SUMMARY
While combinatorial genetic data collection from biological systems in which quantitative phenotypes are controlled by functional and non-functional alleles in each of multiple genes (multi-gene systems) is becoming common, a standard analysis method for such data has not been established. A common additive model of the non-functional allele effects contrasted against the functional alleles, based on ANOVA with interaction, has three issues. First, although it is a long tradition of genetics, modeling the effect of the non-functional allele (a null mutant allele) contrasted against that of the functional allele (the wild-type allele) is not suitable for mechanistic understanding of multi-gene systems. Second, an additive model is highly problematic when the system has more than two genes and a limited phenotypic range: errors propagate toward higher order interactions. Third, interpretations of higher-order interactions defined by an additive model are not intuitive. I propose an averaging model, which is suitable for mechanistic understanding of multi-gene systems. The effect of the functional allele is contrasted against the effect of the non-functional allele for easier mechanistic interpretations. Errors in interactions across the orders consistently stay low, which makes the model highly scalable to systems with many genes. The interactions defined by the averaging model are highly intuitive regardless of the orders. Yet, it is still a general linear model, so model fitting is easy and accurate using common statistical tools.
Competing Interest Statement
The authors have declared no competing interest.