2021/03/03 by Dustin Pluta, Pluta, Dustin, Gui Xue +8
Biochemistry, Genetics and Molecular Biology · Neuroscience · #FOS: Computer and information sciences #Functional Brain Connectivity Studies #Gene expression and cancer classification #Genetic Associations and Epidemiology #Methodology (stat.ME)
paper · pdf · doi:10.48550/arxiv.2103.02156
openalex publication_date 2021/03/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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 health adults, we identified interesting associations of brain connectivity (measured by EEG coherence) with selected genetic features.