decoupleRnival: DecoupleRnival

In saezlab/COSMOS: COSMOS (Causal Oriented Search of Multi-Omic Space)

DecoupleRnival

Description

Iteratively propagate downstream input activity through a signed directed network using the weighted mean enrichment score from decoupleR package

Usage

decoupleRnival(
  upstream_input = NULL,
  downstream_input,
  meta_network,
  n_layers,
  n_perm = 1000,
  downstream_cutoff = 0,
  statistic = "norm_wmean"
)

Arguments

upstream_input	A named vector with up_stream nodes and their corresponding activity.
downstream_input	A named vector with down_stream nodes and their corresponding activity.
meta_network	A network data frame containing signed directed prior knowledge of molecular interactions.
n_layers	The number of layers that will be propagated upstream.
n_perm	The number of permutations to use in decoupleR's algorithm.
downstream_cutoff	If downstream measurments should be included above a given threshold
statistic	the decoupleR stat to consider: "wmean", "norm_wmean", or "ulm"

Value

A data frame containing the score of the nodes upstream of the downstream input based on the iterative propagation

Examples

# Example input data
upstream_input <- c("A" = 1, "B" = -1, "C" = 0.5)
downstream_input <- c("D" = 2, "E" = -1.5)
meta_network <- data.frame(
  source = c("A", "A", "B", "C", "C", "D", "E"),
  target = c("B", "C", "D", "E", "D", "B", "A"),
  sign = c(1, -1, -1, 1, -1, -1, 1)
)

# Run the function with the example input data
result <- decoupleRnival(upstream_input, downstream_input, meta_network, n_layers = 2, n_perm = 100)

# View the results
print(result)

saezlab/COSMOS documentation built on July 24, 2024, 7:37 p.m.