Description Usage Arguments Value Examples
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.
1 2 3 4 5 6 7 8 | plot_gene_group(
gnet_result,
group_idx,
tree_layout = 1,
max_gene_num = 100,
plot_leaf_labels = TRUE,
group_labels = NULL
)
|
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 |
None
1 2 3 4 5 6 7 8 9 10 | 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)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.