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This is the development version of MLSeq; for the stable release version, see MLSeq.

Machine Learning Interface for RNA-Seq Data

Bioconductor version: Development (3.20)

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))

# The following initializes usage of Bioc devel


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 2.23.0
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
System Requirements
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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_2.23.0.tar.gz
Windows Binary
macOS Binary (x86_64) MLSeq_2.23.0.tgz
macOS Binary (arm64) MLSeq_2.23.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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