22 resultados para Mixed model under selection

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.

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In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activation schemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer.

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Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

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In this paper, we propose a random intercept Poisson model in which the random effect is assumed to follow a generalized log-gamma (GLG) distribution. This random effect accommodates (or captures) the overdispersion in the counts and induces within-cluster correlation. We derive the first two moments for the marginal distribution as well as the intraclass correlation. Even though numerical integration methods are, in general, required for deriving the marginal models, we obtain the multivariate negative binomial model from a particular parameter setting of the hierarchical model. An iterative process is derived for obtaining the maximum likelihood estimates for the parameters in the multivariate negative binomial model. Residual analysis is proposed and two applications with real data are given for illustration. (C) 2011 Elsevier B.V. All rights reserved.

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The aim of this work was to evaluate the effect of cryopreservation protocols on subsequent development of in vitro produced bovine embryos under different culture conditions. Expanded in vitro produced blastocysts (n = 600) harvested on days 7-9 were submitted to controlled freezing [slow freezing group: 10% ethylene glycol (EG) for 10 min and 1.2 degrees C/min cryopreservation]; quick-freezing [rapid freezing group: 10% EG for 10 min, 20% EG + 20% glycerol (Gly) for 30 s]; or vitrification [vitrification group: 10% EG for 10 min, 25% EG + 25% Gly for 30 s] protocols. Control group embryos were not exposed to cryoprotectant or cryopreservation protocols and the hatching rate was evaluated on day 12 post-insemination. In order to evaluate development, frozen-thawed embryos were subjected to granulosa cell co-culture in TCM199 or SOFaa for 4 days. Data were analyzed by PROC MIXED model using SAS Systems for Windows (R). Values were significant at p < 0.05. The hatching rate of the control group was 46.09%. In embryos cultured in TCM199, slow freezing and vitrification group hatching rates were 44.65 +/- 5.94% and 9.43 +/- 6.77%, respectively. In embryos cultured in SOFaa, slow freezing and vitrification groups showed hatching rates of 11.65 +/- 3.37 and 8.67 +/- 4.47%, respectively. In contrast, the rapid freezing group embryos did not hatch, regardless of culture medium. The slow freezing group showed higher hatching rates than other cryopreservation groups. Under such conditions, controlled freezing (1.2 degrees C/min) can be an alternative to cryopreservation of in vitro produced bovine embryos.

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We address the problem of selecting the best linear unbiased predictor (BLUP) of the latent value (e.g., serum glucose fasting level) of sample subjects with heteroskedastic measurement errors. Using a simple example, we compare the usual mixed model BLUP to a similar predictor based on a mixed model framed in a finite population (FPMM) setup with two sources of variability, the first of which corresponds to simple random sampling and the second, to heteroskedastic measurement errors. Under this last approach, we show that when measurement errors are subject-specific, the BLUP shrinkage constants are based on a pooled measurement error variance as opposed to the individual ones generally considered for the usual mixed model BLUP. In contrast, when the heteroskedastic measurement errors are measurement condition-specific, the FPMM BLUP involves different shrinkage constants. We also show that in this setup, when measurement errors are subject-specific, the usual mixed model predictor is biased but has a smaller mean squared error than the FPMM BLUP which points to some difficulties in the interpretation of such predictors. (C) 2011 Elsevier By. All rights reserved.

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Os objetivos deste trabalho foram determinar o controle genético da eficiência no uso do nitrogênio (EUN), identificar a importância das eficiências na absorção (EAN) e na utilização (EUtN) na sua composição,  e quantificar relação entre produção de matéria seca da parte aérea (MPS) e do sistema radicular com a EUN e  com seus componentes. Foram avaliadas 41 combinações híbridas em duas disponibilidades de N: baixa (BN)  e alta (AN). Utilizou-se o delineamento de blocos ao acaso com duas repetições, em arranjo fatorial simples  (combinação híbrida x disponibilidade de N). As análises estatísticas foram realizadas por meio das equações  de modelos mistos. Correlações de elevada magnitude foram detectadas entre EAN e EUN, bem como entre  essas eficiências e a MPS, tanto em BN como em AN. Em ambas as disponibilidades de N, efeitos genéticos  aditivos apresentaram maior importância para os caracteres associados à EUN. Dessa forma, a seleção baseada  no desempenho individual de linhagens quanto à MPS pode possibilitar a obtenção de genótipos com alta  EUN. Independentemente da disponibilidade de N, a EAN é o componente mais importante da EUN.

