Methods such as mCLR, and in fact any related methods controlling for heterogeneity statistically, require good eigenmaps. We show such a map, one that successfully identifies clusters of genetically distinct individuals, requires a sufficiently diverse, yet representative base sample. It is not sufficient to use only the most genetically similar and diverse populations available for the base sample. Genetic isolates alone are not ideal for creating an eigenmap meant to differentiate typical individuals in modern populations. A large sample of convenience is also not optimal. A smaller number of individuals chosen to represent the full range of ancestry in the sample of interest will produce a better eigenmap. In the near future, when cases and controls will be matched prior to genomewide sequencing, sound eigenmaps are likely to be even more important.
