The growing number of wildlife endocrinology studies have greatly enhanced our understanding of comparative endocrinology, and have also generated extensive longitudinal data for a vast number of species. However, the extensive graphical analysis required for these longitudinal datasets can be time consuming because there is often a need to create tens, if not hundreds, of graphs. Furthermore, routine methods for summarising hormone profiles, such as the iterative baseline approach and area under the curve (AUC), can be tedious and non-reproducible, especially for large number of individuals. We developed an R package, hormLong, which provides the basic functions to perform graphical and numerical analyses routinely used by wildlife endocrinologists. To encourage its use, hormLong has been developed such that no familiarity with R is necessary. Here, we provide a brief overview of the functions currently available and demonstrate their utility with previously published Asian elephant data. We hope that this package will promote reproducibility and encourage standardization of wildlife hormone data analysis.
Inferring signalling networks from longitudinal data using sampling based approaches in the R-package 'ddepn'
