threshold | R Documentation |
Filters the network based on an r-value, alpha, adaptive alpha, bonferroni, false-discovery rate (FDR), or proportional density (fixed number of edges) value
threshold( data, a, thresh = c("alpha", "adaptive", "bonferroni", "FDR", "proportional"), normal = FALSE, na.data = c("pairwise", "listwise", "fiml", "none"), ... )
data |
Can be a dataset or a correlation matrix |
a |
When |
thresh |
Sets threshold. Defaults to |
normal |
Should data be transformed to a normal distribution? Defaults to FALSE. Data is not transformed to be normal. Set to TRUE if data should be transformed to be normal (computes correlations using the cor_auto function) |
na.data |
How should missing data be handled?
For |
... |
Additional arguments for |
Returns a list containing:
A |
The filtered adjacency matrix |
r.cv |
The critical correlation value used to filter the network |
Alexander Christensen <alexpaulchristensen@gmail.com>
Strimmer, K. (2008). fdrtool: A versatile R package for estimating local and tail area-based false discovery rates. Bioinformatics, 24, 1461-1462.
threshnet<-threshold(neoOpen) alphanet<-threshold(neoOpen, thresh = "alpha", a = .05) bonnet<-threshold(neoOpen, thresh = "bonferroni", a = .05) FDRnet<-threshold(neoOpen, thresh = "FDR", a = .10) propnet<-threshold(neoOpen, thresh = "proportional", a = .15)
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