Kalevan ja Untamon geenit: Estonians, the genetic comparison

I succeeded to download 13 Estonian samples from the study “Upper Palaeolithic Siberiangenome reveals dual ancestry of Native Americans “ released by Estonian Biocenter. After the qualification I had 11 samples, two was removed due to being too close relatives with other samples. I have only a few comments about the Finestructure, otherwise I only hope you enjoy the results.

the Finestructure analysis is based on IBS-similarity.
I removed Lithuanians from the Finestructure run because they show very high national IBS-similarity and it distorts results in the aggregate mode. This happens although the aggregate level is quite low in my analysis. This means practically that Estonians are compared to Slavs (Belarussians).
processes using MCMC-aggregate features usually change individual results and usually you can’t compare individual results on Finestructure matrixes. To see individual results you have to look the raw data matrix, not the aggregate matrix, but in my run the difference between raw and aggregate is very small. In this context I refer to my previous analyses and to the effects of young isolations, they tend to distort aggregated results.
as also in my previous Finestructure analysis, the South European result seems to be somewhat inaccurate, but Northern Europe looks quite good.
the tree result on the matrix seems to imply more differences than similarities between samples. So for example the Finns on the matrix are split into two or three groups. It is at least for me impossible to estimate the balance of similarities and differences between individuals and populations in existing software analyzing tools. It is strongly up to the selected tools, and accordingly to the authors, how similarities and differences are weighted. Some authors prefer similarities, even in case it is very small, and disregard differences. This can be seen by comparing results and analyzing tools. This question is interesting and reminds of the complex history of each population and used data which can be inadequate.