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

This package is for version 3.0 of Bioconductor; for the stable, up-to-date release version, see MLSeq.

Machine learning interface for RNA-Seq data

Bioconductor version: 3.0

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 erciyes.edu.tr>

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

To install this package, start R and enter:

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

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

browseVignettes("MLSeq")

biocViews	Classification, Clustering, Software
Version	1.2.0
In Bioconductor since	BioC 2.14 (R-3.1) (2 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

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

Package Source	MLSeq_1.2.0.tar.gz
Windows Binary	MLSeq_1.2.0.zip
Mac OS X 10.6 (Snow Leopard)	MLSeq_1.2.0.tgz
Mac OS X 10.9 (Mavericks)	MLSeq_1.2.0.tgz
Subversion source	(username/password: readonly)
Git source	https://github.com/Bioconductor-mirror/MLSeq/tree/release-3.0
Package Short Url	http://bioconductor.org/packages/MLSeq/
Package Downloads Report	Download Stats

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