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TWO-SIGMA-G: A New Competitive Gene Set Testing Framework for scRNA-seq Data Accounting for Inter-Gene and Cell-Cell Correlation
Eric Van Buren, Ming Hu, Liang Cheng, John Wrobel, Kirk Wilhelmsen, Lishan Su, Yun Li, View ORCID ProfileDi Wu
doi: https://doi.org/10.1101/2021.01.24.427979
Eric Van Buren
1Department of Biostatistics, Harvard T.H. Chan School of Public Health
Ming Hu
2Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation
Liang Cheng
3Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill
4Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill
5Frontier Science Center for Immunology and Metabolism, Medical Research Institute, Wuhan University
John Wrobel
3Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill
Kirk Wilhelmsen
6Departments of Genetics and Neurology, Renaissance Computing Institute, University of North Carolina at Chapel Hill
Lishan Su
3Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill
4Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill
7Departments of Pharmacology, Microbiology & Immunology University of Maryland School of Medicine
Yun Li
8Department of Biostatistics, The University of North Carolina at Chapel Hill
9Department of Genetics, The University of North Carolina at Chapel Hill
10Department of Computer Science, The University of North Carolina at Chapel Hill
Di Wu
8Department of Biostatistics, The University of North Carolina at Chapel Hill
11Division of Oral and Craniofacial Health Sciences, Adams School of Dentistry, The University of North Carolina at Chapel Hill
Posted January 26, 2021.
TWO-SIGMA-G: A New Competitive Gene Set Testing Framework for scRNA-seq Data Accounting for Inter-Gene and Cell-Cell Correlation
Eric Van Buren, Ming Hu, Liang Cheng, John Wrobel, Kirk Wilhelmsen, Lishan Su, Yun Li, Di Wu
bioRxiv 2021.01.24.427979; doi: https://doi.org/10.1101/2021.01.24.427979
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