Author

Jonathan Jala

University of California, Los Angeles

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

Biology Disciplines

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Genomics· 3 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Assay:GWAS summary statistics· 4 Organism:human· 4 Approach:statistical model· 4 Research Focus:GWAS / association mapping· 3 Research Focus:benchmarking· 1 Research Focus:polygenic risk· 1

Frequent Co-Authors

Daniel Jacob BenjaminiD· 4 shared Patrick TurleyiD· 4 shared David A. CesariniiD· 3 shared Alexander I. YoungiD· 2 shared David LaibsoniD· 2 shared Dhruva Jaishankar· 2 shared Michelle N. MeyeriD· 2 shared Aaron Kleinman· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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4 shared papersGenomics

Daniel Jacob BenjaminORCID

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Author profile →

4 papers

Recent·Most cited

Genomic-Relatedness Matching Expands Population Coverage, Improves Power, and Reduces Bias in Genetic Association Analyses

Dhruva Jaishankar, Tamara Gjorgjieva, Jonathan Jala, Jeffrey Swigert, Alexander I. Young, Daniel Jacob Benjamin, David A. Cesarini, Patrick Turley

The paper introduces GRMA, a method that improves genetic association analyses by reducing bias and expanding population coverage compared to GWAS.

medRxiv · May 18, 2026 · PreprintGenetic & Genomic Medicine

An Updated Polygenic Index Repository: Expanded Phenotypes, New Cohorts, and Improved Causal Inference

Robel G. Alemu, Anastasia Terskaya, Matthew Howell, Junming Guan, Harry Sands, Aaron Kleinman, David Bann, Tim Morris, George B. Ploubidis, Emla Fitzsimons, Kathleen Mullan Harris, Avshalom Caspi, David L. Corcoran, Terrie E. Moffitt, Richie Poulton, , Aysu Okbay

The paper updates a polygenic index repository with more phenotypes, datasets, and improved causal inference methods, enhancing predictive performance and interpretability.

bioRxiv · May 14, 2025 · PreprintGenomics

A General Approach to Adjusting Genetic Studies for Assortative Mating

Marta Bilghese, Regina Manansala, Dhruva Jaishankar, Jonathan Jala, Daniel Jacob Benjamin, Miles Kimball, Paul Livermore Auer, Michael A. Livermore, Patrick Turley

This paper introduces a method to adjust genetic studies for assortative mating using polygenic indexes, finding that assortative mating inflates genetic correlation estimates between health traits and education by 14% on average.

bioRxiv · Sep 1, 2023 · PreprintGenomics

Multi-Ancestry Meta-Analysis yields novel genetic discoveries and ancestry-specific associations

Patrick Turley, Alicia R. Martin, Grant Goldman, Hui Li, Masahiro Kanai, Raymond Kenney Walters, Jonathan Jala, Kuang Lin, Iona Y. Millwood, Caitlin E. Carey, Duncan S. Palmer, Meghan L. Zacher, Elizabeth G. Atkinson, Zhengming Chen, Liming Li, , Benjamin M. Neale

This paper introduces MAMA, a method for multi-ancestry GWAS meta-analysis, which identifies novel genetic associations and improves power across populations.

bioRxiv · Apr 23, 2021 · PreprintGenomics