[adegenet-forum] calculating and presenting sPCA variance components

[Pip Griffin]

Hi Thibaut and adegenet forum users,

I'd appreciate some advice about how to present sPCA variance components.

I understand that it's meaningless to calculate "% variance explained"
by a single eigenvalue as a proportion of the total, the way you can
for a PCA, since each eigenvalue comprises both genetic and spatial
components.

And I see, in the summary(spca), the eigenvalue decomposition of the
retained axes into the genetic variance and Moran's I components.

But, I am not clear how this relates to the *proportion* of total (or
maximum possible) variance (of each type), because the decomposition
is presented only for the eigenvalues that were retained.

It would make sense to present the spatial variance explained by Axis
1 as Axis1$moran/Imax (from the 'connection network statistics' also
presented in the summary) - i.e. as a proportion of the maximum
possible.

But then for the "maximum possible" genetic variance: where can I find
this figure? Should it be the sum of all PCA eigenvalue components
(not just those retained)? - findable by doing an independant PCA on
the same dataset?

Or am I taking the wrong approach here?

thanks in advance for your help
Pip