Package: kebabs 1.39.0

Ulrich Bodenhofer

kebabs: Kernel-Based Analysis of Biological Sequences

The package provides functionality for kernel-based analysis of DNA, RNA, and amino acid sequences via SVM-based methods. As core functionality, kebabs implements following sequence kernels: spectrum kernel, mismatch kernel, gappy pair kernel, and motif kernel. Apart from an efficient implementation of standard position-independent functionality, the kernels are extended in a novel way to take the position of patterns into account for the similarity measure. Because of the flexibility of the kernel formulation, other kernels like the weighted degree kernel or the shifted weighted degree kernel with constant weighting of positions are included as special cases. An annotation-specific variant of the kernels uses annotation information placed along the sequence together with the patterns in the sequence. The package allows for the generation of a kernel matrix or an explicit feature representation in dense or sparse format for all available kernels which can be used with methods implemented in other R packages. With focus on SVM-based methods, kebabs provides a framework which simplifies the usage of existing SVM implementations in kernlab, e1071, and LiblineaR. Binary and multi-class classification as well as regression tasks can be used in a unified way without having to deal with the different functions, parameters, and formats of the selected SVM. As support for choosing hyperparameters, the package provides cross validation - including grouped cross validation, grid search and model selection functions. For easier biological interpretation of the results, the package computes feature weights for all SVMs and prediction profiles which show the contribution of individual sequence positions to the prediction result and indicate the relevance of sequence sections for the learning result and the underlying biological functions.

Authors:Johannes Palme [aut], Ulrich Bodenhofer [aut,cre]

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kebabs.pdf |kebabs.html
kebabs/json (API)
NEWS

# Install 'kebabs' in R:
install.packages('kebabs', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ubod/kebabs/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • ccannot - KeBABS Sequence Data
  • ccgroups - KeBABS Sequence Data
  • ccseq - KeBABS Sequence Data
  • enhancerFB - KeBABS Sequence Data
  • yCC - KeBABS Sequence Data
  • yFB - KeBABS Sequence Data
  • yMC - KeBABS Sequence Data
  • yReg - KeBABS Sequence Data

On BioConductor:kebabs-1.39.0(bioc 3.20)kebabs-1.38.0(bioc 3.19)

bioconductor-package

75 exports 1.69 score 28 dependencies 3 dependents

Last updated 2 months agofrom:2fcfc70a6c

Exports:AAVectorannotationCharsetannotationMetadataannotationMetadata<-as.KernelMatrixaucauc<-baselinescomputeROCandAUCcvResultcvResult<-DNAVectorevaluatePredictionexpWeightfeatureWeightsfeatureWeights<-foldsfprfpr<-fullModelgappyPairKernelgaussWeightgenRandBioSeqsgetExRepgetExRepQuadraticgetFeatureSpaceDimensiongetFeatureWeightsgetKernelMatrixgetPredictionProfilegetPredProfMixturegetSVMSlotValuegridColumnsgridErrorsgridRowsheatmapisUserDefinedkbsvmkebabsCollectInfokebabsDemokernelParameterslinearKernellinWeightmismatchKernelmodelOffsetmodelOffset<-modelSelResultmodelSelResult<-motifKernelperformanceperformCrossValidationplotpositionMetadatapositionMetadata<-predictpredictSVMprobabilityModelprobabilityModel<-profilesRNAVectorselGridColselGridRowseqKernelAsCharsequencesshowshowAnnotatedSeqspectrumKernelSVindexsvmModelsvmModel<-swdWeightsymmetricPairKerneltprtpr<-trainSVMwidth

Dependencies:apclusteraskpassBiocGenericsBiostringsclasscrayoncurle1071GenomeInfoDbGenomeInfoDbDatahttrIRangesjsonlitekernlablatticeLiblineaRMASSMatrixmimeopensslproxyR6RcppS4VectorssysUCSC.utilsXVectorzlibbioc

KeBABS - An R Package for Kernel Based Analysis of Biological Sequences

Rendered fromkebabs.Rnwusingknitr::knitron Jun 30 2024.

