A global envelope test to detect non‐random bursts of trait evolution

Hypothesis tests

A recent article in this journal by Tabak (2006) highlighted a potentially serious source of bias that can arise when multiple statistical tests of a damages theory are performed and even one test rejecting the null hypothesis is regarded as supporting the damages theory. Repeated testing will eventually produce a “false discovery,” that is, rejection of the null hypothesis in favor of the alternative hypothesis when the null hypothesis is true, which statisticians refer to as type I error. Consequently, performing multiple tests without adjusting the critical value can be problematical because it can lead to improperly accepting statistical evidence that apparently supports rejection of the null hypothesis as reliable when it is not. Tabak (2006) recommends making the Sidak (1968, 1971) multiple-comparison adjustment to the standard statistical t-test to correct for the false-discovery bias inherent in multiple-comparison testing. In particular, he recommends making this adjustment when performing 10b-5 securities fraud event studies when more than one corrective disclosure date is involved. This article clarifies the circumstances in which a multiple-comparison adjustment is appropriate and explains why the correction is normally not needed in securities fraud event-study testing. More generally, I explain why it is not required when each of several tests is performed and its results are reported separately, as for example, where the objective is simply to test the statistical significance of the abnormal stock return on each day on which a new and distinct curative disclosure occurred. I show that the Sidak multiple-comparison adjustment is nearly as stringent as the classical Bonferroni procedure (Simes, 1986), which can increase the risk of type II error. This article discusses a more powerful alternative to the Sidak adjustment due to Benjamini and Hochberg (1993), which directly corrects for the false-discovery bias in multiple-comparison testing and reduces the risk of type II error. II. Application of Multiple-Comparison Adjustments to Securities Fraud Event Studies Multiple-comparison-false-discovery bias can arise when (a) several statistical tests are performed on subsets of the same larger data set in an effort to

In this paper, we present a novel object-based statistical colocalization method. Our colocalization relies on multiple hypothesis tests on the distances between all pairs of the (spot-shaped) objects from the two markers. We wish to test among all these pairs how many are significantly close to each other such that they cannot occur just "by chance". Two objects are decided to be co-localized if the test on their distance is significant. For this purpose, we first extract the objects by applying a wavelet-based spot detection approach which fully takes into account the mixed-Poisson-Gaussian noise process of confocal fluorescence images. Then, we build a null hypothesis model in which the distribution of the distance between two independently randomly drawn detections in the cell is estimated by a kernel method. The observed distances are tested against this null model. Our tests control the false discovery rate (FDR) of the co-localizations. Simulations show that this approach has a good specificity. Furthermore, our method has been successfully applied in a real problem of protein colocalization analysis during the endocytic process.

