Bug fixes

global.R

@@ -7,10 +7,11 @@ source('modules/dispTrackStats.R')
 source('modules/trajPlot.R')
 source('modules/trajRibbonPlot.R')
 source('modules/trajPsdPlot.R')
-source('modules/boxPlot.R')
-source('modules/tabAUC.R')
+source('modules/aucPlot.R')
+source('modules/distPlot.R')
 source('modules/clDistPlot.R')
 source('modules/tabScatter.R')
-source('modules/tabBoxPlot.R')
+source('modules/tabDist.R')
+source('modules/tabAUC.R')
 source('modules/tabClHier.R')
 source('modules/tabClHierSpar.R')
\ No newline at end of file

modules/boxPlot.R → modules/aucPlot.R

@@ -2,7 +2,7 @@
 # Time Course Inspector: Shiny app for plotting time series data
 # Author: Maciej Dobrzynski
 #
-# This module is for plotting a choice of box/violin/dot-plots
+# This module is for plotting AUC as a choice of box/violin/dot-plots
 # Assumes in.data contains columns:
 # realtime
 # y
@@ -10,44 +10,46 @@
 # id
 
 # UI ----
-modBoxPlotUI =  function(id, label = "Plot Box-plots") {
+modAUCplotUI =  function(id, label = "Plot AUC distributions") {
   ns <- NS(id)
   
   tagList(
     fluidRow(
       column(
         4,
-        checkboxGroupInput(ns('inPlotType'), 'Plot type:', list('Dot-plot' = 'dot', 
-                                                                'Violin-plot' = 'viol',
-                                                                'Box-plot' = 'box', 
-                                                                'Line-plot' = 'line'), selected = 'box'),
-        checkboxInput(ns('chBPlotBoxInt'), 'Interactive Plot'),
-        actionButton(ns('butPlotBox'), 'Plot!')
+        checkboxInput(ns("chBPlotTypeBox"),  "Box-plot", value = T),
+        checkboxInput(ns("chBPlotTypeDot"),  "Dot-plot", value = F),
+        checkboxInput(ns("chBPlotTypeViol"), "Violin-plot", value = F),
+        checkboxInput(ns('chBPlotInt'), 'Interactive Plot'),
+        actionButton(ns('butPlot'), 'Plot!')
+      ),
+      column(
+        4,
+        uiOutput(ns('uiPlotBoxNotches')),
+        uiOutput(ns('uiPlotBoxOutliers')),
+        uiOutput(ns('uiPlotDotNbins')),
+        uiOutput(ns('uiPlotDotShade'))
       ),
       column(
         4,
         selectInput(
-          ns('selPlotBoxLegendPos'),
+          ns('selPlotLegendPos'),
           label = 'Legend position',
           choices = list(
             "Top" = 'top',
             "Right" = 'right',
             "Bottom" = 'bottom'
           ), 
+          width = "120px",
           selected = 'top'
         ),
-        uiOutput(ns('uiPlotBoxNotches')),
-        uiOutput(ns('uiPlotBoxOutliers')),
-        uiOutput(ns('uiPlotBoxDodge')),
-        #uiOutput(ns('uiPlotBoxWidth')),
-        uiOutput(ns('uiPlotBoxAlpha')),
-        uiOutput(ns('uiPlotDotNbins'))
-      ),
-      column(
-        4,
+        radioButtons(ns("rBAxisLabelsRotate"), "X-axis labels",
+                     c("horizontal" = 0,
+                       "45 deg" = 45,
+                       "90 deg" = 90)),
         numericInput(
           ns('inPlotBoxWidth'),
-          'Width [%]:',
+          'Width [%]',
           value = PLOTWIDTH,
           min = 10,
           width = '100px',
@@ -55,16 +57,12 @@ modBoxPlotUI =  function(id, label = "Plot Box-plots") {
         ),
         numericInput(
           ns('inPlotBoxHeight'),
-          'Height [px]:',
+          'Height [px]',
           value = PLOTBOXHEIGHT,
           min = 100,
           width = '100px',
           step = 50
-        ),
-        radioButtons(ns("rBAxisLabelsRotate"), "X-axis labels:",
-                     c("horizontal" = 0,
-                       "45 deg" = 45,
-                       "90 deg" = 90))
+        )
       )
     ),
     
