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Motivated by a study of human papillomavirus infection in women, we present a Bayesian binomial regression analysis in which the response is subject to an unconstrained misclassification process. Our iterative approach provides inferences for the parameters that describe the relationships of the covariates with the response and for the misclassification probabilities. Furthermore, our approach applies to any meaningful generalized linear model, making model selection possible. Finally, it is straightforward to extend it to multinomial settings. 相似文献
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Andrea Callegaro Jeremie J. P. Lebrec Jeanine J. Houwing‐Duistermaat 《Biometrical journal. Biometrische Zeitschrift》2010,52(1):22-33
In order to study family‐based association in the presence of linkage, we extend a generalized linear mixed model proposed for genetic linkage analysis (Lebrec and van Houwelingen (2007), Human Heredity 64 , 5–15) by adding a genotypic effect to the mean. The corresponding score test is a weighted family‐based association tests statistic, where the weight depends on the linkage effect and on other genetic and shared environmental effects. For testing of genetic association in the presence of gene–covariate interaction, we propose a linear regression method where the family‐specific score statistic is regressed on family‐specific covariates. Both statistics are straightforward to compute. Simulation results show that adjusting the weight for the within‐family variance structure may be a powerful approach in the presence of environmental effects. The test statistic for genetic association in the presence of gene–covariate interaction improved the power for detecting association. For illustration, we analyze the rheumatoid arthritis data from GAW15. Adjusting for smoking and anti‐cyclic citrullinated peptide increased the significance of the association with the DR locus. 相似文献
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Battauz M 《Biometrical journal. Biometrische Zeitschrift》2011,53(3):411-425
Likelihood analysis for regression models with measurement errors in explanatory variables typically involves integrals that do not have a closed-form solution. In this case, numerical methods such as Gaussian quadrature are generally employed. However, when the dimension of the integral is large, these methods become computationally demanding or even unfeasible. This paper proposes the use of the Laplace approximation to deal with measurement error problems when the likelihood function involves high-dimensional integrals. The cases considered are generalized linear models with multiple covariates measured with error and generalized linear mixed models with measurement error in the covariates. The asymptotic order of the approximation and the asymptotic properties of the Laplace-based estimator for these models are derived. The method is illustrated using simulations and real-data analysis. 相似文献
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Deviance residuals and normal scores plots 总被引：1，自引：0，他引：1
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Crop seeds are important sources of protein, oil, and carbohydrates for food, animal feeds, and industrial products. Recently, much attention has been paid to quality and functional properties of crop seeds. However, seed traits possess some distinct genetic characteristics in comparison with plant traits, which increase the difficulty of genetically improving these traits. In this study, diallel analysis for seed models with genotype by environment interaction （GE） effect was applied to estimate the variance-covariance components of seed traits. Mixed linear model approaches were used to estimate the genetic covariances between pair-wise seed and plant traits. The breeding values （BV） were divided into two categories for the seed models. The first category of BV was defined as the combination of direct additive, cytoplasmic, and maternal additive effects, which should be utilized for selecting stable cultivars over multi-environments. The three genetic effects, together with their GE interaction, were included in the second category of BV for selecting special lines to be grown in specific ecosystems. Accordingly, two types of selection indices for seed traits, i.e., general selection index and interaction selection index, were developed and constructed on the first and the second category BV, respectively. These proposed selection indices can be applied to solve the difficult task of simultaneously improving multiple seed traits in various environments. Data of crop seeds with regard to four seed traits and four yield traits based on the modified diallel crosses in Upland cotton （Gossypium hirsutum L.） were used as an example for demonstrating the proposed methodology. 相似文献
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Summary . Standard prospective logistic regression analysis of case–control data often leads to very imprecise estimates of gene-environment interactions due to small numbers of cases or controls in cells of crossing genotype and exposure. In contrast, under the assumption of gene-environment independence, modern \"retrospective\" methods, including the \"case-only\" approach, can estimate the interaction parameters much more precisely, but they can be seriously biased when the underlying assumption of gene-environment independence is violated. In this article, we propose a novel empirical Bayes-type shrinkage estimator to analyze case–control data that can relax the gene-environment independence assumption in a data-adaptive fashion. In the special case, involving a binary gene and a binary exposure, the method leads to an estimator of the interaction log odds ratio parameter in a simple closed form that corresponds to an weighted average of the standard case-only and case–control estimators. We also describe a general approach for deriving the new shrinkage estimator and its variance within the retrospective maximum-likelihood framework developed by Chatterjee and Carroll (2005, Biometrika 92, 399–418). Both simulated and real data examples suggest that the proposed estimator strikes a balance between bias and efficiency depending on the true nature of the gene-environment association and the sample size for a given study. 相似文献
