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

Learning from DNA to Predict Enhancers

Bioconductor version: Development (3.19)

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>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


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

LedPred Example PDF R Script
Reference Manual PDF


biocViews ChIPSeq, Classification, MotifAnnotation, Sequencing, Software, SupportVectorMachine
Version 1.37.0
In Bioconductor since BioC 3.2 (R-3.2) (8.5 years)
License MIT | file LICENSE
Depends R (>= 3.2.0), e1071 (>= 1.6)
Imports akima, ggplot2, irr, jsonlite, parallel, plot3D, plyr, RCurl, ROCR, testthat
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Source Package LedPred_1.37.0.tar.gz
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