Establishing Informative Prior for Gene Expression Variance from Public Databases

Identifying differential expressed genes across various conditions or genotypes is the most typical approach to studying the regulation of gene expression. An estimate of gene-specific variance is often needed for the assessment of statistical significance in most differential expression (DE) detection methods, including linear models (e.g., for transformed and normalized microarray data) and generalized linear models (e.g., for count data in RNAseq). Due to a common limit in sample size, the variance estimate is often unstable in small experiments. Shrinkage estimates using empirical Bayes methods have proven useful in improving the variance estimate, hence improving the detection of DE. The most widely used empirical Bayes methods borrow information across genes within the same experiments. In these methods, genes are considered exchangeable or exchangeable conditioning on expression level. We propose, with the increasing accumulation of expression data, borrowing information from historical data on the same gene can provide better estimate of gene-specific variance, thus further improve DE detection. Specifically, we show that the variation of gene expression is truly gene-specific and reproducible between different experiments. We present a new method to establish informative gene-specific prior on the variance of expression using existing public data, and illustrate how to shrink the variance estimate and detect DE. We demonstrate improvement in DE detection under our strategy compared to leading DE detection methods.     

A rapid procedure for preparing fluorescein-labeled specific antibodies from whole antiserum: its use in analyzing cytoskeletal architecture

A rapid method for the direct conjugation of affinity-purified antibodies with fluorescein (termed DCAPA) is described. This procedure involves the immobilization of antibodies as antigen-antibody complexes on nitrocellulose blots, and subsequently the bound antibodies are reacted with fluorescein isothiocyanate. An enriched sample of smooth muscle tropomysin transferred to nitrocellulose paper by the Western blotting procedure has been used as the affinity medium for purification of specific tropomyosin antibody from whole rabbit antiserum. Direct conjugation of the antibody with fluorescein was carried out following the binding of antibody to antigen. Direct conjugation and affinity purification of antibodies directed against tropomyosin was accomplished in 2-3 d using an enriched tropomyosin sample and whole antiserum directed against tropomyosin. The immunofluorescence images obtained with this procedure exhibit distinct advantages with regard to background fluorescence and overall specificity of antibody binding. The usefulness of this direct conjugation method in various experimental protocols is discussed.     

A new phylogenetic method for identifying exceptional phenotypic diversification

Currently available phylogenetic methods for studying the rate of evolution in a continuously valued character assume that the rate is constant throughout the tree or that it changes along specific branches according to an a priori hypothesis of rate variation provided by the user. Herein, we describe a new method for studying evolutionary rate variation in continuously valued characters given an estimate of the phylogenetic history of the species in our study. According to this method, we propose no specific prior hypothesis for how the variation in evolutionary rate is structured throughout the history of the species in our study. Instead, we use a Bayesian Markov Chain Monte Carlo approach to estimate evolutionary rates and the shift point between rates on the tree. We do this by simultaneously sampling rates and shift points in proportion to their posterior probability, and then collapsing the posterior sample into an estimate of the parameters of interest. We use simulation to show that the method is quite successful at identifying the phylogenetic position of a shift in the rate of evolution, and that estimated rates are asymptotically unbiased. We also provide an empirical example of the method using data for Anolis lizards. [This article was published online on September 20, 2011. An error in a co‐author's name was subsequently identified. This notice is included in the online and print versions to indicate that both have been corrected September 21, 2011.]     

Sampling techniques and the use of Tang's procedure in insect population dynamics studies

Some calculations were performed usingTang 's method as an aid in planning experiments for studying the population dynamics of the Jeffrey pine beetle. The population dynamics studies were aimed at detecting the importance of specific effects, e. g., tree diameter, tree height. TheTang procedure is a method of estimating the sample size required to detect effects of a given magnitude with analysis of variance tests. Using this procedure some sample calculations were performed which indicated the sample size needed, and the efficacy of different strategies of improving the results, e. g., increasing the number of trees sampled versus increasing the area of the tree sampled. The statistical parameters used in the calculations were estimated from some preliminary sampling data. Use of this procedure is recommended in insect population studies as a method of optimally planning experiments, and as a method of making precise conclusions about the significance of specific effects.     

