# Bindings to C++ Libraries for Single-Cell Analysis

## Documentation for package ‘scrapper’ version 1.6.0

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

## Help Pages

scrapper-package | scrapper: Bindings to C++ Libraries for Single-Cell Analysis
adt_quality_control | Quality control for ADT count data
aggregateAcrossCells | Aggregate expression across cells
aggregateAcrossCells.se | Aggregate expression across cells in a SummarizedExperiment
aggregateAcrossGenes | Aggregate expression across genes
aggregateAcrossGenes.se | Aggregate expression across gene sets in a SummarizedExperiment
aggregateColData | Aggregate expression across cells in a SummarizedExperiment
analyze | Analyze single-cell data
analyze.se | Analyze single-cell data from a SummarizedExperiment
buildSnnGraph | Build a shared nearest neighbor graph
centerSizeFactors | Center size factors
chooseHighlyVariableGenes | Choose highly variable genes
choosePseudoCount | Choose a suitable pseudo-count
chooseRnaHvgs.se | Choose highly variable genes from a SummarizedExperiment
clusterGraph | Graph-based clustering of cells
clusterGraph.se | Graph-based clustering of cells in a SingleCellExperiment
clusterKmeans | K-means clustering
clusterKmeans.se | k-means clustering of cells in a SingleCellExperiment
combineFactors | Combine multiple factors
computeAdtQcMetrics | Quality control for ADT count data
computeBlockWeights | Compute block weights
computeClrm1Factors | Compute size factors for ADT counts
computeCrisprQcMetrics | Quality control for CRISPR count data
computeRnaQcMetrics | Quality control for RNA count data
computeRnaQcMetricsWithAltExps | Quick quality control for RNA data in a SummarizedExperiment
convertAnalyzeResults | Convert analysis results into a SingleCellExperiment
correctMnn | Batch correction with mutual nearest neighbors
correctMnn.se | MNN correction on a SingleCellExperiment
countGroupsByBlock | Count cells in groups and blocks
crispr_quality_control | Quality control for CRISPR count data
DelayedArray-method | Delayed log-normalization of a matrix
dim-method | Delayed log-normalization of a matrix
dimnames-method | Delayed log-normalization of a matrix
extract_array-method | Delayed log-normalization of a matrix
extract_sparse_array-method | Delayed log-normalization of a matrix
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
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
getTestAdtData.se | Get datasets for testing
getTestCrisprData.se | Get datasets for testing
getTestData.se | Get datasets for testing
getTestRnaData.se | Get datasets for testing
initializeCpp-method | Delayed log-normalization of a matrix
is_sparse-method | Delayed log-normalization of a matrix
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
matrixClass-method | Delayed log-normalization of a matrix
modelGeneVariances | Model per-gene variances in expression
normalizeAdtCounts.se | Normalize ADT counts in a SummarizedExperiment
normalizeCounts | Normalize the count matrix
normalizeCrisprCounts.se | Normalize CRISPR counts in a SummarizedExperiment
normalizeRnaCounts.se | Normalize RNA counts in a SummarizedExperiment
previewMarkers | Score marker genes in a SummarizedExperiment
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
reportGroupMarkerStatistics | Report marker statistics for a single group
rna_quality_control | Quality control for RNA count data
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
runTsne | t-stochastic neighbor embedding
runTsne.se | t-SNE on a SummarizedExperiment
runUmap | Uniform manifold approximation and projection
runUmap.se | UMAP on a SummarizedExperiment
sanitizeSizeFactors | Sanitize size factors
scaleByNeighbors | Scale and combine multiple embeddings
scaleByNeighbors.se | Scale and combine multiple embeddings in a SingleCellExperiment
scoreGeneSet | Score gene set activity for each cell
scoreGeneSet.se | Score a gene set in a SummarizedExperiment
scoreMarkers | Score marker genes
scoreMarkers.se | Score marker genes in a SummarizedExperiment
scrapper | scrapper: Bindings to C++ Libraries for Single-Cell Analysis
subsampleByNeighbors | Subsample cells based on their neighbors
suggestAdtQcThresholds | Quality control for ADT count data
suggestCrisprQcThresholds | Quality control for CRISPR count data
suggestRnaQcThresholds | Quality control for RNA count data
summarizeEffects | Summarize pairwise effect sizes for each group
testEnrichment | Test for gene set enrichment
tsnePerplexityToNeighbors | t-stochastic neighbor embedding
type-method | Delayed log-normalization of a matrix