Package: scuttle 1.17.0
Aaron Lun
scuttle: Single-Cell RNA-Seq Analysis Utilities
Provides basic utility functions for performing single-cell analyses, focusing on simple normalization, quality control and data transformations. Also provides some helper functions to assist development of other packages.
Authors:
scuttle_1.17.0.tar.gz
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scuttle.pdf |scuttle.html✨
scuttle/json (API)
NEWS
| # Install 'scuttle' in R: |
| install.packages('scuttle', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:scuttle-1.17.0(bioc 3.21)scuttle-1.16.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
immunooncologysinglecellrnaseqqualitycontrolpreprocessingnormalizationtranscriptomicsgeneexpressionsequencingsoftwaredataimport
Last updated 25 days agofrom:59306653a2. Checks:OK: 1 NOTE: 1 ERROR: 2 WARNING: 5. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-win-x86_64 | WARNING | Oct 31 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 31 2024 |
| R-4.4-win-x86_64 | WARNING | Oct 31 2024 |
| R-4.4-mac-x86_64 | WARNING | Oct 31 2024 |
| R-4.4-mac-aarch64 | ERROR | Oct 31 2024 |
| R-4.3-win-x86_64 | WARNING | Oct 31 2024 |
| R-4.3-mac-x86_64 | WARNING | Oct 31 2024 |
| R-4.3-mac-aarch64 | ERROR | Oct 31 2024 |
Exports:.assignIndicesToWorkers.bpNotSharedOrUp.guessMinMean.ranksafeQR.splitColsByWorkers.splitRowsByWorkers.splitVectorByWorkers.subset2index.unpackListsaddPerCellQCaddPerCellQCMetricsaddPerFeatureQCaddPerFeatureQCMetricsaggregateAcrossCellsaggregateAcrossFeaturescalculateAveragecalculateCPMcalculateFPKMcalculateTPMcleanSizeFactorscomputeGeometricFactorscomputeLibraryFactorscomputeMedianFactorscomputePooledFactorscomputeSpikeFactorscorrectGroupSummarydownsampleBatchesdownsampleMatrixfitLinearModelgeometricSizeFactorsisOutlierlibrarySizeFactorslogNormCountsmakePerCellDFmakePerFeatureDFmedianSizeFactorsmockSCEnormalizeCountsnumDetectedAcrossCellsnumDetectedAcrossFeaturesoutlier.filterperCellQCFiltersperCellQCMetricsperFeatureQCMetricspooledSizeFactorsquickPerCellQCreadSparseCountssumCountsAcrossCellssumCountsAcrossFeaturessummarizeAssayByGroupuniquifyDataFrameByGroupuniquifyFeatureNameswhichNonZero
Dependencies:abindaskpassassortheadbeachmatBHBiobaseBiocGenericsBiocParallelcodetoolscpp11crayoncurlDelayedArrayformatRfutile.loggerfutile.optionsGenomeInfoDbGenomeInfoDbDataGenomicRangeshttrIRangesjsonlitelambda.rlatticeMatrixMatrixGenericsmatrixStatsmimeopensslR6RcppS4ArraysS4VectorsSingleCellExperimentsnowSparseArraySummarizedExperimentsysUCSC.utilsXVectorzlibbioc
Quality control for single-cell RNA-seq data
Rendered fromqc.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2021-02-06
Started: 2021-02-06
Normalizing single-cell RNA-seq data
Rendered fromnorm.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2021-02-07
Started: 2021-02-06
Other single-cell RNA-seq analysis utilities
Rendered frommisc.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2024-03-05
Started: 2021-02-06
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Add QC metrics to a SummarizedExperiment | addPerCellQC addPerCellQCMetrics addPerFeatureQC addPerFeatureQCMetrics |
| Aggregate data across groups of cells | aggregateAcrossCells aggregateAcrossCells,SingleCellExperiment-method aggregateAcrossCells,SummarizedExperiment-method |
| Aggregate feature sets in a SummarizedExperiment | aggregateAcrossFeatures |
| Calculate per-feature average counts | calculateAverage calculateAverage,ANY-method calculateAverage,SingleCellExperiment-method calculateAverage,SummarizedExperiment-method |
