRUE")
    clDATA <- data.table("Cluster" = levels(as.factor(wrfile()@meta.data[[input$fsel]])), "Cells_nb" = as.vector(summary(as.factor(wrfile()@meta.data[[input$fsel]]))), "Percentage" =formatC(((as.vector(summary(as.factor(wrfile()@meta.data[[input$fsel]])))/length(as.factor(wrfile()@meta.data[[input$fsel]])))*100),digits=2, format ="f" ))
    t(head( clDATA, n=999 ))}, align="c", striped = TRUE, hover = TRUE, spacing = 'xs',   width = '100%',  colnames = FALSE, rownames=TRUE
  )
  
  output$select_infos <- renderText({
    req(wrfile())
    d <- paste0("Your selection : Cells nb : ", nrow(event_data("plotly_selected")), " | % : ", formatC(((nrow(event_data("plotly_selected"))/length(wrfile()@meta.data[[input$fsel]]))*100),digits=2, format ="f" )  ) 
    if (is.null(nrow(event_data("plotly_selected")))) "Please select some cells" else d
  })
  
  ## Clusters + selection information text in compare page --------
  output$clusters_infos_compare  <- renderTable ({
    req(input$fsel2 != "")
    req(input$show_clusters_compare == "TRUE")
    clDATA2 <- data.table("Cluster" = levels(as.factor(wrfile()@meta.data[[input$fsel2]])), "Cells_nb" = as.vector(summary(as.factor(wrfile()@meta.data[[input$fsel2]]))), "Percentage" =formatC(((as.vector(summary(as.factor(wrfile()@meta.data[[input$fsel2]])))/length(as.factor(wrfile()@meta.data[[input$fsel2]])))*100),digits=2, format ="f" ))
    t(head( clDATA2, n=999 ))}, align="c",  striped = TRUE, hover = TRUE, spacing = 'xs',   width = '100%',  colnames = FALSE, rownames=TRUE
  ) 
  output$select_infos_compare <- renderText({
    req(wrfile())
    d <- paste0("Your selection : Cells nb : ", nrow(event_data("plotly_selected")), " | % : ", formatC(((nrow(event_data("plotly_selected"))/length(wrfile()@meta.data[[input$fsel2]]))*100),digits=2, format ="f" )  )
    if (is.null(nrow(event_data("plotly_selected")))) "Please select some cells" else d