Various tooltip updates

.gitignore

+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata

modules/auxfunc.R

@@ -181,16 +181,16 @@ helpText.server = c(
   'Long format: a row is a single data point. Wide format: a row is a time series with columns as time points.',                   #2
   'Generate 60 random synthetic time series distributed evenly among 6 groups. Every time series has 60 time points.',             #3
   'Load CSV file with a column of track IDs for removal. IDs should correspond to those used for plotting.',                       #4
-  'Load CSV file with 5 columns: grouping, start and end tpts of stimulation, start and end of y-position, dummy column with ID.', #5
-  'Interpolate missing time points and pre-existing NAs. The interval of the time column must be provided!',                       #6
-  'If the track ID is unique only within a group, make it unique globally by combining with grouping columns.',                    #7
+  'Load CSV file with 5 columns: grouping, start and end time points of stimulation, start and end of y-position, dummy column with ID.', #5
+  'Interpolate missing time points indicated with NAs. In addition, add NA if a row with a time point is completely missing. The interval of the time column must be provided to know which rows are missing.',                       #6
+  'If the track ID is not globally unique, try to make it unique by prepending another column to the track ID (typically the group column).',                    #7
   'Select columns to group data according to treatment, condition, etc.',                                                          #8
   'Select math operation to perform on a single or two columns,',                                                                  #9
   'Select range of time for further processing.',                                                                                  #10
-  'Divide measurments by the mean/median or calculate z-score with respect to selected time span.',                                #11
+  'Divide measurements by the mean/median or calculate z-score with respect to selected time span.',                                #11
   'Fold-change or z-score with respect to selected time span.',                                                                    #12
   'Normalise with respect to this time span.',                                                                                     #13
-  'Calculate fold-change and z-score using the median and Median Absolute Deviation, instead of the mean and sd.',                 #14
+  'Calculate fold-change and z-score using the median and Median Absolute Deviation, instead of the mean and standard deviation.',                 #14
   'Normalise to mean/median of selected time calculated globally, per group, or for individual time series.',                      #15
   'Download time series after modification in this section.'                                                                       #16
 )

modules/tabClHier.R

@@ -35,7 +35,7 @@ clustHierUI <- function(id, label = "Hierarchical CLustering") {
                  "Ward D2" = 6,
                  "McQuitty" = 7
                ),
-               selected = 5
+               selected = 2
              )
       ),
       column(4,
@@ -149,9 +149,9 @@ clustHierUI <- function(id, label = "Hierarchical CLustering") {
                  )
                ),
                
-               withSpinner(plotOutput(ns('outPlotHier'))),
                actionButton(ns('butPlotHierHeatMap'), 'Plot!'),
-               downPlotUI(ns('downPlotHier'), "Download PNG")
+               downPlotUI(ns('downPlotHier'), "Download PNG"),
+               withSpinner(plotOutput(ns('outPlotHier')))
       ),
       
       tabPanel('Averages',

modules/tabClHierSpar.R

@@ -34,7 +34,7 @@ clustHierSparUI <- function(id, label = "Sparse Hierarchical CLustering") {
             "Single" = 3,
             "Centroid" = 4
           ),
-          selected = 1
+          selected = 2
         )
       ),
       

modules/tabScatter.R

@@ -14,10 +14,10 @@
 # callModule(clustHier, 'TabClustHier', dataMod)
 # where dataMod is the output from a reactive function that returns dataset ready for clustering
 
-helpText.tabScatter = c("Display measurement values from two different time points as a scatter plot.",
-                  'Y-axis can display a value at a selected time point or a difference between values at two selected time points.', #1
+helpText.tabScatter = c("Display measurement relationship between two different time points as a scatter plot. Instead of using the exact value of time points, can also use local average values around them with the smoothing option.",
+                  'Y-axis can display a value at a selected time point or a difference between values at two selected time points. The former reports the magnitude of the difference while the former reports the amplitude of the difference between the 2 selected time points.', #1
                   'Add a line with linear regression and regions of 95% confidence interval.', #2
-                  'A number of time points left & right of selected time points; use the mean of values from these time points for the scatterplot.', #3
+                  'Window length for moving average smoothing used before plotting the scatterplot. Useful to avoid artefacts in the scatterplot due to spurious variations at specific time points.', #3
                   'Height in pixels of the displayed plot', #4
                   'Number of facets in a row. Each facet displayes a scatter plot for a single group.' #5
 )
@@ -48,7 +48,7 @@ tabScatterPlotUI <- function(id, label = "Comparing t-points") {
         bsTooltip(ns('inNeighTpts'), helpText.tabScatter[4], placement = "bottom", trigger = "hover", options = NULL),
 
         radioButtons(ns('rBfoldChange'), 'Y-axis', 
-                     choices = c("Y" = "y", "Y-X" = "diff"), 
+                     choices = c("Y" = "y", "Y - X" = "diff"), 
                      width = "100px", inline = T),
         bsTooltip(ns('rBfoldChange'), helpText.tabScatter[2], placement = "bottom", trigger = "hover", options = NULL)
         
@@ -79,7 +79,7 @@ tabScatterPlotUI <- function(id, label = "Comparing t-points") {
     
     br(),
     checkboxInput(ns('plotInt'), 
-                  'Interactive Plot?',
+                  'Interactive Plot',
                   value = FALSE),
     actionButton(ns('butGoScatter'), 'Plot!'),
     uiOutput(ns("plotInt_ui")),

modules/trajPlot.R

@@ -170,7 +170,7 @@ modTrajPlot = function(input, output, session,
         ns('inSetYboundsLow'),
         label = 'Lower',
         step = 0.1, 
-        value = floor(min(loc.dt[[COLY]], na.rm = T))
+        value = min(loc.dt[[COLY]], na.rm = T)
       )
     }
   })
@@ -192,7 +192,7 @@ modTrajPlot = function(input, output, session,
         ns('inSetYboundsHigh'),
         label = 'Upper',
         step = 0.1, 
-        value = ceil(max(loc.dt[[COLY]], na.rm = T))
+        value = max(loc.dt[[COLY]], na.rm = T)
       )
     }
   })

modules/trajRibbonPlot.R

@@ -146,7 +146,7 @@ modTrajRibbonPlot = function(input, output, session,
         ns('inSetYboundsLow'),
         label = 'Lower',
         step = 0.1, 
-        value = floor(min(loc.dt[[COLY]], na.rm = T))
+        value = min(loc.dt[[COLY]], na.rm = T)
       )
     }
   })
@@ -168,7 +168,7 @@ modTrajRibbonPlot = function(input, output, session,
         ns('inSetYboundsHigh'),
         label = 'Upper',
         step = 0.1, 
-        value = ceil(max(loc.dt[[COLY]], na.rm = T))
+        value = max(loc.dt[[COLY]], na.rm = T)
       )
     }
   })

server.R

@@ -235,7 +235,7 @@ shinyServer(function(input, output, session) {
         #cat('UI varSelGroup::locColSel ', locColSel, '\n')
         selectInput(
           'inSelGroup',
-          'Select:',
+          'Group column:',
           locCols,
           width = '100%',
           selected = locColSel,

ui.R

@@ -100,7 +100,7 @@ shinyUI(fluidPage(
       uiOutput('uiChBnormGroup'),
 
       tags$hr(),
-      downloadButton('downloadDataClean', 'Download mod\'d data'),
+      downloadButton('downloadDataClean', 'Download processed data'),
       bsTooltip('downloadDataClean', helpText.server[16], placement = "bottom", trigger = "hover", options = NULL)
     ),