CIBERSORT is freely available to academic users. License and binary can be obtained from https://cibersortx.stanford.edu.
Usage
deconvo_cibersort(
eset,
project = NULL,
arrays = FALSE,
perm = 1000,
absolute = FALSE,
abs_method = "sig.score",
parallel = FALSE,
num_cores = 2,
seed = NULL
)Arguments
- eset
Expression matrix with gene symbols as row names.
- project
Optional project name. Default is `NULL`.
- arrays
Logical: optimized for microarray data. Default is `FALSE`.
- perm
Permutations for statistical analysis. Default is 1000.
- absolute
Logical: run in absolute mode. Default is `FALSE`.
- abs_method
Method for absolute mode: `"sig.score"` or `"no.sumto1"`. Default is `"sig.score"`.
- parallel
Enable parallel execution. Default is `FALSE`.
- num_cores
Number of cores for parallel mode. Default is 2.
- seed
Random seed for reproducibility. Default is `NULL`.
Examples
if (FALSE) { # \dontrun{
lm22 <- load_data("lm22")
if (!is.null(lm22)) {
set.seed(123)
sim_eset <- matrix(rnorm(nrow(lm22) * 2), nrow(lm22), 2)
rownames(sim_eset) <- rownames(lm22)
colnames(sim_eset) <- paste0("Sample", 1:2)
result <- deconvo_cibersort(eset = sim_eset, project = "TCGA-STAD", perm = 10)
if (!is.null(result)) head(result)
}
} # }