FVGWAS: Fast Voxelwise Genome Wide Association Analysis
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.
Citation: Huang, M. Y., Nichols, T., Huang, C., Yu, Y., Lu, Z. H., Knickmeyer, R. C., Feng, Q. J., Zhu, H. T., and the Alzheimer’s Disease Neuroimaging Initiative. FVGWAS: Fast Voxelwise Genome Wide Association Analysis of Large-scale Imaging Genetic Data. NeuroImage, 2015.