Bar plot of variance fractions for a subset of genes
Usage
# S4 method for vpDF
plotPercentBars(
  x,
  col = c(ggColorHue(ncol(x) - 3), "grey85"),
  genes = unique(x$gene),
  width = NULL,
  ncol = 3,
  ...
)
# S4 method for cellSpecificityValues
plotPercentBars(
  x,
  col = ggColorHue(ncol(x)),
  genes = rownames(x),
  width = NULL,
  ...
)Arguments
- x
- vpDFobject returned by- fitVarPart()
- col
- color of bars for each variable 
- genes
- name of genes to plot 
- width
- specify width of bars 
- ncol
- number of columns in the plot 
- ...
- other arguments 
Examples
library(muscat)
library(SingleCellExperiment)
data(example_sce)
# create pseudobulk for each sample and cell cluster
pb <- aggregateToPseudoBulk(example_sce,
  assay = "counts",
  cluster_id = "cluster_id",
  sample_id = "sample_id",
  verbose = FALSE
)
# voom-style normalization
res.proc <- processAssays(pb, ~group_id)
#>   B cells...
#> 0.13 secs
#>   CD14+ Monocytes...
#> 0.22 secs
#>   CD4 T cells...
#> 0.15 secs
#>   CD8 T cells...
#> 0.078 secs
#>   FCGR3A+ Monocytes...
#> 0.21 secs
# variance partitioning analysis
vp <- fitVarPart(res.proc, ~group_id)
#>   B cells...
#> 0.71 secs
#>   CD14+ Monocytes...
#> 1 secs
#>   CD4 T cells...
#> 0.77 secs
#>   CD8 T cells...
#> 0.48 secs
#>   FCGR3A+ Monocytes...
#> 0.92 secs
#> 
# Show variance fractions at the gene-level for each cell type
plotPercentBars(vp, genes = vp$gene[2:4], ncol = 2)
