Visualize Cell QC metrics of Seurat object

Usage

VizSeuratCellQC(
  object,
  features = c("nFeature_RNA", "nCount_RNA", "percent.mt", "percent.ribo", "percent.hb",
    "percent.plat"),
  plot_type = c("violin", "box", "scatter", "bar", "ridge", "table"),
  scatter_x = "nCount_RNA",
  palette = "Set1",
  assay = "RNA",
  layer = "counts",
  ...
)

Arguments

object: A Seurat object with cell QC metrics
features: Features to visualize, genes are supported.
plot_type: Type of plot to generate One of 'violin', 'box', 'scatter', 'bar', 'ridge' and 'table' If 'plot_type' is 'table', it will return a data frame with number of cells before and after filtering
scatter_x: Feature to use as x-axis in scatter plot. If it is one of the features, it will be removed from the features
palette: Color palette to use
assay: Assay used to extract expression if genes are included in features. Default is "RNA".
layer: Layer used to extract expression if genes are included in features. Default is "counts". If the specified layer is not found, and there are layers with the specified layer as prefix, it will join layers first and try again.
...: Additional arguments to pass to the plot function

Value

The plot

Examples

# \donttest{
set.seed(8525)
sobj <- SeuratObject::pbmc_small
sobj$.QC <- sample(c(TRUE, FALSE), ncol(sobj), replace = TRUE)
sobj$Sample <- sample(c("Sample1", "Sample2"), ncol(sobj), replace = TRUE)
sobj$percent.mt <- runif(ncol(sobj), 0, 1)
sobj$percent.ribo <- runif(ncol(sobj), 0, 1)
sobj$percent.hb <- runif(ncol(sobj), 0, 1)
sobj$percent.plat <- runif(ncol(sobj), 0, 1)
sobj$nFeature_RNA <- as.integer(runif(ncol(sobj), 1000, 5000))
sobj$nCount_RNA <- as.integer(runif(ncol(sobj), 1000, 5000))

# Visualize cell QC metrics
VizSeuratCellQC(sobj)

VizSeuratCellQC(sobj, plot_type = "scatter")

VizSeuratCellQC(sobj, plot_type = "bar")

VizSeuratCellQC(sobj, plot_type = "ridge")
#> Picking joint bandwidth of 509
#> Picking joint bandwidth of 501
#> Picking joint bandwidth of 0.0973
#> Picking joint bandwidth of 0.128
#> Picking joint bandwidth of 0.125
#> Picking joint bandwidth of 0.12
#> Picking joint bandwidth of 509
#> Picking joint bandwidth of 501
#> Picking joint bandwidth of 0.0973
#> Picking joint bandwidth of 0.128
#> Picking joint bandwidth of 0.125
#> Picking joint bandwidth of 0.12

VizSeuratCellQC(sobj, features = c("percent.mt", "percent.ribo"))

VizSeuratCellQC(sobj, features = c("percent.mt", "percent.ribo"), plot_type = "box")

VizSeuratCellQC(sobj, plot_type = "table")
#> # A tibble: 3 × 4
#>   Sample      failed passed total
#>   <fct>        <int>  <int> <int>
#> 1 Sample1         14     26    40
#> 2 Sample2         21     19    40
#> 3 All_Samples     35     45    80

dim(sobj)
#> [1] 230  80
sobj <- FinishSeuratQC(sobj)
dim(sobj)
#> [1] 230  45
# }