Bindings to C++ Libraries for Single-Cell Analysis

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Documentation for package ‘scrapper’ version 1.7.3

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A B C D E F G I L M N P Q R S T

scrapper-package scrapper: Bindings to C++ Libraries for Single-Cell Analysis

-- A --

adt_quality_control Quality control for ADT count data
adt_quality_control_defaults Default parameters for ADT quality control
aggregateAcrossCells Aggregate expression across cells
aggregateAcrossCells.se Aggregate expression across cells in a SummarizedExperiment
aggregateAcrossCellsDefaults Default parameters for 'aggregateAcrossCells'
aggregateAcrossGenes Aggregate expression across genes
aggregateAcrossGenes.se Aggregate expression across gene sets in a SummarizedExperiment
aggregateAcrossGenesDefaults Default parameters for 'aggregateAcrossGenes'
aggregateColData Aggregate expression across cells in a SummarizedExperiment
analyze Defunct functions
analyze.se Analyze single-cell data from a SummarizedExperiment

-- B --

buildSnnGraph Build a shared nearest neighbor graph
buildSnnGraphDefaults Default parameters for 'buildSnnGraph'

-- C --

centerSizeFactors Center size factors
centerSizeFactorsDefaults Default parameters for 'centerSizeFactors'
centerSpikeInFactors Center spike-in size factors
centerSpikeInFactorsDefaults Default parameters for 'centerSpikeInFactors'
chooseHighlyVariableGenes Choose highly variable genes
chooseHighlyVariableGenesDefaults Default parameters for 'chooseHighlyVariableGenes'
choosePseudoCount Choose a suitable pseudo-count
choosePseudoCountDefaults Default parameters for 'choosePseudoCount'
chooseRnaHvgs.se Choose highly variable genes from a SummarizedExperiment
chooseRnaHvgsWithSpikeIns.se Choose highly variable genes based on spike-ins
clusterGraph Graph-based clustering of cells
clusterGraph.se Graph-based clustering of cells in a SingleCellExperiment
clusterGraphDefaults Default parameters for 'clusterGraph'
clusterKmeans K-means clustering
clusterKmeans.se k-means clustering of cells in a SingleCellExperiment
clusterKmeansDefaults Default parameters for 'clusterKmeans'
combineFactors Combine multiple factors
computeAdtQcMetrics Quality control for ADT count data
computeAdtQcMetricsDefaults Default parameters for ADT quality control
computeBlockWeights Compute block weights
computeBlockWeightsDefaults Default parameters for 'computeBlockWeights'
computeClrm1Factors Compute size factors for ADT counts
computeClrm1FactorsDefaults Default parameters for 'computeClrm1Factors'
computeCrisprQcMetrics Quality control for CRISPR count data
computeCrisprQcMetricsDefaults Default parameters for CRISPR quality control
computeRnaQcMetrics Quality control for RNA count data
computeRnaQcMetricsDefaults Default parameters for RNA quality control
computeRnaQcMetricsWithAltExps Quick quality control for RNA data in a SummarizedExperiment
convertAnalyzeResults Defunct functions
correctMnn Batch correction with mutual nearest neighbors
correctMnn.se MNN correction on a SingleCellExperiment
correctMnnDefaults Default parameters for 'correctMnn'
countGroupsByBlock Count cells in groups and blocks
crispr_quality_control Quality control for CRISPR count data
crispr_quality_control_defaults Default parameters for CRISPR quality control

-- D --

DelayedArray-method Delayed log-normalization of a matrix
dim-method Delayed log-normalization of a matrix
dimnames-method Delayed log-normalization of a matrix

-- E --

extract_array-method Delayed log-normalization of a matrix
extract_sparse_array-method Delayed log-normalization of a matrix

-- F --

filterAdtQcMetrics Quality control for ADT count data
filterCrisprQcMetrics Quality control for CRISPR count data
filterRnaQcMetrics Quality control for RNA count data
fitVarianceTrend Fit a mean-variance trend
fitVarianceTrendDefaults Default parameters for 'fitVarianceTrend'
formatComputeAdtQcMetricsResult Quick quality control for ADT data in a SummarizedExperiment
formatComputeCrisprQcMetricsResult Quick quality control for CRISPR data in a SummarizedExperiment
formatComputeRnaQcMetricsResult Quick quality control for RNA data in a SummarizedExperiment
formatModelGeneVariancesResult Choose highly variable genes from a SummarizedExperiment
formatScoreMarkersResult Score marker genes in a SummarizedExperiment

