| Type: | Package |
| Title: | Projection Visualization Plots for Dimensionally Reduced Data |
| Version: | 0.1.1 |
| Description: | Creates visualization plots for 2D projected data including ellipse plots, Voronoi diagram plots, and combined ellipse-Voronoi plots. Designed to visualize class separation in dimensionally reduced data from techniques like principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) or others. For more details see Lotsch and Ultsch (2024) <doi:10.1016/j.imu.2024.101573>. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| Depends: | R (≥ 3.5.0) |
| Imports: | ggplot2, ggrepel, deldir |
| RoxygenNote: | 7.2.0 |
| NeedsCompilation: | no |
| Packaged: | 2025-06-07 15:00:40 UTC; joern |
| Author: | Jorn Lotsch  [aut,
cre] |
| Maintainer: | Jorn Lotsch <j.lotsch@em.uni-frankfurt.de> |
| Repository: | CRAN |
| Date/Publication: | 2025-06-19 19:20:14 UTC |
Projection Visualization Plots for Dimensionally Reduced Data
Description
Creates visualization plots for 2D projected data including ellipse plots, Voronoi diagram plots, and combined ellipse-Voronoi plots. Designed to visualize class separation in dimensionally reduced data from techniques like principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) or others. For more details see Lotsch and Ultsch (2024) <doi:10.1016/j.imu.2024.101573>.
Details
The VoronoiBiomedPlot package provides functions for creating visualization plots of 2D projected data, particularly useful for biomedical data analysis and dimensionality reduction results.
The package includes two main functions:
-
create_projection_plots: Creates three types of plots (ellipse, Voronoi, and combined) -
create_voronoi_plot: Creates standalone Voronoi tessellation plots
These functions are designed to visualize class separation in dimensionally reduced data from techniques like PCA, PLS-DA, t-SNE, or other projection methods commonly used in biomedical research.
Voronoi tessellation divides the plot space into regions based on proximity to data points, providing an intuitive visualization of class boundaries and decision regions. Confidence ellipses show the distribution spread and correlation structure within each class.
Author(s)
Jorn Lotsch <j.lotsch@em.uni-frankfurt.de>
References
Lötsch, J. and A. Ultsch (2024). Comparative assessment of projection and clustering method combinations in the analysis of biomedical data. Informatics in Medicine Unlocked 50: 101573. https://www.sciencedirect.com/science/article/pii/S2352914824001291
See Also
Report bugs at https://github.com/JornLotsch/voronoi_projection_plot/issues
Examples
# Load the iris dataset
data <- iris[, c("Sepal.Length", "Petal.Length", "Species")]
# Create comprehensive projection plots
plots <- create_projection_plots(
data = data,
class_column = "Species",
legend_position = "bottom",
add_grid_lines = FALSE
)
# Access individual plots
# plots$ellipse_plot
# plots$voronoi_plot
# plots$voronoi_plot_plus_ellipse
# Create standalone Voronoi plot
voronoi_plot <- create_voronoi_plot(
data = data,
class_column = "Species",
legend_position = "bottom",
add_grid_lines = FALSE
)
Create Projection Visualization Plots
Description
Creates three types of visualization plots for 2D projected data: ellipse plots, Voronoi diagram plots, and combined ellipse-Voronoi plots. The function is designed to visualize class separation in dimensionally reduced data.
Usage
create_projection_plots(
data,
class_column = NULL,
alternative_class_column = NULL,
coordinate_columns = NULL,
case_labels = NULL,
coord_names = c("Dim1", "Dim2"),
title = NULL,
show_labels = FALSE,
ellipse_alpha = 0.1,
voronoi_alpha = 0.3,
point_size = 2,
legend_position = "bottom",
color_palette = NULL,
add_grid_lines = FALSE,
color_points = "primary",
fill_voronoi = "primary",
point_shape = "none",
label_fontface = "plain",
label_size = 3.88
)
Arguments
data |
A data frame containing projected data. Must have at least 2 numeric columns. If more than 2 columns are provided, the first 2 are used as coordinates. |
class_column |
Character string specifying the column name containing class labels, or a vector of class labels. If NULL, all observations are treated as a single class. Default: NULL. |
alternative_class_column |
Character string specifying the column name containing alternative class labels, or a vector of alternative class labels. If NULL, uses class_column. Default: NULL. |
coordinate_columns |
Character vector of length 2 specifying the column names to use as coordinates. If NULL, uses the first two numeric columns. Default: NULL. |
case_labels |
Character vector of case labels for individual observations. If NULL, row numbers are used. Default: NULL. |
coord_names |
Character vector of length 2 specifying names for the coordinate axes. Default: c("Dim1", "Dim2"). |
title |
Character string for plot title. If NULL, no title is added. Default: NULL. |
show_labels |
Logical indicating whether to show case labels on plots. Default: FALSE. |
ellipse_alpha |
Numeric value (0-1) for ellipse transparency. Default: 0.1. |
voronoi_alpha |
Numeric value (0-1) for Voronoi polygon transparency. Default: 0.3. |
point_size |
Numeric value for point size. Default: 2. |
legend_position |
Character string or numeric vector specifying legend position. Default: "bottom". |
color_palette |
Function or character vector for color palette. If NULL, uses ggplot2 default colors. Default: NULL. |
add_grid_lines |
Logical indicating whether to add dashed grid lines at origin. Default: FALSE. |
color_points |
Character string specifying which classification to use for point colors. Either "primary" (uses class_column) or "alternative" (uses alternative_class_column). Default: "primary". |
fill_voronoi |
Character string specifying which classification to use for Voronoi fill. Either "primary" (uses class_column) or "alternative" (uses alternative_class_column). Default: "primary". |
point_shape |
Character string specifying which classification to use for point shapes. Either "primary" (uses class_column), "alternative" (uses alternative_class_column), or "none" (no shape differentiation). Default: "none". |
label_fontface |
Character string specifying the font face for text labels. Options include "plain", "bold", "italic", "bold.italic". Default: "plain". |
label_size |
Numeric value specifying the size of text labels. Default: 3.88. |
Details
The function creates visualizations for 2D projected data, particularly useful for displaying results from dimensionality reduction techniques like PCA, PLS-DA, or t-SNE.
