Help for package SCpubr

Type:

Package

Title:

Generate Publication Ready Visualizations of Single Cell Transcriptomics Data

Version:

2.0.2

Description:

A system that provides a streamlined way of generating publication ready plots for known Single-Cell transcriptomics data in a “publication ready” format. This is, the goal is to automatically generate plots with the highest quality possible, that can be used right away or with minimal modifications for a research article.

License:

GPL-3

URL:

https://github.com/enblacar/SCpubr/, https://enblacar.github.io/SCpubr-book/

BugReports:

https://github.com/enblacar/SCpubr/issues/

Depends:

R (≥ 4.0.0)

Suggests:

AnnotationDbi, assertthat, AUCell, circlize, cli, cluster, clusterProfiler, colorspace, ComplexHeatmap, covr, decoupleR, dplyr (≥ 1.1.0), enrichplot, forcats, ggalluvial, ggbeeswarm, ggdist, ggExtra, ggh4x, ggnewscale, ggplot2 (≥ 3.4.0), ggplotify, ggrastr, ggrepel, ggridges, ggsignif, graphics, infercnv, knitr, labeling, magrittr, MASS, Matrix, methods, Nebulosa, org.Hs.eg.db, patchwork, pheatmap, plyr, purrr, qpdf, RColorBrewer, rjags, rlang, rmarkdown, scales, scattermore, Seurat, SeuratObject, sf, stringr, svglite, testthat (≥ 3.0.0), tibble, tidyr, UCell, viridis, withr

VignetteBuilder:

knitr

biocViews:

Software, SingleCell, Visualization

Config/testthat/edition:

Encoding:

UTF-8

LazyData:

true

LazyDataCompression:

RoxygenNote:

7.2.1

NeedsCompilation:

Packaged:

2023-10-11 09:31:17 UTC; e420a

Author:

Enrique Blanco-Carmona

[cre, aut]

Maintainer:

Enrique Blanco-Carmona <scpubr@gmail.com>

Repository:

CRAN

Date/Publication:

2023-10-11 09:50:02 UTC

Generate Alluvial plots.

Description

This function is based on the ggalluvial package. It allows you to generate alluvial plots from a given Seurat object.

Usage

do_AlluvialPlot(
  sample,
  first_group,
  last_group,
  middle_groups = NULL,
  colors.use = NULL,
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  font.size = 14,
  font.type = "sans",
  xlab = NULL,
  ylab = "Number of cells",
  repel = FALSE,
  fill.by = last_group,
  use_labels = FALSE,
  stratum.color = "black",
  stratum.fill = "white",
  stratum.width = 1/3,
  stratum.fill.conditional = FALSE,
  use_geom_flow = FALSE,
  alluvium.color = "white",
  flow.color = "white",
  flip = FALSE,
  label.color = "black",
  curve_type = "sigmoid",
  use_viridis = FALSE,
  viridis.palette = "G",
  viridis.direction = -1,
  sequential.palette = "YlGnBu",
  sequential.direction = 1,
  plot.grid = FALSE,
  grid.color = "grey75",
  grid.type = "dashed",
  na.value = "white",
  legend.position = "right",
  legend.title = NULL,
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

first_group

character | Categorical metadata variable. First group of nodes of the alluvial plot.

last_group

character | Categorical metadata variable. Last group of nodes of the alluvial plot.

middle_groups

character | Categorical metadata variable. Vector of groups of nodes of the alluvial plot.

colors.use

character | Named list of colors corresponding to the unique values in fill.by (which defaults to last_group).

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

xlab, ylab

character | Titles for the X and Y axis.

repel

logical | Whether to repel the text labels.

fill.by

character | One of first_group, middle_groups (one of the values, if multiple mid_groups) or last_group. These values will be used to color the alluvium/flow.

use_labels

logical | Whether to use labels instead of text for the stratum.

stratum.color, alluvium.color, flow.color

character | Color for the border of the alluvium (and flow) and stratum.

stratum.fill

character | Color to fill the stratum.

stratum.width

logical | Width of the stratum.

stratum.fill.conditional

logical | Whether to fill the stratum with the same colors as the alluvium/flow.

use_geom_flow

logical | Whether to use geom_flow instead of geom_alluvium. Visual results might differ.

flip

logical | Whether to invert the axis of the displayed plot.

label.color

character | Color for the text labels.

curve_type

character | Type of curve used in geom_alluvium. One of:

linear.
cubic.
quintic.
sine.
arctangent.
sigmoid.
xspline.

use_viridis

logical | Whether to use viridis color scales.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

plot.grid

logical | Whether to plot grid lines.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

grid.type

character | One of the possible linetype options:

blank.
solid.
dashed.
dotted.
dotdash.
longdash.
twodash.

na.value

character | Color value for NA.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.title

character | Title for the legend.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_AlluvialPlot", passive = TRUE)
  message(value)
  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Compute basic sankey plot.
    p <- SCpubr::do_AlluvialPlot(sample = sample,
                                 first_group = "orig.ident",
                                 last_group = "seurat_clusters")

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Create Bar Plots.

Description

Create Bar Plots.

Usage

do_BarPlot(
  sample,
  group.by,
  order = FALSE,
  add.n = FALSE,
  add.n.face = "bold",
  add.n.expand = c(0, 1.15),
  add.n.size = 4,
  order.by = NULL,
  split.by = NULL,
  facet.by = NULL,
  position = "stack",
  font.size = 14,
  font.type = "sans",
  legend.position = "bottom",
  legend.title = NULL,
  legend.ncol = NULL,
  legend.nrow = NULL,
  legend.byrow = FALSE,
  axis.text.x.angle = 45,
  xlab = NULL,
  ylab = NULL,
  colors.use = NULL,
  flip = FALSE,
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  plot.grid = FALSE,
  grid.color = "grey75",
  grid.type = "dashed",
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain",
  strip.text.face = "bold",
  return_data = FALSE
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

group.by

character | Metadata column to compute the counts of. Has to be either a character or factor column.

order

logical | Whether to order the results in descending order of counts.

add.n

logical | Whether to add the total counts on top of each bar.

add.n.face

character | Font face of the labels added by add.n.

add.n.expand

numeric | Vector of two numerics representing the start and end of the scale. Minimum should be 0 and max should be above 1. This basically expands the Y axis so that the labels fit when flip = TRUE.

stack: Set the bars side by side, displaying the total number of counts. Uses position_stack.
fill: Set the bars on top of each other, displaying the proportion of counts from the total that each group represents. Uses position_fill.

add.n.size

numeric | Size of the labels

order.by

character | When split.by is used, value of group.by to reorder the columns based on its value.

split.by

character | Metadata column to split the values of group.by by. If not used, defaults to the active idents.

facet.by

character | Metadata column to gather the columns by. This is useful if you have other overarching metadata.

position

character | Position function from ggplot2. Either stack or fill.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.title

character | Title for the legend.

legend.ncol

numeric | Number of columns in the legend.

legend.nrow

numeric | Number of rows in the legend.

legend.byrow

logical | Whether the legend is filled by row or not.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

xlab, ylab

character | Titles for the X and Y axis.

colors.use

named_vector | Named vector of valid color representations (either name of HEX codes) with as many named colors as unique values of group.by. If group.by is not provided, defaults to the unique values of Idents. If not provided, a color scale will be set by default.

flip

logical | Whether to invert the axis of the displayed plot.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

plot.grid

logical | Whether to plot grid lines.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

grid.type

character | One of the possible linetype options:

blank.
solid.
dashed.
dotted.
dotdash.
longdash.
twodash.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

strip.text.face

character | Controls the style of the font for the strip text. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

return_data

logical | Returns a data.frame with the count and proportions displayed in the plot.

Value

A ggplot2 object containing a Bar plot.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_BarPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Basic bar plot, horizontal.
    p1 <- SCpubr::do_BarPlot(sample = sample,
                             group.by = "seurat_clusters",
                             legend.position = "none",
                             plot.title = "Number of cells per cluster")

    # Split by a second variable.
    sample$modified_orig.ident <- sample(x = c("Sample_A", "Sample_B", "Sample_C"),
                                         size = ncol(sample),
                                         replace = TRUE,
                                         prob = c(0.2, 0.7, 0.1))

    p <- SCpubr::do_BarPlot(sample,
                            group.by = "seurat_clusters",
                            split.by = "modified_orig.ident",
                            plot.title = "Number of cells per cluster in each sample",
                            position = "stack")


  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

BeeSwarm plot.

Description

BeeSwarm plot.

Usage

do_BeeSwarmPlot(
  sample,
  feature_to_rank,
  group.by = NULL,
  assay = NULL,
  reduction = NULL,
  slot = NULL,
  continuous_feature = FALSE,
  order = FALSE,
  colors.use = NULL,
  legend.title = NULL,
  legend.type = "colorbar",
  legend.position = "bottom",
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.length = 20,
  legend.width = 1,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  legend.ncol = NULL,
  legend.icon.size = 4,
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  xlab = NULL,
  ylab = NULL,
  font.size = 14,
  font.type = "sans",
  remove_x_axis = FALSE,
  remove_y_axis = FALSE,
  flip = FALSE,
  use_viridis = FALSE,
  viridis.palette = "G",
  viridis.direction = 1,
  sequential.palette = "YlGnBu",
  sequential.direction = 1,
  verbose = TRUE,
  raster = FALSE,
  raster.dpi = 300,
  plot_cell_borders = TRUE,
  border.size = 1.5,
  border.color = "black",
  pt.size = 2,
  min.cutoff = NA,
  max.cutoff = NA,
  na.value = "grey75",
  number.breaks = 5,
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

feature_to_rank

character | Feature for which the cells are going to be ranked. Ideal case is that this feature is stored as a metadata column.

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

assay

character | Assay to use. Defaults to the current assay.

reduction

character | Reduction to use. Can be the canonical ones such as "umap", "pca", or any custom ones, such as "diffusion". If you are unsure about which reductions you have, use Seurat::Reductions(sample). Defaults to "umap" if present or to the last computed reduction if the argument is not provided.

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

continuous_feature

logical | Is the feature to rank and color for continuous? I.e: an enrichment score.

order

logical | Whether to reorder the groups based on the median of the ranking.

colors.use

legend.title

character | Title for the legend.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

legend.ncol

numeric | Number of columns in the legend.

legend.icon.size

numeric | Size of the icons in legend.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

xlab, ylab

character | Titles for the X and Y axis.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

remove_x_axis, remove_y_axis

logical | Remove X axis labels and ticks from the plot.

flip

logical | Whether to invert the axis of the displayed plot.

use_viridis

logical | Whether to use viridis color scales.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

verbose

logical | Whether to show extra comments, warnings,etc.

raster

logical | Whether to raster the resulting plot. This is recommendable if plotting a lot of cells.

raster.dpi

numeric | Pixel resolution for rasterized plots. Defaults to 1024. Only activates on Seurat versions higher or equal than 4.1.0.

plot_cell_borders

logical | Whether to plot border around cells.

border.size

numeric | Width of the border of the cells.

border.color

character | Color for the border of the heatmap body.

pt.size

numeric | Size of the dots.

min.cutoff, max.cutoff

numeric | Set the min/max ends of the color scale. Any cell/group with a value lower than min.cutoff will turn into min.cutoff and any cell with a value higher than max.cutoff will turn into max.cutoff. In FeaturePlots, provide as many values as features. Use NAs to skip a feature.

na.value

character | Color value for NA.

