>>11557160>if you use class/category labels in the algo you bias it for finding that grouping opposed to the inherent structure. that is why clustering is used and not classification.That map you posted demonstrates my point quite well. When there are more options to specify ancestral origins, more than just 4 clusters appear, and that's just within Europe.
https://web.stanford.edu/group/pritchardlab/structure.htmlThis is found on Structures Homepage so I think it's author approved:
https://www.genetics.org/content/genetics/204/2/391.full.pdfOne persistent challenge with applying STRUCTURE is inferring the number of source populations (K). Increasing the
value of K adds parameters, which can lead to overfitting the
data, and so model-choice procedures are necessary to estimate K. Numerous procedures have been proposed (Evanno
et al. 2005; Huelsenbeck and Andolfatto 2007), though the
conventional wisdom is that reproducible inference of K is a
difficult problem, with less stability than conventional parameter estimation (e.g., Gilbert et al. 2012). Pritchard,
Stephens, and Donnelly were prescient and acknowledged
problems in the inference and interpretation of K. They have
long advocated instead using STRUCTURE as an exploratory
tool and inspecting results from a range of values of K.
Another challenge is that STRUCTURE has become, in
some sense, a victim of its own success. It is applied by default in most studies without consideration of whether the
underlying model is relevant. For example, if applied to a
geographic continuum, the method will infer source populations that are vaguely spatial but have no real interpretation as source populations in an admixed sample.
All your maps demostrate different ways to group human populations. That's my point. If these different methods consistently produced the same groupings, I'd concede that the groupings aren't arbitrary.