PDF HTML阅读 XML下载 导出引用 引用提醒 生态学中的点格局研究概况及其在国内的应用 DOI: 10.5846/stxb201607081399 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然基金项目（31370633）。 A review of point pattern analysis in ecology and its application in China Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:点格局分析是研究生态学格局的工具之一，近年来在生态学中的应用越来越多。为深入了解点格局分析方法在国内的研究与应用情况，以所总结的研究进展、一般步骤和基本要点为背景，分析评述了1996-2015年期间以点格局为主题的国内中文核心期刊文献。结果表明，在国内生态学格局研究中，应用研究占据主导地位，研究对象广泛，包括以树木为主的乔、灌、草等不同生活型的植物，甚至包括景观；基础研究，包括概括性统计量、零模型与点过程模型等方面，以及专用软件工具包的开发等研究薄弱。在应用中存在一定问题，主要表现为：概括性统计量使用单一，且以Ripley的K-函数及其变形为主；零模型（或点过程模型）是科学问题的统计表达，但是有一半以上的研究未明确给出零模型。建议在未来应用研究中重视多种统计量的组合使用和原假设的建立，在探讨热带、亚热带森林等具有复杂空间结构系统的多样性格局时，考虑对象的不同世代和系统的不同垂直层次，并加强多变量或三维概括性统计量的开发、点格局分析方法与动态过程模型的结合研究等工作。 Abstract:Point pattern analysis, i.e., spatial point pattern analysis (SPPA) is a tool used in ecological pattern research and has recently become increasingly popular in ecology. To better understand SPPA research and its application in China, in this review we examined articles regarding SPPA published from 1996 to 2015 in China, which was based on a summary of the research progress, using steps and key points of SPPA. It was found that most articles focused on application research. Although there were extensive study objects, including forests, shrubs, grasslands, and landscapes, trees in forest communities were the main focus in all these application studies. Fundamental studies were found to be underdeveloped, such as studies regarding summary statistics and null models or point process models in SPPA, and the development of specific software packages for SPPA. Two important problems were found in SPPA applications: Firstly, although there are many alternatives, researchers preferred single summary statistics and only selected the K-function or its transformations; and secondly, although selecting null models as null hypotheses was a key step in SPPA, more than half of the research examined did not specify explicit null models. Therefore, it is recommended that different types of summary statistics are used to capture detailed spatial pattern structures, and the ecological questions or hypotheses should be clearly stated and correctly translated into statistical language, i.e., the null model and tests. Vertical layers and different generations should also be considered when studying systems with complex spatial structures, such as in tropical rainforests and subtropical evergreen broad-leaved forests. To enhance basic SPPA applications, these aspects discussed should be strengthened. 参考文献 相似文献 引证文献

We propose a general framework for the specification testing of continuous treatment effect models. We assume a general residual function, which includes the average and quantile treatment effect models as special cases. The null models are identified under the unconfoundedness condition and contain a nonparametric weighting function. We propose a test statistic for the null model in which the weighting function is estimated by solving an expanding set of moment equations. We establish the asymptotic distributions of our test statistic under the null hypothesis and under fixed and local alternatives. The proposed test statistic is shown to be more efficient than that constructed from the true weighting function and can detect local alternatives deviated from the null models at the rate of . A simulation method is provided to approximate the null distribution of the test statistic. Monte-Carlo simulations show that our test exhibits a satisfactory finite-sample performance, and an application shows its practical value.

The correlation between species diversification and morphological evolution has long been of interest in evolutionary biology. We investigated the relationship between these processes during the radiation of 250+scincid lizards that constitute Australia's most species-rich clade of terrestrial vertebrates. We generated a time-calibrated phylogenetic tree for the group that was more than 85% complete at the species level and collected multivariate morphometric data for 183 species. We reconstructed the dynamics of species diversification and trait evolution using a Bayesian statistical framework (BAMM) that simultaneously accounts for variation in evolutionary rates through time and among lineages. We extended the BAMM model to accommodate time-dependent phenotypic evolution, and we describe several new methods for summarizing and visualizing macroevolutionary rate heterogeneity on phylogenetic trees. Two major clades (Lerista, Ctenotus; >90 spp. each) are associated with high rates of species diversification relative to the background rate across Australian sphenomorphine skinks. The Lerista clade is characterized by relatively high lability of body form and has undergone repeated instances of limb reduction, but Ctenotus is characterized by an extreme deceleration in the rate of body shape evolution. We estimate that rates of phenotypic evolution decreased by more than an order of magnitude in the common ancestor of the Ctenotus clade. These results provide evidence for a modal shift in phenotypic evolutionary dynamics and demonstrate that major axes of morphological variation can be decoupled from species diversification. More generally, the Bayesian framework described here can be used to identify and characterize complex mixtures of dynamic processes on phylogenetic trees. [Bayesian; diversification; evolvability; lizard; macroevolution, punctuated equilibrium, speciation.].

