A B C E F G H I L M N P R S T V misc
| VISION-package | VISION |
| addLatentSpace | Add a latent space computed using an external method |
| addProjection | Add a set of projection coordinates to use for visualization |
| addProjection-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 | Main entry point for running VISION Analysis |
| analyze-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-method | Compute KNN weights based on geodesic distances for Trajectory objects |
| computeKNNWeights-method | compute for each vector the weights to apply to it's K nearest neighbors |
| 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 | Get Latent Space |
| getLatentSpace-method | Get Latent Space |
| getLatentTrajectory | Get Latent Trajectory |
| getLatentTrajectory-method | Get Latent Trajectory |
| getMetaAutocorrelation | Get MetaData Autocorrelation Scores |
| getMetaAutocorrelation-method | Get MetaData Autocorrelation Scores |
| getMetaDifferential | Get Results of One-vs-All Differential Tests with Metadata Variables |
| getMetaDifferential-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 | Get 2D views of the expression data |
| getProjections-method | Get 2D views of the expression data |
| getSelections | Get saved selections |
| getSelections-method | Get saved selections |
| getSignatureAutocorrelation | Get Signature Autocorrelation Scores |
| getSignatureAutocorrelation-method | Get Signature Autocorrelation Scores |
| getSignatureDifferential | Get Results of One-vs-All Differential Signature Tests |
| getSignatureDifferential-method | Get Results of One-vs-All Differential Signature Tests |
| getSignatureScores | Get Signature Scores |
| getSignatureScores-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) |
| readjust_clusters | Repartitions existing clusters to achieve desired granularity. |
| readSignaturesInput | Reads in a list of signature input files. |
| 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 |
| 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 | Save the VISION object as an .RDS file and view the results on a localhost |
| saveAndViewResults-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 | View results of analysis |
| viewResults-method | View results of analysis |
| VISION | VISION |
| Vision | Initializes a new VISION object. |
| Vision-method | Initializes a new VISION object. |
| .colNormHelper | Calculates the column znormalization after row znormalization |