Bar plot of variance fractions

Bar plot of variance fractions for a subset of genes

Usage

# S4 method for class 'vpDF'
plotPercentBars(
  x,
  col = c(ggColorHue(ncol(x) - 3), "grey85"),
  genes = unique(x$gene),
  width = NULL,
  ncol = 3,
  ...
)

# S4 method for class 'cellSpecificityValues'
plotPercentBars(
  x,
  col = ggColorHue(ncol(x)),
  genes = rownames(x),
  width = NULL,
  ...
)

Arguments

x

vpDF object 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

Value

Bar plot showing variance fractions for each gene

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...
#> 0.19 secs
#>   CD14+ Monocytes...
#> 0.3 secs
#>   CD4 T cells...
#> 0.22 secs
#>   CD8 T cells...
#> 0.13 secs
#>   FCGR3A+ Monocytes...
#> 0.27 secs

# variance partitioning analysis
vp <- fitVarPart(res.proc, ~group_id)
#>   B cells...
#> 2 secs
#>   CD14+ Monocytes...
#> 2.6 secs
#>   CD4 T cells...
#> 2 secs
#>   CD8 T cells...
#> 1.2 secs
#>   FCGR3A+ Monocytes...
#> 2.5 secs
#> 

# Show variance fractions at the gene-level for each cell type
plotPercentBars(vp, genes = vp$gene[2:4], ncol = 2)