943 resultados para Bayesian phylogeny


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Paratelmatobius and Scythrophrys are leptodactylid frogs endemic to the Brazilian Atlantic forest and their close phylogenetic relationship was recently inferred in an analysis that included Paratelmatobius sp. and S. sawayae. To investigate the interspecific relationships among Paratelmatobius and Scythrophrys species, we analyzed a mitochondrial region (approximately 2.4 kb) that included the ribosomal genes 12S and 16S and the tRNAval in representatives of all known localities of these genera and in 54 other species. Maximum parsimony inferences were done using PAUP* and support for the clades was evaluated by bootstrapping. A cytogenetic analysis using Giemsa staining, C-banding and silver staining was also done for those populations of Paratelmatobius not included in previous cytogenetic studies of this genus in order to assess their karyotype differentiation. Our results suggested Paratelmatobius and Scythrophrys formed a clade strongly supported by bootstrapping, which corroborated their very close phylogenetic relationship. Among the Paratelmatobius species, two clades were identified and corroborated the groups P. mantiqueira and P. cardosoi previously proposed based on morphological characters. The karyotypes of Paratelmatobius sp. 2 and Paratelmatobius sp. 3 described here had diploid chromosome number 2n = 24 and showed many similarities with karyotypes of other Paratelmatobius representatives. The cytogenetic data and the phylogenetic analysis allowed the proposal/corroboration of several hypotheses for the karyotype differentiation within Paratelmatobius and Scythrophrys. Namely the telocentric pair No. 4 represented a synapomorphy of P. cardosoi and Paratelmatobius sp. 2, while chromosome pair No. 5 with interstitial C-bands could be interpreted as a synapomorphy of the P. cardosoi group. The NOR-bearing chromosome No. 10 in the karyotype of P. poecilogaster was considered homeologous to chromosome No. 10 in the karyotype of Scythrophrys sp., chromosome No. 9 in the karyotype of Paratelmatobius sp. 1, chromosome No. 8 in the karyotypes of Paratelmatobius sp. 2 and of Paratelmatobius sp. 3, and chromosome No. 7 in the karyotype of P. cardosoi. A hypothesis for the evolutionary divergence of these NOR-bearing chromosomes, which probably involved events like gain in heteochromatin, was proposed.