@@ -74,76 +72,63 @@ modBoxPlotUI =  function(id, label = "Plot Box-plots") {
 }
 
 # SERVER ----
-modBoxPlot = function(input, output, session, 
-                      in.data, 
-                      in.cols = list(meas.x = COLRT,
+modAUCplot = function(input, output, session, 
+                      in.data,                       # input data table in long format
+                      in.cols = list(meas.x = COLRT, # column names
                                      meas.y = COLY,
                                      group = COLGR,
                                      id = COLID), 
-                      in.fname) {
+                      in.labels = list(x = "",       # plot labels
+                                       y = "", 
+                                       legend = ""),
+                      in.fname) {                      # file name for saving the plot                 
   
   ns <- session$ns
   
+  # optional UI depending on the type of the plot chosen
   output$uiPlotBoxNotches = renderUI({
-    cat(file = stderr(), 'UI uiPlotBoxNotches\n')
+    cat(file = stderr(), 'aucPlot:uiPlotBoxNotches\n')
     
     ns <- session$ns
     
-    if('box' %in% input$inPlotType)
-      checkboxInput(ns('inPlotBoxNotches'), 'Box plot notches', FALSE)
+    if(input$chBPlotTypeBox)
+      checkboxInput(ns('chBplotBoxNotches'), 'Notches in box-plot', FALSE)
   })
   
   output$uiPlotBoxOutliers = renderUI({
-    cat(file = stderr(), 'UI uiPlotBoxNotches\n')
+    cat(file = stderr(), 'aucPlot:uiPlotBoxNotches\n')
     
     ns <- session$ns
     
-    if('box' %in% input$inPlotType)
-      checkboxInput(ns('inPlotBoxOutliers'), 'Box plot outliers', FALSE)
+    if(input$chBPlotTypeBox)
+      checkboxInput(ns('chBplotBoxOutliers'), 'Outliers in box-plot', FALSE)
   })
   
-  output$uiPlotBoxDodge = renderUI({
-    cat(file = stderr(), 'UI uiPlotBoxDodge\n')
-    
-    ns <- session$ns
-    
-    if(!( 'line' %in% input$inPlotType  ))
-      sliderInput(ns('inPlotBoxDodge'), 'Space between groups:', min = 0, max = 1, value = .4, step = 0.05)
-  })
   
-  output$uiPlotBoxWidth = renderUI({
-    cat(file = stderr(), 'UI uiPlotBoxWidth\n')
+  output$uiPlotDotShade = renderUI({
+    cat(file = stderr(), 'aucPlot:uiPlotDotShade\n')
     
     ns <- session$ns
     
-    if('box' %in% input$inPlotType)
-      sliderInput(ns('inPlotBoxWidth'), 'Box plot width:', min = 0, max = 1, value = .2, step = 0.1)
-  })
-  
-  output$uiPlotBoxAlpha = renderUI({
-    cat(file = stderr(), 'UI uiPlotBoxAlpha\n')
-    
-    ns <- session$ns
-    
-    if('box' %in% input$inPlotType)
-      sliderInput(ns('inPlotBoxAlpha'), 'Box plot transparency:', min = 0, max = 1, value = 1, step = 0.05)
+    if(input$chBPlotTypeDot)
+      sliderInput(ns('slPlotDotShade'), "Shade of grey in dot-plot", min = 0, max = 1, value = 0.5, step = 0.1)
   })
   
   output$uiPlotDotNbins = renderUI({
-    cat(file = stderr(), 'UI uiPlotDotNbins\n')
+    cat(file = stderr(), 'aucPlot:uiPlotDotNbins\n')
     
     ns <- session$ns
     
-    if('dot' %in% input$inPlotType)
-      sliderInput(ns('inPlotDotNbins'), '#Bins for dot-plot:', min = 2, max = 50, value = 30, step = 1)
+    if(input$chBPlotTypeDot)
+      sliderInput(ns('slPlotDotNbins'), 'Number of bins in dot-plot', min = 2, max = 50, value = 30, step = 1)
   })
   
   # Boxplot - display
   output$outPlotBox = renderPlot({
-    locBut = input$butPlotBox
+    locBut = input$butPlot
     
     if (locBut == 0) {
-      cat(file = stderr(), 'plotBox: Go button not pressed\n')
+      cat(file = stderr(), 'aucPlot:Go button not pressed\n')
       return(NULL)
     }
     
