DOI: 10.18129/B9.bioc.LedPred  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see LedPred.

Learning from DNA to Predict Enhancers

Bioconductor version: 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
Text   NEWS


biocViews ChIPSeq, Classification, MotifAnnotation, Sequencing, Software, SupportVectorMachine
Version 1.34.0
In Bioconductor since BioC 3.2 (R-3.2) (8 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
Depends On Me
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Source Package LedPred_1.34.0.tar.gz
Windows Binary LedPred_1.34.0.zip (64-bit only)
macOS Binary (x86_64) LedPred_1.34.0.tgz
macOS Binary (arm64) LedPred_1.34.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/LedPred
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/LedPred
Bioc Package Browser https://code.bioconductor.org/browse/LedPred/
Package Short Url https://bioconductor.org/packages/LedPred/
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