FVGWAS: Fast Voxelwise Genome Wide Association Analysis
Introduction
The aim of this tool is to to develop a Fast Voxelwise Genome Wide Association analysiS (FVGWAS) framework to efficiently carry out whole-genome analyses of whole-brain data. FVGWAS consists of three components including a heteroscedastic linear model, a global sure independence screening (GSIS) procedure, and a detection procedure based on wild bootstrap methods. Specifically, for standard linear association, the computational complexity is O(n*N_V*N_C) for voxelwise genome wide association analysis (VGWAS) method compared with O((N_C+N_V)*n^2) for FVGWAS. Our FVGWAS may be a valuable statistical toolbox for large-scale imaging genetic analysis as the field is rapidly advancing with ultra-high-resolution imaging and whole-genome sequencing.
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References
1. Huang, M. Y., Nichols, T., Huang, C., Yu, Y., Lu, Z. H., Knickmeyer, R. C., Feng, Q. J., Zhu, H. T., and for the Alzheimer's Disease Neuroimaging Initiative FVGWAS: Fast Voxelwise Genome Wide Association Analysis of Large-scale Imaging Genetic Data. NeuroImage, 2015, accepted.