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Operating characteristics of alternative statistical methods for detecting gene-by-measured environment interaction in the presence of gene-environment correlation in twin and sibling studies.

ABSTRACT: It is likely that all complex behaviors and diseases result from interactions between genetic vulnerabilities and environmental factors. Accurately identifying such gene-environment interactions is of critical importance for genetic research on health and behavior. In a previous article we proposed a set of models for testing alternative relationships between a phenotype (P) and a putative moderator (M) in twin studies. These include the traditional bivariate Cholesky model, an extension of that model that allows for interactions between M and the underling influences on P, and a model in which M has a non-linear main effect on P. Here we use simulations to evaluate the type I error rates, power, and performance of the Bayesian Information Criterion under a variety of data generating mechanisms and samples sizes (n = 2,000 and n = 500 twin pairs). In testing the extension of the Cholesky model, false positive rates consistently fell short of the nominal Type I error rates ([Formula: see text]). With adequate sample size (n = 2,000 pairs), the correct model had the lowest BIC value in nearly all simulated datasets. With lower sample sizes, models specifying non-linear main effects were more difficult to distinguish from models containing interaction effects. In addition, we provide an illustration of our approach by examining possible interactions between birthweight and the genetic and environmental influences on child and adolescent anxiety using previously collected data. We found a significant interaction between birthweight and the genetic and environmental influences on anxiety. However, the interaction was accounted for by non-linear main effects of birthweight on anxiety, verifying that interaction effects need to be tested against alternative models.

SUBMITTER: Van Hulle CA

PROVIDER: S-EPMC3552083 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Operating characteristics of alternative statistical methods for detecting gene-by-measured environment interaction in the presence of gene-environment correlation in twin and sibling studies.

Van Hulle Carol A CA Lahey Benjamin B BB Rathouz Paul J PJ

Behavior genetics 20121023 1

It is likely that all complex behaviors and diseases result from interactions between genetic vulnerabilities and environmental factors. Accurately identifying such gene-environment interactions is of critical importance for genetic research on health and behavior. In a previous article we proposed a set of models for testing alternative relationships between a phenotype (P) and a putative moderator (M) in twin studies. These include the traditional bivariate Cholesky model, an extension of that ...[more]

PMID: 23090766

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Project description:BackgroundTo understand the evolutionary role of Lateral Gene Transfer (LGT), accurate methods are needed to identify transferred genes and infer their timing of acquisition. Phylogenetic methods are particularly promising for this purpose, but the reconciliation of a gene tree with a reference (species) tree is computationally hard. In addition, the application of these methods to real data raises the problem of sorting out real and artifactual phylogenetic conflict.ResultsWe present Prunier, a new method for phylogenetic detection of LGT based on the search for a maximum statistical agreement forest (MSAF) between a gene tree and a reference tree. The program is flexible as it can use any definition of "agreement" among trees. We evaluate the performance of Prunier and two other programs (EEEP and RIATA-HGT) for their ability to detect transferred genes in realistic simulations where gene trees are reconstructed from sequences. Prunier proposes a single scenario that compares to the other methods in terms of sensitivity, but shows higher specificity. We show that LGT scenarios carry a strong signal about the position of the root of the species tree and could be used to identify the direction of evolutionary time on the species tree. We use Prunier on a biological dataset of 23 universal proteins and discuss their suitability for inferring the tree of life.ConclusionsThe ability of Prunier to take into account branch support in the process of reconciliation allows a gain in complexity, in comparison to EEEP, and in accuracy in comparison to RIATA-HGT. Prunier's greedy algorithm proposes a single scenario of LGT for a gene family, but its quality always compares to the best solutions provided by the other algorithms. When the root position is uncertain in the species tree, Prunier is able to infer a scenario per root at a limited additional computational cost and can easily run on large datasets.Prunier is implemented in C++, using the Bio++ library and the phylogeny program Treefinder. It is available at: http://pbil.univ-lyon1.fr/software/prunier.

Dataset Information

Operating characteristics of alternative statistical methods for detecting gene-by-measured environment interaction in the presence of gene-environment correlation in twin and sibling studies.

Publications

Operating characteristics of alternative statistical methods for detecting gene-by-measured environment interaction in the presence of gene-environment correlation in twin and sibling studies.

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