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Biomedical Informatics Insights|November 1, 2019
LEP: A Statistical Method Integrating Individual-Level and Summary-Level Data of the Same Trait From Different PopulationsMingwei Dai, Jin Liu, Can Yang
Bioinformatics (Oxford, England)|April 3, 2018
LSMM: a statistical approach to integrating functional annotations with genome-wide association studiesJingsi Ming, Mingwei Dai, Mingxuan Cai, et al.
BMC Genomics|June 30, 2018
LPG: A four-group probabilistic approach to leveraging pleiotropy in genome-wide association studiesYi Yang, Mingwei Dai, Jian Huang, et al.
Bioinformatics (Oxford, England)|May 13, 2017
IGESS: a statistical approach to integrating individual-level genotype data and summary statistics in genome-wide association studiesMingwei Dai, Jingsi Ming, Mingxuan Cai, et al.
Bioinformatics (Oxford, England)|October 12, 2018
Joint analysis of individual-level and summary-level GWAS data by leveraging pleiotropyMingwei Dai, Xiang Wan, Hao Peng, et al.
Methods in Molecular Biology (Clifton, N.J.)|March 18, 2021
Using Collaborative Mixed Models to Account for Imputation Uncertainty in Transcriptome-Wide Association StudiesXingjie Shi, Can Yang, Jin Liu
Bioinformatics (Oxford, England)|May 7, 2016
EPS: an empirical Bayes approach to integrating pleiotropy and tissue-specific information for prioritizing risk genesJin Liu, Xiang Wan, Shuangge Ma, et al.
Plos Genetics|January 4, 2021
Accurate genetic and environmental covariance estimation with composite likelihood in genome-wide association studiesBoran Gao, Can Yang, Jin Liu, et al.
NAR Genomics and Bioinformatics|March 3, 2020
IGREX for quantifying the impact of genetically regulated expression on phenotypesMingxuan Cai, Lin S Chen, Jin Liu, et al.
Bioinformatics and Biology Insights|October 31, 2019
CoMM: A Collaborative Mixed Model That Integrates GWAS and eQTL Data Sets to Investigate the Genetic Architecture of Complex TraitsKar-Fu Yeung, Yi Yang, Can Yang, et al.
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