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635 results for “comparative phylogenetics”
Data from: Detecting adaptive evolution in phylogenetic comparative analysis using the Ornstein-Uhlenbeck model
Phylogenetic comparative analysis is an approach to inferring evolutionary process from a combination of phylogenetic and phenotypic data. The last few years have seen increasingly sophisticated models employed in the evaluation of more and more detailed evolutionary hypotheses, including adaptive hypotheses with multiple selective optima and hypotheses with rate variation within and across lineages. The statistical performance of these sophisticated models has received relatively little systematic attention, however. We conducted an extensive simulation study to quantify the statistical properties of a class of models toward the simpler end of the spectrum that model phenotypic evolution using Ornstein–Uhlenbeck processes. We focused on identifying where, how, and why these methods break down so that users can apply them with greater understanding of their strengths and weaknesses. Our analysis identifies three key determinants of performance: a discriminability ratio, a signal-to-noise ratio, and the number of taxa sampled. Interestingly, we find that model-selection power can be high even in regions that were previously thought to be difficult, such as when tree size is small. On the other hand, we find that model parameters are in many circumstances difficult to estimate accurately, indicating a relative paucity of information in the data relative to these parameters. Nevertheless, we note that accurate model selection is often possible when parameters are only weakly identified. Our results have implications for more sophisticated methods inasmuch as the latter are generalizations of the case we study.
Data from: The local-clock permutation test: a simple test to compare rates of molecular evolution on phylogenetic trees
Rates of molecular evolution vary substantially between lineages, and a growing research effort is directed at uncovering the causes and consequences of this variation. Comparing local-clocks (rates of molecular evolution estimated from sets of branches of a phylogenetic tree) is a common tool in this research effort. Here, I show that a commonly used test (the Likelihood Ratio Test, LRT) will not be statistically valid for comparing local-clocks in most cases. Instead, I propose the local-clock permutation test (LCPT), a simple test which can be used to test the significance of differences between local-clocks. The LCPT could also be used to test for differences between any parameter that can be assigned to individual branches on a phylogenetic tree. Using simulated data, I show that the LCPT has good power to detect differences between local-clocks.
Supplementary material 1 from: Sun C-H, Huang Q, Zeng X-S, Li S, Zhang X-L, Zhang Y-N, Liao J, Lu C-H, Han B-P, Zhang Q (2022) Comparative analysis of the mitogenomes of two Corydoras (Siluriformes, Loricarioidei) with nine known Corydoras, and a phylogenetic analysis of Loricarioidei. ZooKeys 1083: 89-107. https://doi.org/10.3897/zookeys.1083.76887
COI sequences of Corydoras aeneus and C. paleatus Tables S1–S4, Figs S1–S4
Figure 2 from: Sun C-H, Huang Q, Zeng X-S, Li S, Zhang X-L, Zhang Y-N, Liao J, Lu C-H, Han B-P, Zhang Q (2022) Comparative analysis of the mitogenomes of two Corydoras (Siluriformes, Loricarioidei) with nine known Corydoras, and a phylogenetic analysis of Loricarioidei. ZooKeys 1083: 89-107. https://doi.org/10.3897/zookeys.1083.76887
Figure 2 K2P genetic distance a nucleotide diversity b Ka/Ks ratio c analyses of protein-coding genes among the eleven Corydoras mitogenomes.
Figure 3 from: Sun C-H, Huang Q, Zeng X-S, Li S, Zhang X-L, Zhang Y-N, Liao J, Lu C-H, Han B-P, Zhang Q (2022) Comparative analysis of the mitogenomes of two Corydoras (Siluriformes, Loricarioidei) with nine known Corydoras, and a phylogenetic analysis of Loricarioidei. ZooKeys 1083: 89-107. https://doi.org/10.3897/zookeys.1083.76887
Figure 3 Phylogenetic trees of 44 Siluriformes species using concatenated nucleotide sequences of 13 protein-coding genes and two rRNAs using the maximum likelihood method. Numbers in the ML tree represent SH-aLRT support/ultrafast bootstrap support values.
Figure 4 from: Sun C-H, Huang Q, Zeng X-S, Li S, Zhang X-L, Zhang Y-N, Liao J, Lu C-H, Han B-P, Zhang Q (2022) Comparative analysis of the mitogenomes of two Corydoras (Siluriformes, Loricarioidei) with nine known Corydoras, and a phylogenetic analysis of Loricarioidei. ZooKeys 1083: 89-107. https://doi.org/10.3897/zookeys.1083.76887
Figure 4 Phylogenetic tree of 44 Siluriformes species using concatenated nucleotide sequences of 13 protein-coding genes and two rRNAs via the Bayesian interference method. Applicable posterior probability values are shown.
Figure 9 from: Chen Z-T (2022) Comparative mitogenomic analysis of two earwigs (Insecta, Dermaptera) and the preliminary phylogenetic implications. ZooKeys 1087: 105-122. https://doi.org/10.3897/zookeys.1087.78998
Figure 9 Predicted structural elements in the control regions of Challia fletcheri, Euborellia arcanum, Eudohrnia metallica, and Paratimomenus flavocapitatus.
Figure 4 from: Chen Z-T (2022) Comparative mitogenomic analysis of two earwigs (Insecta, Dermaptera) and the preliminary phylogenetic implications. ZooKeys 1087: 105-122. https://doi.org/10.3897/zookeys.1087.78998
Figure 4 Evolutionary rates of PCGs in six species of earwigs. The bar indicates each gene's Ka/Ks value.
