- recipe bioconductor-classifyr
A framework for cross-validated classification problems, with applications to differential variability and differential distribution testing
- Homepage:
https://bioconductor.org/packages/3.18/bioc/html/ClassifyR.html
- License:
GPL-3
- Recipe:
- Links:
biotools: classifyr
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.
- package bioconductor-classifyr¶
- versions:
3.6.2-0,3.4.7-1,3.4.7-0,3.2.0-1,3.2.0-0,2.14.0-0,2.12.0-0,2.10.0-1,2.10.0-0,3.6.2-0,3.4.7-1,3.4.7-0,3.2.0-1,3.2.0-0,2.14.0-0,2.12.0-0,2.10.0-1,2.10.0-0,2.8.0-0,2.6.0-0,2.4.4-0,2.2.6-0,2.2.4-0,2.0.10-0,1.12.2-0- depends bioconductor-biocparallel:
>=1.36.0,<1.37.0- depends bioconductor-biocparallel:
>=1.36.0,<1.37.0a0- depends bioconductor-genefilter:
>=1.84.0,<1.85.0- depends bioconductor-genefilter:
>=1.84.0,<1.85.0a0- depends bioconductor-multiassayexperiment:
>=1.28.0,<1.29.0- depends bioconductor-multiassayexperiment:
>=1.28.0,<1.29.0a0- depends bioconductor-s4vectors:
>=0.40.0,<0.41.0- depends bioconductor-s4vectors:
>=0.40.2,<0.41.0a0- depends libblas:
>=3.9.0,<4.0a0- depends libgcc-ng:
>=12- depends liblapack:
>=3.9.0,<4.0a0- depends libstdcxx-ng:
>=12- depends r-base:
>=4.3,<4.4.0a0- depends r-dplyr:
- depends r-generics:
- depends r-ggplot2:
>=3.0.0- depends r-ggpubr:
- depends r-ggupset:
- depends r-ranger:
- depends r-reshape2:
- depends r-rlang:
- depends r-survival:
- depends r-tidyr:
- requirements:
Installation
You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).
While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.
Given that you already have a conda environment in which you want to have this package, install with:
mamba install bioconductor-classifyr and update with:: mamba update bioconductor-classifyr
To create a new environment, run:
mamba create --name myenvname bioconductor-classifyr
with
myenvnamebeing a reasonable name for the environment (see e.g. the mamba docs for details and further options).Alternatively, use the docker container:
docker pull quay.io/biocontainers/bioconductor-classifyr:<tag> (see `bioconductor-classifyr/tags`_ for valid values for ``<tag>``)
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-classifyr/README.html)
