sigScore: Calculate Signature Score Using PCA, Mean, or Z-score Methods

In IOBR: Immune Oncology Biological Research

Calculate Signature Score Using PCA, Mean, or Z-score Methods

Description

Computes signature scores from gene expression data using Principal Component Analysis (PCA), mean-based, or z-score approaches.

Usage

sigScore(eset, methods = c("PCA", "mean", "zscore"))

Arguments

eset	Normalized expression matrix with genes (signature) as rows and samples as columns.
methods	Scoring method: '"PCA"' (default) for principal component 1, '"mean"' for mean expression, or '"zscore"' for z-score normalized mean.

Value

Numeric vector of length 'ncol(eset)'; a score summarizing the rows of 'eset'.

Author(s)

Dorothee Nickles, Dongqiang Zeng

Examples

# Create small example expression matrix
set.seed(123)
test_eset <- matrix(rnorm(1000), nrow = 10, ncol = 100)
rownames(test_eset) <- paste0("Gene", 1:10)
colnames(test_eset) <- paste0("Sample", 1:100)

# Calculate scores
score_pca <- sigScore(eset = test_eset, methods = "PCA")
score_mean <- sigScore(eset = test_eset, methods = "mean")
score_zscore <- sigScore(eset = test_eset, methods = "zscore")

IOBR documentation built on May 30, 2026, 5:07 p.m.