# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "lme4GS" in publications use:' type: software license: GPL-2.0-or-later title: 'lme4GS: ''lme4'' for Genomic Selection' version: '0.1' doi: 10.32614/CRAN.package.lme4GS abstract: Flexible functions that use 'lme4' as computational engine for fitting models used in Genomic Selection (GS). GS is a technology used for genetic improvement, and it has many advantages over phenotype-based selection. There are several statistical models that adequately approach the statistical challenges in GS, such as in linear mixed models (LMMs). The 'lme4' is the standard package for fitting linear and generalized LMMs in the R-package, but its use for genetic analysis is limited because it does not allow the correlation between individuals or groups of individuals to be defined. The 'lme4GS' package is focused on fitting LMMs with covariance structures defined by the user, bandwidth selection, and genomic prediction. The new package is focused on genomic prediction of the models used in GS and can fit LMMs using different variance-covariance matrices. Several examples of GS models are presented using this package as well as the analysis using real data. For more details see Caamal-Pat et.al. (2021) . authors: - family-names: Caamal Pat given-names: Diana Yanira email: diana.caamal@colpos.mx - family-names: Perez Rodriguez given-names: Paulino email: perpdgo@colpos.mx repository: https://cran.r-universe.dev commit: 9affd0a7a796d81018c85c15e310969d9d1b898a date-released: '2025-04-06' contact: - family-names: Perez Rodriguez given-names: Paulino email: perpdgo@colpos.mx