肿瘤表达谱基因芯片数据的混合效应模型分析

目的:研究混合效应模型(Mixed Effects Model)在肿瘤表达谱基因芯片数据分析中的检验效能,并探讨其分析效果。方法:采用混合效应模型分析肿瘤实例基因芯片数据,并以基因集富集分析方法(GSEA)作为参照比较分析结果的有效性和科学性,探讨其检验效果。结果:通过混合效应模型和基因集富集分析(GSEA)两种方法对肿瘤基因芯片数据的分析和比较,两种方法筛选出共同的差异表达通路外,混合效应模型额外地筛选出来GSEA未能检验到的8条差异表达通路,且得到文献支持;混和效应模型筛选出的前10个差异表达通路中有6个已有生物学证明而基因集富集分析方法(GSEA)筛选出的前10个差异表达通路中仅有4个已有生物学证明。结论:混合效应模型作为top-down方法中的典型代表,其优势在于通过构建潜变量达到降维目的,可有效地减少多个复杂的变异来源从而保证了结果的准确性和科学性,其检验效能优于基因集富集分析方法(GSEA),是一种行之有效的筛选肿瘤基因芯片数据的分析方法。     

Development of Bead-based Immunoassay to Quantify Neutralizing Antibody for Human Papillomavirus 16 and 18

Human papillomavirus (HPV) has drawn great attention globally because of its association with virtually all (99 %) cases of cervical cancer. HPV virus-like particles (VLPs) have been implicated as an effective HPV vaccine candidate. In this study, we optimized the relevant parameters for bacterial production of high-risk HPV16 and HPV18 VLP L1 proteins. The combination of glutathione S-transferase fusion and late log phase culture induction enhanced the solubility and yield of HPV L1 proteins. For detection and quantification of HPV-16 and -18 antibodies, a Luminex-based competitive immunoassay was developed for use in vaccine clinical trials. The characteristics of the assay that were optimized included monoclonal antibody specificity, conjugation of VLP to microspheres, VLP concentration, antibody concentration, dilution of samples, and incubation time. No cross-reactivity occurred. This immunoassay was proven to be sensitive and accurate, and is potentially valuable for vaccine candidate evaluation and clinical use.     

Statistical Analysis of Uniparental Disomy Data Using Hidden Markov Models

Genetic studies of uniparental disomy (UPD) employing many markers have helped geneticists to gain a better understanding of the molecular mechanisms underlying nondisjunction. However, most existing methods cannot simultaneously analyze all genetic markers and consistently incorporate crossover interference; they thus fail to make the most use of genetic information in the data. In the present article, we describe a hidden Markov model for multilocus uniparental disomy data. This method is based on the chi-square model for the crossover process and can simultaneously incorporate all marker information including untyped and uninformative markers. We then apply this novel method to analyze a set of UPD15 data.     

Automated Analysis of Single-Molecule Photobleaching Data by Statistical Modeling of Spot Populations

The number of fluorophores within a molecule complex can be revealed by single-molecule photobleaching imaging. A widely applied strategy to analyze intensity traces over time is the quantification of photobleaching step counts. However, several factors can limit and bias the detection of photobleaching steps, including noise, high numbers of fluorophores, and the possibility that several photobleaching events occur almost simultaneously. In this study, we propose a new approach, to our knowledge, to determine the fluorophore number that correlates the intensity decay of a population of molecule complexes with the decay of the number of visible complexes. We validated our approach using single and fourfold Atto-labeled DNA strands. As an example we estimated the subunit stoichiometry of soluble CD95L using GFP fusion proteins. To assess the precision of our method we performed in silico experiments showing that the estimates are not biased for experimentally observed intensity fluctuations and that the relative precision remains constant with increasing number of fluorophores. In case of fractional fluorescent labeling, our simulations predicted that the fluorophore number estimate corresponds to the product of the true fluorophore number with the labeling fraction. Our method, denoted by spot number and intensity correlation (SONIC), is fully automated, robust to noise, and does not require the counting of photobleaching events.     

Statistical Modeling of Observational Data With Spatial Dependencies

Abstract I provide a brief introduction to the concept of spatial autocorrelation and its incorporation into regression-type models. Spatial autocorrelation occurs when the response variable is correlated with itself at other locations in the region of interest. The autocorrelation usually takes a specific form where observations close in space are more correlated than those farther apart, and the rate of decay of the correlation is a function of the distance separating 2 locations. I present 2 commonly used models: 1) geostatistical modeling in which data are collected at points in the study region and 2) conditional autoregression (lattice) models in which data are aggregated over small nonoverlapping sub-areas of the study region. I also describe incorporation of explanatory covariates, such as habitat or physico-chemical attributes. I emphasize frequentist methods, but I briefly describe Bayesian approaches. I also provide some advantages, such as obtaining correct standard errors for estimators, and disadvantages, such as requirements for larger sample sizes, of incorporating spatial autocorrelation into the modeling effort. This information can aid researchers in designing and analyzing models of the relationships between species distributions and habitat. As a result, more informative models can be developed which further aid in management of wildlife.     

