plot_4d_scatterbar: Plot scatter plot with bar & error bars for 2-way ANOVAs with...

In grafify: Easy Graphs for Data Visualisation and Linear Models for ANOVA

Plot scatter plot with bar & error bars for 2-way ANOVAs with or without a blocking factor.

Description

There are 4 related functions for 2-way ANOVA type plots. In addition to a categorical variable along the X-axis, a grouping factor is passed to either points, bars or boxes argument in these functions. A blocking factor (or any other categorical variable) can be optionally passed to the shapes argument.

1. plot_4d_point_sd (mean & SD, SEM or CI95 error bars)

2. plot_4d_scatterbar (bar & SD, SEM or CI95 error bars)

3. plot_4d_scatterbox (box & whiskers)

4. plot_4d_scatterviolin (box & whiskers, violin)

Usage

plot_4d_scatterbar(
  data,
  xcol,
  ycol,
  bars,
  shapes,
  facet,
  ErrorType = "SD",
  symsize = 3,
  s_alpha = 0.8,
  b_alpha = 1,
  bwid = 0.7,
  jitter = 0.1,
  ewid = 0.2,
  TextXAngle = 0,
  LogYTrans,
  LogYBreaks = waiver(),
  LogYLabels = waiver(),
  LogYLimits = NULL,
  facet_scales = "fixed",
  fontsize = 20,
  group_wid = 0.8,
  symthick,
  bthick,
  ColPal = c("okabe_ito", "all_grafify", "bright", "contrast", "dark", "fishy", "kelly",
    "light", "muted", "pale", "r4", "safe", "vibrant"),
  ColRev = FALSE,
  ColSeq = TRUE,
  ...
)

Arguments

data	a data table, e.g. data.frame or tibble.
xcol	name of the column with the categorical factor to plot on X axis. If column is numeric, enter as factor(col).
ycol	name of the column to plot on quantitative variable on the Y axis.
bars	name of the column containing grouping within the factor plotted on X axis. Can be categorical or numeric X. If your table has numeric X and you want to plot as factor, enter xcol = factor(name of colum).
shapes	name of the column that contains matched observations (e.g. subject IDs, experiment number) or another variable to pass on to symbol shapes. If not provided, the shapes for all groups is the same.
facet	add another variable from the data table to create faceted graphs using ggplot2facet_wrap.
ErrorType	select the type of error bars to display. Default is "SD" (standard deviation). Other options are "SEM" (standard error of the mean) and "CI95" (95% confidence interval based on t distributions).
symsize	size of symbols, default set to 3.
s_alpha	fractional opacity of symbols, default set to 0.8 (i.e. 80% opacity). Set s_alpha = 0 to not show scatter plot.
b_alpha	fractional opacity of boxes. Default is set to 0, which results in white boxes inside violins. Change to any value >0 up to 1 for different levels of transparency.
bwid	width of boxes; default 0.7.
jitter	extent of jitter (scatter) of symbols, default is 0.1. Increase to reduce symbol overlap, set to 0 for aligned symbols.
ewid	width of error bars, default set to 0.2.
TextXAngle	orientation of text on X-axis; default 0 degrees. Change to 45 or 90 to remove overlapping text.
LogYTrans	transform Y axis into "log10" or "log2"
LogYBreaks	argument for ggplot2[scale_y_continuous] for Y axis breaks on log scales, default is waiver(), or provide a vector of desired breaks.
LogYLabels	argument for ggplot2[scale_y_continuous] for Y axis labels on log scales, default is waiver(), or provide a vector of desired labels.
LogYLimits	a vector of length two specifying the range (minimum and maximum) of the Y axis.
facet_scales	whether or not to fix scales on X & Y axes for all facet facet graphs. Can be fixed (default), free, free_y or free_x (for Y and X axis one at a time, respectively).
fontsize	parameter of base_size of fonts in theme_classic, default set to size 20.
group_wid	space between the factors along X-axis, i.e., dodge width. Default group_wid = 0.8 (range 0-1), which can be set to 0 if you'd like the two plotted as position = position_identity().
symthick	size (in 'pt' units) of outline of symbol lines (stroke), default = fontsize/22.
bthick	thickness (in 'pt' units) of bar and error bar lines; default = fontsize/22.
ColPal	grafify colour palette to apply, default "okabe_ito"; see graf_palettes for available palettes.
ColRev	whether to reverse order of colour within the selected palette, default F (FALSE); can be set to T (TRUE).
ColSeq	logical TRUE or FALSE. Default TRUE for sequential colours from chosen palette. Set to FALSE for distant colours, which will be applied using scale_fill_grafify2.
...	any additional arguments to pass to ggplot2stat_summary or ggplot2geom_point.

Details

These can be especially useful when the fourth variable shapes is a random factor or blocking factor (up to 25 levels are allowed; there will be an error with more levels). The shapes argument can be left blank to plot ordinary 2-way ANOVAs without blocking.

In plot_4d_point_sd and plot_4d_scatterbar, the default error bar is SD (can be changed to SEM or CI95). In plot_4d_point_sd, a large coloured symbol is plotted at the mean, all other data are shown as smaller symbols. Boxplot uses geom_boxplot to depict median (thicker line), box (interquartile range (IQR)) and the whiskers (1.5*IQR).

Colours can be changed using ColPal, ColRev or ColSeq arguments. ColPal can be one of the following: "okabe_ito", "dark", "light", "bright", "pale", "vibrant, "muted" or "contrast". ColRev (logical TRUE/FALSE) decides whether colours are chosen from first-to-last or last-to-first from within the chosen palette. ColSeq (logical TRUE/FALSE) decides whether colours are picked by respecting the order in the palette or the most distant ones using colorRampPalette.

The resulting ggplot2 graph can take additional geometries or other layers.

Value

This function returns a ggplot2 object of class "gg" and "ggplot".

Examples

#4d version for 2-way data with blocking
plot_4d_scatterbar(data = data_2w_Tdeath, 
xcol = Genotype, 
ycol = PI, 
bars = Time, 
shapes = Experiment)

#4d version without blocking factor
#`shapes` can be left blank
plot_4d_scatterbar(data = data_2w_Tdeath, 
xcol = Genotype, 
ycol = PI, 
bars = Time)

grafify documentation built on May 29, 2024, 3:49 a.m.