LedPred: Learning from DNA to Predict Enhancers
Version 1.10.0

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.

Browse man pages Browse package API and functions Browse package files

AuthorElodie Darbo, Denis Seyres, Aitor Gonzalez
Bioconductor views ChIPSeq Classification MotifAnnotation Sequencing Software SupportVectorMachine
Date of publicationNone
MaintainerAitor Gonzalez <aitor.gonzalez@univ-amu.fr>
LicenseMIT | file LICENSE
Version1.10.0
Package repositoryView on Bioconductor
InstallationInstall the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("LedPred")

Man pages

createModel: Create the model with the optimal features
crm.features: This is data to be included in my package
evaluateModelPerformance: Evaluate model performances
feature.ranking: This is data to be included in my package
LedPred: Creates an SVM model given a feature matrix
mapFeaturesToCRMs: R interface to bed_to_matrix REST in server
mcTune: Tuning the SVM parameters
rankFeatures: Ranking the features according to their importance
scoreData: Predicting new regulatory regions
tuneFeatureNb: Selecting the optimal number of features

Functions

LedPred Man page Source code
classAgreement2 Source code
createModel Man page Source code
crm.features Man page
evaluateModelPerformance Man page Source code
feature.ranking Man page
mapFeaturesToCRMs Man page Source code
mcTune Man page Source code
plotCostGamma Source code
rankFeatures Man page Source code
scoreData Man page Source code
tuneFeatureNb Man page Source code

Files

DESCRIPTION
LICENSE
NAMESPACE
NEWS
R
R/Data.R
R/FeatureNbTuner.R
R/FeatureRanking.R
R/LedPredClass.R
R/Model.R
R/ModelPerformance.R
R/ParameterTuner.R
R/createModel.R
R/evaluateModelPerformance.R
R/ledpred.R
R/mapFeaturesToCRMs.R
R/mcTune.R
R/rankFeatures.R
R/scoreData.R
R/tuneFeatureNb.R
build
build/vignette.rds
data
data/crm.features.rda
data/feature.ranking.rda
inst
inst/CITATION
inst/doc
inst/doc/LedPred.R
inst/doc/LedPred.Rnw
inst/doc/LedPred.pdf
inst/extdata
inst/extdata/259_matrices_lightNames.tf
inst/extdata/2nt_intergenic_droso.freq
inst/extdata/negative_50CADenhancers.bed
inst/extdata/ngs
inst/extdata/ngs/K4me1_E_F_6_8h_H3_subtracted_reduced.wig
inst/extdata/ngs/docBoundCRM.bed
inst/extdata/ngs/dtcfBoundCRM.bed
inst/extdata/ngs/pmadBoundCRM.bed
inst/extdata/ngs/pnrBoundCRM.bed
inst/extdata/ngs/tinBoundCRM.bed
inst/extdata/positive_50CADenhancers.bed
inst/extdata/prediction_small.bed
inst/extdata/testdata
inst/extdata/testdata/230NonActivesEnhancers4_8h_2seqs.bed
inst/extdata/testdata/23From66ActiveEnhancersInMesoAt68h_2seqs.bed
inst/extdata/testdata/feature_nb.txt
inst/extdata/testdata/feature_rank.txt
inst/extdata/testdata/test_ngs_bed_small
inst/extdata/testdata/test_ngs_bed_small/mfile2.tf
inst/extdata/testdata/test_ngs_bed_small/negative_5seqs.bed
inst/extdata/testdata/test_ngs_bed_small/ngs_beds
inst/extdata/testdata/test_ngs_bed_small/ngs_beds/ngs.bed
inst/extdata/testdata/test_ngs_bed_small/ngs_beds/ngs2.bed
inst/extdata/testdata/test_ngs_bed_small/outdir_bak
inst/extdata/testdata/test_ngs_bed_small/outdir_bak/feature_matrix.tab
inst/extdata/testdata/test_ngs_bed_small/positive_2seqs.bed
man
man/LedPred.Rd
man/createModel.Rd
man/crm.features.Rd
man/evaluateModelPerformance.Rd
man/feature.ranking.Rd
man/mapFeaturesToCRMs.Rd
man/mcTune.Rd
man/rankFeatures.Rd
man/scoreData.Rd
man/tuneFeatureNb.Rd
tests
tests/testthat
tests/testthat.R
tests/testthat/_ROC_perf.png
tests/testthat/_kappa_measures.png
tests/testthat/data_iris2
tests/testthat/data_iris2/feature.ranking.rda
tests/testthat/data_iris2/iris2.rda
tests/testthat/data_iris2/x.rda
tests/testthat/data_iris2/y.rda
tests/testthat/test-iris2_Data.R
tests/testthat/test-iris2_FeatureNbTuner.R
tests/testthat/test-iris2_FeatureRanking.R
tests/testthat/test-iris2_LedPred.R
tests/testthat/test-iris2_ModelCreate.R
tests/testthat/test-iris2_ModelPerformance.R
tests/testthat/test-iris2_ParameterTuner.R
vignettes
vignettes/LedPred.Rnw
vignettes/_ROCR_perf.png
vignettes/_c_g_eval.png
vignettes/_kappa_measures.png
vignettes/figs
vignettes/figs/vignette_ROC_perf.png
vignettes/figs/vignette_c_g_eval.png
vignettes/figs/vignette_kappa_measures.png
LedPred documentation built on May 20, 2017, 10:20 p.m.