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161 results for “Bayesian phylogenetics”
Dataset of the article "Bayesian phylogenetics illuminate shallower relationships in Trans-Himalayan languages in Tibet-Arunachal area"
<p>This repository archives the dataset of the article "Bayesian phylogenetics illuminate shallower relationships in Trans-Himalayan languages in Tibet-Arunachal area". The cognate annotation of Tshangla, Kho-Bwa, Hrusish, Mishmic, and Tani languages were done by us. The cognate decision on the other languages was annotated by Sagart et al. (2019). Please use the following information to cite our work: <br> Wu, M.-S, Bodt, T. A, Tresoldi, T. (2022). Bayesian phylogenetics illuminate shallower relationships Trans-Himalayan languages in the Tibet-Arunachal area. Linguistics of the Tibeto-Burman Area. [forthcoming]</p>
Phlorest phylogeny derived from Kolipakam et al. 2018 'A Bayesian phylogenetic study of the Dravidian language family'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Kolipakam V, Jordan FM, Dunn M, Greenhill SJ, Bouckaert R, Gray RD & Verkerk A. 2018. A Bayesian phylogenetic study of the Dravidian language family. R. Soc. Open Sci. 5: 171504.</p> </blockquote>
Phlorest phylogeny derived from Kitchen et al. 2009 'Bayesian phylogenetic analysis of Semitic languages identifies an Early Bronze Age origin of Semitic in the Near East'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Kitchen A, Ehret C, Assefa S & Mulligan CJ. 2009. Bayesian phylogenetic analysis of Semitic languages identifies an Early Bronze Age origin of Semitic in the Near East. Proceedings of the Royal Society B: Biological Sciences, 270(1668), 2703-2710.</p> </blockquote>
Phlorest phylogeny derived from Lee & Hasegawa 2011 'Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Lee S, Hasegawa T (2011) Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages. Proceedings of the Royal Society B: Biological Sciences, 278(1725):3662–9.</p> </blockquote>
CLDF dataset derived from Lee and Hasegawa's "Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages" from 2011
<p>Cite the source of the dataset as:</p> <blockquote> <p>Lee, Sean and Hasegawa, Toshikazu (2011). Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages. Proceedings of the Royal Society B: Biological Sciences, 278(1725), 3662–3669. doi:10.1098/rspb.2011.0518.</p> </blockquote>
Supplementary Materials to "Subgrouping in a `dialect continuum': A Bayesian phylogenetic analysis of the Mixtecan language family"
<p>SM0: metadata on the languages of the sample</p> <p>SM 1: custom word list</p> <p>SM2: prose explanation of cognate coding and IPA conversion</p> <p>SM3: annotated cognate sets</p> <p>SM4: nexus files of the broad and fine grained cognate coding</p> <p>SM5: NeighborNet visualization with coloring by Josserand (1983)'s groupings and by groupings from our analysis</p> <p>SM6: BEAST2 xml files</p> <p>SM7: MCC trees from BEAST2 analysis</p> <p>SM8: DensiTree visualization and visualization of full MCC tree of best performing model</p>
Phlorest phylogeny derived from Michael et al. 2015 'A Bayesian Phylogenetic Classification of Tupi-Guarani'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Michael L, Chousou-Polydouri N, Bartolomei K, Donnelly E, Wauters V, Meira S & O'Hagan Z. 2015. A Bayesian Phylogenetic Classification of Tupi-Guarani. LIAMES 15(2):1–36.</p> </blockquote>
Fig. 1. Bayesian majority rule consensus tree reconstructed for 90 in Phylogenetic analysis and systematic position of two new species of the ant genus Crematogaster (Hymenoptera, Formicidae) from Southeast Asia
Fig. 1. Bayesian majority rule consensus tree reconstructed for 90 taxa using five genes (ArgK, CAD, LWRh, Top1, Wg) in a MrBayes analysis. Above node numbers indicate posterior probability. Data were partitioned by PartitionFinder v.1.1.1 and analyzed using a best fit model for each gene and codon position, with 10 million generations and a burn-in of 25 %. Area enclosed by dashed lines is enlarged on Fig. 2.
