View source: R/grn_inference.R
get_hubs_grn | R Documentation |
Get hubs for gene regulatory network
Get hubs for protein-protein interaction network
get_hubs_grn(
edgelist,
top_percentile = 0.1,
top_n = NULL,
return_degree = FALSE,
ranked = TRUE
)
get_hubs_ppi(
edgelist,
top_percentile = 0.1,
top_n = NULL,
return_degree = FALSE
)
edgelist |
A protein-protein interaction network represented as an edge list. |
top_percentile |
Numeric from 0 to 1 indicating the percentage of proteins with the highest degree to consider hubs. Default: 0.1. |
top_n |
Numeric indicating the number of proteins with the highest degree to consider hubs. |
return_degree |
Logical indicating whether to return a data frame of degree for all proteins. If TRUE, the function will return a list instead of a data frame. Default: FALSE. |
ranked |
Logical indicating whether to treat third column of the edge list (edge weights) as ranked values. Ignored if the edge list only contains 2 columns. Default: TRUE. |
A data frame with gene ID in the first column and out degree in the second column or a list of two data frames with hubs and degree for all genes, respectively.
A data frame with protein ID in the first column and degree in the second column or a list of two data frames with hubs and degree for all genes, respectively.
data(filt.se)
tfs <- sample(rownames(filt.se), size=50, replace=FALSE)
grn_list <- grn_combined(filt.se, regulators=tfs, nTrees=2)
ranked_grn <- grn_average_rank(grn_list)
# split in only 2 groups for demonstration purposes
filtered_edges <- grn_filter(ranked_grn, nsplit=2)
hubs <- get_hubs_grn(filtered_edges)
ppi_edges <- igraph::sample_pa(n = 500)
ppi_edges <- igraph::as_edgelist(ppi_edges)
hubs <- get_hubs_ppi(ppi_edges, return_degree = TRUE)
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