steiner_comparison_wilcox: Perform wilcox test

Description Usage Arguments Details Value References See Also Examples

Description

Perform pairwise Wilcoxon rank sum tests

Usage

1

Arguments

type

a character vector, which indicates type of algorithms to analyse. Can be "EXA", "SP", "KB", "RSP", "SPM" or "ASP".

method

a character scalar; specifies a calculated parameter based on which comparison is performed. Can be "runtime" (for time of execution), "log10runtime" "edge" (for number of edges in resultant steiner tree), "log10edge", "ter_freq" (for terminal frequency in resultant steiner tree) or "edge_dens" (for edge density in resultant steiner tree).

data

should have structure as output of steiner_simulation function.

Details

"holm" method for adjusting p-values is used.

Value

Object of class "pairwise.htest"

References

1. Afshin Sadeghi and Holger Froehlich, "Steiner tree methods for optimal sub-network identification: an empirical study", BMC Bioinformatics 2013 14:144

See Also

generate_st_samples, steiner_simulation, steinertree, pairwise.wilcox.test

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
g <- graph("Cubical")

data <- steiner_simulation(type = c("SP", "KB", "SPM"),
                           graph = g,
                           ter_list = generate_st_samples(graph = g,
                                                          ter_number = c(2, 3),
                                                          prob = c(0.1, 0.2)))

steiner_comparison_wilcox(type = c("SP", "KB"),
                          method = "ter_freq",
                          data = data)

SteinerNet documentation built on Sept. 7, 2020, 5:09 p.m.