Statistical Analysis of Nonrectangular Family Data

MINQUE (Minimum Norm Quadratic Unbiased Estimators) theory is applied to the problem of estimation of variance components in family data (siblings) with variable family size. Using this approach, the traditional iterative maximum likelihood estimators are shown to be asymptotically normal, even though the data come from non-identical parent distributions. Asymptotic expressions are also obtained for the variance of the MINQUE estimators which hold even if the data are decidedly non-normal (e.g. a mixture of normals). In the case of normal data, exact small-sample variance estimates are derived. Simulations demonstrate the fast rate of convergence to asymptotic properties as the number of families increases. These desirable qualities suggest that the easy to compute MINQUE class of estimators may provide a useful alternative method for modelling familial aggregation.     

Effects on Household Labor of Temporary Out-migration by Male Household Heads in Nicaragua and Peru: an Analysis of Spot-check Time Allocation Data Using Mixed-effects Models

When adult males are temporarily away from the household, observational evidence suggests cross-cultural and intra-cultural variation in the effects of their absence on the labor of other household members. In subsistence-based economies, we predict that other adolescent or older members will work more in essential production activities that otherwise would be performed by the missing men. We test this hypothesis using spot-check time allocation datasets from rural Nicaragua and Peru and the methodology of mixed-effects statistical models. In Nicaragua, we find that the absence of male household heads rarely necessitates substitute labor by household co-residents, apparently because men typically time their absences to coincide with the non-peak agricultural season. In Peru, the absence of male household heads results in increased men’s work by co-residents only under unusual circumstances, as households apparently rely on other strategies to mitigate for the loss of labor. In addition to the comparative empirical analysis of the two cases, we show how mixed-effects models allow for individual heterogeneity and data structures that confound more familiar statistical techniques and occasionally produce spurious results. Mixed-effects modeling techniques will be necessary if we are to realize the analytic potential of the extensive, standardized time allocation datasets gathered by anthropologists.     

Calibrating Statistical Population Reconstruction Models Using Catch-Effort and Index Data

Abstract: This paper illustrates how age-at-harvest data, when combined with hunter-effort information routinely collected by state game management agencies, can be used to estimate and monitor trends in big game abundance. Twenty-four years of age-at-harvest data for black-tailed deer (Odocoileus hemionus) were analyzed to produce abundance estimates ranging from 1,281 adult females to 3,232 adult females on a 22,079-ha tree farm in Pierce County, Washington, USA. The annual natural survival probability was estimated to be 0.7293 ( = 0.0097) for this female population. The estimated abundance was highly correlated with an independent browse damage index (r = 0.8131, P < 0.001). A population reconstruction incorporating the browse index did not substantially improve the model fit but did provide an auxiliary model for predicting deer abundance. This population reconstruction illustrates a cost-effective alternative to expensive big game survey methods.     

利用悬液芯片系统建立一种高通量检测牛奶中头孢氨苄和莱克多巴胺残留的方法

目的:旨在应用基于荧光编码微球技术的悬液芯片系统建立一种方便、稳定性好及高通量的检测牛奶中头孢氨苄和莱克多巴胺残留的免疫检测方法。方法:利用碳二亚胺法将抗生素合成抗原与表面具有羧基的聚苯乙烯微球通过酰胺键偶联成捕获抗原。利用捕获抗原、抗生素的单克隆抗体及抗生素标准品构建竞争性免疫检测体系。荧光标记的羊抗小鼠的IgG作为荧光探针标记与捕获抗原结合的单克隆抗体得到悬液芯片系统的检测物。悬液芯片系统的检测器由两束特殊的激光构成,能够检测荧光探针荧光强度的同时分辨不同型号的微球以实现高通量检测的目的。结果:通过对头孢氨苄和莱克多巴胺合成抗原包被微球的条件进行优化得到包被100μl的微球所需两者合成抗原的量分别是8.4μg 和 87.73μg;实验结果表明抗生素的单克隆抗体特异性良好;在牛奶中,该方法对头孢氨苄和莱克多巴胺的检测限(LOD)分别是20.59 ng/ml 和23.51 ng/ml, 标准添加回收率在70%~110%之间。     

