'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
# 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