Jian Yang
@jyang1981
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Professor of Statistical Genetics, Westlake University
Hangzhou, Zhejiang, China
Joined January 2011
This study shows that lowland individuals living at high altitude exhibit accelerated DNA methylation age.
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gsMap paper online. Source code: Results visualisation website:
Nature research paper: Spatially resolved mapping of cells associated with human complex traits.
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RT @WrayNaomi: *Ten* 3-year post-doc/assistant prof jobs advertised for our Pioneer Centre for SMARTbiomed - address key questions in comm….
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SMR Portal: an online analysis, visualisation, and database platform for mapping complex disease genes. Powered by Westlake FutureGene. Try it out at: See a tutorial video at:
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From genetic associations to genes: methods, applications, and challenges: Trends in Genetics A review paper from a team effort led by Ting @TingQi2.
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“The extent to which MR methods are robust to directional pleiotropy can vary depending on the specific method used. This underscores the importance of comparing different MR methods in real data analysis before making definitive inferences about causality.” Well done, Angli!.
I'm so excited the last piece of my PhD work is finally out! In this study, we unravelled the complex causal relationship between substance use behaviours and common diseases by Mendelian Randomization, genetic correlation, and dosage-dependent analyses.
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RT @dr_appie: Naomi Wray (@WrayNaomi) works at the interface of genetics, statistics and psychiatric disorders. With early training in quan….
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New GCTA version compatible with Apple M1 and M2 chips (ARM architecture).
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RT @Andrew_Akbashev: This is how I advise my #PhD students to write research manuscripts (in case someone finds it helpful). General point….
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The advantage of rare variant analysis? It often leads us straight to the causal variants/genes. As WES/WGS data continues to grow, we anticipate a wave of new therapeutic target genes to be discovered for #obesity and other complex diseases.
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A new method to find the most relevant cells for a complex trait by integrating GWAS summary statistics with scRNA-seq data. Great work led by my collaborators, Dr. Yunlong Ma and Prof. Jianzhong Su.
Polygenic regression uncovers trait-relevant cellular contexts through pathway activation transformation of single-cell RNA sequencing data
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This study elucidates the mechanism behind why individuals born to older mothers tend to be larger. Excellent collaborative work led by my colleague Dr. Lianfeng Wu! .
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RT @doctorveera: Buckle up! We're in for a wild ride today. A new @NatMetabolism paper by scientists from China adds a surprising twist to….
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We show the feasibility of mapping cell-state-dependent (csd) eQTLs and the enrichment of these csd-eQTLs in cell-state-specific chromatin regions, as identified with scATAC-seq data.
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Estimating the abundances of cells at different states in bulk RNA-seq data. Excellent work from Liyang Song, a second-year PhD student at Westlake University. @liyang_song @Westlake_Uni.
. @jyang1981, @liyang_song and colleagues present MeDuSA, a mixed-model approach for deconvoluting cell-state abundances from bulk RNA-seq data using scRNA-seq as a reference.
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The OPERA paper is published in Cell Genomics! The OPERA method integrates GWAS and xQTL summary statistics across multiple omics levels. Findings reveal that 50% of GWAS signals are shared with at least one xQTL signal. @YangWu20.@JianZengR.@Westlake_Uni.
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