deconvo_tme | R Documentation |
Deconvoluting Tumor microenvironment on a transcriptomic dataset
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",
...
)
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 |
'data.frame' with 'ID' as first column and other column with the calculated cell fractions for each sample.
Dongqiang Zeng
Rongfang Shen
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.
# 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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.