The function superplot creates a SuperPlot using ggplot2.
Usage
superplot(
df,
meas,
cond,
repl,
pal = "tol_bright",
xlab = "",
ylab = "Measurement",
datadist = "sina",
size = c(2, 3),
alpha = c(0.5, 0.7),
bars = "mean_sd",
linking = FALSE,
rep_summary = "rep_mean",
shapes = FALSE,
fsize = 12,
gg = NULL,
stats = FALSE,
stats_test = "para_unpaired",
info = FALSE
)Arguments
- df
data frame with at least three columns: meas, cond, repl
- meas
character name of column with measurement (e.g. intensity)
- cond
character name of column with condition (e.g. Control, WT)
- repl
character name of column with replicate (e.g. unique experiment identifiers)
- pal
name of colour palette to use (default is "tol_bright")
- xlab
string for x label (default is empty)
- ylab
string for y label (default is "Measurement")
- datadist
string for data distribution to use, select ("sina" default, "jitter", or "violin")
- size
numeric vector of size range data and summary points (default is c(2, 3))
- alpha
numeric vector of alpha range data and summary points (default is c(0.5, 0.7))
- bars
string for type of error bars to add, select "mean_sd" (default), "mean_sem", or "mean_ci"; for no bars use an empty string (""); for no error bars but still show the mean with a crossbar, use "none".
- linking
logical for whether to link summary points between conditions (default is FALSE)
- rep_summary
string for summary statistic to use for replicates, select ("rep_mean" default, or "rep_median")
- shapes
logical for whether to use different shapes for replicates
- fsize
numeric font size for text (default is 12)
- gg
ggplot object to add to (default is NULL)
- stats
logical for whether to add statistical tests (default is FALSE)
- stats_test
string for statistical test to use, select ("para_unpaired", "para_paired", "nonpara_unpaired", or "nonpara_paired")
- info
logical for whether to print information about the plot (default is FALSE)
