Ascertainment: An Overwiew of the Classical Segregation Analysis Model for Independent Sibships

Several different methodologies for parameter estimation under various ascertainment sampling schemes have been proposed in the past. In this article, some of the methodologies that have been proposed for independent sibships under the classical segregation analysis model are synthesized, and the general likelihoods derived for single, multiple and complete ascertainment. The issue of incorporating the sibship size distribution into the analysis is addressed, and the effect of conditioning the likelihood on the observed sibship sizes is discussed. It is shown that when the number of probands in a sibship is not specified, the corresponding likelihood can be used for a broader class of ascertainment schemes than is subsumed by the classical model.     

基于EM算法的遗传重组率估计方法

EM算法是在不完全信息资料下实现参数极大似然估计的一种通用方法．本文导出了双位点不同标记类型,包括共显性-共显性,共显性-显性和显性-显性3种模式下,估计遗传重组率的EM算法,以及获得重组率抽样方差的Bootstrap方法;并将之推广到部分个体缺失标记基因型(未检测到电泳谱带)下的重组率估计．通过大量Monte Carlo模拟研究发现: (1)连锁紧密时,样本容量对重组率的估计影响不大;连锁松散时,需要较大样本容量才可检测到连锁以及实现重组率的较精确估计．(2)用包含缺失标记的所有个体估计重组率比仅用其中的非缺失标记个体估计更准确,且可显著提高连锁检测的统计功效．     

A Local Agreement Filtering Algorithm for Transmission EM Reconstructions

We present LAFTER, an algorithm for de-noising single particle reconstructions from cryo-EM.Single particle analysis entails the reconstruction of high-resolution volumes from tens of thousands of particle images with low individual signal-to-noise. Imperfections in this process result in substantial variations in the local signal-to-noise ratio within the resulting reconstruction, complicating the interpretation of molecular structure. An effective local de-noising filter could therefore improve interpretability and maximise the amount of useful information obtained from cryo-EM maps.LAFTER is a local de-noising algorithm based on a pair of serial real-space filters. It compares independent half-set reconstructions to identify and retain shared features that have power greater than the noise. It is capable of recovering features across a wide range of signal-to-noise ratios, and we demonstrate recovery of the strongest features at Fourier shell correlation (FSC) values as low as 0.144 over a 256³-voxel cube. A fast and computationally efficient implementation of LAFTER is freely available.We also propose a new way to evaluate the effectiveness of real-space filters for noise suppression, based on the correspondence between two FSC curves: 1) the FSC between the filtered and unfiltered volumes, and 2) C_ref, the FSC between the unfiltered volume and a hypothetical noiseless volume, which can readily be estimated from the FSC between two half-set reconstructions.     

Alternative implementations of Monte Carlo EM algorithms for likelihood inferences

Two methods of computing Monte Carlo estimators of variance components using restricted maximum likelihood via the expectation-maximisation algorithm are reviewed. A third approach is suggested and the performance of the methods is compared using simulated data.     

栽培大豆与半野生大豆杂种F_2群体中RFLP标记的偏分离及其形成原因的分析

本文研究了大豆５６个ＤＮＡ限制性片段长度多态性（ＲＦＬＰ）标记在一栽培大豆／半野生大豆杂种Ｆ２群体中的分离。结果表明,２５％的ＲＦＬＰ标记表现了偏分离,偏离的方向主要趋于栽培大豆亲本,其形成原因主要是存在着配子体选择。这对研究大豆的遗传及育种选择等有着重要的指导意义。     

Modeling segregation distortion for viability selection I. Reconstruction of linkage maps with distorted markers

Molecular markers have been widely used to map quantitative trait loci (QTL). The QTL mapping partly relies on accurate linkage maps. The non-Mendelian segregation of markers, which affects not only the estimation of genetic distance between two markers but also the order of markers on a same linkage group, is usually observed in QTL analysis. However, these distorted markers are often ignored in the real data analysis of QTL mapping so that some important information may be lost. In this paper, we developed a multipoint approach via Hidden Markov chain model to reconstruct the linkage maps given a specified gene order while simultaneously making use of distorted, dominant and missing markers in an F₂ population. The new method was compared with the methods in the MapManager and Mapmaker programs, respectively, and verified by a series of Monte Carlo simulation experiments along with a working example. Results showed that the adjusted linkage maps can be used for further QTL or segregation distortion locus (SDL) analysis unless there are strong evidences to prove that all markers show normal Mendelian segregation.     

