Selecting the number of mutational signatures using a perplexity-based measure and cross-validation


[Up] [Top]

Documentation for package ‘selectKSigs’ version 1.18.0

Help Pages

calcPMSLikelihood A function for calculating the log-likelihood from the data and parameters
Calculate_Likelihood_test Output the maximum potential scale reduction statistic of all parameters estimated
convertFromTurbo_F Restore the converted parameter F for turboEM
convertFromTurbo_Q Restore the converted parameter Q for turboEM
convertToTurbo_F Convert the parameter F so that turboEM can treat
convertToTurbo_Q Convert the parameter Q so that turboEM can treat
cv_PMSignature Output the maximum potential scale reduction statistic of all parameters estimated
getBG Get the statsus of using the background signature
getCounts Get the count data in a matrix
getExposures Get a matrix of mutational exposures of signatures
getFeatures Get a vector of possible features
getFeatureVec Get a matrix of feature vector list
getK Get the number of signatures
getLL Get the values of loglikelihood
getLogLikelihoodC Calculate the value of the log-likelihood for given parameters
getSamplelist Get the sample list
getSamplelistG Get the sample list
getSignatures Get an array of signature feature distributions
getTranscription Get the statsus of specifying the transcription bias
select_kth_fold Output the training data or test data
splitG Output the maximum potential scale reduction statistic of all parameters estimated