generateRef_DEseq2: Generate Reference Signature Matrix Using DESeq2

In IOBR: Immune Oncology Biological Research

Generate Reference Signature Matrix Using DESeq2

Description

Uses DESeq2 to perform differential expression analysis across cell types, identifies significantly expressed genes, and creates a reference signature matrix from median expression levels.

Usage

generateRef_DEseq2(dds, pheno, FDR = 0.05, dat)

Arguments

dds	Matrix. Raw count data from RNA-seq.
pheno	Character vector. Cell type classes for samples.
FDR	Numeric. Threshold for adjusted p-values. Default is 0.05.
dat	Matrix. Normalized expression data (e.g., FPKM, TPM) for calculating median expression.

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

set.seed(123)
dds <- matrix(sample(0:1000, 2000, replace = TRUE), nrow = 100, ncol = 20)
colnames(dds) <- paste("Sample", 1:20, sep = "_")
rownames(dds) <- paste("Gene", 1:100, sep = "_")
pheno <- rep(c("Type1", "Type2"), each = 10)
dat <- matrix(runif(2000), nrow = 100, ncol = 20)
rownames(dat) <- rownames(dds)
colnames(dat) <- colnames(dds)

result <- generateRef_DEseq2(dds = dds, pheno = pheno, FDR = 0.05, dat = dat)
print(result$reference_matrix)

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