Last update: 2024-04-25
Started: 2015-01-12

Readme and manuals

Help Manual

Help pageTopics
DNAVector, RNAVector, AAVector Objects and BioVector ClassAAVector as.character,BioVector-method BioVector c,BioVector-method DNAVector length length,BioVector-method names names,BioVector-method names<- names<-,BioVector-method RNAVector width width,BioVector-method [,BioVector,index,missing,ANY-method [,BioVector-method
BioVector, DNAVector, RNAVector and AAVector ClassesAAVector-class BioVector-class class:AAVector class:BioVector class:DNAVector class:RNAVector DNAVector-class RNAVector-class
Compute Receiver Operating Characteristic And Area Under The CurvecomputeROCandAUC
KeBABS Control Information Classclass:ControlInformation ControlInformation ControlInformation-class
Cross Validation Result Classclass:CrossValidationResult CrossValidationResult CrossValidationResult-class
CrossValidationResult AccessorsCrossValidationResultAccessors folds folds,CrossValidationResult-method performance,CrossValidationResult-method
Evaluate PredictionevaluatePrediction
Explicit Representation Dense and Sparse Classesclass:ExplicitRepresentation class:ExplicitRepresentationDense class:ExplicitRepresentationSparse ExplicitRepresentation ExplicitRepresentation-class ExplicitRepresentationDense ExplicitRepresentationDense-class ExplicitRepresentationSparse ExplicitRepresentationSparse-class
ExplicitRepresentation Accessors%*%,dgRMatrix,numeric-method %*%,matrix,dgRMatrix-method ExplicitRepresentationAccessors [,ExplicitRepresentation,index,index,ANY-method [,ExplicitRepresentationDense,index,index,ANY-method [,ExplicitRepresentationDense,index,missing,ANY-method [,ExplicitRepresentationDense,missing,index,ANY-method [,ExplicitRepresentationSparse,index,index,ANY-method [,ExplicitRepresentationSparse,index,index,logical-method [,ExplicitRepresentationSparse,index,index,missing-method [,ExplicitRepresentationSparse,index,missing,ANY-method [,ExplicitRepresentationSparse,index,missing,logical-method [,ExplicitRepresentationSparse,index,missing,missing-method [,ExplicitRepresentationSparse,missing,index,ANY-method [,ExplicitRepresentationSparse,missing,index,logical-method [,ExplicitRepresentationSparse,missing,index,missing-method
Gappy Pair KernelgappyPairKernel getFeatureSpaceDimension,GappyPairKernel-method
Gappy Pair Kernel Classclass:GappyPairKernel GappyPairKernel GappyPairKernel-class
Generate Random Biological SequencesgenRandBioSeqs
Explict RepresentationgetExRep getExRepQuadratic
Feature WeightsgetFeatureWeights
Calculation Of Predicition ProfilesgetPredictionProfile getPredictionProfile,BioVector-method getPredictionProfile,XString-method getPredictionProfile,XStringSet-method
Calculation Of Predicition Profiles for Mixture KernelsgetPredProfMixture getPredProfMixture,BioVector-method getPredProfMixture,XString-method getPredProfMixture,XStringSet-method
Heatmap Methodsheatmap heatmap,PredictionProfile,missing-method heatmap,PredictionProfile-method
KeBABS Model Classclass:KBModel KBModel KBModel-class
KBModel AccessorscvResult cvResult,KBModel-method cvResult<- cvResult<-,KBModel-method featureWeights featureWeights,KBModel-method featureWeights<- featureWeights<-,KBModel-method getSVMSlotValue KBModelAccessors modelOffset modelOffset,KBModel-method modelOffset<- modelOffset<-,KBModel-method modelSelResult modelSelResult,KBModel-method modelSelResult<- modelSelResult<-,KBModel-method probabilityModel probabilityModel,KBModel-method probabilityModel<- probabilityModel<-,KBModel-method SVindex SVindex,KBModel-method SVindex<- SVindex<-,KBModel-method svmModel svmModel,KBModel-method svmModel<- svmModel<-,KBModel-method
KeBABS Training Methodskbsvm kbsvm,BioVector-method kbsvm,ExplicitRepresentation-method kbsvm,KernelMatrix-method kbsvm,XStringSet-method
Collect KeBABS Package InformationkebabsCollectInfo
KeBABS Sequence Dataccannot ccgroups ccseq enhancerFB kebabsData TFBS yCC yFB yMC yReg
kebabsKEBABS KeBABS kebabs kebabsDemo
Kernel Matrix Classclass:KernelMatrix KernelMatrix KernelMatrix-class
KernelMatrix Accessorsas.KernelMatrix as.KernelMatrix,matrix-method KernelMatrixAccessors [,KernelMatrix,index,index,ANY-method [,KernelMatrix,index,missing,ANY-method [,KernelMatrix,missing,index,ANY-method
Linear KernellinearKernel
