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FeatureStatPlot

Source: R/featurestatplot.R
FeatureStatPlot.Rd

Statistic plot for features

Usage

FeatureStatPlot(
  object,
  features,
  plot_type = c("violin", "box", "bar", "ridge", "dim", "cor", "heatmap", "dot"),
  reduction = NULL,
  graph = NULL,
  bg_cutoff = 0,
  dims = 1:2,
  rows_name = "Features",
  ident = "seurat_clusters",
  assay = NULL,
  layer = NULL,
  agg = mean,
  group_by = NULL,
  split_by = NULL,
  facet_by = NULL,
  xlab = NULL,
  ylab = NULL,
  x_text_angle = NULL,
  ...
)

Arguments

object

A seurat object

features

A character vector of feature names

plot_type

Type of the plot. It can be "violin", "box", "bar", "ridge", "dim", "cor", "heatmap" or "dot"

reduction

Name of the reduction to plot (for example, "umap"), only used when plot_type is "dim" or you can to use the reduction as feature.

graph

Specify the graph name to add edges between cell neighbors to the plot, only used when plot_type is "dim".

bg_cutoff

Background cutoff for the dim plot, only used when plot_type is "dim".

dims

Dimensions to plot, only used when plot_type is "dim".

rows_name

The name of the rows in the heatmap, only used when plot_type is "heatmap".

ident

The column name in the meta data to identify the cells.

assay

The assay to use for the feature data.

layer

The layer to use for the feature data.

agg

The aggregation function to use for the bar plot.

group_by

The column name in the meta data to group the cells.

split_by

Column name in the meta data to split the cells to different plots. If TRUE, the cells are split by the features.

facet_by

Column name in the meta data to facet the plots. Should be always NULL.

xlab

The x-axis label.

ylab

The y-axis label.

x_text_angle

The angle of the x-axis text. Only used when plot_type is "violin", "bar", or "box".

...

Other arguments passed to the plot functions.

  • For plot_type "violin", the arguments are passed to plotthis::ViolinPlot.

  • For plot_type "box", the arguments are passed to plotthis::BoxPlot.

  • For plot_type "bar", the arguments are passed to plotthis::BarPlot.

  • For plot_type "ridge", the arguments are passed to plotthis::RidgePlot.

  • For plot_type "dim", the arguments are passed to plotthis::FeatureDimPlot.

  • For plot_type "heatmap", the arguments are passed to plotthis::Heatmap.

  • For plot_type "cor" with 2 features, the arguments are passed to plotthis::CorPlot.

  • For plot_type "cor" with more than 2 features, the arguments are passed to plotthis::CorPairsPlot.

  • For plot_type "dot", the arguments are passed to plotthis::Heatmap with cell_type set to "dot".

Value

A ggplot object or a list if combine is FALSE

Examples

data(pancreas_sub)

FeatureStatPlot(pancreas_sub, features = c("G2M_score", "nCount_RNA"),
   ident = "SubCellType", facet_scales = "free_y")

FeatureStatPlot(pancreas_sub, features = c("G2M_score", "nCount_RNA"),
   ident = "SubCellType", plot_type = "box", facet_scales = "free_y")

FeatureStatPlot(pancreas_sub, features = c("G2M_score", "nCount_RNA"),
   ident = "SubCellType", plot_type = "bar", facet_scales = "free_y")

FeatureStatPlot(pancreas_sub, features = c("G2M_score", "nCount_RNA"),
   ident = "SubCellType", plot_type = "ridge", flip = TRUE, facet_scales = "free_y")
#> Picking joint bandwidth of 0.0498
#> Picking joint bandwidth of 516
#> Picking joint bandwidth of 0.0498
#> Picking joint bandwidth of 516

FeatureStatPlot(pancreas_sub, features = c("G2M_score", "nCount_RNA"),
   ident = "SubCellType", facet_scales = "free_y", add_point = TRUE)

FeatureStatPlot(pancreas_sub, features = c("G2M_score", "nCount_RNA"),
   ident = "SubCellType", facet_scales = "free_y", add_trend = TRUE)

FeatureStatPlot(pancreas_sub, features = c("G2M_score", "nCount_RNA"),
   ident = "SubCellType", facet_scales = "free_y", add_stat = mean)

FeatureStatPlot(pancreas_sub, features = c("G2M_score", "nCount_RNA"),
   ident = "SubCellType", facet_scales = "free_y", group_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: 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.

FeatureStatPlot(pancreas_sub, features = c("G2M_score"),
   ident = "SubCellType", group_by = "Phase", comparisons = TRUE)
#> Detected more than 2 groups. Use multiple_method 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.

