run_aucell {decoupleR}R Documentation

AUCell

Description

Calculates regulatory activities using Area Under the Curve (AUC) from AUCell

Usage

run_aucell(
  mat,
  network,
  .source = .data$source,
  .target = .data$target,
  aucMaxRank = ceiling(0.05 * nrow(rankings)),
  nproc = 4,
  seed = 42
)

Arguments

mat

Matrix to evaluate (e.g. expression matrix). Target nodes in rows and conditions in columns. rownames(mat) must have at least one intersection with the elements in network .target column.

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.

Details

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.

See Also

Other decoupleR statistics: decouple(), run_fgsea(), run_gsva(), run_mdt(), run_mlm(), run_ora(), run_udt(), run_ulm(), run_viper(), run_wmean(), run_wsum()

Examples

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)

[Package decoupleR version 1.99.5 Index]