In a recent article (Colwell et al. 2004; hereafter CRG), we reviewed all studies of the mid-domain effect (MDE) published up to that time and responded to earlier critiques of MDE by (among others) Hawkins and Diniz-Filho (2002) and Zapata et al. (2003). The discussion continues here with comments on our article by Hawkins, DinizFilho, and Weiss (2005; hereafter HDW) and by Zapata, Gaston, and Chown (2005; hereafter ZGC). In this article, we respond to HDW and ZGC. Null models and null hypotheses. ZGC defend their view of MDE models as null hypotheses subject to falsification. In contrast, proponents of MDE theory have always held that richness patterns have multiple causes. For example, referring to the effect of geometric (boundary) constraints on geographic patterns of species richness, Colwell and Lees (2000, p. 79) stated that “the question is not whether geometry affects such patterns, but by how much.” We view any assessment of the role of geometric constraints as a problem of estimating the magnitude of the contribution (if any) of MDE to richness patterns (“how much”). Just as with other candidate causes of richness patterns (e.g., climatic, topographic, or historical drivers), the appropriate null hypothesis (if any) is that MDE makes no contribution to richness patterns, not that MDE uniquely and fully accounts for richness patterns. It is for this reason that we distinguish between MDE as a model and the hypotheses that can be framed regarding its predictions.

Studies of resting state functional MRI (rs-fRMI) are increasingly focused on “dynamics”, or on those properties of brain activation that manifest and vary on timescales shorter than the scan's full duration. This shift in focus has led to a flurry of interest in developing hypothesis testing frameworks and null models applicable to the dynamical setting. Thus far however, these efforts have been weakened by a number of crucial shortcomings that are outlined and discussed in this article. We focus here on aspects of recently proposed null models that, we argue, are poorly formulated relative to the hypotheses they are designed to test, i.e., their potential role in separating functionally relevant BOLD signal dynamics from noise or intermittent background and maintenance type processes is limited by factors that are fundamental rather than merely quantitative or parametric. In this short position paper, we emphasize that (1) serious care must be exercised in building null models for rs-fMRI dynamics from distributionally stationary univariate or multivariate timeseries, i.e., timeseries whose values are each independently drawn from one pre-specified probability distribution; and (2) measures such as kurtosis that quantify over-concentration of observed values in the far tails of some reference distribution may not be particularly suitable for capturing signal features most plausibly contributing to functionally relevant brain dynamics. Other metrics targeted, for example, at capturing the type of epochal signal variation that is often viewed as a signature of brain responsiveness to stimuli or experimental tasks, could play a more scientifically clarifying role. As we learn more about the phenomenon of functionally relevant brain dynamics and its imaging correlates, scientifically meaningful null hypotheses and well-tuned null models will naturally emerge. We also revisit the important concept of distributional stationarity, discuss how it manifests within realizations vs. across multiple realizations, and provide guidance on the benefits and limitations of employing this type of stationarity in modeling the absence of functionally relevant temporal dynamics in resting state fMRI. We hope that the discussions herein are useful, and promote thoughtful consideration of these important issues.

Morphology reflects ecological pressures, phylogeny, and genetic and biophysical constraints. Disentangling their influence is fundamental to understanding selection and trait evolution. Here, we assess the contributions of function, phylogeny, and habitat to patterns of plastron (ventral shell) shape variation in emydine turtles. We quantify shape variation using geometric morphometrics, and determine the influence of several variables on shape using path analysis. Factors influencing plastron shape variation are similar between emydine turtles and the more inclusive Testudinoidea. We evaluate the fit of various evolutionary models to the shape data to investigate the selective landscape responsible for the observed morphological patterns. The presence of a hinge on the plastron accounts for most morphological variance, but phylogeny and habitat also correlate with shape. The distribution of shape variance across emydine phylogeny is most consistent with an evolutionary model containing two adaptive zones--one for turtles with kinetic plastra, and one for turtles with rigid plastra. Models with more complex adaptive landscapes often fit the data only as well as the null model (purely stochastic evolution). The adaptive landscape of plastron shape in Emydinae may be relatively simple because plastral kinesis imposes overriding mechanical constraints on the evolution of form.

