most citedCross-trait prediction accuracy of high-dimensional ridge-type estimators in genome-wide association studies

6 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

stat.AP20222 cited

Statistical learning methods for neuroimaging data analysis with applications

Hongtu Zhu, Tengfei Li, Bingxin Zhao

The aim of this paper is to provide a comprehensive review of statistical challenges in neuroimaging data analysis from neuroimaging techniques to large-scale neuroimaging studies…

stat.ME2022

Estimating trans-ancestry genetic correlation with unbalanced data resources

Bingxin Zhao, Xiaochen Yang, Hongtu Zhu

The aim of this paper is to propose a novel estimation method of using genetic-predicted observations to estimate trans-ancestry genetic correlations, which describes how genetic a…

stat.ME20221 cited

On block-wise and reference panel-based estimators for genetic data prediction in high dimensions

Bingxin Zhao, Shurong Zheng, Hongtu Zhu

Genetic prediction of complex traits and diseases has attracted enormous attention in precision medicine, mainly because it has the potential to translate discoveries from genome-w…

stat.ME20196 cited

Cross-trait prediction accuracy of high-dimensional ridge-type estimators in genome-wide association studies

Bingxin Zhao, Hongtu Zhu

Marginal association summary statistics have attracted great attention in statistical genetics, mainly because the primary results of most genome-wide association studies (GWAS) ar…

stat.ME20194 cited

On genetic correlation estimation with summary statistics from genome-wide association studies

Bingxin Zhao, Hongtu Zhu

Genome-wide association studies (GWAS) have been widely used to examine the association between single nucleotide polymorphisms (SNPs) and complex traits, where both the sample siz…