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object containing a Bee Swarm plot.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_BeeSwarmPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Basic Bee Swarm plot - categorical coloring.
    # This will color based on the unique values of seurat_clusters.
    p <- SCpubr::do_BeeSwarmPlot(sample = sample,
                                 feature_to_rank = "PC_1",
                                 group.by = "seurat_clusters",
                                 continuous_feature = FALSE)

    # Basic Bee Swarm plot - continuous coloring.
    # This will color based on the PC_1 values.
    p <- SCpubr::do_BeeSwarmPlot(sample = sample,
                                 feature_to_rank = "PC_1",
                                 group.by = "seurat_clusters",
                                 continuous_feature = TRUE)
  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Generate Box Plots.

Description

Generate Box Plots.

Usage

do_BoxPlot(
  sample,
  feature,
  group.by = NULL,
  split.by = NULL,
  assay = NULL,
  slot = "data",
  font.size = 14,
  font.type = "sans",
  axis.text.x.angle = 45,
  colors.use = NULL,
  na.value = "grey75",
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  xlab = NULL,
  ylab = NULL,
  legend.title = NULL,
  legend.title.position = "top",
  legend.position = "bottom",
  boxplot.line.color = "black",
  outlier.color = "black",
  outlier.alpha = 0.5,
  boxplot.linewidth = 0.5,
  boxplot.width = NULL,
  plot.grid = TRUE,
  grid.color = "grey75",
  grid.type = "dashed",
  flip = FALSE,
  order = FALSE,
  use_silhouette = FALSE,
  use_test = FALSE,
  comparisons = NULL,
  test = "wilcox.test",
  map_signif_level = TRUE,
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

feature

character | Feature to represent.

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

split.by

character | Secondary metadata variable to further group (split) the output by. Has to be a character of factor column.

assay

character | Assay to use. Defaults to the current assay.

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

colors.use

na.value

character | Color value for NA.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

xlab, ylab

character | Titles for the X and Y axis.

legend.title

character | Title for the legend.

legend.title.position

character | Position for the title of the legend. One of:

top: Top of the legend.
bottom: Bottom of the legend.
left: Left of the legend.
right: Right of the legend.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

boxplot.line.color

character | Color of the borders of the boxplots if use_silhouette is FALSE.

outlier.color

character | Color of the outlier dots.

outlier.alpha

numeric | Alpha applied to the outliers.

boxplot.linewidth

numeric | Width of the lines in the boxplots. Also controls the lines of the tests applied if use_test is set to true.

boxplot.width

numeric | Width of the boxplots.

plot.grid

logical | Whether to plot grid lines.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

grid.type

character | One of the possible linetype options:

blank.
solid.
dashed.
dotted.
dotdash.
longdash.
twodash.

flip

logical | Whether to invert the axis of the displayed plot.

order

logical | Whether to order the boxplots by average values. Can not be used alongside split.by.

use_silhouette

logical | Whether to color the borders of the boxplots instead of the inside area.

use_test

logical | Whether to apply a statistical test to a given pair of elements. Can not be used alongside split.by.

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 columns of interest.

test

the name of the statistical test that is applied to the values of the 2 columns (e.g. t.test, wilcox.test etc.). If you implement a custom test make sure that it returns a list that has an entry called p.value.

map_signif_level

Boolean value, if the p-value are directly written as annotation or asterisks are used instead. Alternatively one can provide a named numeric vector to create custom mappings from p-values to annotation: For example: c("***"=0.001, "**"=0.01, "*"=0.05). Alternatively, one can provide a function that takes a numeric argument (the p-value) and returns a string.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_BoxPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Basic box plot.
    p <- SCpubr::do_BoxPlot(sample = sample,
                            feature = "nCount_RNA")
    p

    # Use silhouette style.
    p <- SCpubr::do_BoxPlot(sample = sample,
                            feature = "nCount_RNA",
                            use_silhouette = TRUE)
    p

    # Order by mean values.
    p <- SCpubr::do_BoxPlot(sample = sample,
                            feature = "nCount_RNA",
                            order = TRUE)
    p

    # Apply second grouping.
    sample$orig.ident <- ifelse(sample$seurat_clusters %in% c("0", "1", "2", "3"), "A", "B")
    p <- SCpubr::do_BoxPlot(sample = sample,
                            feature = "nCount_RNA",
                            split.by = "orig.ident")
    p

    # Apply statistical tests.
    p <- SCpubr::do_BoxPlot(sample = sample,
                            feature = "nCount_RNA",
                            group.by = "orig.ident",
                            use_test = TRUE,
                            comparisons = list(c("A", "B")))
    p

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Cellular States plot.

Description

This plot aims to show the relationships between distinct enrichment scores. If 3 variables are provided, the relationship is between the Y axis and the dual X axis. If 4 variables are provided, each corner of the plot represents how enriched the cells are in that given list. How to interpret this? In a 3-variable plot, the Y axis just means one variable. The higher the cells are in the Y axis the more enriched they are in that given variable. The X axis is a dual parameter one. Cells falling into each extreme of the axis are highly enriched for either x1 or x2, while cells falling in between are not enriched for any of the two. In a 4-variable plot, each corner shows the enrichment for one of the 4 given features. Cells will tend to locate in either of the four corners, but there will be cases of cells locating mid-way between two given corners (enriched in both features) or in the middle of the plot (not enriched for any).

Usage

do_CellularStatesPlot(
  sample,
  input_gene_list,
  x1,
  y1,
  x2 = NULL,
  y2 = NULL,
  group.by = NULL,
  colors.use = NULL,
  legend.position = "bottom",
  legend.icon.size = 4,
  legend.ncol = NULL,
  legend.nrow = NULL,
  legend.byrow = FALSE,
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  font.size = 14,
  font.type = "sans",
  xlab = NULL,
  ylab = NULL,
  axis.ticks = TRUE,
  axis.text = TRUE,
  verbose = FALSE,
  enforce_symmetry = FALSE,
  plot_marginal_distributions = FALSE,
  marginal.type = "density",
  marginal.size = 5,
  marginal.group = TRUE,
  plot_cell_borders = TRUE,
  plot_enrichment_scores = FALSE,
  border.size = 2,
  border.color = "black",
  pt.size = 2,
  raster = FALSE,
  raster.dpi = 1024,
  plot_features = FALSE,
  features = NULL,
  use_viridis = TRUE,
  viridis.palette = "G",
  viridis.direction = 1,
  sequential.palette = "YlGnBu",
  sequential.direction = -1,
  nbin = 24,
  ctrl = 100,
  number.breaks = 5,
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

input_gene_list

named_list | Named list of lists of genes to be used as input.

x1

character | A name of a list from input_gene_list. First feature in the X axis. Will go on the right side of the X axis if y2 is not provided and top-right quadrant if provided.

y1

character | A name of a list from input_gene_list. First feature on the Y axis. Will become the Y axis if y2 is not provided and bottom-right quadrant if provided.

x2

character | A name of a list from input_gene_list. Second feature on the X axis. Will go on the left side of the X axis if y2 is not provided and top-left quadrant if provided.

y2

character | A name of a list from input_gene_list. Second feature on the Y axis. Will become the bottom-left quadrant if provided.

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

colors.use

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.icon.size

numeric | Size of the icons in legend.

legend.ncol

numeric | Number of columns in the legend.

legend.nrow

numeric | Number of rows in the legend.

legend.byrow

logical | Whether the legend is filled by row or not.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

xlab, ylab

character | Titles for the X and Y axis.

axis.ticks

logical | Whether to show axis ticks.

axis.text

logical | Whether to show axis text.

verbose

logical | Whether to show extra comments, warnings,etc.

enforce_symmetry

logical | Whether to enforce the plot to follow a symmetry (3 variables, the X axis has 0 as center, 4 variables, all axis have the same range and the plot is squared).

plot_marginal_distributions

logical | Whether to plot marginal distributions on the figure or not.

marginal.type

character | One of:

density: Compute density plots on the margins.
histogram: Compute histograms on the margins.
boxplot: Compute boxplot on the margins.
violin: Compute violin plots on the margins.
densigram: Compute densigram plots on the margins.

marginal.size

numeric | Size ratio between the main and marginal plots. A value of 5 means that the main plot is 5 times bigger than the marginal plots.

marginal.group

logical | Whether to group the marginal distribution by group.by or current identities.

plot_cell_borders

logical | Whether to plot border around cells.

plot_enrichment_scores

logical | Whether to report enrichment scores for the input lists as plots.

border.size

numeric | Width of the border of the cells.

border.color

character | Color for the border of the heatmap body.

pt.size

numeric | Size of the dots.

raster

logical | Whether to raster the resulting plot. This is recommendable if plotting a lot of cells.

raster.dpi

numeric | Pixel resolution for rasterized plots. Defaults to 1024. Only activates on Seurat versions higher or equal than 4.1.0.

plot_features

logical | Whether to also report any other feature onto the primary plot.

features

character | Additional features to plot.

use_viridis

logical | Whether to use viridis color scales.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

nbin

numeric | Number of bins to use in AddModuleScore.

ctrl

numeric | Number of genes in the control set to use in AddModuleScore.

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Details

This plots are based on the following publications:

Neftel, C. et al. An Integrative Model of Cellular States, Plasticity, and Genetics for Glioblastoma. Cell 178, 835-849.e21 (2019). doi:10.1016/j.cell.2019.06.024
Tirosh, I., Venteicher, A., Hebert, C. et al. Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma. Nature 539, 309–313 (2016). doi:10.1038/nature20123

Value

A ggplot2 object containing a butterfly plot.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_CellularStatesPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Define some gene sets to query. It has to be a named list.
    gene_set <- list("A" = rownames(sample)[1:10],
                     "B" = rownames(sample)[11:20],
                     "C" = rownames(sample)[21:30],
                     "D" = rownames(sample)[31:40])

    # Using two variables: A scatter plot X vs Y.
    p <- SCpubr::do_CellularStatesPlot(sample = sample,
                                       input_gene_list = gene_set,
                                       x1 = "A",
                                       y1 = "B",
                                       nbin = 1,
                                       ctrl = 10)
    p


    # Using three variables. Figure from: https://www.nature.com/articles/nature20123.
    p <- SCpubr::do_CellularStatesPlot(sample = sample,
                                       input_gene_list = gene_set,
                                       x1 = "A",
                                       y1 = "B",
                                       x2 = "C",
                                       nbin = 1,
                                       ctrl = 10)
    p


    # Using four variables. Figure from: https://pubmed.ncbi.nlm.nih.gov/31327527/
    p <- SCpubr::do_CellularStatesPlot(sample = sample,
                                       input_gene_list = gene_set,
                                       x1 = "A",
                                       y1 = "C",
                                       x2 = "B",
                                       y2 = "D",
                                       nbin = 1,
                                       ctrl = 10)
    p
  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Generate a Chord diagram.

Description

Generate a Chord diagram.

