LongDat (version 1.1.2)

cuneiform_plot: Create cuneiform plots of result table from longdat_disc() or longdat_cont()

Description

Create cuneiform plots of result table from longdat_disc() or longdat_cont()

Value

a 'ggplot' object

Arguments

result_table

The result table from longdat_disc() or longdat_cont() output, or any data frame that has the same format.

x_axis_order

The plotting order of the x axis. It should be a character vector (e.g. c("Effect_1_2", "Effect_2_3", "Effect_1_3")).

covariate_panel

A boolean vector indicating whether to plot covariate status alongside the effect panel. The default is TRUE.

pos_color

The color for a positive effect size. It should be a hex color code (e.g. "#b3e6ff") or the colors recognized by R. The default is "red".

neg_color

The color for a negative effect size. It should be a hex color code (e.g. "#b3e6ff") or the colors recognized by R. The default is "blue".

panel_width

The width of the effect size panel on the left relative to the covariate status panel on the right (width set to 1). It should be a numerical vector. The default is 4.

title

The name of the plot title. The default is "LongDat result cuneiform plot".

title_size

The size of the plot title. The default is 20.

covariate_text_size

The size of the text in the covariate status panel. The default is 4.

x_label_size

The size of the x label. The default is 10.

y_label_size

The size of the y label. The default is 10.

legend_title_size

The size of the legend title. The default is 12.

legend_text_size

The size of the legend text The default is 10.

Details

This function creates a cuneiform plot which displays the result of longdat_disc() or longdat_cont(). It plots the effect sizes within each time interval for each feature, and also shows the covariate status. Only the features with non-NS signals will be included in the plot. The output is a ggplot object in patchwork structure. For further customization of the plot, please refer to the vignette.

Examples

test_disc <- longdat_disc(input = LongDat_disc_master_table,
data_type = "count", test_var = "Time_point",
variable_col = 7, fac_var = c(1:3))
test_plot <- cuneiform_plot(result_table = test_disc[[1]],
x_axis_order = c("Effect_1_2", "Effect_2_3", "Effect_1_3"))