plot_gsva_heatmap-ReactomeAnalysisResult-method: plot_gsva_heatmap - ReactomeAnalysisResult function

In ReactomeGSA: Client for the Reactome Analysis Service for comparative multi-omics gene set analysis

Description

Plots pathway expression values / sample as a heatmap. Ranks pathways based on their expression difference.

Usage

## S4 method for signature 'ReactomeAnalysisResult'
plot_gsva_heatmap(
  object,
  pathway_ids = NULL,
  max_pathways = 20,
  truncate_names = TRUE,
  ...
)

Arguments

object	The ReactomeAnalysisResult object.
pathway_ids	A vector of pathway ids. If set, only these pathways are included in the plot.
max_pathways	The maximum number of pathways to include. Only takes effect if pathway_ids is not set.
truncate_names	If set, long pathway names are truncated.
...	Additional parameters passed to the heatmap.2 function.

Value

None

See Also

Other ReactomeAnalysisResult functions: get_result(), names,ReactomeAnalysisResult-method, open_reactome(), pathways(), plot_correlations(), plot_gsva_pathway(), plot_volcano(), reactome_links(), result_types()

Examples

# load the scRNA-seq example data
library(ReactomeGSA.data)
data(jerby_b_cells)

# perform the GSVA analysis
gsva_result <- analyse_sc_clusters(jerby_b_cells, verbose = FALSE)

# plot the heatmap
relevant_pathways <- c("R-HSA-983170", "R-HSA-388841", "R-HSA-2132295", "R-HSA-983705", "R-HSA-5690714")
plot_gsva_heatmap(gsva_result, 
                  pathway_ids = relevant_pathways, # limit to these pathways
                  margins = c(6,30), # adapt the figure margins in heatmap.2
                  dendrogram = "col", # only plot column dendrogram
                  scale = "row", # scale for each pathway
                  key = FALSE, # don't display the color key
                  lwid=c(0.1,4)) # remove the white space on the left

ReactomeGSA documentation built on April 17, 2021, 6:01 p.m.