A note on the histochemical and morphological characterization of the asbestoid degeneration of cartilage

Summary Using only one histologic preparation and under the light microscope, the simple Picrosirius-polarization method permitted the histochemical characterization of the collagenous nature of amianthoid fibers infile cases of salivary gland tumors. In this regard the foregoing results agree with the electron microscopic and X-ray diffraction observations recorded in the literature. Not only did the Picrosirius-polarization method permit the precise characterization of the collagenous nature of asbestoid change but it was also useful for studying the degree of collagen polymerization in the lesion. Collagen molecules in the amianthoid fibers showed hyperpolymerization whereas the molecules in the compact areas were disoriented. Since the foregoing results demonstrate that the Picrosirius-polarization method is a simple and sensitive procedure for detecting asbestoid change in cartilage sections obtained from paraffin-embedded tissues, the usefulness of this technique for studying file cases is evident.Dedicated to Professor Dr. T.H. Schiebler on the occasion of his 65th birthday     

Genetic model for longitudinal studies of aging, health, and longevity and its potential application to incomplete data

Many longitudinal studies of aging collect genetic information only for a sub-sample of participants of the study. These data also do not include recent findings, new ideas and methodological concepts developed by distinct groups of researchers. The formal statistical analyses of genetic data ignore this additional information and therefore cannot utilize the entire research potential of the data. In this paper, we present a stochastic model for studying such longitudinal data in joint analyses of genetic and non-genetic sub-samples. The model incorporates several major concepts of aging known to date and usually studied independently. These include age-specific physiological norms, allostasis and allostatic load, stochasticity, and decline in stress resistance and adaptive capacity with age. The approach allows for studying all these concepts in their mutual connection, even if respective mechanisms are not directly measured in data (which is typical for longitudinal data available to date). The model takes into account dependence of longitudinal indices and hazard rates on genetic markers and permits evaluation of all these characteristics for carriers of different alleles (genotypes) to address questions concerning genetic influence on aging-related characteristics. The method is based on extracting genetic information from the entire sample of longitudinal data consisting of genetic and non-genetic sub-samples. Thus it results in a substantial increase in the accuracy of statistical estimates of genetic parameters compared to methods that use only information from a genetic sub-sample. Such an increase is achieved without collecting additional genetic data. Simulation studies illustrate the increase in the accuracy in different scenarios for datasets structurally similar to the Framingham Heart Study. Possible applications of the model and its further generalizations are discussed.     

Suitability testing of commercial solid-phase extraction sorbents for sample clean-up in systematic toxicological analysis using liquid chromatography-(tandem) mass spectrometry

An entire series of SPE sorbents, classified into three different categories (apolar, mixed-mode and polymeric) was evaluated for sample preparation of a data-dependent LC-MS-MS "general unknown" screening procedure. An extraction procedure was formulated for each individual column, in agreement with the enclosed instructions, according to the characteristics of each packing. For conciseness, only neutral and basic compounds were chosen for this sorbent suitability test. Thus, the goal of our research was to select the best sorbent with regard to extraction yield and cleanliness of the extracts, all with respect to data-dependent acquisition (DDA) mediated LC-MS-MS general unknown screening. We conclude that for that purpose an Isolute C(8) sorbent performs best in terms of extraction yield and clean-up potential.     

Individual recognition during bouts of antiphonal calling in common marmosets

Many vocalizations are encoded with a diversity of acoustic information about the signal producer. Amongst this information content are social categories related to the identity of the caller that are important for determining if and how a signal receiver may interact with that individual. Here, we employed a novel playback method in common marmosets (Callithrix jacchus) to test individual recognition during bouts of antiphonal calling. These experiments utilized custom, interactive playback software that effectively engaged subjects in antiphonal calling using vocalizations produced by a single individual and presented 'probe' vocalization stimuli representing a different individual at specific points within bouts of calling. The aim here was to test whether marmosets would recognize that the probe stimulus was a phee call produced by a different individual. Data indicated that marmosets were able to detect the change in caller identity; subjects produced significantly fewer antiphonal call responses to probe than control stimuli and, in some conditions, exhibited a shorter latency to produce the vocal response. These data suggest that marmosets recognize the identity of the individual during bouts of antiphonal calling. Furthermore, these results provide a methodological foundation for implementing the probe playback procedure to examine a broader range of social categorization during vocal interactions.     

