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Machine Learning Interface for RNA-Seq Data

Bioconductor version: Release (3.19)

This package applies several machine learning methods, including SVM, bagSVM, Random Forest and CART to RNA-Seq data.

Author: Gokmen Zararsiz [aut, cre], Dincer Goksuluk [aut], Selcuk Korkmaz [aut], Vahap Eldem [aut], Izzet Parug Duru [ctb], Ahmet Ozturk [aut], Ahmet Ergun Karaagaoglu [aut, ths]

Maintainer: Gokmen Zararsiz <gokmenzararsiz at>

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


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

if (!require("BiocManager", quietly = TRUE))


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


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

Beginner's guide to the "MLSeq" package PDF R Script
Reference Manual PDF


biocViews Classification, Clustering, ImmunoOncology, RNASeq, Sequencing, Software
Version 2.22.0
In Bioconductor since BioC 2.14 (R-3.1) (10 years)
License GPL(>=2)
Depends caret, ggplot2
Imports testthat, VennDiagram, pamr, methods, DESeq2, edgeR, limma, Biobase, SummarizedExperiment, plyr, foreach, utils, sSeq, xtable
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Suggests knitr, e1071, kernlab
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Follow Installation instructions to use this package in your R session.

Source Package MLSeq_2.22.0.tar.gz
Windows Binary (64-bit only)
macOS Binary (x86_64) MLSeq_2.22.0.tgz
macOS Binary (arm64) MLSeq_2.22.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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