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Run ESTIMATE tumor microenvironment scoring

Source: R/RunESTIMATE.R
RunESTIMATE.Rd

Compute ESTIMATE stromal, immune, combined ESTIMATE, and tumor-purity scores from bulk or pseudo-bulk expression data. The implementation uses the original stromal and immune ESTIMATE signatures with an in-package scoring routine, so it does not require the external estimate package.

Usage

RunESTIMATE(
  object = NULL,
  count_matrix = NULL,
  assay = NULL,
  layer = "data",
  bulk_assay = "counts",
  sample.by = NULL,
  group.by = NULL,
  aggregate_fun = c("mean", "sum"),
  platform = c("rnaseq", "affymetrix", "agilent", "illumina"),
  filter_common_genes = TRUE,
  min_sig_genes = 10,
  purity = TRUE,
  verbose = TRUE
)

Arguments

object

Optional expression matrix, SummarizedExperiment, or Seurat object.

count_matrix

Optional expression matrix with genes in rows and samples in columns. Used when object is not provided as a matrix.

assay

Assay used for Seurat input.

layer

Assay layer used for Seurat input.

bulk_assay

Assay name used for SummarizedExperiment input.

sample.by

Metadata column used to aggregate Seurat cells into pseudo-bulk samples.

group.by

Optional metadata column used for grouping pseudo-bulk samples. If sample.by is not supplied, group.by is used as the aggregation variable.

aggregate_fun

Pseudo-bulk aggregation function for Seurat input.

platform

Platform label stored in the result metadata.

filter_common_genes

Whether to restrict the expression matrix to the ESTIMATE common-gene universe before scoring.

min_sig_genes

Minimum number of observed stromal and immune signature genes required after filtering.

purity

Whether to calculate ESTIMATE tumor purity. The purity formula was calibrated in the original ESTIMATE work primarily for Affymetrix data; for RNA-seq it is best interpreted cautiously.

verbose

Whether to print progress messages.

Value

A result bundle for matrix input, the modified SummarizedExperiment for SummarizedExperiment input, or the modified Seurat object for Seurat input.

References

Yoshihara et al. (2013) doi:10.1038/ncomms3612. Barbie et al. (2009) doi:10.1038/nature08460.