Package: RegParallel Type: Package Title: Standard regression functions in R enabled for parallel processing over large data-frames Version: 1.31.0 Authors@R: c( person("Kevin", "Blighe", role = c("aut", "cre"), email = "kevin@clinicalbioinformatics.co.uk"), person("Sarega", "Gurudas", role = c("ctb")), person("Jessica", "Lasky-Su", role = c("aut"))) Maintainer: Kevin Blighe Description: In many analyses, a large amount of variables have to be tested independently against the trait/endpoint of interest, and also adjusted for covariates and confounding factors at the same time. The major bottleneck in these is the amount of time that it takes to complete these analyses. With RegParallel, a large number of tests can be performed simultaneously. On a 12-core system, 144 variables can be tested simultaneously, with 1000s of variables processed in a matter of seconds via 'nested' parallel processing. Works for logistic regression, linear regression, conditional logistic regression, Cox proportional hazards and survival models, and Bayesian logistic regression. Also caters for generalised linear models that utilise survey weights created by the 'survey' CRAN package and that utilise 'survey::svyglm'. License: GPL-3 Depends: doParallel, foreach, parallel, iterators, data.table, stringr, survival, arm, stats, utils, methods Imports: Suggests: RUnit, BiocGenerics, knitr, DESeq2, airway, magrittr, Biobase, GEOquery, biomaRt, survminer, survey, rmarkdown URL: https://github.com/kevinblighe/RegParallel biocViews: DiseaseModel VignetteBuilder: knitr Config/pak/sysreqs: cmake make libicu-dev Repository: https://bioc.r-universe.dev Date/Publication: 2026-04-28 12:32:16 UTC RemoteUrl: https://github.com/bioc/RegParallel RemoteRef: HEAD RemoteSha: 9402c751a8ec7bd07cf14fe8311b0bfcb3aa3689 NeedsCompilation: no Packaged: 2026-10-10 10:39:50 UTC; root Author: Kevin Blighe [aut, cre], Sarega Gurudas [ctb], Jessica Lasky-Su [aut]