@@ -153,10 +138,10 @@ modBoxPlot = function(input, output, session,
   
   
   output$outPlotBoxInt = renderPlotly({
-    locBut = input$butPlotBox
+    locBut = input$butPlot
     
     if (locBut == 0) {
-      cat(file = stderr(), 'plotBox: Go button not pressed\n')
+      cat(file = stderr(), 'aucPlot:Go button not pressed\n')
       return(NULL)
     }
     
@@ -175,7 +160,7 @@ modBoxPlot = function(input, output, session,
   output$uiPlotBox <- renderUI({
     ns <- session$ns
     
-    if (input$chBPlotBoxInt)
+    if (input$chBPlotInt)
       plotlyOutput(ns("outPlotBoxInt"), 
                    width = paste0(input$inPlotBoxWidth, '%'),
                    height = paste0(input$inPlotBoxHeight, 'px'))
@@ -193,7 +178,7 @@ modBoxPlot = function(input, output, session,
   # This function is used to plot and to downoad a pdf
   
   plotBox <- function() {
-    cat(file = stderr(), 'plotBox\n')
+    cat(file = stderr(), 'aucPlot:plotBox\n')
     
     loc.dt = in.data()
     
@@ -205,51 +190,53 @@ modBoxPlot = function(input, output, session,
     
     cat(file = stderr(), 'plotBox:dt not NULL\n')
     
-    loc.par.dodge <- position_dodge(width = input$inPlotBoxDodge)
-    p.out = ggplot(loc.dt, aes_string(x = sprintf("factor(%s)", in.cols$meas.x), y = in.cols$meas.y)) 
+    p.out = ggplot(loc.dt, aes_string(x = sprintf("factor(%s)", in.cols$meas.x), 
+                                      y = in.cols$meas.y)) 
+    
+    
+    if(input$chBPlotTypeDot) {
+      # calculate bin width for dot-plot based on nBins provided in the UI
+      loc.binwidth = abs(max(loc.dt[[ in.cols$meas.y ]], 
+                             na.rm = T) - 
+                           min(loc.dt[[ in.cols$meas.y ]], 
+                               na.rm = T)) / (input$slPlotDotNbins - 1)
       
-    if('dot' %in% input$inPlotType)
-      p.out = p.out + geom_dotplot(aes_string(fill = in.cols[[COLGR]]), 
+      p.out = p.out + geom_dotplot(fill = grey(input$slPlotDotShade),
                                    color = NA,
-                                   binaxis = in.cols$meas.y, 
+                                   binaxis = "y", 
                                    stackdir = "center", 
-                                   position = loc.par.dodge, 
-                                   binwidth = abs(max(loc.dt[[ in.cols$meas.y ]], na.rm = T) - min(loc.dt[[ in.cols$meas.y ]], na.rm = T)) / (input$inPlotDotNbins - 1), 
+                                   binwidth = loc.binwidth, 
                                    method = 'histodot')
       
-    if('viol' %in% input$inPlotType)
-      p.out = p.out + geom_violin(aes_string(fill = in.cols[[COLGR]]),
-                                  position = loc.par.dodge,
-                                  width = 0.2)
+    }
     
-    if('line' %in% input$inPlotType)
+    if(input$chBPlotTypeViol)
       p.out = p.out + 
-      geom_path(aes_string(color = in.cols[[COLGR]], group = in.cols[[COLID]])) +
-      facet_wrap(as.formula(paste("~", in.cols[[COLGR]])))
+      geom_violin(fill = NA,
+                  color = "black",
+                  width = 0.2)
     
