Author

Sarah Sumner

University of ChicagoORCID 0000-0001-6243-3651Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:gene regulatory network inference· 2 Research Focus:GWAS / association mapping· 2 Assay:GWAS summary statistics· 2 Organism:human· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Festus M. NyasimiiD· 3 shared Hae Kyung ImiD· 3 shared Abraham A. PalmeriD· 2 shared Sandra Sanchez‐RoigeiD· 2 shared Yanyu LiangiD· 2 shared Alesa Hughson· 1 shared Alexander C. LamparelliiD· 1 shared Alexander F. GiletaiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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3 shared papersGenetics

Festus M. NyasimiORCID

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3 papers

Recent·Most cited

GeneticsbioRxivPreprintJul 17, 2026

MetaboXcan: A multiomic framework linking genetically predicted metabolites, gene expression, and complex traits

Festus M. Nyasimi, Sarah Sumner, Yanyu Liang…·Hae Kyung Im

MetaboXcan predicts plasma metabolites from genetic data and associates them with complex traits, identifying disease risk genes and metabolites in chronic kidney disease.

DOI 10.64898/2026.07.15.738631

humanGWAS summary statistics

𝕏 PostBluesky

GenomicsPLoS GeneticsPeer-reviewedMar 31, 2025

RatXcan: A framework for cross-species integration of genome-wide association and gene expression data

Natasha Santhanam, Sandra Sanchez‐Roige, Sabrina Mi…·Hae Kyung Im

RatXcan extends transcriptome-wide association studies to rats, enabling cross-species integration of GWAS and gene expression data to identify shared genetic mechanisms of complex traits.

3 citations

ratGWAS summary statistics

𝕏 PostBluesky

GeneticsbioRxivPreprintNov 11, 2024

scPrediXcan integrates advances in deep learning and single-cell data into a powerful cell-type-specific transcriptome-wide association study framework

Yichao Zhou, Temidayo Adeluwa, Lisha Zhu…·Hae Kyung Im

scPrediXcan improves transcriptome-wide association studies by integrating deep learning for cell-type-specific gene expression prediction, identifying more causal genes and explaining more GWAS loci in type 2 diabetes and systemic lupus erythematosus.

1 citation

humanbulk RNA-seq

𝕏 PostBluesky