Dependent Gaussian Processes for Longitudinal Correlated Factors R package DGP4LCF version 1.0.0.1 Functionalities for analyzing high-dimensional and longitudinal biomarker data to facilitate precision medicine, using a joint model of Bayesian sparse factor analysis and dependent Gaussian processes. This paper illustrates the method in detail: J Cai, RJB Goudie, C Starr, BDM Tom (2023) <doi:10.48550/arXiv.2307.02781>. Software Depends: R (>= 2.10) Imports: GPFDA, Rcpp, factor.switching, mvtnorm, combinat, coda, corrplot, pheatmap, stats LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Jiachen Cai <jiachen.cai@mrc-bsu.cam.ac.uk> Comprehensive R Archive Network (CRAN) Jiachen Cai [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=DGP4LCF/LICENSE) 2025-03-08 application/tgz https://CRAN.R-project.org/package=DGP4LCF doi:10.32614/CRAN.package.DGP4LCF