Package: opticskxi Title: OPTICS K-Xi Density-Based Clustering Version: 1.2.1 Authors@R: person("Thomas", "Charlon", role = c("aut", "cre"), email = "charlon@protonmail.com", comment = c(ORCID = "0000-0001-7497-0470")) Description: Density-based clustering methods are well adapted to the clustering of high-dimensional data and enable the discovery of core groups of various shapes despite large amounts of noise. This package provides a novel density-based cluster extraction method, OPTICS k-Xi, and a framework to compare k-Xi models using distance-based metrics to investigate datasets with unknown number of clusters. The vignette first introduces density-based algorithms with simulated datasets, then presents and evaluates the k-Xi cluster extraction method. Finally, the models comparison framework is described and experimented on 2 genetic datasets to identify groups and their discriminating features. The k-Xi algorithm is a novel OPTICS cluster extraction method that specifies directly the number of clusters and does not require fine-tuning of the steepness parameter as the OPTICS Xi method. Combined with a framework that compares models with varying parameters, the OPTICS k-Xi method can identify groups in noisy datasets with unknown number of clusters. Results on summarized genetic data of 1,200 patients are in Charlon T. (2019) . A short video tutorial can be found at . Imports: ggplot2, magrittr, Matrix, rlang Depends: R (>= 3.5.0) Suggests: amap, dbscan, cowplot, fastICA, fpc, ggrepel, grid, grDevices, gtable, knitr, parallel, plyr, reshape2, testthat VignetteBuilder: knitr License: GPL-3 Encoding: UTF-8 RoxygenNote: 7.3.2 URL: https://gitlab.com/thomaschln/opticskxi BugReports: https://gitlab.com/thomaschln/opticskxi/-/issues Repository: https://thomaschln.r-universe.dev Date/Publication: 2026-06-10 12:31:26 UTC RemoteUrl: https://gitlab.com/thomaschln/opticskxi RemoteRef: HEAD RemoteSha: e8e7e08ed6af6c9b1261593dba0af4dda976cd37 NeedsCompilation: no Packaged: 2026-06-10 15:26:07 UTC; root Author: Thomas Charlon [aut, cre] (ORCID: ) Maintainer: Thomas Charlon