混合家系遗传参数估计方法研究

针对混合家系遗传参数估计,本文在假定公畜方差组分和母畜方差组分相等这一理论基础上,通过对方差分析的期望均方组成分析,提出了新的遗传力估计方法,以及某些特殊情况下的近似估计方法。通过一个估测实例比较了几种遗传力估计方法,结果表明,本文方法与全同胞组分估计最为接近,而且遗传力标准误最小,本文近似估计方法的效果也较好。对各种方法而言,资料越不平衡其差异越大。本文方法可以在一定程度上弥补全同胞分析时,因实际资料的公母畜方差组分差异过大的缺陷,具有实际可行性。此外,由于本文方法是用单因方差分析解决二因方差分析问题,计算更为简便,并可免于计算混合家系平均亲缘相关系数。     

Comparative analysis of methods for estimating arm segment parameters and joint torques from inverse dynamics

A common problem in the analyses of upper limb unfettered reaching movements is the estimation of joint torques using inverse dynamics. The inaccuracy in the estimation of joint torques can be caused by the inaccuracy in the acquisition of kinematic variables, body segment parameters (BSPs), and approximation in the biomechanical models. The effect of uncertainty in the estimation of body segment parameters can be especially important in the analysis of movements with high acceleration. A sensitivity analysis was performed to assess the relevance of different sources of inaccuracy in inverse dynamics analysis of a planar arm movement. Eight regression models and one water immersion method for the estimation of BSPs were used to quantify the influence of inertial models on the calculation of joint torques during numerical analysis of unfettered forward arm reaching movements. Thirteen subjects performed 72 forward planar reaches between two targets located on the horizontal plane and aligned with the median plane. Using a planar, double link model for the arm with a floating shoulder, we calculated the normalized joint torque peak and a normalized root mean square (rms) of torque at the shoulder and elbow joints. Statistical analyses quantified the influence of different BSP models on the kinetic variable variance for given uncertainty on the estimation of joint kinematics and biomechanical modeling errors. Our analysis revealed that the choice of BSP estimation method had a particular influence on the normalized rms of joint torques. Moreover, the normalization of kinetic variables to BSPs for a comparison among subjects showed that the interaction between the BSP estimation method and the subject specific somatotype and movement kinematics was a significant source of variance in the kinetic variables. The normalized joint torque peak and the normalized root mean square of joint torque represented valuable parameters to compare the effect of BSP estimation methods on the variance in the population of kinetic variables calculated across a group of subjects with different body types. We found that the variance of the arm segment parameter estimation had more influence on the calculated joint torques than the variance of the kinematics variables. This is due to the low moments of inertia of the upper limb, especially when compared with the leg. Therefore, the results of the inverse dynamics of arm movements are influenced by the choice of BSP estimation method to a greater extent than the results of gait analysis.     

Variance Component Estimation for Mixed Model Analysis of cDNA Microarray Data

Microarrays provide a valuable tool for the quantification of gene expression. Usually, however, there is a limited number of replicates leading to unsatisfying variance estimates in a gene‐wise mixed model analysis. As thousands of genes are available, it is desirable to combine information across genes. When more than two tissue types or treatments are to be compared it might be advisable to consider the array effect as random. Then information between arrays may be recovered, which can increase accuracy in estimation. We propose a method of variance component estimation across genes for a linear mixed model with two random effects. The method may be extended to models with more than two random effects. We assume that the variance components follow a log‐normal distribution. Assuming that the sums of squares from the gene‐wise analysis, given the true variance components, follow a scaled χ²‐distribution, we adopt an empirical Bayes approach. The variance components are estimated by the expectation of their posterior distribution. The new method is evaluated in a simulation study. Differentially expressed genes are more likely to be detected by tests based on these variance estimates than by tests based on gene‐wise variance estimates. This effect is most visible in studies with small array numbers. Analyzing a real data set on maize endosperm the method is shown to work well. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Designs for slope ratio assays

Optimal designs are obtained for the estimation of relative potency in a slope ratio assay. Three criteria are considered based on the asymptotic variance of the standard point estimator. Efficiency functions are derived and numerical examples are given.     

