ridgeEnrichment: Generate a ridge plot to examine enrichment distributions

In escape: Easy single cell analysis platform for enrichment

Description

This function allows to the user to examine the distribution of enrichment across groups by generating a ridge plot.

Usage

ridgeEnrichment(
  enriched,
  group = "cluster",
  gene.set = NULL,
  scale.bracket = NULL,
  facet = NULL,
  add.rug = FALSE,
  colors = c("#0348A6", "#7AC5FF", "#C6FDEC", "#FFB433", "#FF4B20")
)

Arguments

enriched	The output of enrichIt
group	The parameter to group, displayed on the y-axis.
gene.set	The gene set to graph on the x-axis.
scale.bracket	This will filter the enrichment scores to remove extreme outliers. Values entered (1 or 2 numbers) will be the filtering parameter using z-scores of the selected gene.set. If only 1 value is given, a seocndary bracket is autommatically selected as the inverse of the number.
facet	A parameter to separate the graph.
add.rug	Binary classifier to add a rug plot to the x-axis.
colors	The color palette for the ridge plot.

Value

ggplot2 object with ridge-based distributions of selected gene.set

See Also

enrichIt for generating enrichment scores.

Examples

ES2 <- readRDS(url(
"https://ncborcherding.github.io/vignettes/escape_enrichment_results.rds"))
ridgeEnrichment(ES2, gene.set = "HALLMARK_DNA_REPAIR", group = "cluster", 
facet = "Type", add.rug = TRUE)

escape documentation built on Nov. 8, 2020, 8:21 p.m.