In the framework of the Trees4Future project, we are developing breedR: an R-package with statistical methods for forest genetic resources analysts.

1. Development of an statistical package for
genetic evaluation of trees
Facundo Muñoz
Unité de Recherche Amélioration, Génétique et Physiologie Forestières
Dec. 2013
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2. Context: WP6 and the Trees4Future project
T4F: Designing Trees for the Future
(Coordinator: Luc Paques)
WP6: Integrated statistical platform for analysing forest genetic
resources
(Leader: Leopoldo Sanchez)
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3. WP6 objectives
Make available a ready-to-use software suite of key statistical
tools for monitoring and evaluating forest genetic resources
Be realistic at the task by avoiding exhaustiveness and building
from-scratch alternatives, while focusing in users needs
Make the suite open and publicly available, for maximum flexibility
and evolvability
Foster interchange in statistical issues in forest data analyses
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4. Why
Existing tools and methodologies scattered through several
software (dyogene, Treeplan, AS-REML, gs3...)
It is not always possible to combine different tools to work together
in one analysis
Some of theme are expensive
Others are available only as Fortran libraries that are difficult to use
Most are closed applications that cannot be adapted to specific
needs
We will put together the most essential and some novel analytical tools
that are relevant to the community of forest genetics and breeding
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5. What
BreedR: A software suit of key statistical tools
Based on very efficient Mixed-Models solvers (both frequentist and
Bayesian)
Additional modules will integrate specific effects for common
scenarios
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6. How
Implemented as an R-package at
https://github.com/famuvie/breedR
Free and Open Source Software (FOSS) with GPL-3 License
This allows for sustainability of the development
The code can be modified, updated, improved and enhanced by
anyone, now or in the future
Institutions can benefit from it for free
A group of external experts will contribute their knowledge (and/or
code) on specific fields
A community of beta-testers will compile a collection of datasets
with varying characteristics and analyse them using the software
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7. GitHub repository
https://github.com/famuvie/breedR
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8. When
Version 0.1-0 available with basic functionality
Progeny/family, provenance, or more complex pedigree trials
Fixed and random effects (e.g. blocks)
The Spatial module is under active development
Eduardo Cappa was the first contributing expert on this module
We have already a working prototype
Will be usable in the next few weeks
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9. breedR demo
Run it yourself!
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