run_gsva {decoupleR} | R Documentation |
This function is a convenient wrapper for the GSVA::gsva()
function.
run_gsva(mat, network, .source = .data$tf, .target = .data$target, ...)
mat |
Matrix to evaluate (e.g. expression matrix).
Target nodes in rows and conditions in columns.
|
network |
Tibble or dataframe with edges and it's associated metadata. |
.source |
Column with source nodes. |
.target |
Column with target nodes. |
... |
Arguments passed on to |
A long format tibble of the enrichment scores for each tf across the samples. Resulting tibble contains the following columns:
statistic
: Indicates which method is associated with which score.
tf
: Source nodes of network
.
condition
: Condition representing each column of mat
.
score
: Regulatory activity (enrichment score).
Other decoupleR statistics:
decouple()
,
run_mean()
,
run_ora()
,
run_pscira()
,
run_scira()
,
run_viper()
inputs_dir <- system.file("testdata", "inputs", package = "decoupleR") mat <- readRDS(file.path(inputs_dir, "input-expr_matrix.rds")) network <- readRDS(file.path(inputs_dir, "input-dorothea_genesets.rds")) run_gsva(mat, network, tf, target, verbose = FALSE)