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sigFeature

This is the released version of sigFeature; for the devel version, see sigFeature.

All versions 3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11, 3.10, 3.9, 3.8

sigFeature: Significant feature selection using SVM-RFE & t-statistic


Bioconductor version: Release (3.23)

This package provides a novel feature selection algorithm for binary classification using support vector machine recursive feature elimination SVM-RFE and t-statistic. In this feature selection process, the selected features are differentially significant between the two classes and also they are good classifier with higher degree of classification accuracy.

Author: Pijush Das Developer [aut, cre], Dr. Susanta Roychudhury User [ctb], Dr. Sucheta Tripathy User [ctb]

Maintainer: Pijush Das Developer <topijush at gmail.com>

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

Pijush Das Developer. sigFeature: sigFeature: Significant feature selection using SVM-RFE & t-statistic. doi:10.18129/B9.bioc.sigFeature, R package version 1.30.0, https://bioconductor.org/packages/sigFeature.

Generated from the package metadata; it may differ from the package's own citation.

Installation

To install this package, start R (version "4.6") and enter:

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

BiocManager::install("sigFeature")

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

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("sigFeature")
sigFeature HTML R Script
Reference ManualPDF
NEWSText

Details

biocViews Classification, FeatureExtraction, GeneExpression, GenePrediction, Microarray, Normalization, Software, SupportVectorMachine, Transcription, mRNAMicroarray
Version1.30.0
In Bioconductor sinceBioC 3.8 (R-3.5) (8 years)
License GPL (>= 2)
Depends R (>= 3.5.0)
Imports biocViews, nlme, e1071, openxlsx, pheatmap, RColorBrewer, Matrix, SparseM, graphics, stats, utils, SummarizedExperiment, BiocParallel, methods
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Suggests RUnit, BiocGenerics, knitr, rmarkdown
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package sigFeature_1.30.0.tar.gz
Windows Binary (x86_64) sigFeature_1.30.0.zip
macOS Binary (big-sur-x86_64) sigFeature_1.30.0.tgz
macOS Binary (sonoma-arm64) sigFeature_1.30.0.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/sigFeature
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/sigFeature
Package Short Url https://bioconductor.org/packages/sigFeature/
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