Title
Comparing Likelihood Ratios To Understand Genome-Wide Variation In Phylogenetic Support
Document Type
Article
Publication Date
3-1-2022
Abstract
Genomic data have only sometimes brought resolution to the tree of life. Large phylogenomic studies can reach conflicting conclusions about important relationships, with mutually exclusive hypotheses receiving strong support. Reconciling such differences requires a detailed understanding of how phylogenetic signal varies among data sets. Two complementary strategies for better understanding phylogenomic conflicts are to examine support on a locus-by-locus basis and use support values that capture a larger range of variation in phylogenetic information, such as likelihood ratios. Likelihood ratios can be calculated using either maximum or marginal likelihoods. Despite being conceptually similar, differences in how these ratios are calculated and interpreted have not been closely examined in phylogenomics. Here, we compare the behavior of maximum and marginal likelihood ratios when evaluating alternate resolutions of recalcitrant relationships among major squamate lineages. We find that these ratios are broadly correlated between loci, but the correlation is driven by extreme values. As a consequence, the proportion of loci that support a hypothesis can change depending on which ratio is used and whether smaller values are discarded. In addition, maximum likelihood ratios frequently exhibit identical support for alternate hypotheses, making conflict resolution a challenge. We find surprising support for a sister relationship between snakes and iguanians across four different phylogenomic data sets in contrast to previous empirical studies. [Bayes factors; likelihood ratios; marginal likelihood; maximum likelihood; phylogenomics; squamates.]
Publication Source (Journal or Book title)
Systemic Biology
Recommended Citation
Mount, G. G., & Brown, J. M. (2022). Comparing Likelihood Ratios To Understand Genome-Wide Variation In Phylogenetic Support. Systemic Biology https://doi.org/10.1093/sysbio/syac014