Abstract
BackgroundLog-linear and multinomial modeling offer a flexible framework for genetic association analyses of offspring (child), parent-of-origin and maternal effects, based on genotype data from a variety of child-parent configurations. Although the calculation of statistical power or sample size is an important first step in the planning of any scientific study, there is currently a lack of software for genetic power calculations in family-based study designs. Here, we address this shortcoming through new implementations of power calculations in the R package Haplin, which is a flexible and robust software for genetic epidemiological analyses. Power calculations in Haplin can be performed analytically using the asymptotic variance-covariance structure of the parameter estimator, or else by a straightforward simulation approach. Haplin performs power calculations for child, parent-of-origin and maternal effects, as well as for gene-environment interactions. The power can be calculated for both single SNPs and haplotypes, either autosomal or X-linked. Moreover, Haplin enables power calculations for different child-parent configurations, including (but not limited to) case-parent triads, case-mother dyads, and case-parent triads in combination with unrelated control-parent triads.ResultsWe compared the asymptotic power approximations to the power of analysis attained with Haplin. For external validation, the results were further compared to the power of analysis attained by the EMIM software using data simulations from Haplin. Consistency observed between Haplin and EMIM across various genetic scenarios confirms the computational accuracy of the inference methods used in both programs. The results also demonstrate that power calculations in Haplin are applicable to genetic association studies using either log-linear or multinomial modeling approaches.ConclusionsHaplin provides a robust and reliable framework for power calculations in genetic association analyses for a wide range of genetic effects and etiologic scenarios, based on genotype data from a variety of child-parent configurations.
Highlights
Log-linear and multinomial modeling offer a flexible framework for genetic association analyses of offspring, parent-of-origin and maternal effects, based on genotype data from a variety of child-parent configurations
We propose a complete setup for power calculations tailored to binary disease traits, which we have implemented as a new module in the R package Haplin [10, 13]
We have developed and showcased extensive, new and easy-to-use functionalities for statistical power analyses based on log-linear modeling, incorporated in the R package Haplin
Summary
Comparison of the asymptotic power approximations to the simulated power in Haplin and EMIM Similar to Haplin, the command line software PREMIM and EMIM are easy-to-use tools for the estimation of child, PoO and maternal effects based on genotype data from a number of different study designs [11, 12]. Note that panels b and e are equivalent because the power to detect a given child or maternal effect is identical when adjusting for possible confounding of the effects with one another This symmetry depends on the study design and will not necessarily hold if case-mothers are unavailable for genotyping (results not shown). The results indicate that Haplin provides a robust and reliable framework for power calculations in genetic association studies when the genetic analyses are based on either log-linear or multinomial modeling
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