On the use of min-max combination of biomarkers to maximize the partial area under the ROC curve [0.03%]
关于使用最小化最大化生物标志物组合以最大限度地提高ROC曲线部分区域下的面积的使用
Hua Ma,Susan Halabi,Aiyi Liu
Hua Ma
Background: Evaluation of diagnostic assays and predictive performance of biomarkers based on the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) are vital in diagnostic and targeted m...
A Bayesian Adaptive Design in Cancer Phase I Trials using Dose Combinations in the Presence of a Baseline Covariate [0.03%]
一种基于贝叶斯自适应设计的癌症一期试验中，在存在基线协变量的情况下使用剂量组合的方法
Márcio Augusto Diniz,Sungjin Kim,Mourad Tighiouart
Márcio Augusto Diniz
A Bayesian adaptive design for dose finding of a combination of two drugs in cancer phase I clinical trials that takes into account patients heterogeneity thought to be related to treatment susceptibility is described. The estimation of the...
Genotype-Based Bayesian Analysis of Gene-Environment Interactions with Multiple Genetic Markers and Misclassification in Environmental Factors [0.03%]
基于基因分型的贝叶斯分析：多个遗传标志物及环境因素错分条件下基因与环境的互作分析
Iryna Lobach,Ruzong Fan
Iryna Lobach
A key component to understanding etiology of complex diseases, such as cancer, diabetes, alcohol dependence, is to investigate gene-environment interactions. This work is motivated by the following two concerns in the analysis of gene-envir...
Clustering-Based Method for Developing a Genomic Copy Number Alteration Signature for Predicting the Metastatic Potential of Prostate Cancer [0.03%]
基于聚类的基因组拷贝数改变标志物开发方法用于预测前列腺癌转移潜能
Alexander Pearlman,Christopher Campbell,Eric Brooks et al.
Alexander Pearlman et al.
The transition of cancer from a localized tumor to a distant metastasis is not well understood for prostate and many other cancers, partly, because of the scarcity of tumor samples, especially metastases, from cancer patients with long-term...
Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies [0.03%]
遗传关联研究中分析多变量表型的方法
Qiong Yang,Yuanjia Wang
Qiong Yang
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Multivariate phenotypes a...
Terrance Savitsky,Marina Vannucci
Terrance Savitsky
We expand a framework for Bayesian variable selection for Gaussian process (GP) models by employing spiked Dirichlet process (DP) prior constructions over set partitions containing covariates. Our approach results in a nonparametric treatme...
Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's Disease [0.03%]
基于患者及其家族成员数据预测突变引起的疾病发病状况并将其应用于亨廷顿舞蹈病的研究
Tianle Chen,Yuanjia Wang,Yanyuan Ma et al.
Tianle Chen et al.
Huntington's disease (HD) is a progressive neurodegenerative disorder caused by an expansion of CAG repeats in the IT15 gene. The age-at-onset (AAO) of HD is inversely related to the CAG repeat length and the minimum length thought to cause...
A Multinomial Ordinal Probit Model with Singular Value Decomposition Method for a Multinomial Trait [0.03%]
基于奇异值分解的多项式序值概率模型及其在多项性状中的应用研究
Soonil Kwon,Mark O Goodarzi,Kent D Taylor et al.
Soonil Kwon et al.
We developed a multinomial ordinal probit model with singular value decomposition for testing a large number of single nucleotide polymorphisms SNPs simultaneously for association with multidisease status when sample size is much smaller th...
A Semiparametric Marginalized Model for Longitudinal Data with Informative Dropout [0.03%]
具有信息缺失的纵向数据的半参数边缘模型
Mengling Liu,Wenbin Lu
Mengling Liu
We propose a marginalized joint-modeling approach for marginal inference on the association between longitudinal responses and covariates when longitudinal measurements are subject to informative dropouts. The proposed model is motivated by...