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Background: Some studies have reported a decreased absorption of mycophenolic acid (MPA) from mycophenolate mofetil (MMF) in renal transplanted (RTx) patients under proton-pump inhibitors (PPIs). There is still a lack of information regarding (1) whether this effect occurs when MMF is administered with either tacrolimus or cyclosporine A [calcineurin inhibitors (CNIs)], (2) whether the effect has the same amplitude during the first year after RTx, and finally (3) whether this decrease in exposure is clinically relevant. Methods: We retrospectively analyzed the omeprazole effect in 348 12-hour pharmacokinetic samplings [area under the curve (AUC) 0-12h] performed on days 7, 14, 30, 60, 180, and 360 after RTx in 77 patients who participated in previous trials. Results: For all periods, the groups with and without PPI did not differ in all variables. By mixed-model analysis of variance, PPI reduced the MPA AUC(0-12h) (P < 0.0008) in the patients under both CNIs mainly due to decreased absorption (P = 0.049). In the tacrolimus group, a lower exposure seemed also due to a decreased MPA reabsorption at 10-12 hours. The PPI effect remains throughout the first year but was clinically more important on day 7. By Cox analysis, the use of PPI was associated with a 25% less chance of being adequately exposed to MPA (95% confidence interval 0.58-0.99, P = 0.04). Similarly, the number of patients underexposed to MPA (AUC < 30 ng.h/mL) was higher at most periods in the PPI group but again not statistically significant. Conclusions: These data indicate that PPI decreases the MPA exposure when associated with both CNIs but particularly in the first week after RTx. In this period, the MMF dose should be increased. This effect lasts throughout the first year but does not seem to be clinically relevant after the first week.

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Objectives: To evaluate the effect of insertion torque on micromotion to a lateral force in three different implant designs. Material and methods: Thirty-six implants with identical thread design, but different cutting groove design were divided in three groups: (1) non-fluted (no cutting groove, solid screw-form); (2) fluted (901 cut at the apex, tap design); and (3) Blossomt (Patent pending) (non-fluted with engineered trimmed thread design). The implants were screwed into polyurethane foam blocks and the insertion torque was recorded after each turn of 901 by a digital torque gauge. Controlled lateral loads of 10N followed by increments of 5 up to 100N were sequentially applied by a digital force gauge on a titanium abutment. Statistical comparison was performed with two-way mixed model ANOVA that evaluated implant design group, linear effects of turns and displacement loads, and their interaction. Results: While insertion torque increased as a function of number of turns for each design, the slope and final values increased (Po0.001) progressively from the Blossomt to the fluted to the non-fluted design (M +/- standard deviation [SD] = 64.1 +/- 26.8, 139.4 +/- 17.2, and 205.23 +/- 24.3 Ncm, respectively). While a linear relationship between horizontal displacement and lateral force was observed for each design, the slope and maximal displacement increased (Po0.001) progressively from the Blossomt to the fluted to the non-fluted design (M +/- SD 530 +/- 57.7, 585.9 +/- 82.4, and 782.33 +/- 269.4 mm, respectively). There was negligible to moderate levels of association between insertion torque and lateral displacement in the Blossomt, fluted and non-fluted design groups, respectively. Conclusion: Insertion torque was reduced in implant macrodesigns that incorporated cutting edges, and lesser insertion torque was generally associated with decreased micromovement. However, insertion torque and micromotion were unrelated within implant designs, particularly for those designs showing the least insertion torque.

