Sensitivity of methods for estimating breeding values using genetic markers to the number of QTL and distribution of QTL variance

The objective of this simulation study was to compare the effect of the number of QTL and distribution of QTL variance on the accuracy of breeding values estimated with genomewide markers (MEBV). Three distinct methods were used to calculate MEBV: a Bayesian Method (BM), Least Angle Regression (LARS) and Partial Least Square Regression (PLSR). The accuracy of MEBV calculated with BM and LARS decreased when the number of simulated QTL increased. The accuracy decreased more when QTL had different variance values than when all QTL had an equal variance. The accuracy of MEBV calculated with PLSR was affected neither by the number of QTL nor by the distribution of QTL variance. Additional simulations and analyses showed that these conclusions were not affected by the number of individuals in the training population, by the number of markers and by the heritability of the trait. Results of this study show that the effect of the number of QTL and distribution of QTL variance on the accuracy of MEBV depends on the method that is used to calculate MEBV.     

Parameter estimation with a novel gradient-based optimization method for biological lattice-gas cellular automaton models

Lattice-gas cellular automata (LGCAs) can serve as stochastic mathematical models for collective behavior (e.g. pattern formation) emerging in populations of interacting cells. In this paper, a two-phase optimization algorithm for global parameter estimation in LGCA models is presented. In the first phase, local minima are identified through gradient-based optimization. Algorithmic differentiation is adopted to calculate the necessary gradient information. In the second phase, for global optimization of the parameter set, a multi-level single-linkage method is used. As an example, the parameter estimation algorithm is applied to a LGCA model for early in vitro angiogenic pattern formation.     

基于RS和GIS的毛乌素沙地植被盖度定量估测

选取毛乌素沙地东北部的伊金霍洛旗为研究区域,以少量野外定位调查数据与其对应的遥感信息和GIS信息为基础,利用岭估计分析方法,对植被盖度估测模型及其影响因子进行系统研究.结果表明,植被盖度除受NDVI影响外,还与其他遥感信息紧密相关,岭估计方法明显地改善了最小二乘估计的缺陷,克服了变量间由于存在复共线性关系对求解待定参数所造成的不利影响,提高了估测精度.建立了以像元为单位的植被盖度估测模型,其模型检验精度达98.7%.此外,还建立了区域性植被盖度地理信息系统,实现了研究区域内任意一点(像元)或任意土地单元植被盖度的查询、更新及自动制图.     

Least-squares methods for identifying biochemical regulatory networks from noisy measurements

Background  

We consider the problem of identifying the dynamic interactions in biochemical networks from noisy experimental data. Typically, approaches for solving this problem make use of an estimation algorithm such as the well-known linear Least-Squares (LS) estimation technique. We demonstrate that when time-series measurements are corrupted by white noise and/or drift noise, more accurate and reliable identification of network interactions can be achieved by employing an estimation algorithm known as Constrained Total Least Squares (CTLS). The Total Least Squares (TLS) technique is a generalised least squares method to solve an overdetermined set of equations whose coefficients are noisy. The CTLS is a natural extension of TLS to the case where the noise components of the coefficients are correlated, as is usually the case with time-series measurements of concentrations and expression profiles in gene networks.     

Model Comparison for Breast Cancer Prognosis Based on Clinical Data

We compared the performance of several prediction techniques for breast cancer prognosis, based on AU-ROC performance (Area Under ROC) for different prognosis periods. The analyzed dataset contained 1,981 patients and from an initial 25 variables, the 11 most common clinical predictors were retained. We compared eight models from a wide spectrum of predictive models, namely; Generalized Linear Model (GLM), GLM-Net, Partial Least Square (PLS), Support Vector Machines (SVM), Random Forests (RF), Neural Networks, k-Nearest Neighbors (k-NN) and Boosted Trees. In order to compare these models, paired t-test was applied on the model performance differences obtained from data resampling. Random Forests, Boosted Trees, Partial Least Square and GLMNet have superior overall performance, however they are only slightly higher than the other models. The comparative analysis also allowed us to define a relative variable importance as the average of variable importance from the different models. Two sets of variables are identified from this analysis. The first includes number of positive lymph nodes, tumor size, cancer grade and estrogen receptor, all has an important influence on model predictability. The second set incudes variables related to histological parameters and treatment types. The short term vs long term contribution of the clinical variables are also analyzed from the comparative models. From the various cancer treatment plans, the combination of Chemo/Radio therapy leads to the largest impact on cancer prognosis.     

