Do maximum likelihood analysis for gBGC and selection using nucleotide model
bgc.nucleotide.tests(align, neutralMod, branch, sel.limits = c(-200, 200),
bgc.limits = c(0, 200))A nucleotide alignment of type msa
A model of neutral evolution of type tm. Should be a nucleotide (4x4) model.
A character string giving the name of a branch from neutralMod$tree where lineage-specific selection/gBGC
Numeric vector of length 2 giving lower and upper limits for selection parameter.
Numeric vector of length 2 giving lower and upper limits for gBGC parameter B
A data.frame with four rows. Each row represents one of the models "null", "sel", "bgc", and "sel+bgc". All models have a global selection coefficient; the sel and sel+bgc models have a lineage-specific selection coefficient as well, and the bgc and sel+bgc models have a lineage-specific gBGC parameter. The likelihoods and parameter estimates for each model are returned in the data frame.