A critical examination of a recent article by Brooks and McLennan has led to the conclusion that their phylogeny of parasitic Platyhelminthes is based on "synapomorphies" that are clearly wrong or superficial similarities whose homology is unlikely. Using characters likely to be homologous and DNA analyses, it has been shown that Temnocephalida is not the sister group of the parasitic Platyhelminthes (Neodermata), Udonellidea is unlikely to be the sister group of the other Neodermata, the sister group of the Neodermata is unknown but likely to be a large taxon comprising several turbellarian groups, no evidence indicates that the Arthropoda are the original hosts of the parasitic Platyhelminthes, the possibility cannot be ruled out that species poverty of some groups of parasitic Platyhelminthes is an artifact, and "key innovations" supposedly explaining the great species richness of the parasitic Platyhelminthes and some taxa within them are based on insufficient or faulty evidence. Based on an examination of the recent literature, I suggest the following steps to identify key innovations: first, establish phylogenetic trees using characters likely to be homologous on the basis of established homology criteria; second, examine whether trees are "significantly" unbalanced using null models; finally, use multiple testing to tentatively identify putative key innovations. Retrospective studies of processes that have led to radiations in the past will in many cases be impossible, and the best one can hope for is a tentative identification of putative key innovations by multiple testing. If multiple testing cannot be done, then even a tentative identification is impossible, and one is left with a "plausible suggestion." Concerning the practice of phylogenetic systematics, it is emphasized that phylogenetic analyses using a few characters whose homology has been made likely by careful assessment are more likely to reveal phylogenetic relationships than analyses using large numbers of unassessed characters.

This study examines the evolution hindwing shape in Chinese dung beetle species using morphometric and phylogenetic analyses. Previous studies have analyzed the evolution of wing shape within a single or very few species, or by comparing only a few wing traits. No study has analyzed wing shape evolution of a large number of species, or quantitatively compared morphological variation of wings with proposed phylogenetic relationships. This study examines the morphological variation of hindwings based on 19 landmarks, 119 morphological characters, and 81 beetle species. Only one most parsimonious tree (MPT) was found based on 119 wing and body characters. To better understand the possible role of the hindwing in the evolution of Scarabaeinae, additional phylogenetic analyses were proposed based on the only body features (106 characters, wing characters excluded). Two MPT were found based on 106 body characters, and five nodes were collapsed in a strict consensus. There was a strong correlation between the morphometric tree and all phylogenetic trees (r>0.5). Reconstructions of the ancestral wing forms suggest that Scarabaeinae hindwing morphology has not changed substantially over time, but the morphological changes that do occur are focused at the base of the wing. These results suggest that flight has been important since the origin of Scarabaeinae, and that variation in hindwing morphology has been limited by functional constraints. Comparison of metric disparity values and relative evolutionary sequences among Scarabaeinae tribes suggest that the primitive dung beetles had relatively diverse hindwing morphologies, while advanced dung beetles have relatively similar wing morphologies. The strong correlation between the morphometric tree and phylogenetic trees suggest that hindwing features reflect the evolution of whole body morphology and that wing characters are suitable for the phylogenetic analyses. By integrating morphometric and cladistic approaches, this paper sheds new light on the evolution of dung beetle hind wings.

BackgroundFilamentous cyanobacteria that differentiate multiple cell types are considered the peak of prokaryotic complexity and their evolution has been studied in the context of multicellularity origins. Species that form true-branching filaments exemplify the most complex cyanobacteria. However, the mechanisms underlying the true-branching morphology remain poorly understood despite of several investigations that focused on the identification of novel genes or pathways. An alternative route for the evolution of novel traits is based on existing phenotypic plasticity. According to that scenario – termed genetic assimilation – the fixation of a novel phenotype precedes the fixation of the genotype.ResultsHere we show that the evolution of transcriptional regulatory elements constitutes a major mechanism for the evolution of new traits. We found that supplementation with sucrose reconstitutes the ancestral branchless phenotype of two true-branching Fischerella species and compared the transcription start sites (TSSs) between the two phenotypic states. Our analysis uncovers several orthologous TSSs whose transcription level is correlated with the true-branching phenotype. These TSSs are found in genes that encode components of the septosome and elongasome (e.g., fraC and mreB).ConclusionsThe concept of genetic assimilation supplies a tenable explanation for the evolution of novel traits but testing its feasibility is hindered by the inability to recreate and study the evolution of present-day traits. We present a novel approach to examine transcription data for the plasticity first route and provide evidence for its occurrence during the evolution of complex colony morphology in true-branching cyanobacteria. Our results reveal a route for evolution of the true-branching phenotype in cyanobacteria via modification of the transcription level of pre-existing genes. Our study supplies evidence for the ‘plasticity-first’ hypothesis and highlights the importance of transcriptional regulation in the evolution of novel traits.

