Description Usage Arguments Details Value References See Also Examples
Perform pairwise Wilcoxon rank sum tests
1 | steiner_comparison_wilcox(type, method, data)
|
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. |
"holm" method for adjusting p-values is used.
Object of class "pairwise.htest"
1. Afshin Sadeghi and Holger Froehlich, "Steiner tree methods for optimal sub-network identification: an empirical study", BMC Bioinformatics 2013 14:144
generate_st_samples
, steiner_simulation
,
steinertree
, pairwise.wilcox.test
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)
|
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