Statistical Object Data Analysis of Taxonomic Trees from Human Microbiome Data

Human microbiome research characterizes the microbial content of samples from human habitats to learn how interactions between bacteria and their host might impact human health. In this work a novel parametric statistical inference method based on object-oriented data analysis (OODA) for analyzing HMP data is proposed. OODA is an emerging area of statistical inference where the goal is to apply statistical methods to objects such as functions, images, and graphs or trees. The data objects that pertain to this work are taxonomic trees of bacteria built from analysis of 16S rRNA gene sequences (e.g. using RDP); there is one such object for each biological sample analyzed. Our goal is to model and formally compare a set of trees. The contribution of our work is threefold: first, a weighted tree structure to analyze RDP data is introduced; second, using a probability measure to model a set of taxonomic trees, we introduce an approximate MLE procedure for estimating model parameters and we derive LRT statistics for comparing the distributions of two metagenomic populations; and third the Jumpstart HMP data is analyzed using the proposed model providing novel insights and future directions of analysis.     

肿瘤微阵列数据统计分析概述

微阵列技术已广泛应用于生物学和医学研究领域,如肿瘤的诊断和分型、预测和治疗,理解肿瘤的发生机制、生物学通路和基因网络。统计学方法在这一科学挑战中的地位至关重要。我们综述了微阵列实验数据分析的统计学方法最新发展,主要描述了微阵列数据的标准化、差异表达基因的统计学检验及微阵列技术在肿瘤治疗中的应用,重点介绍了时间序列微阵列数据分析方法和基因调控网络在肿瘤研究中的最新发展。     

Characterization of DNA-Binding Proteins Using Multiplexed Competitor EMSA

We describe a low-cost high-throughput technique to characterize nuclear protein DNA-binding interactions. This technique, known as Multiplexed Competitor Electrophoretic Mobility Shift Assay, uses a series of multiplexed oligonucleotide DNA consensus competitors, in combination with a standard electrophoretic mobility shift assay procedure, to efficiently characterize DNA-binding proteins. We show utility for the method to identify a previously unreported hepatocyte nuclear factor-3 site created in intron 8 of the lipoprotein lipase gene by a common single-nucleotide polymorphism (rs327).     

Multiplexed Fluorescent Microarray for Human Salivary Protein Analysis Using Polymer Microspheres and Fiber-optic Bundles

Herein, we describe a protocol for simultaneously measuring six proteins in saliva using a fiber-optic microsphere-based antibody array. The immuno-array technology employed combines the advantages of microsphere-based suspension array fabrication with the use of fluorescence microscopy. As described in the video protocol, commercially available 4.5 μm polymer microspheres were encoded into seven different types, differentiated by the concentration of two fluorescent dyes physically trapped inside the microspheres. The encoded microspheres containing surface carboxyl groups were modified with monoclonal capture antibodies through EDC/NHS coupling chemistry. To assemble the protein microarray, the different types of encoded and functionalized microspheres were mixed and randomly deposited in 4.5 μm microwells, which were chemically etched at the proximal end of a fiber-optic bundle. The fiber-optic bundle was used as both a carrier and for imaging the microspheres. Once assembled, the microarray was used to capture proteins in the saliva supernatant collected from the clinic. The detection was based on a sandwich immunoassay using a mixture of biotinylated detection antibodies for different analytes with a streptavidin-conjugated fluorescent probe, R-phycoerythrin. The microarray was imaged by fluorescence microscopy in three different channels, two for microsphere registration and one for the assay signal. The fluorescence micrographs were then decoded and analyzed using a homemade algorithm in MATLAB.     

DNA芯片技术中利用内标对数据归一化后检测基因的表达变化

在DNA芯片技术中 ,通过反转录反应 ,由mRNA合成带有荧光标记物的cDNA的过程中 ,往往要参入已知质量的poly(A) + RNA ,以对DNA芯片的检测灵敏度进行归一化处理 .通过体外转录的方法 ,以真核生物的cDNA克隆中的DNA片段为模板合成poly(A) +RNA ,对之定量后 ,以不同的质量比参入到样品的反转录体系中 ,代表不同的RNA拷贝丰度 ,从而对DNA芯片检测的灵敏度进行了定量 ,并得到DNA芯片上杂交点的荧光信号强度与基因表达的RNA拷贝数成正相关的关系 .利用含有内标的DNA芯片检测了热击反应后酵母细胞的基因表达变化 ,结果与Northern印迹方法检测结果是相符的