Constructs a "pseudobulk" gene expression matrix summarizing the expression levels of each gene across a grouping variable (cell types for example) in each biological replicate.
Usage
ConstructPseudobulk(
seurat_obj,
group.by,
replicate_col,
label_col = NULL,
assay = "RNA",
slot = "counts",
layer = "counts",
min_reps = 20,
wgcna_name = NULL
)Arguments
- seurat_obj
A Seurat object
- group.by
column in seurat_obj@meta.data containing grouping info, ie clusters or celltypes
- replicate_col
column in seurat_obj@meta.data denoting each replicate / sample
- label_col
column in seurat_obj@meta.data denoting an additional label of interest, for example disease status or biological sex. This is not a required argument and is typically only used for consensus WGCNA
- assay
Assay in seurat_obj containing isoform expression information.
- slot
Slot to extract data for aggregation. Default = 'counts'
- layer
Layer to extract data for aggregation. Default = 'counts'. Layer is used with Seurat v5 instead of slot.
- min_reps
The minimum number of different biological replicates allowed. Error will be thrown if the number of reps is too low.
- wgcna_name
The name of the hdWGCNA experiment in the seurat_obj@misc slot
Details
This function constructs pseudobulk gene expression profiles across the provided cell groups and the provided biological replicates. We note that low numbers of replicates are typical in single-cell and spatial transcriptomics due to the large monetary cost of running these experiments, and pseudobulk-ing your data for hdWGCNA is only recommended in the case where you have a sufficient number of replicates. Here we have set the minimum recommended number to 20. Using fewer than 20 replicates risks the results not being reproducible or robust, and therefore are not biologically meaningful due to spurious noisy correlations.