Resolution:
## Figure 3.
Finite supragenome model results using (. In our previous supragenome analyses carried out with K = 6) variable population gene frequency classesHaemophilus influenzae and Streptococcus pneumoniae we used a version of the finite supragenome model that required fixed population gene
frequency classes. This model has been updated to make the optimization function (the
log-likelihood of the observed sample gene frequency histogram, i.e., the observed
gene frequency class distribution among the |S| strains examined) dependent on the values of the population gene frequency vector
(μ) as well as the values of the corresponding mixture coefficient vector (π, for the probability that a gene in a supragenome will be represented in one of the
K classes of population gene frequencies). For a given species, the bottom graph plots
the values of the vector μ against the product of the estimate of supragenome size and the values of the vector
π, all obtained at the maximization of the log-likelihood function.
Boissy |