Usage

do_ChordDiagramPlot(
  sample = NULL,
  from = NULL,
  to = NULL,
  colors.from = NULL,
  colors.to = NULL,
  big.gap = 10,
  small.gap = 1,
  link.border.color = NA,
  link.border.width = 1,
  highlight_group = NULL,
  alpha.highlight = 25,
  link.sort = NULL,
  link.decreasing = TRUE,
  z_index = FALSE,
  self.link = 1,
  symmetric = FALSE,
  directional = 1,
  direction.type = c("diffHeight", "arrows"),
  link.arr.type = "big.arrow",
  scale = FALSE,
  alignment = "default",
  annotationTrack = c("grid", "axis"),
  padding_labels = 4,
  ...
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

from, to

character | Categorical metadata variable to be used as origin and end points of the interactions.

colors.from, colors.to

named_vector | Named vector of colors corresponding to the unique values of "from" and "to".

big.gap

numeric | Space between the groups in "from" and "to".

small.gap

numeric | Space within the groups.

link.border.color

character | Color for the border of the links. NA = no color.

link.border.width

numeric | Width of the border line of the links.

highlight_group

character | A value from from that will be used to highlight only the links coming from it.

alpha.highlight

numeric | A value between 00 (double digits) and 99 to depict the alpha of the highlighted links. No transparency needs "FF"

link.sort

pass to chordDiagramFromMatrix or chordDiagramFromDataFrame

link.decreasing

pass to chordDiagramFromMatrix or chordDiagramFromDataFrame

z_index

logical | Whether to bring the bigger links to the top.

self.link

numeric | Behavior of the links. One of:

1: Prevents self linking.
2: Allows self linking.

symmetric

pass to chordDiagramFromMatrix

directional

numeric | Set the direction of the links. One of:

0: Non-directional data.
1: Links go from "from" to "to".
-1: Links go from "to" to "from".
2: Links go in both directions.

direction.type

character | How to display the directions. One of:

diffHeight: Sets a line at the origin of the group showing to how many groups and in which proportion this group is linked to.
arrows: Sets the connection as arrows.
both: Sets up both behaviors. Use as: c("diffHeight", "arrows").

link.arr.type

character | Sets the appearance of the arrows. One of:

triangle: Arrow with a triangle tip at the end displayed on top of the link.
big.arrow: The link itself ends in a triangle shape.

scale

logical | Whether to put all nodes the same width.

alignment

character | How to align the diagram. One of:

default: Allows circlize to set up the plot as it sees fit.
horizontal: Sets the break between "from" and "to" groups on the horizontal axis.
vertical: Sets the break between "from" and "to" groups on the vertical axis.

annotationTrack

pass to chordDiagramFromMatrix or chordDiagramFromDataFrame

padding_labels

numeric | Number of extra padding (white spaces) of the labels so that they do not overlap with the scales.

...

For internal use only.

Value

A circlize plot.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_ChordDiagramPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Basic chord diagram.
    sample$assignment <- ifelse(sample$seurat_clusters %in% c("0", "4", "7"), "A", "B")
    sample$assignment[sample$seurat_clusters %in% c("1", "2")] <- "C"
    sample$assignment[sample$seurat_clusters %in% c("10", "5")] <- "D"
    sample$assignment[sample$seurat_clusters %in% c("8", "9")] <- "E"

    p <- SCpubr::do_ChordDiagramPlot(sample = sample,
                                     from = "seurat_clusters",
                                     to = "assignment")

    p

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Generate color scales based on a value.

Description

This function is an adaptation of colortools package. As the package was removed from CRAN on 23-06-2022, this utility function came to existence in order to cover the gap. It is, on its basis, an adaptation of the package into a single function. Original code, developed by Gaston Sanchez, can be found in: https://github.com/gastonstat/colortools

Usage

do_ColorPalette(
  colors.use,
  n = 12,
  opposite = FALSE,
  adjacent = FALSE,
  triadic = FALSE,
  split_complementary = FALSE,
  tetradic = FALSE,
  square = FALSE,
  complete_output = FALSE,
  plot = FALSE,
  font.size = 14,
  font.type = "sans"
)

Arguments

colors.use

character | One color upon which generate the color scale. Can be a name or a HEX code.

n

numeric | Number of colors to include in the color wheel. Use it when all other options are FALSE, otherwise, it becomes 12.

opposite

logical | Return the opposing color to the one provided.

adjacent

logical | Return the adjacent colors to the one provided.

triadic

logical | Return the triadic combination of colors to the one provided.

split_complementary

logical | Return the split complementary combination of colors to the one provided.

tetradic

logical | Return the tetradic combination of colors to the one provided.

square

logical | Return the square combination of colors to the one provided.

complete_output

logical | Runs all the previous options and returns all the outputs as a list that contains all color vectors, all plots and a combined plot with everything.

plot

logical | Whether to also return a plot displaying the values instead of a vector with the color.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

Value

A character vector with the desired color scale.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_ColorPalette", passive = TRUE)
  
  if (isTRUE(value)){
    # Generate a color wheel based on a single value.
    colors <- SCpubr::do_ColorPalette(colors.use = "steelblue")
    p <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                 plot = TRUE)
  
    # Generate a pair of opposite colors based on a given one.
    colors <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                      opposite = TRUE)
    p <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                 opposite = TRUE,
                                 plot = TRUE)
  
    # Generate a trio of adjacent colors based on a given one.
    colors <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                      adjacent = TRUE)
    p <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                 adjacent = TRUE,
                                 plot = TRUE)
  
    # Generate a trio of triadic colors based on a given one.
    colors <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                      triadic = TRUE)
    p <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                 triadic = TRUE,
                                 plot = TRUE)
  
    # Generate a trio of split complementary colors based on a given one.
    colors <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                      split_complementary = TRUE)
    p <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                 split_complementary = TRUE,
                                 plot = TRUE)
  
    # Generate a group of tetradic colors based on a given one.
    colors <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                      tetradic = TRUE)
    p <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                 tetradic = TRUE,
                                 plot = TRUE)
  
    # Generate a group of square colors based on a given one.
    colors <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                      square = TRUE)
    p <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                 square = TRUE,
                                 plot = TRUE)
  
    # Retrieve the output of all options.
    out <- SCpubr::do_ColorPalette(colors.use = "steelblue",
                                   complete_output = TRUE)
    ## Retrieve the colors.
    colors <- out$colors
    ## Retrieve the plots.
    plots <- out$plots
    ## Retrieve a combined plot with all the options.
    p <- out$combined_plot
  
  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Display CNV scores from inferCNV as Feature Plots.

Description

Display CNV scores from inferCNV as Feature Plots.

Usage

do_CopyNumberVariantPlot(
  sample,
  infercnv_object,
  chromosome_locations,
  group.by = NULL,
  using_metacells = FALSE,
  metacell_mapping = NULL,
  legend.type = "colorbar",
  legend.position = "bottom",
  legend.length = 20,
  legend.width = 1,
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  font.size = 14,
  pt.size = 1,
  font.type = "sans",
  axis.text.x.angle = 45,
  enforce_symmetry = TRUE,
  legend.title = NULL,
  na.value = "grey75",
  viridis.palette = "G",
  viridis.direction = 1,
  verbose = FALSE,
  min.cutoff = NA,
  max.cutoff = NA,
  number.breaks = 5,
  diverging.palette = "RdBu",
  diverging.direction = -1,
  sequential.palette = "YlGnBu",
  sequential.direction = -1,
  use_viridis = TRUE,
  return_object = FALSE,
  grid.color = "white",
  border.color = "black",
  flip = FALSE,
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

infercnv_object

infercnv | Output inferCNV object run on the same Seurat object.

chromosome_locations

tibble | Tibble containing the chromosome regions to use. Can be obtained using utils::data("human_chr_locations", package = "SCpubr").

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

using_metacells

logical | Whether inferCNV was run using metacells or not.

metacell_mapping

named_vector | Vector or cell - metacell mapping.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

pt.size

numeric | Size of the dots.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

enforce_symmetry

logical | Return a symmetrical plot axes-wise or continuous color scale-wise, when applicable.

legend.title

character | Title for the legend.

na.value

character | Color value for NA.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

verbose

logical | Whether to show extra comments, warnings,etc.

min.cutoff, max.cutoff

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

diverging.palette

character | Type of symmetrical color palette to use. Out of the diverging palettes defined in brewer.pal.

diverging.direction

numeric | Either 1 or -1. Direction of the divering palette. This basically flips the two ends.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

use_viridis

logical | Whether to use viridis color scales.

return_object

logical | Returns the Seurat object with the modifications performed in the function. Nomally, this contains a new assay with the data that can then be used for any other visualization desired.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

border.color

character | Color for the border of the heatmap body.

flip

logical | Whether to invert the axis of the displayed plot.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A list containing Feature Plots for different chromosome regions and corresponding dot plots by groups..

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_CopyNumberVariantPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # This function expects that you have run inferCNV on your
    # own and you have access to the output object.

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds",
                                  package = "SCpubr"))

    # Define your inferCNV object.
    infercnv_object <- readRDS(system.file("extdata/infercnv_object_example.rds",
                                           package = "SCpubr"))

    # Get human chromosome locations.
    chromosome_locations = SCpubr::human_chr_locations

    # Compute for a all chromosomes.
    p <- SCpubr::do_CopyNumberVariantPlot(sample = sample,
                                          infercnv_object = infercnv_object,
                                          using_metacells = FALSE,
                                          chromosome_locations = chromosome_locations)

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Create correlation matrix heatmaps.

Description

Create correlation matrix heatmaps.

Usage

do_CorrelationPlot(
  sample = NULL,
  input_gene_list = NULL,
  cluster = TRUE,
  remove.diagonal = TRUE,
  mode = "hvg",
  assay = NULL,
  group.by = NULL,
  legend.title = "Pearson coef.",
  enforce_symmetry = ifelse(mode == "hvg", TRUE, FALSE),
  font.size = 14,
  font.type = "sans",
  na.value = "grey75",
  legend.width = 1,
  legend.length = 20,
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  legend.type = "colorbar",
  legend.position = "bottom",
  min.cutoff = NA,
  max.cutoff = NA,
  number.breaks = 5,
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  diverging.palette = "RdBu",
  diverging.direction = -1,
  use_viridis = FALSE,
  viridis.palette = "G",
  viridis.direction = -1,
  sequential.palette = "YlGnBu",
  sequential.direction = 1,
  axis.text.x.angle = 45,
  grid.color = "white",
  border.color = "black",
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

input_gene_list

named_list | Named list of lists of genes to be used as input.

cluster

logical | Whether to cluster the elements in the heatmap or not.

remove.diagonal

logical | Whether to convert diagnoal to NA. Normally this value would be 1, heavily shifting the color scale.

mode

character | Different types of correlation matrices can be computed. Right now, the only possible value is "hvg", standing for Highly Variable Genes. The sample is subset for the HVG and the data is re-scaled. Scale data is used for the correlation.

assay

character | Assay to use. Defaults to the current assay.

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

legend.title

character | Title for the legend.

enforce_symmetry

logical | Return a symmetrical plot axes-wise or continuous color scale-wise, when applicable.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

na.value

character | Color value for NA.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

min.cutoff, max.cutoff

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

diverging.palette

character | Type of symmetrical color palette to use. Out of the diverging palettes defined in brewer.pal.

diverging.direction

numeric | Either 1 or -1. Direction of the divering palette. This basically flips the two ends.

use_viridis

logical | Whether to use viridis color scales.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

border.color

character | Color for the border of the heatmap body.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_CorrelationPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Default values.
    p <- SCpubr::do_CorrelationPlot(sample = sample)
    p

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Wrapper for DimPlot.

Description

Wrapper for DimPlot.

