Ekrami, OmidClaes, PeterWhite, Julie D.Weinberg, Seth M.Marazita, Mary L.Walsh, SusanShriver, Mark D.Van Dongen, Stefan2022-05-182022-05-182020-03Ekrami O, Claes P, White JD, et al. A Multivariate Approach to Determine the Dimensionality of Human Facial Asymmetry. Symmetry (Basel). 2020;12(3):348. doi:10.3390/sym12030348https://hdl.handle.net/1805/29048Many studies have suggested that developmental instability (DI) could lead to asymmetric development, otherwise known as fluctuating asymmetry (FA). Several attempts to unravel the biological meaning of FA have been made, yet the main step in estimating FA is to remove the effects of directional asymmetry (DA), which is defined as the average bilateral asymmetry at the population level. Here, we demonstrate in a multivariate context that the conventional method of DA correction does not adequately compensate for the effects of DA in other dimensions of asymmetry. This appears to be due to the presence of between-individual variation along the DA dimension. Consequently, we propose to decompose asymmetry into its different orthogonal dimensions, where we introduce a new measure of asymmetry, namely fluctuating directional asymmetry (F-DA). This measure describes individual variation in the dimension of DA, and can be used to adequately correct the asymmetry measurements for the presence of DA. We provide evidence that this measure can be useful in disentangling the different dimensions of asymmetry, and further studies on this measure can provide valuable insight into the underlying biological processes leading to these different asymmetry dimensions.en-USPublisher PolicyFluctuating asymmetry3D morphometricsDirectional asymmetrySexual dimorphismArticle