module_networks | R Documentation |
Given a distance matrix, calculate gene modules based on hierarchical clustering method and then get module level networks
module_networks( data, k = 10, quantile_cutoff = 10, centrality_degree_mod = "out", components_mod = "weak", network_min_genes = 10 )
data |
distance matrix |
k |
number of gene clusters for module inference |
quantile_cutoff |
distance cutoff based on quantile(1-99) for edge identification |
centrality_degree_mod |
"in" or "out" for nodes popularity calculation |
components_mod |
"weak" or "strong" for sub-network components inference |
network_min_genes |
minial number of genes required for a network |
a list networks for each module
example_data <- pGRNDB expression_matrix <- example_data[["expression"]] pseudotime_list <- example_data[["ptime"]]$PseudoTime dtw_dist_matrix <- get_dtw_dist_mat(expression_matrix, pseudotime_list, cores=1) nets <- module_networks(dtw_dist_matrix,k=1,quantile_cutoff=50) plot_network(nets[["module1"]])
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