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Statistical plot of features

Source: R/FeatureStatPlot.R
FeatureStatPlot.Rd

This function generates a statistical plot for features.

Usage

FeatureStatPlot(
  srt,
  stat.by,
  group.by = NULL,
  split.by = NULL,
  bg.by = NULL,
  plot.by = c("group", "feature"),
  fill.by = c("group", "feature", "expression"),
  cells = NULL,
  layer = "data",
  assay = NULL,
  keep_empty = FALSE,
  individual = FALSE,
  plot_type = c("violin", "box", "bar", "dot", "col"),
  palette = "Paired",
  palcolor = NULL,
  alpha = 1,
  bg_palette = "Paired",
  bg_palcolor = NULL,
  bg_alpha = 0.2,
  add_box = FALSE,
  box_color = "black",
  box_width = 0.1,
  box_ptsize = 2,
  add_point = FALSE,
  pt.color = "grey30",
  pt.size = NULL,
  pt.alpha = 1,
  jitter.width = 0.4,
  jitter.height = 0.1,
  add_trend = FALSE,
  trend_color = "black",
  trend_linewidth = 1,
  trend_ptsize = 2,
  add_stat = c("none", "mean", "median"),
  stat_color = "black",
  stat_size = 1,
  stat_stroke = 1,
  stat_shape = 25,
  add_line = NULL,
  line_color = "red",
  line_size = 1,
  line_type = 1,
  cells.highlight = NULL,
  cols.highlight = "red",
  sizes.highlight = 1,
  alpha.highlight = 1,
  calculate_coexp = FALSE,
  same.y.lims = FALSE,
  y.min = NULL,
  y.max = NULL,
  y.trans = "identity",
  y.nbreaks = 5,
  sort = FALSE,
  stack = FALSE,
  flip = FALSE,
  comparisons = NULL,
  ref_group = NULL,
  pairwise_method = "wilcox.test",
  multiplegroup_comparisons = FALSE,
  multiple_method = "kruskal.test",
  sig_label = c("p.signif", "p.format"),
  sig_labelsize = 3.5,
  aspect.ratio = NULL,
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = "Expression level",
  legend.position = "right",
  legend.direction = "vertical",
  theme_use = "theme_scop",
  theme_args = list(),
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  force = FALSE,
  seed = 11
)

Arguments

srt

A Seurat object.

stat.by

A character vector specifying the features to plot.

group.by

Name of one or more meta.data columns to group (color) cells by.

split.by

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

bg.by

A character vector specifying the variable to use as the background color. Default is NULL.

plot.by

A character vector specifying how to plot the data, by group or feature. Possible values are "group" or "feature". Default is "group".

fill.by

A string specifying what to fill the plot by. Possible values are "group", "feature", or "expression". Default is "group".

cells

A character vector of cell names to use. Default is NULL.

layer

Which layer to use. Default is data.

assay

Which assay to use. If NULL, the default assay of the Seurat object will be used.

keep_empty

Whether to keep empty levels in the plot. Default is FALSE.

individual

Whether to create individual plots for each group. Default is FALSE.

plot_type

A string specifying the type of plot to create. Possible values are "violin", "box", "bar", "dot", or "col". Default is "violin".

palette

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

palcolor

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

alpha

The transparency of the plot. Default is 1.

bg_palette

A string specifying the color palette to use for the background. Default is "Paired".

bg_palcolor

A character vector specifying specific colors to use for the background. Default is NULL.

bg_alpha

The transparency of the background. Default is 0.2.

add_box

Whether to add a box plot to the plot. Default is FALSE.

box_color

A string specifying the color of the box plot. Default is "black".

box_width

The width of the box plot. Default is 0.1.

box_ptsize

The size of the points of the box plot. Default is 2.

add_point

Whether to add individual data points to the plot. Default is FALSE.

pt.color

A string specifying the color of the data points. Default is "grey30".

pt.size

The size of the points in the plot.

pt.alpha

The transparency of the data points. Default is 1.

