threshold.select: Estimate of the overall Jaccard stability

In bootcluster: Bootstrapping Estimates of Clustering Stability

Estimate of the overall Jaccard stability

Description

Estimate of the overall Jaccard stability

Arguments

data.input	a data.frame of the data set where the rows are observations and columns are covariates
threshold.seq	a numeric sequence of candidate threshold
B	number of bootstrap re-samplings
cor.method	the correlation method applied to the data set,three method are available: "pearson", "kendall", "spearman".
large.size	the smallest set of modules, the large.size=0 is recommended to use right now.
PermuNo	number of random graphs for the estimation of expected stability
no_cores	a interger number of CPU cores on the current host (This function can't not be used yet).

Details

threshold.select is used to estimate of the overall Jaccard stability from a sequence of given threshold candidates, threshold.seq.

Value

stabilityresult

a list of result for nodes-wise stability

modularityresult

a list of modularity information with each candidate threshold

jaccardresult

a list estimated unconditional observed stability and the estimates of expected stability under the nul

originalinformation

a list information for original data, igraph object and adjacency matrix constructed with each candidate threshold

threshold.seq

a list of candicate threshold given to the function

Author(s)

Mingmei Tian

References

A framework for stability-based module detection in correlation graphs. Mingmei Tian,Rachael Hageman Blair,Lina Mu, Matthew Bonner, Richard Browne and Han Yu.

Examples

set.seed(1)
data(wine)
x0 <- wine[1:50,]

mytest<-threshold.select(data.input=x0,threshold.seq=seq(0.5,0.8,by=0.05), B=20, 
cor.method='pearson',large.size=0,
PermuNo = 10,
no_cores=1,
scheme_2 = FALSE)

bootcluster documentation built on April 3, 2025, 7:45 p.m.