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GSEA Plot

Source: R/GSEAPlot.R
GSEAPlot.Rd

Generates various types of plots for Gene Set Enrichment Analysis (GSEA) results.

Usage

GSEAPlot(
  srt,
  db = "GO_BP",
  group.by = NULL,
  test.use = "wilcox",
  res = NULL,
  plot_type = c("line", "bar", "network", "enrichmap", "wordcloud", "comparison"),
  group_use = NULL,
  id_use = NULL,
  pvalueCutoff = NULL,
  padjustCutoff = 0.05,
  topTerm = ifelse(plot_type == "enrichmap", 100, 6),
  direction = c("pos", "neg", "both"),
  compare_only_sig = FALSE,
  topWord = 100,
  word_type = c("term", "feature"),
  word_size = c(2, 8),
  words_excluded = NULL,
  line_width = 1.5,
  line_alpha = 1,
  line_color = "#6BB82D",
  n_coregene = 10,
  sample_coregene = FALSE,
  features_label = NULL,
  label.fg = "black",
  label.bg = "white",
  label.bg.r = 0.1,
  label.size = 4,
  network_layout = "fr",
  network_labelsize = 5,
  network_blendmode = "blend",
  network_layoutadjust = TRUE,
  network_adjscale = 60,
  network_adjiter = 100,
  enrichmap_layout = "fr",
  enrichmap_cluster = "fast_greedy",
  enrichmap_label = c("term", "feature"),
  enrichmap_labelsize = 5,
  enrlichmap_nlabel = 4,
  enrichmap_show_keyword = FALSE,
  enrichmap_mark = c("ellipse", "hull"),
  enrichmap_expand = c(0.5, 0.5),
  character_width = 50,
  lineheight = 0.7,
  palette = "Spectral",
  palcolor = NULL,
  aspect.ratio = NULL,
  legend.position = "right",
  legend.direction = "vertical",
  theme_use = "theme_scop",
  theme_args = list(),
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  seed = 11,
  verbose = TRUE
)

Arguments

srt

A Seurat object containing the results of RunDEtest and RunGSEA. If specified, GSEA results will be extracted from the Seurat object automatically. If not specified, the res arguments must be provided.

db

The database to use for enrichment plot.

group.by

Grouping variable in the Seurat object. This argument is only used if srt is specified.

test.use

Test to be used in differential expression analysis. This argument is only used if srt is specified.

res

Enrichment results generated by RunGSEA function. If provided, 'srt', 'test.use' and 'group.by' are ignored.

plot_type

The type of plot to generate. Options are: "line", "comparison", "bar", "network", "enrichmap", "wordcloud".

group_use

The group(s) to be used for enrichment plot.

id_use

List of IDs to be used to display specific terms in the enrichment plot. Default value is NULL.

pvalueCutoff

The p-value cutoff. Only work when padjustCutoff is NULL.

padjustCutoff

The p-adjusted cutoff.

topTerm

The number of top terms to display. Default is 6, or 100 if plot_type is "enrichmap".

direction

The direction of enrichment to include in the plot. Must be one of "pos", "neg", or "both".

compare_only_sig

Whether to compare only significant terms.

topWord

The number of top words to display for wordcloud.

word_type

The type of words to display in wordcloud. Options are "term" and "feature".

word_size

The size range for words in wordcloud.

words_excluded

Words to be excluded from the wordcloud. Default is NULL, which means that the built-in words (words_excluded) will be used.

line_width

The linewidth for the line plot.

line_alpha

The alpha value for the line plot.

line_color

The color for the line plot.

n_coregene

The number of core genes to label in the line plot.

sample_coregene

Whether to randomly sample core genes for labeling in the line plot.

features_label

Feature names to include as labels in the line plot.

label.fg

The color of the labels.

label.bg

The background color of the labels.

label.bg.r

The radius of the rounding of the label's background.

label.size

The size of the labels.

network_layout

The layout algorithm to use for network plot. Options are "fr", "kk", "random", "circle", "tree", "grid", or other algorithm from igraph package.

