Show the distance, include the participation of Perrine, remove useless print

Rfunctions/DiagPlot.R

@@ -39,7 +39,7 @@ Plot_diag <- function(input,resDiff,tree,getTable=FALSE)
     if(input$DiagPlot=="MajTax") res = majTaxPlot(input,counts, group = group, col=colors)
     if(input$DiagPlot=="SfactorsVStot") res = diagSFactors(input,normFactors,resDiff$raw_counts) 
     if(input$DiagPlot=="pcaPlot") res = PCAPlot_meta(input,dds, group,  type.trans = input$TransType, col = colors)
-    if(input$DiagPlot=="pcoaPlot") res = PCoAPlot_meta(input,dds, group,CT,tree, col = colors) 
+    if(input$DiagPlot=="pcoaPlot") res = PCoAPlot_meta(input,dds, group,CT,tree, col = colors)$plot 
     if(input$DiagPlot=="nmdsPlot") res = NMDSPlot(input, dds, group,CT,tree, col = colors) 
     if(input$DiagPlot=="clustPlot") res = HCPlot(input,dds,group,type.trans=input$TransType,counts,CT,tree,col=colors)
   }
@@ -170,7 +170,8 @@ Plot_diag_Eigen <- function(input,resDiff)
   maxFact =max(sapply(group,FUN=function(x) length(levels(x))))
   if(maxFact>=4) colors = rainbow(maxFact) 
   
-  PCAPlot_meta(input,dds, group,  type.trans = input$TransType, col = colors, plot = "eigen") 
+  res = PCAPlot_meta(input,dds, group,  type.trans = input$TransType, col = colors, plot = "eigen")
+  return(res)
 }
 
 
@@ -383,6 +384,8 @@ diagSFactors<-function (input,normFactors,counts)
 ### PCoA
 PCoAPlot_meta <-function (input, dds, group_init, CT,tree,col = c("SpringGreen","dodgerblue","black","firebrick1"), plot = "pcoa") 
 {
+  dist.counts.norm = NULL
+  pp = NULL
   cval=c()
   time_set = 0
   # Set of shape
@@ -478,7 +481,7 @@ PCoAPlot_meta <-function (input, dds, group_init, CT,tree,col = c("SpringGreen",
         ## Plot axis, label and circles
         v_axes = c(as.numeric(gsub("PC","",input$PCaxe1)),as.numeric(gsub("PC","",input$PCaxe2)))
         
-        plot(pco.counts.norm$li[v_axes], 
+        pp = plot(pco.counts.norm$li[v_axes], 
              xlab=paste(input$PCaxe1, ": ",round(eigen[v_axes[1]],1),"%") , 
              ylab=paste(input$PCaxe2, ": ",round(eigen[v_axes[2]],1),"%"),
              xlim=c(min+0.25*min,max+0.25*max), ylim=c(min-0.1,max+0.1), 
@@ -510,11 +513,11 @@ PCoAPlot_meta <-function (input, dds, group_init, CT,tree,col = c("SpringGreen",
         nbBar = max(7,max(v_axes))
         col = rep("grey",nbBar)
         col[v_axes] = "black"
-        barplot(eigen[1:nbBar], xlab="Dimensions", ylab="Eigenvalues (%)", names.arg = 1:nbBar, col = col, ylim=c(0,max(eigen)+5), cex.axis=1.2, cex.lab=1.4,cex.names=1.2)
+        pp = barplot(eigen[1:nbBar], xlab="Dimensions", ylab="Eigenvalues (%)", names.arg = 1:nbBar, col = col, ylim=c(0,max(eigen)+5), cex.axis=1.2, cex.lab=1.4,cex.names=1.2)
       }
     }
   }
-  
+  return(list(plot=pp,dataDiv = dist.counts.norm))
 }
 
 
@@ -647,6 +650,7 @@ my.boxplot <- function(x, pol.col = 1, pol.density = NULL, pol.angle = 45,
 ### Get PCOA table (useful to get the number of axes)
 Get_pcoa_table <-function (input, dds, group_init,CT,tree) 
 {
+  dist.counts.norm = NULL
   cval=c()
   time_set = 0
   # Set of shape

Rfunctions/DiffTable.R

@@ -17,7 +17,7 @@ TableDiff_print <- function(input,BaseContrast,resDiff, info = NULL)
   result[[input$ContrastList_table]] <- results(dds,contrast=BaseContrast[,input$ContrastList_table],pAdjustMethod=input$AdjMeth,
                                                 cooksCutoff=cooksCutoff,
                                                 independentFiltering=input$IndFiltering,alpha=alpha)
-  print(result[[input$ContrastList_table]])
+  #print(result[[input$ContrastList_table]])
   #names(result) <- gsub("_", " ", names(result))
   if (is.null(info))  info <- data.frame(Id = rownames(result[[1]]))
   else names(info)[1] <- "Id"

Rfunctions/VisuPlot.R

@@ -391,10 +391,8 @@ Plot_Visu_Scatterplot<- function(input,resDiff,export=FALSE,lmEst = FALSE,CorEst
     Rsq = sumRes$r.squared
     return(list(regCoef=regCoef,Rsq = Rsq))
   }
-  print("HERE")
   if(CorEst)
   {
-    print("HERE2")
     #typesTarget = sapply(target,class)
     #print(typesTarget)
     #numInd = (typesTarget=="numeric")[1:ncol(target)]
@@ -849,10 +847,10 @@ Plot_network <- function(input,resDiff,availableTaxo, ind_taxo, qualiVariable, e
   else{sec_variable = NULL}
   
