findDACombinedClusters: Combine differential abundant subpopulation

In altairwei/rhapsodykit: A Set of Tools for BD Rhapsody WTA Downstream Analysis

Combine differential abundant subpopulation

Description

This function assumes that each DAseq result is produced from a different subset of the same integrated cell embedding and has a common reference condition (aka. control).

Usage

findDACombinedClusters(
  obj_list,
  ref_label,
  resolution = 0.05,
  prune.SNN = 1/15,
  group.singletons = FALSE,
  min.cell = NULL,
  ...
)

Arguments

obj_list	A list of DAseq results
ref_label	The control condition common to all DAseq results
resolution	parameter for Seurat function FindClusters(), default 0.05
prune.SNN	parameter for Seurat function FindNeighbors(), default 1/15
group.singletons	parameter for Seurat function FindClusters(), default True
min.cell	integer, number of cells below which a DA region will be removed as outliers, default NULL, use minimum k value in k-vector
...	other parameters to pass to Seurat FindClusters()

altairwei/rhapsodykit documentation built on Feb. 1, 2023, 8:52 a.m.