ConstructMetacells: ConstructMetacells
In smorabit/hdWGCNA: hdWGCNA

ConstructMetacells

R Documentation

ConstructMetacells

Description

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