Misspecification in mixed-model based association analysis

Additive genetic variance in natural populations is commonly estimated using mixed models, in which the covariance of the genetic effects is modeled by a genetic similarity matrix derived from a dense set of markers. An important but usually implicit assumption is that the presence of any non-additive genetic effect only increases the residual variance, and does not affect estimates of additive genetic variance. Here we show that this is only true for panels of unrelated individuals. In case there is genetic relatedness, the combination of population structure and epistatic interactions can lead to inflated estimates of additive genetic variance

Genetic and environmental links between self-reports and parent-reports of child personality

Personality ratings have been consistently found to be reliable and moderately heritable, but interrater agreement between self- and other-report of personality are low-to-moderate, particularly in childhood samples. The current study aims to examine the agreement between child self-reports and parent-informant reports of Big Five personality traits using a genetically informative approach. Using data from a sample of 2756 (982 monozygotic) twins ages six to 21 from The Texas Twin Project, we find that agreement between parent ratings and child-self reports for all Big 5 personality traits are mediated by both genetic and non-shared environmental influences. Models incorporating dominant genetic effects rather than additive genetic effects alone proved to better fit the data. In these models, the effect of additive genetics was strongly reduced or eliminated altogether in favor of strong dominant genetic influences, suggesting that dominant genetic effects play a key role in parent and child ratings of personality and should be more widely incorporated into similar research. Additive genetic effects were observed in parent reports of child extraversion, agreeableness, and neuroticism, but not in any self-reported traits. Dominant genetic effects, however, were observed in parent and child reports of extraversion, openness, conscientiousness, and neuroticism, as well as parent reports of agreeableness. Non-environmental effects were strong for all Big 5 traits reported by children and parents. Contrast effects, while slight, were observed in parent and self-reports of extraversion as well as parent reports of conscientiousness and neuroticism.Psycholog

Spike-and-Slab Priors for Function Selection in Structured Additive Regression Models

Structured additive regression provides a general framework for complex Gaussian and non-Gaussian regression models, with predictors comprising arbitrary combinations of nonlinear functions and surfaces, spatial effects, varying coefficients, random effects and further regression terms. The large flexibility of structured additive regression makes function selection a challenging and important task, aiming at (1) selecting the relevant covariates, (2) choosing an appropriate and parsimonious representation of the impact of covariates on the predictor and (3) determining the required interactions. We propose a spike-and-slab prior structure for function selection that allows to include or exclude single coefficients as well as blocks of coefficients representing specific model terms. A novel multiplicative parameter expansion is required to obtain good mixing and convergence properties in a Markov chain Monte Carlo simulation approach and is shown to induce desirable shrinkage properties. In simulation studies and with (real) benchmark classification data, we investigate sensitivity to hyperparameter settings and compare performance to competitors. The flexibility and applicability of our approach are demonstrated in an additive piecewise exponential model with time-varying effects for right-censored survival times of intensive care patients with sepsis. Geoadditive and additive mixed logit model applications are discussed in an extensive appendix

Scaling Effects in Laser-Based Additive Manufacturing Processes

Mechanical Engineerin

Emergent Bistability : Effects of Additive and Multiplicative Noise

Positive feedback and cooperativity in the regulation of gene expression are generally considered to be necessary for obtaining bistable expression states. Recently, a novel mechanism of bistability termed emergent bistability has been proposed which involves only positive feedback and no cooperativity in the regulation. An additional positive feedback loop is effectively generated due to the inhibition of cellular growth by the synthesized proteins. The mechanism, demonstrated for a synthetic circuit, may be prevalent in natural systems also as some recent experimental results appear to suggest. In this paper, we study the effects of additive and multiplicative noise on the dynamics governing emergent bistability. The calculational scheme employed is based on the Langevin and Fokker-Planck formalisms. The steady state probability distributions of protein levels and the mean first passage times are computed for different noise strengths and system parameters. In the region of bistability, the bimodal probability distribution is shown to be a linear combination of a lognormal and a Gaussian distribution. The variances of the individual distributions and the relative weights of the distributions are further calculated for varying noise strengths and system parameters. The experimental relevance of the model results is also pointed out.Comment: 16 pages, 11 figures, version accepted for publication in Eur. Phys. J.

