sortCols-method: Sort variance partition statistics

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

Sort variance partition statistics

Description

Sort variance partition statistics

Usage

## S4 method for signature 'vpDF'
sortCols(
  x,
  FUN = sum,
  decreasing = TRUE,
  last = c("Residuals", "Measurement.error"),
  ...
)

Arguments

x	object returned by fitVarPart()
FUN	function giving summary statistic to sort by. Defaults to sum
decreasing	logical. Should the sorting be increasing or decreasing?
last	columns to be placed on the right, regardless of values in these columns
...	other arguments to sort

Value

data.frame with columns sorted by mean value, with Residuals in last column

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)

# variance partitioning analysis
vp <- fitVarPart(res.proc, ~group_id)

# Summarize variance fractions genome-wide for each cell type
plotVarPart(sortCols(vp))

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