Package: LedPred 1.47.0
Aitor Gonzalez
LedPred: Learning from DNA to Predict Enhancers
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.
Authors:
LedPred_1.47.0.tar.gz
LedPred_1.47.0.zip(r-4.7)LedPred_1.47.0.zip(r-4.6)LedPred_1.47.0.zip(r-4.5)
LedPred_1.47.0.tgz(r-4.6-any)LedPred_1.47.0.tgz(r-4.5-any)
LedPred_1.47.0.tar.gz(r-4.7-any)LedPred_1.47.0.tar.gz(r-4.6-any)
LedPred_1.47.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
LedPred/json (API)
| # Install 'LedPred' in R: |
| install.packages('LedPred', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/aitgon/ledpred/issues
Datasets:
- crm.features - This is data to be included in my package
- feature.ranking - This is data to be included in my package
On BioConductor:LedPred-1.47.0(bioc 3.24)LedPred-1.46.0(bioc 3.23)
supportvectormachinesoftwaremotifannotationchipseqsequencingclassification
Last updated from:1cfe7242af. Checks:1 ERROR, 7 WARNING, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 161 | ||
| linux-devel-x86_64 | WARNING | 171 | ||
| source / vignettes | OK | 209 | ||
| linux-release-x86_64 | WARNING | 164 | ||
| macos-release-arm64 | WARNING | 142 | ||
| macos-oldrel-arm64 | WARNING | 98 | ||
| windows-devel | WARNING | 106 | ||
| windows-release | WARNING | 97 | ||
| windows-oldrel | WARNING | 95 | ||
| wasm-release | OK | 162 |
Exports:createModelevaluateModelPerformanceLedPredmapFeaturesToCRMsmcTunerankFeaturesscoreDatatuneFeatureNb
Dependencies:akimabitopsbriocallrcaToolsclassclicpp11crayondescdiffobje1071evaluatefarverfsggplot2gluegplotsgtablegtoolsirrisobandjsonliteKernSmoothlabelinglatticelifecyclelpSolvemagrittrMASSmisc3dotelpkgbuildpkgloadplot3DplyrpraiseprocessxproxypsR6RColorBrewerRcppRCurlrlangROCRrprojrootS7scalessptestthatvctrsviridisLitewaldowithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Create the model with the optimal features | createModel |
| This is data to be included in my package | crm.features |
| Evaluate model performances | evaluateModelPerformance |
| This is data to be included in my package | feature.ranking |
| Creates an SVM model given a feature matrix | LedPred |
| R interface to bed_to_matrix REST in server | mapFeaturesToCRMs |
| Tuning the SVM parameters | mcTune |
| Ranking the features according to their importance | rankFeatures |
| Predicting new regulatory regions | scoreData |
| Selecting the optimal number of features | tuneFeatureNb |
