extract.edges — extract.edges • FCtools

Generates edge-wise masks for calculating subject-level network strengths

Usage

extract.edges(NBS.obj, network = 1)

Arguments

NBS.obj: A list object generated from an earlier NBS() analysis
network: the network number (reported in the earlier NBS results) of the network to be masked. Set to 1 by default

Value

Returns a list object containing

clust.tstat thresholded edge-wise t-statistics.Edges not belonging to this cluster will be zeroed.
pos.edges A vector of 1s and 0s indicating the significant network-thresholded positive edges.
neg.edges A vector of -1s and 0s indicating the significant network-thresholded negative edges.
pos.mask A vector of 1s and 0s indicating the significant network-thresholded positive edges.
neg.mask A vector of 1s and 0s indicating the significant network-thresholded negative edges.

Details

This function generates positive and negative masks (vectors of 1s and 0s), where 1s indicate a significant network-thresholded edge. These masks can then be used to perform a matrix multiplication with the vectorized FC matrices to object subject-level network strengths

Examples

demomat=get('demomat')
contrast=c(1,1,2,2)
random=c('sub1','sub2','sub3','sub4')
model1=NBS(model=contrast, contrast=contrast, FC_data=demomat, nperm=2, nthread=1, p=0.001)
#> 
  |                                                                            
  |                                                                      |   0%
#> Estimating permuted network strengths...
#> 
  |                                                                            
  |===================================                                   |  50%
  |                                                                            
  |======================================================================| 100%
#> Completed in :0.1 minutes 

edges=extract.edges(model1,network=1)