FVGWAS: Fast Voxelwise Genome Wide Association Analysis
The 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. Speci cally, 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.
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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Recent Activity - Documents
FGWAS: Functional genome wide association analysis posted by Chao Huang on Mar 27, 2018
FVGWAS-3.0_Manual posted by Chao Huang on May 24, 2016
FVGWAS-2.0_Manual posted by Chao Huang on Nov 9, 2015
Recent Activity - Forums
Welcome to Open-Discussion posted by Chao Huang on Jun 11, 2015
Welcome to Help posted by Chao Huang on Jun 11, 2015
Recent Activity - Files
fvgwas: FVGWAS-3.0-linux release
FVGWAS-3.0-linux.zip posted by Chao Huang on May 24, 2016
FVGWAS-2.0-linux.zip posted by Chao Huang on Nov 9, 2015
FVGWAS-2.0-win64.zip posted by Chao Huang on Nov 9, 2015
FVGWAS-1.1.zip posted by Chao Huang on Jul 31, 2015
BIAS posted by Chao Huang on Jun 11, 2015
FVGWAS-1.0.zip posted by Chao Huang on Jun 11, 2015