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,...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Ying Zhang, Li’ang Yang, Weiguo Cui, Runqing Yang
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2026-02-01
Schriftenreihe:	Biology
Schlagworte:	growth trajectory genome-wide association analysis hierarchical non-linear mixed model multivariate mixed model computing efficiency
Online-Zugang:	https://www.mdpi.com/2079-7737/15/4/361
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