Package: SFSI 1.4.1
Marco Lopez-Cruz
SFSI: Sparse Family and Selection Index
Here we provide tools for the estimation of coefficients in penalized regressions when the (co)variance matrix of predictors and the covariance vector between predictors and response, are provided. These methods are extended to the context of a Selection Index (commonly used for breeding value prediction). The approaches offer opportunities such as the integration of high-throughput traits in genetic evaluations ('Lopez-Cruz et al., 2020') <doi:10.1038/s41598-020-65011-2> and solutions for training set optimization in Genomic Prediction ('Lopez-Cruz & de los Campos, 2021') <doi:10.1093/genetics/iyab030>.
Authors:
SFSI_1.4.1.tar.gz
SFSI_1.4.1.tar.gz(r-4.5-noble)SFSI_1.4.1.tar.gz(r-4.4-noble)
SFSI_1.4.1.tgz(r-4.4-emscripten)SFSI_1.4.1.tgz(r-4.3-emscripten)
SFSI.pdf |SFSI.html✨
SFSI/json (API)
NEWS
# Install 'SFSI' in R: |
install.packages('SFSI', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/marcoolopez/sfsi/issues
Last updated 4 months agofrom:d36d57c6dd. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 22 2024 |
R-4.5-linux-x86_64 | OK | Dec 22 2024 |
Exports:cov2cor2cov2distfitBLUPget_foldsgetGenCovLARSmultitrait.plotnetpath.plotPruneread_SGPread_summaryreadBinarysaveBinarySGPSGP.CVsolveEN
Dependencies:clicolorspacecpp11fansifarverggplot2gluegridExtragtableigraphisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppreshape2rlangscalesstringistringrtensorEVDtibbleutf8vctrsviridisviridisLitewithr
Documentation: Optimal breeding value prediction using a Sparse Selection Index
Rendered fromSGP-documentation.Rmd
usingknitr::rmarkdown
on Dec 22 2024.Last update: 2024-06-26
Started: 2024-06-26
Documentation: Regularized selection indices for breeding value prediction using hyper-spectral image data
Rendered fromSSI-documentation.Rmd
usingknitr::rmarkdown
on Dec 22 2024.Last update: 2024-06-26
Started: 2021-05-03
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Save/read binary files | readBinary saveBinary |
Conversion of a covariance matrix to a distance/correlation matrix | cov2cor2 cov2dist |
Coordinate Descent algorithm to solve Elastic-Net-type problems | solveEN |
Least Angle Regression to solve LASSO-type problems | LARS |
Sparse Genomic Prediction | SGP SGP.CV |
Fitting a Linear Mixed model to calculate BLUP | fitBLUP |
Pairwise Genetic Covariance | getGenCov |
Accuracy vs penalization plot | plot.SGP |
Data partition into folds of the same size | get_folds |
Graphical Network | net |
Plotting a network | plot.net |
Accuracy vs penalization from multi-trait SGP | multitrait.plot |
R-squared pruning | Prune |
Read and combine SGP outputs | read_SGP read_summary |
LASSO methods | coef.LASSO predict.LASSO |
Coefficients path plot | path.plot |
SGP methods | coef.SGP predict.SGP summary.SGP |
Wheat dataset | genCOV_xy genCOV_yy M resCOV_yy VI_E1 wheatHTP X_E1 Y |