This repository contains R
functions for integrating (genomic) estimated breeding values ((G)EBVs) into national evaluations following Bonifazi et al., 2023, GSE. These functions compute Effective Records Contribution (ERC), de-regressed proof (DRP), adjusted de-regressed ERC (dERC*) and adjusted DRP (DRP*).
Two R packages are required: dplyr
(for data manipulation) and assertthat
(for asserting arguments' type). For installation, please refer to the respective packages' links.
Either download All_functions.R or copy-paste the code contained in it. This file contains all R functions.
Load the R functions into your R session either by including them in your scripts (copy-paste and run them before using them) or by sourcing the downloaded R file into your R code as
source("my_directory/All_functions.R")
See the documentation of each R function for a description of its input, output, and usage. To view the help documentation of any function, use the docstring
R package as docstring(fun = <function_name>)
. For instance:
#install.packages("docstring") # install docstring pkg
library(docstring) # load docstring pkg
# view the documentation associated with the function compute_ERC_and_DRP
docstring(fun = compute_ERC_and_DRP)
This project is licensed under the MIT licence - see the LICENSE file for details.
If you use this code in your research or find it helpful, please consider citing our paper: Bonifazi, R., Calus, M.P.L., ten Napel, J. et al. Integration of beef cattle international pedigree and genomic estimated breeding values into national evaluations, with an application to the Italian Limousin population. Genet Sel Evol 55, 41 (2023). https://doi.org/10.1186/s12711-023-00813-2
@article{Bonifazi2023,
title={Integration of beef cattle international pedigree and genomic estimated breeding values into national evaluations, with an application to the Italian Limousin population},
author={Bonifazi, R. and Calus, M.P.L. and ten Napel, J. and others},
journal={Genetics Selection Evolution},
year={2023},
volume={55},
pages={41},
doi={10.1186/s12711-023-00813-2}
}
For questions or support, please contact [email protected] or [email protected].
1: Figure from Bonifazi et al., 2023, GSE. See the publication for more details.