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HILAMA: High-dimensional multi-omic mediation analysis with latent confounding
Xinbo Wang, Junyuan Liu, Sheng’en Shawn Hu, Zhonghua Liu, Hui Lu, View ORCID ProfileLin Liu, the Alzheimer’s Disease Neuroimaging Initiative
doi: https://doi.org/10.1101/2023.09.15.557839
Xinbo Wang
1State Key Lab of Microbial Metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
2SJTU-Yale Joint Center of Biostatistics and Data Science, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
Junyuan Liu
3School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China
Sheng’en Shawn Hu
4Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
Zhonghua Liu
5Department of Biostatistics, Columbia University, New York, NY, USA
Hui Lu
1State Key Lab of Microbial Metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
2SJTU-Yale Joint Center of Biostatistics and Data Science, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
6Shanghai Children’s Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
Lin Liu
2SJTU-Yale Joint Center of Biostatistics and Data Science, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
3School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China
7Institute of Natural Sciences, MOE-LSC, CMA-Shanghai, Shanghai Jiao Tong University, Shanghai, China
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Posted September 15, 2023.
HILAMA: High-dimensional multi-omic mediation analysis with latent confounding
Xinbo Wang, Junyuan Liu, Sheng’en Shawn Hu, Zhonghua Liu, Hui Lu, Lin Liu, the Alzheimer’s Disease Neuroimaging Initiative
bioRxiv 2023.09.15.557839; doi: https://doi.org/10.1101/2023.09.15.557839
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