do_AffinityAnalysisPlot: Compute affinity of gene sets to cell populations using...

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

Compute affinity of gene sets to cell populations using decoupleR.

Description

Major contributions to this function:

• Marc Elosua Bayés for the core concept code and idea.

• Pau Badia i Mompel for the network generation.

Usage

do_AffinityAnalysisPlot(
  sample,
  input_gene_list,
  subsample = 2500,
  group.by = NULL,
  assay = NULL,
  slot = NULL,
  statistic = "ulm",
  number.breaks = 5,
  use_viridis = FALSE,
  viridis.palette = "G",
  viridis.direction = -1,
  sequential.palette = "YlGnBu",
  sequential.direction = 1,
  diverging.palette = "RdBu",
  diverging.direction = -1,
  enforce_symmetry = TRUE,
  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",
  na.value = "grey75",
  font.size = 14,
  font.type = "sans",
  axis.text.x.angle = 45,
  flip = FALSE,
  colors.use = NULL,
  min.cutoff = NA,
  max.cutoff = NA,
  verbose = TRUE,
  return_object = FALSE,
  grid.color = "white",
  border.color = "black",
  flavor = "Seurat",
  nbin = 24,
  ctrl = 100,
  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.
subsample	numeric | Number of cells to subset for the analysis. NA will use all. Cells are selected at random.
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.
slot	character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".
statistic	character | DecoupleR statistic to use for the analysis. values in the Idents of the Seurat object are reported, assessing how specific a given gene set is for a given cell population compared to other gene sets of equal expression.
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.
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.
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.
enforce_symmetry	logical | Return a symmetrical plot axes-wise or continuous color scale-wise, when applicable.
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.
na.value	character | Color value for NA.
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.
flip	logical | Whether to invert the axis of the displayed plot.
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.
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.
verbose	logical | Whether to show extra comments, warnings,etc.
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.
flavor	character | One of: Seurat, UCell. Compute the enrichment scores using AddModuleScore or AddModuleScore_UCell.
nbin	numeric | Number of bins to use in AddModuleScore.
ctrl	numeric | Number of genes in the control set to use in AddModuleScore.
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 different plots.

Examples

  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_AffinityAnalysisPlot", 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_AffinityAnalysisPlot(sample = sample,
                                         input_gene_list = genes,
                                         nbin = 1,
                                         ctrl = 5,
                                         flavor = "Seurat",
                                         subsample = NA,
                                         verbose = 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()`.")
  }

enblacar/SCpubr documentation built on Feb. 11, 2024, 4:15 a.m.