View source: R/decoupleRnival.R
moon | R Documentation |
Iteratively propagate downstream input activity through a signed directed network using the weighted mean enrichment score from decoupleR package
moon(
upstream_input = NULL,
downstream_input,
meta_network,
n_layers,
n_perm = 1000,
downstream_cutoff = 0,
statistic = "ulm",
return_levels = F
)
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" |
return_levels |
true or false, if true the layers that the protein belongs to will be returned alongside the scores |
A data frame containing the score of the nodes upstream of the downstream input based on the iterative propagation
# 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 <- moon(upstream_input, downstream_input, meta_network, n_layers = 2, statistic = "wmean")
# View the results
print(result)
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