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Xiang Zhou
Researcher at University of Michigan
Publications - 172
Citations - 20187
Xiang Zhou is an academic researcher from University of Michigan. The author has contributed to research in topics: Medicine & Genome-wide association study. The author has an hindex of 33, co-authored 133 publications receiving 16025 citations. Previous affiliations of Xiang Zhou include Duke University & University of Chicago.
Papers
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Journal ArticleDOI
SRTsim: spatial pattern preserving simulations for spatially resolved transcriptomics
TL;DR: SRTsim as mentioned in this paper is an SRT-specific simulator for scalable, reproducible, and realistic SRT simulations, which not only maintains various expression characteristics of SRT data but also preserves spatial patterns.
Journal ArticleDOI
Longitudinal analysis of epigenome-wide DNA methylation reveals novel smoking-related loci in African Americans.
Jiaxuan Liu,Wei Zhao,Farah Ammous,Stephen T. Turner,Thomas H. Mosley,Xiang Zhou,Jennifer A. Smith +6 more
TL;DR: In conclusion, epigenetic signatures for cigarette smoking that may have been missed in cross-sectional analyses are identified, providing insight into the epigenetic effect of smoking and highlighting the importance of longitudinal analysis in understanding the dynamic human epigenome.
Journal ArticleDOI
Mendelian randomization under the omnigenic architecture.
TL;DR: In this paper, the omnigenic Mendelian randomization (OMR) method was proposed to identify multiple complex traits that potentially causally influence coronary artery disease (CAD) and asthma.
Posted ContentDOI
Birth weight is not causally associated with adult asthma: results from instrumental variable analyses
Ping Zeng,Xinghao Yu,Xiang Zhou +2 more
TL;DR: This Mendelian randomization study provides no evidence for the fetal origins of diseases hypothesis for adult asthma, implying that the impact of birth weight on asthma in years of children and adolescents does not persist into adult and previous findings may be biased by confounders.
Journal ArticleDOI
Efficient and effective control of confounding in eQTL mapping studies through joint differential expression and Mendelian randomization analyses.
TL;DR: A simple and computationally scalable alternative, ECCO, to determine the optimal number of PEER factors used for eQTL mapping studies, which jointly applies differential expression analysis and Mendelian randomization (MR) analysis, leading to substantial computational savings.