Data from: Multivariate analysis of genotype-phenotype association

Philipp Mitteroecker, James M. Cheverud & Mihaela Pavlicev
With the advent of modern imaging and measurement technology, complex phenotypes are increasingly represented by large numbers of measurements, which may not bear biological meaning one by one. For such multivariate phenotypes, studying the pairwise associations between all measurements and all alleles is highly inefficient and prevents insight into the genetic pattern underlying the observed phenotypes. We present a new method for identifying patterns of allelic variation (genetic latent variables) that are maximally associated—in terms...
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These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
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