plotBeeswarm: Beeswarm plot of effect sizes for each assay

In GabrielHoffman/dreamlet: Scalable differential expression analysis of single cell transcriptomics datasets with complex study designs

Beeswarm plot of effect sizes for each assay

Description

Beeswarm plot of effect sizes for each assay, colored by sign and FDR

Usage

plotBeeswarm(res.dl, coef, fdr.range = 4, assays = assayNames(res.dl))

Arguments

res.dl	dreamletResult object from dreamlet()
coef	coefficient name fed to topTable()
fdr.range	range for coloring FDR
assays	which assays to plot

Value

ggplot2 of logFC by assay

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)

# Differential expression analysis within each assay,
# evaluated on the voom normalized data
res.dl <- dreamlet(res.proc, ~group_id)

# Beeswarm plot of effect sizes for each assay,
# colored by sign and FDR
plotBeeswarm(res.dl, "group_idstim")

GabrielHoffman/dreamlet documentation built on Nov. 8, 2024, 2:45 a.m.