Figure 1. Bayesian phylogenetic tree inferred from the 640 in Two new Geoplaninae species (Platyhelminthes: Continenticola) from Southern Brazil based on an integrative taxonomic approach
Figure 1. Bayesian phylogenetic tree inferred from the 640-bp of cytochrome c oxidase subunit I gene under GTR + I + G model of sequence evolution. The two new species are highlighted in light grey (Cratera ochra sp. nov.) and dark grey (Obama maculipunctata sp. nov.). Values indicate support for each node according to the maximum posterior probabilities>70% and bootstrap support values> 70%, respectively.
Anatomical partitioning has little influence in topologies from Bayesian phylogenetic analyses of morphological data
<p>Morphological data is a fundamental source of evidence to reconstruct the Tree of Life, and Bayesian phylogenetic methods are increasingly being used for this task, along with, or instead of, traditional parsimony approaches. Bayesian phylogenetic analyses require the use of proper evolutionary models and their performance have been intensively studied in the past few years, with significant improvements to our knowledge regarding their performance. Notwithstanding, it was only recently that partitioned models for morphology received attention in studies of empirical data, but a systematic evaluation of its performances using simulations was never performed. Here we evaluate the influence of partitioned models defined by anatomical criterion in the precision and accuracy of consensus tree topologies, evaluating the possible negative effects of under and overpartitioning. For that, we analysed datasets simulated using parameters and properties of two empirical datasets, using Bayesian phylogenetic analyses in MrBayes. Additionally, we reanalysed 32 empirical datasets for diverse groups of vertebrates, applying unpartitioned and partitioned models. We found that in general, partitioning by anatomy has little to no influences in the performance of Bayesian phylogenetic methods in respect to the metrics studied here, with analyses under alternative partitioning schemes presenting very similar tree precision and accuracy. We discuss the possible reasons for the disagreement between the results obtained here and previous studies for empirical morphological data, and with empirical and simulation studies of molecular data, discussing the adequacy of anatomical partitioning relative to alternative methods to partition morphological datasets and how morphological and molecular partitioning are related.</p>
CLDF dataset derived from Kitchen et al.'s "Bayesian phylogenetic analysis of Semitic languages" from 2009
<p>Cite the source of the dataset as:</p> <blockquote> <p>Bayesian phylogenetic analysis of Semitic languages identifies an Early Bronze Age origin of Semitic in the Near East. Andrew Kitchen, Christopher Ehret, Shiferaw Assefa, Connie J. Mulligan. Proc. R. Soc. B 2009 -; DOI: 10.1098/rspb.2009.0408. Published 29 April 2009</p> </blockquote>
FIGURE 4 Phylogenetic relationships within the genus Longidorus. Bayesian 50 in Molecular phylogenetic analysis and comparative morphology reveals the diversity and distribution of needle nematodes of the genus Longidorus (Dorylaimida: Longidoridae) from Spain
FIGURE 4 Phylogenetic relationships within the genus Longidorus. Bayesian 50% majority rule consensus tree as inferred from cytochrome c oxidase subunit I (CoxI) mtDNA gene sequence alignment under the general time-reversible model of sequence evolution with correction for invariable sites and a gammashaped distribution (GTR + I + G). Posterior probabilities greater than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site.
FIGURE 3 Phylogenetic relationships within the genus Longidorus. Bayesian 50 in Molecular phylogenetic analysis and comparative morphology reveals the diversity and distribution of needle nematodes of the genus Longidorus (Dorylaimida: Longidoridae) from Spain
FIGURE 3 Phylogenetic relationships within the genus Longidorus. Bayesian 50% majority rule consensus tree as inferred from 18S rRNA gene sequence alignment under a transitional model with invariable sites and a gamma correction (TIM 2 + I + G). Posterior probabilities greater Downloaded than 0.70 from are Brill given.comfor08/29/ appropriate 2023 05:44:51PM clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changesvia per site free. access
FIGURE 1 Phylogenetic relationships within the genus Longidorus. Bayesian 50 in Molecular phylogenetic analysis and comparative morphology reveals the diversity and distribution of needle nematodes of the genus Longidorus (Dorylaimida: Longidoridae) from Spain
FIGURE 1 Phylogenetic relationships within the genus Longidorus. Bayesian 50% majority rule consensus tree as inferred from D2 and D3 expansion domains of 28S rRNA sequence alignment under an SYM model with invariable sites and a gamma-shaped distribution (SYM + I + G). Posterior probabilities greater than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site. ** = Branches collapsed, indicating clustered Longidorus species. For a more specific detail of collapsed clades, see supplementary fig. S1.
