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GSbench

0.1.0Package record

Benchmarking Genomic Selection and Machine-Learning Prediction Models

0packages depend
901downloads / year
75.4%test coverage
13/13flavors OK

Overview

About

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.

Changes in 0.1.0

First release.

  • Core (base R): simulate_population(), qc_markers(), impute_markers(), Gmatrix() (VanRaden), and gblup() (GBLUP by REML, validated against rrBLUP::mixed.solve).
  • Unified modelling interface gs_fit() / predict() covering GBLUP, elastic net (glmnet), random forest (ranger) and gradient boosting (xgboost).
  • gs_cv() for breeding-relevant cross-validation (random k-fold and leave-one-group-out).
  • gs_ensemble(), a stacked super-learner combining base models with non-negative, out-of-fold-fitted weights.
  • gs_benchmark() with print/summary/plot to compare all available models under one cross-validation.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 2.8 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK7 OK2026-07-01
Advisories

none known

Documentation

In release 0.1.0
READMEYes · 505 wordsVignettesYes · 1 · evaluation depends on the environmentNEWSYes · 67% structured · mentions 0.1.0Citation fileNo
Help pages
15 (1 internal)includes a package overview page
Examples that run
100%14 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
20%

Downloads

901
CRAN downloads in the past year
Rank #18,899 · ~2/day · ~75/mo
Daily download trend is not available in this view yet.
26730 days
68990 days
9011 year
Compare downloads with other packages →
Also on20 r2u2 autocran

Repository

0Stars
0Forks
0Open issues
0Open PRs
0Releases
Last activity 2026-07-27 · Default branch at 0.1.0.9000, ahead of CRAN 0.1.0 (checked 2026-10-18)
Responsiveness
not measured
PracticesBeta

7 development-tooling and community-health practices detected across 5 families in the upstream repository

Checks run against github.com/mqfarooqi1/gsbench on 2026-10-18.

Continuous integration (1)
GitHub Actions
Docs source (3)
pkgdown

GitHub Pages site last deployed 2026-07-27 · The repository has a site deploy workflow

Reproducibility and dev environment (1)
Dockerfile
CRAN release process (1)
cran-comments.md
Show all practicesHide 1 practice
Research and citation (1)
CITATION.cff
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
9 external dependencies (excludes base and recommended)

Installing GSbench adds 1 package (0 with compiled code, 102 KB of source tarballs). Heaviest: withr 102 KB.

Depends (1)
R >= 4.1.0
Imports (3)
graphicsstatswithr
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (1)
Author, Maintainer since 0.1.0 (2026)
Releases (1)
  • 0.1.0Latest
    2026-06-30 · current release
  • R
    R 4.6.0 released · 2026-04-24

Package metadata

First published
2026-06-30
Total releases
1 / 1 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 4.1.0
Download size
33 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("GSbench")
Farooqi, M. (2026). GSbench: Benchmarking Genomic Selection and Machine-Learning Prediction Models (Version 0.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.GSbench

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

The repository also keeps a CITATION.cff.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for GSbench version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-10-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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