Mar 31, 2020

Flexible multivariate linear mixed models for structured multiple traits

BioRxiv : the Preprint Server for Biology
Jitka Polechová, Nick Barton

Abstract

Many genetic studies collect structured multivariate traits that have rich information about the traits encoded in trait covariates, in addition to the genotype and covariate information on individuals. Examples of such data include gene-environment studies where the same genotype/clone is measured in multiple enviroments, and longitudinal studies where a measurement is taken at multiple time points. We present a flexible multivariate linear mixed model (fMulti-LMM) suitable for genetic analysis of structured multivariate traits. Our model can incorporate low- and high-dimensional trait covariates to test the genetic association across structured multiple traits while capturing the correlations due to individual-to-individual similarity measured by genome-wide markers and trait-to-trait similarity measured by trait covariates.

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Mentioned in this Paper

Genetic Drift
Abnormal Fragmented Structure
Spatial Distribution
Environment
Adaptation
Species
Biological Evolution
Adapt (substance)
Habitat
Human Activity Profile Test

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