Conducts co-expression analysis using MRNET \insertCitemeyer07dnapath.
Uses the implementation from the
minet package \insertCitemeyer08dnapath.
Can be used for the
network_inference argument in
run_mrnet(x, estimator = "spearman", weights = NULL, ...)
A n by p matrix of gene expression data (n samples and p genes).
Argument is passed into
An optional vector of weights. This is used by
Additional arguments are ignored.
A p by p matrix of association scores.
data(meso) data(p53_pathways) # To create a short example, we subset on two pathways from the p53 pathway list, # and will only run 3 permutations for significance testing. pathway_list <- p53_pathways[c(8, 13)] n_perm <- 3 # Use this method to perform differential network analysis. # The parameters in run_mrnet() can be adjusted using the ... argument. # For example, the 'estimator' parameter can be specified as shown here. results <- dnapath(x = meso$gene_expression, pathway_list = pathway_list, group_labels = meso$groups, n_perm = n_perm, network_inference = run_mrnet, estimator = "spearman") summary(results) # The group-specific association matrices can be extracted using get_networks(). nw_list <- get_networks(results[]) # Get networks for pathway 1. # nw_list has length 2 and contains the inferred networks for the two groups. # The gene names are the Entrezgene IDs from the original expression dataset. # Renaming the genes in the dnapath results to rename those in the networks. # NOTE: The temporary directory, tempdir(), is used in this example. In practice, # this argument can be removed or changed to an existing directory results <- rename_genes(results, to = "symbol", species = "human", dir_save = tempdir()) nw_list <- get_networks(results[]) # The genes (columns) will have new names. # (Optional) Plot the network using SeqNet package (based on igraph plotting). # First rename entrezgene IDs into gene symbols. SeqNet::plot_network(nw_list[])
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