Plot tf-idf results in reduced dimensions

Source: R/plot_tfidf.R

Plot tf-idf enrichment results in reduced dimensional space (e.g. PCA/tSNe/UMAP), Reduced dimensions can be computed based on single-cell data (e.g. RNA expression). .

plot_tfidf(
  object = NULL,
  reduction = "UMAP",
  label_var = "label",
  cluster_var = "seurat_clusters",
  replace_regex = "[.]|[_]|[-]",
  terms_per_cluster = 3,
  size_var = 1,
  color_var = "cluster",
  point_alpha = 0.7,
  point_palette = c(unname(pals::alphabet()), rev(unname(pals::alphabet2()))),
  density_palette = "Purples",
  density_adjust = 0.2,
  label_fill = alpha(c("white"), 0.7),
  show_plot = T,
  background_color = "white",
  text_color = "black",
  interact = F,
  verbose = T,
  ...
)

Arguments

object

Single-cell data object. Can be in SingleCellExperiment or Seurat format.
reduction

Name of the reduction to use (case insensitive).
label_var

Which cell metadata column to input to tf-idf enrichment analysis.
cluster_var

Which cell metadata column to use to identify which cluster each cell is assigned to.
replace_regex

Characters by which to split label_var into terms (i.e. tokens) for tf-idf enrichment analysis.
terms_per_cluster

The number of top significantly enriched terms to include per cluster.
size_var

Point size variable in object metadata.
color_var

Point color variable in object metadata.
point_alpha

Point opacity.
point_palette

Point palette.
density_palette

Density palette.
density_adjust

Density adjust (controls granularity of density plot).
label_fill

Cluster label background color.
show_plot

Whether to print the plot.
background_color

Plot background color.
text_color

Cluster label text color.
interact

Whether to make the plot interactive with plotly.
verbose

Whether to print messages.
...

Additional arguments to be passed to ggplot2::geom_point(aes_string(...)).

Examples

data("scNLP")

#> Warning: data set ‘scNLP’ not found
data("pseudo_seurat")

res <- plot_tfidf(object = pseudo_seurat, 
                  label_var = "celltype", 
                  cluster_var = "cluster", 
                  show_plot = T)

#> Loading required package: SeuratObject
#> [1] "+ Extracting data from Seurat object."
#> [1] "+ Using reduction: umap"
#> Joining, by = "word"
#> Joining, by = "cluster"
#> Joining, by = "cluster"
#> Warning: Ignoring unknown aesthetics: label