Tumor Microenvironment (TME) Deconvolution Pipeline

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

Dongqiang Zeng

Examples

if (FALSE) { # \dontrun{
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)
}
} # }