Abundance estimation of the Northwestern Atlantic harp seal population

Summary A general method—the Least Square Index Method—for estimating marine mammal populations is developed and applied to the Northwestern Atlantic harp seals. Each age group is allowed to have their own vulnearability, catchability, and natural mortality. The age samples need therefore not be representative of the age structure of the animals on the hunting grounds. The abundance estimates are not dependent on the values of the natural mortalities. The sensitivity to fluctuations in the vulnerability and catchability is tested by simulation. This analysis shows that the estimate of the average pup production, , is robust, while the estimate of the rate of change in pup production is not robust. Consequently, only may be used in the assessment. A new method for estimating the average natural mortality may then be developed by starting a population projection with . The estimates obtained by the Least Square Index Method are: Average pup production in the 1960's: 400 000; Average natural mortality: 0.105; Pup production around 1980: 390 000.     

Estimating Population Size and Density Using Line Transect Sampling

ANDERSON and POSPAHALA (1970) investigated the estimation of wildlife population size using the belt or line transect sampling method and devised a correction for bias, thus leading to a class of estimators with desirable characteristics. This work was given a basic and rigorous mathematica framework by BURNHAM and ANDERSON (1976). In the present article we use this mathematical framework to develop an estimator of population size and density using weighted least squares. The approach is a two-stage Method.     

结合改进卷积神经网络和最小二乘法的颅骨性别鉴定

颅骨性别鉴定在法医学和颅骨面貌复原等领域具有重要研究意义和应用价值,针对传统颅骨性别鉴定需要专家参与且主观性强、计算机辅助方法需要人工标定特征点等问题,本文提出了结合改进卷积神经网络和最小二乘法的颅骨性别鉴定方法。首先,获取三维颅骨模型多角度颅骨图像,利用改进的卷积神经网络计算每个样本的每张图像属于男性和女性的概率;其次,基于概率均值采用最小二乘法计算每张图像对性别鉴定的权重;最后,利用上述步骤得到的最优参数构造决策函数,通过决策值完成颅骨性别鉴定。本文方法抛弃了繁琐的手动测量,对完整颅骨的性别鉴定正确率高达94.4%,对不完整颅骨的性别鉴定正确率高达87.5%,能够获得较好的颅骨性别鉴定性能。     

Statistical determination of the average values of the extinction coefficients of tryptophan and tyrosine in native proteins.

Spectroscopic measurement of protein concentration requires knowledge of the value of the relevant extinction coefficient. If the amino acid composition of a protein is known, however, extinction coefficients can be calculated approximately, provided that the values of the molar absorptivities for tryptophan and tyrosine residues in the protein are known. We have applied a matrix linear regression procedure and a mapping of average absolute deviations between experimental and calculated values to find molar extinction coefficients (epsilon M, 1 cm, 280 nm) of 5540 M-1 cm-1 for tryptophan and 1480 M-1 cm-1 for tyrosine residues in an "average" protein, as defined by a set of experimentally determined extinction coefficients for more than 30 proteins. Use of these values provides a significant improvement in extinction coefficient estimation over that obtained with the commonly used values obtained from solutions of model compounds in guanidine-HCl. The consistency of these results when compared to the large deviations often observed between experimentally determined extinction coefficients suggest that this method may offer acceptable accuracy in the initial estimation of molar absorptivities of globular proteins.     

Rapid Quantification of Methamphetamine: Using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) and Chemometrics

In Australia and increasingly worldwide, methamphetamine is one of the most commonly seized drugs analysed by forensic chemists. The current well-established GC/MS methods used to identify and quantify methamphetamine are lengthy, expensive processes, but often rapid analysis is requested by undercover police leading to an interest in developing this new analytical technique. Ninety six illicit drug seizures containing methamphetamine (0.1%–78.6%) were analysed using Fourier Transform Infrared Spectroscopy with an Attenuated Total Reflectance attachment and Chemometrics. Two Partial Least Squares models were developed, one using the principal Infrared Spectroscopy peaks of methamphetamine and the other a Hierarchical Partial Least Squares model. Both of these models were refined to choose the variables that were most closely associated with the methamphetamine % vector. Both of the models were excellent, with the principal peaks in the Partial Least Squares model having Root Mean Square Error of Prediction 3.8, R² 0.9779 and lower limit of quantification 7% methamphetamine. The Hierarchical Partial Least Squares model had lower limit of quantification 0.3% methamphetamine, Root Mean Square Error of Prediction 5.2 and R² 0.9637. Such models offer rapid and effective methods for screening illicit drug samples to determine the percentage of methamphetamine they contain.     