-    if ('box' %in% input$inPlotType)
+    if (input$chBPlotTypeBox)
       p.out = p.out + geom_boxplot(
-        aes_string(fill = in.cols[[COLGR]]), 
-        position = loc.par.dodge,
-        #width = 0.2, #input$inPlotBoxWidth,
-        notch = input$inPlotBoxNotches, 
-        alpha = input$inPlotBoxAlpha,
-        outlier.colour = if (input$inPlotBoxOutliers)
+        fill = NA,
+        color = "black",
+        notch = input$chBplotBoxNotches, 
+        outlier.colour = if (input$chBplotBoxOutliers)
           'red'
         else
           NA
       ) 
     
     p.out = p.out +
-      scale_fill_discrete(name = '') +
-      xlab('') +
-      ylab('') +
+      scale_fill_discrete(name = in.labels$legend) +
+      xlab(in.labels$x) +
+      ylab(in.labels$y) +
       LOCggplotTheme(in.font.base = PLOTFONTBASE, 
                      in.font.axis.text = PLOTFONTAXISTEXT, 
                      in.font.axis.title = PLOTFONTAXISTITLE, 
                      in.font.strip = PLOTFONTFACETSTRIP, 
                      in.font.legend = PLOTFONTLEGEND) + 
-      theme(legend.position = input$selPlotBoxLegendPos,
+      theme(legend.position = input$selPlotLegendPos,
             axis.text.x = LOCrotatedAxisElementText(as.numeric(input$rBAxisLabelsRotate), 
                                                     size = PLOTFONTAXISTEXT))
     

modules/auxfunc.R

@@ -129,16 +129,16 @@ l.col.pal.dend.2 = list(
 
 # Clustering algorithms ----
 
-s.cl.linkage = c("average",
-                 "complete",
+s.cl.linkage = c("complete",
+                 "average",
                  "single",
                  "centroid",
                  "ward.D",
                  "ward.D2",
                  "mcquitty")
 
-s.cl.spar.linkage = c("average",
-                      "complete", 
+s.cl.spar.linkage = c("complete",
+                      "average",
                       "single",
                       "centroid")
 
@@ -191,10 +191,9 @@ help.text.short = c(
   'Normalise with respect to this time span.',                                                                                     #12
   'Calculate fold-change and z-score using the median and Median Absolute Deviation, instead of the mean and sd.',                 #13
   'Normalise to mean/median of selected time calculated globally, per group, or for individual time series.',                      #14
-  'Instead of the value at a selected time point, y-axis can display a difference between values at time points on y- and x-axis.',#15
+  'Instead of the value at a selected time point, y-axis can display a difference between values at two selected time points.',    #15
   'Add a line with linear regression and regions of 95% confidence interval.',                                                     #16
-  'A number of time points left & right of selected time points; use the mean/min/max of values from these time points for the scatterplot.', #17
-  'Operations to perform on values at time points selected in the field above.'                                                    #18
+  'A number of time points left & right of selected time points; use the mean of values from these time points for the scatterplot.' #17
 )
 
 # Functions for data processing ----
@@ -809,7 +808,7 @@ LOCggplotScat = function(dt.arg,
                         trend.arg = T,
                         ci.arg = 0.95) {
   
-  p.tmp = ggplot(dt.arg, aes(x = x, y = y)) +
+  p.tmp = ggplot(dt.arg, aes(x = x, y = y, label = id)) +
     geom_point(alpha = alpha.arg)
 
   if (trend.arg) {

modules/clDistPlot.R

@@ -65,7 +65,7 @@ modClDistPlot = function(input, output, session, in.data, in.cols = NULL, in.fna
     
     p.out = p.out + 
       scale_y_continuous(labels = percent) +
-      ylab("Percentage of time-series\n") +  
+      ylab("Percentage of time series\n") +  
       xlab("Groups") +  
       LOCggplotTheme(in.font.base = PLOTFONTBASE, 
                      in.font.axis.text = PLOTFONTAXISTEXT, 

