To install this package, start R and enter:

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

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

LedPred

   

This package is for version 3.2 of Bioconductor; for the stable, up-to-date release version, see LedPred.

Learning from DNA to Predict enhancers

Bioconductor version: 3.2

This package aims at creating a predictive model of regulatory sequences used to score unknown sequences based on the content of DNA motifs, next-generation sequencing (NGS) peaks and signals and other numerical scores of the sequences using supervised classification. The package contains a workflow based on the support vector machine (SVM) algorithm that maps features to sequences, optimize SVM parameters and feature number and creates a model that can be stored and used to score the regulatory potential of unknown sequences.

Author: Elodie Darbo, Denis Seyres, Aitor Gonzalez

Maintainer: Aitor Gonzalez <aitor.gonzalez at univ-amu.fr>

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

Installation

To install this package, start R and enter:

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

Documentation

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

browseVignettes("LedPred")

 

PDF LedPred Example
PDF   Reference Manual
Text   NEWS
Text   LICENSE

Details

biocViews ChIPSeq, MotifAnnotation, Software, SupportVectorMachine
Version 1.2.1
In Bioconductor since BioC 3.2 (R-3.2) (0.5 years)
License MIT | file LICENSE
Depends R (>= 3.2.0), e1071 (>= 1.6)
Imports akima, GenomicRanges(>= 1.18.4), irr, jsonlite, parallel, plot3D, plyr, RCurl, ROCR, testthat
LinkingTo
Suggests
SystemRequirements
Enhances
URL
BugReports https://github.com/aitgon/LedPred/issues
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source LedPred_1.2.1.tar.gz
Windows Binary LedPred_1.2.1.zip
Mac OS X 10.6 (Snow Leopard) LedPred_1.2.0.tgz
Mac OS X 10.9 (Mavericks) LedPred_1.2.1.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/LedPred/tree/release-3.2
Package Short Url http://bioconductor.org/packages/LedPred/
Package Downloads Report Download Stats

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