Author

Josh Smith

University of Washington

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· 2 Genetics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:DNA methylation· 2 Assay:proteomics· 2 Approach:statistical model· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:database / resource· 1

Frequent Co-Authors

François AguetiD· 3 shared Jerome I. RotteriD· 3 shared Kent D. TayloriD· 3 shared Kristin ArdlieiD· 3 shared Russell P. TracyiD· 3 shared Stacey GabrieliD· 3 shared Stephen S. RichiD· 3 shared Yongmei LiuiD· 3 shared

Activity by Year

2022-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersGenomics

François AguetORCID

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Author profile →

3 papers

Recent·Most cited

The functional impact of rare variation across the regulatory cascade

Taibo Li, Nicole M. Ferraro, Benjamin J. Strober, François Aguet, Silva Kasela, Marios Arvanitis, Bohan Ni, Laurens Wiel, Elliot A. Hershberg, Kristin Ardlie, Dan E. Arking, Rebecca L. Beer, Jennifer A. Brody, Thomas W. Blackwell, Clary B. Clish, , Stephen B. Montgomery

The paper identifies impactful rare variants by integrating multi-omic data from MESA, showing that combining expression and protein data increases the detection of rare stop and frameshift variants.

Cell Genomics · Sep 6, 2023Peer-reviewedGenomics

Uncovering Cross-Cohort Molecular Features with Multi-Omics Integration Analysis

Min-Zhi Jiang, François Aguet, Kristin Ardlie, Jiawen Carmen Chen, Elaine S. Cornell, Dan Cruz, Peter Durda, Stacey Gabriel, Robert Edgardo Gerszten, Xiuqing Guo, Craig W Johnson, Silva Kasela, Leslie A. Lange, Tuuli Lappalainen, Yongmei Liu, , TOPMed Analysis Working Group

This paper improves multi-omics integration by enhancing orthogonality in canonical vectors and demonstrates transferability across cohorts for proteomics and methylomics data.

bioRxiv · Nov 10, 2022 · PreprintGenomics

Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits

Roshni A. Patel, Shaila A. Musharoff, Jeffrey P. Spence, Harold Pimentel, Catherine Tcheandjieu, Hakhamanesh Mostafavi, Nasa Sinnott-Armstrong, Shoa L. Clarke, Courtney J. Smith, VA Million Veteran Program, Peter Durda, Kent D. Taylor, Russell P. Tracy, Yongmei Liu, Craig W Johnson, , Jonathan K. Pritchard

The paper tests for genetic interactions affecting causal variant effect sizes in gene expression and LDL-C across European and African American populations, finding significant evidence in gene expression but not LDL-C.

The American Journal of Human Genetics · Jun 17, 2022Peer-reviewedGenetics