jitter.width

The width of the jitter. Default is 0.5.

jitter.height

The height of the jitter. Default is 0.1.

add_trend

Whether to add a trend line to the plot. Default is FALSE.

trend_color

A string specifying the color of the trend line. Default is "black".

trend_linewidth

The width of the trend line. Default is 1.

trend_ptsize

The size of the points of the trend line. Default is 2.

add_stat

A string specifying which statistical summary to add to the plot. Possible values are "none", "mean", or "median". Default is "none".

stat_color

A string specifying the color of the statistical summary. Default is "black".

stat_size

The size of the statistical summary. Default is 1.

stat_stroke

The stroke width of the statistical summary. Default is 1.

stat_shape

The shape of the statistical summary. Default is 25.

add_line

The y-intercept for adding a horizontal line. Default is NULL.

line_color

A string specifying the color of the horizontal line. Default is "red".

line_size

The width of the horizontal line. Default is 1.

line_type

The type of the horizontal line. Default is 1.

cells.highlight

A logical or character vector specifying the cells to highlight in the plot. If TRUE, all cells are highlighted. If FALSE, no cells are highlighted. Default is NULL.

cols.highlight

A string specifying the color of the highlighted cells. Default is "red".

sizes.highlight

The size of the highlighted cells. Default is 1.

alpha.highlight

The transparency of the highlighted cells. Default is 1.

calculate_coexp

Whether to calculate co-expression values. Default is FALSE.

same.y.lims

Whether to use the same y-axis limits for all plots. Default is FALSE.

y.min

A numeric or character value specifying the minimum y-axis limit. If a character value is provided, it must be of the form "qN" where N is a number between 0 and 100 (inclusive) representing the quantile to use for the limit. Default is NULL.

y.max

A numeric or character value specifying the maximum y-axis limit. If a character value is provided, it must be of the form "qN" where N is a number between 0 and 100 (inclusive) representing the quantile to use for the limit. Default is NULL.

y.trans

A string specifying the transformation to apply to the y-axis. Possible values are "identity" or "log2". Default is "identity".

y.nbreaks

A number of breaks to use for the y-axis. Default is 5.

sort

A logical or character value specifying whether to sort the groups on the x-axis. If TRUE, groups are sorted in increasing order. If FALSE, groups are not sorted. If "increasing", groups are sorted in increasing order. If "decreasing", groups are sorted in decreasing order. Default is FALSE.

stack

A logical specifying whether to stack the plots on top of each other. Default is FALSE.

flip

A logical specifying whether to flip the plot vertically. Default is FALSE.

comparisons

A list of length-2 vectors. The entries in the vector are either the names of 2 values on the x-axis or the 2 integers that correspond to the index of the groups of interest, to be compared.

ref_group

A string specifying the reference group for pairwise comparisons. Default is NULL.

pairwise_method

Method to use for pairwise comparisons. Default is "wilcox.test".

multiplegroup_comparisons

Whether to add multiple group comparisons to the plot. Default is FALSE.

multiple_method

Method to use for multiple group comparisons. Default is "kruskal.test".

sig_label

A string specifying the label to use for significant comparisons. Possible values are "p.signif" or "p.format". Default is "p.format".

sig_labelsize

The size of the significant comparison labels. Default is 3.5.

aspect.ratio

Aspect ratio of the panel. Default is NULL.

title

The text for the title. Default is NULL.

subtitle

The text for the subtitle for the plot which will be displayed below the title. Default is NULL.

xlab

The x-axis label of the plot. Default is NULL.

ylab

A string specifying the label of the y-axis. Default is "Expression level".

legend.position

The position of legends, one of "none", "left", "right", "bottom", "top". Default is "right".

legend.direction

The direction of the legend in the plot. Can be one of "vertical" or "horizontal".

theme_use

Theme used. Can be a character string or a theme function. Default is "theme_scop".

theme_args

Other arguments passed to the theme_use. Default is list().

combine

Combine plots into a single patchwork object. If FALSE, return a list of ggplot objects.

nrow

Number of rows in the combined plot. Default is NULL, which means determined automatically based on the number of plots.

ncol

Number of columns in the combined plot. Default is NULL, which means determined automatically based on the number of plots.

byrow

Whether to arrange the plots by row in the combined plot. Default is TRUE.

force

Whether to force drawing regardless of maximum levels in any cell group is greater than 100. Default is FALSE.

seed

Random seed for reproducibility. Default is 11.