Possibilities of creating a genetic information database and its processing based on the DBase3-plus system

Special methods are required for computing information on biological objects under complex research. The DBASE3-PLUS system offers vast possibilities for working with large quantity of different sets of information in multi-aspect statistical analysis. Usefulness of this system for creation of and operation with the data on distribution of genetic and non-genetic traits in a population was shown by means of the special set of applied programs in the dBase language. An example presented is aimed at distinguishing those genetic markers which probably can influence common individual health of the members of population. Special regression procedure was suggested to divide the population sample into subgroups with different health levels. Significant differences in distribution of some genetic markers were demonstrated between healthy persons and those who were suffering from chronic diseases.     

Distance-constrained molecular docking by simulated annealing

An optimized method based on the principle of simulated annealing is presented for determining the relative position and orientation of interacting molecules. The spatial relationships of these molecules are described by intermolecular distance constraints between specific pairs of atoms, such as found in hydrogen bonds or from experimentally determined data. The method makes use of a random walk through six rotational and translational degrees of freedom where the constituent molecules are treated as rigid bodies. Van der Waals repulsions are used only to define a lower bound on distances between constrained atom pairs within the docking procedure. A cost function comprised of purely geometric constraints is optimized via simulated annealing, in order to search for the best orientation and position of the two molecules. Our docking procedure is applied to eight serine proteinase complexes from the Brookhaven Protein Data Bank. For each simulation 100 computations were performed. A typical docking computation requires only a few seconds of CPU time on a VAXserver 3500. The influence of the number of constraints on the final docked positions was studied. The sensitivity of the docking procedure to a ligand structure which is not well defined is also addressed. Possible applications of this method include using approximate distances incorporating complete energy functions.     

PHYLOGENETIC ANALYSES OF THE CORRELATED EVOLUTION OF CONTINUOUS CHARACTERS: A SIMULATION STUDY

We use computer simulation to compare the statistical properties of several methods that have been proposed for estimating the evolutionary correlation between two continuous traits, and define alternative evolutionary correlations that may be of interest. We focus on Felsenstein's (1985) method and some variations of it and on several “minimum evolution” methods (of which the procedure of Huey and Bennett [1987] is a special case), as compared with a nonphylogenetic correlation. The last, a simple correlation of trait values across the tips of a phylogeny, virtually always yields inflated Type I error rates, relatively low power, and relatively poor estimates of evolutionary correlations. We therefore cannot recommend its use. In contrast, Felsenstein's (1985) method yields acceptable significance tests, high power, and good estimates of what we term the input correlation and the standardized realized evolutionary correlation, given complete phylogenetic information and knowledge of the rate and mode of character change (e.g., gradual and proportional to time [“Brownian motion”] or punctuational, with change only at speciation events). Inaccurate branch length information may affect any method adversely, but only rarely does it cause Felsenstein's (1985) method to perform worse than do the others tested. Other proposed methods generally yield inflated Type I error rates and have lower power. However, certain minimum evolution methods (although not the specific procedure used by Huey and Bennett [1987]) often provide more accurate estimates of what we term the unstandardized realized evolutionary correlation, and their use is recommended when estimation of this correlation is desired. We also demonstrate how correct Type I error rates can be obtained for any method by reference to an empirical null distribution derived from computer simulations, and provide practical suggestions on choosing an analytical method, based both on the evolutionary correlation of interest and on the availability of branch lengths and knowledge of the model of evolutionary change appropriate for the characters being analyzed. Computer programs that implement the various methods and that will simulate (correlated) character evolution along a known phylogeny are available from the authors on request. These programs can be used to test the effectiveness of any new methods that might be proposed, and to check the generality of our conclusions with regard to other phylogenies.     

Yahtzee: An Anonymized Group Level Matching Procedure

Researchers often face the problem of needing to protect the privacy of subjects while also needing to integrate data that contains personal information from diverse data sources. The advent of computational social science and the enormous amount of data about people that is being collected makes protecting the privacy of research subjects ever more important. However, strict privacy procedures can hinder the process of joining diverse sources of data that contain information about specific individual behaviors. In this paper we present a procedure to keep information about specific individuals from being “leaked” or shared in either direction between two sources of data without need of a trusted third party. To achieve this goal, we randomly assign individuals to anonymous groups before combining the anonymized information between the two sources of data. We refer to this method as the Yahtzee procedure, and show that it performs as predicted by theoretical analysis when we apply it to data from Facebook and public voter records.     

