run_aucell {decoupleR} | R Documentation |
Calculates regulatory activities using Area Under the Curve (AUC) from AUCell
run_aucell( mat, network, .source = .data$source, .target = .data$target, aucMaxRank = ceiling(0.05 * nrow(rankings)), nproc = 4, seed = 42 )
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. |
aucMaxRank |
Threshold to calculate the AUC. |
nproc |
Number of cores to use for computation. |
seed |
A single value, interpreted as an integer, or NULL for random number generation. |
This function is a wrapper for the method AUCell
. It uses the
"Area Under the Curve" (AUC) to calculate whether a critical subset of input
molecular features is enriched for each sample.
Other decoupleR statistics:
decouple()
,
run_fgsea()
,
run_gsva()
,
run_mdt()
,
run_mlm()
,
run_ora()
,
run_udt()
,
run_ulm()
,
run_viper()
,
run_wmean()
,
run_wsum()
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_aucell(mat, network, .source='tf', nproc=1)