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Results: We introduce a generalized rarefaction approach for counting alleles private to combinations of populations.
ADZE is a generalized rarefaction approach that counts alleles private to populations as well as combinations of populations.
First, assessing alleles private to combinations of populations can assist in dealing with sampling designs that are uneven.
Pooling information cannot be applied to all combinations of populations, since treating data from different sources equivalently is flawed.
Notable differences in allele frequency exist among combinations of populations, but also at putatively functional sites that are monomorphic in all but one population, where a high frequency derived allele is found.
This analysis was performed at each temperature separately using the model Y = M + G(P) + P + E. QST values were calculated for all pairwise combinations of populations as well as across all populations (SAS Institute 2008; PROC MIXED, method = reml).
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Additional file 10c shows the mean number of shared private alleles between the three combinations of population pairs, when corrected for equal population size.
For BEAST, various combinations of population size change and molecular clock models were compared to find the model that best fit the data.
For each of the simulated combinations of population, genetic architecture, and heritability, the data contain phenotypic information for 1000 individuals and genotypic information for 2000 biallelic markers (the possible values coded as "A" and "H") for each individual.
Priority populations of rice CWRs for the collection of accessions for ex situ conservation and the development of in situ conservation strategies are a combination of populations that hold the highest levels of genetic diversity (alpha diversity) and are complementary in terms of adaptive traits and their degree of genetic differentiation (beta diversity).
On the basis of this observation, we developed a framework to efficiently search for a follow-up study design: our framework searches for the best combination of populations from a pool of available populations to maximize the LSR for detection of a causal variant.
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