Ridge-penalized adaptive Mantel test and its application in imaging genetics
Type
ArticleKAUST Department
Biostatistics GroupComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Statistics Program
Date
2021-07-02Preprint Posting Date
2021-03-03Online Publication Date
2021-07-02Print Publication Date
2021-10-30Embargo End Date
2022-07-02Submitted Date
2020-07-20Permanent link to this record
http://hdl.handle.net/10754/668442
Metadata
Show full item recordAbstract
We propose a ridge-penalized adaptive Mantel test (AdaMant) for evaluating the association of two high-dimensional sets of features. By introducing a ridge penalty, AdaMant tests the association across many metrics simultaneously. We demonstrate how ridge penalization bridges Euclidean and Mahalanobis distances and their corresponding linear models from the perspective of association measurement and testing. This result is not only theoretically interesting but also has important implications in penalized hypothesis testing, especially in high-dimensional settings such as imaging genetics. Applying the proposed method to an imaging genetic study of visual working memory in healthy adults, we identified interesting associations of brain connectivity (measured by electroencephalogram coherence) with selected genetic features.Citation
Pluta, D., Shen, T., Xue, G., Chen, C., Ombao, H., & Yu, Z. (2021). Ridge-penalized adaptive Mantel test and its application in imaging genetics. Statistics in Medicine. doi:10.1002/sim.9127Sponsors
We thank Professor Daniel L. Gillen, University of California, Irvine for the helpful discussions. We greatly appreciate the reviewers' insightful, careful, and constructive comments on our manuscript. These valuable comments have helped us improve the quality of our work.Publisher
WileyJournal
Statistics in MedicineDOI
10.1002/sim.9127PubMed ID
34216035arXiv
2103.02156Additional Links
https://onlinelibrary.wiley.com/doi/10.1002/sim.9127ae974a485f413a2113503eed53cd6c53
10.1002/sim.9127
Scopus Count
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