Sources of variability in foot and mouth disease vaccine potency estimates based on serum neutralizing antibody assay

Some vaccines can be assayed for potency by measuring the serum antibody response they produce in vaccinated test animals. Using data obtained from potency assays on batches of foot and mouth disease vaccine, the sources of variability in such a method were examined. A linear model is proposed for the analysis of replicate serum neutralizing antibody assays, which represents an improvement on the usual approach of working with only a mean serum assay value for each test animal. Components of variance were calculated, allowing the relative importance of the numbers of test animals, or the numbers of serum assays per test animal, to be estimated in terms of the variability of the overall group mean antibody response. A method is described for calculating fiducial intervals for the serological potency estimates, and it is shown that these intervals are no larger than, and are in fact probably smaller than, those obtained from quantal challenge tests. The results have important implications for the design and analysis of similar biological tests used for other products.     

MIXED MODEL APPROACHES FOR ESTIMATING GENETIC VARIANCES AND COVARIANCES

The limitations of methods for analysis of variance(ANOVA)in estimating genetic variances are discussed. Among the three methods(maximum likelihood ML, restricted maximum likelihood REML, and minimum norm quadratic unbiased estimation MINQUE)for mixed linear models, MINQUE method is presented with formulae for estimating variance components and covariances components and for predicting genetic effects. Several genetic models, which cannot be appropriately analyzed by ANOVA methods, are introduced in forms of mixed linear models. Genetic models with independent random effects can be analyzed by MINQUE(1)method whieh is a MINQUE method with all prior values setting 1. MINQUE(1)method can give unbiased estimation for variance components and covariance components, and linear unbiased prediction (LUP) for genetic effects. There are more complicate genetic models for plant seeds which involve correlated random effects. MINQUE(0/1)method, which is a MINQUE method with all prior covariances setting 0 and all prior variances setting 1, is suitable for estimating variance and covariance components in these models. Mixed model approaches have advantage over ANOVA methods for the capacity of analyzing unbalanced data and complicated models. Some problems about estimation and hypothesis test by MINQUE method are discussed.     

GCTA: a tool for genome-wide complex trait analysis

For most human complex diseases and traits, SNPs identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability. Here we report a user-friendly software tool called genome-wide complex trait analysis (GCTA), which was developed based on a method we recently developed to address the "missing heritability" problem. GCTA estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation. We focus on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation. The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets.     

Variance-component estimation from human sibship data

The large-sample relative efficiencies of the analysis-of-variance (ANOVA) estimators of variance components and the intraclass correlation coefficient rho are investigated for the unbalanced single classification in the context of family studies. The efficiency of an analysis based on the method of unweighted group means is also investigated. From a Monte Carlo study which generates the group sizes from typical family-size distributions it is found that the relative efficiency of the ANOVA estimators of the between-group variance component exceeds 95% for values of .2 less than or equal to rho less than or equal to .4, but can fall below 60% for values of rho that are very close to zero. For the estimation of the between-group variance component the method of unweighted means tends to be preferable to the ANOVA method only if rho greater than .5.     

利用单元内方差分析法估计遗传参数的探讨

在遗传力的估计过程中,需将多种非遗传因素的影响从公畜间方差或者母畜间方差中剔除。在我国常使用的是盛志廉教授提出的单元内同胞相关法。本文对该法从理论上进行了更详细的证明,并将其推广到两层分类方差分析时的情况。同时还给出了当公母畜彼此间有亲缘关系时,利用单元内方差分析估计遗传力的方法。这些方法既可使遗传力的估计简便,又具有多因方差分析的功用。     

遗传参数估计原理探讨——亲本间亲缘相关时的参数估计方法

本文通过对方差分析模型和相应的期望均方组成的分析,提出了用同胞资料估计遗传参数,当父本间、母本间及父母本间存在亲缘相关时的参数估计方法,并以实例阐明其应用方法。采用本文方法估计的遗传参数高于采用假定亲本间不相关时的常规估计方法的结果,亲本间相关越大,这种偏差也越大。计算机程序PARESTH、PARESTF为本方法推广应用提供了方便。此外,本文结论对一般的方差分析,在因素水平间相关程度能确定的情况下也是适用的。     

In vitro assay for erythropoietin

An in vitro assay method for the quantitative estimation of erythropoietin has been developed. The principle of the method is based on the stimulation of LP catalyzed iodination of MIT by erythropoietin and the iodination reaction was found to be linearly proportional to the increasing concentration of erythropoietin of same potency or same concentration of increasing potency. This assay procedure could be utilized for clinical purposes for the estimation of erythropoietin content of biological samples, like urine, serum etc. This method is very simple, rapid, highly specific and sensitive enough to detect as little as 0.25 mU of erythropoietin.     

