BioThermR (version 0.1.0)

viz_thermal_barplot: Generate Publication-Ready Comparative Barplots

Description

Creates a high-quality bar plot to compare thermal metrics across experimental groups. The visualization includes bars representing the mean, customizable error bars (SD or SE), and overlaid individual data points to show biological variation.

Usage

viz_thermal_barplot(
  data,
  y_var,
  x_var,
  fill_var = NULL,
  error_bar = "mean_sd",
  add_points = TRUE,
  point_size = 1.5,
  point_alpha = 0.6,
  palette = "npg"
)

Value

A ggplot object. Can be further customized with standard ggplot2 functions.

Arguments

data

Data frame. The merged dataset (e.g., output from aggregate_replicates).

y_var

String. The name of the numeric column to plot (e.g., "Max_Temp", "Mean_Temp").

x_var

String. The name of the categorical column for the X-axis groupings (e.g., "Treatment", "Genotype").

fill_var

String. The name of the variable used for fill colors. Default is NULL, which uses x_var.

error_bar

String. The type of error bar to display. Options:

• "mean_sd": Mean +/- Standard Deviation (shows spread of data).

• "mean_se": Mean +/- Standard Error of the Mean (shows precision of the mean).

add_points

Logical. If TRUE (default), overlays individual data points using geom_jitter. This is highly recommended for small sample sizes (n < 20) to maintain transparency.

point_size

Numeric. The size of the individual jitter points. Default is 1.5.

point_alpha

Numeric. The transparency of the jitter points (0 = transparent, 1 = opaque). Default is 0.6 to handle overlapping points.

palette

String or Vector.

• If a string: Pre-defined scientific palettes ("npg" for Nature Publishing Group, "jco" for Journal of Clinical Oncology).

• If a character vector: A custom list of hex codes (e.g., c("#FF0000", "#0000FF")).

Details

This function is designed to produce figures that are immediately suitable for scientific manuscripts. Key features include:

• Automatic Statistics: Calculates Mean and SD/SE internally using stat_summary.

• Smart Coloring: Supports scientific palettes ("npg", "jco"). If the number of groups exceeds the palette size, it automatically interpolates to generate distinct colors.

• Layout: Uses theme_classic() and automatically expands the Y-axis limit by 15% to ensure error bars and significance annotations fit comfortably.

Examples

df_bio <- data.frame(
  Treatment = rep(c("ND", "HFD"), each = 5),
  Mean = c(runif(5, 33, 35), runif(5, 34, 36))
)

# Boxplot with individual points
p <- viz_thermal_barplot(df_bio,y_var="Mean",x_var="Treatment",error_bar = "mean_se")
p