plot.dnapath {dnapath}

Plot function for 'dnapath' object.

Description

Uses the plotting functions for networks from the SeqNet package (Grimes and Datta 2019)

Usage

## S3 method for class 'dnapath'
plot(
  x,
  alpha = NULL,
  monotonized = FALSE,
  only_dc = FALSE,
  require_dc_genes = FALSE,
  scale_edges = 1,
  scale_nodes = 1,
  ...
)

Arguments

x

A 'dnapath' object from dnapath.

alpha

Threshold for p-values to infer differentially connected edges. If NULL (the default) then no edges are removed from the plot.

monotonized

If TRUE, monotonized (i.e. step-down) p-values from the permutation test will be used.

only_dc

If TRUE, only differentially connected edges will be shown; any edges that are present in both groups are hidden. If FALSE, the edges shared by both groups are shown. If a non-sparse estimator for network edges is used, then the graph may be dense and setting this argument to TRUE will be useful for highlighting the DC edges.

require_dc_genes

If TRUE, the gene-level differential connectivity p-value of the two genes for a given edge are also considered when deciding whether an edge is differentially connected. If neither gene is significantly differentially connected, then the edge between them will not be either.

scale_edges

(Optional) multiplier for edge widths.

scale_nodes

(Optional) multiplier for node radius

...

Additional arguments are passed into the plotting function plot_network.

Value

Plots the differential network and returns the graph object. See plot_network for details.

References

Grimes T, Datta S (2019). SeqNet: Generate RNA-Seq Data from Gene-Gene Association Networks. R package version 1.1.0, https://CRAN.R-project.org/package=SeqNet.

Examples

data(meso)
data(p53_pathways)
set.seed(0)
results <- dnapath(x = meso$gene_expression, pathway_list = p53_pathways,
                   group_labels = meso$groups, n_perm = 10)
# Plot of the differential network for pathway 1.
plot(results[[1]]) 
# Plot of the differential network for pathway 1; remove any edges from
# the plot that have p-values above 0.1.
plot(results[[1]], alpha = 0.1)