plotEnrichmentDetailed: Plot detailed output of the Feature Set Enrichment Analysis

In bioFAM/MOFA: Multi-Omics Factor Analysis (MOFA)

Description

Method to plot a detailed output of the Feature Set Enrichment Analyisis (FSEA).
Each row corresponds to a significant pathway, sorted by statistical significance, and each dot corresponds to a gene.
For each pathway, we display the top genes of the pathway sorted by the corresponding feature statistic (by default, the absolute value of the loading) The top genes with the highest statistic (max.genes argument) are displayed and labeled in black. The remaining genes are colored in grey.

Usage

plotEnrichmentDetailed(object, factor, feature.sets, fsea.results,
  adjust = TRUE, alpha = 0.1, max.genes = 5, max.pathways = 10,
  text_size = 3)

Arguments

object	MOFAmodel object on which FSEA was performed
factor	string with factor name or numeric with factor index
feature.sets	data structure that holds feature set membership information, as used in the runEnrichmentAnalysis function.
fsea.results	output of runEnrichmentAnalysis function
adjust	use adjusted p-values?
alpha	p.value threshold to filter out feature sets
max.genes	maximum number of genes to display, per pathway
max.pathways	maximum number of enriched pathways to display
text_size	size of the text to label the top genes

Value

a ggplot2 object

Examples

# Example on the CLL data
filepath <- system.file("extdata", "CLL_model.hdf5", package = "MOFAdata")
MOFAobject <- loadModel(filepath)

# perform Enrichment Analysis on mRNA data using pre-build Reactome gene sets
data("reactomeGS", package = "MOFAdata")
fsea.results <- runEnrichmentAnalysis(MOFAobject, view="mRNA", feature.sets=reactomeGS)

# Plot detailed output of the enrichment analysis results
plotEnrichmentDetailed(
object = MOFAobject, 
factor = 5,
feature.sets = reactomeGS,
fsea.results = fsea.results,

)

bioFAM/MOFA documentation built on Oct. 3, 2020, 12:53 a.m.