strum: an R package for structural modeling of latent variables for general pedigrees

Abstract

BackgroundStructural equation modeling (SEM) is an extremely general and powerful approach to account for measurement error and causal pathways when analyzing data, and it has been used in wide range of applied sciences. There are many commercial and freely available software packages for SEM. However, it is difficult to use any of the packages to analyze general pedigree data, and SEM packages for genetics are limited in their application.ResultsWe present the new R package strum to serve the need of a suitable SEM software tool for genetic analysis. It implements a general framework for SEM within the context of general pedigree data. This context requires specialized considerations such as familial correlations and ascertainment. Our package is an extraordinarily flexible tool capable of modeling genetic association, linkage analysis, polygenic effects, shared environment, and ascertainment combined with confirmatory factor analysis and general SEM. It also provides a convenient tool for model visualization, and integrates tools for simulating pedigree data. The various features of this package are tested through a simulation study to evaluate performance, and our results show that strum is very reliable and robust in terms of the accuracy and coverage of parameter estimates.Conclusionsstrum is a valuable new tool for genetic analysis. It can be easily used with general pedigree data, incorporating both measurement and structural models, giving it some significant advantages over other software packages. It also includes a built-in approach for handling ascertainment, a helpful integrated tool for genetic data simulation, and built-in tools for model visualization, providing a significant addition to biomedical research.

Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds

“…The families also received single word reading ( Word Identification ) and single non-word reading ( Word Attack ) tasks from the Woodcock Reading Mastery Tests ((Woodcock 1997). We combined the two reading measures into a latent trait using the R (R Core Team 2013) structural equation modeling in pedigrees package strum version 0.6.2 (Morris and Song 2015) as described in (Song et al 2015). …”

Correcting and complementing freeway traffic accident data using Mahalanobis distance based outlier detection

“…On one hand, R [42] provides a multiplatform commonly used environment [43,44] to perform state-ofthe-art data analysis [45] (R environment is used throughout this paper). On the other hand, the speed-flow diagrams (Fig.…”

Association of gene variants with longitudinal changes in high density lipoprotein cholesterol among Tehranian People: A latent growth curve model

“…In strum a novel score test developed. This method is a computationally rapid test of association with many SNPs in GWAS data (Song et al 2015). In this new score test, we fi rst assessed the null model fi t without any SNPs in the model to confi rm the appropriateness of the model for the data.…”

“…One of these models is Morris and his colleagues that it would be in addition to the relationships between variables over time, taking into account the simultaneous equations to analyze genetic family data (Morris et al 2010). The model can be able to run a wide range of genetic models with latent variables under SEM, and in recent months the model R package, strum, has been released (Song et al 2015).…”