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Summary . Quantitative trait loci mapping in experimental organisms is of great scientific and economic importance. There has been a rapid advancement in statistical methods for quantitative trait loci mapping. Various methods for normally distributed traits have been well established. Some of them have also been adapted for other types of traits such as binary, count, and categorical traits. In this article, we consider a unified mixture generalized linear model (GLIM) for multiple interval mapping in experimental crosses. The multiple interval mapping approach was proposed by Kao, Zeng, and Teasdale (1999, Genetics 152, 1203–1216) for normally distributed traits. However, its application to nonnormally distributed traits has been hindered largely by the lack of an efficient computation algorithm and an appropriate mapping procedure. In this article, an effective expectation–maximization algorithm for the computation of the mixture GLIM and an epistasis-effect-adjusted multiple interval mapping procedure is developed. A real data set, Radiata Pine data, is analyzed and the data structure is used in simulation studies to demonstrate the desirable features of the developed method. 相似文献
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Zhe Li ZhenZhen Xiong Lydia C. Manor Hongbao Cao Tao Li 《Saudi Journal of Biological Sciences》2018,25(5):996-1002
Recent studies have reported hundreds of genes linked to Alzheimer’s Disease (AD). However, many of these candidate genes may be not identified in different studies when analyses were replicated. Moreover, results could be controversial. Here, we proposed a computational workflow to curate and evaluate AD related genes. The method integrates large scale literature knowledge data and gene expression data that were acquired from postmortem human brain regions (AD case/control: 31/32 and 22/8). Pathway Enrichment, Sub-Network Enrichment, and Gene-Gene Interaction analysis were conducted to study the pathogenic profile of the candidate genes, with 4 metrics proposed and validated for each gene. By using our approach, a scalable AD genetic database was developed, including AD related genes, pathways, diseases and info of supporting references. The AD case/control classification supported the effectiveness of the 4 proposed metrics, which successfully identified 21 well-studied AD genes (i.g. TGFB1, CTNNB1, APP, IL1B, PSEN1, PTGS2, IL6, VEGFA, SOD1, AKT1, CDK5, TNF, GSK3B, TP53, CCL2, BDNF, NGF, IGF1, SIRT1, AGER and TLR) and highlighted one recently reported AD gene (i.g. ITGB1). The computational biology approach and the AD database developed in this study provide a valuable resource which may facilitate the understanding of the AD genetic profile. 相似文献
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BackgroundThere is evidence vitamin A plays a role in neuroblastoma. Not only is 13-cis-retinoic acid used as maintenance therapy for high-risk cases, but prenatal vitamin intake use may decrease neuroblastoma risk. We hypothesized that single nucleotide polymorphisms (SNPs) in vitamin A-related genes are may be associated with neuroblastoma risk and potentially be modified by vitamin A intake.MethodsThe Neuroblastoma Epidemiology in North America (NENA) study recruited 563 case-parent sets through the Children’s Oncology Group’s Childhood Cancer Research Network. We ascertained dietary nutrient intake through questionnaires and genotyped 463 SNPs in vitamin A-related genes from saliva DNA. Offspring and maternal log-additive risk ratios (RR) and stratum-specific RR for gene-environment interaction were estimated with a log-linear model. We avoided false positives due to multiple testing by using the false discovery rate (FDR).ResultsWhen all neuroblastoma cases were considered together, no offspring variants met the significance criteria (FDR Q-value < 0.2). One maternal SNP (rs12442054) was associated with decreased risk of neuroblastoma (RR: 0.61; 95% Confidence Interval (CI): 0.47–0.79, Q = 0.076). When the cases were categorized according to prognostic risk category and age at onset, nine offspring SNPs were significantly associated with intermediate-risk neuroblastoma. Maternal rs6776706 was associated with (RR: 0.49; 95% CI: 0.33–0.72, Q = 0.161) high-risk neuroblastoma and maternal rs11103603 (RR: 0.60; 95% CI: 0.45–0.79, Q = 0.127) was associated with neuroblastoma aged <1 year. For gene-environment interaction, maternal rs729147 was associated with decreased risk of neuroblastoma among mothers with vitamin A consumption above the recommendation.ConclusionsAlthough there is biologic plausibility for the role of vitamin A in neuroblastoma, we found weak evidence of a relationship between vitamin A related genes and neuroblastoma. 相似文献
