Related Experiment Video

Updated: Jun 17, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Growth mixture modeling as an exploratory analysis tool in longitudinal quantitative trait loci analysis

Su-Wei Chang1, Seung Hoan Choi, Ke Li

  • 1Department of Applied Mathematics and Statistics, Stony Brook University, 100 Nicolls Road, Stony Brook, New York 11794, USA. shuchang@ams.sunysb.edu.

BMC Proceedings
|December 19, 2009
PubMed
Summary

Growth mixture modeling shows promise for genome-wide association studies (GWAS) in identifying quantitative trait loci (QTLs). While the likelihood-ratio test was unreliable, direct and Bayesian tests effectively identified genetic markers associated with traits, even when near, not directly at, the gene.

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