Conducting statistical inference on comparing the mutational exposures of mutational signatures by using hierarchical latent Dirichlet allocation

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Documentation for package ‘HiLDA’ version 1.22.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

boundaryTurbo_F	Check whether the parameter F is within the appropriate range
boundaryTurbo_Q	Check whether the parameter Q is within the appropriate range
calcPMSLikelihood	A function for calculating the log-likelihood from the data and parameters
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
EstimatedParameters-class	An S4 class representing the estimated parameters
getLogLikelihoodC	Calculate the value of the log-likelihood for given parameters
getMutationFeatureVector	Get mutation feature vector from context sequence data and reference and alternate allele information
hildaBarplot	Read the raw mutation data with the mutation feature vector format, estimate and plot both mutation signatures and their fractions
hildaDiffPlot	Read the raw mutation data with the mutation feature vector format, estimate and plot both mutation signatures and their fractions
hildaGlobalResult	Compute the Bayes factor
hildaLocalResult	Extract the posterior distributions of the mean differences in muational exposures
hildaPlotSignature	Plot mutation signatures from HiLDA output
hildaReadMPFile	Read the raw mutation data of Mutation Position Format.
hildaRhat	Output the maximum potential scale reduction statistic of all parameters estimated
hildaTest	Apply HiLDA to statistically testing the global difference in burdens of mutation signatures between two groups
MetaInformation-class	An S4 class to represent a mutation meta information common to many data types
MutationFeatureData-class	An S4 class representing the mutation data
mySquareEM	A function for estimating parameters using Squared EM algorithm
pmBarplot	Plot both mutation signatures and their mutational exposures from pmsignature output
pmgetSignature	Obtain the parameters for mutation signatures and memberships
pmMultiBarplot	Plot both mutation signatures and their mutational exposures from pmsignature output for more than two groups
pmPlotSignature	Plot mutation signatures from pmsignature output
PMSboundary	A functional for generating the function checking the parameter (p) is within the restricted conditions or not
updateMstepFQC	Update the parameter F and Q (M-step in the EM-algorithm)
updatePMSParam	A function for updating parameters using EM-algorithm
updateTheta_NormalizedC	Update the auxiliary parameters theta and normalize them so that the summation of each group sums to 1 (E-step), also calculate the current log-likelihood value
visPMS	visualize probabisitic mutaiton signature for the independent model