do_TFActivityPlot: Plot TF Activities from decoupleR using Dorothea prior...

In SCpubr: Generate Publication Ready Visualizations of Single Cell Transcriptomics Data

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	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.
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()`.")
  }

SCpubr documentation built on Oct. 11, 2023, 5:15 p.m.