Author

Yuta Matsuda

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Genetic & Genomic Medicine· 4

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Assay:GWAS summary statistics· 4 Organism:human· 4 Approach:statistical model· 4 Research Focus:benchmarking· 2 Approach:benchmark study· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1

Frequent Co-Authors

Alexander G. IoannidisiD· 4 shared Arturo López PinedaiD· 4 shared Babak MoatamediD· 4 shared Kensuke Numakura· 4 shared Manvi VernekariD· 4 shared Ming Ta Michael LeeiD· 4 shared Sonia Moreno–GrauiD· 4 shared Agustin Rojas‐MuñoziD· 3 shared

Activity by Year

2022-2024 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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4 shared papersGenetic & Genomic Medicine

Alexander G. IoannidisORCID

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4 papers

Recent·Most cited

Polygenic risk score portability for common diseases across genetically diverse populations

Sonia Moreno–Grau, Manvi Vernekar, Arturo López Pineda, Daniel Mas Montserrat, Míriam Barrabés, Consuelo D. Quinto-Cortés, Babak Moatamed, Ming Ta Michael Lee, Zhenning Yu, Kensuke Numakura, Yuta Matsuda, Jeffrey D. Wall, Alexander G. Ioannidis, Nicholas Katsanis, Tomohiro Takano, Carlos D. Bustamante

This study evaluates polygenic risk score (PRS) performance across four ancestry groups for 14 diseases, finding that ancestry-specific PRS models improve accuracy and identifying cross-trait interactions.

Human Genomics · Sep 1, 2024Peer-reviewedGenetic & Genomic Medicine

Meta-analysis fine-mapping is often miscalibrated at single-variant resolution

Masahiro Kanai, Roy Elzur, Wei Zhou, Kuan-Han Wu, Humaira Rasheed, Kristin Tsuo, Jibril B Hirbo, Ying Wang, Arjun Bhattacharya, Huiling Zhao, Shinichi Namba, Ida L. Surakka, Brooke N. Wolford, Valeria Lo Faro, Esteban A. Lopera-Maya, , Tom R. Gaunt

This paper shows that meta-analysis fine-mapping is often miscalibrated due to cohort heterogeneity and introduces a QC method to identify suspicious loci.

Cell Genomics · Nov 4, 2022Peer-reviewedGenetic & Genomic Medicine

Global Biobank Meta-analysis Initiative: powering genetic discovery across human diseases

Wei Zhou, Masahiro Kanai, Kuan-Han Wu, Humaira Rasheed, Kristin Tsuo, Jibril B Hirbo, Ying Wang, Arjun Bhattacharya, Huiling Zhao, Shinichi Namba, Ida L. Surakka, Brooke N. Wolford, Valeria Lo Faro, Esteban A. Lopera-Maya, Kristi Läll, , Jennifer E. Huffman

Meta-analysis of harmonized GWAS from up to 18 biobanks (six ancestry groups) across 14 endpoints replicated 320 known loci and identified 188 apparently novel loci.

Cell Genomics · Oct 1, 2022Peer-reviewedGenetic & Genomic Medicine✦ In-depth digest

Validating and automating learning of cardiometabolic polygenic risk scores from direct-to-consumer genetic and phenotypic data: implications for scaling precision health research.

Arturo López Pineda, Manvi Vernekar, Sonia Moreno–Grau, Agustin Rojas‐Muñoz, Babak Moatamed, Ming Ta Michael Lee, Marco A. Nava-Aguilar, Gilberto Gonzalez-Arroyo, Kensuke Numakura, Yuta Matsuda, Alexander G. Ioannidis, Nicholas Katsanis, Tomohiro Takano, Carlos D. Bustamante

This study validates and automates polygenic risk score (PRS) development for cardiometabolic diseases using direct-to-consumer genetic and phenotypic data, showing comparable performance to larger clinical datasets.

Human Genomics · Sep 8, 2022Peer-reviewedGenetic & Genomic Medicine