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Objectives: This study compared the biomechanical fixation and bone-to-implant contact (BIC) of implants with different surfaces treatment (experimental resorbable blasting media-processed nanometer roughness scale surface, and control dual acid-etched) in a dog model. Material and methods: Surface characterization was made in six implants by means of scanning electron microscopic imaging, atomic force microscopy to evaluate roughness parameters, and X-ray photoelectron spectroscopy (XPS) for chemical assessment. The animal model comprised the bilateral placement of control (n = 24) and experimental surface (n = 24) implants along the proximal tibiae of six mongrel dogs, which remained in place for 2 or 4 weeks. Half of the specimens were biomechanically tested (torque), and the other half was subjected to histomorphologic/ morphometric evaluation. BIC and resistance to failure measures were each evaluated as a function of time and surface treatment in a mixed model ANOVA. Results: Surface texturing was significantly higher for the experimental compared with the control surface. The survey XPS spectra detected O, C, Al, and Ti at the control group, and Ca (similar to 0.2-0.9%) and P (similar to 1.7-4.1%) besides O, C, Al, and Ti at experimental surfaces. While no statistical difference in BIC was found between experimental and control surfaces or between 2 and 4 weeks in vivo, both longer time and use of experimental surface significantly increased resistance to failure. Conclusions: The experimental surface resulted in enhanced biomechanical fixation but comparable BIC relative to control, suggesting higher bone mechanical properties around the experimental implants.

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mitochondrial genomes are generally thought to be under selection for compactness, due to their small size, consistent gene content, and a lack of introns or intergenic spacers. As more animal mitochondrial genomes are fully sequenced, rearrangements and partial duplications are being identified with increasing frequency, particularly in birds (Class Ayes). In this study, we investigate the evolutionary history of mitochondrial control region states within the avian order Psittaciformes (parrots and cockatoos). To this aim, we reconstructed a comprehensive multi-locus phylogeny of parrots, used PCR of three diagnostic fragments to classify the mitochondrial control region state as single or duplicated, and mapped these states onto the phylogeny. We further sequenced 44 selected species to validate these inferences of control region state. Ancestral state reconstruction using a range of weighting schemes identified six independent origins of mitochondrial control region duplications within Psittaciformes. Analysis of sequence data showed that varying levels of mitochondrial gene and tRNA homology and degradation were present within a given clade exhibiting duplications. Levels of divergence between control regions within an individual varied from 0-10.9% with the differences occurring mainly between 51 and 225 nucleotides 3' of the goose hairpin in domain I. Further investigations into the fates of duplicated mitochondrial genes, the potential costs and benefits of having a second control region, and the complex relationship between evolutionary rates, selection, and time since duplication are needed to fully explain these patterns in the mitochondrial genome. (C) 2012 Elsevier Inc. All rights reserved.

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The complexity of power systems has increased in recent years due to the operation of existing transmission lines closer to their limits, using flexible AC transmission system (FACTS) devices, and also due to the increased penetration of new types of generators that have more intermittent characteristics and lower inertial response, such as wind generators. This changing nature of a power system has considerable effect on its dynamic behaviors resulting in power swings, dynamic interactions between different power system devices, and less synchronized coupling. This paper presents some analyses of this changing nature of power systems and their dynamic behaviors to identify critical issues that limit the large-scale integration of wind generators and FACTS devices. In addition, this paper addresses some general concerns toward high compensations in different grid topologies. The studies in this paper are conducted on the New England and New York power system model under both small and large disturbances. From the analyses, it can be concluded that high compensation can reduce the security limits under certain operating conditions, and the modes related to operating slip and shaft stiffness are critical as they may limit the large-scale integration of wind generation.

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In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.

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A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.

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The issue of assessing variance components is essential in deciding on the inclusion of random effects in the context of mixed models. In this work we discuss this problem by supposing nonlinear elliptical models for correlated data by using the score-type test proposed in Silvapulle and Silvapulle (1995). Being asymptotically equivalent to the likelihood ratio test and only requiring the estimation under the null hypothesis, this test provides a fairly easy computable alternative for assessing one-sided hypotheses in the context of the marginal model. Taking into account the possible non-normal distribution, we assume that the joint distribution of the response variable and the random effects lies in the elliptical class, which includes light-tailed and heavy-tailed distributions such as Student-t, power exponential, logistic, generalized Student-t, generalized logistic, contaminated normal, and the normal itself, among others. We compare the sensitivity of the score-type test under normal, Student-t and power exponential models for the kinetics data set discussed in Vonesh and Carter (1992) and fitted using the model presented in Russo et al. (2009). Also, a simulation study is performed to analyze the consequences of the kurtosis misspecification.