Linked Inference of Genomic Experimental Relationships


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Documentation for package ‘liger’ version 0.5.0.9000

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liger-package Linked Inference of Genomic Experimental Relationships
%>% Pipe operator
aggregateByCluster Aggregate gene-level measurements across cells within clusters to allow correlation across datasets
alignment_metric_per_factor Calculate alignment metric per factor.
calcAgreement Calculate agreement metric
calcAlignment Calculate alignment metric
calcAlignmentPerCluster Calculate alignment for each cluster
calcARI Calculate adjusted Rand index
calcDatasetSpecificity Calculate a dataset-specificity score for each factor
calcPurity Calculate purity
clusterLouvainJaccard Perform graph-based clustering (Louvain algorithm) using number of shared nearest neighbors (Jaccard index) as a distance metric. Note that use of this function requires Seurat to be loaded.
convertOldLiger Convert older liger object into most current version (based on class definition)
createLiger Create a liger object.
getFactorMarkers Find shared and dataset-specific markers
getGeneValues Get gene expression values from list of expression matrices.
getProportionMito Calculate proportion mitochondrial contribution
imputeKNN Impute the query cell expression matrix
liger Linked Inference of Genomic Experimental Relationships
liger The LIGER Class
liger-class The LIGER Class
ligerToSeurat Create a Seurat object containing the data from a liger object
linkGenesAndPeaks Linking genes to putative regulatory elements
louvainCluster Louvain algorithm for community detection
makeInteractTrack Export predicted gene-pair interaction
makeRiverplot Generate a river (Sankey) plot
Matrix.column_norm Perform fast and memory-efficient normalization operation on sparse matrix data.
nnzeroGroups nnzeroGroups
nnzeroGroups.dgCMatrix nnzeroGroups
nnzeroGroups.matrix nnzeroGroups
normalize Normalize raw datasets to column sums
optimizeALS Perform iNMF on scaled datasets
optimizeALS.liger Perform iNMF on scaled datasets
optimizeALS.list Perform iNMF on scaled datasets
optimizeNewData Perform factorization for new data
optimizeNewK Perform factorization for new value of k
optimizeNewLambda Perform factorization for new lambda value
optimizeSubset Perform factorization for subset of data
plotByDatasetAndCluster Plot t-SNE coordinates of cells across datasets
plotClusterFactors Plot heatmap of cluster/factor correspondence
plotClusterProportions Plot cluster proportions by dataset
plotFactors Plot scatter plots of unaligned and aligned factor loadings
plotFeature Plot specific feature on t-SNE coordinates
plotGene Plot gene expression on dimensional reduction (t-SNE) coordinates
plotGeneLoadings Generate t-SNE plots and gene loading plots
plotGenes Plot expression of multiple genes
plotGeneViolin Plot violin plots for gene expression
plotWordClouds Generate word clouds and t-SNE plots
quantileAlignSNF Quantile align (normalize) factor loadings
quantileAlignSNF.liger Quantile align (normalize) factor loadings
quantileAlignSNF.list Quantile align (normalize) factor loadings
quantile_norm Quantile align (normalize) factor loadings
rank_matrix rank_matrix
rank_matrix.dgCMatrix rank_matrix
rank_matrix.matrix rank_matrix
read10X Read 10X alignment data (including V3)
removeMissingObs Remove cells/genes with no expression across any genes/cells
reorganizeLiger Construct a liger object organized by another feature
runTSNE Perform t-SNE dimensionality reduction
runUMAP Perform UMAP dimensionality reduction
runWilcoxon Perform Wilcoxon rank-sum test
scaleNotCenter Scale genes by root-mean-square across cells
scaleNotCenter_sparse Perform fast and memory-efficient data scaling operation on sparse matrix data.
selectGenes Select a subset of informative genes
seuratToLiger Create liger object from one or more Seurat objects
show show method for liger
show-method show method for liger
SNF Generate shared factor neighborhood graph
SNF.liger Generate shared factor neighborhood graph
SNF.list Generate shared factor neighborhood graph
subsetLiger Construct a liger object with a specified subset
suggestK Visually suggest appropiate k value
suggestLambda Visually suggest appropriate lambda value
sumGroups sumGroups
sumGroups.dgCMatrix sumGroups
sumGroups.matrix sumGroups