Usage

do_DimPlot(
  sample,
  reduction = NULL,
  group.by = NULL,
  split.by = NULL,
  colors.use = NULL,
  shuffle = TRUE,
  order = NULL,
  raster = FALSE,
  pt.size = 1,
  label = FALSE,
  label.color = "black",
  label.fill = "white",
  label.size = 4,
  label.box = TRUE,
  repel = FALSE,
  cells.highlight = NULL,
  idents.highlight = NULL,
  idents.keep = NULL,
  sizes.highlight = 1,
  ncol = NULL,
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  legend.title = NULL,
  legend.position = "bottom",
  legend.title.position = "top",
  legend.ncol = NULL,
  legend.nrow = NULL,
  legend.icon.size = 4,
  legend.byrow = FALSE,
  raster.dpi = 2048,
  dims = c(1, 2),
  font.size = 14,
  font.type = "sans",
  na.value = "grey75",
  plot_cell_borders = TRUE,
  border.size = 2,
  border.color = "black",
  border.density = 1,
  plot_marginal_distributions = FALSE,
  marginal.type = "density",
  marginal.size = 5,
  marginal.group = TRUE,
  plot.axes = FALSE,
  plot_density_contour = FALSE,
  contour.position = "bottom",
  contour.color = "grey90",
  contour.lineend = "butt",
  contour.linejoin = "round",
  contour_expand_axes = 0.25,
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

reduction

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

split.by

character | Secondary metadata variable to further group (split) the output by. Has to be a character of factor column.

colors.use

shuffle

logical | Whether to shuffle the cells or not, so that they are not plotted cluster-wise. Recommended.

order

character | Vector of identities to be plotted. Either one with all identities or just some, which will be plotted last.

raster

logical | Whether to raster the resulting plot. This is recommendable if plotting a lot of cells.

pt.size

numeric | Size of the dots.

label

logical | Whether to plot the cluster labels in the UMAP. The cluster labels will have the same color as the cluster colors.

label.color

character | Color of the labels in the plot.

label.fill

character | Color to fill the labels. Has to be a single color, that will be used for all labels. If NULL, the colors of the clusters will be used instead.

label.size

numeric | Size of the labels in the plot.

label.box

logical | Whether to plot the plot labels as geom_text (FALSE) or geom_label (TRUE).

repel

logical | Whether to repel the text labels.

cells.highlight, idents.highlight

character | Vector of cells/identities to focus into. The identities have to much those in Seurat::Idents(sample) The rest of the cells will be grayed out. Both parameters can be used at the same time.

idents.keep

character | Vector of identities to keep. This will effectively set the rest of the cells that do not match the identities provided to NA, therefore coloring them according to na.value parameter.

sizes.highlight

numeric | Point size of highlighted cells using cells.highlight parameter.

ncol

numeric | Number of columns used in the arrangement of the output plot using "split.by" parameter.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

legend.title

character | Title for the legend.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.title.position

character | Position for the title of the legend. One of:

top: Top of the legend.
bottom: Bottom of the legend.
left: Left of the legend.
right: Right of the legend.

legend.ncol

numeric | Number of columns in the legend.

legend.nrow

numeric | Number of rows in the legend.

legend.icon.size

numeric | Size of the icons in legend.

legend.byrow

logical | Whether the legend is filled by row or not.

raster.dpi

numeric | Pixel resolution for rasterized plots. Defaults to 1024. Only activates on Seurat versions higher or equal than 4.1.0.

dims

numeric | Vector of 2 numerics indicating the dimensions to plot out of the selected reduction. Defaults to c(1, 2) if not specified.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

na.value

character | Color value for NA.

plot_cell_borders

logical | Whether to plot border around cells.

border.size

numeric | Width of the border of the cells.

border.color

character | Color for the border of the heatmap body.

border.density

numeric | Controls the number of cells used when plot_cell_borders = TRUE. Value between 0 and 1. It computes a 2D kernel density and based on this cells that have a density below the specified quantile will be used to generate the cluster contour. The lower this number, the less cells will be selected, thus reducing the overall size of the plot but also potentially preventing all the contours to be properly drawn.

plot_marginal_distributions

logical | Whether to plot marginal distributions on the figure or not.

marginal.type

character | One of:

density: Compute density plots on the margins.
histogram: Compute histograms on the margins.
boxplot: Compute boxplot on the margins.
violin: Compute violin plots on the margins.
densigram: Compute densigram plots on the margins.

marginal.size

numeric | Size ratio between the main and marginal plots. A value of 5 means that the main plot is 5 times bigger than the marginal plots.

marginal.group

logical | Whether to group the marginal distribution by group.by or current identities.

plot.axes

logical | Whether to plot axes or not.

plot_density_contour

logical | Whether to plot density contours in the UMAP.

contour.position

character | Whether to plot density contours on top or at the bottom of the visualization layers, thus overlapping the clusters/cells or not.

contour.color

character | Color of the density lines.

contour.lineend

character | Line end style (round, butt, square).

contour.linejoin

character | Line join style (round, mitre, bevel).

contour_expand_axes

numeric | To make the contours fit the plot, the limits of the X and Y axis are expanding a given percentage from the min and max values for each axis. This controls such percentage.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object containing a DimPlot.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_DimPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Basic DimPlot.
    p <- SCpubr::do_DimPlot(sample = sample)


    # Restrict the amount of identities displayed.
    p <- SCpubr::do_DimPlot(sample = sample,
                            idents.keep = c("1", "3", "5"))

    # Group by another variable rather than `Seurat::Idents(sample)`
    p <- SCpubr::do_DimPlot(sample = sample,
                            group.by = "seurat_clusters")

    # Split the output in as many plots as unique identities.
    p <- SCpubr::do_DimPlot(sample = sample,
                            split.by = "seurat_clusters")

    # Highlight given identities
    p <- SCpubr::do_DimPlot(sample,
                            idents.highlight = c("1", "3"))

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

This function is a wrapper for DotPlot. It provides most of its functionalities while adding extra. You can

Description

This function is a wrapper for DotPlot. It provides most of its functionalities while adding extra. You can

Usage

do_DotPlot(
  sample,
  features,
  assay = NULL,
  group.by = NULL,
  scale = FALSE,
  legend.title = NULL,
  legend.type = "colorbar",
  legend.position = "bottom",
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.length = 20,
  legend.width = 1,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  colors.use = NULL,
  dot.scale = 6,
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  xlab = NULL,
  ylab = NULL,
  font.size = 14,
  font.type = "sans",
  cluster = FALSE,
  flip = FALSE,
  axis.text.x.angle = 45,
  scale.by = "size",
  use_viridis = FALSE,
  viridis.palette = "G",
  viridis.direction = -1,
  sequential.palette = "YlGnBu",
  sequential.direction = 1,
  na.value = "grey75",
  dot_border = TRUE,
  plot.grid = TRUE,
  grid.color = "grey75",
  grid.type = "dashed",
  number.breaks = 5,
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

features

character | Features to represent.

assay

character | Assay to use. Defaults to the current assay.

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

scale

logical | Whether the data should be scaled or not. Non-scaled data allows for comparison across genes. Scaled data allows for an easier comparison along the same gene.

legend.title

character | Title for the legend.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

colors.use

dot.scale

numeric | Scale the size of the dots.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

xlab, ylab

character | Titles for the X and Y axis.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

cluster

logical | Whether to cluster the identities based on the expression of the features.

flip

logical | Whether to invert the axis of the displayed plot.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

scale.by

character | How to scale the size of the dots. One of:

radius: use radius aesthetic.
size: use size aesthetic.

use_viridis

logical | Whether to use viridis color scales.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

na.value

character | Color value for NA.

dot_border

logical | Whether to plot a border around dots.

plot.grid

logical | Whether to plot grid lines.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

grid.type

character | One of the possible linetype options:

blank.
solid.
dashed.
dotted.
dotdash.
longdash.
twodash.

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object containing a Dot Plot.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_DotPlot", passive = TRUE)

  if (isTRUE(value)){
    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Basic Dot plot.
    p <- SCpubr::do_DotPlot(sample = sample,
                            features = "EPC1")

    # Querying multiple features.
    genes <- rownames(sample)[1:14]
    p <- SCpubr::do_DotPlot(sample = sample,
                            features = genes)

    # Inverting the axes.
    p <- SCpubr::do_DotPlot(sample = sample,
                            features = genes,
                            cluster = TRUE,
                            plot.title = "Clustered",
                            flip = TRUE)

    # Modifying default colors.
    # Two colors to generate a gradient.
    p <- SCpubr::do_DotPlot(sample = sample,
                            features = genes,
                            colors.use = c("#001219", "#e9d8a6"))

    # Querying multiple features as a named list - splitting by each item in list.
    # Genes have to be unique.
    genes <- list("Naive CD4+ T" = rownames(sample)[1:2],
                  "EPC1+ Mono" = rownames(sample)[3:4],
                  "Memory CD4+" = rownames(sample)[5],
                  "B" = rownames(sample)[6],
                  "CD8+ T" = rownames(sample)[7],
                  "FCGR3A+ Mono" = rownames(sample)[8:9],
                  "NK" = rownames(sample)[10:11],
                  "DC" = rownames(sample)[12:13],
                  "Platelet" = rownames(sample)[14])

    p <- SCpubr::do_DotPlot(sample = sample,
                            features = genes)

    # Clustering the identities.
    p <- SCpubr::do_DotPlot(sample = sample,
                            features = genes,
                            cluster = TRUE,
                            plot.title = "Clustered")
  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Create enrichment scores heatmaps.

Description

This function computes the enrichment scores for the cells using AddModuleScore and then aggregates the scores by the metadata variables provided by the user and displays it as a heatmap, computed by Heatmap.

Usage

do_EnrichmentHeatmap(
  sample,
  input_gene_list,
  features.order = NULL,
  groups.order = NULL,
  cluster = TRUE,
  scale_scores = TRUE,
  assay = NULL,
  slot = NULL,
  reduction = NULL,
  group.by = NULL,
  verbose = FALSE,
  na.value = "grey75",
  legend.position = "bottom",
  use_viridis = FALSE,
  viridis.palette = "G",
  viridis.direction = 1,
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.length = 20,
  legend.width = 1,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  legend.type = "colorbar",
  font.size = 14,
  font.type = "sans",
  axis.text.x.angle = 45,
  enforce_symmetry = FALSE,
  nbin = 24,
  ctrl = 100,
  flavor = "Seurat",
  legend.title = NULL,
  ncores = 1,
  storeRanks = TRUE,
  min.cutoff = NA,
  max.cutoff = NA,
  pt.size = 1,
  plot_cell_borders = TRUE,
  border.size = 2,
  return_object = FALSE,
  number.breaks = 5,
  sequential.palette = "YlGnBu",
  diverging.palette = "RdBu",
  diverging.direction = -1,
  sequential.direction = 1,
  flip = FALSE,
  grid.color = "white",
  border.color = "black",
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

input_gene_list

named_list | Named list of lists of genes to be used as input.

features.order

character | Should the gene sets be ordered in a specific way? Provide it as a vector of characters with the same names as the names of the gene sets.

groups.order

named_list | Should the groups in theheatmaps be ordered in a specific way? Provide it as a named list (as many lists as values in group.by) with the order for each of the elements in the groups.

cluster

logical | Whether to perform clustering of rows and columns.

scale_scores

logical | Whether to transform the scores to a range of 0-1 for plotting.

assay

character | Assay to use. Defaults to the current assay.

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

reduction

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

verbose

logical | Whether to show extra comments, warnings,etc.

na.value

character | Color value for NA.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

use_viridis

logical | Whether to use viridis color scales.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

enforce_symmetry

logical | Whether the geyser and feature plot has a symmetrical color scale.

nbin

numeric | Number of bins to use in AddModuleScore.

ctrl

numeric | Number of genes in the control set to use in AddModuleScore.

flavor

character | One of: Seurat, UCell. Compute the enrichment scores using AddModuleScore or AddModuleScore_UCell.

legend.title

character | Title for the legend.

ncores

numeric | Number of cores used to run UCell scoring.

storeRanks

logical | Whether to store the ranks for faster UCell scoring computations. Might require large amounts of RAM.

min.cutoff, max.cutoff

pt.size

numeric | Size of the dots.

plot_cell_borders

logical | Whether to plot border around cells.

border.size

numeric | Width of the border of the cells.

return_object

logical | Return the Seurat object with the enrichment scores stored.

