The goal of the labradoR R package is to facilitate the handling and post-processing in R of the output from Retriever software.

Retriever is a software for retrieving information on population structure, inbreeding, and kinship from pedigrees analysis generating many statistics and plots. For more information on Retriever please refer to the official software website and it associated publication.

labradoR help users to import the output generated by Retriever into R for further manipulation and downstream analyses. labradoR loads the main tabular information into data.frames and generates associated ggplot2 plots objects similar to those of Retriever.

You can install the development version of labradoR from GitHub with:

# install.packages("devtools")
devtools::install_github("bonifazi/labradoR")

The below is a basic example showing the package usage. As input, you need to provide the path to the .out file generated by Retriever. Note that the .out file can be in English or in Dutch (depending on the settings used when running Retriever). Both languages are supported: set the needed language using the language argument (ENG for English and DUT for Dutch).

## example usage
library(labradoR)

output <- process_retriever(
  file_name = "C:/myPath/pedigree_Retriever.out",
  language = "ENG"
  )

str(output, max.levels = 1, give.attr = F)

The output is a list with data.frames and associated ggplot2 plots.

Use the argument xinterval to show plots on a specific interval of years.

Use the argument delta_intervals to return rates of inbreeding and kinship between provided years.

For example:

output <- process_retriever(
    file_name = "C:/myPath/pedigree_Retriever.out",
    xinterval = c(1990, 2020),
    delta_intervals = c(1990, 2000, 2010, 2014, 2020),
    language = "ENG"
  )

Note: sub-populations are not supported yet.

Note: since the logic of labradoR is that of “fetching” lines from Retriever’s output, if anything changes in the format of the .out file, then labradoR’s associated code will need to be adapted accordingly.

The current labradoR version 1.1.0 has been tested and used for the output of Retriver version compiled on 08-02-2025.
Older versions are compatible with older Retriever output, and are kept for legacy. You can install an older version of labradoR using, for example:

# install.packages("devtools")
devtools::install_github("bonifazi/[email protected]")

Legacy list:

• labradoR version 1.0.0 has been tested and used with Retriever v7.

You can find an example of the output generated by labradoR here.
Note that this report is just to show the main outputs of the package. Here Retriever was run on a sheep pedigree simulated using MoBPS (code here ). Real pedigrees will likely show much more uneven distributions.

If you use the labradoR package, please cite it as follows:

Citing the Associated Paper and Software

For now, you can refer to the associated preprint, and R package, using:

citation("labradoR")
#> To cite labradoR in publications, please use the following:
#> 
#>   Bonifazi R, Meuwissen THE, Croiseau P, Restoux G, Minéry S, Windig JJ
#>   (2025).  'Impact of genomic selection on genetic diversity in five
#>   local European cattle breeds.' bioRxiv.
#>   doi:10.1101/2025.09.08.674844.
#> 
#>   Bonifazi R (2025). labradoR: An R package for handling and
#>   post-processing Retriever output. Version 1.1.7. Available at
#>   https://github.com/bonifazi/labradoR.
#> 
#> To see these entries in BibTeX format, use 'print(<citation>,
#> bibtex=TRUE)', 'toBibtex(.)', or set
#> 'options(citation.bibtex.max=999)'.

You are welcome to contribute to the development of labradoR.

• Feature Requests: If you have a new feature in mind or a suggestion for improvement, please open a GitHub issue to discuss it.

• Bug Reports: If you encounter any bugs or issues while using labradoR, please submit a bug report with detailed information about the problem.

• Pull Requests: feel free to fork the repository, make your changes, and submit a pull request.

Check out the NEWS file for the latest updates and changes to the package.

• Jack J. Windig for helping with the interpretation of the Retriever’s output.

• Julia Höglund for helping editing with labradoR logo.

• Torsten Pook for helping with the MoBPS simulations.