| Calculate CPMs | calculateCPM calculateCPM,ANY-method calculateCPM,SingleCellExperiment-method calculateCPM,SummarizedExperiment-method |
| Calculate FPKMs | calculateFPKM |
| Calculate TPMs | calculateTPM calculateTPM,ANY-method calculateTPM,SingleCellExperiment-method calculateTPM,SummarizedExperiment-method |
| Clean out non-positive size factors | cleanSizeFactors |
| Normalization by deconvolution | computePooledFactors pooledSizeFactors pooledSizeFactors,ANY-method pooledSizeFactors,SummarizedExperiment-method |
| Normalization with spike-in counts | computeSpikeFactors |
| Correct group-level summaries | correctGroupSummary |
| Downsample batches to equal coverage | downsampleBatches |
| Downsample a count matrix | downsampleMatrix |
| Fit a linear model | fitLinearModel |
| Compute geometric size factors | computeGeometricFactors geometricSizeFactors geometricSizeFactors,ANY-method geometricSizeFactors,SummarizedExperiment-method |
| Identify outlier values | isOutlier outlier.filter outlier.filter-class [.outlier.filter |
| Compute library size factors | computeLibraryFactors librarySizeFactors librarySizeFactors,ANY-method librarySizeFactors,SummarizedExperiment-method |
| Compute log-normalized expression values | logNormCounts logNormCounts,SingleCellExperiment-method logNormCounts,SummarizedExperiment-method |
| Create a per-cell data.frame | makePerCellDF |
| Create a per-feature data.frame | makePerFeatureDF |
| Compute median-based size factors | computeMedianFactors medianSizeFactors medianSizeFactors,ANY-method medianSizeFactors,SummarizedExperiment-method |
| Mock up a SingleCellExperiment | mockSCE |
| Compute normalized expression values | normalizeCounts normalizeCounts,ANY-method normalizeCounts,SingleCellExperiment-method normalizeCounts,SummarizedExperiment-method |
| Number of detected expression values per group of cells | numDetectedAcrossCells numDetectedAcrossCells,ANY-method numDetectedAcrossCells,SummarizedExperiment-method |
| Number of detected expression values per group of features | numDetectedAcrossFeatures numDetectedAcrossFeatures,ANY-method numDetectedAcrossFeatures,SummarizedExperiment-method |
| Compute filters for low-quality cells | perCellQCFilters |
| Per-cell quality control metrics | perCellQCMetrics perCellQCMetrics,ANY-method perCellQCMetrics,SingleCellExperiment-method perCellQCMetrics,SummarizedExperiment-method |
| Per-feature quality control metrics | perFeatureQCMetrics perFeatureQCMetrics,ANY-method perFeatureQCMetrics,SummarizedExperiment-method |
| Quick cell-level QC | quickPerCellQC quickPerCellQC,ANY-method quickPerCellQC,SummarizedExperiment-method |
| Read sparse count matrix from file | readSparseCounts |
| Single-cell utilities | scuttle-pkg |
| Developer utilities | .assignIndicesToWorkers .bpNotSharedOrUp .checkCountMatrix .guessMinMean .ranksafeQR .splitColsByWorkers .splitRowsByWorkers .splitVectorByWorkers .subset2index .unpackLists scuttle-utils |
| Sum expression across groups of cells | sumCountsAcrossCells sumCountsAcrossCells,ANY-method sumCountsAcrossCells,SummarizedExperiment-method |
| Sum counts across feature sets | sumCountsAcrossFeatures sumCountsAcrossFeatures,ANY-method sumCountsAcrossFeatures,SummarizedExperiment-method |
| Summarize an assay by group | summarizeAssayByGroup summarizeAssayByGroup,ANY-method summarizeAssayByGroup,SummarizedExperiment-method |
| Groupwise unique rows of a DataFrame | uniquifyDataFrameByGroup |
| Make feature names unique | uniquifyFeatureNames |