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

diverging.palette

character | Type of symmetrical color palette to use. Out of the diverging palettes defined in brewer.pal.

diverging.direction

numeric | Either 1 or -1. Direction of the divering palette. This basically flips the two ends.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

flip

logical | Whether to invert the axis of the displayed plot.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

border.color

character | Color for the border of the heatmap body.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_EnrichmentHeatmap", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Genes have to be unique.
    genes <- list("A" = rownames(sample)[1:5],
                  "B" = rownames(sample)[6:10],
                  "C" = rownames(sample)[11:15])

    # Default parameters.
    p <- SCpubr::do_EnrichmentHeatmap(sample = sample,
                                      input_gene_list = genes,
                                      nbin = 1,
                                      ctrl = 10)
    p

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Create heatmaps of averaged expression by groups.

Description

This function generates a heatmap with averaged expression values by the unique groups of the metadata variables provided by the user.

Usage

do_ExpressionHeatmap(
  sample,
  features,
  group.by = NULL,
  assay = NULL,
  cluster = TRUE,
  features.order = NULL,
  groups.order = NULL,
  slot = "data",
  legend.title = "Avg. Expression",
  na.value = "grey75",
  legend.position = "bottom",
  legend.width = 1,
  legend.length = 20,
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  legend.type = "colorbar",
  font.size = 14,
  font.type = "sans",
  axis.text.x.angle = 45,
  enforce_symmetry = FALSE,
  min.cutoff = NA,
  max.cutoff = NA,
  diverging.palette = "RdBu",
  diverging.direction = -1,
  sequential.palette = "YlGnBu",
  sequential.direction = 1,
  number.breaks = 5,
  use_viridis = FALSE,
  viridis.palette = "G",
  viridis.direction = -1,
  flip = FALSE,
  grid.color = "white",
  border.color = "black",
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

features

character | Features to represent.

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

assay

character | Assay to use. Defaults to the current assay.

cluster

logical | Whether to perform clustering of rows and columns.

features.order

character | Should the gene sets be ordered in a specific way? Provide it as a vector of characters with the same names as the names of the gene sets.

groups.order

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

legend.title

character | Title for the legend.

na.value

character | Color value for NA.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

enforce_symmetry

logical | Return a symmetrical plot axes-wise or continuous color scale-wise, when applicable.

min.cutoff, max.cutoff

diverging.palette

character | Type of symmetrical color palette to use. Out of the diverging palettes defined in brewer.pal.

diverging.direction

numeric | Either 1 or -1. Direction of the divering palette. This basically flips the two ends.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

use_viridis

logical | Whether to use viridis color scales.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

flip

logical | Whether to invert the axis of the displayed plot.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

border.color

character | Color for the border of the heatmap body.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_ExpressionHeatmap", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Define list of genes.
    genes <- rownames(sample)[1:10]

    # Default parameters.
    p <- SCpubr::do_ExpressionHeatmap(sample = sample,
                                      features = genes,
                                      viridis.direction = -1)
    
    p
  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Wrapper for FeaturePlot.

Description

Wrapper for FeaturePlot.

Usage

do_FeaturePlot(
  sample,
  features,
  assay = NULL,
  reduction = NULL,
  slot = NULL,
  order = FALSE,
  group.by = NULL,
  group.by.colors.use = NULL,
  group.by.legend = NULL,
  group.by.show.dots = TRUE,
  group.by.dot.size = 8,
  group.by.cell_borders = FALSE,
  group.by.cell_borders.alpha = 0.1,
  split.by = NULL,
  idents.keep = NULL,
  cells.highlight = NULL,
  idents.highlight = NULL,
  dims = c(1, 2),
  enforce_symmetry = FALSE,
  symmetry.type = "absolute",
  symmetry.center = NA,
  pt.size = 1,
  font.size = 14,
  font.type = "sans",
  legend.title = NULL,
  legend.type = "colorbar",
  legend.position = "bottom",
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.length = 20,
  legend.width = 1,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  legend.ncol = NULL,
  legend.nrow = NULL,
  legend.byrow = FALSE,
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  individual.titles = NULL,
  individual.subtitles = NULL,
  individual.captions = NULL,
  ncol = NULL,
  use_viridis = FALSE,
  viridis.palette = "G",
  viridis.direction = 1,
  raster = FALSE,
  raster.dpi = 1024,
  plot_cell_borders = TRUE,
  border.size = 2,
  border.color = "black",
  border.density = 1,
  na.value = "grey75",
  verbose = TRUE,
  plot.axes = FALSE,
  min.cutoff = rep(NA, length(features)),
  max.cutoff = rep(NA, length(features)),
  plot_density_contour = FALSE,
  contour.position = "bottom",
  contour.color = "grey90",
  contour.lineend = "butt",
  contour.linejoin = "round",
  contour_expand_axes = 0.25,
  label = FALSE,
  label.color = "black",
  label.size = 4,
  number.breaks = 5,
  diverging.palette = "RdBu",
  diverging.direction = -1,
  sequential.palette = "YlGnBu",
  sequential.direction = 1,
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

features

character | Features to represent.

assay

character | Assay to use. Defaults to the current assay.

reduction

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

order

logical | Whether to order the cells based on expression.

group.by

character | Metadata variable based on which cells are grouped. This will effectively introduce a big dot in the center of each cluster, colored using a categorical color scale or with the values provided by the user in group.by.colors.use. It will also displays a legend.

group.by.colors.use

character | Colors to use for the group dots.

group.by.legend

character | Title for the legend when group.by is used. Use NA to disable it and NULL to use the default column title provided in group.by.

group.by.show.dots

logical | Controls whether to place in the middle of the groups.

group.by.dot.size

numeric | Size of the dots placed in the middle of the groups.

group.by.cell_borders

logical | Plots another border around the cells displaying the same color code of the dots displayed with group.by. Legend is shown always with alpha = 1 regardless of the alpha settings.

group.by.cell_borders.alpha

numeric | Controls the transparency of the new borders drawn by group.by.cell_borders.

split.by

character | Secondary metadata variable to further group (split) the output by. Has to be a character of factor column.

idents.keep

character | Vector of identities to plot. The gradient scale will also be subset to only the values of such identities.

cells.highlight, idents.highlight

dims

numeric | Vector of 2 numerics indicating the dimensions to plot out of the selected reduction. Defaults to c(1, 2) if not specified.

enforce_symmetry

logical | Return a symmetrical plot axes-wise or continuous color scale-wise, when applicable.

symmetry.type

character | Type of symmetry to be enforced. One of:

absolute: The highest absolute value will be taken into a account to generate the color scale. Works after min.cutoff and max.cutoff.
centered: Centers the scale around the provided value in symmetry.center. Works after min.cutoff and max.cutoff.

symmetry.center

numeric | Value upon which the scale will be centered.

pt.size

numeric | Size of the dots.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

legend.title

character | Title for the legend.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

legend.ncol

numeric | Number of columns in the legend.

legend.nrow

numeric | Number of rows in the legend.

legend.byrow

logical | Whether the legend is filled by row or not.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

individual.titles, individual.subtitles, individual.captions

character | Titles or subtitles. for each feature if needed. Either NULL or a vector of equal length of features.

ncol

numeric | Number of columns used in the arrangement of the output plot using "split.by" parameter.

use_viridis

logical | Whether to use viridis color scales.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

raster

logical | Whether to raster the resulting plot. This is recommendable if plotting a lot of cells.

raster.dpi

numeric | Pixel resolution for rasterized plots. Defaults to 1024. Only activates on Seurat versions higher or equal than 4.1.0.

plot_cell_borders

logical | Whether to plot border around cells.

border.size

numeric | Width of the border of the cells.

border.color

character | Color for the border of the heatmap body.

border.density

na.value

character | Color value for NA.

verbose

logical | Whether to show extra comments, warnings,etc.

plot.axes

logical | Whether to plot axes or not.

min.cutoff, max.cutoff

plot_density_contour

logical | Whether to plot density contours in the UMAP.

contour.position

character | Whether to plot density contours on top or at the bottom of the visualization layers, thus overlapping the clusters/cells or not.

contour.color

character | Color of the density lines.

contour.lineend

character | Line end style (round, butt, square).

contour.linejoin

character | Line join style (round, mitre, bevel).

contour_expand_axes

numeric | To make the contours fit the plot, the limits of the X and Y axis are expanding a given percentage from the min and max values for each axis. This controls such percentage.

label

logical | Whether to plot the cluster labels in the UMAP. The cluster labels will have the same color as the cluster colors.

label.color

character | Color of the labels in the plot.

label.size

numeric | Size of the labels in the plot.

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

diverging.palette

character | Type of symmetrical color palette to use. Out of the diverging palettes defined in brewer.pal.

diverging.direction

numeric | Either 1 or -1. Direction of the divering palette. This basically flips the two ends.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object containing a Feature Plot.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_FeaturePlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Regular FeaturePlot.
    p <- SCpubr::do_FeaturePlot(sample = sample,
                                features = "nCount_RNA")

    # FeaturePlot with a subset of identities
    # (in Seurat::Idents(sample)) maintaining the original UMAP shape.
    idents.use <- levels(sample)[!(levels(sample) %in% c("2", "5", "8"))]
    p <- SCpubr::do_FeaturePlot(sample = sample,
                                idents.highlight = idents.use,
                                features = c("EPC1"))

    # Splitting the FeaturePlot by a variable and
    # maintaining the color scale and the UMAP shape.
    p <- SCpubr::do_FeaturePlot(sample = sample,
                                features = "EPC1",
                                split.by = "seurat_clusters")

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Compute functional annotation plots using GO or KEGG ontologies

Description

Compute functional annotation plots using GO or KEGG ontologies

Usage

do_FunctionalAnnotationPlot(
  genes,
  org.db,
  organism = "hsa",
  database = "GO",
  GO_ontology = "BP",
  min.overlap = NULL,
  p.adjust.cutoff = 0.05,
  pAdjustMethod = "BH",
  minGSSize = 10,
  maxGSSize = 500,
  font.size = 10,
  font.type = "sans",
  axis.text.x.angle = 45,
  xlab = NULL,
  ylab = NULL,
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  legend.type = "colorbar",
  legend.position = "bottom",
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.length = 10,
  legend.width = 1,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  number.breaks = 5,
  return_matrix = FALSE,
  grid.color = "white",
  border.color = "black",
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

genes

character | Vector of gene symbols to query for functional annotation.

org.db

OrgDB | Database object to use for the query.

organism

character | Supported KEGG organism.

database

character | Database to run the analysis on. One of:

GO.
KEGG.

GO_ontology

character | GO ontology to use. One of:

BP: For Biological Process.
MF: For Molecular Function.
CC: For Cellular Component.

min.overlap

numeric | Filter the output result to the terms which are supported by this many genes.

p.adjust.cutoff

numeric | Significance cutoff used to filter non-significant terms.

pAdjustMethod

character | Method to adjust for multiple testing. One of:

holm.
hochberg.
hommel.
bonferroni.
BH.
BY.
fdr.
none.

minGSSize

numeric | Minimal size of genes annotated by Ontology term for testing.

maxGSSize

numeric | Maximal size of genes annotated for testing.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

xlab, ylab

character | Titles for the X and Y axis.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

return_matrix

logical | Returns the matrices with the enriched Terms for further use.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

border.color

character | Color for the border of the heatmap body.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A list containing a heatmap of the presence/absence of the genes in the enriched term, as well as a bar plot, dot plot and tree plot of the enriched terms.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_FunctionalAnnotationPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Need to load this library or equivalent.
    suppressMessages(library("org.Hs.eg.db"))

    # Define list of genes to query.
    genes.use <- c("CCR7", "CD14", "LYZ",
                   "S100A4", "MS4A1",
                   "MS4A7", "GNLY", "NKG7", "FCER1A",
                   "CST3", "PPBP")

    # Compute the grouped GO terms.
    out <- SCpubr::do_FunctionalAnnotationPlot(genes = genes.use,
                                               org.db = org.Hs.eg.db)

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Generate a Geyser plot.