ACUTE ETHANOL EXPOSURE DECREASES THE ANALGESIC POTENCY OF MORPHINE IN MICE

Chronic (7 days), forced ethanol drinking can decrease the analgesic potency of opioid agonists in mice. In the present study, the effect of short-term ethanol treatment was examined using forced ethanol access and ethanol injection protocols. Mice were given forced access to 1, 3 or 7% (v/v) ethanol for 24 hr and then tested for s.c. morphine analgesia using the tailflick assay. Controls had access to water. Another group of mice was injected i.p. with 2.5 g/kg ethanol or water 4 times over a 21 hr period and tested 3 hr after the final injection for morphine analgesia. Other mice were injected once i.p. with 1, 2 or 3 g/kg ethanol or water and tested 24 hr later using the tailflick. In the forced access study, ethanol dose-dependently decreased morphine's analgesic potency with the highest dose (7%) producing a 1.6-fold shift in the ED₅₀. This decrease in morphine potency was similar to that found in a related study using 7% ethanol for 7 days (1.8-fold shift). Repeated ethanol injections significantly reduced the analgesic potency of morphine (1.9-fold shift), whereas, a single injection of 1, 2 or 3 g/kg ethanol did not alter the potency of morphine. Control studies indicated that neither 24 hr water nor food deprivation affected morphine potency. Overall, these data show that sustained exposure to ethanol over a 24 hr period will dose-dependently decrease morphine's analgesic potency. © 1998 Elsevier Science Inc.     

Approximating identity-by-descent matrices using multiple haplotype configurations on pedigrees

Identity-by-descent (IBD) matrix calculation is an important step in quantitative trait loci (QTL) analysis using variance component models. To calculate IBD matrices efficiently for large pedigrees with large numbers of loci, an approximation method based on the reconstruction of haplotype configurations for the pedigrees is proposed. The method uses a subset of haplotype configurations with high likelihoods identified by a haplotyping method. The new method is compared with a Markov chain Monte Carlo (MCMC) method (Loki) in terms of QTL mapping performance on simulated pedigrees. Both methods yield almost identical results for the estimation of QTL positions and variance parameters, while the new method is much more computationally efficient than the MCMC approach for large pedigrees and large numbers of loci. The proposed method is also compared with an exact method (Merlin) in small simulated pedigrees, where both methods produce nearly identical estimates of position-specific kinship coefficients. The new method can be used for fine mapping with joint linkage disequilibrium and linkage analysis, which improves the power and accuracy of QTL mapping.     

脑磁图神经活动源数目的估计

在脑磁图信号的分析中,正确估计出脑磁图神经活动源的数目是进一步分析脑磁图信号的前提。目前广泛采用的信息论方法和主成分分析方法都是根据特征值来确定源的数目,这两种方法在源数目较多、噪声较强的情况下,会导致误判。该文提出了一种噪声调节自动阈值的脑磁图源数目判断方法,利用基于噪声调节的主成分分析并结合聂曼- 皮尔逊准则对脑磁图源数目进行估计。同时,该方法采用了基于小波的噪声方差估计,实现了脑磁图信号中噪声方差的精确估计。通过对基于信息论方法、主成分分析方法以及该文所提议方法的实验结果的比较,表明该文所提议方法能更准确地估计脑磁图源数目,特别是在源数目较多、信噪比较小的情况下,仍能准确地估计脑磁图源数目,具有较大的实际意义。     

Possibilities and limitations of weighted averaging

A statistical analysis of a weighted averaging procedure for the estimation of small signals buried in noise (Hoke et al. 1984a) is given. The weighting factor used by this method is in inverse proportion to the variance estimated for the noise. It is shown that, compred to conventional averaging, weighted averaging can improve the signal-to-noise ratio to a high extent if the variance of the noise changes as a function of time. On the other hand, uncritical application of the method involves the danger that the signal amplitude is underestimated. How serious this effect is depends on the number of degrees of freedom available for the estimation of the weighting factor. The effect can be neglected, if this number is sufficiently increased by means of an appropriate preprocessing.     

