Added tooltips for normalisation section

modules/auxfunc.R

@@ -165,9 +165,13 @@ help.text.short = c(
   'Select columns to group data according to treatment, condition, etc.',
   'Select math operation to perform on a single or two columns,',
   'Select range of time for further processing.',
-  'Normalise time series to a selected region.',
+  'Divide measurments by the mean/median or calculate z-score with respect to selected time span.',
   'Download time series after modification in this section.',
-  'Long format: a row is a single data point. Wide format: a row contains entire time series with columns as time points.'
+  'Long format: a row is a single data point. Wide format: a row is a time series with columns as time points.',
+  'Fold-change or z-score with respect to selected time span.',
+  'Normalise with respect to this time span.',
+  'Calculate fold-change and z-score using the median and Median Absolute Deviation, instead of the mean and sd.',
+  'Normalise to mean/median of selected time calculated globally, per group, or for individual time series.'
 )
 
 # Functions for data processing ----

server.R

@@ -327,19 +327,28 @@ shinyServer(function(input, output, session) {
   })
   
   # UI-side-panel-normalization ----
+  
+  # select normalisation method
+  # - fold-change calculates fold change with respect to the mean
+  # - z-score calculates z-score of the selected regione of the time series
   output$uiChBnorm = renderUI({
     if (DEB)
       cat(file = stdout(), 'server:uiChBnorm\n')
     
     if (input$chBnorm) {
+      tagList(
       radioButtons(
         'rBnormMeth',
         label = 'Select method',
-        choices = list('fold-change' = 'mean', 'z-score' = 'z.score')
+        choices = list('fold-change' = 'mean', 'z-score' = 'z.score'),
+        width = "40%"
+      ),
+      bsTooltip('rBnormMeth', help.text.short[11], placement = "right", trigger = "hover", options = NULL)
       )
     }
   })
   
+  # select the region of the time series for normalisation
   output$uiSlNorm = renderUI({
     if (DEB)
       cat(file = stdout(), 'server:uiSlNorm\n')
@@ -353,36 +362,49 @@ shinyServer(function(input, output, session) {
       locRTmin = min(locTpts)
       locRTmax = max(locTpts)
       
+      tagList(
       sliderInput(
         'slNormRtMinMax',
-        label = 'Time range for norm.',
+        label = 'Time span',
         min = locRTmin,
         max = locRTmax,
         value = c(locRTmin, 0.1 * locRTmax), 
         step = 1
+      ),
+      bsTooltip('slNormRtMinMax', help.text.short[12], placement = "right", trigger = "hover", options = NULL)
       )
     }
   })
   
+  # use robust stats (median instead of mean, mad instead of sd)
   output$uiChBnormRobust = renderUI({
     if (DEB)
       cat(file = stdout(), 'server:uiChBnormRobust\n')
     
     if (input$chBnorm) {
+      tagList(
       checkboxInput('chBnormRobust',
                     label = 'Robust stats',
-                    FALSE)
+                    FALSE, 
+                    width = "40%"),
+      bsTooltip('chBnormRobust', help.text.short[13], placement = "right", trigger = "hover", options = NULL)
+      )
     }
   })
   
+  # choose whether normalisation should be calculated for the entire dataset, group, or trajectory
   output$uiChBnormGroup = renderUI({
     if (DEB)
       cat(file = stdout(), 'server:uiChBnormGroup\n')
     
     if (input$chBnorm) {
+      tagList(
       radioButtons('chBnormGroup',
                    label = 'Normalisation grouping',
-                   choices = list('Entire dataset' = 'none', 'Per facet' = 'group', 'Per trajectory' = 'id'))
+                   choices = list('Entire dataset' = 'none', 'Per group' = 'group', 'Per trajectory' = 'id'), 
+                   width = "40%"),
+      bsTooltip('chBnormGroup', help.text.short[14], placement = "right", trigger = "hover", options = NULL)
+      )
     }
   })