View source: R/ridgeEnrichment.R
ridgeEnrichment | R Documentation |
This function allows to the user to examine the distribution of enrichment across groups by generating a ridge plot.
ridgeEnrichment(
input.data,
assay = NULL,
group.by = NULL,
gene.set = NULL,
color.by = "group",
order.by = NULL,
scale = FALSE,
facet.by = NULL,
add.rug = FALSE,
palette = "inferno"
)
input.data |
Enrichment output from |
assay |
Name of the assay to plot if data is a single-cell object. |
group.by |
Categorical parameter to plot along the x.axis. If input is a single-cell object the default will be cluster. |
gene.set |
Gene set to plot (on y-axis). |
color.by |
How the color palette applies to the graph - can be "group" for a categorical color palette based on the group.by parameter or use the gene.set name if wanting to apply a gradient palette. |
order.by |
Method to organize the x-axis: "mean" will arrange the x-axis by the mean of the gene.set, while "group" will arrange the x-axis by in alphanumerical order. Using NULL will not reorder the x-axis. |
scale |
Visualize raw values FALSE or Z-transform enrichment values TRUE. |
facet.by |
Variable to facet the plot into n distinct graphs. |
add.rug |
Add visualization of the discrete cells along the ridge plot (TRUE). |
palette |
Colors to use in visualization - input any hcl.pals. |
ggplot2 object with ridge-based distributions of selected gene.set
GS <- list(Bcells = c("MS4A1", "CD79B", "CD79A", "IGH1", "IGH2"),
Tcells = c("CD3E", "CD3D", "CD3G", "CD7","CD8A"))
pbmc_small <- SeuratObject::pbmc_small
pbmc_small <- runEscape(pbmc_small,
gene.sets = GS,
min.size = NULL)
ridgeEnrichment(pbmc_small,
assay = "escape",
gene.set = "Tcells")
ridgeEnrichment(pbmc_small,
assay = "escape",
gene.set = "Tcells",
color.by = "Tcells")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.