Package: sigFeature
Type: Package
Title: sigFeature: Significant feature selection using 
       SVM-RFE & t-statistic
Version: 1.29.0
Date: 2021-11-21
Authors@R: c(person("Pijush Das", "Developer", role = c("aut", "cre"),
              email = "topijush@gmail.com"),
              person("Dr. Susanta Roychudhury", "User", role = "ctb"),
              person("Dr. Sucheta Tripathy", "User", role = "ctb",
              email = "tsucheta@iicb.res.in"))
Depends: R (>= 3.5.0)
Suggests: RUnit, BiocGenerics, knitr, rmarkdown 
Description: 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.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: TRUE
biocViews: FeatureExtraction, GeneExpression, Microarray, Transcription, mRNAMicroarray, 
           GenePrediction, Normalization, Classification, SupportVectorMachine
Imports: biocViews, nlme, e1071, openxlsx, pheatmap, RColorBrewer, Matrix, SparseM, 
         graphics, stats, utils, SummarizedExperiment, BiocParallel, methods
VignetteBuilder: knitr
git_url: https://git.bioconductor.org/packages/sigFeature
git_branch: devel
git_last_commit: 0877319
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.23
