TY - JOUR T1 - AlphaPart - R implementation of the method for partitioning genetic trends JF - bioRxiv DO - 10.1101/2020.04.24.059071 SP - 2020.04.24.059071 AU - Jana Obšteter AU - Justin Holl AU - John M. Hickey AU - Gregor Gorjanc Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/04/25/2020.04.24.059071.abstract N2 - Background In this paper we present the AlphaPart R package, an open-source software that implements a method for partitioning breeding values and genetic trends to identify sources of genetic gain. Breeding programmes improve populations for a set of traits, which can be measured with a genetic trend calculated from averaged year of birth estimated breeding values of selection candidates. While sources of the overall genetic gain are generally known, their realised contributions are hard to quantify in complex breeding programmes. The aim of this paper is to present the AlphaPart R package and demonstrate it with a simulated pig breeding example.Results The package includes the main partitioning function AlphaPart, that partitions the breeding values and genetic trends by analyst defined paths, and a set of functions for handling data and results. The package is freely available from CRAN repository at http://CRAN.R-project.org/package=AlphaPart. We demonstrate the use of the package by examining the genetic gain in a pig breeding example, in which the multiplier achieved higher breeding values than the nucleus for traits measured and selected in the multiplier. The partitioning analysis revealed that these higher values depended on the accuracy and intensity of selection in the multiplier and the extent of gene flow from the nucleus. For traits measured only in the nucleus, the multiplier achieved comparable or smaller genetic gain than the nucleus depending on the amount of gene flow.Conclusions AlphaPart implements a method for partitioning breeding values and genetic trends and provides a useful tool for quantifying the sources of genetic gain in breeding programmes. The use of AlphaPart will help breeders to better understand or improve their breeding programmes.Competing Interest StatementThe authors have declared no competing interest. ER -