dispRity: A modular R package for measuring disparity

Abstract

Biological data is multivariate in essence: many traits in organisms covary with each other in space and time. This causes biologists to either reduce these to a manageable number of variables or, increasingly, to use multivariate toolkits. One such toolkit is based on creating a multidimensional space where the variables are the axes. It is then possible to measure diverse aspects of the distribution of some observation (e.g. species) in this space. For example, if studying morphology, one can create a morphospace for two groups of species, measure the volume occupied by each of these groups and then test whether these two volumes are significantly different or not. There are as many definitions of these multidimensional spaces, metrics and tests as there are questions that can be tackled with such methods. Many of these methods are implemented in specific software or r packages. However, the definition of the space, metric and test is often dependent on the software/package and authors points of view or specific questions. This can unfortunately hamper researchers’ ability to apply different methods that best suits their specific questions. Here I present the dispRity package, a flexible R package for performing multidimensional analysis. It allows users to define each step of the analysis (whether it is the space, the metric or the test) through a highly modular architecture where each definition can be passed as a function. It also provides a tidy interface through the dispRity object, allowing users to easily run reproducible multivariate analysis. The dispRity package also comes with an extend manual regularly updated following users’ questions or suggestions. Furthermore, the package contains some simulation tools (e.g to simulate complex multidimensional space or morphological data). Finally, it also contains a suite of utility functions to work with dispRity objects aimed at helping users to develop their own multidimensional metrics and/or tests.