Sampling strategy optimization to increase statistical power in landscape genomics: A simulation-based approach.

ABSTRACT: An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. Implementation of this approach requires the sampling phase to consider the complexity of environmental settings and the burden of logistical constraints. These important aspects are often underestimated in the literature dedicated to sampling strategies. In this study, we computed simulated genomic data sets to run against actual environmental data in order to trial landscape genomics experiments under distinct sampling strategies. These strategies differed by design approach (to enhance environmental and/or geographical representativeness at study sites), number of sampling locations and sample sizes. We then evaluated how these elements affected statistical perf

SUBMITTER: Selmoni O 

PROVIDER: S-EPMC6972490 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature