FindSubpopulationMarkers: Identify marker genes for previously identified...

In jr-leary7/SCISSORS: Identify cell subpopulations in single cell RNA-seq data

Identify marker genes for previously identified subpopulations.

Description

This function determines which cells characterize the subpopulations identified using ReclusterCells. It is intended to be run on a single re-clustered Seurat object at a time, though if you wish you could iterate over the list of reclustering results, and save the outputs from this function in a matching array of lists. The function returns a list of dataframes, one dataframe per cluster, containing normal and Bonferroni-adjusted p-values, gene prevalence, and effect size in the form of log2 fold change.

Usage

FindSubpopulationMarkers(
  seurat.object = NULL,
  reclust.data = NULL,
  which.compare = "all cells",
  diff.exp.test = "wilcox",
  logfc.thresh = 2,
  random.seed = 629
)

Arguments

seurat.object	The original Seurat object containing the entire cell population and related metadata.
reclust.data	A specific Seurat object from the list of objects returned by ReclusterCells.
which.compare	Should subpopulation marker genes be determined in the context of the entire sample, or solely the single cluster? Defaults to "all cells"; choose "within cluster" to determine marker genes at the cluster level.
diff.exp.test	The test used to calculate differential expression using FindMarkers. Defaults to "wilcox".
logfc.thresh	The log2 fold-change cutoff used when performing differential expression analysis. Defaults to 2.
random.seed	(Optional) The seed used to control stochasticity in several functions. Defaults to 629.

Author(s)

Jack Leary

See Also

FindSpecificMarkers

Examples

## Not run: FindSubpopulationMarkers(seurat.object, reclust.data = reclust_results)

jr-leary7/SCISSORS documentation built on April 20, 2023, 8:21 p.m.