On conditional skewness with applications to environmental data

The statistical literature contains many univariate and multivariate skewness measures that allow two datasets to be compared, some of which are defined in terms of quantile values. In most situations, the comparison between two random vectors focuses on univariate comparisons of conditional random variables truncated in quantiles; this kind of comparison is of particular interest in the environmental sciences. In this work, we describe a new approach to comparing skewness in terms of the univariate convex transform ordering proposed by van Zwet (Convex transformations of random variables. Mathematical Centre Tracts, Amsterdam, 1964), associated with skewness as well as concentration. The key to these comparisons is the underlying dependence structure of the random vectors. Below we describe graphical tools and use several examples to illustrate these comparisons.The research of Félix Belzunce, Julio Mulero and José María Ruíz is partially funded by the Ministerio de Economía y Competitividad (Spain) under Grant MTM2012-34023-FEDER. Alfonso Suárez-Llorens acknowledges support received from the Ministerio de Economía y Competitividad (Spain) under Grant MTM2014-57559-P

Systematical Detection of Significant Genes in Microarray Data by Incorporating Gene Interaction Relationship in Biological Systems

Many methods, including parametric, nonparametric, and Bayesian methods, have been used for detecting differentially expressed genes based on the assumption that biological systems are linear, which ignores the nonlinear characteristics of most biological systems. More importantly, those methods do not simultaneously consider means, variances, and high moments, resulting in relatively high false positive rate. To overcome the limitations, the SWang test is proposed to determine differentially expressed genes according to the equality of distributions between case and control. Our method not only latently incorporates functional relationships among genes to consider nonlinear biological system but also considers the mean, variance, skewness, and kurtosis of expression profiles simultaneously. To illustrate biological significance of high moments, we construct a nonlinear gene interaction model, demonstrating that skewness and kurtosis could contain useful information of function association among genes in microarrays. Simulations and real microarray results show that false positive rate of SWang is lower than currently popular methods (T-test, F-test, SAM, and Fold-change) with much higher statistical power. Additionally, SWang can uniquely detect significant genes in real microarray data with imperceptible differential expression but higher variety in kurtosis and skewness. Those identified genes were confirmed with previous published literature or RT-PCR experiments performed in our lab

Application of 3D Zernike descriptors to shape-based ligand similarity searching

Background: The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. Results: In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability

The intergenerational association between parents' problem gambling and impulsivity-hyperactivity/inattention behaviors in children

Despite the well-established association between problem gambling and ADHD core categories of impulsivity-hyperactivity and inattention, the link between parents’ problem gambling and impulsivity-hyperactivity/inattention (IH/I) behaviors in children has not been investigated. This study investigated the association between parents’ problem gambling and children’s IH/I behaviors while controlling for potential confounding variables. A population-based prospective cohort followed-up from kindergarten to age 30, the Quebec Longitudinal Study of Kindergarten Children (QLSKC), provided data over three generations. Among 1358 participants at age 30, parents with a child aged 1 year or older (N=468; Mean age=4.65 years; SD=2.70) were selected. Generalized Linear Models included measures of grandparents’ and parents’ problem gambling, parents’ IH/I behaviors in childhood, and a host of risk factors and comorbidities to predict IH/I in children. Intergenerational bivariate associations were observed between grandparents’ problem gambling, parents’ IH/I in childhood and problem gambling at age 30, and between parents’ IH/I, problem gambling, and children’s IH/I behaviors. Parents’ problem gambling predicted children’s IH/I behaviors above and beyond the effects of covariates such as family and socioeconomic characteristics, alcohol and drug use, depression symptoms and parents’ gambling involvement. Parents’ IH/I behaviors in childhood also predicted children’s IH/I and had a moderating, enhancing effect on parents’ problem gambling association with their offspring’s IH/I behaviors. Problem gambling is a characteristic of parents’ mental health that is distinctively associated with children’s IH/I behaviors, above and beyond parents’ own history of IH/I and of typically related addictive, psychopathological or socioeconomic risk factors and comorbidities

Body Size Distribution of the Dinosaurs

The distribution of species body size is critically important for determining resource use within a group or clade. It is widely known that non-avian dinosaurs were the largest creatures to roam the Earth. There is, however, little understanding of how maximum species body size was distributed among the dinosaurs. Do they share a similar distribution to modern day vertebrate groups in spite of their large size, or did they exhibit fundamentally different distributions due to unique evolutionary pressures and adaptations? Here, we address this question by comparing the distribution of maximum species body size for dinosaurs to an extensive set of extant and extinct vertebrate groups. We also examine the body size distribution of dinosaurs by various sub-groups, time periods and formations. We find that dinosaurs exhibit a strong skew towards larger species, in direct contrast to modern day vertebrates. This pattern is not solely an artefact of bias in the fossil record, as demonstrated by contrasting distributions in two major extinct groups and supports the hypothesis that dinosaurs exhibited a fundamentally different life history strategy to other terrestrial vertebrates. A disparity in the size distribution of the herbivorous Ornithischia and Sauropodomorpha and the largely carnivorous Theropoda suggests that this pattern may have been a product of a divergence in evolutionary strategies: herbivorous dinosaurs rapidly evolved large size to escape predation by carnivores and maximise digestive efficiency; carnivores had sufficient resources among juvenile dinosaurs and non-dinosaurian prey to achieve optimal success at smaller body size. © 2012 O'Gorman, Hone