.colNormHelper          Calculates the column znormalization after row
                        znormalization
addLatentSpace          Add a latent space computed using an external
                        method
addProjection,Vision-method
                        Add a set of projection coordinates to use for
                        visualization
addSignatures           Add signatures to VISION object
addTSNE                 Adds a tSNE projection
addUMAP                 Adds a UMAP projection
analyze,Vision-method   Main entry point for running VISION Analysis
analyzeLocalCorrelations
                        Compute local correlations for all signatures
analyzeTrajectoryCorrelations
                        Compute trajectory correlations for all
                        signatures
annotateLatentComponents
                        Compute pearson correlation between signature
                        scores and components of the Latent Space
applyFilters            Applies filters to the inputted expression data
                        (may remove rows)
applyICA                Performs ICA on data
applyISOMap             Performs ISOMap on data
applyMicroClustering    Pool cells into microclusters
applyPCA                Performs PCA on data
applyPermutationWPCA    Applies pemutation method to return the most
                        significant components of PCA data
applyRBFPCA             Performs PCA on data that has been transformed
                        with the Radial Basis Function.
applySimplePPT          Applies the Simple PPT algorithm onto the
                        expression data.
applySpectralEmbedding
                        Performs Spectral Embedding on data
applytSNE10             Performs tSNE with perplexity 10 on data
applytSNE30             Performs tSNE with perplexity 30 on data
applyUMAP               Performs UMAP on data
batchify                Utility methods Helper utility to group list
                        items into batches
batchSigEvalNorm        Evaluate signature scores efficiently in
                        batches
calcInterEdgeDistMat    Calculate all distances between points on two
                        different edges
calcIntraEdgeDistMat    Calculate distances between all points on a
                        given edge, including edge vertices
calcSignatureScores     calculate signature scores
calculateTrajectoryDistances
                        Calculate distance matrix between all pairs of
                        ponts based on their projection onto the tree
clipBottom              Sets all values below a certain level in the
                        data equal to 0
Cluster                 Wrapper class for a particular cluster. Maps a
                        cluster type to the the resulting cluster data.
clusterCells            Creates clustering of the cells
clusterSignatures       Clusters signatures according to the rank sum
clusterSigScores        Compute Ranksums Test, for all factor meta
                        data.  One level vs all others
colNormalization        Performs z-normalization on all columns
colRankNormalization    Creaes a new version of the data that has ranks
                        (column-wise) instead of values.
colVarsSp               Compute col-wise variance on matrix without
                        densifying
computeKNNWeights,matrix-method
                        compute for each vector the weights to apply to
                        it's K nearest neighbors
computeKNNWeights,Trajectory-method
                        Compute KNN weights based on geodesic distances
                        for Trajectory objects
computeLatentSpace      Computes the latent space of the expression
                        matrix using PCA
computeProjectionGenes
                        filter data accourding to the provided filters
convertGeneIds          Change Gene Identifiers
coordinatesToJSON       Converts a projection into a JSON object
                        mapping each sample to a projection coordinate.
createGeneSignature     Create a user-defined gene signature
createTrajectoryMetaData
                        Generate meta-data associated with this
                        trajectory
evalSigGeneImportance   Calculate gene-signature importance
evalSigGeneImportanceSparse
                        Calculate Gene-Signature Importance
fbConsistencyScores     Evaluates the significance of each protein
filterGenesFano         Applies the Fano filter to the input data (may
                        remove rows)
filterGenesNovar        Eliminate genes whose sample variance is equal
                        to 0 (may remove rows); run when -nofilter
                        option is selected
filterGenesThreshold    Filter genes whose values sum to less than some
                        threshold value (may remove rows)
find_knn_parallel       Parallel KNN
fitTree                 Fit tree using input parameters
geary_sig_v_proj        Evaluates values vs coordinates using the Geary
                        C
generatePermutationNull
                        Generate random signatures for a null
                        distribution by permuting the data
generateProjections     generate projections
generateProjectionsInner
                        Projects data into 2 dimensions using a variety
                        of linear and non-linear methods.
