FR.test: Friedman-Rafsky (FR) test

Description

FR test is a multivariate generalization of nonparametric two-sample test. This function is an implementation with customized options, including a visualization of the minimum spanning tree (MST).

Usage

FR.test(
  samp1,
  samp2,
  use.cosine = FALSE,
  binary = FALSE,
  binary.cutoff = 2,
  plot.MST = FALSE,
  col = c("#F0E442", "#56B4E9"),
  label.names = c("Sample 1", "Sample 2"),
  vertex.size = 5,
  edge.width = 1,
  ...
)

Value

Test statistics and p-values.

runs: Total number of subtrees.
runs.samp1: Number of subtrees of Sample 1.
runs.samp2: Number of subtrees of Sample 2.
stat: The standardized FR statistic.
p.value: P-value of the FR test.

Arguments

samp1: Numeric matrix or data frame for Sample 1. Rows are multivariate dimensions, and columns are samples. E.g. gene by cell.
samp2: Numeric matrix or data frame for Sample 2.
use.cosine: An option if to use cosine distance. Logical variable. By default (FALSE), Euclidean distance is used.
binary: An option if to use binary values. Logical variable. Default: FALSE. If TRUE, use binary.cutoff to dichotomize samp1 and samp2.
binary.cutoff: Numeric value for binary cutoff. Binary value = 1 if greater than binary.cutoff, 0 otherwise. Default: 2.
plot.MST: Boolean variable indicating if to plot the minimum spanning tree (MST). Default: FALSE.
col: Character vector of length two for customized colors of the nodes in MST. Default: c("#F0E442", "#56B4E9").
label.names: Character vector of length two for customized names of the two samples. Default: c("Sample 1","Sample 2").
vertex.size, edge.width, ...: Additional plotting parammeters passed to plot.igraph. Default: vertex.size=5, edge.width=1.