Evaluation of second osmotic virial coefficients from molecular simulation following scaled-particle theory

ABSTRACT

We report a scaled particle theory-based method for evaluation of second osmotic virial coefficients from molecular simulations of dilute species in solution. In this method, we evaluate the work associated with growing a cavity in solution that is perfectly permeable to the solvent but is completely impermeable to the solutes, thereby establishing an osmotic stress between the cavity interior and exterior. Extrapolating our results to determine the solute concentration in contact with a cavity with an infinite radius, we are able to evaluate the solute osmotic pressure and second osmotic virial coefficient. A finite size correction is introduced to account for the impact of effectively concentrating the solutes in the periphery of the simulation box with increasing cavity size. We demonstrate the utility of the proposed method by evaluating second osmotic virial coefficients for methane in water as a function of temperature. The approach proposed here provides a physically transparent route for calculation of second osmotic virial coefficients by direct interrogation of simulation configurations without having to explicitly evaluate the long-range integral over solute-solute correlations required following McMillan-Mayer theory.     

Visual representation of DNA sequences for exon detection using non-parametric spectral estimation techniques

This paper presents a new approach for modeling of DNA sequences for the purpose of exon detection. The proposed model adopts the sum-of-sinusoids concept for the representation of DNA sequences. The objective of the modeling process is to represent the DNA sequence with few coefficients. The modeling process can be performed on the DNA signal as a whole or on a segment-by-segment basis. The created models can be used instead of the original sequences in a further spectral estimation process for exon detection. The accuracy of modeling is evaluated evaluated by using the Root Mean Square Error (RMSE) and the R-square metrics. In addition, non-parametric spectral estimation methods are used for estimating the spectral of both original and modeled DNA sequences. The results of exon detection based on original and modeled DNA sequences coincide to a great extent, which ensures the success of the proposed sum-of-sinusoids method for modeling of DNA sequences.     

多反应变量重复测量的混合效应模型及其应用

本文给出了多反应变量重复测量的协方差矩阵结构,探讨了用迭代广义最小二乘法来求解其带协变量和不带协变量的混合效应模型中固定效应和随机效应系数,并对１９９１年四川省高血压调查资料进行实例分析,得到其结论符合实际情况．     

Nonparametric correction for covariate measurement error in a stratified Cox model

Stratified Cox regression models with large number of strata and small stratum size are useful in many settings, including matched case-control family studies. In the presence of measurement error in covariates and a large number of strata, we show that extensions of existing methods fail either to reduce the bias or to correct the bias under nonsymmetric distributions of the true covariate or the error term. We propose a nonparametric correction method for the estimation of regression coefficients, and show that the estimators are asymptotically consistent for the true parameters. Small sample properties are evaluated in a simulation study. The method is illustrated with an analysis of Framingham data.     

Offspring fitness in relation to population size and genetic variation in the rare perennial plant species Gentiana pneumonanthe (Gentianaceae)

Seeds were sampled from 19 populations of the rare Gentiana pneumonanthe, ranging in size from 5 to more than 50,000 flowering plants. An analysis was made of variation in a number of life-history characters in relation to population size and offspring heterozygosity (based on seven polymorphic isozyme loci). Life-his-tory characters included seed weight, germination rate, proportion of seeds germinating, seedling mortality, seedling weight, adult weight, flower production per plant and proportion of plants flowering per family. Principal component analysis (PCA) reduced the dataset to three main fitness components. The first component was highly correlated with adult weight and flowering performance, the second with germination performance and the third component with seed and seedling weight and seedling mortality. The latter two components were considered as being maternally influenced, since these comprised life-history traits that were significantly correlated with seed weight. Multiple regression analysis showed that variation in the first fitness component was mainly associated with heterozygosity and not with population size, while the third fitness component was only correlated with population size and not with heterozygosity. The latter relationship appeared to be non-linear, which suggests a stronger loss of fitness in the smallest populations. The second (germination) component was neither correlated with population size nor with genetic variation. There was only a weak association between population size, heterozygosity and the population coefficients of variation for each life history character. Most correlation coefficients were negative, however, which suggests that there is more variation among progeny from smaller populations. We conclude that progeny from small populations of Gentiana pneumonanthe show reduced fitness and may be phenotypically more variable. One of the possible causes of the loss of fitness is a combination of unfavourable environmental circumstances for maternal plants in small populations and increased inbreeding. The higher phenotypic variation in small populations may also be a result of inbreeding, which can lead to deviation of individuals from the average phenotype through a loss of developmental stability.     

