calculate_sig_score_integration: Calculating signature score using Integration method

In IOBR/IOBR: Immune Oncology Biological Research

Calculating signature score using Integration method

Description

Calculating signature score using Integration method

Usage

calculate_sig_score_integration(
  pdata = NULL,
  eset,
  signature,
  mini_gene_count = 2,
  column_of_sample = "ID",
  adjust_eset = FALSE,
  parallel.size = 1L
)

Arguments

pdata	phenotype data of input sample; if phenotype data is NULL, create a data frame with 'Index' and 'ID' contain column names of eset
eset	normalizaed transcriptomic data: normalized (CPM, TPM, RPKM, FPKM, etc.)
signature	List of gene signatures
mini_gene_count	filter out signatures with genes less than minimal gene in expression set; default is 5; the minimal gene count for ssGSEA methods should larger than 5 for the robustness of the calculation
column_of_sample	Defines in which column of pdata the sample identifier can be found.
adjust_eset	default is FALSE, if true, data with Inf or zero sd will be replaced
parallel.size	default is 1

Value

data frame with pdata and signature scores for gene sets; signatures in columns, samples in rows

Author(s)

Dongqiang Zeng

Examples

# Loading TCGA-STAD expresion data(raw count matrix)
data("eset_stad", package = "IOBR")
# transform count data to tpm
eset <- count2tpm(eset_stad, idType = "ensembl")
# signature score estimation using PCA, z-score, and ssgsea method
calculate_sig_score_integration(eset = eset, signature = signature_tme)

IOBR/IOBR documentation built on April 4, 2024, 1:07 a.m.