Methods for Single-Cell RNA-Seq Data Analysis


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Documentation for package ‘scran’ version 1.8.4

Help Pages

buildKNNGraph Build a nearest-neighbor graph
buildKNNGraph-method Build a nearest-neighbor graph
buildSNNGraph Build a nearest-neighbor graph
buildSNNGraph-method Build a nearest-neighbor graph
clusterModularity Compute the cluster-wise modularity
combineVar Combine variance decompositions
computeSpikeFactors Normalization with spike-in counts
computeSpikeFactors-method Normalization with spike-in counts
computeSumFactors Normalization by deconvolution
computeSumFactors-method Normalization by deconvolution
convertTo Convert to other classes
convertTo-method Convert to other classes
correlateNull Test for significant correlations
correlatePairs Test for significant correlations
correlatePairs-method Test for significant correlations
cyclone Cell cycle phase classification
cyclone-method Cell cycle phase classification
decomposeVar Decompose the gene-level variance
decomposeVar-method Decompose the gene-level variance
denoisePCA Denoise expression with PCA
denoisePCA-method Denoise expression with PCA
DM Compute the distance-to-median statistic
exploreData Shiny app for explorative data analysis
findMarkers Find marker genes
findMarkers-method Find marker genes
improvedCV2 Stably model the technical coefficient of variation
improvedCV2-method Stably model the technical coefficient of variation
makeTechTrend Make a technical trend
mnnCorrect Mutual nearest neighbors correction
multiBlockVar Per-block variance statistics
overlapExprs Overlap expression profiles
overlapExprs-method Overlap expression profiles
parallelPCA Parallel analysis for PCA
parallelPCA-method Parallel analysis for PCA
quickCluster Quick clustering of cells
quickCluster-method Quick clustering of cells
sandbag Cell cycle phase training
sandbag-method Cell cycle phase training
selectorPlot Construct a selector plot via Shiny
technicalCV2 Model the technical coefficient of variation
technicalCV2-method Model the technical coefficient of variation
testVar Test for significantly large variances
trendVar Fit a variance trend
trendVar-method Fit a variance trend