Phylogenetics: The Theory and Practice of Phylogenetic Systematics.

Wiley, E. O.; Lieberman, Bruce S.

doi:10.2307/2413420

Cited by 286 publications

(280 citation statements)

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“…In contrast, balance statistics such as Colless' index (Colless, 1982), which considers the average balance of the tree across all internal nodes, are less suited for population genetic applications, since balance at lower nodes can usually not be estimated from sequence data, due to the paucity of polymorphisms which separate closely related sequences. Furthermore, recombination affects mostly the lower part of the tree, hence it introduces additional noise preventing accurate reconstruction of its topology.…”

Section: Discussionmentioning

confidence: 99%

Decomposing the Site Frequency Spectrum: The Impact of Tree Topology on Neutrality Tests

et al. 2017

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We investigate the dependence of the site frequency spectrum (SFS) on the topological structure of genealogical trees. We show that basic population genetic statistics -for instance estimators of θ or neutrality tests such as Tajima's D -can be decomposed into components of waiting times between coalescent events and of tree topology. Our results clarify the relative impact of the two components on these statistics. We provide a rigorous interpretation of positive or negative values of an important class of neutrality tests in terms of the underlying tree shape. In particular, we show that values of Tajima's D and Fay and Wu's H depend in a direct way on a peculiar measure of tree balance which is mostly determined by the root * Email: luca.ferretti@gmail.com 1 arXiv:1510.06748v2 [q-bio.PE] 12 Jan 2017 balance of the tree. We present a new test for selection in the same class as Fay and Wu's H and discuss its interpretation and power. Finally, we determine the trees corresponding to extreme expected values of these neutrality tests and present formulae for these extreme values as a function of sample size and number of segregating sites.

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Section: Discussionmentioning

confidence: 99%

Decomposing the Site Frequency Spectrum: The Impact of Tree Topology on Neutrality Tests

et al. 2017

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“…To avoid this problem, Monte Carlo approximations of the distribution of whole-tree statistics are used in SYMMETREE. Six M statistics were used: M ⌸ , M* ⌸ , M ⌺ , M* ⌺ , and M R (Chan and Moore 2002;Moore et al 2004) as well as the Ic (Colless 1982) imbalance measure, which have different sensitivities depending on where the asymmetry is located in the tree. For example, the M R statistic is sensitive to large asymmetry, such as the ones found near the base of the tree.…”

Section: Diversification Assessmentsmentioning

confidence: 99%

Large Trees, Supertrees, and Diversification of the Grass Family

Hodkinson¹,

Salamin²,

Chase³

et al. 2007

aliso

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Phylogenetic studies of grasses (Poaceae) are advanced in comparison with most other angiosperm families. However, few studies have attempted to build large phylogenetic trees of the family and use these for evaluating patterns of diversification or other macroevolutionary hypotheses. Two contrasting approaches can be used to generate large trees: supermatrix analyses and supertrees. In this paper, we evaluated the suitability of each of these methods for the study of patterns and processes of evolution in the grasses. We collected data from DDBJ/EMBL/GenBank to determine sequence availability and asked how far we are from a complete generic-level phylogenetic tree of the grasses. We generated almost complete tribal-level supertrees (39 tribes) with over 400 genera using MRP methods, described their major clades, assessed their accuracy, and used them for the study of diversification. We generated a proportional supertree, by modifying the original supertree, to remove sampling bias associated with the original supertree that may affect diversification statistics. We used methods that incorporate information on the topological distribution of taxon diversity from all internal nodes of the phylogenetic tree to show that the grasses have experienced significant variations in diversification rates (M statistic P-values Ͻ0.001 for the original tree; Ͻ0.002 for the proportional tree) and show where on the trees significant shifts in diversification have occurred (seven shifts for the original tree; four shifts for the proportional tree). Such tests have not previously been attempted for the grasses, and we discuss future research directions in this area.

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“…Then, a multiple regression was used to analyze the number of eigenvalues (k) extracted from each cladogram and the proportion of variance (>1.%) explained by them, using as predictors the number of species (n) and two measurements related to cladogram topology: the coefficient of variation in branch lengths of the phylogeny (CVB) and an index of phylogeny asymmetry, or imbalance (1m). In this study, we followed Heard (1992) and estimated cladogram imbalance using a modification of Colless's (1982) index, corrected by sample sizes size and given by…”

Section: Datasets and Simulationsmentioning

confidence: 99%

An Eigenvector Method for Estimating Phylogenetic Inertia

Sant’Ana²,

1998

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Abstract.-We propose a new method to estimate and correct for phylogenetic inertia in comparative data analysis. The method, called phylogenetic eigenvector regression (PVR) starts by performing a principal coordinate analysis on a pairwise phylogenetic distance matrix between species. Traits under analysis are regressed on eigenvectors retained by a broken-stick model in such a way that estimated values express phylogenetic trends in data and residuals express independent evolution of each species. This partitioning is similar to that realized by the spatial autoregressive method, but the method proposed here overcomes the problem of low statistical performance that occurs with autoregressive method when phylogenetic correlation is low or when sample size is too small to detect it. Also, PVR is easier to perform with large samples because it is based on well-known techniques of multivariate and regression analyses. We evaluated the performance of PVR and compared it with the autoregressive method using real datasets and simulations. A detailed worked example using body size evolution of Carnivora mammals indicated that phylogenetic inertia in this trait is elevated and similarly estimated by both methods. In this example, Type I error at a = 0.05 of PVR was equal to 0.048, but an increase in the number of eigenvectors used in the regression increases the error. Also, similarity between PVR and the autoregressive method, defined by correlation between their residuals, decreased by overestimating the number of eigenvalues necessary to express the phylogenetic distance matrix. To evaluate the influence of c1adogram topology on the distribution of eigenvalues extracted from the double-centered phylogenetic distance matrix, we analyzed 100 randomly generated c1adograms (up to 100 species). Multiple linear regression of log transformed variables indicated that the number of eigenvalues extracted by the broken-stick model can be fully explained by c1adogram topology. Therefore, the broken-stick model is an adequate criterion for determining the correct number of eigenvectors to be used by PVR. We also simulated distinct levels of phylogenetic inertia by producing a trend across 10, 25, and 50 species arranged in "comblike" c1adograms and then adding random vectors with increased residual variances around this trend. In doing so, we provide an evaluation of the performance of both methods with data generated under different evolutionary models than tested previously. The results showed that both PVR and autoregressive method are efficient in detecting inertia in data when sample size is relatively high (more than 25 species) and when phylogenetic inertia is high. However, PVR is more efficient at smaller sample sizes and when level of phylogenetic inertia is low. These conclusions were also supported by the analysis of 10 real datasets regarding body size evolution in different animal clades. We concluded that PVR can be a useful alternative to an autoregressive method in comparative data analysis.

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Phylogenetics: The Theory and Practice of Phylogenetic Systematics.

Cited by 286 publications

References 0 publications

Decomposing the Site Frequency Spectrum: The Impact of Tree Topology on Neutrality Tests

Decomposing the Site Frequency Spectrum: The Impact of Tree Topology on Neutrality Tests

Large Trees, Supertrees, and Diversification of the Grass Family

An Eigenvector Method for Estimating Phylogenetic Inertia

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