Plot voom curves from each cell type

Usage

plotVoom(x, ncol = 3, alpha = 0.5, ...)

# S4 method for dreamletProcessedData
plotVoom(x, ncol = 3, alpha = 0.5, assays = names(x))

# S4 method for EList
plotVoom(x, ncol = 3, alpha = 0.5)

Arguments

x: dreamletProcessedData
ncol: number of columns in the plot
alpha: transparency of points
...: other arguments
assays: which assays to plot

Value

Plot of mean-variance trend

Examples

library(muscat)
library(SingleCellExperiment)

data(example_sce)

# create pseudobulk for each sample and cell cluster
pb <- aggregateToPseudoBulk(example_sce,
  assay = "counts",
  cluster_id = "cluster_id",
  sample_id = "sample_id",
  verbose = FALSE
)

# voom-style normalization
res.proc <- processAssays(pb, ~group_id)
#>   B cells...
#> 0.22 secs
#>   CD14+ Monocytes...
#> 0.33 secs
#>   CD4 T cells...
#> 0.25 secs
#>   CD8 T cells...
#> 0.13 secs
#>   FCGR3A+ Monocytes...
#> 0.31 secs

# Show mean-variance trend from voom
plotVoom(res.proc)


# plot for first two cell types
plotVoom(res.proc[1:2])