-- G --

getTestAdtData.se Get datasets for testing
getTestCrisprData.se Get datasets for testing
getTestData.se Get datasets for testing
getTestRnaData.se Get datasets for testing

-- I --

initializeCpp-method Delayed log-normalization of a matrix
is_sparse-method Delayed log-normalization of a matrix

-- L --

LogNormalizedMatrix Delayed log-normalization of a matrix
LogNormalizedMatrix-class Delayed log-normalization of a matrix
LogNormalizedMatrixSeed Delayed log-normalization of a matrix
LogNormalizedMatrixSeed-class Delayed log-normalization of a matrix

-- M --

matrixClass-method Delayed log-normalization of a matrix
modelGeneVariances Model per-gene variances in expression
modelGeneVariancesDefaults Default parameters for 'modelGeneVariances'

-- N --

normalizeAdtCounts.se Normalize ADT counts in a SummarizedExperiment
normalizeCounts Normalize the count matrix
normalizeCountsDefaults Default parameters for 'normalizeCounts'
normalizeCrisprCounts.se Normalize CRISPR counts in a SummarizedExperiment
normalizeRnaCounts.se Normalize RNA counts in a SummarizedExperiment
normalizeRnaCountsWithSpikeIns.se Normalize RNA and spike-in counts

-- P --

previewMarkers Score marker genes in a SummarizedExperiment

-- Q --

quickAdtQc.se Quick quality control for ADT data in a SummarizedExperiment
quickCrisprQc.se Quick quality control for CRISPR data in a SummarizedExperiment
quickRnaQc.se Quick quality control for RNA data in a SummarizedExperiment

-- R --

reportGroupMarkerStatistics Report marker statistics for a single group
rna_quality_control Quality control for RNA count data
rna_quality_control_defaults Default parameters for RNA quality control
runAllNeighborSteps Run all neighbor-related steps
runAllNeighborSteps.se Run all nearest neighbor steps on a SummarizedExperiment
runPca Principal components analysis
runPca.se Principal components analysis of a Summarizedexperiment
runPcaDefaults Default parameters for 'runPca'
runTsne t-stochastic neighbor embedding
runTsne.se t-SNE on a SummarizedExperiment
runTsneDefaults Default parameters for 'runTsne'
runUmap Uniform manifold approximation and projection
runUmap.se UMAP on a SummarizedExperiment
runUmapDefaults Default parameters for 'runUmap'

-- S --

sanitizeSizeFactors Sanitize size factors
sanitizeSizeFactorsDefaults Default parameters for 'sanitizeSizeFactors'
scaleByNeighbors Scale and combine multiple embeddings
scaleByNeighbors.se Scale and combine multiple embeddings in a SingleCellExperiment
scaleByNeighborsDefaults Default parameters for 'scaleByNeighbors'
scoreGeneSet Score gene set activity for each cell
scoreGeneSet.se Score a gene set in a SummarizedExperiment
scoreGeneSetDefaults Default parameters for 'scoreGeneSet'
scoreMarkers Score marker genes
scoreMarkers.se Score marker genes in a SummarizedExperiment
scoreMarkersDefaults Default parameters for 'scoreMarkers'
scrapper scrapper: Bindings to C++ Libraries for Single-Cell Analysis
subsampleByNeighbors Subsample cells based on their neighbors
subsampleByNeighborsDefaults Default parameters for 'subsampleByNeighbors'
subsampleByPartition Subsample by partition
subsampleByPartitionDefaults Default parameters for 'subsampleByPartition'
suggestAdtQcThresholds Quality control for ADT count data
suggestAdtQcThresholdsDefaults Default parameters for ADT quality control
suggestCrisprQcThresholds Quality control for CRISPR count data
suggestCrisprQcThresholdsDefaults Default parameters for CRISPR quality control
suggestRnaQcThresholds Quality control for RNA count data
suggestRnaQcThresholdsDefaults Default parameters for RNA quality control
summarizeEffects Summarize pairwise effect sizes for each group
summarizeEffectsDefaults Default parameters for 'summarizeEffectsDefaults'

-- T --

testEnrichment Test for gene set enrichment
testEnrichmentDefaults Default parameters for 'testEnrichment'
tsnePerplexityToNeighbors t-stochastic neighbor embedding
type-method Delayed log-normalization of a matrix