In this study, led by Xiaohe (Lucy) Tian, we showed that ancestry-aware integration of tissue-specific genomic annotations enhances the transferability of polygenic scores (PGS).
We developed GenoBoost, a polygenic score modeling approach, incorporating both additive and non-additive genetic dominance effects.
We developed a polygenic score training approach that allows direct inclusion of admixed individuals without the need for local ancestry inference and showed ancestry-diverse …
In this study led by Junyang Qian, we present a method to fit sparse multi-variate and multi-response regression model.
We performed a systematic assessment of the predictive performance of PRS models across >1,500 traits in UK Biobank and report 813 PRS models with significant predictive …
In this paper led by Ruilin Li, we describe memory-efficient implementation of snpnet (sparse-snpnet and snpnet-v2).
[invited review written in Japanese] 日本語総説の執筆の機会をいただき、ゲノムワイド相関解析（GWAS）、ポリジェニック・リスク・スコア（polygenic risk score）、高次元データセットでの正則化つきの回帰モデル（penalized regression、Lasso 回帰など）に関する人類統計遺伝学の解析手法 …
In this paper led by Ruilin Li, we describe a new method to fit a sparse Cox Model for multiple time-to-event phenotypes from a large-scale (> 1 million features) genetic dataset.
In this project led by Junyang Qian, we developed BASIL, a novel algorithm to fit large-scale L1 penalized (Lasso) regression model using an iterative procedure, and implemented R …
We propose extending the BASIL/snpnet algorithm to fit the L1 penalized Cox proportional hazards model using a large-scale dataset from a genotyped cohort.