Volcano plot for each cell type

Usage

plotVolcano(
  x,
  coef,
  nGenes = 5,
  size = 12,
  minp = 9.99999999999997e-311,
  cutoff = 0.05,
  ncol = 3,
  ...
)

# S4 method for list
plotVolcano(
  x,
  coef,
  nGenes = 5,
  size = 12,
  minp = 9.99999999999997e-311,
  cutoff = 0.05,
  ncol = 3,
  assays = names(x),
  ...
)

# S4 method for MArrayLM
plotVolcano(
  x,
  coef,
  nGenes = 5,
  size = 12,
  minp = 9.99999999999997e-311,
  cutoff = 0.05,
  ncol = 3,
  ...
)

# S4 method for dreamlet_mash_result
plotVolcano(
  x,
  coef,
  nGenes = 5,
  size = 12,
  minp = 1e-16,
  cutoff = 0.05,
  ncol = 3,
  assays = colnames(x$logFC.original),
  ...
)

Arguments

x: result from dreamlet
coef: coefficient to test with topTable
nGenes: number of genes to highlight in each volcano plot
size: text size
minp: minimum p-value to show on the y-axis
cutoff: adj.P.Val cutoff to distinguish significant from non-significant genes
ncol: number of columns in the plot
...: arguments passed to facet_wrap(). Useful for specifying scales = "free_y"
assays: which assays to plot

Value

Volcano plot for each cell type

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...
#> 0.2 secs
#>   CD14+ Monocytes...
#> 0.35 secs
#>   CD4 T cells...
#> 0.23 secs
#>   CD8 T cells...
#> 0.15 secs
#>   FCGR3A+ Monocytes...
#> 0.29 secs

# Differential expression analysis within each assay,
# evaluated on the voom normalized data
res.dl <- dreamlet(res.proc, ~group_id)
#>   B cells...
#> 0.16 secs
#>   CD14+ Monocytes...
#> 0.21 secs
#>   CD4 T cells...
#> 0.17 secs
#>   CD8 T cells...
#> 0.15 secs
#>   FCGR3A+ Monocytes...
#> 0.2 secs

# show coefficients estimated for each cell type
coefNames(res.dl)
#> [1] "(Intercept)"  "group_idstim"

# volcano plot for each cell type
plotVolcano(res.dl, coef = "group_idstim")
#> Warning: Removed 1 rows containing missing values (`geom_text_repel()`).


# volcano plot for first two cell types
plotVolcano(res.dl[1:2], coef = "group_idstim")
#> Warning: Removed 1 rows containing missing values (`geom_text_repel()`).