Using sampling experiments, we found that, when there are fewer groups than variables,
between-groups PCA (bgPCA) may suggest surprisingly distinct differences among groups …

Between group PCA (bgPCA) has been developed to summarize group differences in high
dimensional spaces like in geometric morphometrics and microarray data where the number …

Evaluating statistical trends in high-dimensional phenotypes poses challenges for
comparative biologists, because the high-dimensionality of the trait data relative to the …

Good empirical applications of geometric morphometrics (GMM) typically involve several
times more variables than specimens, a situation the statistician refers to as “high p/n,” …

Phylogenetic regression is frequently used in macroevolutionary studies, and its statistical
properties have been thoroughly investigated. By contrast, phylogenetic ANOVA has …

How do we quantify patterns (such as responses to local selection) sampled across multiple
populations within a single species? Key to this question is the extent to which populations …

Background The dramatic progress in sequencing technologies offers unprecedented
prospects for deciphering the organization of natural populations in space and time …

Comparative studies investigating evolutionary questions are generally concerned with
interspecific variation of trait values, while variations observed within species are inherently …

Phylogenetic methods for the analysis of species data are widely used in evolutionary
studies. However, preliminary data transformations and data reduction procedures (such as …

Abstract Comparison of population structure between studies can be difficult, because the
value of the often‐used FST‐statistic depends on the amount of genetic variation within …