Plot Scissor results

Plot Scissor results

Usage

ScissorPlot(
  srt,
  plot_type = c("umap", "heatmap", "bar", "upset", "rose", "ring", "pie", "dot"),
  reduction = NULL,
  prefix = "Scissor",
  group.by = NULL,
  split.by = NULL,
  features = NULL,
  nfeatures = 50,
  feature_method = c("variance", "status_diff", "coef_cor", "input_order"),
  tool_name = "Scissor",
  status = c("Scissor+", "Scissor-"),
  include.background = TRUE,
  upset_top_n = NULL,
  cells = NULL,
  layer = "data",
  assay = NULL,
  max_cells = 100,
  cell_order = NULL,
  exp_method = "zscore",
  stat_type = c("percent", "count"),
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  pt.size = NULL,
  pt.alpha = 1,
  palette = "Chinese",
  palcolor = NULL,
  heatmap_palette = "RdBu",
  group_palette = "Chinese",
  group_palcolor = NULL,
  cell_annotation = NULL,
  cell_annotation_palette = "Chinese",
  cell_annotation_palcolor = NULL,
  show_row_names = FALSE,
  show_column_names = FALSE,
  cluster_rows = FALSE,
  cluster_columns = FALSE,
  theme_use = "theme_scop",
  theme_args = list(),
  verbose = TRUE,
  ...
)

Arguments

srt

A Seurat object after RunScissor.

plot_type

Plot type. "umap" shows embedding panels, "heatmap" shows a FeatureHeatmap, and statistical views such as "bar" and "upset" are drawn with thisplot::StatPlot.

reduction

Reduction to plot. NULL uses DefaultReduction.

prefix

Prefix used by RunScissor.

group.by

Optional metadata column shown together with Scissor status. For "heatmap", the default is the Scissor status column. For statistical plots, it is passed to thisplot::StatPlot, except that "upset" uses it to split Scissor status distributions by group.

split.by

Metadata column to facet by.

features

Features to plot.

nfeatures

Number of features to show when plot_type = "heatmap" and features = NULL.

feature_method

Method used to rank heatmap features when features = NULL. "variance" ranks genes by variance in selected cells, "status_diff" ranks by the largest mean-expression difference between Scissor status groups, "coef_cor" ranks by absolute correlation with Scissor coefficients, and "input_order" keeps the RunScissor input order.

tool_name

Name of the srt@tools entry created by RunScissor.

status

Scissor status levels included in the heatmap.

include.background

Whether to include background cells in heatmap and background status in upset plots.

upset_top_n

Maximum number of group.by levels to show in plot_type = "upset". The most frequent levels are kept. NULL keeps all.

cells

Cell names to include.

layer

Assay layer to use.

assay

Assay to use. NULL uses the default assay.

max_cells

An integer, maximum number of cells to sample per group.

cell_order

A vector of cell names defining the order of cells.

exp_method

Expression transform: "zscore", "raw", "fc", "log2fc", or "log1p".

stat_type

The type of statistic to compute for the plot. Can be one of "percent", "count", or "value". Continuous value mode supports plot_type = "bar" and plot_type = "dot".

combine

Whether to combine UMAP panels or StatPlot panels.

nrow, ncol, byrow

Layout parameters passed to patchwork::wrap_plots() or thisplot::StatPlot.

pt.size, pt.alpha

Point size and transparency. pt.size = NULL scales with sqrt(n) (minimum 0.3). Rasterized points keep at least a two-pixel radius at raster.dpi = c(512, 512) and scale with raster.dpi.

palette, palcolor

Palette name (thisplot::show_palettes) or custom colors.

heatmap_palette

Palette used for CNV heatmap values.

group_palette

Palette for cell types (groups) in Manhattan plot.

group_palcolor

Custom colors for cell types (groups) in Manhattan plot.

cell_annotation

Cell annotations. Palette length should match cell_annotation.

cell_annotation_palette

Color palette for cell-type annotations.

cell_annotation_palcolor

Custom colors for cell-type annotations.

show_row_names

Whether to draw row/column names for the heatmap body.

show_column_names

Whether to draw row/column names for the heatmap body.

cluster_rows

Whether to cluster heatmap rows/columns. Defaults are both FALSE.

cluster_columns

Whether to cluster heatmap rows/columns. Defaults are both FALSE.

theme_use, theme_args

Theme used by thisplot::StatPlot.

verbose

Whether to print messages.

...

Additional arguments passed to CellDimPlot, FeatureDimPlot, FeatureHeatmap, or thisplot::StatPlot, depending on plot_type.

Value

A ggplot/patchwork object for embedding and statistical plots, or a list returned by FeatureHeatmap for plot_type = "heatmap".

See also

ScissorPlot

Examples

data(panc8_sub)
data(islet_bulk)
panc8_sub <- RunScissor(
  panc8_sub,
  bulk_dataset = islet_bulk,
  condition.by = "condition",
  positive = "bfa",
  family = "binomial",
  features = head(intersect(
    rownames(panc8_sub),
    rownames(SummarizedExperiment::assay(islet_bulk, "counts"))
  ), 1000),
  alpha = 0.2,
  cutoff = 0.5
)
#> ℹ [2026-08-30 05:54:35] Build a temporary Scissor-style SNN graph
#> ℹ [2026-08-30 05:55:30] Scissor alpha 0.2 selected 1 positive and 501 negative cells (31.375%)
#> ✔ [2026-08-30 05:55:30] Scissor stored 1 Scissor+ and 501 Scissor- cells
panc8_sub <- RunStandardWorkflow(panc8_sub, verbose = FALSE)
#> ℹ [2026-08-30 05:55:32] Skip `log1p()` because `layer = data` is not "counts"

ScissorPlot(
  panc8_sub,
  xlab = "UMAP_1",
  ylab = "UMAP_2"
)


ScissorPlot(
  panc8_sub,
  group.by = "celltype",
  xlab = "UMAP_1",
  ylab = "UMAP_2"
)


ht <- ScissorPlot(
  panc8_sub,
  plot_type = "heatmap",
  group.by = "celltype"
)
ht$plot


ScissorPlot(
  panc8_sub,
  plot_type = "bar",
  group.by = "celltype"
)


ScissorPlot(
  panc8_sub,
  plot_type = "upset"
)
#> `geom_line()`: Each group consists of only one observation.
#> ℹ Do you need to adjust the group aesthetic?
#> `geom_line()`: Each group consists of only one observation.
#> ℹ Do you need to adjust the group aesthetic?


ScissorPlot(
  panc8_sub,
  plot_type = "rose",
  label = TRUE
)


ScissorPlot(
  panc8_sub,
  plot_type = "ring",
  label = TRUE
)
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).


ScissorPlot(
  panc8_sub,
  plot_type = "pie",
  label = TRUE
)


ScissorPlot(
  panc8_sub,
  plot_type = "dot",
  label = TRUE
)