Description

A Geyser plot is a custom plot in which we plot continuous values on the Y axis grouped by a categorical value in the X. This is plotted as a dot plot, jittered so that the dots span all the way to the other groups. On top of this, the mean and .66 and .95 of the data is plotted, depicting the overall distribution of the dots. The cells can, then, be colored by a continuous variable (same as Y axis or different) or a categorical one (same as X axis or different).

Usage

do_GeyserPlot(
  sample,
  features,
  assay = NULL,
  slot = "data",
  group.by = NULL,
  split.by = NULL,
  enforce_symmetry = FALSE,
  scale_type = "continuous",
  order = TRUE,
  plot_cell_borders = TRUE,
  jitter = 0.45,
  pt.size = 1,
  border.size = 2,
  border.color = "black",
  legend.position = "bottom",
  legend.width = 1,
  legend.length = 20,
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  legend.type = "colorbar",
  font.size = 14,
  font.type = "sans",
  axis.text.x.angle = 45,
  viridis.palette = "G",
  viridis.direction = 1,
  colors.use = NULL,
  na.value = "grey75",
  legend.ncol = NULL,
  legend.nrow = NULL,
  legend.icon.size = 4,
  legend.byrow = FALSE,
  legend.title = NULL,
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  xlab = "Groups",
  ylab = feature,
  flip = FALSE,
  min.cutoff = rep(NA, length(features)),
  max.cutoff = rep(NA, length(features)),
  number.breaks = 5,
  diverging.palette = "RdBu",
  diverging.direction = -1,
  sequential.palette = "YlGnBu",
  sequential.direction = -1,
  use_viridis = TRUE,
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

features

character | Features to represent.

assay

character | Assay to use. Defaults to the current assay.

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

split.by

character | Secondary metadata variable to further group (split) the output by. Has to be a character of factor column.

enforce_symmetry

logical | Return a symmetrical plot axes-wise or continuous color scale-wise, when applicable.

scale_type

character | Type of color scale to use. One of:

categorical: Use a categorical color scale based on the values of "group.by".
continuous: Use a continuous color scale based on the values of "feature".

order

logical | Whether to order the groups by the median of the data (highest to lowest).

plot_cell_borders

logical | Whether to plot border around cells.

jitter

numeric | Amount of jitter in the plot along the X axis. The lower the value, the more compacted the dots are.

pt.size

numeric | Size of the dots.

border.size

numeric | Width of the border of the cells.

border.color

character | Color for the border of the heatmap body.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

colors.use

character | Named vector of colors to use. Has to match the unique values of group.by when scale_type is set to categorical.

na.value

character | Color value for NA.

legend.ncol

numeric | Number of columns in the legend.

legend.nrow

numeric | Number of rows in the legend.

legend.icon.size

numeric | Size of the icons in legend.

legend.byrow

logical | Whether the legend is filled by row or not.

legend.title

character | Title for the legend.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

xlab, ylab

character | Titles for the X and Y axis.

flip

logical | Whether to invert the axis of the displayed plot.

min.cutoff, max.cutoff

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

diverging.palette

character | Type of symmetrical color palette to use. Out of the diverging palettes defined in brewer.pal.

diverging.direction

numeric | Either 1 or -1. Direction of the divering palette. This basically flips the two ends.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

use_viridis

logical | Whether to use viridis color scales.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Details

Special thanks to Christina Blume for coming up with the name of the plot.

Value

Either a plot of a list of plots, depending on the number of features provided.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_GeyserPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Geyser plot with categorical color scale.
    p <- SCpubr::do_GeyserPlot(sample = sample,
                              features = "nCount_RNA",
                              scale_type = "categorical")
    p

    # Geyser plot with continuous color scale.
    p <- SCpubr::do_GeyserPlot(sample = sample,
                              features = "nCount_RNA",
                              scale_type = "continuous")


    p

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Compute an overview of the GO terms associated with the input list of genes.

Description

Compute an overview of the GO terms associated with the input list of genes.

Usage

do_GroupedGOTermPlot(
  genes,
  org.db,
  levels.use = NULL,
  GO_ontology = "BP",
  min.overlap = 3,
  flip = TRUE,
  colors.use = c(Present = "#1e3d59", Absent = "#bccbcd"),
  legend.position = "bottom",
  reverse.levels = TRUE,
  axis.text.x.angle = 45,
  font.size = 10,
  font.type = "sans",
  plot.title = paste0("GO | ", GO_ontology),
  plot.subtitle = NULL,
  plot.caption = NULL,
  verbose = FALSE,
  return_matrices = FALSE,
  grid.color = "white",
  border.color = "black",
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

genes

character | Vector of gene symbols to query for functional annotation.

org.db

OrgDB | Database object to use for the query.

levels.use

numeric | Vector of numerics corresponding to the GO ontology levels to plot. If NULL will compute all recursively until there are no results.

GO_ontology

character | GO ontology to use. One of:

BP: For Biological Process.
MF: For Molecular Function.
CC: For Cellular Component.

min.overlap

numeric | Filter the output result to the terms which are supported by this many genes.

flip

logical | Whether to invert the axis of the displayed plot.

colors.use

character | Named vector with two colors assigned to the names Present and Absent.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

reverse.levels

logical | Whether to place the higher levels first when computing the joint heatmap.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

verbose

logical | Whether to show extra comments, warnings,etc.

return_matrices

logical | Returns the matrices of grouped GO terms.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

border.color

character | Color for the border of the heatmap body.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A list containing all the matrices for the respective GO levels and all the individual and combined heatmaps.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_GroupedGOTermPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Need to load this library or equivalent.
    suppressMessages(library("org.Hs.eg.db"))

    # Define list of genes to query.
    genes.use <- c("CCR7", "CD14", "LYZ",
                   "S100A4", "MS4A1",
                   "MS4A7", "GNLY", "NKG7", "FCER1A",
                   "CST3", "PPBP")

    # Compute the grouped GO terms.
    out <- SCpubr::do_GroupedGOTermPlot(genes = genes.use,
                                        org.db = org.Hs.eg.db)
  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Compute a heatmap with the results of a group-wise DE analysis.

Description

Compute a heatmap with the results of a group-wise DE analysis.

Usage

do_GroupwiseDEPlot(
  sample,
  de_genes,
  group.by = NULL,
  number.breaks = 5,
  top_genes = 5,
  use_viridis = FALSE,
  viridis.direction = -1,
  viridis.palette.pvalue = "C",
  viridis.palette.logfc = "E",
  viridis.palette.expression = "G",
  sequential.direction = 1,
  sequential.palette.pvalue = "YlGn",
  sequential.palette.logfc = "YlOrRd",
  sequential.palette.expression = "YlGnBu",
  assay = NULL,
  slot = "data",
  legend.position = "bottom",
  legend.width = 1,
  legend.length = 20,
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  legend.type = "colorbar",
  font.size = 14,
  font.type = "sans",
  axis.text.x.angle = 45,
  min.cutoff = NA,
  max.cutoff = NA,
  na.value = "grey75",
  grid.color = "white",
  border.color = "black",
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

de_genes

tibble | DE genes matrix resulting of running Seurat::FindAllMarkers().

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

top_genes

numeric | Top N differentially expressed (DE) genes by group to retrieve.

use_viridis

logical | Whether to use viridis color scales.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

viridis.palette.pvalue, viridis.palette.logfc, viridis.palette.expression

character | Viridis color palettes for the p-value, logfc and expression heatmaps. A capital letter from A to H or the scale name as in scale_fill_viridis.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

sequential.palette.pvalue, sequential.palette.expression, sequential.palette.logfc

character | Sequential palettes for p-value, logfc and expression heatmaps. Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

assay

character | Assay to use. Defaults to the current assay.

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

min.cutoff, max.cutoff

na.value

character | Color value for NA.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

border.color

character | Color for the border of the heatmap body.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A heatmap composed of 3 main panels: -log10(adjusted p-value), log2(FC) and mean expression by cluster.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_GroupwiseDEPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Compute DE genes and transform to a tibble.
    de_genes <- readRDS(system.file("extdata/de_genes_example.rds", package = "SCpubr"))

    # Default output.
    p <- SCpubr::do_GroupwiseDEPlot(sample = sample,
                                    de_genes = de_genes)

    p

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Wrapper for Nebulosa::plot_density in Seurat.

Description

Wrapper for Nebulosa::plot_density in Seurat.

Usage

do_NebulosaPlot(
  sample,
  features,
  slot = NULL,
  dims = c(1, 2),
  pt.size = 1,
  reduction = NULL,
  combine = TRUE,
  method = c("ks", "wkde"),
  joint = FALSE,
  return_only_joint = FALSE,
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  legend.type = "colorbar",
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.length = 20,
  legend.width = 1,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  font.size = 14,
  font.type = "sans",
  legend.position = "bottom",
  plot_cell_borders = TRUE,
  border.size = 2,
  border.color = "black",
  viridis.palette = "G",
  viridis.direction = 1,
  verbose = TRUE,
  na.value = "grey75",
  plot.axes = FALSE,
  number.breaks = 5,
  use_viridis = FALSE,
  sequential.palette = "YlGnBu",
  sequential.direction = 1,
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

features

character | Features to represent.

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

dims

numeric | Vector of 2 numerics indicating the dimensions to plot out of the selected reduction. Defaults to c(1, 2) if not specified.

pt.size

numeric | Size of the dots.

reduction

combine

logical | Whether to create a single plot out of multiple features.

method

Kernel density estimation method:

ks: Computes density using the kde function from the ks package.
wkde: Computes density using a modified version of the kde2d function from the MASS package to allow weights. Bandwidth selection from the ks package is used instead.

joint

logical | Whether to plot different features as joint density.

return_only_joint

logical | Whether to only return the joint density panel.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

plot_cell_borders

logical | Whether to plot border around cells.

border.size

numeric | Width of the border of the cells.

border.color

character | Color for the border of the heatmap body.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

verbose

logical | Whether to show extra comments, warnings,etc.

na.value

character | Color value for NA.

plot.axes

logical | Whether to plot axes or not.

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

use_viridis

logical | Whether to use viridis color scales.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object containing a Nebulosa plot.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_NebulosaPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Basic Nebulosa plot.
    p <- SCpubr::do_NebulosaPlot(sample = sample,
                                 features = "EPC1")

    # Compute joint density.
    p <- SCpubr::do_NebulosaPlot(sample = sample,
                                 features = c("EPC1", "TOX2"),
                                 joint = TRUE)

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Plot Pathway Activities from decoupleR using Progeny prior knowledge.

Description

Plot Pathway Activities from decoupleR using Progeny prior knowledge.

Usage

do_PathwayActivityPlot(
  sample,
  activities,
  group.by = NULL,
  split.by = NULL,
  slot = "scale.data",
  statistic = "norm_wmean",
  pt.size = 1,
  border.size = 2,
  na.value = "grey75",
  legend.position = "bottom",
  legend.width = 1,
  legend.length = 20,
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  legend.type = "colorbar",
  font.size = 14,
  font.type = "sans",
  axis.text.x.angle = 45,
  enforce_symmetry = TRUE,
  min.cutoff = NA,
  max.cutoff = NA,
  number.breaks = 5,
  diverging.palette = "RdBu",
  diverging.direction = -1,
  use_viridis = FALSE,
  viridis.palette = "G",
  viridis.direction = -1,
  sequential.palette = "YlGnBu",
  sequential.direction = 1,
  flip = FALSE,
  return_object = FALSE,
  grid.color = "white",
  border.color = "black",
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

activities

tibble | Result of running decoupleR method with progeny regulon prior knowledge.

