cyt_pca: Analyze Data with Principal Component Analysis (PCA) for...

In CytoProfile: Cytokine Profiling Analysis Tool

Analyze Data with Principal Component Analysis (PCA) for Cytokines.

Description

This function performs Principal Component Analysis (PCA) on cytokine data and generates several types of plots, including:

• 2D PCA plots using mixOmics' plotIndiv function,

• 3D scatter plots (if style is "3d" or "3D" and comp_num is 3) via the plot3D package,

• Scree plots showing both individual and cumulative explained variance,

• Loadings plots, and

• Biplots and correlation circle plots.

Usage

cyt_pca(
  data,
  group_col = NULL,
  group_col2 = NULL,
  colors = NULL,
  output_file,
  ellipse = FALSE,
  comp_num = 2,
  scale = c("none", "log2", "log10", "zscore", "custom"),
  custom_fn = NULL,
  pch_values = NULL,
  style = NULL
)

Arguments

data	A data frame containing cytokine data. It should include at least one column representing grouping information and optionally a second column representing treatment or stimulation.
group_col	A string specifying the column name that contains the first group information. If group_col2 is not provided, an overall analysis will be performed.
group_col2	A string specifying the second grouping column. Default is NULL.
colors	A vector of colors corresponding to the groups. If set to NULL, a palette is generated using rainbow() based on the number of unique groups.
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 that the file extension matches the desired format (e.g., ".pdf" for PDF output or ".png" for PNG output or .tiff for TIFF output).
ellipse	Logical. If TRUE, a 95% confidence ellipse is drawn on the PCA individuals plot. Default is FALSE.
comp_num	Numeric. The number of principal components to compute and display. Default is 2.
scale	Character string specifying a transformation to apply to numeric variables before PCA. Options are "none" (no transformation), "log2", "log10", "zscore", or "custom". When "custom" is selected, a user supplied function must be given via custom_fn. Defaults to "none".
custom_fn	A custom function used when scale = "custom". Should take a numeric vector and return a numeric vector. Ignored otherwise.
pch_values	A vector of plotting symbols (pch values) to be used in the PCA plots. Default is NULL.
style	Character. If set to "3d" or "3D" and comp_num equals 3, a 3D scatter plot is generated using the plot3D package. Default is NULL.

Value

A PDF file containing the PCA plots is generated and saved when output_file is provided. Otherwise, plots are displayed on the current graphics device.

Author(s)

Shubh Saraswat

Examples

# Load sample data
data <- ExampleData1[, -c(3,23)]
data_df <- dplyr::filter(data, Group != "ND" & Treatment != "Unstimulated")
# Run PCA analysis and save plots to a PDF file
cyt_pca(
  data = data_df,
  output_file = NULL,
  colors = c("black", "red2"),
  scale = "log2",
  comp_num = 3,
  pch_values = c(16, 4),
  style = "3D",
  group_col = "Group",
  group_col2 = "Treatment",
  ellipse = FALSE
)

CytoProfile documentation built on Feb. 27, 2026, 5:06 p.m.