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Wiens (2007, Q. Rev. Biol. 82, 55-56) recently published a severe critique of Frost et al.'s (2006, Bull. Am. Mus. Nat. Hist. 297, 1-370) monographic study of amphibian systematics, concluding that it is a disaster and recommending that readers simply ignore this study. Beyond the hyperbole, Wiens raised four general objections that he regarded as fatal flaws: (1) the sampling design was insufficient for the generic changes made and taxonomic changes were made without including all type species; (2) the nuclear gene most commonly used in amphibian phylogenetics, RAG-1, was not included, nor were the morphological characters that had justified the older taxonomy; (3) the analytical method employed is questionable because equally weighted parsimony assumes that all characters are evolving at equal rates; and (4) the results were at times clearly erroneous, as evidenced by the inferred non-monophyly of marsupial frogs. In this paper we respond to these criticisms. In brief: (1) the study of Frost et al. did not exist in a vacuum and we discussed our evidence and evidence previously obtained by others that documented the non-monophyletic taxa that we corrected. Beyond that, we agree that all type species should ideally be included, but inclusion of all potentially relevant type species is not feasible in a study of the magnitude of Frost et al. and we contend that this should not prevent progress in the formulation of phylogenetic hypotheses or their application outside of systematics. (2) Rhodopsin, a gene included by Frost et al. is the nuclear gene that is most commonly used in amphibian systematics, not RAG-1. Regardless, ignoring a study because of the absence of a single locus strikes us as unsound practice. With respect to previously hypothesized morphological synapomorphies, Frost et al. provided a lengthy review of the published evidence for all groups, and this was used to inform taxonomic decisions. We noted that confirming and reconciling all morphological transformation series published among previous studies needed to be done, and we included evidence from the only published data set at that time to explicitly code morphological characters (including a number of traditionally applied synapomorphies from adult morphology) across the bulk of the diversity of amphibians (Haas, 2003, Cladistics 19, 23-90). Moreover, the phylogenetic results of the Frost et al. study were largely consistent with previous morphological and molecular studies and where they differed, this was discussed with reference to the weight of evidence. (3) The claim that equally weighted parsimony assumes that all characters are evolving at equal rates has been shown to be false in both analytical and simulation studies. (4) The claimed strong support for marsupial frog monophyly is questionable. Several studies have also found marsupial frogs to be non-monophyletic. Wiens et al. (2005, Syst. Biol. 54, 719-748) recovered marsupial frogs as monophyletic, but that result was strongly supported only by Bayesian clade confidence values (which are known to overestimate support) and bootstrap support in his parsimony analysis was < 50%. Further, in a more recent parsimony analysis of an expanded data set that included RAG-1 and the three traditional morphological synapomorphies of marsupial frogs, Wiens et al. (2006, Am. Nat. 168, 579-596) also found them to be non-monophyletic.Although we attempted to apply the rule of monophyly to the naming of taxonomic groups, our phylogenetic results are largely consistent with conventional views even if not wth the taxonomy current at the time of our writing. Most of our taxonomic changes addressed examples of non-monophyly that had previously been known or suspected (e.g., the non-monophyly of traditional Hyperoliidae, Microhylidae, Hemiphractinae, Leptodactylidae, Phrynobatrachus, Ranidae, Rana, Bufo; and the placement of Brachycephalus within Eleutherodactylus, and Lineatriton within Pseudoeurycea), and it is troubling that Wiens and others, as evidenced by recent publications, continue to perpetuate recognition of non-monophyletic taxonomic groups that so profoundly misrepresent what is known about amphibian phylogeny. (C) The Willi Hennig Society 2007.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Um modelo bayesiano de regressão binária é desenvolvido para predizer óbito hospitalar em pacientes acometidos por infarto agudo do miocárdio. Métodos de Monte Carlo via Cadeias de Markov (MCMC) são usados para fazer inferência e validação. Uma estratégia para construção de modelos, baseada no uso do fator de Bayes, é proposta e aspectos de validação são extensivamente discutidos neste artigo, incluindo a distribuição a posteriori para o índice de concordância e análise de resíduos. A determinação de fatores de risco, baseados em variáveis disponíveis na chegada do paciente ao hospital, é muito importante para a tomada de decisão sobre o curso do tratamento. O modelo identificado se revela fortemente confiável e acurado, com uma taxa de classificação correta de 88% e um índice de concordância de 83%.

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In this work we compared the estimates of the parameters of ARCH models using a complete Bayesian method and an empirical Bayesian method in which we adopted a non-informative prior distribution and informative prior distribution, respectively. We also considered a reparameterization of those models in order to map the space of the parameters into real space. This procedure permits choosing prior normal distributions for the transformed parameters. The posterior summaries were obtained using Monte Carlo Markov chain methods (MCMC). The methodology was evaluated by considering the Telebras series from the Brazilian financial market. The results show that the two methods are able to adjust ARCH models with different numbers of parameters. The empirical Bayesian method provided a more parsimonious model to the data and better adjustment than the complete Bayesian method.

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A molecular phylogenetic analysis of the Hyla pulchella species group was performed to test its monophyly, explore the interrelationships of its species, and evaluate the validity of the taxa that were considered subspecies of H. pulchella. Approximately 2.8 kb from the mitochondrial genes 12s, tRNA valine, 16s, and Cytochrome b were sequenced. The analysis included 50 terminals representing 10 of the 14-15 species currently recognized in the H. pulchella group, including samples from several localities for some taxa, several outgroups, as well as two species previously suspected to be related with the group (Hyla guentheri and Hyla hischoffi). The results show that the H. pulchella and Hyla circumdata groups are distantly related, and, therefore, should be recognized as separate groups. As currently defined, the H. pulchella group is paraphyletic with respect to the Hyla polytaenia group; therefore, we recognize the Hyla polytaenia clade in the H. pulchella group. Two subspecies of H. pulchella recognized by some authors are considered full species including Hyla pulchella riojana because it is only distantly related to H. pulchella, and Hyla pulchella cordobae because molecular and non-molecular evidence suggests that it is specifically distinct. With the inclusion of the H. polytaenia clade, H. guentheri, and H. bischoffi, and the recognition of the two former subspecies of H. pulchella as distinct species, the H. pulchella group now comprises 25 described species. All representatives of the H. pulchella group with an Andean distribution are monophyletic and nested within a clade from the Atlantic forest from south-southeastern Brazil/northeastern Argentina, and Cerrado gallery forest from central Brazil. (C) 2004 Elsevier B.V. All rights reserved.

