run_c3net: Wrapper for C3Net method

In dnapath: Differential Network Analysis using Gene Pathways

Wrapper for C3Net method

Description

Conducts co-expression analysis using C3Net \insertCitealtay10dnapath. Uses the implementation from the bc3net package \insertCitebc3netdnapath. Can be used for the network_inference argument in dnapath.

Usage

run_c3net(
  x,
  weights = NULL,
  estimator = "spearman",
  disc = "equalwidth",
  mtc = TRUE,
  adj = "bonferroni",
  alpha = 0.05,
  ...
)

Arguments

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 dnapath() to apply the probabilistic group labels to each observation when estimating the group-specific network.
estimator	Argument is passed into c3mtc.
disc	Argument is passed into c3mtc.
mtc	Argument is passed into c3mtc.
adj	Argument is passed into c3mtc.
alpha	Argument is passed into c3mtc.
...	Additional arguments are ignored.

Value

A p by p matrix of association scores.

References

\insertRef

altay10dnapath

\insertRef

bc3netdnapath

See Also

run_aracne, run_bc3net, run_clr, run_corr, run_dwlasso, run_genie3, run_glasso, run_mrnet, run_pcor, and run_silencer

Examples

data(meso)
data(p53_pathways)

# To create a short example, we subset on one pathway from the p53 pathway list,
# and will only run 1 permutation for significance testing.
pathway_list <- p53_pathways[13]
n_perm <- 1

# Use this method to perform differential network analysis.
# The parameters in run_c3net() 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_c3net,
                   estimator = "pearson",
                   mtc = FALSE)
summary(results)

# The group-specific association matrices can be extracted using get_networks().
nw_list <- get_networks(results) # Get networks for the pathway.


# 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[[1]])

dnapath documentation built on May 9, 2022, 9:05 a.m.