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However, in the 40 ascertained families, where parental HLA information was missing and some sibs were genotyped, the inference was implemented as in 1), despite the fact that some inconsistent genotypes may then be obtained.
Maximum likelihood inference was implemented in GARLI v.0.942 (Genetic Algorithm for Rapid Likelihood Inference) [56] also sampling 2×106 generations for multiple runs to ensure similar trees and lnL scores.
Bayesian inference was implemented in MrBayes 3.1.2 [ 80].
Bayesian inference was implemented in BEAST version 1.8.0 (Drummond et al. 2012).
Bayesian inference was implemented using the Markov chain Monte Carlo algorithm.
This phylogeographic inference was implemented in BEAST 1.8 (Drummond et al., 2012) similar to the temporal phylogenies described above.
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Bayesian estimation and inference are implemented using the Winbugs package via Markov chain Monte Carlo (MCMC) methods (Lunn et al. 2009).
Short read processing, mapping, and miRNA gene inference were implemented in a custom bioinformatics pipeline (fig. 1 C; supplementary methods, Supplementary Material online).
The developed algorithms for the network inference were implemented in the software package NETI, freely available from our web page [ 22].
For both PLS methods, statistical inferences are implemented using cross-validation techniques to identify significant patterns of voxel activation.
Bayesian inferences were implemented in PAUP*b4.10 [ 72] and MrBayes (MrBayes 3.0b4, [ 73]).
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