FeatureStatPlot(pancreas_sub, features = c("Rbp4", "Pyy"), ident = "SubCellType",
   add_bg = TRUE, add_box = TRUE, stack = TRUE)

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

FeatureStatPlot(pancreas_sub, plot_type = "box", features = c(
      "Sox9", "Anxa2", "Bicc1", # Ductal
      "Neurog3", "Hes6", # EPs
      "Fev", "Neurod1", # Pre-endocrine
      "Rbp4", "Pyy", # Endocrine
      "Ins1", "Gcg", "Sst", "Ghrl" # Beta, Alpha, Delta, Epsilon
   ), ident = "SubCellType", add_bg = TRUE, stack = TRUE, flip = TRUE,
   legend.position = "top", legend.direction = "horizontal")

# Use splitting instead of facetting
FeatureStatPlot(pancreas_sub, features = c("Neurog3", "Rbp4", "Ins1"),
   ident = "CellType", split_by = TRUE)


FeatureStatPlot(pancreas_sub, plot_type = "dim", features = "G2M_score", reduction = "UMAP")

FeatureStatPlot(pancreas_sub, plot_type = "dim", features = "G2M_score", reduction = "UMAP",
   bg_cutoff = -Inf)

FeatureStatPlot(pancreas_sub, plot_type = "dim", features = "G2M_score", reduction = "UMAP",
   theme = "theme_blank")

FeatureStatPlot(pancreas_sub, plot_type = "dim", features = "G2M_score", reduction = "UMAP",
   theme = ggplot2::theme_classic, theme_args = list(base_size = 16))


# Label and highlight cell points
FeatureStatPlot(pancreas_sub, plot_type = "dim", features = "Rbp4", reduction = "UMAP",
   highlight = 'SubCellType == "Delta"')

FeatureStatPlot(pancreas_sub, plot_type = "dim",
   features = "Rbp4", split_by = "Phase", reduction = "UMAP",
   highlight = TRUE, theme = "theme_blank")


# Add a density layer
FeatureStatPlot(pancreas_sub, plot_type = "dim", features = "Rbp4", reduction = "UMAP",
   add_density = TRUE)

FeatureStatPlot(pancreas_sub, plot_type = "dim", features = "Rbp4", reduction = "UMAP",
   add_density = TRUE, density_filled = TRUE)
#> Warning: Removed 396 rows containing missing values or values outside the scale range
#> (`geom_raster()`).
#> Warning: Removed 396 rows containing missing values or values outside the scale range
#> (`geom_raster()`).


# Change the plot type from point to the hexagonal bin
FeatureStatPlot(pancreas_sub, plot_type = "dim", features = "Rbp4", reduction = "UMAP",
   hex = TRUE)
#> Warning: Removed 4 rows containing missing values or values outside the scale range
#> (`geom_hex()`).
#> Warning: Removed 4 rows containing missing values or values outside the scale range
#> (`geom_hex()`).

FeatureStatPlot(pancreas_sub, plot_type = "dim", features = "Rbp4", reduction = "UMAP",
   hex = TRUE, hex_bins = 20)
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_hex()`).
#> Warning: Removed 5 rows containing missing values or values outside the scale range
#> (`geom_hex()`).
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_hex()`).
#> Warning: Removed 5 rows containing missing values or values outside the scale range
#> (`geom_hex()`).


# Show lineages on the plot based on the pseudotime
FeatureStatPlot(pancreas_sub, plot_type = "dim", features = "Lineage3", reduction = "UMAP",
   lineages = "Lineage3")

FeatureStatPlot(pancreas_sub, plot_type = "dim", features = "Lineage3", reduction = "UMAP",
   lineages = "Lineage3", lineages_whiskers = TRUE)

FeatureStatPlot(pancreas_sub, plot_type = "dim", features = "Lineage3", reduction = "UMAP",
   lineages = "Lineage3", lineages_span = 0.1)


FeatureStatPlot(pancreas_sub, plot_type = "dim",
  features = c("Sox9", "Anxa2", "Bicc1"), reduction = "UMAP",
  theme = "theme_blank",
  theme_args = list(plot.subtitle = ggplot2::element_text(size = 10),
     strip.text = ggplot2::element_text(size = 8))
)


# Plot multiple features with different scales
endocrine_markers <- c("Ins1", "Gcg", "Sst", "Ghrl")
FeatureStatPlot(pancreas_sub, endocrine_markers, reduction = "UMAP", plot_type = "dim")

FeatureStatPlot(pancreas_sub, endocrine_markers, reduction = "UMAP", lower_quantile = 0,
   upper_quantile = 0.8, plot_type = "dim")

FeatureStatPlot(pancreas_sub, endocrine_markers, reduction = "UMAP",
   lower_cutoff = 1, upper_cutoff = 4, plot_type = "dim")

FeatureStatPlot(pancreas_sub, endocrine_markers, reduction = "UMAP", bg_cutoff = 2,
   lower_cutoff = 2, upper_cutoff = 4, plot_type = "dim")

FeatureStatPlot(pancreas_sub, c("Sst", "Ghrl"), split_by = "Phase", reduction = "UMAP",
   plot_type = "dim")

FeatureStatPlot(pancreas_sub, features = c("G2M_score", "nCount_RNA"),
   ident = "SubCellType", plot_type = "dim", facet_by = "Phase", split_by = TRUE, ncol = 1)


