bb_cluster_representation: Cluster Representation By Fisher Exact Test Per Cell

In blaserlab/blaseRtools: R Tools for Blaser Lab Data Analysis

Cluster Representation By Fisher Exact Test Per Cell

Description

Use this function to determine the differential representation of cells in clusters. It will determine fold change in a single experimental class over a single control or reference class. This value is normalized to the number of cells captured in all clusters from the class. Significance is determined using Fisher's exact test. This test may overestimate significance in large data sets. In this case, bb_cluster_representation2 may be more robust.

Usage

bb_cluster_representation(
  cds,
  cluster_var,
  class_var,
  experimental_class,
  control_class,
  pseudocount = 1,
  return_value = c("table", "plot")
)

Arguments

cds	A cell data set object
cluster_var	The CDS cell metadata column holding cluster data. There can be any number of clusters in this column.
class_var	The CDS cell metadata column holding sample class data. There can be only 2 classes in this column. You may need to subset or reclass the samples to achieve this.
experimental_class	The value from the class column indicating the experimental group.
control_class	The value from the class column indicating the control or reference class.
return_value	Option to return either a plot or a data table for plotting in a separate step. Must be either "plot" or "table".

Value

A ggplot or a table of data for plotting

blaserlab/blaseRtools documentation built on April 14, 2025, 6:04 p.m.