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LedPred

Learning from DNA to Predict Enhancers

Bioconductor version: 3.24 · Package version: 1.47.0

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.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("LedPred")

Details

MaintainerAitor Gonzalez <aitor.gonzalez@univ-amu.fr>
AuthorElodie Darbo, Denis Seyres, Aitor Gonzalez
LicenseMIT | file LICENSE
Bug Reportshttps://github.com/aitgon/LedPred/issues
Downloads rank370
Source branchdevel
biocViewsChIPSeq, Classification, MotifAnnotation, Sequencing, Software, SupportVectorMachine

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageLedPred_1.47.0.tar.gz
Windows binary (x86_64)LedPred_1.47.0.zip
macOS binary (arm64)LedPred_1.47.0.tgz
macOS binary (x86_64)LedPred_1.47.0.tgz
Dependencies

Depends: R (>= 3.2.0), e1071 (>= 1.6)

Imports: akima, ggplot2, irr, jsonlite, parallel, plot3D, plyr, RCurl, ROCR, testthat