network_labelsize

The label size for network plot.

network_blendmode

The blend mode for network plot.

network_layoutadjust

Whether to adjust the layout of the network plot to avoid overlapping words.

network_adjscale

The scale for adjusting network plot layout.

network_adjiter

The number of iterations for adjusting network plot layout.

enrichmap_layout

The layout algorithm to use for enrichmap plot. Options are "fr", "kk", "random", "circle", "tree", "grid", or other algorithm from igraph package.

enrichmap_cluster

The clustering algorithm to use for enrichmap plot. Options are "walktrap", "fast_greedy", or other algorithm from igraph package.

enrichmap_label

The label type for enrichmap plot. Options are "term" and "feature".

enrichmap_labelsize

The label size for enrichmap plot.

enrlichmap_nlabel

The number of labels to display for each cluster in enrichmap plot.

enrichmap_show_keyword

Whether to show the keyword of terms or features in enrichmap plot.

enrichmap_mark

The mark shape for enrichmap plot. Options are "ellipse" and "hull".

enrichmap_expand

The expansion factor for enrichmap plot.

character_width

The maximum width of character of descriptions.

lineheight

The line height for y-axis labels.

palette

Color palette name. Available palettes can be found in thisplot::show_palettes.

palcolor

Custom colors used to create a color palette.

aspect.ratio

Panel aspect ratio.

legend.position

Legend placement ("none", "left", "right", "bottom", "top"), direction, and title. legend.title = NULL uses the group name.

legend.direction

Legend direction: "horizontal" or "vertical".

theme_use, theme_args

Theme name or function, plus extra theme arguments.

combine, nrow, ncol, byrow

Combine plots with patchwork. combine = FALSE returns a list of ggplots.

seed

Random seed.

verbose

Whether to print messages.

See also

RunGSEA

Examples

term2gene <- data.frame(
  Term = c(rep("Endocrine markers", 5), rep("Ductal markers", 5)),
  symbol = c("INS", "GCG", "SST", "IAPP", "PCSK1", "KRT19", "SOX9", "MUC1", "CFTR", "KRT7")
)
genes <- unique(term2gene$symbol)
scores <- seq_along(genes)
names(scores) <- genes
gsea_out <- RunGSEA(
  geneID = genes,
  geneScore = scores,
  geneID_groups = rep("Cluster1", length(genes)),
  TERM2GENE = term2gene,
  minGSSize = 2
)
#> ℹ [2026-08-30 04:31:12] Start GSEA analysis
#> ! [2026-08-30 04:31:12] All values in the `geneScore` are greater than zero. Set scoreType = 'pos'
#> Warning: All values in the `geneScore` are greater than zero. Set scoreType = 'pos'
#> ℹ [2026-08-30 04:31:12] Preparing custom GSEA database from `TERM2GENE`/`TERM2NAME` ...
#> ℹ [2026-08-30 04:31:12] Prepared 10 ranked gene rows after ID mapping.
#> ℹ [2026-08-30 04:31:12] Running GSEA for 1 group/database combination(s) using 1 core(s) ...
#> ℹ [2026-08-30 04:31:12] Using 1 core
#> ℹ [2026-08-30 04:31:12] Running GSEA: group "Cluster1", database "custom", genes 10 ...
#> Registered S3 method overwritten by 'ggtree':
#>   method         from     
#>   fortify.igraph ggnetwork
#> ℹ [2026-08-30 04:31:13] Finished GSEA: group "Cluster1", database "custom".
#> ℹ [2026-08-30 04:31:12] Building results
#> ✔ [2026-08-30 04:31:13] GSEA analysis done
GSEAPlot(res = gsea_out, db = "custom", plot_type = "comparison")
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's alpha values.

GSEAPlot(res = gsea_out, db = "custom", plot_type = "bar")
#> Warning: `guide_colourbar()` cannot be used for alpha.
#> ℹ Use one of colour, color, or fill instead.