Two blind spots in the demographic inference of human origins from genomic data
Ryan N Gutenkunst
Abstract
Ancient DNA and new inference methods have transformed the study of human origins, but consensus has not followed. Evidence increasingly indicates that hominin populations were pervasively structured and admixed, so complexity rather than simplicity is the appropriate prior. Here I highlight two blind spots that impede resolving that complexity. First, every inference passes through summaries of the data, and those summaries bound what can be recovered. Second, the space of candidate models is vast, yet competing model classes are rarely fit to common data, so a reported best model carries little evidence about untested model classes. This second blind spot reflects practice rather than data. It can be narrowed by testing competing models against withheld summaries and by reporting the models that were tried and rejected rather than only the winner.
Create a lesson
Related papers
Observation delays can bias inference of selective advantage in evolutionary competition
Robert Valaska, Katarina Bodova
Linking individual bioenergetics to ecosystem dynamics with integral projection models
Willem Bonnaffé, Martina Muraro, William Goulding et al.
Reservoir: A Large-Scale Simulated Dataset for Training and Evaluating Epidemiological Models
Carson Dudley, Reiden Magdaleno, Marisa Eisenberg
What sets the critical genome length for sympatric speciation? A closed form and asymptotic theory
Dan Braha, Marcus A. M. de Aguiar, Vitor M. Marquioni
The emergence and evolution of a referential code in populations of bee-like agents
Grzegorz Chrupała
Tree Buckets and the Reconstruction of Pairs of Phylogenetic Trees
Sky Basire, Michael Hendriksen