Hierarchical clustering on cell types from pseudobulk — buildClusterTreeFromPB • dreamlet

Perform hierarchical clustering on cell types from pseudobulk by aggregating read counts from each cell type.

Usage

buildClusterTreeFromPB(
  pb,
  method = c("complete", "ward.D", "single", "average", "mcquitty", "median", "centroid",
    "ward.D2"),
  dist.method = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"),
  assays = assayNames(pb)
)

Arguments

pb: SingleCellObject storing pseudobulk for each cell type in in assay() field
method: clustering method for hclust()
dist.method: distance metric
assays: which assays to include

Value

hierarchical clustering object of class hclust

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
)

# Hierarchical clustering of cell types
hcl <- buildClusterTreeFromPB(pb)

plot(hcl)