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

Which dimensionality reduction to use. If not specified, will use the reduction returned by 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

Name of a column in meta.data column to split plot by. Default is NULL.

features

A character vector of features to use. Default is NULL.

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

A character vector of cell names to use.

layer

Which layer to use. Default is "counts".

assay

Which assay to use. If NULL, the default assay of the Seurat object will be used. When the object also contains ChromatinAssay, the default assay and additional ChromatinAssay will be preprocessed sequentially.

max_cells

An integer, maximum number of cells to sample per group. Default is 100.

cell_order

A vector of cell names defining the order of cells. Default is NULL.

exp_method

A character vector specifying the method for calculating expression values. Options are "zscore", "raw", "fc", "log2fc", or "log1p". Default is "zscore".

stat_type

Set stat types ("percent" or "count").

combine

Whether to combine UMAP panels or StatPlot panels.

nrow, ncol, byrow

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

pt.size

The size of the points in the plot.

pt.alpha

The transparency of the data points. Default is 1.

palette

Color palette name. Available palettes can be found in thisplot::show_palettes. Default is "Chinese".

palcolor

Custom colors used to create a color palette. Default is NULL.

heatmap_palette

A character vector specifying the palette to use for the heatmap. Default is "RdBu".

group_palette

A character vector specifying the palette to use for groups. Default is "Chinese".

group_palcolor

A character vector specifying the group color to use. Default is NULL.

cell_annotation

A character vector specifying the cell annotation(s) to include. Default is NULL.

cell_annotation_palette

A character vector specifying the palette to use for cell annotations. The length of the vector should match the number of cell_annotation. Default is "Chinese".

cell_annotation_palcolor

A list of character vector specifying the cell annotation color(s) to use. The length of the list should match the number of cell_annotation. Default is NULL.

show_row_names

Whether to show row names in the heatmap. Default is FALSE.

show_column_names

Whether to show column names in the heatmap. Default is FALSE.

cluster_rows

Whether to cluster rows in the heatmap. Default is FALSE.

cluster_columns

Whether to cluster columns in the heatmap. Default is FALSE.

theme_use, theme_args

Theme used by thisplot::StatPlot.

verbose

Whether to print the message. Default is TRUE.

...

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
)
panc8_sub <- standard_scop(panc8_sub, verbose = FALSE)

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"
)

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

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

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

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