monocle3 (version 0.1.3)

top_markers: Identify the genes most specifically expressed in groups of cells

Description

Identify the genes most specifically expressed in groups of cells

Usage

top_markers(cds, group_cells_by = "cluster",
  genes_to_test_per_group = 25, reduction_method = "UMAP",
  marker_sig_test = TRUE, reference_cells = NULL, cores = 1,
  verbose = FALSE)

Arguments

cds

A cell_data_set object to calculate top markers for.

group_cells_by

String indicating what to group cells by for comparison. Default is "cluster".

genes_to_test_per_group

Numeric, how many genes of the top ranked specific genes by Jenson-Shannon to do the more expensive regression test on.

reduction_method

String indicating the method used for dimensionality reduction. Currently only "UMAP" is supported.

marker_sig_test

A flag indicating whether to assess the discriminative power of each marker through logistic regression. Can be slow, consider disabling to speed up top_markers().

reference_cells

If provided, top_markers will perform the marker significance test against a "reference set" of cells. Must be either a list of cell ids from colnames(cds), or a positive integer. If the latter, top_markers() will randomly select the specified number of reference cells. Accelerates the marker significance test at some cost in sensitivity.

cores

Number of cores to use.

verbose

Whether to print verbose progress output.