generateTrajectoryProjections
                        Generate 2d representations of a trajectory
                        model
getLatentSpace,Vision-method
                        Get Latent Space
getLatentTrajectory,Vision-method
                        Get Latent Trajectory
getMetaAutocorrelation,Vision-method
                        Get MetaData Autocorrelation Scores
getMetaDifferential,Vision-method
                        Get Results of One-vs-All Differential Tests
                        with Metadata Variables
getMSE                  Calculates the MSE between C and X
getNormalizedCopy       Calculates the specified normalized data matrix
getNormalizedCopySparse
                        Calculates the specified normalized data matrix
getParam                Gets parameters with defaults
getProjections,Vision-method
                        Get 2D views of the expression data
getSelections,Vision-method
                        Get saved selections
getSignatureAutocorrelation,Vision-method
                        Get Signature Autocorrelation Scores
getSignatureDifferential,Vision-method
                        Get Results of One-vs-All Differential
                        Signature Tests
getSignatureScores,Vision-method
                        Get Signature Scores
hasUnnormalizedData     Tests for Unnormalized Data
ilog1p                  inverse log-scale transform a dense OR sparse
                        matrix
innerEvalSignatureBatchNorm
                        Used in inner loop of batchSigEvalNorm
launchServer            Lanch the server
louvainCluster          Applies the Louvain algorithm to generate
                        micro-clustered data
matLog2                 log2-scale transform a dense OR sparse matrix
matrix_chisq            Perform 1vAll factor analysis given a factor
                        matrix and group definition
matrix_wilcox           Vectorized wilcox rank-sums test
matrix_wilcox_cpp       C++ wilcox rank-sums test
noNormalization         Does nothing, just returns the original data
NormData                Initialize a new NormData object
pearsonCorrToJSON       convert perason correlation coeffcients between
                        PCs and sgnatures into a JSON object
poolCells               create micro-clusters that reduce noise and
                        complexity while maintaining the overall signal
                        in the data
poolMatrixCols          Pools columns of a numeric matrix
poolMatrixCols_Inner    create "super-cells" by pooling together single
                        cells
poolMatrixRows          Pools rows of a numeric matrix
poolMetaData            Aggregate meta-data for cells in pools
processSignatures       Processes signatures on input
projectOnTree           Project the given dataoints onto the tree
                        defined by the vertices (V.pos) and binary
                        adjacency matrix (princAdj)
read_10x                Read 10x Output
read_10x_h5             Read 10x HDF5 Output
read_10x_h5_v2          Read 10x HDF5 Output - CellRanger 2.0
read_10x_h5_v3          Read 10x HDF5 Output - CellRanger 3.0
readjust_clusters       Repartitions existing clusters to achieve
                        desired granularity.
readSignaturesInput     Reads in a list of signature input files.
registerMethods         Registers the projection methods to be used
rowAndColNormalization
                        Performs z-normalization on all columns and
                        rows
rowNormalization        Performs z-normalization on all rows
rowVarsSp               Compute row-wise variance on matrix without
                        densifying
saveAndViewResults,Vision-method
                        Save the VISION object as an .RDS file and view
                        the results on a localhost
ServerExpression        Wrapper class for gene expression object for
                        JSON.
ServerSigProjMatrix     Wrapper class for Signature Projection Matrix
sigConsistencyScores    Evaluates the significance of each signature in
                        each cluster
Signature               Initialize a new Signature object.
signatureToJSON         Converts Signature object to JSON
sigProjMatrixToJSON     Converts a sigProjMatrix from an R Object to a
                        JSON object
sigScoresToJSON         Converts row of sigantures score matrix to JSON
sigsToSparseMatrix      Utility method to load signatures into a sparse
                        matrix
sigsVsProjection_n      Evaluates the significance of each numeric
                        signature vs. a single projections weights
sigsVsProjection_pcf    Evaluates the significance of each meta data
                        factor signature vs. a single projections
                        weights
sigsVsProjection_pcn    Evaluates the significance of each meta data
                        numeric signature vs. a single projections
                        weights
sqdist                  Alternative computation of distance matrix,
                        based on matrix multiplication.
Trajectory              Initialize a new Trajectory object.
TrajectoryProjection    Initialize a new TrajectoryProjection object.
translateCellPositions
                        Translate cell positions
versionCheck            Checks the version of the Vision object and
                        displays error if necessary
viewResults,Vision-method
                        View results of analysis
Vision                  Initializes a new VISION object.
VISION                  VISION
