rs11872654 - AIDAP3 - METTL4

Magnitude 2.0 · 1 study on file

Reported associations

• Incorporating spatial-anatomical similarity into the VGWAS framework for AD biomarker detection. - Bioinformatics (Oxford, England) (2020) · Huang M, Yu Y, Yang W, Feng Q · PubMed 31095298

  The detection of potential biomarkers of Alzheimer's disease (AD) is crucial for its early prediction, diagnosis and treatment. Voxel-wise genome-wide association study (VGWAS) is a commonly used method in imaging genomics and usually applied to detect AD biomarkers in imaging and genetic data. However, existing VGWAS methods entail large computational cost and disregard spatial correlations within imaging data. A novel method is proposed to solve these issues. We introduce a novel method to incorporate spatial correlations into a VGWAS framework for the detection of potential AD biomarkers. To consider the characteristics of AD, we first present a modification of a simple linear iterative clustering method for spatial grouping in an anatomically meaningful manner. Second, we propose a spa

Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.