Author

Tianying Wang

Colorado State UniversityORCID 0000-0002-2826-5364Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Approach:statistical model· 3 Research Focus:GWAS / association mapping· 2 Assay:GWAS summary statistics· 2 Organism:human· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:imputation· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Chen WangiD· 2 shared Iuliana Ionita‐LazaiD· 2 shared Edoardo FiorilloiD· 1 shared Fan WangiD· 1 shared Francesco CuccaiD· 1 shared Hugues AschardiD· 1 shared Marcella DevotoiD· 1 shared Marco MasalaiD· 1 shared

Activity by Year

2023-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 26 mutual co-author links

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2 shared papersBioinformatics

Chen WangORCID

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3 papers

Recent·Most cited

Denoising Single-Cell RNA-Seq Data with a Deep Learning-Embedded Statistical Framework

Qinhuan Luo, Yongzhen Yu, Tianying Wang

ZILLNB denoises and imputes scRNA-seq data by combining zero-inflated negative binomial regression with deep generative modeling, improving gene expression accuracy and subpopulation identification.

BMC Bioinformatics · Nov 19, 2025Peer-reviewedBioinformatics

Regenie.QRS: computationally efficient whole-genome quantile regression at biobank scale

Fan Wang, Chen Wang, Tianying Wang, Marco Masala, Edoardo Fiorillo, Marcella Devoto, Francesco Cucca, Iuliana Ionita‐Laza

Regenie.QRS is a computationally efficient whole-genome quantile regression method for biobank-scale GWAS data, showing improved power to detect heterogeneous genetic effects.

bioRxiv · May 2, 2025 · PreprintBioinformatics

Quantile Regression for biomarkers in the UK Biobank

Chen Wang, Tianying Wang, Ying Wei, Hugues Aschard, Iuliana Ionita‐Laza

This paper applies quantile regression to GWAS in the UK Biobank to identify significant loci for quantitative traits, finding 259 loci only detected by quantile regression.

bioRxiv · Jun 5, 2023 · PreprintGenomics