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Several statistical models can be used for assessing genotype X environment interaction (GEI) and studying genotypic stability. The objectives of this research were to show how (i) to use Bayesian methodology for computing Shukla's phenotypic stability variance and (ii) to incorporate prior information on the parameters for better estimation. Potato [Solanum tuberosum subsp. andigenum (Juz. & Bukasov) Hawkes], wheat (Triticum aestivum L.), and maize (Zea mays L.) multi environment trials (MET) were used for illustrating the application of the Bayes paradigm. The potato trial included 15 genotypes, but prior information for just three genotypes was used. The wheat trial used prior information on all 10 genotypes included in the trial, whereas for the maize trial, noninformative priors for the nine genotypes was used. Concerning the posterior distribution of the genotypic means, the maize MET with 20 sites gave less disperse posterior distributions of the genotypic means than did the posterior distribution of the genotypic means of the other METs, which included fewer environments. The Bayesian approach allows use of other statistical strategies such as the normal truncated distribution (used in this study). When analyzing grain yield, a lower bound of zero and an upper bound set by the researcher's experience can be used. The Bayesian paradigm offers plant breeders the possibility of computing the probability of a genotype being the best performer. The results of this study show that although some genotypes may have a very low probability of being the best in all sites, they have a relatively good chance of being among the five highest yielding genotypes.

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The first quantitative analysis of phylogenetic relationships of green lacewings (Chrysopidae) is presented based on DNA sequence data. A single nuclear and two mitochondrial genes are used in the analysis: carbomoylphosphate synthase (CPS) domain of carbamoyl-phosphate synthetase-aspartate transcarbamoylase-dihydroorotase (CAD) (i.e. rudimentary locus), large subunit ribosomal gene (16S) and cytochrome oxidase I (COI). This study represents the first use of the CAD gene to investigate phylogenetic relationships of the lacewings. DNA sequences for 33 chrysopid species from 18 genera, representing all subfamilies and tribes, were compared with outgroups sampled from families Hemerobiidae, Osmylidae and Polystoechotidae. Parsimony analyses of the combined data set recovered all of the previously established subfamilial and tribal groups as monophyletic clades (although relatively weakly supported) except Apochrysinae sensu lato. The enigmatic Nothancyla verreauxi Navas has historically been difficult to place in a subfamily group based on morphological characteristics; molecular data presented herein do not adequately resolve this problem.

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Linear mixed effects models are frequently used to analyse longitudinal data, due to their flexibility in modelling the covariance structure between and within observations. Further, it is easy to deal with unbalanced data, either with respect to the number of observations per subject or per time period, and with varying time intervals between observations. In most applications of mixed models to biological sciences, a normal distribution is assumed both for the random effects and for the residuals. This, however, makes inferences vulnerable to the presence of outliers. Here, linear mixed models employing thick-tailed distributions for robust inferences in longitudinal data analysis are described. Specific distributions discussed include the Student-t, the slash and the contaminated normal. A Bayesian framework is adopted, and the Gibbs sampler and the Metropolis-Hastings algorithms are used to carry out the posterior analyses. An example with data on orthodontic distance growth in children is discussed to illustrate the methodology. Analyses based on either the Student-t distribution or on the usual Gaussian assumption are contrasted. The thick-tailed distributions provide an appealing robust alternative to the Gaussian process for modelling distributions of the random effects and of residuals in linear mixed models, and the MCMC implementation allows the computations to be performed in a flexible manner.