# Heatmap
features <- c(
   "Sox9", "Anxa2", "Bicc1", # Ductal
   "Neurog3", "Hes6", # EPs
   "Fev", "Neurod1", # Pre-endocrine
   "Rbp4", "Pyy", # Endocrine
   "Ins1", "Gcg", "Sst", "Ghrl" # Beta, Alpha, Delta, Epsilon
)
rows_data <- data.frame(
   features = features,
   group = c(
       "Ductal", "Ductal", "Ductal", "EPs", "EPs", "Pre-endocrine",
       "Pre-endocrine", "Endocrine", "Endocrine", "Beta", "Alpha", "Delta", "Epsilon"),
   TF = c(TRUE, FALSE, FALSE, TRUE, FALSE, TRUE, FALSE, TRUE, FALSE, TRUE,
       TRUE, TRUE, TRUE),
   CSPA = c(FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, TRUE, TRUE,
       FALSE, FALSE, FALSE)
)
FeatureStatPlot(pancreas_sub, features = features, ident = "SubCellType",
   plot_type = "heatmap", name = "Expression Level")

FeatureStatPlot(pancreas_sub, features = features, ident = "Phase",
   plot_type = "heatmap", name = "Expression Level", columns_split_by = "SubCellType")

FeatureStatPlot(pancreas_sub, features = features, ident = "SubCellType",
   plot_type = "heatmap", cell_type = "bars", name = "Expression Level")

FeatureStatPlot(pancreas_sub, features = features, ident = "SubCellType", cell_type = "dot",
   plot_type = "heatmap", name = "Expression Level", dot_size = function(x) sum(x > 0) / length(x),
   dot_size_name = "Percent Expressed", add_bg = TRUE,
   rows_data = rows_data, show_row_names = TRUE, rows_split_by = "group", cluster_rows = FALSE,
   column_annotation = c("Phase", "G2M_score"),
   column_annotation_type = list(Phase = "pie", G2M_score = "violin"),
   column_annotation_params = list(G2M_score = list(show_legend = FALSE)),
   row_annotation = c("TF", "CSPA"),
   row_annotation_side = "right",
   row_annotation_type = list(TF = "simple", CSPA = "simple"))
#> Warning: Assuming 'row_annotation_agg["TF"] = dplyr::first' for the simple column annotation
#> Warning: Assuming 'row_annotation_agg["CSPA"] = dplyr::first' for the simple column annotation

FeatureStatPlot(pancreas_sub, features = features, ident = "SubCellType", cell_type = "dot",
   plot_type = "heatmap", name = "Expression Level", dot_size = function(x) sum(x > 0) / length(x),
   dot_size_name = "Percent Expressed", add_bg = TRUE,
   rows_data = rows_data, show_column_names = TRUE, rows_split_by = "group",
   cluster_rows = FALSE, flip = TRUE, palette = "YlOrRd",
   column_annotation = c("Phase", "G2M_score"),
   column_annotation_type = list(Phase = "pie", G2M_score = "violin"),
   column_annotation_params = list(G2M_score = list(show_legend = FALSE)),
   row_annotation = c("TF", "CSPA"),
   row_annotation_side = "right",
   row_annotation_type = list(TF = "simple", CSPA = "simple"))
#> Warning: Assuming 'row_annotation_agg["TF"] = dplyr::first' for the simple column annotation
#> Warning: Assuming 'row_annotation_agg["CSPA"] = dplyr::first' for the simple column annotation

FeatureStatPlot(pancreas_sub, features = features, ident = "SubCellType", cell_type = "violin",
   plot_type = "heatmap", name = "Expression Level", show_row_names = TRUE,
   cluster_columns = FALSE, rows_split_by = "group", rows_data = rows_data)

FeatureStatPlot(pancreas_sub, features = features, ident = "SubCellType", cell_type = "dot",
   plot_type = "heatmap", dot_size = function(x) sum(x > 0) / length(x),
   dot_size_name = "Percent Expressed", palette = "viridis", add_reticle = TRUE,
   rows_data = rows_data, name = "Expression Level", show_row_names = TRUE,
   rows_split_by = "group")


# Use plot_type = "dot" to as a shortcut for heatmap with cell_type = "dot"
FeatureStatPlot(pancreas_sub, features = features, ident = "SubCellType", plot_type = "dot")


named_features <- list(
   Ductal = c("Sox9", "Anxa2", "Bicc1"),
   EPs = c("Neurog3", "Hes6"),
   `Pre-endocrine` = c("Fev", "Neurod1"),
   Endocrine = c("Rbp4", "Pyy"),
   Beta = "Ins1", Alpha = "Gcg", Delta = "Sst", Epsilon = "Ghrl"
)
FeatureStatPlot(pancreas_sub, features = named_features, ident = "SubCellType",
   plot_type = "heatmap", name = "Expression Level", show_row_names = TRUE)


# Correlation plot
FeatureStatPlot(pancreas_sub, features = c("Pyy", "Rbp4"), plot_type = "cor",
   anno_items = c("eq", "r2", "spearman"))

FeatureStatPlot(pancreas_sub, features = c("Ins1", "Gcg", "Sst", "Ghrl"),
   plot_type = "cor")