Marker-Based Estimation of Genetic Parameters in Genomics

Linear mixed model (LMM) analysis has been recently used extensively for estimating additive genetic variances and narrow-sense heritability in many genomic studies. While the LMM analysis is computationally less intensive than the Bayesian algorithms, it remains infeasible for large-scale genomic data sets. In this paper, we advocate the use of a statistical procedure known as symmetric differences squared (SDS) as it may serve as a viable alternative when the LMM methods have difficulty or fail to work with large datasets. The SDS procedure is a general and computationally simple method based only on the least squares regression analysis. We carry out computer simulations and empirical analyses to compare the SDS procedure with two commonly used LMM-based procedures. Our results show that the SDS method is not as good as the LMM methods for small data sets, but it becomes progressively better and can match well with the precision of estimation by the LMM methods for data sets with large sample sizes. Its major advantage is that with larger and larger samples, it continues to work with the increasing precision of estimation while the commonly used LMM methods are no longer able to work under our current typical computing capacity. Thus, these results suggest that the SDS method can serve as a viable alternative particularly when analyzing ‘big’ genomic data sets.     

黄土沟壑区小流域景观格局演变及生态服务价值响应

以黄土沟壑区典型小流域泥河沟为研究区,基于1986年的彩红外航空相片、2002年SPOT影像、2016年GF-1卫星影像的解译结果和社会经济统计数据,利用景观指数、土地利用程度、信息熵等方法分析了该流域近30年的景观格局演变规律,并借鉴生态服务价值当量估算法定量探讨了生态系统服务价值的变化特征。结果表明:(1)近30年来研究区土地利用景观格局发生了显著变化,除了林地和建设用地景观面积增加,耕地、园地、未利用地均有不同比例的减少。(2)流域内景观整体破碎度减少,优势斑块的连通性呈增加趋势。(3)土地利用程度整体呈上升趋势且高于全国平均水平231,土地利用信息熵先减少后增加,流域景观经历了"无序-有序-无序"的变化。(4)研究期内流域的总生态系统服务价值呈持续上升趋势,单项生态服务功能主要为土壤形成与保护、废物处理、水源涵养和生物多样性保护。高分辨率卫星影像为流域景观格局演变和生态服务价值分析提供了较为详细的数据支撑。     

A comparison of individual‐based genetic distance metrics for landscape genetics

A major aim of landscape genetics is to understand how landscapes resist gene flow and thereby influence population genetic structure. An empirical understanding of this process provides a wealth of information that can be used to guide conservation and management of species in fragmented landscapes and also to predict how landscape change may affect population viability. Statistical approaches to infer the true model among competing alternatives are based on the strength of the relationship between pairwise genetic distances and landscape distances among sampled individuals in a population. A variety of methods have been devised to quantify individual genetic distances, but no study has yet compared their relative performance when used for model selection in landscape genetics. In this study, we used population genetic simulations to assess the accuracy of 16 individual‐based genetic distance metrics under varying sample sizes and degree of population genetic structure. We found most metrics performed well when sample size and genetic structure was high. However, it was much more challenging to infer the true model when sample size and genetic structure was low. Under these conditions, we found genetic distance metrics based on principal components analysis were the most accurate (although several other metrics performed similarly), but only when they were derived from multiple principal components axes (the optimal number varied depending on the degree of population genetic structure). Our results provide guidance for which genetic distance metrics maximize model selection accuracy and thereby better inform conservation and management decisions based upon landscape genetic analysis.     

Fixed-bin analysis for statistical evaluation of continuous distributions of allelic data from VNTR loci, for use in forensic comparisons.

The detection of DNA polymorphisms by RFLP analysis is having a major impact on identity testing in forensic science. At present, this approach is the best effort a forensic scientist can make to exclude an individual who has been falsely associated with an evidentiary sample found at a crime scene. When an analysis fails to exclude a suspect as a potential contributor of an evidentiary sample, a means should be provided to assess suitable weight to the putative match. Most important, the statistical analysis should not place undue weight on a genetic profile derived from an unknown sample that is attributed to an accused individual. The method must allow for limitations in conventional agarose-submarine-gel electrophoresis and Southern blotting procedure, limited sample population data, possible subpopulation differences, and potential sampling error. A conservative statistical method was developed based on arbitrarily defined fixed bins. This approach permits classification of continuous allelic data, provides for a simple and portable data-base system, and is unlikely to underestimate the frequency of occurrence of a set of alleles. This will help ensure that undue weight is not placed on a sample attributed to an accused individual.     

