Visualize gene QC metrics of Seurat object

Usage

VizSeuratGeneQC(
  object,
  plot_type = c("histogram", "box", "violin", "ridge", "table"),
  palette = "Set1",
  ylab = "Number of cells a gene is expressed in",
  ...
)

Arguments

object: A Seurat object with gene QC metrics
plot_type: Type of plot to generate One of 'histogram', 'box', 'violin', 'ridge' and 'table' If 'plot_type' is 'table', it will return a data frame with number of genes before and after filtering
palette: Color palette to use
ylab: Y-axis label When plot_type is ridge, it will be used as x-axis label
...: Additional arguments to pass to the plot function plotthis::BarPlot()

Value

The plot

Examples

# \donttest{
set.seed(8525)
sobj <- SeuratObject::pbmc_small
sobj@misc$gene_qc <- data.frame(
  Sample = rep(c("Sample1", "Sample2"), each = nrow(sobj)),
  Feature = rep(rownames(sobj), 2),
  Count = as.integer(runif(nrow(sobj) * 2, 0, 100))
)
sobj@misc$gene_qc$QC <- (
  sobj@misc$gene_qc$Count >= 20 |
     sample(c(TRUE, FALSE), nrow(sobj) * 2, prob = c(0.8, 0.2), replace = TRUE)
)

# Visualize gene QC metrics
VizSeuratGeneQC(sobj)
#> Using `bins = 30`. Pick better value with `binwidth`.

VizSeuratGeneQC(sobj, plot_type = "box")

VizSeuratGeneQC(sobj, plot_type = "violin")

VizSeuratGeneQC(sobj, plot_type = "ridge")
#> Picking joint bandwidth of 5.79
#> Picking joint bandwidth of 6.29
#> Picking joint bandwidth of 5.79
#> Picking joint bandwidth of 6.29

VizSeuratGeneQC(sobj, plot_type = "table")
#> # A tibble: 3 × 4
#>   Sample         failed passed total
#>   <fct>           <int>  <int> <int>
#> 1 Sample1             9    221   230
#> 2 Sample2             8    222   230
#> 3 Final_Features     17    213   230
# }