ArticleBehavior genetics2021
Combining Structural-Equation Modeling with Genomic-Relatedness-Matrix Restricted Maximum Likelihood in OpenMx.
Article in Behavior genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Tracing the Right Path: Determination of Large Pedigree Segmentation and Relatedness.Behavior genetics · 2026Article
- Observational and genetically-informed characterization of Gulf War Illness symptoms in 1990-1991 Gulf War deployed Veterans and non-deployed Gulf War Era Veterans.Environmental health : a global access science source · 2026Article
- BGmisc: An R Package for Extended Behavior Genetics Analysis.Journal of open source software · 2024Article
- Heritability Estimation of Cognitive Phenotypes in the ABCD StudyBehavior genetics · 2023Article
- Determining the stability of genome-wide factors in BMI between ages 40 to 69 years.PLoS genetics · 2022Article
- The Analytic Identification of Variance Component Models Common to Behavior Genetics.Behavior genetics · 2021Article
- Partitioning Phenotypic Variance Due to Parent-of-Origin Effects Using Genomic Relatedness Matrices.Behavior genetics · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
There is a long history of fitting biometrical structural-equation models (SEMs) in the pregenomic behavioral-genetics literature of twin, family, and adoption studies. Recently, a method has emerged for estimating biometrical variance-covariance components based not upon the expected degree of genetic resemblance among relatives, but upon the observed degree of genetic resemblance among unrelated individuals for whom genome-wide genotypes are available-genomic-relatedness-matrix restricted maximum-likelihood (GREML). However, most existing GREML software is concerned with quickly and efficiently estimating heritability coefficients, genetic correlations, and so on, rather than with allowing the user to fit SEMs to multitrait samples of genotyped participants. We therefore introduce a feature in the OpenMx package, "mxGREML", designed to fit the biometrical SEMs from the pregenomic era in present-day genomic study designs. We explain the additional functionality this new feature has brought to OpenMx, and how the new functionality works. We provide an illustrative example of its use. We discuss the feature's current limitations, and our plans for its further development.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.