30 citations · 30 across the 5 of their papers we have counts for
5 papers · 1 filter
Bayesian Weighted Mendelian Randomization for Causal Inference based on Summary Statistics
Jia Zhao, Jingsi Ming, Xianghong Hu +3
The results from Genome-Wide Association Studies (GWAS) on thousands of phenotypes provide an unprecedented opportunity to infer the causal effect of one phenotype (exposure) on an…
VIMCO: Variational Inference for Multiple Correlated Outcomes in Genome-wide Association Studies
Xingjie Shi, Yuling Jiao, Yi Yang +4
In Genome-Wide Association Studies (GWAS) where multiple correlated traits have been measured on participants, a joint analysis strategy, whereby the traits are analyzed jointly, c…
REMI: Regression with marginal information and its application in genome-wide association studies
Jian Huang, Yuling Jiao, Jin Liu +1
In this study, we consider the problem of variable selection and estimation in high-dimensional linear regression models when the complete data are not accessible, but only certain…
Joint Analysis of Individual-level and Summary-level GWAS Data by Leveraging Pleiotropy
Mingwei Dai, Xiang Wan, Hao Peng +5
A large number of recent genome-wide association studies (GWASs) for complex phenotypes confirm the early conjecture for polygenicity, suggesting the presence of large number of va…
BIVAS: A scalable Bayesian method for bi-level variable selection with applications
Mingxuan Cai, Mingwei Dai, Jingsi Ming +3
In this paper, we consider a Bayesian bi-level variable selection problem in high-dimensional regressions. In many practical situations, it is natural to assign group membership to…