See also

CellStatPlot, StatPlot

Examples

data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
#> ℹ [2026-01-27 07:49:50] Start standard scop workflow...
#> ℹ [2026-01-27 07:49:51] Checking a list of <Seurat>...
#> ! [2026-01-27 07:49:51] Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2026-01-27 07:49:51] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on the data 1/1 of the `srt_list`...
#> ℹ [2026-01-27 07:49:53] Perform `Seurat::FindVariableFeatures()` on the data 1/1 of the `srt_list`...
#> ℹ [2026-01-27 07:49:54] Use the separate HVF from srt_list
#> ℹ [2026-01-27 07:49:54] Number of available HVF: 2000
#> ℹ [2026-01-27 07:49:54] Finished check
#> ℹ [2026-01-27 07:49:54] Perform `Seurat::ScaleData()`
#> ℹ [2026-01-27 07:49:54] Perform pca linear dimension reduction
#> ℹ [2026-01-27 07:49:55] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#> ℹ [2026-01-27 07:49:55] Reorder clusters...
#> ℹ [2026-01-27 07:49:55] Perform umap nonlinear dimension reduction
#> ℹ [2026-01-27 07:49:55] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#> ℹ [2026-01-27 07:49:59] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#> ✔ [2026-01-27 07:50:03] Run scop standard workflow completed
FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType"
) |> thisplot::panel_fix(height = 1, width = 2)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType",
  plot_type = "box"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType",
  plot_type = "bar"
)
#> Warning: Computation failed in `stat_summary()`.
#> Caused by error in `fun.data()`:
#> ! The package "Hmisc" is required.
#> Warning: Computation failed in `stat_summary()`.
#> Caused by error in `fun.data()`:
#> ! The package "Hmisc" is required.
#> Warning: Computation failed in `stat_summary()`.
#> Caused by error in `fun.data()`:
#> ! The package "Hmisc" is required.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: Computation failed in `stat_summary()`.
#> Caused by error in `fun.data()`:
#> ! The package "Hmisc" is required.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType",
  plot_type = "dot"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.

FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType",
  plot_type = "col"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType",
  add_box = TRUE
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType",
  add_point = TRUE
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.

FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType",
  add_trend = TRUE
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType",
  add_stat = "mean"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType",
  add_line = 0.2,
  line_type = 2
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType",
  split.by = "Phase"
)
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType",
  split.by = "Phase",
  add_box = TRUE,
  add_trend = TRUE
)
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("G2M_score", "Fev"),
  group.by = "SubCellType",
  split.by = "Phase",
  comparisons = TRUE
)
#> ℹ [2026-01-27 07:50:25] Detected more than 2 groups. Use "kruskal.test" for comparison
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> ℹ [2026-01-27 07:50:25] Detected more than 2 groups. Use "kruskal.test" for comparison
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("Rbp4", "Pyy"),
  group.by = "SubCellType",
  fill.by = "expression",
  palette = "Blues",
  same.y.lims = TRUE
)


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("Rbp4", "Pyy"),
  group.by = "SubCellType",
  multiplegroup_comparisons = TRUE
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("Rbp4", "Pyy"),
  group.by = "SubCellType",
  comparisons = list(c("Alpha", "Beta"), c("Alpha", "Delta"))
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("Rbp4", "Pyy"),
  group.by = "SubCellType",
  comparisons = list(c("Alpha", "Beta"), c("Alpha", "Delta")),
  sig_label = "p.format"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("Rbp4", "Pyy"),
  group.by = "SubCellType",
  bg.by = "CellType",
  add_box = TRUE, stack = TRUE
)


