Acupuncture and knee osteoarthritis.
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Biomedical subjects
Publications and source records attributed to Richard H Baker.
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Combined analysis of multiple phylogenetic data sets can reveal emergent character support that is not evident in separate analyses of individual data sets. Previous parsimony analyses have shown that this hidden support often accounts for a large percentage of the overall phylogenetic signal in cladistic studies. Here, reanalysis of a large comparative genomic data set for yeast (genus Saccharomyces) demonstrates that hidden support can be an important factor in maximum likelihood analyses of multiple data sets as well. Emergent signal in a concatenation of 106 genes was responsible for up to 64% of the likelihood support at a particular node (the difference in log likelihood scores between optimal topologies that included and excluded a supported clade). A grouping of four yeast species (S. cerevisiae, S. paradoxus, S. mikatae, and S. kudriavzevii) was robustly supported by combined analysis of all 106 genes, but separate analyses of individual genes suggested numerous conflicts. Forty-eight genes strictly contradicted S. cerevisiae + S. paradoxus + S. mikatae + S. kudriavzevii in separate analyses, but combined likelihood analyses that included up to 45 of the "wrong" data sets supported this group. Extensive hidden support also emerged in a combined likelihood analysis of 41 genes that each recovered the exact same topology in separate analyses of the individual genes. These results show that isolated analyses of individual data sets can mask congruence and distort interpretations of clade stability, even in strictly model-based phylogenetic methods. Consensus and supertree procedures that ignore hidden phylogenetic signals are, at best, incomplete.
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Morphological divergence among species may be constrained by the pattern of genetic variances and covariances among traits within species. Assessing the existence of such a relationship in nature requires information on the stability of intraspecific correlation and covariance structure and the correspondence of this structure to the pattern of evolutionary divergence within a lineage. Here, we investigate these issues for nine morphological traits and 15 species of stalk-eyed flies in the genus Diasemopsis. Within-species matrices for these traits were generated from phenotypic data for all the Diasemopsis species and from genetic data for a single Diasemopsis species, D. dubia. The among-species pattern of divergence was assessed by calculating the evolutionary correlations for all pairwise combinations of the morphological traits along the phylogeny of these species. Comparisons of intraspecific matrices reveal significant similarity among all species in the phenotypic correlations matrices but not the covariance matrices. In addition, the differences in correlation structure that do exist among species are not related to their phylogenetic placement or change in the means of the traits. Comparisons of the phenotypic and phylogenetic matrices suggest a strong relationship between the pattern of evolutionary change among species and both the intraspecific correlation structure and the stability of this structure among species. The phenotypic and the phylogenetic matrices are significantly similar, and pairs of traits whose intraspecific correlations are more stable across taxa exhibit stronger coevolution on the phylogeny. These results suggest either the existence of strong constraints on the pattern of evolutionary change or a consistent pattern of correlated selection shaping both the phenotypic and phylogenetic matrices. The genetic correlation structure for D. dubia, however, does not correspond with patterns found in the phenotypic and phylogenetic data. Possible reasons for this disagreement are discussed.
The utility of morphological data in modern systematics has recently been challenged because strong selection pressures are thought to create widespread patterns of convergent evolution at this level. This concern has led to suggestions that morphological data should be excluded either from all analyses or at least from analyses where there is conflict with molecular data. These concerns, however, are generally unwarranted and excluding data is not a defensible strategy for dealing with problems that do exist. We emphasize the importance of empirical responses, such as collecting additional and diverse data and exploring taxa and data set interactions, rather than the implementation of a priori assumptions, to overcoming many of the concerns associated with combining morphological and molecular data. Numerous factors may create biases in both molecules and morphology. While these biases are prevalent enough to cause widespread incongruence, they highlight the importance of combining, rather than separating, data. Morphological data also offer distinct advantages over molecular data, such as the inclusion of fossil taxa, cost-effectiveness and presence of biases different from those in molecular data.