MLSeq

Machine Learning Interface for RNA-Seq Data


Bioconductor version: Release (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 hotmail.com>

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

Installation

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


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

BiocManager::install("MLSeq")

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("MLSeq")
Beginner's guide to the "MLSeq" package PDF R Script
Reference Manual PDF
NEWS Text

Details

biocViews Classification, Clustering, ImmunoOncology, RNASeq, Sequencing, Software
Version 2.24.0
In Bioconductor since BioC 2.14 (R-3.1) (10.5 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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Build Report Build Report

Package Archives

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

Source Package MLSeq_2.24.0.tar.gz
Windows Binary (x86_64) MLSeq_2.24.0.zip (64-bit only)
macOS Binary (x86_64) MLSeq_2.24.0.tgz
macOS Binary (arm64) MLSeq_2.24.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/MLSeq
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/MLSeq
Bioc Package Browser https://code.bioconductor.org/browse/MLSeq/
Package Short Url https://bioconductor.org/packages/MLSeq/
Package Downloads Report Download Stats