   data <- GetDataToPlot(input,resDiff,VarInt,availableTaxo, sec_variable = sec_variable, aggregate = FALSE)
-  if(!is.null(data)){
+  if(!is.null(data) && !is.null(data$targetInt)){
   counts_tmp_combined <- data$counts
   dataVariables <- as.matrix(data$targetInt)
-  if(isolate(input$colorCorr && qualiVariable())){dataVariables[,sec_variable] <- sapply(dataVariables[,sec_variable], function(x) if(is.element(x,isolate(input$values1))){1}else{0})}
+  if(isolate(input$colorCorr && qualiVariable()) && !is.null(dataVariables)){dataVariables[,sec_variable] <- sapply(dataVariables[,sec_variable], function(x) if(is.element(x,isolate(input$values1))){1}else{0})}
   
   if(!is.null(counts_tmp_combined)){
     countsMatrix <- as.matrix(counts_tmp_combined)

server.R

@@ -2813,7 +2813,7 @@ shinyServer(function(input, output,session) {
     ## Phylogenetic tree
     tree = dataInputTree()$data
     
-    Plot_diag_pcoaEigen(input,resDiff,tree)
+    Plot_diag_pcoaEigen(input,resDiff,tree)$plot
   },height = 400)
   
   
@@ -2830,6 +2830,32 @@ shinyServer(function(input, output,session) {
     
   })
   
+  output$Distancetable <- DT::renderDataTable(
+    datatable({
+      resDiff = ResDiffAnal()
+      ## Phylogenetic tree
+      tree = dataInputTree()$data
+      as.matrix(Plot_diag_pcoaEigen(input,resDiff,tree)$dataDiv)
+    }, rownames= FALSE, options = list(lengthMenu = list(c(10, 50, -1), c('10', '50', 'All')), scroller = TRUE,
+                                       pageLength = 10,scrollX=TRUE
+    ))
+  )
+  
+  ## Export Distancetable in .csv
+  output$ExportDistancetable <- downloadHandler(
+    filename = function() {
+      if(input$sepdiversity=="\t") 'SHAMAN_Distance.tsv'
+      else 'SHAMAN_Distance.csv'
+    },
+    content = function(file){
+      resDiff = ResDiffAnal()
+      ## Phylogenetic tree
+      tree = dataInputTree()$data
+      tmp = as.matrix(Plot_diag_pcoaEigen(input,resDiff,tree)$dataDiv)
+      datatable(tmp,rownames= FALSE)
+      write.table(tmp, file,row.names = FALSE, sep=input$sepdistance)
+    })
+  
   
   output$ResPermaTestBox <- renderUI({
     
@@ -3672,7 +3698,7 @@ shinyServer(function(input, output,session) {
   output$tooltippValueDensity <- renderUI({
     hover <- input$plot_hover_pValueDensity
     point <- nearPoints(pValueDensityData(), hover, xvar = "x", yvar = "y", threshold = 20, maxpoints = 1)
-    if (nrow(point) == 0) return(NULL)
+    if (is.null(nrow(point)) || nrow(point) == 0) return(NULL)
     # calculate point position INSIDE the image as percent of total dimensions from left (horizontal) and from top (vertical)
     left_pct <- (hover$x - hover$domain$left) / (hover$domain$right - hover$domain$left)
     top_pct <- (hover$domain$top - hover$y) / (hover$domain$top - hover$domain$bottom)

ui.R

@@ -59,6 +59,7 @@ function(request) {
                                     tabPanel("Authors", h3("The main contributors to SHAMAN:"),
                                              p(a("Stevenn Volant", href="mailto:stevenn.volant@pasteur.fr"), "(Initiator, coding, testing, documentation, evaluation)"),
                                              p(a("Amine Ghozlane",href="mailto:amine.ghozlane@pasteur.fr"), "(Coding, testing, documentation, evaluation, packaging)"),
+                                             p("Perrine Woringer", "(Coding, testing, Documentation)"),
                                              p("Pierre Lechat", "(Coding, testing, feature suggestions)"),
                                              h3("Acknowledgements"),
                                              p("Thanks to the following people for patches and other suggestions for improvements:"),
@@ -87,6 +88,7 @@ function(request) {
                          box(
                            title = "What's new in SHAMAN", width = NULL, status = "primary",
                            div(style = 'overflow-y: scroll; height: 550px',
+                               addNews("August 14th 2019","Major update","We performed a global improvement of SHAMAN. The application is now migrated to R 3.6.1. We implemented several visualization for differential analysis and network of abundance. We hope you will enjoy this main update."),
                                addNews("April 11th 2019","Debugging","We fixed few bugs in export system and scatterplot visualisation system."),
                                addNews("March 28th 2019","Packaging","SHAMAN is now available as packrat package. Take a look at download section."),
                                addNews("April 17th 2018","Bioinformatics","The bioinformatic treatment offers a larger access to parameters. We also worked a lot on the documentation."),
@@ -752,6 +754,17 @@ function(request) {
                            ),
                            conditionalPanel(condition="input.DiagPlot=='pcoaPlot' || input.DiagPlot=='nmdsPlot'",
                                             uiOutput("ResPermaTestBox")
+                           ),
+                           conditionalPanel(condition="input.DiagPlot=='pcoaPlot' || input.DiagPlot=='nmdsPlot'",
+                                            br(),
+                                            box(title = "Distance values",  width = 6, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= TRUE,
+                                                DT::dataTableOutput("Distancetable"),
+                                                fluidRow(
+                                                  column(width=3,downloadButton('ExportDistancetable', 'Export table')),
+                                                  column(width=3,selectInput("sepdistance", "Separator:", c("Tab" = "\t", "Comma" = ",", "Semicolon" = ";")))
+                                                ),
+                                                tags$style(type='text/css', "#ExportDistancetable { margin-top: 37px;}")
+                                            )
                            )
                          )