SVM2CRM: support vector machine for cis-regulatory elements detections

Documentation for package ‘SVM2CRM’ version 1.12.0

cisREfindbed	Create and preprocessing of the input for SVM2CRM analysis
createBed	Create bed file of predictions using svm.
createSVMinput	Take the output of findFeatureOverlap and then create a positive and negative set of cis-regulatory elements
featSelectionWithKmeans	This function select the most meaningful variables in a matrix of ChIP-seq data using k-means and ICRR.
findFeatureOverlap	Find the overlap of genomic regions between the output of cisREfind and a database of validated cis-regulatory elements.
frequencyHM	frequencyHM
getSignal	Model the signals of each histone marks around genomic features (e.g. enhancers, not_enhancers).
performanceSVM	Estimate the performance of prediction.
plotFscore	Plot the F-score in relation with the sensitivity and specificity
plotROC	Plot the ROC curve of the best model
predictionGW	Perform prediction of cis-regulatory elements genome-wide
smoothInputFS	Smooth the signals of the histone marks to prepare the input for feature selection analysis
tuningParametersCombROC	Test different models using different kernel of SVM, values of cost functions, the number of histone marks.