Author

Tim Morrison

Stanford University

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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Bioinformatics· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Research Focus:differential expression· 1 Research Focus:fine-mapping· 1 Assay:GWAS summary statistics· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Benjamin B. ChuiD· 2 shared Chiara SabattiiD· 2 shared Emmanuel J. CandèsiD· 2 shared Hua TangiD· 2 shared Iuliana Ionita‐LazaiD· 2 shared Jiaqi GuiD· 2 shared Linxi LiuiD· 2 shared Zhaomeng CheniD· 2 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Benjamin B. ChuORCID

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2 papers

Recent·Most cited

Uncovering Heterogeneous Effects via Localized Feature Selection

Xiaoxia Liu, Jiaqi Gu, Zhaomeng Chen, Benjamin B. Chu, Linxi Liu, Tim Morrison, Robert R. Butler, Jacob L Edelson, Jinzhou Li, Frank M. Longo, Hua Tang, Iuliana Ionita‐Laza, Chiara Sabatti, Emmanuel J. Candès, Zihuai He

This paper introduces a framework for identifying disease-associated features tailored to individual profiles using localized test statistics, applied to single-cell RNA sequencing data for Alzheimer's disease.

Proceedings of the National Academy of Sciences · Sep 15, 2026Peer-reviewedBioinformatics

Beyond guilty by association at scale: searching for causal variants on the basis of genome-wide summary statistics

Zihuai He, Benjamin B. Chu, James Yang, Jiaqi Gu, Zhaomeng Chen, Linxi Liu, Tim Morrison, Michaël E. Belloy, Xinran Qi, Nima S. Hejazi, Maya B. Mathur, Yann Le Guen, Hua Tang, Trevor J. Hastie, Iuliana Ionita‐Laza, , Chiara Sabatti

This paper introduces a method to identify causal variants from genome-wide summary statistics, outperforming existing methods and discovering additional loci for complex traits.

bioRxiv · Feb 28, 2024 · PreprintGenetics