Functional interpretation of single cell RNA-seq latent manifolds

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Documentation for package ‘VISION’ version 2.0.0

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A B C E F G H I L M N P R S T V misc

VISION-package VISION

-- A --

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

-- B --

batchify Utility methods Helper utility to group list items into batches
batchSigEvalNorm Evaluate signature scores efficiently in batches

-- C --

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

-- E --

evalSigGeneImportance Calculate gene-signature importance
evalSigGeneImportanceSparse Calculate Gene-Signature Importance

-- F --

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

-- G --

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

-- H --

hasUnnormalizedData Tests for Unnormalized Data

-- I --

ilog1p inverse log-scale transform a dense OR sparse matrix
innerEvalSignatureBatchNorm Used in inner loop of batchSigEvalNorm

-- L --

launchServer Lanch the server
louvainCluster Applies the Louvain algorithm to generate micro-clustered data

-- M --

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

-- N --

noNormalization Does nothing, just returns the original data
NormData Initialize a new NormData object

-- P --

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)

-- R --

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

-- S --

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.

-- T --

Trajectory Initialize a new Trajectory object.
TrajectoryProjection Initialize a new TrajectoryProjection object.
translateCellPositions Translate cell positions

-- V --

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.

-- misc --

.colNormHelper Calculates the column znormalization after row znormalization