4 citations · 8 across the 3 of their papers we have counts for
4 papers
High-dimensional genome-wide association study and misspecified mixed model analysis
Jiming Jiang, Cong Li, Debashis Paul +2
We study behavior of the restricted maximum likelihood (REML) estimator under a misspecified linear mixed model (LMM) that has received much attention in recent gnome-wide associat…
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…
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…
Improving genetic risk prediction by leveraging pleiotropy
Cong Li, Can Yang, Joel Gelernter +1
An important task of human genetics studies is to accurately predict disease risks in individuals based on genetic markers, which allows for identifying individuals at high disease…