Figure 5 from: Chen Z-T (2022) Comparative mitogenomic analysis of two earwigs (Insecta, Dermaptera) and the preliminary phylogenetic implications. ZooKeys 1087: 105-122. https://doi.org/10.3897/zookeys.1087.78998
Figure 5 Secondary structures of tRNA genes in the mitogenome of Apachyus feae. Mismatched base pairs are indicated by red circles; reduced arms are indicated by red arrowheads.
Figure 6 from: Chen Z-T (2022) Comparative mitogenomic analysis of two earwigs (Insecta, Dermaptera) and the preliminary phylogenetic implications. ZooKeys 1087: 105-122. https://doi.org/10.3897/zookeys.1087.78998
Figure 6 Secondary structures of tRNA genes in the mitogenome of Diplatys flavicollis. Mismatched base pairs are indicated by red circles; reduced arms are indicated by red arrowheads.
Figure 1 from: Chen Z-T (2022) Comparative mitogenomic analysis of two earwigs (Insecta, Dermaptera) and the preliminary phylogenetic implications. ZooKeys 1087: 105-122. https://doi.org/10.3897/zookeys.1087.78998
Figure 1 Mitochondrial maps of Apachyus feae and Diplatys flavicollis. Genes outside the map are transcribed clockwise, whereas those inside the map are transcribed counterclockwise. Names and other details of the genes are listed in Tables 2 and 3. The inside circles show the GC content and the GC skew. GC content and GC skew are plotted as the deviation from the average value of the entire sequence.
Figure 10 from: Chen Z-T (2022) Comparative mitogenomic analysis of two earwigs (Insecta, Dermaptera) and the preliminary phylogenetic implications. ZooKeys 1087: 105-122. https://doi.org/10.3897/zookeys.1087.78998
Figure 10 Phylogenetic relationships within Dermaptera inferred by Bayesian inference and maximum likelihood analysis. Numbers at the nodes are posterior probabilities (left) and bootstrap values (right). The family names are listed after the species. Infraorders and parvorders are indicated below each family name.
Supplementary material 6 from: Yang C, Du X, Liu Y, Yuan H, Wang Q, Hou X, Gong H, Wang Y, Huang Y, Li X, Ye H (2022) Comparative mitogenomics of the genus Motacilla (Aves, Passeriformes) and its phylogenetic implications. ZooKeys 1109: 49-65. https://doi.org/10.3897/zookeys.1109.81125
Figure S6
Supplementary material 2 from: Yang C, Du X, Liu Y, Yuan H, Wang Q, Hou X, Gong H, Wang Y, Huang Y, Li X, Ye H (2022) Comparative mitogenomics of the genus Motacilla (Aves, Passeriformes) and its phylogenetic implications. ZooKeys 1109: 49-65. https://doi.org/10.3897/zookeys.1109.81125
Figure S2
Supplementary material 1 from: Yang C, Du X, Liu Y, Yuan H, Wang Q, Hou X, Gong H, Wang Y, Huang Y, Li X, Ye H (2022) Comparative mitogenomics of the genus Motacilla (Aves, Passeriformes) and its phylogenetic implications. ZooKeys 1109: 49-65. https://doi.org/10.3897/zookeys.1109.81125
Figure S1
Supplementary material 5 from: Yang C, Du X, Liu Y, Yuan H, Wang Q, Hou X, Gong H, Wang Y, Huang Y, Li X, Ye H (2022) Comparative mitogenomics of the genus Motacilla (Aves, Passeriformes) and its phylogenetic implications. ZooKeys 1109: 49-65. https://doi.org/10.3897/zookeys.1109.81125
Figure S5
Supplementary material 9 from: Yang C, Du X, Liu Y, Yuan H, Wang Q, Hou X, Gong H, Wang Y, Huang Y, Li X, Ye H (2022) Comparative mitogenomics of the genus Motacilla (Aves, Passeriformes) and its phylogenetic implications. ZooKeys 1109: 49-65. https://doi.org/10.3897/zookeys.1109.81125
Table S3
Supplementary material 7 from: Yang C, Du X, Liu Y, Yuan H, Wang Q, Hou X, Gong H, Wang Y, Huang Y, Li X, Ye H (2022) Comparative mitogenomics of the genus Motacilla (Aves, Passeriformes) and its phylogenetic implications. ZooKeys 1109: 49-65. https://doi.org/10.3897/zookeys.1109.81125
Table S1
Supplementary material 8 from: Yang C, Du X, Liu Y, Yuan H, Wang Q, Hou X, Gong H, Wang Y, Huang Y, Li X, Ye H (2022) Comparative mitogenomics of the genus Motacilla (Aves, Passeriformes) and its phylogenetic implications. ZooKeys 1109: 49-65. https://doi.org/10.3897/zookeys.1109.81125
Table S2
Supplementary material 4 from: Yang C, Du X, Liu Y, Yuan H, Wang Q, Hou X, Gong H, Wang Y, Huang Y, Li X, Ye H (2022) Comparative mitogenomics of the genus Motacilla (Aves, Passeriformes) and its phylogenetic implications. ZooKeys 1109: 49-65. https://doi.org/10.3897/zookeys.1109.81125
Figure S4
ScienceDex guides
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.