extractData-methods: Extract normalized expression and 'colData'

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

Extract normalized expression and colData

Description

Extract normalized expression and colData

Extract normalized (i.e. log2 CPM) expression and colData from dreamletProcessedData

Usage

extractData(x, assay, cols = colnames(colData(x)), genes = rownames(x))

## S4 method for signature 'dreamletProcessedData,character'
extractData(
  x,
  assay,
  cols = colnames(colData(x)),
  genes = rownames(assay(x, assay))
)

Arguments

x	dreamletProcessedData object
assay	assay to extract
cols	columns in colData(x) to extract. defaults to all columns as colnames(colData(x))
genes	genes to extract from assay(x, assay)$E. defaults to all genes as rownames(x)

Value

data.frame or DataFrame of merged expression and colData

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)

# Extract all:
# Extract tibble of colData merged with expression.
# variables and genes are stored as columns, samples as rows
df_merge <- extractData(res.proc, "B cells")

# first few columns
df_merge[, 1:6]

# Extract subset:
df_merge <- extractData(res.proc, "B cells", cols = "group_id", genes = c("SSU72", "U2AF1"))

df_merge

# Boxplot of expression
boxplot(SSU72 ~ group_id, df_merge)
#

GabrielHoffman/dreamlet documentation built on May 20, 2024, 2:05 p.m.