Positive and Unlabeled Learning from Unbalanced Cases and Sparse Structures R package xplus version 1.0.2 Provides PLUS-derived extensions for positive and unlabeled (PU) learning from unbalanced cases and sparse structures, based on Zhou et al. (2022) <doi:10.1371/journal.pcbi.1009956>. Iteratively relabels unlabeled observations via penalised logistic regression and pseudo-label updates, then refits a final sparse model. Includes weighted bootstrap sampling, convergence diagnostics, prediction, coefficient extraction, and assessment utilities. Software Depends: R (>= 4.1.0) Imports: glmnet (>= 4.1-8), Matrix, methods, stats, tibble, utils Suggests: covr, knitr, rmarkdown, survival, testthat (>= 3.0.0) Angel Robles <a.l.robles.fernandez@gmail.com> Comprehensive R Archive Network (CRAN) Angel Robles [aut, cre] (ORCID: <https://orcid.org/0000-0002-4674-4270>) GPL (>= 3) 2026-09-26 application/tgz https://CRAN.R-project.org/package=xplus doi:10.32614/CRAN.package.xplus