run_pcor | R Documentation |
Conducts co-expression analysis using full partial correlations; these are
computed using the shrinkage approach for covariance estimation
\insertCiteschafer05dnapath from the
corpcor
package \insertCitecorpcordnapath.
Can be used for the network_inference
argument in dnapath
.
run_pcor(x, weights = NULL, ranks = FALSE, verbose = FALSE, ...)
x |
A n by p matrix of gene expression data (n samples and p genes). |
weights |
An optional vector of weights. This is used by |
ranks |
If TRUE, the gene expression values will be converted to ranks (across samples) prior to covariance estimation. |
verbose |
Argument is passed into |
... |
Additional arguments are ignored. |
A p by p matrix of association scores.
schafer05dnapath
\insertRefcorpcordnapath
run_aracne
,
run_bc3net
, run_c3net
,
run_clr
, run_corr
,
run_dwlasso
, run_genie3
,
run_glasso
, run_mrnet
, and run_silencer
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. results <- dnapath(x = meso$gene_expression, pathway_list = pathway_list, group_labels = meso$groups, n_perm = n_perm, network_inference = run_pcor) summary(results) # The group-specific association matrices can be extracted using get_networks(). nw_list <- get_networks(results[[1]]) # 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[[1]]) # 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[[1]])
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