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Differential expression testing on cell level

Source: R/differential_testing.R
marker_wilcox_test.Rd

EXPERIEMTAL FEATURE, we advise against using it yet and suggest you have a look at the Vignette "Differential Analysis" for other options. marker_wilcox_test() performes a Wilcoxon Rank Sum Test for two groups of cells for each marker and cell population combination.

Usage

marker_wilcox_test(
  fcd,
  cluster_slot,
  cluster_var,
  group_var,
  group1,
  group2,
  p.adjust.method = "BH",
  marker = NULL,
  min_cells_per_group = 10
)

Arguments

fcd

flow cytometry data set, that has been subjected to the clustering or cell type label prediction with cyCONDOR

cluster_slot

string specifying which clustering slot to use to find variable specified in cluster_var

cluster_var

string specifying variable name in cluster_slot that identifies cell population labels to be used (e.g. clusters, metaclusters or predicted labels).

group_var

string indicating variable name in cell_anno that should be used as grouping variable. The grouping variable needs to have two or more groupss

group1

string indicating group level in group_var that should be used to select cells for group 1

group2

string indicating group level in group_var that should be used to select cells for group 2

p.adjust.method

p-value adjustment method to use for multiple comparison testing, e.g "BH" (Benjamini-Hochberg, default) or "bonferroni". All available options can be checked in the documentation of the adjust_pvalue function from the package rstatix.

marker

(optional) vector of character strings indicating which features in the expression expr_slot should be considered during testing. by default, all features are tested.

min_cells_per_group

Minimum number of cells per group required to include a cell population for differential testing.

Value

A data frame containing test results for each marker and cell population combination - one combination per row.

  • cluster : cell population that was tested

  • marker : feature from expression data that was tested

  • group1 : group name (level) of group 1

  • group2 : group name (level) of group 2

  • n1 / n2 : absolute cell counts in group 1 (n1) and group 2 (n2)

  • mean1 / mean2 : mean marker expression in group 1 (mean1) and group 2 (mean2)

  • p : p-value

  • p.adj : adjusted p-value.

  • delta_mean : delta of mean1 and mean2

Details

marker_wilcox_test

The function marker_wilcox_test() compares two groups of cells for each marker-cell population combination. Expression values will be extracted from expr_slot "orig", containing the transformed data. In case group_var has more than two levels, the dataset will be subsetted to the two levels specified in group1 and group2. Wilcoxon Rank Sum Test is performed using the wilcox.test implemented in the stats package. Afterwards p-value adjustment is performed considering all comparisons that were made.