GSEAPlot | R Documentation |
This function generates various types of plots for Gene Set Enrichment Analysis (GSEA) results.
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 = 0.5,
palette = "Spectral",
palcolor = NULL,
aspect.ratio = NULL,
legend.position = "right",
legend.direction = "vertical",
theme_use = "theme_scp",
theme_args = list(),
combine = TRUE,
nrow = NULL,
ncol = NULL,
byrow = TRUE,
seed = 11
)
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 |
db |
The database to use for enrichment plot. Default is "GO_BP". |
group_by |
A character vector specifying the grouping variable in the Seurat object. This argument is only used if |
test.use |
A character vector specifying the test to be used in differential expression analysis. This argument is only used if |
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". Default is "line". |
group_use |
The group(s) to be used for enrichment plot. Default is NULL. |
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. Default is NULL. Only work when |
padjustCutoff |
The p-adjusted cutoff. Default is 0.05. |
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". The default value is "both". |
compare_only_sig |
Whether to compare only significant terms. Default is FALSE. |
topWord |
The number of top words to display for wordcloud. Default is 100. |
word_type |
The type of words to display in wordcloud. Options are "term" and "feature". Default is "term". |
word_size |
The size range for words in wordcloud. Default is c(2, 8). |
words_excluded |
Words to be excluded from the wordcloud. The default value is NULL, which means that the built-in words (SCP::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 |
A character vector of 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. Default is "fr". |
network_labelsize |
The label size for network plot. Default is 5. |
network_blendmode |
The blend mode for network plot. Default is "blend". |
network_layoutadjust |
Whether to adjust the layout of the network plot to avoid overlapping words. Default is TRUE. |
network_adjscale |
The scale for adjusting network plot layout. Default is 60. |
network_adjiter |
The number of iterations for adjusting network plot layout. Default is 100. |
enrichmap_layout |
The layout algorithm to use for enrichmap plot. Options are "fr", "kk","random", "circle", "tree", "grid", or other algorithm from 'igraph' package. Default is "fr". |
enrichmap_cluster |
The clustering algorithm to use for enrichmap plot. Options are "walktrap", "fast_greedy", or other algorithm from 'igraph' package. Default is "fast_greedy". |
enrichmap_label |
The label type for enrichmap plot. Options are "term" and "feature". Default is "term". |
enrichmap_labelsize |
The label size for enrichmap plot. Default is 5. |
enrlichmap_nlabel |
The number of labels to display for each cluster in enrichmap plot. Default is 4. |
enrichmap_show_keyword |
Whether to show the keyword of terms or features in enrichmap plot. Default is FALSE. |
enrichmap_mark |
The mark shape for enrichmap plot. Options are "ellipse" and "hull". Default is "ellipse". |
enrichmap_expand |
The expansion factor for enrichmap plot. Default is c(0.5, 0.5). |
character_width |
The maximum width of character of descriptions. Default is 50. |
lineheight |
The line height for y-axis labels. Default is 0.5. |
palette |
The color palette to use. Default is "Spectral". |
palcolor |
Custom colors for palette. Default is NULL. |
aspect.ratio |
The aspect ratio of the plot. Default is 1. |
legend.position |
The position of the legend. Default is "right". |
legend.direction |
The direction of the legend. Default is "vertical". |
theme_use |
The theme to use for the plot. Default is "theme_scp". |
theme_args |
The arguments to pass to the theme. Default is an empty list. |
combine |
Whether to combine multiple plots into a single plot. Default is TRUE. |
nrow |
The number of rows in the combined plot. Default is NULL, calculated based on the number of plots. |
ncol |
The number of columns in the combined plot. Default is NULL, calculated based on the number of plots. |
byrow |
Whether to fill the combined plot by row. Default is TRUE. |
seed |
The random seed to use. Default is 11. |
RunGSEA
data("pancreas_sub")
pancreas_sub <- RunDEtest(pancreas_sub, group_by = "CellType", only.pos = FALSE, fc.threshold = 1)
pancreas_sub <- RunGSEA(pancreas_sub, group_by = "CellType", db = "GO_BP", species = "Mus_musculus")
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", group_use = "Ductal")
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", group_use = "Ductal", id_use = "GO:0006412")
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", group_use = "Endocrine", id_use = c("GO:0046903", "GO:0015031", "GO:0007600")) %>%
panel_fix_overall(height = 6) # As the plot is created by combining, we can adjust the overall height and width directly.
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", topTerm = 3, plot_type = "comparison")
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", topTerm = 3, plot_type = "comparison", direction = "neg")
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", topTerm = 3, plot_type = "comparison", direction = "both")
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", topTerm = 3, plot_type = "comparison", compare_only_sig = TRUE)
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", plot_type = "bar")
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", plot_type = "bar", direction = "both")
GSEAPlot(pancreas_sub,
db = "GO_BP", group_by = "CellType", group_use = "Ductal",
plot_type = "bar", topTerm = 20, direction = "both", palcolor = c("red3", "steelblue")
)
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", group_use = "Endocrine", plot_type = "network")
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", group_use = "Endocrine", plot_type = "enrichmap")
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", group_use = "Endocrine", plot_type = "wordcloud")
GSEAPlot(pancreas_sub, db = "GO_BP", group_by = "CellType", group_use = "Endocrine", plot_type = "wordcloud", word_type = "feature")
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