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Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes

Published in Nature Communications, 2018

This paper conducted the largest T2D meta-analysis of GWAS and identified 139 common and 4 rare variants associated with T2D.

Recommended citation: Angli Xue*, Yang Wu*, Zhihong Zhu, Futao Zhang, Kathryn E Kemper, Zhili Zheng, …, Jian Zeng#, Jian Yang#. Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes. Nature Communications. 12, 6450 (2018). https://www.nature.com/articles/s41467-018-04951-w

Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes

Published in Nature Communications, 2021

This paper demonstrated that behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses.

Recommended citation: Angli Xue, Longda Jiang, Zhihong Zhu, Naomi R. Wray, Peter M. Visscher, Jian Zeng, Jian Yang. Genome-wide analyses of behavioral traits are subject to bias by misreports and longitudinal changes. Nature Communications. 12, 6450 (2021). https://www.nature.com/articles/s41467-020-20237-6

Pitfalls and opportunities for applying latent variables in single-cell eQTL analyses

Published in Genome Biology, 2023

This paper discussed the pitfalls and opportunities when using latent variables in the single-cell eQTL mapping analysis.

Recommended citation: Angli Xue#, Seyhan Yazar, Drew Neavin, Joseph E. Powell#. "Pitfalls and opportunities for applying latent variables in single-cell eQTL analyses". Genome Biology. 24.1 (2023): 1-11. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-023-02873-5

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