Insight into Genome-Wide Associations of Growth Trajectories Using a Hierarchical Non-Linear Mixed Model

In applying a hierarchical mixed model to genome-wide association analysis (GWAS) of longitudinal data, dimensionality reduction through modeling repeated measurements improves both computational efficiency and statistical power. Legendre polynomials can flexibly fit population growth trajectories,...

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Auteurs principaux:	Ying Zhang, Li’ang Yang, Weiguo Cui, Runqing Yang
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2026-02-01
Collection:	Biology
Sujets:	growth trajectory genome-wide association analysis hierarchical non-linear mixed model multivariate mixed model computing efficiency
Accès en ligne:	https://www.mdpi.com/2079-7737/15/4/361
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