FeatureStatPlot(
  pancreas_sub,
  stat.by = c(
    "Sox9", "Anxa2", "Bicc1", # Ductal
    "Neurog3", "Hes6", # EPs
    "Fev", "Neurod1", # Pre-endocrine
    "Rbp4", "Pyy", # Endocrine
    "Ins1", "Gcg", "Sst", "Ghrl" # Beta, Alpha, Delta, Epsilon
  ),
  legend.position = "top",
  legend.direction = "horizontal",
  group.by = "SubCellType",
  bg.by = "CellType",
  stack = TRUE
)


FeatureStatPlot(
  pancreas_sub,
  stat.by = c(
    "Sox9", "Anxa2", "Bicc1", # Ductal
    "Neurog3", "Hes6", # EPs
    "Fev", "Neurod1", # Pre-endocrine
    "Rbp4", "Pyy", # Endocrine
    "Ins1", "Gcg", "Sst", "Ghrl" # Beta, Alpha, Delta, Epsilon
  ),
  fill.by = "feature",
  plot_type = "box",
  group.by = "SubCellType",
  bg.by = "CellType", stack = TRUE, flip = TRUE
) |> thisplot::panel_fix_overall(
  width = 8, height = 5
)

# As the plot is created by combining,
# we can adjust the overall height and width directly.

FeatureStatPlot(
  pancreas_sub,
  stat.by = c("Neurog3", "Rbp4", "Ins1"),
  group.by = "CellType",
  plot.by = "group"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("Neurog3", "Rbp4", "Ins1"),
  group.by = "CellType",
  plot.by = "feature"
)
#> ℹ [2026-01-27 07:50:43] Setting `group.by` to "Features" as `plot.by` is set to "feature"
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("Neurog3", "Rbp4", "Ins1"),
  group.by = "CellType",
  plot.by = "feature",
  multiplegroup_comparisons = TRUE,
  sig_label = "p.format",
  sig_labelsize = 4
)
#> ℹ [2026-01-27 07:50:44] Setting `group.by` to "Features" as `plot.by` is set to "feature"
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.


FeatureStatPlot(
  pancreas_sub,
  stat.by = c("Neurog3", "Rbp4", "Ins1"),
  group.by = "CellType",
  plot.by = "feature",
  comparisons = list(c("Neurog3", "Rbp4"), c("Rbp4", "Ins1")),
  stack = TRUE
)
#> ℹ [2026-01-27 07:50:47] Setting `group.by` to "Features" as `plot.by` is set to "feature"


FeatureStatPlot(pancreas_sub,
  stat.by = c(
    "Sox9", "Anxa2", "Bicc1", # Ductal
    "Neurog3", "Hes6", # EPs
    "Fev", "Neurod1", # Pre-endocrine
    "Rbp4", "Pyy", # Endocrine
    "Ins1", "Gcg", "Sst", "Ghrl" # Beta, Alpha, Delta, Epsilon
  ), group.by = "SubCellType",
  plot.by = "feature",
  stack = TRUE
)
#> ℹ [2026-01-27 07:50:50] Setting `group.by` to "Features" as `plot.by` is set to "feature"


data <- GetAssayData5(
  pancreas_sub,
  assay = "RNA",
  layer = "data"
)
pancreas_sub <- SeuratObject::SetAssayData(
  object = pancreas_sub,
  layer = "scale.data",
  assay = "RNA",
  new.data = data / Matrix::rowMeans(data)
)
#> Warning: Different features in new layer data than already exists for scale.data
FeatureStatPlot(
  pancreas_sub,
  stat.by = c("Neurog3", "Rbp4"),
  group.by = "CellType",
  layer = "scale.data",
  ylab = "FoldChange",
  same.y.lims = TRUE,
  y.max = 4
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's colour values.