generateRef: Generate Reference Signature Matrix

In IOBR: Immune Oncology Biological Research

Generate Reference Signature Matrix

Description

Generates a reference signature matrix for cell types based on differential expression analysis. Supports both limma for normalized data and DESeq2 for raw count data.

Usage

generateRef(dds, pheno, FDR = 0.05, dat, method = "limma")

Arguments

dds	Matrix. Raw count data from RNA-seq. Required if 'method = "DESeq2"'.
pheno	Character vector. Cell type class of the samples.
FDR	Numeric. Genes with BH adjusted p-value < FDR are considered significant. Default is 0.05.
dat	Matrix or data frame. Normalized transcript quantification data (e.g., FPKM, TPM).
method	Character. Method for differential expression: '"limma"' or '"DESeq2"'. Default is '"limma"'.

Value

List containing: - 'reference_matrix': Data frame of median expression for significant genes across cell types. - 'G': Optimal number of probes minimizing condition number. - 'condition_number': Minimum condition number. - 'whole_matrix': Full median expression matrix.

Examples

expressionData <- matrix(runif(1000 * 4, min = 0, max = 10), ncol = 4)
rownames(expressionData) <- paste("Gene", 1:1000, sep = "_")
colnames(expressionData) <- paste("Sample", 1:4, sep = "_")

phenotype <- c("celltype1", "celltype2", "celltype1", "celltype2")

rawCountData <- matrix(sample(1:100, 1000 * 4, replace = TRUE), ncol = 4)
rownames(rawCountData) <- paste("Gene", 1:1000, sep = "_")
colnames(rawCountData) <- paste("Sample", 1:4, sep = "_")


result <- generateRef(
  dds = rawCountData, pheno = phenotype,
  FDR = 0.05, dat = expressionData, method = "DESeq2"
)

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