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MLSeq

Machine Learning Interface for RNA-Seq Data

Bioconductor version: Release (3.17)

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 "4.3") 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 2.18.0
In Bioconductor since BioC 2.14 (R-3.1) (9.5 years)
License GPL(>=2)
Depends caret, ggplot2
Imports testthat, VennDiagram, pamr, methods, DESeq2, edgeR, limma, Biobase, SummarizedExperiment, plyr, foreach, utils, sSeq, xtable
Linking To
Suggests knitr, e1071, kernlab
System Requirements
Enhances
URL
See More
Depends On Me
Imports Me GARS
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package MLSeq_2.18.0.tar.gz
Windows Binary MLSeq_2.18.0.zip
macOS Binary (x86_64) MLSeq_2.18.0.tgz
macOS Binary (arm64) MLSeq_2.18.0.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