Applied thermionic research Quarterly progress report, 25 Jan. - 25 Mar. 1965

Cesium fluoride and argon plasma additive effects in thermionic converter

Efficiency of genomic selection with models including dominance effect in the context of perennial crop breeding

In perennial plants, varieties can be produced by clones or elite full-sib families, where both additive and non-additive effects are taken into account in the selection process. Although this point is crucial in perennial crops, very few studies have analysed the value of including non-additive effects in the Genomic Selection (GS) model (Meuwissen et al. 2001) and there is a growing interest in testing new models(Lorenzana and Bernardo 2009). We developed a simulation study to test the efficiency of GS in the case of perennials crop breeding with the example Eucalyptus one of the most used forest tree genus in plantation. We simulated a recurrent selection scheme for clone production over four breeding cycles. Scenarios crossing broad sense heritabilities (H²=0.6 and 0.1) and dominance to additive variance ratios (R=0.1; 0.5 and 1) were compared. GS was performed with 1000 SNPs and 22 QTLs per morgan and tested against phenotypic selection (PS) based on best linear unbiased prediction of parents and clones. Our analyses are based on data simulated with R software version 2.13.0 (R Development Core Team 2009) and the HaploSim package, developed by Coster and Bastiaansen (2009). When the training population was made up of the first cycle progeny tests and the candidate populations were the progeny tests of three successive cycles, GS accuracy decreased with breeding cycles (e.g. from 0.9 to 0.4 with H²=0.6 and R=0.1), whereas PS presented constant performances (accuracy of 0.8 with H²=0.6 and R=0.1). When the training population set was updated by associating data of previous cycles, GS accuracy was improved from 25 to 418%, especially with H²=0.1. The GS model including dominance effects performed better in clone selection (genotypic value) when dominance effects were preponderant (R=1), heritability was high (H²=0.6 and with an updated training set), but no improvement was detected for parent selection (breeding value). The genetic gains over cycles were lower with the GS method without updating the data set but, with an updated training set, were similar to PS. However, the genetic gain per unit time with GS was 1.5 to 3 times higher than with PS for breeding and clone populations. Our results demonstrate how GS efficiency is augmented by increasing the relationship between the training and candidate populations, the training population size and heritability. Moreover, our study brings new insight by analysing the value of modelling the dominance effect in GS when both additive and non-additive effects are taken into account to select genotypes.These results highlight the value of GS in perennial crop and especially in Eucalyptus breeding

Additive noise effects in active nonlinear spatially extended systems

We examine the effects of pure additive noise on spatially extended systems with quadratic nonlinearities. We develop a general multiscale theory for such systems and apply it to the Kuramoto-Sivashinsky equation as a case study. We first focus on a regime close to the instability onset (primary bifurcation), where the system can be described by a single dominant mode. We show analytically that the resulting noise in the equation describing the amplitude of the dominant mode largely depends on the nature of the stochastic forcing. For a highly degenerate noise, in the sense that it is acting on the first stable mode only, the amplitude equation is dominated by a pure multiplicative noise, which in turn induces the dominant mode to undergo several critical state transitions and complex phenomena, including intermittency and stabilisation, as the noise strength is increased. The intermittent behaviour is characterised by a power-law probability density and the corresponding critical exponent is calculated rigorously by making use of the first-passage properties of the amplitude equation. On the other hand, when the noise is acting on the whole subspace of stable modes, the multiplicative noise is corrected by an additive-like term, with the eventual loss of any stabilised state. We also show that the stochastic forcing has no effect on the dominant mode dynamics when it is acting on the second stable mode. Finally, in a regime which is relatively far from the instability onset, so that there are two unstable modes, we observe numerically that when the noise is acting on the first stable mode, both dominant modes show noise-induced complex phenomena similar to the single-mode case