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

split.by

character | Secondary metadata variable to further group (split) the output by. Has to be a character of factor column.

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

statistic

character | DecoupleR statistic to use. One of:

wmean: For weighted mean.
norm_wmean: For normalized weighted mean.
corr_wmean: For corrected weighted mean.

pt.size

numeric | Size of the dots.

border.size

numeric | Width of the border of the cells.

na.value

character | Color value for NA.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

enforce_symmetry

logical | Return a symmetrical plot axes-wise or continuous color scale-wise, when applicable.

min.cutoff, max.cutoff

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

diverging.palette

character | Type of symmetrical color palette to use. Out of the diverging palettes defined in brewer.pal.

diverging.direction

numeric | Either 1 or -1. Direction of the divering palette. This basically flips the two ends.

use_viridis

logical | Whether to use viridis color scales.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

flip

logical | Whether to invert the axis of the displayed plot.

return_object

logical | Returns the Seurat object with the modifications performed in the function. Nomally, this contains a new assay with the data that can then be used for any other visualization desired.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

border.color

character | Color for the border of the heatmap body.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_PathwayActivityPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds",
                                  package = "SCpubr"))

    # Define your activities object.
    progeny_activities <- readRDS(system.file("extdata/progeny_activities_example.rds",
                                              package = "SCpubr"))

    # General heatmap.
    out <- SCpubr::do_PathwayActivityPlot(sample = sample,
                                          activities = progeny_activities)
    p <- out$heatmaps$average_scores
    p

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Create ridge plots.

Description

This function computes ridge plots based on the ggridges package.

Usage

do_RidgePlot(
  sample,
  feature,
  group.by = NULL,
  split.by = NULL,
  assay = "SCT",
  slot = "data",
  continuous_scale = FALSE,
  legend.title = NULL,
  legend.ncol = NULL,
  legend.nrow = NULL,
  legend.byrow = FALSE,
  legend.position = NULL,
  legend.width = 1,
  legend.length = 20,
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  legend.type = "colorbar",
  colors.use = NULL,
  font.size = 14,
  font.type = "sans",
  axis.text.x.angle = 45,
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  xlab = NULL,
  ylab = NULL,
  compute_quantiles = FALSE,
  compute_custom_quantiles = FALSE,
  quantiles = c(0.25, 0.5, 0.75),
  compute_distribution_tails = FALSE,
  prob_tails = 0.025,
  color_by_probabilities = FALSE,
  use_viridis = TRUE,
  viridis.palette = "G",
  viridis.direction = 1,
  sequential.palette = "YlGnBu",
  sequential.direction = 1,
  plot.grid = TRUE,
  grid.color = "grey75",
  grid.type = "dashed",
  flip = FALSE,
  number.breaks = 5,
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

feature

character | Feature to represent.

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

split.by

character | Secondary metadata variable to further group (split) the output by. Has to be a character of factor column.

assay

character | Assay to use. Defaults to the current assay.

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

continuous_scale

logical | Whether to color the ridges depending on a categorical or continuous scale.

legend.title

character | Title for the legend.

legend.ncol

numeric | Number of columns in the legend.

legend.nrow

numeric | Number of rows in the legend.

legend.byrow

logical | Whether the legend is filled by row or not.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

colors.use

character | Named vector of colors to use. Has to match the unique values of group.by or color.by (if used) when scale_type is set to categorical.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

xlab, ylab

character | Titles for the X and Y axis.

compute_quantiles

logical | Whether to compute quantiles of the distribution and color the ridge plots by them.

compute_custom_quantiles

logical | Whether to compute custom quantiles.

quantiles

numeric | Numeric vector of quantiles.

compute_distribution_tails

logical | Whether to compute distribution tails and color them.

prob_tails

numeric | The accumulated probability that the tails should contain.

color_by_probabilities

logical | Whether to color the ridges depending on the probability.

use_viridis

logical | Whether to use viridis color scales.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

plot.grid

logical | Whether to plot grid lines.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

grid.type

character | One of the possible linetype options:

blank.
solid.
dashed.
dotted.
dotdash.
longdash.
twodash.

flip

logical | Whether to invert the axis of the displayed plot.

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_RidgePlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Compute the most basic ridge plot.
    p <- SCpubr::do_RidgePlot(sample = sample,
                              feature = "nFeature_RNA")
    p

    # Use continuous color scale.
    p <- SCpubr::do_RidgePlot(sample = sample,
                              feature = "nFeature_RNA",
                              continuous_scale = TRUE,
                              viridis.direction = 1)
    p

    # Draw quantiles of the distribution.
    p <- SCpubr::do_RidgePlot(sample = sample,
                              feature = "nFeature_RNA",
                              continuous_scale = TRUE,
                              compute_quantiles = TRUE,
                              compute_custom_quantiles = TRUE)
    p

    # Draw probability tails.
    p <- SCpubr::do_RidgePlot(sample = sample,
                              feature = "nFeature_RNA",
                              continuous_scale = TRUE,
                              compute_quantiles = TRUE,
                              compute_distribution_tails = TRUE)
    p

    # Draw probability tails.
    p <- SCpubr::do_RidgePlot(sample = sample,
                              feature = "nFeature_RNA",
                              continuous_scale = TRUE,
                              compute_quantiles = TRUE,
                              color_by_probabilities = TRUE)
    p
  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Plot TF Activities from decoupleR using Dorothea prior knowledge.

Description

Plot TF Activities from decoupleR using Dorothea prior knowledge.

Usage

do_TFActivityPlot(
  sample,
  activities,
  n_tfs = 25,
  slot = "scale.data",
  statistic = "norm_wmean",
  tfs.use = NULL,
  group.by = NULL,
  split.by = NULL,
  na.value = "grey75",
  legend.position = "bottom",
  legend.width = 1,
  legend.length = 20,
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  legend.type = "colorbar",
  font.size = 14,
  font.type = "sans",
  axis.text.x.angle = 45,
  enforce_symmetry = TRUE,
  diverging.palette = "RdBu",
  diverging.direction = -1,
  use_viridis = FALSE,
  viridis.palette = "G",
  viridis.direction = -1,
  sequential.palette = "YlGnBu",
  sequential.direction = 1,
  min.cutoff = NA,
  max.cutoff = NA,
  number.breaks = 5,
  flip = FALSE,
  return_object = FALSE,
  grid.color = "white",
  border.color = "black",
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

activities

tibble | Result of running decoupleR method with dorothea regulon prior knowledge.

n_tfs

numeric | Number of top regulons to consider for downstream analysis.

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

statistic

character | DecoupleR statistic to use. One of:

wmean: For weighted mean.
norm_wmean: For normalized weighted mean.
corr_wmean: For corrected weighted mean.

tfs.use

character | Restrict the analysis to given regulons.

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

split.by

character | Secondary metadata variable to further group (split) the output by. Has to be a character of factor column.

na.value

character | Color value for NA.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

enforce_symmetry

logical | Whether the geyser and feature plot has a symmetrical color scale.

diverging.palette

character | Type of symmetrical color palette to use. Out of the diverging palettes defined in brewer.pal.

diverging.direction

numeric | Either 1 or -1. Direction of the divering palette. This basically flips the two ends.

use_viridis

logical | Whether to use viridis color scales.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

min.cutoff, max.cutoff

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

flip

logical | Whether to invert the axis of the displayed plot.

return_object

logical | Returns the Seurat object with the modifications performed in the function. Nomally, this contains a new assay with the data that can then be used for any other visualization desired.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

border.color

character | Color for the border of the heatmap body.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_TFActivityPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds",
                                  package = "SCpubr"))

    # Define your activities object.
    dorothea_activities <- readRDS(system.file("extdata/dorothea_activities_example.rds",
                                               package = "SCpubr"))

    # General heatmap.
    out <- SCpubr::do_TFActivityPlot(sample = sample,
                                     activities = dorothea_activities)
    p <- out$heatmaps$average_scores
    p

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Display the enriched terms for a given list of genes.

Description

Display the enriched terms for a given list of genes.

Usage

do_TermEnrichmentPlot(
  enriched_terms,
  nchar_wrap = 20,
  nterms = 10,
  font.size = 14,
  font.type = "sans",
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  legend.position = "bottom",
  legend.type = "colorbar",
  colors.use = NULL,
  text_labels_size = 4,
  legend.length = 30,
  legend.width = 1,
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

enriched_terms

list | List containing the output(s) of running Enrichr.

nchar_wrap

numeric | Number of characters to use as a limit to wrap the term names. The higher this value, the longer the lines would be for each term in the plots. Defaults to 60.

nterms

numeric | Number of terms to report for each database. Terms are arranged by adjusted p-value and selected from lowest to highest. Defaults to 5.

Enrichr.
FlyEnrichr.
WormEnrichr.
YeastEnrichr.
FishEnrichr.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

colors.use

character | Character vector of 2 colors (low and high ends of the color scale) to generate the gradient.

text_labels_size

numeric | Controls how big or small labels are in the plot.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object with enriched terms.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_TermEnrichmentPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your enriched terms.
    enriched_terms <- readRDS(system.file("extdata/enriched_terms_example.rds", package = "SCpubr"))
    enriched_terms$GO_Cellular_Component_2021 <- NULL
    enriched_terms$Azimuth_Cell_Types_2021 <- NULL

    # Default plot.
    p <- SCpubr::do_TermEnrichmentPlot(enriched_terms = enriched_terms)
    p
  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Wrapper for VlnPlot.

Description

Wrapper for VlnPlot.

Usage

do_ViolinPlot(
  sample,
  features,
  assay = NULL,
  slot = NULL,
  group.by = NULL,
  split.by = NULL,
  colors.use = NULL,
  pt.size = 0,
  line_width = 0.5,
  y_cut = rep(NA, length(features)),
  plot_boxplot = TRUE,
  boxplot_width = 0.2,
  legend.position = "bottom",
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  xlab = rep(NA, length(features)),
  ylab = rep(NA, length(features)),
  font.size = 14,
  font.type = "sans",
  axis.text.x.angle = 45,
  plot.grid = TRUE,
  grid.color = "grey75",
  grid.type = "dashed",
  flip = FALSE,
  ncol = NULL,
  share.y.lims = FALSE,
  legend.title = NULL,
  legend.title.position = "top",
  legend.ncol = NULL,
  legend.nrow = NULL,
  legend.byrow = FALSE,
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

features

character | Features to represent.

assay

character | Assay to use. Defaults to the current assay.

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

split.by

character | Secondary metadata variable to further group (split) the output by. Has to be a character of factor column.

colors.use

pt.size

numeric | Size of points in the Violin plot.

line_width

numeric | Width of the lines drawn in the plot. Defaults to 1.

y_cut

numeric | Vector with the values in which the Violins should be cut. Only works for one feature.

plot_boxplot

logical | Whether to plot a Box plot inside the violin or not.

boxplot_width

numeric | Width of the boxplots. Defaults to 0.2.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

xlab, ylab

character | Titles for the X and Y axis.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

plot.grid

logical | Whether to plot grid lines.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

grid.type

character | One of the possible linetype options:

blank.
solid.
dashed.
dotted.
dotdash.
longdash.
twodash.

flip

logical | Whether to invert the axis of the displayed plot.

ncol

numeric | Number of columns used in the arrangement of the output plot using "split.by" parameter.

share.y.lims

logical | When querying multiple features, force the Y axis of all of them to be on the same range of values (this being the max and min of all features combined).

legend.title

character | Title for the legend.

legend.title.position

character | Position for the title of the legend. One of:

top: Top of the legend.
bottom: Bottom of the legend.
left: Left of the legend.
right: Right of the legend.

legend.ncol

numeric | Number of columns in the legend.

legend.nrow

numeric | Number of rows in the legend.

legend.byrow

logical | Whether the legend is filled by row or not.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A ggplot2 object containing a Violin Plot.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_ViolinPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Basic violin plot.
    p <- SCpubr::do_ViolinPlot(sample = sample,
                               feature = "nCount_RNA")
    p

    # Remove the box plots.
    p <- SCpubr::do_ViolinPlot(sample = sample,
                               feature = "nCount_RNA",
                               plot_boxplot = FALSE)
    p

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Compute a Volcano plot out of DE genes.

