29 citations · 77 across the 13 of their papers we have counts for
14 papers
A U-Statistic-based random forest approach for genetic interaction study
Ming Li, Ruo-Sin Peng, Changshuai Wei +1
Variations in complex traits are influenced by multiple genetic variants, environmental risk factors, and their interactions. Though substantial progress has been made in identifyi…
Collapsing ROC approach for risk prediction research on both common and rare variants
Changshuai Wei, Qing Lu
Risk prediction that capitalizes on emerging genetic findings holds great promise for improving public health and clinical care. However, recent risk prediction research has shown…
Functional Analysis of Variance for Association Studies
Olga A. Vsevolozhskaya, Dmitri V. Zaykin, Mark C. Greenwood +2
While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only accoun…
A multi-locus predictiveness curve and its summary assessment for genetic risk prediction
Changshuai Wei, Ming Li, Yalu Wen +2
With the advance of high-throughput genotyping and sequencing technologies, it becomes feasible to comprehensive evaluate the role of massive genetic predictors in disease predicti…
A Kernel-Based Neural Network for High-dimensional Genetic Risk Prediction Analysis
Xiaoxi Shen, Xiaoran Tong, Qing Lu
Risk prediction capitalizing on emerging human genome findings holds great promise for new prediction and prevention strategies. While the large amounts of genetic data generated f…
Asymptotic Theory of Expectile Neural Networks
Jinghang Lin, Xiaoxi Shen, Qing Lu
Neural networks are becoming an increasingly important tool in applications. However, neural networks are not widely used in statistical genetics. In this paper, we propose a new n…
Expectile Neural Networks for Genetic Data Analysis of Complex Diseases
Jinghang Lin, Xiaoran Tong, Chenxi Li +1
The genetic etiologies of common diseases are highly complex and heterogeneous. Classic statistical methods, such as linear regression, have successfully identified numerous geneti…
Asymptotic Properties of Neural Network Sieve Estimators
Xiaoxi Shen, Chang Jiang, Lyudmila Sakhanenko +1
Neural networks are one of the most popularly used methods in machine learning and artificial intelligence nowadays. Due to the universal approximation theorem (Hornik et al. (1989…
Trees Assembling Mann Whitney Approach for Detecting Genome-wide Joint Association among Low Marginal Effect loci
Changshuai Wei, Daniel J. Schaid, Qing Lu
Common complex diseases are likely influenced by the interplay of hundreds, or even thousands, of genetic variants. Converging evidence shows that genetic variants with low margina…
A Weighted U Statistic for Genetic Association Analyses of Sequencing Data
Changshuai Wei, Ming Li, Zihuai He +3
With advancements in next generation sequencing technology, a massive amount of sequencing data are generated, offering a great opportunity to comprehensively investigate the role…
GWGGI: software for genome-wide gene-gene interaction analysis
Changshuai Wei, Qing Lu
Background: While the importance of gene-gene interactions in human diseases has been well recognized, identifying them has been a great challenge, especially through association s…
A Generalized Similarity U Test for Multivariate Analysis of Sequencing Data
Changshuai Wei, Qing Lu
Sequencing-based studies are emerging as a major tool for genetic association studies of complex diseases. These studies pose great challenges to the traditional statistical method…
A weighted U statistic for association analysis considering genetic heterogeneity
Changshuai Wei, Robert C. Elston, Qing Lu
Converging evidence suggests that common complex diseases with the same or similar clinical manifestations could have different underlying genetic etiologies. While current researc…
Modeling and Testing for Joint Association Using a Genetic Random Field Model
Zihuai He, Min Zhang, Xiaowei Zhan +1
Substantial progress has been made in identifying single genetic variants predisposing to common complex diseases. Nonetheless, the genetic etiology of human diseases remains large…