modules/distPlot.R

+#
+# Time Course Inspector: Shiny app for plotting time series data
+# Author: Maciej Dobrzynski
+#
+# This module is for plotting distrubutions at selected time points as a choice of box/violin/dot-plots
+# Assumes in.data contains columns:
+# realtime
+# y
+# group
+# id
+
+# UI ----
+modDistPlotUI =  function(id, label = "Plot distributions") {
+  ns <- NS(id)
+  
+  tagList(
+    fluidRow(
+      column(
+        4,
+        checkboxInput(ns("chBplotTypeBox"),  "Box-plot", value = T),
+        checkboxInput(ns("chBplotTypeDot"),  "Dot-plot", value = F),
+        checkboxInput(ns("chBplotTypeViol"), "Violin-plot", value = F),
+        checkboxInput(ns("chBplotTypeLine"), "Line-plot", value = F),
+        checkboxInput(ns('chBplotInt'), 'Interactive Plot'),
+        actionButton(ns('butPlot'), 'Plot!')
+      ),
+      column(
+        4,
+        uiOutput(ns('uiPlotBoxNotches')),
+        uiOutput(ns('uiPlotBoxOutliers')),
+        uiOutput(ns('uiPlotBoxDodge')),
+        uiOutput(ns('uiPlotBoxAlpha')),
+        uiOutput(ns('uiPlotDotNbins')),
+        uiOutput(ns('uiPlotDotAlpha')),
+        uiOutput(ns('uiPlotViolAlpha')),
+        uiOutput(ns('uiPlotLineAlpha'))
+      ),
+      column(
+        4,
+        selectInput(
+          ns('selPlotBoxLegendPos'),
+          label = 'Legend position',
+          choices = list(
+            "Top" = 'top',
+            "Right" = 'right',
+            "Bottom" = 'bottom'
+          ), 
+          width = "120px",
+          selected = 'top'
+        ),
+        radioButtons(ns("rBAxisLabelsRotate"), "X-axis labels",
+                     c("horizontal" = 0,
+                       "45 deg" = 45,
+                       "90 deg" = 90)),
+        numericInput(
+          ns('inPlotBoxWidth'),
+          'Width [%]',
+          value = PLOTWIDTH,
+          min = 10,
+          width = '100px',
+          step = 10
+        ),
+        numericInput(
+          ns('inPlotBoxHeight'),
+          'Height [px]',
+          value = PLOTBOXHEIGHT,
+          min = 100,
+          width = '100px',
+          step = 50
+        )
+      )
+    ),
+    
+    uiOutput(ns('uiPlotBox')),
+    downPlotUI(ns('downPlotBox'), "Download PDF")
+  )
+}
+
+# SERVER ----
+modDistPlot = function(input, output, session, 
+                      in.data,                       # input data table in long format
+                      in.cols = list(meas.x = COLRT, # column names
+                                     meas.y = COLY,
+                                     group = COLGR,
+                                     id = COLID), 
+                      in.labels = list(x = "",       # plot labels
+                                       y = "", 
+                                       legend = ""),
+                      in.fname) {                      # file name for saving the plot
+
+  ns <- session$ns
+  
+  output$uiPlotBoxNotches = renderUI({
+    cat(file = stderr(), 'boxPlot:uiPlotBoxNotches\n')
+    
+    ns <- session$ns
+    
+    if(input$chBplotTypeBox)
+      checkboxInput(ns('chBplotBoxNotches'), 'Notches in box-plot ', FALSE)
+  })
+  
+  output$uiPlotBoxOutliers = renderUI({
+    cat(file = stderr(), 'boxPlot:uiPlotBoxOutliers\n')
+    
+    ns <- session$ns
+    
+    if(input$chBplotTypeBox)
+      checkboxInput(ns('chBplotBoxOutliers'), 'Outliers in box-plot', FALSE)
+  })
+  
+  output$uiPlotBoxDodge = renderUI({
+    cat(file = stderr(), 'boxPlot:uiPlotBoxDodge\n')
+    
+    ns <- session$ns
+    
+    # Adjust spacing between box-, violin-, dot-plots.
+    # Valid only when plotting multiple groups at a time point.
+    # For line plot, each group is drawn separately per facet, thus no need for dodging..
+    
+    if(!input$chBplotTypeLine)
+      sliderInput(ns('slPlotBoxDodge'), 'Space between groups', min = 0, max = 1, value = .4, step = 0.05)
+  })
+  
+  output$uiPlotBoxAlpha = renderUI({
