Author

Gang Feng

Shiga University of Medical SciencePrimary ORCID profile (0000-0003-4054-6828 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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Gang FengiD1 paper · University of Chinese Academy of Sciences

Biology Disciplines

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Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Assay:GWAS summary statistics· 1 Research Focus:polygenic risk· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Agung A. A. A. Kusumawardhani· 1 shared Akira SawaiD· 1 shared Akitoyo HishimotoiD· 1 shared Alice Zheng· 1 shared Alicia R. MartiniD· 1 shared Byung Dae LeeiD· 1 shared Chia‐Yen CheniD· 1 shared Dieter B. WildenaueriD· 1 shared

Activity by Year

2022-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperGenetic & Genomic Medicine

Agung A. A. A. Kusumawardhani

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1 paper

Recent·Most cited

Improving Polygenic Prediction in Ancestrally Diverse Populations

Yunfeng Ruan, Kuang Lin, Yen‐Chen Anne Feng, Chia‐Yen Chen, Max Lam, Zhenglin Guo, Stanley Global Asia Initiatives, Yong Min Ahn, Kazufumi Akiyama, Makoto Arai, Ji Hyun Baek, Wei J. Chen, Young‐Chul Chung, Gang Feng, Kumiko Fujii, , Tian Ge

This paper introduces PRS-CSx, a method that improves polygenic prediction across ancestrally diverse populations by integrating GWAS summary statistics and sharing genetic effects.

Nature Genetics · May 1, 2022Peer-reviewedGenetic & Genomic Medicine