54 citations · 208 across the 29 of their papers we have counts for
9 papers · 1 filter
A set of efficient methods to generate high-dimensional binary data with specified correlation structures
Wei Jiang, Shuang Song, Lin Hou +1
High dimensional correlated binary data arise in many areas, such as observed genetic variations in biomedical research. Data simulation can help researchers evaluate efficiency an…
Prediction analysis for microbiome sequencing data
Tao Wang, Can Yang, Hongyu Zhao
One primary goal of human microbiome studies is to predict host traits based on human microbiota. However, microbial community sequencing data present significant challenges to the…
Joint Models for Time-to-Event Data and Longitudinal Biomarkers of High Dimension
Molei Liu, Jiehuan Sun, Jose D. Herazo-Maya +2
Joint models for longitudinal biomarkers and time-to-event data are widely used in longitudinal studies. Many joint modeling approaches have been proposed to deal with different ty…
A Bayesian Semiparametric Factor Analysis Model for Subtype Identification
Jiehuan Sun, Joshua L. Warren, Hongyu Zhao
Disease subtype identification (clustering) is an important problem in biomedical research. Gene expression profiles are commonly utilized to infer disease subtypes, which often le…
Distance-Correlation based Gene Set Analysis in Longitudinal Studies
Jiehuan Sun, Jose D. Herazo-Maya, Xiu Huang +2
Longitudinal gene expression profiles of patients are collected in some clinical studies to monitor disease progression and understand disease etiology. The identification of gene…
A Dirichlet Process Mixture Model for Clustering Longitudinal Gene Expression Data
Jiehuan Sun, Jose D. Herazo-Maya, Naftali Kaminski +2
Subgroup identification (clustering) is an important problem in biomedical research. Gene expression profiles are commonly utilized to define subgroups. Longitudinal gene expressio…
GPA: A statistical approach to prioritizing GWAS results by integrating pleiotropy information and annotation data
Dongjun Chung, Can Yang, Cong Li +2
Genome-wide association studies (GWAS) suggests that a complex disease is typically affected by many genetic variants with small or moderate effects. Identification of these risk v…
Asymptotically Normal and Efficient Estimation of Covariate-Adjusted Gaussian Graphical Model
Mengjie Chen, Zhao Ren, Hongyu Zhao +1
A tuning-free procedure is proposed to estimate the covariate-adjusted Gaussian graphical model. For each finite subgraph, this estimator is asymptotically normal and efficient. As…
A Penalized Multi-trait Mixed Model for Association Mapping in Pedigree-based GWAS
Jin Liu, Can Yang, Xingjie Shi +4
In genome-wide association studies (GWAS), penalization is an important approach for identifying genetic markers associated with trait while mixed model is successful in accounting…