Author
Ontario Institute for Cancer ResearchORCID 0000-0002-8956-5299Unclaimed ORCID profile · follow to get notified of new preprints
6 papers
Recent·Most cited
Qile Dai, Geyu Zhou, Hongyu Zhao…·Jingjing Yang
OTTERS is a TWAS framework that uses summary-level eQTL reference data to estimate eQTL weights and perform omnibus TWAS, showing improved power and applicability.
Urmo Võsa, Annique Claringbould, Harm-Jan Westra…·Bruce M. Psaty
The paper uses blood eQTL meta-analysis to explore the polygenic architecture of complex traits, finding that trans-eQTLs are more informative for identifying causal genes than cis-eQTLs.
Johanne Tremblay, Mounsif Haloui, Redha Attaoua…·Pavel Hamet
This paper develops a polygenic risk score model to predict diabetic complications and their response to therapy using genome-wide association study data.
Eleonora Porcu, Sina Rüeger, Kaido Lepik…·René Luijk
This paper introduces TWMR, a Mendelian Randomization method that identifies gene-trait associations by integrating GWAS and eQTL data, revealing 3,913 novel associations across 43 human phenotypes.
Angli Xue, Yang Wu, Zhihong Zhu…·Jian Yang
This study identifies 139 common and 4 rare genetic variants associated with type 2 diabetes through GWAS and integrates gene expression and epigenomic data to highlight potential functional genes and regulatory mechanisms.
Ting Qi, Yang Wu, Jian Zeng…·Jian Yang
The paper identifies gene targets for brain-related traits using transcriptomic and methylomic data from blood, finding strong correlations between genetic effects in brain and blood tissues.