consensusTMEAnalysis: Run ConsensusTME Cell Type Estimation 'consensusTMEAnalysis'...

In cansysbio/ConsensusTME: A Consensus Approach To Tumour Microenvironment Cell Estimation

Run ConsensusTME Cell Type Estimation consensusTMEAnalysis takes bulk tumour gene expression data and returns cell type specific enrichment scores for each sample

Description

Run ConsensusTME Cell Type Estimation consensusTMEAnalysis takes bulk tumour gene expression data and returns cell type specific enrichment scores for each sample

Usage

consensusTMEAnalysis(bulkExp, cancerType, statMethod = c("ssgsea",
  "gsva", "plage", "zscore", "singScore"), singScoreDisp = FALSE,
  immuneScore = TRUE, excludeCells = NULL, parallel.sz = 0,
  parallel.type = "SOCK")

Arguments

bulkExp	bulk tumour gene expression matrix. HUGO gene symbols as row names & sample IDs as column names.
cancerType	string passed to indicate which TCGA cancer type samples are most similar to. N.B samples of different cancer types should be run seperately. Available cancer types: "ACC", "BLCA", "BRCA", "CESC", "CHOL", "COAD", "DLBC", "ESCA", "GBM", "HNSC", "KICH", "KIRC", "KIRP","LGG", "LIHC", "LUAD", "LUSC", "MESO", "OV", "PAAD", "PCPG", "PRAD", "READ", "SARC", "SKCM", "STAD", "TGCT", "THCA", "THYM", "UCEC", "UCS", "UVM".
statMethod	statistical framework to be used in generating gene set enrichment scores. These mirror the parameter options of GSVA::gsva() with the exception of singScore. which leverages singscore::multiScore(). Default: ssgsea
singScoreDisp	logical, when using singscore method should the dispersion for each gene set be returned with the enrichment scores. Default: FALSE
immuneScore	logical, when TRUE (default) an Immune Score is produced representing overall level of immune infiltration for each sample.
excludeCells	a character vector that defines cell types to not generate enrichment scores for.
parallel.sz	parameter passed to GSVA::gsva() - Number of processors to use when doing the calculations in parallel. This requires to previously load either the parallel or the snow library. If parallel is loaded and this argument is left with its default value (parallel.sz = 0) then it will use all available core processors unless this is set with a smaller number. If snow is loaded then this must be set to a positive integer number that specifies the number of processors to employ in the parallel calculation.
parallel.type	parameter passed to GSVA::gsva() - Type of cluster architecture when using snow. "SOCK" - works on any system (including Windows). "FORK" - faster but should be only used for POSIX systems (Mac, Linux, Unix, BSD).

Value

returns estimation of cell type abundance for each sample in the bulk tumour gene expression matrix

cansysbio/ConsensusTME documentation built on June 10, 2024, 5:36 p.m.