Modification of the response to opioid and nonopioid drugs by chronic opioid antagonist treatment

Chronic exposure to opioid antagonists increases the analgesic actions of opioids such as morphine. In the present studies, morphine's analgesic potency was increased (supersensitivity) following an 8 day subcutaneous naltrexone implant in mice, but not following a 1 day implant. Supersensitivity was maximal 24hr following the 8 day implant and declined linearly and had returned to control levels by 120hr. Implantation of naltrexone pellets for 8 days was found to increase the relative analgesic potency of methadone by 120%, while the lethal potency of cocaine was slightly (19%), but significantly, decreased. In contrast, identical treatment did not alter the potency of the benzodiazepine alprazolam to induce ataxia.     

The utility of the macrophage migration inhibition test for in vitro titration of tuberculins

The purpose of this study was to explore the fundamental principle of the potency estimation of tuberculins, as applied in vitro by the macrophage migration inhibition test (MIT) under agarose. The MIT was performed using specifically sensitized mouse and guinea-pig peritoneal macrophages and serial dilutions of the analogous PPD (purified protein derivatives of tuberculin) tuberculins as antigen. Statistical studies performed included (a) the standard deviation of the mean migration areas, (b) the analysis of variance, (c) the regression analysis, (d) its corresponding linearity test and (e) the determination of the related correlation coefficient. It was shown for the first time and in both animal species under study that there is correspondence between the log dose-response relationship of the tuberculin PPD in MIT under agarose and the well known in tuberculin cutaneous reaction. The MIT may therefore successfully replace the in vivo titration of tuberculins.     

Effect of apoE on triglyceride emulsion interaction with hepatocyte and hepatoma G2 cells

The uptake and internalization of a triglyceride emulsion by rat hepatocytes in culture less than 24 hr was either inhibited or uninfluenced by apoE. ApoE significantly increased the uptake of these emulsions in later cultures. Specific low density lipoprotein (LDL) binding was similar for hepatocyte monolayers prior to and after 24 hr. Rat hepatocytes in culture for 2 days, which were treated with collagenase, detached and then replated within 1 hr and were apoE-responsive in 2 hr. Heparin inhibited the apoE stimulation in both hepatocytes and hepatoma monolayers. Heparin wash of hepatocytes or hepatoma cells incubated with apoE-[14C]triolein emulsions at 4 degrees C resulted in a considerable loss in radiolabeled cell lipid. A similar wash after 37 degrees C incubations produced little loss suggesting internalization. Hepatocytes had lower affinity but similar apoE-emulsion binding capacity compared to hepatoma cells. Triolein emulsions with apoE were significantly more rapidly metabolized by the hepatocyte than unsupplemented emulsions. The apoE-mediated hepatocyte lipid uptake was inhibited by apoC proteins. High molar ratios of free fatty acid/albumin also suppressed hepatocyte apoE-mediated lipid uptake. Both rat high density lipoprotein (HDL) and LDL inhibited with a potency directly related to their content of apoE. Human LDL and HDL without apoE also inhibited the interaction with less potency than the rat lipoproteins. Human HDL inhibition was diminished after removal of apoC proteins.     

多QTL定位的压缩估计方法

本文综述了多标记分析和多QTL定位的压缩估计方法。对于前者,Xu（Genetics,2003,163：789—801）首先提出了Bayesian压缩估计方法。其关键在于让每个效应有一个特定的方差参数,而该方差又服从一定的先验分布,以致能从资料中估计之。由此,能够同时估计大量分子标记基因座的遗传效应,即使大多数标记的效应是可忽略的。然而,对于上位性遗传模型,其运算时间还是过长。为此,笔者将上述思想嵌入极大似然法,提出了惩罚最大似然方法。模拟研究显示：该方法能处理变量个数大于样本容量10倍左右的线性遗传模型。对于后者,本文详细介绍了基于固定区间和可变区间的Bayesian压缩估计方法。固定区间方法可处理中等密度的分子标记资料;可变区间方法则可分析高密度分子标记资料,甚至是上位性遗传模型。对于上位性检测,已介绍的惩罚最大似然方法和可变区间Bayesian压缩估计方法可供利用。应当指出,压缩估计方法在今后的eQTL和QTN定位以及基因互作网络分析等研究中也是有应用价值的。