Author

Jiamao Zheng

University of Chicago

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

Signature Assays, Organisms & Methods

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Assay:GWAS summary statistics· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Research Focus:eQTL / molecular QTL mapping· 1 Research Focus:gene regulatory network inference· 1 Research Focus:GWAS / association mapping· 1

Frequent Co-Authors

Alvaro BarbeiraiD· 2 shared Heather E. WheeleriD· 2 shared Alexandra J. ScottiD· 1 shared Alexis J. BattleiD· 1 shared Andrew B. NobeliD· 1 shared Andrew BrowniD· 1 shared Andrey A. ShabaliniD· 1 shared Anne W. Ndungu· 1 shared

Activity by Year

2018-2019 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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2 shared papersGenomics

Alvaro BarbeiraORCID

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2 papers

Recent·Most cited

Integrating Predicted Transcriptome From Multiple Tissues Improves Association Detection

Alvaro Barbeira, Milton Pividori, Jiamao Zheng, Heather E. Wheeler, Dan L. Nicolae, Hae Kyung Im

The paper introduces MulTiXcan, a method that improves association detection by integrating eQTL data across tissues, showing it identifies more significant genes than single-tissue analyses.

PLoS Genetics · Jan 22, 2019Peer-reviewedGenomics

Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics

Alvaro Barbeira, Scott P. Dickinson, Rodrigo Bonazzola, Jiamao Zheng, Heather E. Wheeler, Jason M. Torres, Eric S. Torstenson, Kaanan P. Shah, Tzintzuni Garcia, Todd L. Edwards, Eli Stahl, Laura M. Huckins, François Aguet, Kristin Ardlie, Beryl B. Cummings, , Benjamin J. Strober

The paper develops S-PrediXcan to compute gene expression associations from GWAS summary data and applies it to 44 GTEx tissues and 100+ phenotypes, finding tissue-specific effects and colocalized associations.

Nature Communications · May 2, 2018Peer-reviewedGenomics