MA Plot of LogFC Versus Mean Expression

Usage

# S4 method for class 'lucida'
plotMA(
  object,
  coef,
  method = c("classic", "Bayesian"),
  size = 12,
  ymax = NULL,
  cutoff = 0.05,
  ncol = 3,
  cluster_ids = names(object),
  ...
)

Arguments

object: result from lucida()
coef: coefficient to test with results()
method: "classic": multiple testing correction using Benjamini–Hochberg method, or "Bayesian": shrink coefficient estimates and report local FDR from ashr::ash() using empirical Bayes approach.
size: text size
ymax: maximum value to show on the y-axis. if NULL set to max observed value
cutoff: adj.P.Val cutoff to distinguish significant from non-significant genes
ncol: number of columns in the plot
cluster_ids: which assays to plot
...: arguments passed to facet_wrap(). Useful for specifying scales = "free_y"

Value

Volcano plot for each cell type

Examples

library(SingleCellExperiment)

# Load example data
data(example_sce, package="muscat")
sce <- example_sce

# Compute library size for each cell
sce$libSize <- colSums(counts(sce))

# Specify regression formula and cell annotation 
form <- ~ group_id 
fit <- lucida(sce, form, "cluster_id", verbose=FALSE)
#> B cells 
#> CD14+ Monocytes 
#> CD4 T cells 
#> CD8 T cells 
#> FCGR3A+ Monocytes 

# MA plot
plotMA(fit, "group_idstim")