Package: scMerge 1.29.0

Yingxin Lin

scMerge: scMerge: Merging multiple batches of scRNA-seq data

Like all gene expression data, single-cell data suffers from batch effects and other unwanted variations that makes accurate biological interpretations difficult. The scMerge method leverages factor analysis, stably expressed genes (SEGs) and (pseudo-) replicates to remove unwanted variations and merge multiple single-cell data. This package contains all the necessary functions in the scMerge pipeline, including the identification of SEGs, replication-identification methods, and merging of single-cell data.

Authors:Yingxin Lin [aut, cre], Kevin Wang [aut], Sydney Bioinformatics and Biometrics Group [fnd]

scMerge_1.29.0.tar.gz
scMerge_1.29.0.zip(r-4.7)scMerge_1.29.0.zip(r-4.6)scMerge_1.29.0.zip(r-4.5)
scMerge_1.29.0.tgz(r-4.6-any)scMerge_1.29.0.tgz(r-4.5-any)
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scMerge_1.29.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
scMerge/json (API)

# Install 'scMerge' in R:
install.packages('scMerge', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sydneybiox/scmerge/issues

Datasets:
  • example_sce - Subsetted mouse ESC 'SingleCellExperiment' object
  • segList - Stably expressed gene list in official gene symbols for both human and mouse
  • segList_ensemblGeneID - Stably expressed gene list in EnsemblGeneID for both human and mouse

On BioConductor:scMerge-1.29.0(bioc 3.24)scMerge-1.28.0(bioc 3.23)

batcheffectgeneexpressionnormalizationrnaseqsequencingsinglecellsoftwaretranscriptomicsbioinformaticssingle-cell

9.98 score 73 stars 2 packages 183 scripts 8 mentions 11 exports 163 dependencies

Last updated from:1e0025846a. Checks:1 FAILURE, 7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksFAILURE250
linux-devel-x86_64WARNING605
source / vignettesOK455
linux-release-x86_64WARNING603
macos-release-arm64WARNING540
macos-oldrel-arm64WARNING387
windows-develWARNING488
windows-releaseWARNING457
windows-oldrelWARNING486
wasm-releaseOK245

Exports:fastRUVIIIgetAdjustedMatruvSimulatesce_cbindscMergescMerge2scMerge2hscReplicatescRUVgscRUVIIIscSEGIndex

Dependencies:abindassortheadbackportsbase64encbatchelorbbmlebdsmatrixbeachmatbeeswarmBHBiobaseBiocGenericsBiocNeighborsBiocParallelBiocSingularbitopsblusterbslibcachemcallrcaToolscheckmatecliclustercodetoolscolorspacecpp11cvToolsdata.tableDelayedArrayDelayedMatrixStatsdensEstBayesDEoptimRdescdigestdistrdistributionaldqrngedgeRevaluatefarverfastmapFNNfontawesomeforeignformatRFormulafsfutile.loggerfutile.optionsgenericsGenomicRangesggbeeswarmggplot2ggrepelgluegplotsgridExtragtablegtoolshighrHmischtmlTablehtmltoolshtmlwidgetsigraphinlineIRangesirlbaisobandjquerylibjsonliteKernSmoothknitrlabelinglambda.rlatticelifecyclelimmalocfitlooM3DropmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemetapodmgcvmimemvtnormnlmennetnumDerivotelpheatmappillarpkgbuildpkgconfigposteriorprocessxproxyCpsQuickJSRR6rappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppMLRcppParallelRcppProgressreldistResidualMatrixrlangrmarkdownrobustbaserpartRSpectrarstanrstantoolsrstudioapirsvdRtsneruvS4ArraysS4VectorsS7sassScaledMatrixscalesscaterscranscuttleSeqinfosfsmiscSingleCellExperimentsitmosnowSparseArraysparseMatrixStatsStanHeadersstartupmsgstatmodstringistringrSummarizedExperimenttensorAtibbletinytexutf8uwotvctrsviporviridisviridisLitewithrxfunXVectoryaml

An introduction to scMerge2
Introduction | Loading Packages and Data | scMerge2 | Unsupervised scMerge2 | Semi-supervised scMerge2 | More details of scMerge2 | Number of pseudobulk | Return matrix by batch | Hierarchical scMerge2 | Scenario 1 | Scenario 2 | Session Info
Rendered fromscMerge2.Rmdusingknitr::rmarkdown

Last update: 2023-08-02
Started: 2022-10-21

An introduction to the scMerge package
Introduction | Loading Packages and Data | Illustrating pseudo-replicates constructions | Unsupervised scMerge | Selecting all cells | Supervised scMerge | Semi-supervised scMerge I | Semi-supervised scMerge II | Selecting negative controls | Achieving fast and memory-efficient computation | Using approximated SVD | Parallelised computing | Sparse array | Out-of-memory computations (through HDF5Array) | Reference | Session Info
Rendered fromscMerge.Rmdusingknitr::rmarkdown

Last update: 2022-10-21
Started: 2018-08-09