threshold.select {bootcluster}

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)