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This is the development version of ClassifyR; for the stable release version, see ClassifyR.

A framework for cross-validated classification problems, with applications to differential variability and differential distribution testing

Bioconductor version: Development (3.19)

The software formalises a framework for classification and survival model evaluation in R. There are four stages; Data transformation, feature selection, model training, and prediction. The requirements of variable types and variable order are fixed, but specialised variables for functions can also be provided. The framework is wrapped in a driver loop that reproducibly carries out a number of cross-validation schemes. Functions for differential mean, differential variability, and differential distribution are included. Additional functions may be developed by the user, by creating an interface to the framework.

Author: Dario Strbenac [aut, cre], Ellis Patrick [aut], Sourish Iyengar [aut], Harry Robertson [aut], Andy Tran [aut], John Ormerod [aut], Graham Mann [aut], Jean Yang [aut]

Maintainer: Dario Strbenac <dario.strbenac at>

Citation (from within R, enter citation("ClassifyR")):


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Reference Manual PDF


biocViews Classification, Software, Survival
Version 3.7.5
In Bioconductor since BioC 3.0 (R-3.1) (9.5 years)
License GPL-3
Depends R (>= 4.1.0), generics, methods, S4Vectors, MultiAssayExperiment, BiocParallel, survival
Imports grid, genefilter, utils, dplyr, tidyr, rlang, ranger, ggplot2 (>= 3.0.0), ggpubr, reshape2, ggupset
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Suggests limma, edgeR, car, Rmixmod, gridExtra (>= 2.0.0), cowplot, BiocStyle, pamr, PoiClaClu, parathyroidSE, knitr, htmltools, gtable, scales, e1071, rmarkdown, IRanges, robustbase, glmnet, class, randomForestSRC, MatrixModels, xgboost, data.tree, ggnewscale
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