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

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

## Documentation for package ‘HiLDA’ version 1.27.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## 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