plot_gene_group: Plot a module

In chrischen1/GNET2: Constructing gene regulatory networks from expression data through functional module inference

Plot a module

Description

Plot the regulators module and heatmap of the expression inferred downstream genes for each sample. It can be interpreted as two parts: the bars at the top shows how samples are splited by the regression tree and the heatmap at the bottom shows how downstream genes are regulated by each subgroup determined by the regulators.

Usage

plot_gene_group(
  gnet_result,
  group_idx,
  tree_layout = 1,
  max_gene_num = 100,
  plot_leaf_labels = TRUE,
  group_labels = NULL
)

Arguments

gnet_result	Results returned by gnet().
group_idx	Index of the module.
tree_layout	zoom ratio for the regulatory tree. Default is 1. Need to be increased for trees with >5 regulators.
max_gene_num	Max size of gene to plot in the heatmap. Only genes with highest n variances will be kept.
plot_leaf_labels	If the plot includes a color bar of leaf labels at the bottom.
group_labels	Labels of experiment conditions,Used for the color bar of experiment conditions. Default is NULL

Value

None

Examples

set.seed(1)
init_group_num = 5
init_method = 'boosting'
exp_data <- matrix(rnorm(50*10),50,10)
reg_names <- paste0('TF',1:5)
rownames(exp_data) <- c(reg_names,paste0('gene',1:(nrow(exp_data)-length(reg_names))))
colnames(exp_data) <- paste0('condition_',1:ncol(exp_data))
se <- SummarizedExperiment::SummarizedExperiment(assays=list(counts=exp_data))
gnet_result <- gnet(se,reg_names,init_method,init_group_num)
plot_gene_group(gnet_result,group_idx=1)

chrischen1/GNET2 documentation built on June 29, 2022, 8:53 a.m.