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CAEN

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


Bioconductor version: Development (3.19)

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.

Author: Zhou Yan [aut, cre]

Maintainer: Zhou Yan <2160090406 at email.szu.edu.cn>

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

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("CAEN")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Reference Manual PDF

Details

biocViews ATACSeq, Classification, DifferentialExpression, GeneExpression, RIPSeq, RNASeq, Sequencing, SingleCell, Software
Version 1.11.0
In Bioconductor since BioC 3.13 (R-4.1) (3 years)
License GPL-2
Depends R (>= 4.1)
Imports stats, PoiClaClu, SummarizedExperiment, methods
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