ConstructMetacells

This function takes a Seurat object and constructs averaged 'metacells' based on neighboring cells.

Usage

ConstructMetacells(
  seurat_obj,
  name = "agg",
  ident.group = "seurat_clusters",
  k = 25,
  reduction = "pca",
  dims = NULL,
  assay = "RNA",
  cells.use = NULL,
  slot = "counts",
  layer = "counts",
  meta = NULL,
  return_metacell = FALSE,
  mode = "average",
  max_shared = 15,
  target_metacells = 1000,
  max_iter = 5000,
  verbose = FALSE,
  wgcna_name = NULL
)

Arguments

seurat_obj

A Seurat object

name

A string appended to resulting metalcells. Default = 'agg'

k

Number of nearest neighbors to aggregate. Default = 50

reduction

A dimensionality reduction stored in the Seurat object. Default = 'umap'

dims

A vector represnting the dimensions of the reduction to use. Either specify the names of the dimensions or the indices. Default = NULL to include all dims.

assay

Assay to extract data for aggregation. Default = 'RNA'

slot

Slot to extract data for aggregation. Default = 'counts'. Slot is used with Seurat v4 instead of layer.

layer

Layer to extract data for aggregation. Default = 'counts'. Layer is used with Seurat v5 instead of slot.

return_metacell

Logical to determine if we return the metacell seurat object (TRUE), or add it to the misc in the original Seurat object (FALSE). Default to FALSE.

mode

determines how to make gene expression profiles for metacells from their constituent single cells. Options are "average" or "sum".

max_shared

the maximum number of cells to be shared across two metacells

target_metacells

the maximum target number of metacells to construct

max_iter

the maximum number of iterations in the metacells bootstrapping loop

verbose

logical indicating whether to print additional information

wgcna_name

name of the WGCNA experiment