AIME: Autoencoder-based integrative multi-omics data embedding that allows for confounder adjustments

Tianwei Yu

doi:10.1371/journal.pcbi.1009826

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Open Access

Peer-reviewed

Research Article

AIME: Autoencoder-based integrative multi-omics data embedding that allows for confounder adjustments

Tianwei Yu

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: yutianwei@cuhk.edu.cn

Affiliations School of Data Science, The Chinese University of Hong Kong–Shenzhen, Shenzhen, Guangdong, China, Shenzhen Research Institute of Big Data, Shenzhen, Guangdong, China, Warshel Institute for Computational Biology, Shenzhen, Guangdong, China

https://orcid.org/0000-0003-2502-1628

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AIME: Autoencoder-based integrative multi-omics data embedding that allows for confounder adjustments

Tianwei Yu

Published: January 26, 2022
https://doi.org/10.1371/journal.pcbi.1009826

About the Authors

Tianwei Yu

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: yutianwei@cuhk.edu.cn

Affiliations School of Data Science, The Chinese University of Hong Kong–Shenzhen, Shenzhen, Guangdong, China, Shenzhen Research Institute of Big Data, Shenzhen, Guangdong, China, Warshel Institute for Computational Biology, Shenzhen, Guangdong, China

https://orcid.org/0000-0003-2502-1628

Competing Interests

The authors have declared that no competing interests exist.

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