An important problem in evolutionary genomics is to investigate whether a certain trait measured on each sample is associated with the sample phylogenetic tree. The phylogenetic tree represents the shared evolutionary history of the samples and it is usually estimated from molecular sequence data at a locus or from other type of genetic data. We propose a model for trait evolution inspired by the Chinese Restaurant Process that includes a parameter that controls the degree of preferential attachment, that is, the tendency of nodes in the tree to subtend from nodes of the same type. This model with no preferential attachment is equivalent to a structured coalescent model with simultaneous migration and coalescence events and serves as a null model. We derive a test for phylogenetic binary trait association with linear computational complexity and empirically demonstrate that it is more powerful than some other methods. We apply our test to study the phylogenetic association of some traits in swordtail fish, breast cancer, yellow fever virus, and influenza A H1N1 virus. R-package implementation of our methods is available at https://github.com/jyzhang27/CRPTree.

It is generally assumed that the likelihood ratio statistic for testing the null hypothesis that data arise from a homoscedastic normal mixture distribution versus the alternative hypothesis that data arise from a heteroscedastic normal mixture distribution has an asymptotic ? 2 reference distribution with degrees of freedom equal to the difference in the number of parameters being estimated under the alternative and null models under some regularity conditions. Simulations show that the ? 2 reference distribution will give a reasonable approximation for the likelihood ratio test only when the sample size is 2000 or more and the mixture components are well separated when the restrictions suggested by Hathaway (Ann. Stat. 13:795---800, 1985) are imposed on the component variances to ensure that the likelihood is bounded under the alternative distribution. For small and medium sample sizes, parametric bootstrap tests appear to work well for determining whether data arise from a normal mixture with equal variances or a normal mixture with unequal variances.

The consequences of selection at linked sites are multiple and widespread across the genomes of most species. Here, I first review the main concepts behind models of selection and linkage in recombining genomes, present the difficulty in parametrizing these models simply as a reduction in effective population size (Ne) and discuss the predicted impact of recombination rates on levels of diversity across genomes. Arguments are then put forward in favour of using a model of selection and linkage with neutral and deleterious mutations (i.e. the background selection model, BGS) as a sensible null hypothesis for investigating the presence of other forms of selection, such as balancing or positive. I also describe and compare two studies that have generated high-resolution landscapes of the predicted consequences of selection at linked sites in Drosophila melanogaster. Both studies show that BGS can explain a very large fraction of the observed variation in diversity across the whole genome, thus supporting its use as null model. Finally, I identify and discuss a number of caveats and challenges in studies of genetic hitchhiking that have been often overlooked, with several of them sharing a potential bias towards overestimating the evidence supporting recent selective sweeps to the detriment of a BGS explanation. One potential source of bias is the analysis of non-equilibrium populations: it is precisely because models of selection and linkage predict variation in Ne across chromosomes that demographic dynamics are not expected to be equivalent chromosome- or genome-wide. Other challenges include the use of incomplete genome annotations, the assumption of temporally stable recombination landscapes, the presence of genes under balancing selection and the consequences of ignoring non-crossover (gene conversion) recombination events.This article is part of the themed issue ‘Evolutionary causes and consequences of recombination rate variation in sexual organisms’.