Meta-analysis of quantitative pleiotropic traits for
next-generation sequencing with multivariate functional
linear models
Prof. Mei-Ling Ting Lee (丁美齡)
University of Maryland, College Park, MD
USA
[email protected]
Abstract
To analyze next-generation sequencing data, multivariate functional linear models
are developed for a meta-analysis of multiple studies to connect genetic variant data to
multiple quantitative traits adjusting for covariates. The goal is to take the advantage
of both meta-analysis and pleiotropic analysis in order to improve power and to carry
out a unified association analysis of multiple studies and multiple traits of complex
disorders. The proposed methods are applied to analyze lipid traits in eight European
cohorts. The proposed methods can be applied to studies that have individual genotype
data; it can also be used as a criterion for future work that uses summary statistics to
build test statistics to meta-analyze the data.