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BackgroundAssociation between fasting serum glucose (FSG) and certain mineral elements has been extensively reported. Investigation regarding multi-element exposure among subjects with different exposure level is warranted to confirm the association and further explore dose-dependent relationship.MethodsA total of 3488 participants were recruited from four counties of Hunan province, South China. Basic characteristics were collected by face to face interview and 23 elements in plasma were determined by inductively coupled plasma mass spectrometry. We applied fully adjusted generalized linear regression model and multivariable restricted cubic spline function to test the association and dose-response relationship of FSG with 23 elements.ResultsThe results indicated that FSG was positively associated with plasma78selenium level [regression coefficient (β), 0.001; 95 % confidence interval (CI), 0.001, 0.001] in a dose-dependent manner, robust to the adjustment for suspected covariates and stratification by age, gender, BMI and smoking status. A negative association was found between FSG and plasma 208lead (β, -0.004; 95 % CI, -0.016, -0.002), 52chromium (β, -0.002; 95 % CI, -0.004, -0.001) and 47titanium (β, -0.001; 95 % CI, -0.002, -0.001).Conclusion78selenium was positively while 208lead, 52chromium and 47titanium were negatively associated with FSG in the present study. However, prospective studies are needed to confirm the results. 相似文献
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Often, the functional form of covariate effects in an additive model varies across groups defined by levels of a categorical variable. This structure represents a factor-by-curve interaction. This article presents penalized spline models that incorporate factor-by-curve interactions into additive models. A mixed model formulation for penalized splines allows for straightforward model fitting and smoothing parameter selection. We illustrate the proposed model by applying it to pollen ragweed data in which seasonal trends vary by year. 相似文献
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Trait-based analyses for the detection of linkage between marker loci and quantitative trait loci in crosses between inbred lines 总被引：1，自引：0，他引：1
R. J. Lebowitz M. Soller J. S. Beckmann 《TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik》1987,73(4):556-562
Summary Methods are presented for determining linkage between a marker locus and a nearby locus affecting a quantitative trait (quantitative trait locus=QTL), based on changes in the marker allele frequencies in selection lines derived from the F-2 of a cross between inbred lines, or in the high and low phenotypic classes of an F-2 or BC population. The power of such trait-based (TB) analyses was evaluated and compared with that of methods for determining linkage based on the mean quantitative trait value of marker genotypes in F-2 or BC populations [marker-based (MB) analyses]. TB analyses can be utilized for marker-QTL linkage determination in situations where the MB analysis is not applicable, including analysis of polygenic resistance traits where only a part of the population survives exposure to the Stressor and analysis of marker-allele frequency changes in selection lines. TB analyses may be a useful alternative to MB analyses when interest is centered on a single quantitative trait only and costs of scoring for markers are high compared with costs of raising and obtaining quantitative trait information on F-2 or BC individuals. In this case, a TB analysis will enable equivalent power to be obtained with fewer individuals scored for the marker, but more individuals scored for the quantitative trait. MB analyses remain the method of choice when more than one quantitative trait is to be analyzed in a given population.Contribution from the ARO, Bet Dagan, Israel. No. 1698-E, 1986 series 相似文献
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Jari Oksanen 《植被学杂志》1997,8(1):147-152
Abstract. The beta-function (β-function) has been suggested for testing the significance of the skewness of species responses along a gradient. However, the location of the optimum and skewness are correlated so that these parameters cannot be estimated independently. The only way for an independent estimation is to let the endpoints of the response curve vary. In that case they would no longer define the range of species occurrence. However, non-linear estimation of endpoints often leads to overwhelming problems in model fitting. Therefore, the beta-function is not suitable to test the shape of species response curves. Hierarchic models proposed by Huisman et al. (1993) seem to be superior to generalized additive models or third-degree polynomials and seem to be the best alternative to study the skewness of responses. 相似文献
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摘要目的：类风湿性关节炎是一种全身的慢性炎症型疾病,可能影响许多组织和器官,主要发作于灵活的关节。全世界人群中大约有1%会患有类风湿性关节炎。目前已经证实了一些基因与类风湿性关节炎相关,但是这些基因只能解释一小部分遗传风险,因此我们需要新的策略和方法来解决这个问题。方法：表达数量性状位点（eQTL）是指能够调控基因或蛋白质表达的基因组位点,本文采用了eQTL数据构建基因- 基因网络并挖掘候选类风湿性关节炎风险基因。结果：首先,利用eQTL 数据,基于基因之间的共调控系数,建立基因- 基因网络,我们建立了5 个不同阈值(0、0.2、0.4、0.6和0.8)的基因-基因网络;然后,在OMIM 和GAD数据库中搜索已经证实的与类风湿性关节炎相关的186 个基因;最后我们将已证实与类风湿性关节炎相关的186 个基因分别投入到这5 个网络中,利用基因与基因之间的相关性来挖掘到一些可能与类风湿性关节炎相关的候选风险基因。结论：本文基于eQTL构建了基因-基因网络,结合已知类风湿性关节炎风险基因,挖掘未知风险基因,得到了较好的结果,证明了本方法的有效性,且对于类风湿性关节炎的发病机制研究具有重要价值。除了类风湿性关节炎外,本方法还可推广到其它复杂疾病中,因此本方法对人类复杂疾病的研究具有很强的学术理论价值和应用价值。 相似文献
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Substantial research and theory over a number of years have linked father absence to earlier age at menarche (AAM). More recent work has centered on explaining the relative genetic and environmental contributions to this correlation. The purpose of the current study was to evaluate the combined effects of father absence and variation in the LIN28B gene on AAM. A sample of 300 women (age 18–25) successfully genotyped for two LIN28B single nucleotide polymorphisms (SNPs; rs364663 and rs314273) were used to test gene-environment interaction models. Results for both SNPs were consistent with the hypothesis that father absence would attenuate later AAM associated with LIN28B. Genetic index analysis of combined LIN28B SNPs showed that girls with at least one copy of the T/T genotype had later AAM if they were father present. Study strengths and the implications of GxE research for life history models are discussed. 相似文献
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Xu Han Lixuan Gui Bing Liu Jing Wang Yaru Li Xiayun Dai Jun Li Binyao Yang Gaokun Qiu Jing Feng Xiaomin Zhang Tangchun Wu Meian He 《BMC genetics》2015,16(1)