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The database is implemented in Structured Query Language (SQL), and is hosted on a Sun workstation running the Informix Database Management System (DBMS).
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Population genetic structure of the cultivars was estimated using the Bayesian clustering method implemented in STRUCTURE 2.3.4 (Pritchard et al. 2000).
To determine the best K value, previous information about O. sativa population structure was used in combination with the Evanno method (Evanno et al. [2005]), implemented in Structure Harvester (Earl and VonHoldt [2012]).
The Bayesian clustering method as implemented in STRUCTURE revealed 4 subpopulations.
First, the Bayesian model-based clustering method of Pritchard et al. [12] was employed as implemented in Structure 2.3 [34].
Structure was used to infer the genetic structure; the model-based clustering algorithm implemented in Structure identifies clusters and subclusters by allelic frequencies.
In fact, the models implemented in STRUCTURE specifically allow for the reconstruction of ancestral clusters even if most individuals are largely composed of admixed genotypes [51].
The most likely number of populations in the Huia dataset of genotypes was estimated using a Bayesian clustering approach implemented in STRUCTURE [30].
The fully Bayesian model-based clustering method implemented in STRUCTURE v2.2 [21] was used to infer the most likely number of genetic clusters (K) in the data set.
We used several Bayesian algorithms implemented in Structure [49], [50], Instruct [51] and Structurama [52], to cluster individuals into genetically distinct groups.
Three independent methods were used to estimate individual genetic ancestry: two Bayesian approaches using a Markov chain Monte Carlo algorithm, implemented in Structure 2.2 [71] and ADMIXMAP [72], and a maximum likelihood method [73] implemented in software provided by Xianyun Mao.
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