iobr_deconvo_pipeline: Tumor Microenvironment (TME) Deconvolution Pipeline

In IOBR: Immune Oncology Biological Research

Tumor Microenvironment (TME) Deconvolution Pipeline

Description

Executes an integrated TME analysis on a gene expression matrix: performs immune/stromal cell deconvolution using multiple algorithms, computes signature scores, and aggregates results. Designed for exploratory immunogenomic profiling.

Usage

iobr_deconvo_pipeline(
  eset,
  project,
  array,
  tumor_type,
  path = NULL,
  permutation = 1000
)

Arguments

eset	Numeric matrix. Gene expression (TPM/log scale) with genes in rows.
project	Character. Project name (used in output naming).
array	Logical. Whether data originated from an array platform. Affects deconvolution choices.
tumor_type	Character. Tumor type code (e.g., "stad") used by certain methods.
path	Character. Output directory. Default is NULL (uses tempdir()).
permutation	Integer. Number of permutations for CIBERSORT (and similar). Default is 1000.

Value

Data frame integrating cell fractions and signature scores (also writes intermediate outputs to disk).

Author(s)

Dongqiang Zeng

Examples

## Not run: 
lm22 <- load_data("lm22")
cancer_genes <- load_data("cancer_type_genes")
if (!is.null(lm22) && !is.null(cancer_genes)) {
  set.seed(123)
  genes <- rownames(lm22)
  xcell <- load_data("xCell.data")
  if (!is.null(xcell)) genes <- unique(c(genes, xcell$genes))
  genes <- unique(c(genes, cancer_genes[["stad"]]))
  eset <- matrix(runif(length(genes) * 2), nrow = length(genes), ncol = 2)
  rownames(eset) <- genes
  colnames(eset) <- paste0("Sample", 1:2)
  res <- iobr_deconvo_pipeline(
    eset = eset, project = "TEST",
    array = FALSE, tumor_type = "stad",
    path = tempdir(), permutation = 2
  )
  if (!is.null(res)) head(res)
}

## End(Not run)

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