run_gsva {decoupleR}R Documentation

GSVA wrapper

Description

This function is a convenient wrapper for the GSVA::gsva() function.

Usage

run_gsva(mat, network, .source = .data$tf, .target = .data$target, ...)

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.

...

Arguments passed on to GSVA::gsva

Value

A long format tibble of the enrichment scores for each tf across the samples. Resulting tibble contains the following columns:

  1. statistic: Indicates which method is associated with which score.

  2. tf: Source nodes of network.

  3. condition: Condition representing each column of mat.

  4. score: Regulatory activity (enrichment score).

See Also

Other decoupleR statistics: decouple(), run_mean(), run_ora(), run_pscira(), run_scira(), run_viper()

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_gsva(mat, network, tf, target, verbose = FALSE)

[Package decoupleR version 1.0.0 Index]