Fast and powerful heritability inference for family-based neuroimaging studies

摘要

Heritability estimation has become an important tool for imaging genetics studies. The large number of voxel-and vertex-wise measurements in imaging genetics studies presents a challenge both in terms of computational intensity and the need to account for elevated false positive risk because of the multiple testing problem. There is a gap in existing tools, as standard neuroimaging software cannot estimate heritability, and yet standard quantitative genetics tools cannot provide essential neuroimaging inferences, like family-wise error corrected voxel-wise or cluster-wiseP-values. Moreover, available heritability tools rely on P-values that can be inaccurate with usual parametric inference methods.