Package: CAEN 1.19.0

Zhou Yan

CAEN: Category encoding method for selecting feature genes for the classification of single-cell RNA-seq

With the development of high-throughput techniques, more and more gene expression analysis tend to replace hybridization-based microarrays with the revolutionary technology.The novel method encodes the category again by employing the rank of samples for each gene in each class. We then consider the correlation coefficient of gene and class with rank of sample and new rank of category. The highest correlation coefficient genes are considered as the feature genes which are most effective to classify the samples.

Authors:Zhou Yan [aut, cre]

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CAEN.pdf |CAEN.html
CAEN/json (API)
NEWS

# Install 'CAEN' in R:
install.packages('CAEN', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • realData - A real dataset of gene expression RNA-seq.

On BioConductor:CAEN-1.19.0(bioc 3.23)CAEN-1.18.0(bioc 3.22)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

differentialexpressionsequencingclassificationrnaseqatacseqsinglecellgeneexpressionripseq

4.60 score 2 scripts 296 downloads 4 mentions 5 exports 18 dependencies

Last updated from:af0f850aa3. Checks:7 NOTE, 2 OK. Indexed: yes.

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bioc-checksNOTE168
linux-devel-x86_64NOTE226
source / vignettesOK274
linux-release-x86_64NOTE264
macos-devel-arm64NOTE125
macos-release-arm64NOTE150
windows-develNOTE193
windows-releaseNOTE171
wasm-releaseOK116

Exports:CAENestimatepnewCountDataSetZIPLDAZIPLDA.cv

Dependencies:abindBiobaseBiocGenericsDelayedArraygenericsGenomicRangesIRangeslatticeMatrixMatrixGenericsmatrixStatsPoiClaCluS4ArraysS4VectorsSeqinfoSparseArraySummarizedExperimentXVector

CAEN Tutorial

Rendered fromCAEN.Rmdusingknitr::rmarkdownon Mar 23 2026.

Last update: 2023-04-12
Started: 2020-03-14