[adegenet-forum] global rtest/ choice of spca axes of significance.

[Nevil Amos]

The global.rtest gives a test of whether there is significant global ( 
ie cross-landscape) structure between sampled locations, correct?

In the spca tutorial example a single pca lambda1  clealy stands out .

How does one decide where more than one axis is involved, should it 
stand out ( ie have substantially greater values) on both variance and 
SA axes?  or simply be an outlier on the variance axis?

Goes the global.rtest test just the first spca axis , or for any 
significant global structure ( that may be across the first few axes)

If it does the latter is what objective approach can be taken to decide 
how many axes should be considered as contributing to the structure?

cheers

Nevil Amos
School of Biological Sciences
Monash University