# Single-Cell RNA-Seq Analysis Utilities

## Documentation for package ‘scuttle’ version 1.16.0

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

## Help Pages

.assignIndicesToWorkers | Developer utilities
.bpNotSharedOrUp | Developer utilities
.checkCountMatrix | Developer utilities
.guessMinMean | Developer utilities
.ranksafeQR | Developer utilities
.splitColsByWorkers | Developer utilities
.splitRowsByWorkers | Developer utilities
.splitVectorByWorkers | Developer utilities
.subset2index | Developer utilities
.unpackLists | Developer utilities
addPerCellQC | Add QC metrics to a SummarizedExperiment
addPerCellQCMetrics | Add QC metrics to a SummarizedExperiment
addPerFeatureQC | Add QC metrics to a SummarizedExperiment
addPerFeatureQCMetrics | Add QC metrics to a SummarizedExperiment
aggregateAcrossCells | Aggregate data across groups of cells
aggregateAcrossCells-method | Aggregate data across groups of cells
aggregateAcrossFeatures | Aggregate feature sets in a SummarizedExperiment
calculateAverage | Calculate per-feature average counts
calculateAverage-method | Calculate per-feature average counts
calculateCPM | Calculate CPMs
calculateCPM-method | Calculate CPMs
calculateFPKM | Calculate FPKMs
calculateTPM | Calculate TPMs
calculateTPM-method | Calculate TPMs
cleanSizeFactors | Clean out non-positive size factors
computeGeometricFactors | Compute geometric size factors
computeLibraryFactors | Compute library size factors
computeMedianFactors | Compute median-based size factors
computePooledFactors | Normalization by deconvolution
computeSpikeFactors | Normalization with spike-in counts
correctGroupSummary | Correct group-level summaries
downsampleBatches | Downsample batches to equal coverage
downsampleMatrix | Downsample a count matrix
fitLinearModel | Fit a linear model
geometricSizeFactors | Compute geometric size factors
geometricSizeFactors-method | Compute geometric size factors
isOutlier | Identify outlier values
librarySizeFactors | Compute library size factors
librarySizeFactors-method | Compute library size factors
logNormCounts | Compute log-normalized expression values
logNormCounts-method | Compute log-normalized expression values
makePerCellDF | Create a per-cell data.frame
makePerFeatureDF | Create a per-feature data.frame
medianSizeFactors | Compute median-based size factors
medianSizeFactors-method | Compute median-based size factors
mockSCE | Mock up a SingleCellExperiment
normalizeCounts | Compute normalized expression values
normalizeCounts-method | Compute normalized expression values
numDetectedAcrossCells | Number of detected expression values per group of cells
numDetectedAcrossCells-method | Number of detected expression values per group of cells
numDetectedAcrossFeatures | Number of detected expression values per group of features
numDetectedAcrossFeatures-method | Number of detected expression values per group of features
outlier.filter | Identify outlier values
outlier.filter-class | Identify outlier values
perCellQCFilters | Compute filters for low-quality cells
perCellQCMetrics | Per-cell quality control metrics
perCellQCMetrics-method | Per-cell quality control metrics
perFeatureQCMetrics | Per-feature quality control metrics
perFeatureQCMetrics-method | Per-feature quality control metrics
pooledSizeFactors | Normalization by deconvolution
pooledSizeFactors-method | Normalization by deconvolution
quickPerCellQC | Quick cell-level QC
quickPerCellQC-method | Quick cell-level QC
readSparseCounts | Read sparse count matrix from file
scuttle-pkg | Single-cell utilities
scuttle-utils | Developer utilities
sumCountsAcrossCells | Sum expression across groups of cells
sumCountsAcrossCells-method | Sum expression across groups of cells
sumCountsAcrossFeatures | Sum counts across feature sets
sumCountsAcrossFeatures-method | Sum counts across feature sets
summarizeAssayByGroup | Summarize an assay by group
summarizeAssayByGroup-method | Summarize an assay by group
uniquifyDataFrameByGroup | Groupwise unique rows of a DataFrame
uniquifyFeatureNames | Make feature names unique
[.outlier.filter | Identify outlier values