topTable-methods: Table of Top Genes from dreamlet fit

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

Table of Top Genes from dreamlet fit

Description

Extract a table of the top-ranked genes from a dreamlet fit.

Usage

## S4 method for signature 'dreamletResult'
topTable(
  fit,
  coef = NULL,
  number = 10,
  genelist = NULL,
  adjust.method = "BH",
  sort.by = "P",
  resort.by = NULL,
  p.value = 1,
  lfc = 0,
  confint = FALSE
)

Arguments

fit	dreamletResult object
coef	coef
number	number
genelist	genelist
adjust.method	adjust.method
sort.by	sort.by
resort.by	resort.by
p.value	p.value
lfc	lfc
confint	confint

Value

data.frame storing hypothesis test for each gene and cell type

See Also

limma::topTable(), variancePartition::topTable()

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)

# show coefficients estimated for each cell type
coefNames(res.dl)

# extract results using limma-style syntax
# combines all cell types together
# adj.P.Val gives study-wide FDR
topTable(res.dl, coef = "group_idstim", number = 3)

GabrielHoffman/dreamlet documentation built on July 20, 2024, 9:03 p.m.