Voronoi tessellation divides the plot space into regions based on proximity to data points, providing an intuitive visualization of class boundaries and decision regions.
Confidence ellipses show the distribution spread and correlation structure within each class.
Value
A list containing three ggplot objects:
ellipse_plot |
Plot with confidence ellipses for each class |
voronoi_plot |
Plot with Voronoi tessellation regions |
voronoi_plot_plus_ellipse |
Combined plot with both Voronoi regions and ellipses |
Examples
# Basic usage with iris dataset
data <- iris[, c("Sepal.Length", "Petal.Length", "Species")]
plots <- create_projection_plots(
data = data,
class_column = "Species",
legend_position = "bottom",
add_grid_lines = FALSE
)
Create Voronoi Projection Visualization Plot
Description
Creates a Voronoi tessellation visualization for 2D projected data, showing class separation through proximity-based regions.
Usage
create_voronoi_plot(
data,
class_column = NULL,
alternative_class_column = NULL,
coordinate_columns = NULL,
case_labels = NULL,
coord_names = c("Dim1", "Dim2"),
title = NULL,
show_labels = FALSE,
voronoi_alpha = 0.3,
point_size = 2,
legend_position = "bottom",
color_palette = NULL,
add_grid_lines = FALSE,
color_points = "primary",
fill_voronoi = "primary",
point_shape = "none",
label_fontface = "plain",
label_size = 3.88
)
Arguments
data |
A data frame containing projected data. Must have at least 2 numeric columns. If more than 2 columns are provided, the first 2 are used as coordinates. |
class_column |
Character string specifying the column name containing class labels, or a vector of class labels. If NULL, all observations are treated as a single class. Default: NULL. |
alternative_class_column |
Character string specifying the column name containing alternative class labels, or a vector of alternative class labels. If NULL, uses class_column. Default: NULL. |
coordinate_columns |
Character vector of length 2 specifying the column names to use as coordinates. If NULL, uses the first two numeric columns. Default: NULL. |
case_labels |
Character vector of case labels for individual observations. If NULL, row numbers are used. Default: NULL. |
coord_names |
Character vector of length 2 specifying names for the coordinate axes. Default: c("Dim1", "Dim2"). |
title |
Character string for plot title. If NULL, no title is added. Default: NULL. |
show_labels |
Logical indicating whether to show case labels on plots. Default: FALSE. |
voronoi_alpha |
Numeric value (0-1) for Voronoi polygon transparency. Default: 0.3. |
point_size |
Numeric value for point size. Default: 2. |
legend_position |
Character string or numeric vector specifying legend position. Default: "bottom". |
color_palette |
Function or character vector for color palette. If NULL, uses ggplot2 default colors. Default: NULL. |
add_grid_lines |
Logical indicating whether to add dashed grid lines at origin. Default: TRUE. |
color_points |
Character string specifying which classification to use for point colors. Either "primary" (uses class_column) or "alternative" (uses alternative_class_column). Default: "primary". |
fill_voronoi |
Character string specifying which classification to use for Voronoi fill. Either "primary" (uses class_column) or "alternative" (uses alternative_class_column). Default: "primary". |
point_shape |
Character string specifying which classification to use for point shapes. Either "primary" (uses class_column), "alternative" (uses alternative_class_column), or "none" (no shape differentiation). Default: "none". |
label_fontface |
Character string specifying the font face for text labels. Options include "plain", "bold", "italic", "bold.italic". Default: "plain". |
label_size |
Numeric value specifying the size of text labels. Default: 3.88. |
Details
The function creates a Voronoi tessellation visualization for 2D projected data, particularly useful for displaying results from dimensionality reduction techniques. Voronoi tessellation divides the plot space into regions based on proximity to data points, providing an intuitive visualization of class boundaries and decision regions.
Value
A ggplot object showing the Voronoi tessellation plot.
Examples
# Basic usage with iris dataset
data <- iris[, c("Sepal.Length", "Petal.Length", "Species")]
plot <- create_voronoi_plot(
data = data,
class_column = "Species",
legend_position = "bottom",
add_grid_lines = FALSE
)