Population genetics of the population in the European north of the RSFSR. V. An evaluation of the virtual size of the population by computer simulation of marriage and migration processes

The paper deals with the effect of assortative matings on some parameters of population structure. To solve this problem, two rural populations near Archangelsk (river Peosa region) were used. Some genetic and demographic characteristics of these populations were described in previous publications. A comparison between random matches through a random number generator and true marriages was made by computer estimation of the spouses kinship coefficients. Significant avoidance of first and second cousins marriages in real populations was discovered. As a consequence of this avoidance of consanguinity, the effective breeding size of villages is increased twofold. Similar results were obtained by estimation os isonymy.     

Development of the caudal exoskeleton of the pliomerid trilobite Hintzeia plicamarginis new species

The later juvenile ontogeny of the caudal plate of the early Ordovician pliomerid trilobite Hintzeia plicamarginis new species likely comprised an initial phase during which the rate of appearance of new segments subterminally exceeded that of segment release into the thorax, a short phase of constant segment numbers, and a later phase during which release occurred but in which no new segments appeared. A distinct terminal region became manifest in the second phase. During the second and third phases growth coefficients for individual segments were about 1.1--1.2 per instar. Although the shapes of segments varied during growth, the pattern of ontogenetic shape change appears to have been broadly similar among segments. This suggests an homonomous trunk segment morphology regardless of thoracic or caudal identity in maturity. These results imply that control of trunk exoskeletal segment appearance and articulation were decoupled in this trilobite, and that the terminal region had a distinct mature morphology. H. plicamarginis is described as a new species.     

At-line determination of octanoic acid in cultivation broth--an electronic tongue (ET) feasibility study

Production monitoring of "natural" 2-heptanone from octanoic acid in an industrial fed-batch cultivation based on Penicillium roqueforti requires development of a method for determination of octanoic acid dissolved in the water phase. An electronic tongue array using six non-specific potentiometric sensors with solid inner contact, and a pH electrode, has been introduced by spiking octanoic acid to a substrate obtained from four different cultivations, representing variations in the relevant industrial matrix. Multivariate calibration was performed on acid concentrations spanning 0.65-20 mmol l(-1). Excluding the lowest concentration a global Partial Least Square regression model with a predicted versus measured correlation of 0.98 and a relative root mean square error of prediction of 5.1% (ln units) (RPD=5.5) signifies a highly acceptable prediction facility. This model was further tested by subjecting it to undiluted as well as diluted samples obtained from a cultivation process in which octanoic acid was catabolized; this led to acceptable prediction errors within the same range as for the global model. It is concluded that the ET sensor array can be applied for determination of octanoic acid in cultivation systems of the general P. roqueforti type.     

Sample Size Estimation in Cluster Randomized Studies with Varying Cluster Size

Cluster randomized studies are common in community trials. The standard method for estimating sample size for cluster randomized studies assumes a common cluster size. However often in cluster randomized studies, size of the clusters vary. In this paper, we derive sample size estimation for continuous outcomes for cluster randomized studies while accounting for the variability due to cluster size. It is shown that the proposed formula for estimating total cluster size can be obtained by adding a correction term to the traditional formula which uses the average cluster size. Application of these results to the design of a health promotion educational intervention study is discussed.     

The Effects of Variable Mutation Rates across Sites on the Phylogenetic Estimation of Effective Population Size or Mutation Rate of DNA Sequences

Multiple hits at some sites of human mitochondrial DNA sequences suggest that the commonly assumed infinite-sites model can be violated. Under the neutral Wright-Fisher model without recombination and population subdivision, we investigated, by computer simulations, the effect of multiple hits on the estimation of the essential parameter θ = 4N(e)μ by FU's UPBLUE procedure. We found that with moderate mutation rate heterogeneity, UPBLUE performs very well in terms of unbiasness and efficiency. Under extreme mutation rate heterogeneity, if sample size is reasonably large (e.g., >60), UPBLUE is still very satisfactory; otherwise we developed a new correction equation. Given knowledge of the degree of mutation rate heterogeneity, the performance of UPBLUE with the new correction equation was tested to be fairly satisfactory: there is almost no bias and the sampling variance is only slightly higher than the theoretical minimum variance. Thus, with an appropriate correction, UPBLUE is relatively robust to the multiple hits. In genealogies reconstructed by UPGMA, we found that the total length of branches directly linked to the tips is underestimated, and those far away tend to be overestimated, while the total length of all branches is not biased.