run_bc3net {dnapath}

Wrapper for BC3Net method

Description

Conducts co-expression analysis using BC3Net (Matos Simoes and Emmert-Streib 2012). Uses the implementation from the bc3net package (de Matos Simoes and Emmert-Streib 2016). Can be used for the network_inference argument in dnapath.

Usage

run_bc3net(
  x,
  weights = NULL,
  boot = 100,
  estimator = "spearman",
  disc = "equalwidth",
  mtc1 = TRUE,
  adj1 = "bonferroni",
  alpha1 = 0.05,
  mtc2 = TRUE,
  adj2 = "bonferroni",
  alpha2 = 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.

boot

Argument is passed into bc3net.

estimator

Argument is passed into bc3net.

disc

Argument is passed into bc3net.

mtc1

Argument is passed into bc3net.

adj1

Argument is passed into bc3net.

alpha1

Argument is passed into bc3net.

mtc2

Argument is passed into bc3net.

adj2

Argument is passed into bc3net.

alpha2

Argument is passed into bc3net.

...

Additional arguments are ignored.

Value

A p by p matrix of association scores.

References

Matos Simoes Rd, Emmert-Streib F (2012). “Bagging Statistical Network Inference from Large-Scale Gene Expression Data.” PloS ONE, 7(3), e33624.

de Matos Simoes R, Emmert-Streib F (2016). bc3net: Gene Regulatory Network Inference with Bc3net. R package version 1.0.4, https://CRAN.R-project.org/package=bc3net.

See Also

run_aracne, run_c3net, 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_bc3net() can be adjusted using the ... argument.
# For example, the 'estimator' and 'boot' 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_bc3net,
                   boot = 10,
                   estimator = "pearson",
                   mtc1 = FALSE,
                   mtc2 = FALSE)
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[[1]])