deconvo_tme: Deconvoluting Tumor microenvironment on a transcriptomic...

In IOBR/IOBR: Immune Oncology Biological Research

Deconvoluting Tumor microenvironment on a transcriptomic dataset

Description

Deconvoluting Tumor microenvironment on a transcriptomic dataset

Usage

deconvo_tme(
  eset,
  project = NULL,
  method = tme_deconvolution_methods,
  arrays = FALSE,
  tumor = TRUE,
  perm = 1000,
  reference,
  scale_reference,
  plot = FALSE,
  scale_mrna,
  group_list = NULL,
  platform = "affymetrix",
  absolute.mode = FALSE,
  abs.method = "sig.score",
  ...
)

Arguments

eset	A gene expression matrix Either: A numeric matrix or data.frame with HGNC gene symbols as row names and sample identifiers as column names. In both cases.
project	project name used to distinguish different data sets, default is NULL
method	a string specifying the method. Supported methods are 'mcpcounter', 'epic', 'xcell', 'cibersort', 'cibersort_abs', 'ips', 'quantiseq', 'estimate','timer', 'svr','lsei'，'timer', 'quantiseq'.
arrays	Runs methods in a mode optimized for microarray data. Currently affects 'CIBERSORT', 'svr' and 'xCell'.
tumor	logical. use a signature matrix/procedure optimized for tumor samples, if supported by the method. Currently affects 'EPIC'
perm	set permutations for statistical analysis (≥100 permutations recommended). Currently affects 'CIBERSORT' and 'svr_ref'
reference	immune cell gene matrix; eg lm22, lm6 or can be generate using generateRef/generateRef_rnaseq
scale_reference	a logical value indicating whether the reference be scaled or not. If TRUE, the value in reference file will be centered and scaled in row direction. Currently affects 'svr' and 'lsei' method
plot	Currently affects 'IPS' method
scale_mrna	logical. If FALSE, disable correction for mRNA content of different cell types. This is supported by methods that compute an absolute score (EPIC and quanTIseq)
group_list	tumor type list of samples
platform	character string indicating platform type. Defaults to "affymetrix" Currently affects 'ESTIMATE' method
absolute.mode	Run CIBERSORT or svr in absolute mode (default = FALSE)
abs.method	if absolute is set to TRUE, choose method: 'no.sumto1' or 'sig.score'
...	arguments passed to the respective method

Value

'data.frame' with 'ID' as first column and other column with the calculated cell fractions for each sample.

Author(s)

Dongqiang Zeng

Rongfang Shen

References

1. Newman, A. M., Liu, C. L., Green, M. R., Gentles, A. J., Feng, W., Xu, Y., … Alizadeh, A. A. (2015). Robust enumeration of cell subsets from tissue expression profiles. Nature Methods, 12(5), 453–457. 2. Vegesna R, Kim H, Torres-Garcia W, …, Verhaak R. (2013). Inferring tumour purity and stromal and immune cell admixture from expression data. Nature Communications 4, 2612. 3. Finotello, F., Mayer, C., Plattner, C., Laschober, G., Rieder, D., Hackl, H., …, Sopper, S. (2019). Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data. Genome medicine, 11(1), 34. 4. Li, B., Severson, E., Pignon, J.-C., Zhao, H., Li, T., Novak, J., … Liu, X. S. (2016). Comprehensive analyses of tumor immunity: implications for cancer immunotherapy. Genome Biology, 17(1), 174. 5. P. Charoentong et al., Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade. Cell Reports 18, 248-262 (2017). 6. Becht, E., Giraldo, N. A., Lacroix, L., Buttard, B., Elarouci, N., Petitprez, F., … de Reyniès, A. (2016). Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression. Genome Biology, 17(1), 218. 7. Aran, D., Hu, Z., & Butte, A. J. (2017). xCell: digitally portraying the tissue cellular heterogeneity landscape. Genome Biology, 18(1), 220. 8. Racle, J., de Jonge, K., Baumgaertner, P., Speiser, D. E., & Gfeller, D. (2017). Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data. ELife, 6, e26476.

Examples

# Loading TCGA-STAD expression data(raw count matrix)
data(eset_stad, package = "IOBR")
eset <- count2tpm(countMat = eset_stad, source = "local", idType = "ensembl")
deconvo_tme(eset = eset, arrays = FALSE, method = "cibersort")
# Absolute mode
deconvo_tme(eset = eset, arrays = FALSE, method = "cibersort", absolute.mode = TRUE)

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