# Methods for Single-Cell RNA-Seq Data Analysis

## Documentation for package ‘scran’ version 1.4.5

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

buildSNNGraph | Build a SNN graph
buildSNNGraph-method | Build a SNN graph
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
isSpike<- | Set spike-in rows
isSpike<--method | Set spike-in rows
mnnCorrect | Mutual nearest neighbors correction
overlapExprs | Overlap expression profiles
overlapExprs-method | Overlap expression profiles
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