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A function to generate clusters from scRNA-seq data

Source: R/bb_triplecluster.R
bb_triplecluster.Rd

Based on Monocle3's Partitions, Leiden, and Louvain clustering methods. Implemented mostly with default values. Seurat objects will be converted to cell_data_set objects for the clustering. The function produces a list of top markers for each cluster type and returns these assignments to the original object as new cell metadata columnts.

Usage

bb_triplecluster(
  obj,
  n_top_markers = 50,
  outfile = NULL,
  n_cores = 8,
  cds = NULL
)

Arguments

obj

A Seurat or cell_data_set object

n_top_markers

Number of top markers to identify per cell group, Default: 50

outfile

Name of a csv file to hold the top marker results. If null, will place "top_markers.csv" in the working directory, Default: NULL

n_cores

Number of processor cores to use, Default: 8

cds

Provided for backwards compatibility for existing code. If a value is supplied it will be transferred to obj and a warning message will be emitted, Default: NULL

Value

A modified Seurat or cell_data_set object