Package: STGS 0.1.0

STGS: Genomic Selection using Single Trait

Genomic Selection (GS) is a latest development in animal and plant breeding where whole genome markers information is used to predict genetic merit of an individuals in a practical breeding programme. GS is one of the promising tool for improving genetic gain in animal and plants in today’s scenario. This package is basically developed for genomic predictions by estimating marker effects. These marker effects further used for calculation of genotypic merit of individual i.e. genome estimated breeding values (GEBVs). Genomic selection may be based on single trait or multi traits information. This package performs genomic selection only for single traits hence named as STGS i.e. single trait genomic selection. STGS is a comprehensive package which gives single step solution for genomic selection based on most commonly used statistical methods.

Authors:Neeraj Budhlakoti, D C Mishra, Anil Rai, K K Chaturvedi

STGS_0.1.0.tar.gz
STGS_0.1.0.zip(r-4.5)STGS_0.1.0.zip(r-4.4)STGS_0.1.0.zip(r-4.3)
STGS_0.1.0.tgz(r-4.4-any)STGS_0.1.0.tgz(r-4.3-any)
STGS_0.1.0.tar.gz(r-4.5-noble)STGS_0.1.0.tar.gz(r-4.4-noble)
STGS_0.1.0.tgz(r-4.4-emscripten)STGS_0.1.0.tgz(r-4.3-emscripten)
STGS.pdf |STGS.html
STGS/json (API)

# Install 'STGS' in R:
install.packages('STGS', repos = c('https://budhlakotin.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • wheat_data - Genotyping and phenotypic dataset for wheat

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

6 exports 0.71 score 16 dependencies 2 mentions 8 scripts 139 downloads

Last updated 5 years agofrom:43ab7c2d99. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 21 2024
R-4.5-winOKAug 21 2024
R-4.5-linuxOKAug 21 2024
R-4.4-winOKAug 21 2024
R-4.4-macOKAug 21 2024
R-4.3-winOKAug 21 2024
R-4.3-macOKAug 21 2024

Exports:STGS.annSTGS.blupSTGS.lassoSTGS.rfSTGS.rrSTGS.svm

Dependencies:brnncodetoolsforeachFormulaglmnetiteratorskernlablatticeMatrixrandomForestRcppRcppEigenrrBLUPshapesurvivaltruncnorm