Package: MLSeq
Type: Package
Title: Machine Learning Interface for RNA-Seq Data
Version: 2.29.0
Date: 2021-08-14
Authors@R: c(person("Gokmen", "Zararsiz", role = c("aut", "cre"), email = "gokmenzararsiz@hotmail.com"),
  person("Dincer", "Goksuluk", role = "aut"),
  person("Selcuk", "Korkmaz", role = "aut"),
  person("Vahap", "Eldem", role = "aut"),
  person(c("Izzet", "Parug"), "Duru", role = "ctb"),
  person("Ahmet", "Ozturk", role = "aut"),
  person(c("Ahmet", "Ergun"), "Karaagaoglu", role = c("aut", "ths")))
Depends:
  caret,
  ggplot2
VignetteBuilder: knitr
Suggests:
  knitr,
  e1071,
  kernlab
Imports:
  testthat,
  VennDiagram,
  pamr,
  methods,
  DESeq2,
  edgeR,
  limma,
  Biobase,
  SummarizedExperiment,
  plyr,
  foreach,
  utils,
  sSeq,
  xtable
biocViews: ImmunoOncology, Sequencing, RNASeq, Classification, Clustering
Description: This package applies several machine learning methods, including SVM, bagSVM, Random Forest and CART to RNA-Seq data.
License: GPL(>=2)
NeedsCompilation: no
Encoding: UTF-8
RoxygenNote: 7.1.1
Collate: 
  'all_classes.R'
  'all_generics.R'
  'voomFunctions.R'
  'classify.R'
  'helper_functions.R'
  'predict.R'
  'methods.R'
  'onAttach.R'
  'package_and_suppl.R'
  'plda_nblda_functions.R'
git_url: https://git.bioconductor.org/packages/MLSeq
git_branch: devel
git_last_commit: b1aac87
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.23
