To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("MLSeq")

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

MLSeq

Machine learning interface for RNA-Seq data

Bioconductor version: Release (2.14)

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")):

Installation

To install this package, start R and enter:

source("http://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 Bioinformatics, Classification, Clustering, Software
Version 1.0.0
In Bioconductor since BioC 2.14 (R-3.1)
License GPL(>=2)
Depends R (>= 3.0.0), caret, DESeq2, Biobase, limma, randomForest, edgeR
Imports methods
Suggests knitr, e1071, kernlab, earth, ellipse, fastICA, gam, ipred, klaR, MASS, mda, mgcv, mlbench, nnet, party, pls, pROC, proxy, RANN, spls, affy
System Requirements
URL
Depends On Me
Imports Me
Suggests Me

Package Archives

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

Package Source MLSeq_1.0.0.tar.gz
Windows Binary MLSeq_1.0.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) MLSeq_1.0.0.tgz
Mac OS X 10.9 (Mavericks) MLSeq_1.0.0.tgz
Browse/checkout source (username/password: readonly)
Package Downloads Report Download Stats

Mailing Lists »

Post questions about Bioconductor packages to our mailing lists. Read the posting guide before posting!

Fred Hutchinson Cancer Research Center