Genetic Segregation Analysis of Early-Onset Recurrent Unipolar Depression

Major depression is a relatively common psychiatric disorder that can be quite debilitating. Family, twin, and adoption studies indicate that unipolar depression has both genetic and environmental components. Early age at onset and recurrent episodes in the proband each increase the familiarity of the illness. To investigate the potential genetic underpinnings of the disease, we have performed a complex segregation analysis on 832 individuals from 50 multigenerational families ascertained through a proband with early-onset recurrent unipolar major depression. The analysis was conducted by use of regressive models, to test a variety of hypotheses to explain the familial aggregation of recurrent unipolar depression. Analyses were conducted under two alternative definitions of affection status for the relatives of probands: (1) "narrow," in which relatives were assumed to be affected only if they were diagnosed with recurrent unipolar depression; and (2) "broad," in which relatives were assumed to be affected if diagnosed with any major affective illness. Under the narrow-definition assumption, the model that best explains these family data is a transmitted (although non-Mendelian) recessive major effect with significant residual parental effects on affection status. Under the broad-definition assumption, the best-fitting model is a Mendelian codominant major locus with significant residual parental and spousal effects.     

非线性再生散度随机效应模型的极大似然估计及EM算法

非线性再生散度随机效应模型是指数族非线性随机效应模型和非线性再生散度模型的推广和发展．通过视模型中的随机效应为假想的缺失数据和应用Metropolis-Hastings（MH）算法,提出了模型参数极大似然估计的Monte-Carlo EM（MCEM）算法,并用模拟研究和实例分析说明了该算法的可行性．     

Testing for familial correlation in age-at-onset

The analysis of family-study data sometimes focuses on whether a dichotomous trait tends to cluster in families. For traits with variable age-at-onset, it may be of interest to investigate whether age-at-onset itself also exhibits familial clustering. A complication in such investigations is that censoring by age-at-ascertainment can induce artifactual familial correlation in the age-at-onset of affected members. A further complication can be that sample inclusion criteria involve the affection status of family members. The purpose here is to present an approach to testing for correlation that is not confounded by censoring by age-at-ascertainment and may be applied with a broad range of inclusion criteria. The approach involves regression statistics in which subjects's covariate terms are chosen to reflect age-at-onset information from the subjects's affected family members. The results of analyses of data from a family-study of panic disorder illustrate the approach.     

Imputing unobserved values with the EM algorithm under left and right-truncation, and interval censoring for estimating the size of hidden populations

Capture–recapture techniques have been used for considerable time to predict population size. Estimators usually rely on frequency counts for numbers of trappings; however, it may be the case that these are not available for a particular problem, for example if the original data set has been lost and only a summary table is available. Here, we investigate techniques for specific examples; the motivating example is an epidemiology study by Mosley et al., which focussed on a cholera outbreak in East Pakistan. To demonstrate the wider range of the technique, we also look at a study for predicting the long-term outlook of the AIDS epidemic using information on number of sexual partners. A new estimator is developed here which uses the EM algorithm to impute unobserved values and then uses these values in a similar way to the existing estimators. The results show that a truncated approach – mimicking the Chao lower bound approach – gives an improved estimate when population homogeneity is violated.     

