Methods for Single-Cell RNA-Seq Data Analysis


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Documentation for package ‘scran’ version 1.14.6

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bootstrapCluster Assess cluster stability by bootstrapping
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
calculateSumFactors Normalization by deconvolution
calculateSumFactors-method Normalization by deconvolution
cleanSizeFactors Clean size factors
clusterModularity Compute the cluster-wise modularity
combineCV2 Combine variance decompositions
combineMarkers Combine pairwise DE results into a marker list
combinePValues Combine p-values
combineVar Combine variance decompositions
computeSpikeFactors Normalization with spike-in counts
computeSumFactors Normalization by deconvolution
convertTo Convert to other classes
correlateGenes Per-gene correlation statistics
correlateNull Build null 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
denoisePCANumber Denoise expression with PCA
DM Compute the distance-to-median statistic
doubletCells Detect doublet cells
doubletCells-method Detect doublet cells
doubletCluster Detect doublet clusters
doubletCluster-method Detect doublet clusters
findMarkers Find marker genes
findMarkers-method Find marker genes
fitTrendCV2 Fit a trend to the CV2
fitTrendPoisson Generate a trend for Poisson noise
fitTrendVar Fit a trend to the variances of log-counts
getClusteredPCs Use clusters to choose the number of PCs
getDenoisedPCs Denoise expression with PCA
getDenoisedPCs-method Denoise expression with PCA
getTopHVGs Identify HVGs
getTopMarkers Get top markers
improvedCV2 Stably model the technical coefficient of variation
improvedCV2-method Stably model the technical coefficient of variation
makeTechTrend Make a technical trend
modelGeneCV2 Model the per-gene CV2
modelGeneCV2-method Model the per-gene CV2
modelGeneCV2WithSpikes Model the per-gene CV2 with spike-ins
modelGeneCV2WithSpikes-method Model the per-gene CV2 with spike-ins
modelGeneVar Model the per-gene variance
modelGeneVar-method Model the per-gene variance
modelGeneVarByPoisson Model the per-gene variance with Poisson noise
modelGeneVarByPoisson-method Model the per-gene variance with Poisson noise
modelGeneVarWithSpikes Model the per-gene variance with spike-ins
modelGeneVarWithSpikes-method Model the per-gene variance with spike-ins
multiBlockNorm Per-block scaling normalization
multiBlockVar Per-block variance statistics
neighborsToKNNGraph Build a nearest-neighbor graph
neighborsToSNNGraph Build a nearest-neighbor graph
overlapExprs Overlap expression profiles
overlapExprs-method Overlap expression profiles
pairwiseBinom Perform pairwise binomial tests
pairwiseTTests Perform pairwise t-tests
pairwiseWilcox Perform pairwise Wilcoxon rank sum tests
parallelPCA Parallel analysis for PCA
parallelPCA-method Parallel analysis for PCA
quickCluster Quick clustering of cells
quickCluster-method Quick clustering of cells
quickSubCluster Quick and dirty subclustering
quickSubCluster-method Quick and dirty subclustering
sandbag Cell cycle phase training
sandbag-method Cell cycle phase training
scaledColRanks Compute scaled column ranks
scran-gene-selection Gene selection
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