FIGURE 2 Phylogenetic relationships within the genus Longidorus. Bayesian 50 in Molecular phylogenetic analysis and comparative morphology reveals the diversity and distribution of needle nematodes of the genus Longidorus (Dorylaimida: Longidoridae) from Spain
FIGURE 2 Phylogenetic relationships within the genus Longidorus. Bayesian 50% majority rule consensus tree as inferred from ITS1 rRNA sequence alignment under a 3-parameter model with invariable sites and a gamma-shaped distribution (TPM3 µf + I + G). Posterior probabilities greater than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site. Downloaded from Brill.com08/29/2023 05:44:51PM via free access
FI GU R E 3 Maximum likelihood phylogenetic tree of the Hyalospheniformes with a focus on Apodera, Alocodera, and Padaungiella based on COI gene sequences. Bootstrap values (bs) and Bayesian posterior probabilities (p.p.) are indicated respectively between branches. COI sequences from genera other than Apodera were retrieved from GenBank in Superficially described and ignored for 92 years, rediscovered and emended: Apodera angatakere (Amoebozoa: Arcellinida: Hyalospheniformes) is a new flagship testate amoeba taxon from Aotearoa (New Zealand)
FI GU R E 3 Maximum likelihood phylogenetic tree of the Hyalospheniformes with a focus on Apodera, Alocodera, and Padaungiella based on COI gene sequences. Bootstrap values (bs) and Bayesian posterior probabilities (p.p.) are indicated respectively between branches. COI sequences from genera other than Apodera were retrieved from GenBank
Fig. 1. – Bayesian 50 in Description and phylogenetic position of a new species of Nematanthus (Gesneriaceae) from Bahia, Brazil
Fig. 1. – Bayesian 50 % majority rule consensus tree of Nematanthus resulting from the combined analysis of plastid loci atpB-rbcL, matK, rps16, rpl16, trnT-trnL, trnL-trnF, trnS-trnG, and the nuclear regions ncpGS and ITS. Numbers above branches are Bayesian posterior probabilities. Numbers below branches are maximum likelihood bootstrap when ≥50 %. Asterisks indicate species with funnel-shaped and laterally compressed corollas.
Fig. 6. Bayesian inference tree for 5519 in First Record of Poecilobdella nanjingensis (Hirudinida: Arhynchobdellida: Hirudinidae) from Taiwan and its Molecular Phylogenetic Position within the Family
Fig. 6. Bayesian inference tree for 5519 bp alignment positions of nuclear 18S rRNA, 28S rRNA, mitochondrial cytochrome c oxidase subunit I, and 12S rRNA markers. Numbers on nodes indicate bootstrap values for maximum likelihood and Bayesian inference posterior probabilities.
Fig. 1. – Bayesian 50 in Description and phylogenetic position of a new species of Nematanthus (Gesneriaceae) from Bahia, Brazil
Fig. 1. – Bayesian 50% majority rule consensus tree of Nematanthus resulting from the combined analysis of plastid loci atpB-rbcL, matK, rps16, rpl16, trnT-trnL, trnL-trnF, trnS-trnG, and the nuclear regions ncpGS and ITS. Numbers above branches are Bayesian posterior probabilities. Numbers below branches are maximum likelihood bootstrap when ≥50 %. Asterisks indicate species with funnel-shaped and laterally compressed corollas.
Figure 5. Bayesian Inference tree calculated with complete cox1 in Novel phylogenetic clade of avian Haemoproteus parasites (Haemosporida, Haemoproteidae) from Accipitridae raptors, with description of a new Haemoproteus species
Figure 5. Bayesian Inference tree calculated with complete cox1 (1428 bp), cox3 (753 bp), and cytb (1127 bp) sequences of haemosporidian parasites and Klossiella equi (MH203050) and Klossia razorbacki (MT084562) as the outgroup. Bayesian posterior probabilities and Maximum Likelihood bootstrap values are indicated at most nodes. The scale bar indicates the expected number of substitutions per site according to the model of sequence evolution applied.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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