Sibship reconstruction from genetic data with typing errors

Likelihood methods have been developed to partition individuals in a sample into full-sib and half-sib families using genetic marker data without parental information. They invariably make the critical assumption that marker data are free of genotyping errors and mutations and are thus completely reliable in inferring sibships. Unfortunately, however, this assumption is rarely tenable for virtually all kinds of genetic markers in practical use and, if violated, can severely bias sibship estimates as shown by simulations in this article. I propose a new likelihood method with simple and robust models of typing error incorporated into it. Simulations show that the new method can be used to infer full- and half-sibships accurately from marker data with a high error rate and to identify typing errors at each locus in each reconstructed sib family. The new method also improves previous ones by adopting a fresh iterative procedure for updating allele frequencies with reconstructed sibships taken into account, by allowing for the use of parental information, and by using efficient algorithms for calculating the likelihood function and searching for the maximum-likelihood configuration. It is tested extensively on simulated data with a varying number of marker loci, different rates of typing errors, and various sample sizes and family structures and applied to two empirical data sets to demonstrate its usefulness.     

Power priors based on multiple historical studies for binary outcomes

Incorporating historical information into the design and analysis of a new clinical trial has been the subject of much recent discussion. For example, in the context of clinical trials of antibiotics for drug resistant infections, where patients with specific infections can be difficult to recruit, there is often only limited and heterogeneous information available from the historical trials. To make the best use of the combined information at hand, we consider an approach based on the multiple power prior that allows the prior weight of each historical study to be chosen adaptively by empirical Bayes. This choice of weight has advantages in that it varies commensurably with differences in the historical and current data and can choose weights near 1 if the data from the corresponding historical study are similar enough to the data from the current study. Fully Bayesian approaches are also considered. The methods are applied to data from antibiotics trials. An analysis of the operating characteristics in a binomial setting shows that the proposed empirical Bayes adaptive method works well, compared to several alternative approaches, including the meta‐analytic prior.     

Scientific knowledge is possible with small-sample classification

A typical small-sample biomarker classification paper discriminates between types of pathology based on, say, 30,000 genes and a small labeled sample of less than 100 points. Some classification rule is used to design the classifier from this data, but we are given no good reason or conditions under which this algorithm should perform well. An error estimation rule is used to estimate the classification error on the population using the same data, but once again we are given no good reason or conditions under which this error estimator should produce a good estimate, and thus we do not know how well the classifier should be expected to perform. In fact, virtually, in all such papers the error estimate is expected to be highly inaccurate. In short, we are given no justification for any claims.Given the ubiquity of vacuous small-sample classification papers in the literature, one could easily conclude that scientific knowledge is impossible in small-sample settings. It is not that thousands of papers overtly claim that scientific knowledge is impossible in regard to their content; rather, it is that they utilize methods that preclude scientific knowledge. In this paper, we argue to the contrary that scientific knowledge in small-sample classification is possible provided there is sufficient prior knowledge. A natural way to proceed, discussed herein, is via a paradigm for pattern recognition in which we incorporate prior knowledge in the whole classification procedure (classifier design and error estimation), optimize each step of the procedure given available information, and obtain theoretical measures of performance for both classifiers and error estimators, the latter being the critical epistemological issue. In sum, we can achieve scientific validation for a proposed small-sample classifier and its error estimate.     

The ecological causes of individual specialisation

Many generalist populations are composed of specialised individuals, whose niches are small subsets of the population niche. This 'individual specialisation' is a widespread phenomenon in natural populations, but until recently few studies quantified the magnitude of individual specialisation and how this magnitude varies among populations or contexts. Such quantitative approaches are necessary for us to understand how ecological interactions influence the amount of among-individual variation, and how the amount of variation might affect ecological dynamics. Herein, we review recent studies of individual specialisation, emphasising the novel insights arising from quantitative measures of diet variation. Experimental and comparative studies have confirmed long-standing theoretical expectations that the magnitude of among-individual diet variation depends on the level of intra and interspecific competition, ecological opportunity and predation. In contrast, there is little empirical information as to how individual specialisation affects community dynamics. We discuss some emerging methodological issues as guidelines for researchers studying individual specialisation, and make specific recommendations regarding avenues for future research.