Violin plot of variance fraction for each gene and each variable
Usage
# S4 method for DataFrame
plotVarPart(
  obj,
  col = c(ggColorHue(base::ncol(obj) - 3), "grey85"),
  label.angle = 20,
  main = "",
  ylab = "",
  convertToPercent = TRUE,
  ncol = 3,
  ...
)Arguments
- obj
- varParFracobject returned by- fitExtractVarPartor- extractVarPart
- col
- vector of colors 
- label.angle
- angle of labels on x-axis 
- main
- title of plot 
- ylab
- text on y-axis 
- convertToPercent
- multiply fractions by 100 to convert to percent values 
- ncol
- number of columns in the plot 
- ...
- additional arguments 
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...
#> 0.13 secs
#>   CD14+ Monocytes...
#> 0.24 secs
#>   CD4 T cells...
#> 0.15 secs
#>   CD8 T cells...
#> 0.078 secs
#>   FCGR3A+ Monocytes...
#> 0.19 secs
# variance partitioning analysis
vp <- fitVarPart(res.proc, ~group_id)
#>   B cells...
#> 0.7 secs
#>   CD14+ Monocytes...
#> 0.92 secs
#>   CD4 T cells...
#> 0.74 secs
#>   CD8 T cells...
#> 0.44 secs
#>   FCGR3A+ Monocytes...
#> 0.89 secs
#> 
# Summarize variance fractions genome-wide for each cell type
plotVarPart(vp)