Position Dependent KernelDistanceWeightedKernel distanceWeightedKernel expWeight gaussWeight linWeight PositionDependentKernel positionDependentKernel positionMetadata positionMetadata,BioVector-method positionMetadata,XStringSet-method positionMetadata<- positionMetadata<-,BioVector-method positionMetadata<-,XStringSet-method PositionSpecificKernel positionSpecificKernel swdWeight
Mismatch KernelgetFeatureSpaceDimension,MismatchKernel-method mismatchKernel
Mismatch Kernel Classclass:MismatchKernel MismatchKernel MismatchKernel-class
Model Selection Result Classclass:ModelSelectionResult ModelSelectionResult ModelSelectionResult-class
ModelSelectionResult AccessorsfullModel fullModel,ModelSelectionResult-method gridColumns gridColumns,ModelSelectionResult-method gridErrors gridErrors,ModelSelectionResult-method gridRows gridRows,ModelSelectionResult-method ModelSelectionResultAccessors performance performance,ModelSelectionResult-method selGridCol selGridCol,ModelSelectionResult-method selGridRow selGridRow,ModelSelectionResult-method
Motif KernelgetFeatureSpaceDimension,MotifKernel-method motifKernel
Motif Kernel Classclass:MotifKernel MotifKernel MotifKernel-class
KeBABS Cross Validationcross.validation CrossValidation crossValidation performCrossValidation performCrossValidation,ExplicitRepresentation-method performCrossValidation,KernelMatrix-method
KeBABS Grid Searchgrid.search GridSearch gridSearch performGridSearch
KeBABS Model Selectionmodel.selection ModelSelection modelSelection performModelSelection
Plot Prediction Profiles, Cross Validation Result, Grid Search Performance Parameters and Receiver Operating Characteristicsplot plot,CrossValidationResult,missing-method plot,CrossValidationResult-method plot,ModelSelectionResult,missing-method plot,ModelSelectionResult-method plot,PredictionProfile,missing-method plot,PredictionProfile-method plot,ROCData,missing-method plot,ROCData-method
KeBABS Prediction Methodspredict predict,KBModel-method predict.KBModel predict.kbsvm
Prediction Profile Classclass:PredictionProfile PredictionProfile PredictionProfile-class
PredictionProfile Accessorsbaselines baselines,PredictionProfile-method PredictionProfileAccessors profiles profiles,PredictionProfile-method sequences sequences,PredictionProfile-method [,PredictionProfile,index,ANY,ANY-method
SVM Access for Training and PredictionpredictSVM predictSVM,ExpicitRepresentation-method predictSVM,ExplicitRepresentation-method predictSVM,KernelMatrix-method predictSVM,missing-method predictSVM.KernelMatrix trainSVM trainSVM,ExplicitRepresentation-method trainSVM,KernelMatrix-method
ROC Data Classclass:ROCData ROCData ROCData-class
ROCData Accessorsauc auc,ROCData-method auc<- auc<-,ROCData-method fpr fpr,ROCData-method fpr<- fpr<-,ROCData-method ROCDataAccessors tpr tpr,ROCData-method tpr<- tpr<-,ROCData-method
Sequence KernelgetKernelMatrix isUserDefined isUserDefined,SequenceKernel-method kernelParameters kernelParameters,GappyPairKernel-method kernelParameters,MismatchKernel-method kernelParameters,MotifKernel-method kernelParameters,SpectrumKernel-method kernelParameters,SymmetricPair-method kernelParameters,SymmetricPairKernel-method kernelParameters-method seqKernelAsChar sequenceKernel
Sequence Kernel Classclass:SequenceKernel SequenceKernel SequenceKernel-class
Display Various KeBABS Objectsshow show,BioVector-method show,CrossValidationResult-method show,ExplicitRepresentationDense-method show,ExplicitRepresentationSparse-method show,GappyPairKernel-method show,KBModel-method show,MismatchKernel-method show,ModelSelectionResult-method show,MotifKernel-method show,PredictionProfile-method show,ROCData-method show,SpectrumKernel-method show,SVMInformation-method show,SymmetricPairKernel-method show.BioVector
Annotation Specific KernelannotationCharset annotationCharset,BioVector-method annotationCharset,XStringSet-method annotationMetadata annotationMetadata,BioVector-method annotationMetadata,XStringSet-method annotationMetadata<- annotationMetadata<-,BioVector-method annotationMetadata<-,XStringSet-method AnnotationSpecificKernel annotationSpecificKernel character set showAnnotatedSeq
Spectrum KernelgetFeatureSpaceDimension getFeatureSpaceDimension,ANY-method getFeatureSpaceDimension,SpectrumKernel-method spectrumKernel
Spectrum Kernel Classclass:SpectrumKernel SpectrumKernel SpectrumKernel-class
SVM Information Classclass:SVMInformation SVMInformation SVMInformation-class
Symmetric Pair KernelsymmetricPairKernel
Symmetric Pair Kernel Classclass:SymmetricPairKernel SymmetricPairKernel SymmetricPairKernel-class