DOI: 10.18129/B9.bioc.LedPred    

This is the development version of LedPred; for the stable release version, see LedPred.

Learning from DNA to Predict Enhancers

Bioconductor version: Development (3.17)

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")):


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PDF R Script LedPred Example
PDF   Reference Manual


biocViews ChIPSeq, Classification, MotifAnnotation, Sequencing, Software, SupportVectorMachine
Version 1.33.0
In Bioconductor since BioC 3.2 (R-3.2) (7 years)
License MIT | file LICENSE
Depends R (>= 3.2.0), e1071 (>= 1.6)
Imports akima, ggplot2, irr, jsonlite, parallel, plot3D, plyr, RCurl, ROCR, testthat
BugReports https://github.com/aitgon/LedPred/issues
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Source Package LedPred_1.33.0.tar.gz
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Source Repository git clone https://git.bioconductor.org/packages/LedPred
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/LedPred
Package Short Url https://bioconductor.org/packages/LedPred/
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