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Lake acidity was inferred using a diatom inference model.
Horizontally transferred genes from distantly related organisms were inferred using a Bayesian inference program with training models based on the nucleotide composition.
Thermal conductivity was inferred using a geometrical mean model from porosities estimated from LWD resistivity for two assumed grain conductivity values (k g = 2.5W/K/m and 3.0W/K/m).
Population structure was inferred using a Bayesian clustering approach implemented using STRUCTURE v2.3 [29] [31] software.
The phylogeny was inferred using a concatenated (all loci) alignments under Maximum Parsimony with PAUP* 4.0b10 [46].
One-to-one orthologs regrouped into the PHYLOME-T60 database were inferred using a large scale phylogenetic approach.
Ancestral geographic states were inferred using a geographically explicit Bayesian MCMC method implemented in BEAST v1.5.4 package [32], [33].
Selective pressures at individual codons were inferred using a Bayesian approach with model M2a used as a prior distribution on ω.
These numbers were inferred using a strict regimen requiring core genes to be present in all 13 genomes and should be considered the extreme lower boundaries for the core and pan-genomes.
Since this is not sufficient to reliably estimate an evolutionary rate or the tMRCA, the tMRCA was inferred using a normal distribution with a mean value of 50 years and standard deviation (stdev) of 20 years as prior distribution, based on our prior belief about the history of the Wheelwright epidemic.
Causal networks were inferred using a multistep procedure (Fig. 1).
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