两个位点主基因控制的质量—数量性状的遗传分析

应用极大似然法和EM算法提出了关于两个位点主基因控制的质量．数量性状的遗传分析方法,参照质量性状两位点互作在F_2代的分离比率建立了7种遗传假设及其似然比测验的程序,讨论了应用这一方法时应注意的几个问题．     

Segregation of the photosystems in higher plant thylakoids and short- and long-term regulation by a mesoscopic approach

In this paper we consider the relationship between the lateral segregation of photosystems I and II in the grana and characteristics of the short- and long-term regulation in thylakoids following the mesoscopic approach. Our study is thermodynamic; it is based on the Flory-Huggins theory for binary mixtures and the McMillan-Mayer theory of heterogeneous solutions. We demonstrate that state transitions promote rearrangement of photosystems by either favoring their mixing after LHCII phosphorylation or enhancing their segregation after LHCII dephosphorylation. This regulation influences the entire system properties locally. We also demonstrate that the variations of the photosystem ratio promote rearrangement of the photosystems preserving their segregation. This regulation influences the entire system properties globally. The studies presented are another indication of the importance of the segregation of the photosystems in the grana thylakoids of higher plants. Segregation of PSIs and PSIIs is a signature of the spinodal decomposition, which is a fine regulatory mechanism, related to both the short- and long-term adaptations of the photosynthetic apparatus in higher plant thylakoids.     

Analysis and Design of an Agent Searching Algorithm for e-Marketplaces

Recently, agent techniques in electronic marketplaces (e-marketplaces) bring B-to-B trading into a new era. However, not much analysis on the behavior of agents has been reported. In this paper, based on the ant algorithm in network routing, we introduce a jumping (searching) model for agents in an e-marketplace network. However, we should be aware that if there are too many agents in the e-marketplace network, they will use up all communication bandwidth and computing resource. It is inevitable to investigate the behavior of agents, such as agent population. Based on the existing results in the ant algorithm in network routing, we present the behavior of agents in an e-marketplace network. Hence, we can control the agent population by setting the appropriate agent generation rate.     

Numerical comparison between powers of maximum likelihood and analysis of variance methods for QTL detection in progeny test designs: the case of monogenic inheritance

Simulations are used to compare four statistics for the detection of a quantitative trait locus (QTL) in daughter and grand-daughter designs as defined by Soller and Genizi (1978) and Weller et al. (1990): (1) the Fisher test of a linear model including a marker effect within sire or grand-sire effect; (2) the likelihood ratio test of a segregation analysis without the information given by the marker; (3) the likelihood ratio test of a segregation analysis considering the information from the marker; and (4) the lod score which is the likelihood ratio test of absence of linkage between the marker and the QTL. In all cases the two segregation analyses are more powerful for QTL detection than are either the linear method or the lod score. The differences in power are generally limited but may be significant (in a ratio of 1 to 3 or 4) when the QTL has a small effect (0.2 standard deviations) and is not closely linked to the marker (recombination rate of 20% or more).     

A disequilibrium model for detecting genetic mutations for cancer

It has been recognized that genetic mutations in specific nucleotides may give rise to cancer via the alteration of signaling pathways. Thus, the detection of those cancer-causing mutations has received considerable interest in cancer genetic research. Here, we propose a statistical model for characterizing genes that lead to cancer through point mutations using genome-wide single nucleotide polymorphism (SNP) data. The basic idea of the model is that mutated genes may be in high association with their nearby SNPs because of evolutionary forces. By genotyping SNPs in both normal and cancer cells, we formulate a polynomial likelihood to estimate the population genetic parameters related to cancer, such as allele frequencies of cancer-causing alleles, mutation rates of alleles derived from maternal or paternal parents, and zygotic linkage disequilibria between different loci after the mutation occurs. We implement the EM algorithm to estimate some of these parameters because of the missing information in the likelihood construction. The model allows the elegant tests of the significant associations between mutated cancer genes and genome-wide SNPs, thus providing a way for predicting the occurrence and formation of cancer with genetic information. The model, validated through computer simulation, may help cancer geneticists design efficient experiments and formulate hypotheses for cancer gene identification.