Dear all,
I am currently working on the population structure of clonal parasitic mites, and as Structure was no option as it clusters samples following Hardy-Weinberg assumption, I am now trying to use Adegenet (which does not follow this assumption). I have succesfuly run the Discriminant Analysis of Principal Components (DAPC) following the tutorial provided by Thibaut Jombart (2014), but whenever I repeat the analysis with the same dataset, I have drastically different outcome (although I use the same settings). More specifically, for the choice of the numbers of cluster, the "Value of BIC versus number of clusters" graph always suggests different outcomes... In the end, most attempts are going in the same direction as other approaches I used, but some others appear to be quite different...
Does anybody have previously experienced this situation? If yes, how did you solve that problem?
Cheers!
Alex
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