DataOptions             DataOptions: set and retrieve data options
Dimensions              Dimensions: set and retrieve dimensions
Expectations            Expectations: set and retrieve expectations of
                        model components
FeatureIntercepts       FeatureIntercepts: set and retrieve feature
                        intercepts
ImputedData             ImputedData: set and retrieve imputed data
InputData               InputData: set and retrieve input data
MOFA                    Multi-Omics Factor Analysis (MOFA)
MOFAmodel               Class to store a Multi-Omics Factor Analysis
                        (MOFA) model
ModelOptions            ModelOptions: set and retrieve model options
Status                  Status: set and retrieve training status
TrainData               TrainData: set and retrieve training data
TrainOptions            TrainOptions: set and retrieve training options
TrainStats              TrainStats: set and retrieve training statistcs
calculateVarianceExplained
                        Calculate variance explained by the model
clusterSamples          clusterSamples: K-means clustering on samples
                        based on latent factors
compareFactors          Correlation of the latent factors across
                        different trials
compareModels           Compare different instances of trained
                        'MOFAmodel'
createMOFAobject        Initialize a MOFA object
factorNames             factorNames: set and retrieve factor names
featureNames            featureNames: set and retrieve feature names
getCovariates           getCovariates
getDefaultDataOptions   Get default data options
getDefaultModelOptions
                        Get default model options
getDefaultTrainOptions
                        Get default training options
getDimensions           getDimensions
getELBO                 getELBO
getExpectations         getExpectations
getFactors              getFactors
getImputedData          getImputedData
getTrainData            getTrainData
getWeights              getWeights
impute                  Impute missing values from a fitted MOFA model
loadModel               loading a trained MOFA model
makeExampleData         make an example multi-view data set for
                        illustration of MOFA
plotDataHeatmap         Plot heatmap of relevant features
plotDataOverview        Plot overview of the input data
plotDataScatter         Scatterplots of feature values against latent
                        factors
plotEnrichment          Plot output of Feature Set Enrichment Analysis
plotEnrichmentBars      Barplot of Feature Set Enrichment Analysis
                        results
plotEnrichmentDetailed
                        Plot detailed output of the Feature Set
                        Enrichment Analysis
plotEnrichmentHeatmap   Heatmap of Feature Set Enrichment Analysis
                        results
plotFactorBeeswarm      Beeswarm plot of latent factors
plotFactorCor           Plot correlation matrix between latent factors
plotFactorHist          Plot histogram of latent factor values
plotFactorScatter       Scatterplot of two latent factors
plotFactorScatters      Pairwise scatterplots of multiple latent
                        factors
plotTopWeights          Plot top weights
plotVarianceExplained   Plot variance explained by the model
plotWeights             Plot Weights
plotWeightsHeatmap      Plot heatmap of the weights
predict                 Do predictions using a fitted MOFA model
prepareMOFA             prepare a MOFAobject for training
qualityControl          qualityControl
regressCovariates       regress out a covariate from the training data
runEnrichmentAnalysis   Feature Set Enrichment Analysis
runMOFA                 train a MOFA model
sampleNames             sampleNames: set and retrieve sample names
selectModel             Select the best model from a list of trained
                        'MOFAmodel' objects
subsetFactors           Subset factors
subsetSamples           Subset samples
subsetViews             Subset views
trainCurveELBO          Training curve for Evidence Lower Bound (ELBO)
trainCurveFactors       Training curve for the number of active factors
viewNames               viewNames: set and retrieve view names
