3 papers
stat.ME2026
Scalable Ultra-High-Dimensional Quantile Regression with Genomic Applications
Hanqing Wu, Jonas Wallin, Iuliana Ionita-Laza
Modern datasets arising from social media, genomics, and biomedical informatics are often heterogeneous and (ultra) high-dimensional, creating substantial challenges for convention…
stat.ME2022
A unified quantile framework for nonlinear heterogeneous transcriptome-wide associations
Tianying Wang, Iuliana Ionita-Laza, Ying Wei
Transcriptome-wide association studies (TWAS) are powerful tools for identifying gene-level associations by integrating genome-wide association studies and gene expression data. Ho…
stat.ME2019
Integrated Quantile RAnk Test (iQRAT) for gene-level associations
Tianying Wang, Iuliana Ionita-Laza, Ying Wei
Gene-based testing is a commonly employed strategy in many genetic association studies. Gene-trait associations can be complex due to underlying population heterogeneity, gene-envi…