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Jian Yang, Ph.D.
Statistical Genetics Laboratory
Jian Yang, Ph.D.
Statistical Genetics Laboratory
"Westlake University, the place to pursue your scientific dreams."
Jian Yang is a Professor of Statistical Genetics at the School of Life Sciences, Westlake University, China. He received his PhD in 2008 from Zhejiang University, China, before undertaking postdoctoral research at the QIMR Berghofer Medical Research Institute in Australia (2008-2011). He moved to The University of Queensland (UQ), Australia, as a Research Fellow in 2012 and was reappointed as a Senior Research Fellow and Group Leader in January 2014. He was promoted to be an Associate Professor in December 2014, and then a Professor in 2017 at UQ. He joined Westlake University in 2020. His primary research interests are focused on understanding the genomic variations among individuals within and between populations and the links of genomic variations with health outcomes.
He was the 2012 recipient of the Centenary Institute Lawrence Creative Prize, in recognition of his contribution to solving the ‘missing heritability’ paradox. He was awarded the Australian Academy of Science Ruth Stephens Gani Medal for distinguished research in human genetics (2015) and the Prime Minister’s Prize for Sciences - Frank Fenner Prize for Life Scientist of the Year (2017). He was named in the Clarivate Highly Cited Researchers from 2018 to 2021. He has published a career total of >200 papers, which have received >37,000 citations (Web of Science, Nov 2021).
1. Jiang L, Zheng Z, Fang H, Yang J (2021) A generalized linear mixed model association tool for biobank-scale data. Nature Genetics, 53:1616-1621.
2. Wu Y, Qi T, Wang H, Zhang F, Zheng Z, Phillips-Cremins JE, Deary IJ, McRae AF, Wray NR, Zeng J, Yang J (2020) Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data. Nature Communications, 11:2061.
3. Jiang L, Zheng Z, Qi T, Kemper KE, Wray NR, Visscher PM, Yang J (2019) A resource-efficient tool for mixed model association analysis of large-scale data. Nature Genetics, 51:1749-1755.
4. Wang H, Zhang F, Zeng J, Wu Y, Kemper KE, Xue A, Zhang M, Powell JE, Goddard ME, Wray NR, Visscher PM, McRae AF, Yang J (2019) Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank. Science Advances, Vol. 5, no. 8, eaaw3538.
5. Zhang F, Chen W, Zhu Z, Zhang Q, Nabais MF, Qi T, Deary IJ, Wray NR, Visscher PM, McRae AF, Yang J (2019) OSCA: a tool for omic-data-based complex trait analysis. Genome Biology, 20:107.
6. Zeng J, de Vlaming R, Wu Y, Robinson M, Lloyd-Jones LR, Yengo L, Yap CX, Xue A, Sidorenko J, McRae AF, Powell JE, Montgomery GW, Metspalu A, Esko T, Gibson G, Wray NR, Visscher PM, Yang J (2018) Signatures of negative selection in the genetic architecture of human complex traits. Nature Genetics, 50: 746-753.
7. Xue A, Wu Y, Zhu Z, Zhang F, Kemper KE, Zheng Z, Yengo L, Lloyd-Jones LR, Sidorenko J, Wu Y, eQTLGen Consortium, McRae AF, Visscher PM, Zeng J, Yang J (2018) Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes. Nature Communications, 9:2941.
8. Qi T, Wu Y, Zeng J, Zhang F, Xue A, Jiang L, Zhu Z, Kemper K, Yengo L, Zheng Z, eQTLGen Consortium, Marioni RE, Montgomery GW, Deary IJ, Wray NR, Visscher PM, McRae AF, Yang J (2018) Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood. Nature Communications, 9: 2282.
9. Wu Y, Zeng J, Zhang F, Zhu F, Qi T, Zheng Z, Lloyd-Jones LR, Marioni RE, Martin NG, Montgomery GW, Deary IJ, Wray NR, Visscher PM, McRae AF, Yang J (2018) Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits. Nature Communications, 9: 918.
10. Zhu Z, Zheng Z, Zhang F, Wu Y, Trzaskowski M, Maier R, Robinson MR, McGrath JJ, Visscher PM, Wray NR, Yang J (2018) Causal associations between risk factors and common diseases inferred from GWAS summary data. Nature Communications, 9: 224.
11. Wu Y, Zheng Z, Visscher PM, Yang J (2017) Quantifying the mapping precision of genome-wide association studies using whole-genome sequencing data. Genome Biology, 18: 86.
12. Zhu Z, Zhang F, Hu H, Bakshi A, Robinson MR, Powell JE, Montgomery GW, Goddard ME, Wray NR, Visscher PM, Yang J (2016) Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nature Genetics, 48: 481-487.
13. Zhu, ZH, Bakshi A, Vinkhuyzen AAE, Hemani G, Lee SH, Nolte IM, van Vliet-Ostaptchouk JV, Snieder H, The LifeLines Cohort Study, Esko T, Milani L, Mägi R, Metspalu A, Hill WG, Weir BS, Goddard ME, Visscher PM, Yang J (2015) Dominance genetic variation contributes little to the missing heritability for human complex traits. Am J Hum Genet, 96: 377-385.
14. Yang J, Bakshi A, Zhu Z, Hemani G, Vinkhuyzen AAE, …, Keller MC, Wray NR, Goddard ME, Visscher PM (2015) Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index. Nature Genetics, 47: 1114-1120.
15. Yang J, Zaitlen NA, Goddard ME, Visscher PM, Price AL (2014) Advantages and pitfalls in the application of mixed model association methods. Nature Genetics, 46: 100–106.
16. Yang J, Loos RJF, Powell JE, Medland SE, et al. (2012) FTO genotype is associated with phenotypic variability of body mass index. Nature, 490: 267-272.
17. Yang J, Ferreira T, Morris AP, Medland SE, GIANT Consortium, DIAGRAM Consortium, Madden PAF, Heath AC, Martin NG, Montgomery GW, Weedon MN, Loos RJ, Frayling TM, McCarthy MI, Hirschhorn JN, Goddard ME, Visscher PM (2012) Conditional and joint multiple SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nature Genetics, 44: 369-375.
18. Yang J, Manolio TA, Pasquale LR, Boerwinkle E, Caporaso N, Cunningham JM, de Andrade M, Feenstra B, Feingold E, Hayes MG, Hill WG, Landi MT, Alonso A, Lettre G, Lin P, Ling H, Lowe W, Mathias RA, Melbye M, Pugh E, Cornelis MC, Weir BS, Goddard ME, Visscher PM (2011) Genome partitioning of genetic variation for complex traits using common SNPs. Nature Genetics, 43: 519-525.
19. Yang J, Lee SH, Goddard ME, Visscher PM (2011) GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet, 88: 76-82.
20. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, Madden PA, Heath AC, Martin NG, Montgomery GW, Goddard ME, Visscher PM (2010) Common SNPs explain a large proportion of the heritability for human height. Nature Genetics, 42: 565-569.
Lab website: https://yanglab.westlake.edu.cn