Genetically informed spatial mapping of cells for complex traits. Integrates GWAS summary statistics with spatial transcriptomics to map trait-associated cells in tissue.
About
- Hi, I am Liyang. I received my Ph.D. in statistical genetics from Westlake University (joint program with Zhejiang University) in 2026, advised by Prof. Jian Yang. I am now a postdoctoral researcher in the Yang Lab at Westlake University.
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My research sits at the intersection of statistical genetics and
artificial intelligence. I develop statistical models and deep-learning
methods that integrate single-cell and spatial omics data with human genetics, to identify
the cell states and tissue locations associated with complex traits and diseases. Topics include:
- Integrating GWAS with spatial and single-cell transcriptomics
- Graph neural networks and deep learning for omics data
- Mixed models and cellular deconvolution
- Scalable, open-source software for large-scale genomic data
- I developed gsMap (Nature, 2025), which maps trait-associated cells in tissue by combining GWAS summary statistics with spatial transcriptomics, and MeDuSA (Nature Computational Science, 2023), a mixed-model method for estimating cell-state abundance from bulk RNA-seq.
- I am always open to discussions and collaborations — feel free to reach out via email. :)
News
- Honored to receive the Ray Wu Prize at the 15th Ray Wu Symposium (USTC, Hefei), where I also gave a talk on gsMap.
- Received my Ph.D. from Westlake University. 🎓
- Presented gsMap (poster) at the ASHG 2025 Annual Meeting, Boston.
- Honored to receive the President's Award of Westlake University, the Tencent Qingyun Award and the Su Wu Scholarship.
- My perspective, Mapping trait-associated cells with spatial transcriptomics, is out in Nature Reviews Genetics.
- gsMap is published in Nature (code, docs). Later selected as a research highlight by Nature Methods and Nature Reviews Genetics.
- Our review From genetic associations to genes is published in Trends in Genetics.
- MeDuSA is published in Nature Computational Science (code).
- Received the Dean's Award of Westlake University and the National Scholarship.
Selected Publications
(# equal contribution, * corresponding author) ·
Full list on Google Scholar
Spatial genetics
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★ Research highlight in Nature Methods and Nature Reviews Genetics
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2025Nat Rev Genet Mapping trait-associated cells with spatial transcriptomics
Cellular deconvolution
Reviews
Earlier work
Software
Fine-resolution cellular deconvolution. Uses an scRNA-seq reference and a linear mixed model to estimate cell-state abundance along a trajectory from bulk RNA-seq.
Extends gsMap to 3D spatial transcriptomics atlases: mapping the cellular etiology of complex traits in 3D tissue architecture. Manuscript under revision.
Education
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Ph.D., Statistical Genetics — Westlake University (joint program with Zhejiang University), Hangzhou
Advisor: Prof. Jian Yang
Honors & Awards
- Ray Wu Prize, Ray Wu Memorial Fund (2026)
- President's Award, Westlake University (2025)
- Tencent Qingyun Award (2025)
- Su Wu Scholarship, Westlake University (2025)
- National Scholarship, Westlake University – Zhejiang University (2023)
- Dean's Award, Westlake University (2023)
- Outstanding Student, Zhejiang University (2023, 2025)
- Excellent Student, Zhejiang University (2023, 2024, 2025)
- Learning and Innovation Award, Westlake University (2024, 2025)
- Knowledge Exploration Award, Westlake University (2023)
Talks & Posters
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Award talk — Dissecting cellular heterogeneity and spatial context in human complex traits. The 15th Ray Wu Symposium, University of Science and Technology of China, Hefei, China.
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Invited talk — Dissecting the cells and spatial contexts underlying human complex diseases. Jiao–Chuang Academic Forum, Shanghai Jiao Tong University, Shanghai, China.
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Poster — gsMap: spatially resolved mapping of cells associated with human complex traits. ASHG 2025 Annual Meeting, Boston, USA.
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Invited talk — Spatially resolved mapping of cells associated with human complex traits. Human Genetics Exchange Network seminar, online.
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Talk — Spatially resolved mapping of cells associated with human complex traits. The 9th National Doctoral Forum on Life Sciences, Life Sciences Institute, Zhejiang University, Hangzhou, China.
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Invited talk — Mixed model-based deconvolution of cell-state abundances. 2024 Hangzhou International Conference on Frontiers of Data Science, Hangzhou, China.
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Talk — Mixed model-based deconvolution of cell-state abundance. Topic-contributed session “Computational and statistical methods for modern genetic studies”, Joint Statistical Meetings (JSM 2023), Toronto, Canada.
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Talk — MeDuSA: mixed model-based deconvolution of cell-state abundances. Young Scholars Forum, the 1st Yangtze River Delta Bioinformatics Conference, Huzhou, China.
Teaching
- Teaching assistant, BIO3002 Biostatistics (undergraduate), Westlake University