Author

Shijia Bian

Emory UniversityORCID 0000-0001-5314-0726Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetics· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Research Focus:GWAS / association mapping· 2 Assay:GWAS summary statistics· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1

Frequent Co-Authors

Aliza P. WingoiD· 2 shared Andrew J. BassiD· 2 shared David J. CutleriD· 2 shared Michael P. EpsteiniD· 2 shared Thomas S. WingoiD· 2 shared Ana Navas Acien· 1 shared Andrea BaccarelliiD· 1 shared Badri Narayan VardarajaniD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersGenetics

Aliza P. WingoORCID

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3 papers

Recent·Most cited

BioinformaticsBriefings in BioinformaticsPeer-reviewedJan 1, 2026

CoxMDS: Multiple Data Splitting for High-dimensional Mediation Analysis with Survival Outcomes in Epigenome-wide Studies

Minhao Yao, Peixin Tian, Xihao Li…·the Alzheimer’s Disease Neuroimaging Initiative

CoxMDS identifies causal mediators in DNA methylation studies with survival outcomes, maintaining FDR control and higher power than existing methods.

DOI 10.1093/bib/bbaf730

humanDNA methylation

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GeneticsbioRxivPreprintSep 10, 2024

SCAMPI: A scalable statistical framework for genome-wide interaction testing harnessing cross-trait correlations

Shijia Bian, Andrew J. Bass, Yue Liu…·Michael P. Epstein

SCAMPI detects SNP interactions across multiple traits by analyzing trait correlation patterns, improving power over univariate methods in lipid-related traits from UK Biobank data.

2 citations

humanGWAS summary statistics

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GeneticsGenome MedicinePeer-reviewedApr 25, 2024

Identifying latent genetic interactions in genome-wide association studies using multiple traits

Andrew J. Bass, Shijia Bian, Aliza P. Wingo…·Michael P. Epstein

This paper introduces LIT, a method to detect latent genetic interactions using multiple traits, showing improved power compared to univariate methods in obesity-related traits.

8 citations

humanGWAS summary statistics

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