Improved genetic discovery and fine-mapping resolution through multivariate latent factor analysis of high-dimensional traits.

Abstract excerpt

Genome-wide association studies (GWASs) of high-dimensional traits, such as blood cell or metabolic traits, often use univariate approaches, ignoring trait relationships. Biological mechanisms generating variation in high-dimensional traits can be captured parsimoniously through a GWAS of latent factors. Here, we introduce flashfmZero, a zero-correlation latent-factor-based multi-trait fine-mapping approach. In...

Topics

• Humans
• Genome-Wide Association Study
• Quantitative Trait Loci
• Chromosome Mapping
• Multivariate Analysis
• Polymorphism, Single Nucleotide