GSbench: Benchmarking Genomic Selection and Machine-Learning Prediction
Models
A unified interface to fit, cross-validate and benchmark genomic
prediction models from SNP marker data. It implements genomic best linear
unbiased prediction (GBLUP) and ridge-regression BLUP in base R, and offers
a common interface to machine-learning predictors (elastic net, random
forest and gradient boosting) through optional packages, together with a
stacked ensemble. Cross-validation uses breeding-relevant schemes and
reports prediction accuracy honestly, so models can be compared fairly. The
genomic relationship matrix follows VanRaden (2008)
<doi:10.3168/jds.2007-0980>; the mixed-model solver follows Endelman (2011)
<doi:10.3835/plantgenome2011.08.0024>; the genomic-selection framework
follows Meuwissen, Hayes and Goddard (2001) <doi:10.1093/genetics/157.4.1819>.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
graphics, stats, withr |
| Suggests: |
rrBLUP, glmnet, ranger, xgboost, testthat (≥ 3.0.0), knitr, rmarkdown, spelling |
| Published: |
2026-06-30 |
| DOI: |
10.32614/CRAN.package.GSbench (may not be active yet) |
| Author: |
Muhammad Farooqi [aut, cre] |
| Maintainer: |
Muhammad Farooqi <mqfarooqi at gmail.com> |
| BugReports: |
https://github.com/mqfarooqi1/GSbench/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/mqfarooqi1/GSbench |
| NeedsCompilation: |
no |
| Language: |
en-GB |
| Materials: |
README, NEWS |
| CRAN checks: |
GSbench results |
Documentation:
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