These concerns are still not fully resolved by studies based on whole genome data from a few teleost species [ 36, 37], and they can be resolved only by ancestral-state inferences by using multiple genome data, and phylogenetic frameworks and divergence time estimations.
In addition, in teleosts, whole-genome sequence data from multiple species [ 16, 20, 27], reliable phylogenetic frameworks, and estimated divergence times between lineages [ 28- 33] are now available.
To test the relationship between MSI and phylogenetic relatedness, multiple phylogenetic similarity matrices were constructed for all of the taxa examined, using recently published phylogenetic hypotheses [33] [43].
We performed multiple phylogenetic analyses of these sequences with up-to-date phylogenetic methods.
This new 'PhyloCSF' method fully leverages multiple alignments in a phylogenetic framework, produces meaningful likelihood ratios as its output and rests upon the sweeping theoretical foundation for statistical model comparison.
Multiple regression analyses in a phylogenetic framework were performed on hook angle.
Multiple regression analyses in a phylogenetic framework [17], [18] as described below were performed on PC1 and PC2 (which together explained 80% of the variation in hook shape).
To elucidate the dynamics underlying pathway and trait evolution across multiple lineages, it is of paramount importance to identify and distinguish the complete set of orthologous and paralogous loci present within multiple genome annotations in a phylogenetic framework [ 34].
To account for the non-independence of data points due to shared ancestry of species we used a generalized least-squares (GLS) approach in a phylogenetic framework (PGLS) to perform multiple regression analysis.
