To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("MLSeq")

In most cases, you don't need to download the package archive at all.

MLSeq

DOI: 10.18129/B9.bioc.MLSeq    

Machine learning interface for RNA-Seq data

Bioconductor version: Release (3.5)

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

Author: Gokmen Zararsiz, Dincer Goksuluk, Selcuk Korkmaz, Vahap Eldem, Izzet Parug Duru, Turgay Unver, Ahmet Ozturk

Maintainer: Gokmen Zararsiz <gokmenzararsiz at hotmail.com>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("MLSeq")

Documentation

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

browseVignettes("MLSeq")

 

PDF R Script MLSeq
PDF   Reference Manual
Text   README

Details

biocViews Classification, Clustering, RNASeq, Sequencing, Software
Version 1.16.0
In Bioconductor since BioC 2.14 (R-3.1) (3.5 years)
License GPL(>=2)
Depends R (>= 3.0.0), caret, DESeq2, Biobase, limma, randomForest, edgeR
Imports methods
LinkingTo
Suggests knitr, e1071, kernlab, earth, ellipse, fastICA, gam, ipred, klaR, MASS, mda, mgcv, mlbench, nnet, party, pls, pROC, proxy, RANN, spls, affy
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Source Package MLSeq_1.16.0.tar.gz
Windows Binary MLSeq_1.16.0.zip
Mac OS X 10.11 (El Capitan) MLSeq_1.16.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/MLSeq
Package Short Url http://bioconductor.org/packages/MLSeq/
Package Downloads Report Download Stats

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