Description

Compute a Volcano plot out of DE genes.

Usage

do_VolcanoPlot(
  sample,
  de_genes,
  pval_cutoff = 0.05,
  FC_cutoff = 2,
  pt.size = 2,
  border.size = 1.5,
  border.color = "black",
  font.size = 14,
  font.type = "sans",
  plot.title = NULL,
  plot.subtitle = NULL,
  plot.caption = NULL,
  plot_lines = TRUE,
  line_color = "grey75",
  line_size = 0.5,
  add_gene_tags = TRUE,
  order_tags_by = "both",
  n_genes = 5,
  use_labels = FALSE,
  colors.use = "steelblue",
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

de_genes

tibble | Output of Seurat::FindMarkers().

pval_cutoff

numeric | Cutoff for the p-value.

FC_cutoff

numeric | Cutoff for the avg_log2FC.

pt.size

numeric | Size of the dots.

border.size

numeric | Width of the border of the cells.

border.color

character | Color for the border of the heatmap body.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

plot_lines

logical | Whether to plot the division lines.

line_color

character | Color for the lines.

line_size

numeric | Size of the lines in the plot.

add_gene_tags

logical | Whether to plot the top genes.

order_tags_by

character | Either "both", "pvalue" or "logfc".

n_genes

numeric | Number of top genes in each side to plot.

use_labels

logical | Whether to use labels instead of text for the tags.

colors.use

character | Color to generate a tetradic color scale with.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

Value

A volcano plot as a ggplot2 object.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_VolcanoPlot", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Retrieve DE genes.
    de_genes <- readRDS(system.file("extdata/de_genes_example.rds", package = "SCpubr"))

    # Generate a volcano plot.
    p <- SCpubr::do_VolcanoPlot(sample = sample,
                                de_genes = de_genes)
    p

  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }

Mock function used to document all main function.

Description

Mock function used to document all main function.

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

mono: Mono spaced font.
serif: Serif font family.
sans: Default font family.

legend.type

character | Type of legend to display. One of:

normal: Default legend displayed by ggplot2.
colorbar: Redefined colorbar legend, using guide_colorbar.

legend.position

character | Position of the legend in the plot. One of:

top: Top of the figure.
bottom: Bottom of the figure.
left: Left of the figure.
right: Right of the figure.
none: No legend is displayed.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

plot.title, plot.subtitle, plot.caption

character | Title, subtitle or caption to use in the plot.

assay

character | Assay to use. Defaults to the current assay.

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

reduction

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

raster

logical | Whether to raster the resulting plot. This is recommendable if plotting a lot of cells.

raster.dpi

numeric | Pixel resolution for rasterized plots. Defaults to 1024. Only activates on Seurat versions higher or equal than 4.1.0.

plot_cell_borders

logical | Whether to plot border around cells.

border.size

numeric | Width of the border of the cells.

border.color

character | Color for the border of the heatmap body.

na.value

character | Color value for NA.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

xlab, ylab

character | Titles for the X and Y axis.

pt.size

numeric | Size of the dots.

verbose

logical | Whether to show extra comments, warnings,etc.

flip

logical | Whether to invert the axis of the displayed plot.

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

split.by

character | Secondary metadata variable to further group (split) the output by. Has to be a character of factor column.

colors.use

legend.title

character | Title for the legend.

legend.icon.size

numeric | Size of the icons in legend.

legend.byrow

logical | Whether the legend is filled by row or not.

legend.ncol

numeric | Number of columns in the legend.

legend.nrow

numeric | Number of rows in the legend.

plot_marginal_distributions

logical | Whether to plot marginal distributions on the figure or not.

marginal.type

character | One of:

density: Compute density plots on the margins.
histogram: Compute histograms on the margins.
boxplot: Compute boxplot on the margins.
violin: Compute violin plots on the margins.
densigram: Compute densigram plots on the margins.

marginal.size

numeric | Size ratio between the main and marginal plots. A value of 5 means that the main plot is 5 times bigger than the marginal plots.

marginal.group

logical | Whether to group the marginal distribution by group.by or current identities.

enforce_symmetry

logical | Return a symmetrical plot axes-wise or continuous color scale-wise, when applicable.

column_title

character | Title for the columns of the heatmaps. Only works with single heatmaps.

row_title

character | Title for the rows of the heatmaps. Only works with single heatmaps.

cluster_cols

logical | Cluster the columns or rows of the heatmaps.

cluster_rows

logical | Cluster the rows or rows of the heatmaps.

column_names_rot

numeric | Degree in which to rotate the column labels.

row_names_rot

numeric | Degree in which to rotate the row labels.

cell_size

numeric | Size of each cell in the heatmap.

input_gene_list

named_list | Named list of lists of genes to be used as input.

column_title_rot

numeric | Degree in which to rotate the column titles.

row_title_rot

numeric | Degree in which to rotate the row titles.

column_names_side

character | Side to put the column names. Either left or right.

row_names_side

character | Side to put the row names. Either left or right.

column_title_side

character | Side to put the column titles Either left or right.

row_title_side

character | Side to put the row titles Either left or right.

heatmap.legend.length, heatmap.legend.width

numeric | Width and length of the legend in the heatmap.

heatmap.legend.framecolor

character | Color of the edges and ticks of the legend in the heatmap.

scale_direction

numeric | Direction of the viridis scales. Either -1 or 1.

heatmap_gap

numeric | Gap in cm between heatmaps.

legend_gap

numeric | Gap in cm between legends.

cells.highlight, idents.highlight

ncol

numeric | Number of columns used in the arrangement of the output plot using "split.by" parameter.

dims

numeric | Vector of 2 numerics indicating the dimensions to plot out of the selected reduction. Defaults to c(1, 2) if not specified.

feature

character | Feature to represent.

features

character | Features to represent.

use_viridis

logical | Whether to use viridis color scales.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

plot.grid

logical | Whether to plot grid lines.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

grid.type

character | One of the possible linetype options:

blank.
solid.
dashed.
dotted.
dotdash.
longdash.
twodash.

plot.axes

logical | Whether to plot axes or not.

individual.titles, individual.subtitles, individual.captions

character | Vector. Title, subtitle or caption to use in the plot when multiple features are passed on. Use NA to keep the original title.

legend.title.position

character | Position for the title of the legend. One of:

top: Top of the legend.
bottom: Bottom of the legend.
left: Left of the legend.
right: Right of the legend.

repel

logical | Whether to repel the text labels.

plot_density_contour

logical | Whether to plot density contours in the UMAP.

contour.position

character | Whether to plot density contours on top or at the bottom of the visualization layers, thus overlapping the clusters/cells or not.

contour.color

character | Color of the density lines.

contour.lineend

character | Line end style (round, butt, square).

contour.linejoin

character | Line join style (round, mitre, bevel).

contour_expand_axes

numeric | To make the contours fit the plot, the limits of the X and Y axis are expanding a given percentage from the min and max values for each axis. This controls such percentage.

label

logical | Whether to plot the cluster labels in the UMAP. The cluster labels will have the same color as the cluster colors.

label.color

character | Color of the labels in the plot.

label.fill

character | Color to fill the labels. Has to be a single color, that will be used for all labels. If NULL, the colors of the clusters will be used instead.

label.size

numeric | Size of the labels in the plot.

label.box

logical | Whether to plot the plot labels as geom_text (FALSE) or geom_label (TRUE).

min.overlap

numeric | Filter the output result to the terms which are supported by this many genes.

GO_ontology

character | GO ontology to use. One of:

BP: For Biological Process.
MF: For Molecular Function.
CC: For Cellular Component.

genes

character | Vector of gene symbols to query for functional annotation.

org.db

OrgDB | Database object to use for the query.

disable_white_in_viridis

logical | Remove the white in viridis color scale when viridis.direction is set to -1.

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

strip.spacing

numeric | Controls the size between the different facets.

strip.text.color

character | Color of the strip text.

strip.text.angle

numeric | Rotation of the strip text (angles).

diverging.palette

character | Type of symmetrical color palette to use. Out of the diverging palettes defined in brewer.pal.

diverging.direction

numeric | Either 1 or -1. Direction of the divering palette. This basically flips the two ends.

subsample

numeric | Number of cells to subset for the analysis. NA will use all. Cells are selected at random.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

plain: For normal text.
italic: For text in itallic.
bold: For text in bold.
bold.italic: For text both in itallic and bold.

flavor

character | One of: Seurat, UCell. Compute the enrichment scores using AddModuleScore or AddModuleScore_UCell.

features.order

character | Should the gene sets be ordered in a specific way? Provide it as a vector of characters with the same names as the names of the gene sets.

groups.order

interpolate

logical | Smoothes the output heatmap, saving space on disk when saving the image. However, the image is not as crisp.

viridis.palette.pvalue, viridis.palette.logfc, viridis.palette.expression

character | Viridis color palettes for the p-value, logfc and expression heatmaps. A capital letter from A to H or the scale name as in scale_fill_viridis.

nbin

numeric | Number of bins to use in AddModuleScore.

ctrl

numeric | Number of genes in the control set to use in AddModuleScore.

min.cutoff, max.cutoff

border.density

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.palette.pvalue, sequential.palette.expression, sequential.palette.logfc

character | Sequential palettes for p-value, logfc and expression heatmaps. Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

return_object

logical | Returns the Seurat object with the modifications performed in the function. Nomally, this contains a new assay with the data that can then be used for any other visualization desired.

statistic

character | DecoupleR statistic to use. One of:

wmean: For weighted mean.
norm_wmean: For normalized weighted mean.
corr_wmean: For corrected weighted mean.

cluster

logical | Whether to perform clustering of rows and columns.

Value

Nothing. This is a mock function.

Examples


# This a mock function that stores the documentation for many other functions.
# It is not intended for user usage.

Chromosome arm locations for human genome GRCh38.

Description

A tibble containing the chromosome, arm and start and end coordinates.

Usage

data(human_chr_locations)

Format

A tibble with 48 rows and 4 columns:

chr: Chromosome.
arm: Chromosome arm.
start: Start coordinates.
end: End coordinates.

Named list.

Description

Named list.

Value

Nothing. This is a mock function.

Examples

# This is a named vector.
x <- list("first_element" = c("GENE A", "GENE B"),
          "second_element" = c("GENE C", "GENE D"))
print(x)

Named vector.

Description

Named vector.

Value

Nothing. This is a mock function.

Examples

# This is a named vector.
x <- c("first_element" = 3,
       "second_element" = TRUE)
print(x)

Generate a status report of SCpubr and its dependencies.

Description

This function generates a summary report of the installation status of SCpubr, which packages are still missing and which functions can or can not currently be used.

Usage

package_report(startup = FALSE, extended = FALSE)

Arguments

startup

logical | Whether the message should be displayed at startup, therefore, also containing welcoming messages and tips. If FALSE, only the report itself will be printed.

extended

logical | Whether the message should also include installed packages, current and available version, and which SCpubr functions can be used with the currently installed packages.

Value

None

Examples



# Print a package report.
SCpubr::package_report(startup = FALSE, extended = FALSE)