Boxplots for Continuous Variables with Optional Grouping — cyt

This function generates boxplots for numeric variables in a data frame or matrix. It supports optional grouping by one or more categorical variables. Numeric variables can be scaled using various transformations before plotting. When grouping is not used, boxplots are arranged in pages with a specified maximum number of plots per page. Plots can be saved to a PDF file or returned as a list of ggplot2 objects.

Usage

cyt_bp(
  data,
  output_file = NULL,
  group_by = NULL,
  bin_size = 25,
  y_lim = NULL,
  scale = c("none", "log2", "log10", "zscore", "custom"),
  custom_fn = NULL,
  font_settings = NULL,
  progress = NULL
)

Arguments

data: A matrix or data frame containing numeric and categorical variables.
output_file: Optional string specifying the name of the file to be created. When NULL (default), plots are drawn on the current graphics device. Ensure the file extension matches the desired format (e.g., ".pdf", ".png", ".tiff").
group_by: Optional character vector specifying one or more columns to use for grouping. If NULL (default) no grouping is applied.
bin_size: Integer. Maximum number of boxplots per page when grouping is not used. Default is 25.
y_lim: Optional numeric vector giving y-axis limits for the plots. Applies to all plots.
scale: Character specifying a transformation for numeric variables. One of "none", "log2", "log10", "zscore", or "custom". When "custom", supply a function via custom_fn.
custom_fn: A user-supplied function to transform numeric columns when scale = "custom".
font_settings: Optional named list of font sizes for supported plot text elements.
progress: Optional. A Shiny Progress object for reporting progress updates.

Value

Invisibly returns a list of ggplot objects. When output_file is provided, plots are written to the specified file.

Author

Shubh Saraswat

Examples

data("ExampleData1")
# Boxplots without grouping
cyt_bp(ExampleData1[, -c(1:3)], output_file = NULL, scale = "log2")

# Boxplots grouped by Group
cyt_bp(ExampleData1[, -c(3, 5:28)], group_by = "Group", scale = "zscore")