https://ianoverton.r-universe.devRecent package updates in ianovertonR-universehttps://github.com/ianoverton.pnghttps://ianoverton.r-universe.devTue, 22 Sep 2026 21:27:38 GMTi.overton@qub.ac.uk (Ian Overton)A tool for the preparation and enrichment of health datasets for analysis (Toner et al. (2023) <doi:10.1093/gigascience/giad030>). Provides functionality for assessing data quality and for improving the reliability and machine interpretability of a dataset. 'eHDPrep' also enables semantic enrichment of a dataset where metavariables are discovered from the relationships between input variables determined from user-provided ontologies.https://github.com/r-universe/overton-group/actions/runs/35795751227Tue, 22 Sep 2026 21:27:38 GMTeHDPrep2.0.1successhttps://overton-group.r-universe.devhttps://github.com/overton-group/ehdprepIntroduction_to_eHDPrep.RmdIntroduction_to_eHDPrep.html'eHDPrep': an 'R' package for Electronic Health Data Quality Control and Semantic Enrichment2022-07-26 10:54:442026-09-22 21:22:37i.overton@qub.ac.uk (Ian Overton)Predicts gene dependency relationships (GDRs) from functional genomics data. Regularised Gaussian mixture modelling may be applied for unsupervised clustering in addition to other data partitioning strategies. GDR analysis tools include discovery of synthetic lethal relationships and predicting population coverage for candidate drug targets from cancer patient mutational profiles. Functionality for visualisation is also available. 'MultiSEp' is applicable to data from a variety of sources including clinical cohorts, organoids and cell lines.https://github.com/r-universe/ianoverton/actions/runs/36233876592Thu, 27 Aug 2026 10:30:02 GMTMultiSEp4.1.3successhttps://ianoverton.r-universe.devhttps://github.com/cran/MultiSEpMultiSEpVignette.RmdMultiSEpVignette.htmlMultiSEp: Predicting Gene Dependency Relationships (GDRs) from Multiomics Data2026-08-27 10:30:022026-08-27 10:30:02