+    cat(file = stderr(), 'boxPlot:uiPlotBoxAlpha\n')
+    
+    ns <- session$ns
+    
+    if(input$chBplotTypeBox)
+      sliderInput(ns('slPlotBoxAlpha'), 'Box-plot transparency', min = 0, max = 1, value = 1, step = 0.1)
+  })
+  
+  output$uiPlotViolAlpha = renderUI({
+    cat(file = stderr(), 'boxPlot:uiPlotViolAlpha\n')
+    
+    ns <- session$ns
+    
+    if(input$chBplotTypeViol)
+      sliderInput(ns('slPlotViolAlpha'), 'Violin-plot transparency', min = 0, max = 1, value = 1, step = 0.1)
+  })
+  
+  output$uiPlotDotAlpha = renderUI({
+    cat(file = stderr(), 'boxPlot:uiPlotDotAlpha\n')
+    
+    ns <- session$ns
+    
+    if(input$chBplotTypeDot)
+      sliderInput(ns('slPlotDotAlpha'), 'Dot-plot transparency', min = 0, max = 1, value = 1, step = 0.1)
+  })
+  
+  output$uiPlotLineAlpha = renderUI({
+    cat(file = stderr(), 'boxPlot:uiPlotLineAlpha\n')
+    
+    ns <- session$ns
+    
+    if(input$chBplotTypeLine)
+      sliderInput(ns('slPlotLineAlpha'), 'Line-plot transparency', min = 0, max = 1, value = 1, step = 0.1)
+  })
+  
+  output$uiPlotDotNbins = renderUI({
+    cat(file = stderr(), 'boxPlot:uiPlotDotNbins\n')
+    
+    ns <- session$ns
+    
+    if(input$chBplotTypeDot)
+      sliderInput(ns('slPlotDotNbins'), 'Number of bins in dot-plot', min = 2, max = 50, value = 30, step = 1)
+  })
+  
+  # Boxplot - display
+  output$outPlotBox = renderPlot({
+    locBut = input$butPlot
+    
+    if (locBut == 0) {
+      cat(file = stderr(), 'boxPlot:Go button not pressed\n')
+      return(NULL)
+    }
+    
+    plotBox()
+    
+  })
+  
+  
+  output$outPlotBoxInt = renderPlotly({
+    locBut = input$butPlot
+    
+    if (locBut == 0) {
+      cat(file = stderr(), 'boxPlot:Go button not pressed\n')
+      return(NULL)
+    }
+    
+    # This is required to avoid 
+    # "Warning: Error in <Anonymous>: cannot open file 'Rplots.pdf'"
+    # When running on a server. Based on:
+    # https://github.com/ropensci/plotly/issues/494
+    if (names(dev.cur()) != "null device") dev.off()
+    pdf(NULL)
+    
+    return( ggplotly(plotBox())  %>% layout(boxmode = 'group', width = '100%', height = '100%'))
+    
+  })
+  
+  
+  output$uiPlotBox <- renderUI({
+    ns <- session$ns
+    
+    if (input$chBplotInt)
+      plotlyOutput(ns("outPlotBoxInt"), 
+                   width = paste0(input$inPlotBoxWidth, '%'),
+                   height = paste0(input$inPlotBoxHeight, 'px'))
+    else
+      plotOutput(ns('outPlotBox'),
+                 width = paste0(input$inPlotBoxWidth, '%'),
+                 height = paste0(input$inPlotBoxHeight, 'px'))
+  })
+  
+  # Boxplot - download pdf
+  callModule(downPlot, "downPlotBox", in.fname, plotBox, TRUE)
+  
+  # Function instead of reactive as per:
+  # http://stackoverflow.com/questions/26764481/downloading-png-from-shiny-r
+  # This function is used to plot and to downoad a pdf
+  
+  plotBox <- function() {
+    cat(file = stderr(), 'plotBox\n')
+    
+    loc.dt = in.data()
+    
+    cat(file = stderr(), "plotBox: on to plot\n\n")
+    if (is.null(loc.dt)) {
+      cat(file = stderr(), 'plotBox: dt is NULL\n')
+      return(NULL)
+    }
+    
+    cat(file = stderr(), 'plotBox:dt not NULL\n')
+    
+    if(!input$chBplotTypeLine) {
+      # Dodging series only for box-, dot-, and violin-plots 
+      loc.par.dodge <- position_dodge(width = input$slPlotBoxDodge)
+      
+      # Color fill for all oplots except line, in which groups are plotted per facet
+      p.out = ggplot(loc.dt, aes_string(x = sprintf("factor(%s)", in.cols$meas.x), 
+                                        y = in.cols$meas.y,
+                                        fill = in.cols$group)) 
+      
+    }
+    else {
+      loc.par.dodge = position_dodge(width = 1)
+      p.out = ggplot(loc.dt, aes_string(x = sprintf("factor(%s)", in.cols$meas.x), 
+                                        y = in.cols$meas.y))