Back to Build/check report for BioC 3.23:   simplified   long
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This page was generated on 2026-04-27 11:33 -0400 (Mon, 27 Apr 2026).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.4 LTS)x86_644.6.0 RC (2026-04-17 r89917) -- "Because it was There" 4980
Click on any hostname to see more info about the system (e.g. compilers)      (*) as reported by 'uname -p', except on Windows and Mac OS X

Package 2080/2417HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.21.1  (landing page)
Joshua David Campbell
Snapshot Date: 2026-04-26 13:40 -0400 (Sun, 26 Apr 2026)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: devel
git_last_commit: 15d4a13
git_last_commit_date: 2026-01-11 08:42:53 -0400 (Sun, 11 Jan 2026)
nebbiolo1Linux (Ubuntu 24.04.4 LTS) / x86_64  OK    OK    WARNINGS  UNNEEDED, same version is already published
See other builds for singleCellTK in R Universe.


CHECK results for singleCellTK on nebbiolo1

To the developers/maintainers of the singleCellTK package:
- Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/singleCellTK.git to reflect on this report. See Troubleshooting Build Report for more information.
- Use the following Renviron settings to reproduce errors and warnings.
- If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information.

raw results


Summary

Package: singleCellTK
Version: 2.21.1
Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings singleCellTK_2.21.1.tar.gz
StartedAt: 2026-04-27 04:50:04 -0400 (Mon, 27 Apr 2026)
EndedAt: 2026-04-27 05:06:14 -0400 (Mon, 27 Apr 2026)
EllapsedTime: 969.1 seconds
RetCode: 0
Status:   WARNINGS  
CheckDir: singleCellTK.Rcheck
Warnings: 3

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings singleCellTK_2.21.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-04-27 08:50:05 UTC
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.21.1’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 80 non-default packages.
Importing from so many packages makes the package vulnerable to any of
them becoming unavailable.  Move as many as possible to Suggests and
use conditionally.
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘singleCellTK’ can be installed ... OK
* checking installed package size ... INFO
  installed size is  5.6Mb
  sub-directories of 1Mb or more:
    R       1.0Mb
    shiny   2.3Mb
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... WARNING
Missing or unexported object: 'harmony::HarmonyMatrix'
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... WARNING
Missing link(s) in Rd file 'runHarmony.Rd':
  ‘[harmony]{HarmonyMatrix}’

See section 'Cross-references' in the 'Writing R Extensions' manual.

Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
  dedupRowNames.Rd: SingleCellExperiment-class
  detectCellOutlier.Rd: colData
  diffAbundanceFET.Rd: colData
  downSampleCells.Rd: SingleCellExperiment-class
  downSampleDepth.Rd: SingleCellExperiment-class
  featureIndex.Rd: SummarizedExperiment-class,
    SingleCellExperiment-class
  getBiomarker.Rd: SingleCellExperiment-class
  getDEGTopTable.Rd: SingleCellExperiment-class
  getEnrichRResult.Rd: SingleCellExperiment-class
  getFindMarkerTopTable.Rd: SingleCellExperiment-class
  getGenesetNamesFromCollection.Rd: SingleCellExperiment-class
  getPathwayResultNames.Rd: SingleCellExperiment-class
  getSampleSummaryStatsTable.Rd: SingleCellExperiment-class, assay,
    colData
  getSoupX.Rd: SingleCellExperiment-class
  getTSCANResults.Rd: SingleCellExperiment-class
  getTopHVG.Rd: SingleCellExperiment-class
  importAlevin.Rd: DelayedArray, readMM
  importAnnData.Rd: DelayedArray, readMM
  importBUStools.Rd: readMM
  importCellRanger.Rd: readMM, DelayedArray
  importCellRangerV2Sample.Rd: readMM, DelayedArray
  importCellRangerV3Sample.Rd: readMM, DelayedArray
  importDropEst.Rd: DelayedArray, readMM
  importExampleData.Rd: scRNAseq, Matrix, DelayedArray,
    ReprocessedFluidigmData, ReprocessedAllenData, NestorowaHSCData
  importFromFiles.Rd: readMM, DelayedArray, SingleCellExperiment-class
  importGeneSetsFromCollection.Rd: GeneSetCollection-class,
    SingleCellExperiment-class, GeneSetCollection, GSEABase, metadata
  importGeneSetsFromGMT.Rd: GeneSetCollection-class,
    SingleCellExperiment-class, getGmt, GSEABase, metadata
  importGeneSetsFromList.Rd: GeneSetCollection-class,
    SingleCellExperiment-class, GSEABase, metadata
  importGeneSetsFromMSigDB.Rd: SingleCellExperiment-class, msigdbr,
    GeneSetCollection-class, GSEABase, metadata
  importMitoGeneSet.Rd: SingleCellExperiment-class,
    GeneSetCollection-class, GSEABase, metadata
  importMultipleSources.Rd: DelayedArray
  importOptimus.Rd: readMM, DelayedArray
  importSEQC.Rd: readMM, DelayedArray
  importSTARsolo.Rd: readMM, DelayedArray
  iterateSimulations.Rd: SingleCellExperiment-class
  listSampleSummaryStatsTables.Rd: SingleCellExperiment-class, metadata
  plotBarcodeRankDropsResults.Rd: SingleCellExperiment-class
  plotBarcodeRankScatter.Rd: SingleCellExperiment-class
  plotBatchCorrCompare.Rd: SingleCellExperiment-class
  plotBatchVariance.Rd: SingleCellExperiment-class
  plotBcdsResults.Rd: SingleCellExperiment-class
  plotClusterAbundance.Rd: colData
  plotCxdsResults.Rd: SingleCellExperiment-class
  plotDEGHeatmap.Rd: SingleCellExperiment-class
  plotDEGRegression.Rd: SingleCellExperiment-class
  plotDEGViolin.Rd: SingleCellExperiment-class
  plotDEGVolcano.Rd: SingleCellExperiment-class
  plotDecontXResults.Rd: SingleCellExperiment-class
  plotDoubletFinderResults.Rd: SingleCellExperiment-class
  plotEmptyDropsResults.Rd: SingleCellExperiment-class
  plotEmptyDropsScatter.Rd: SingleCellExperiment-class
  plotEnrichR.Rd: SingleCellExperiment-class
  plotFindMarkerHeatmap.Rd: SingleCellExperiment-class
  plotPCA.Rd: SingleCellExperiment-class
  plotPathway.Rd: SingleCellExperiment-class
  plotRunPerCellQCResults.Rd: SingleCellExperiment-class
  plotSCEBarAssayData.Rd: SingleCellExperiment-class
  plotSCEBarColData.Rd: SingleCellExperiment-class
  plotSCEBatchFeatureMean.Rd: SingleCellExperiment-class
  plotSCEDensity.Rd: SingleCellExperiment-class
  plotSCEDensityAssayData.Rd: SingleCellExperiment-class
  plotSCEDensityColData.Rd: SingleCellExperiment-class
  plotSCEDimReduceColData.Rd: SingleCellExperiment-class
  plotSCEDimReduceFeatures.Rd: SingleCellExperiment-class
  plotSCEHeatmap.Rd: SingleCellExperiment-class
  plotSCEScatter.Rd: SingleCellExperiment-class
  plotSCEViolin.Rd: SingleCellExperiment-class
  plotSCEViolinAssayData.Rd: SingleCellExperiment-class
  plotSCEViolinColData.Rd: SingleCellExperiment-class
  plotScDblFinderResults.Rd: SingleCellExperiment-class
  plotScdsHybridResults.Rd: SingleCellExperiment-class
  plotScrubletResults.Rd: SingleCellExperiment-class
  plotSoupXResults.Rd: SingleCellExperiment-class
  plotTSCANClusterDEG.Rd: SingleCellExperiment-class
  plotTSCANClusterPseudo.Rd: SingleCellExperiment-class
  plotTSCANDimReduceFeatures.Rd: SingleCellExperiment-class
  plotTSCANPseudotimeGenes.Rd: SingleCellExperiment-class
  plotTSCANPseudotimeHeatmap.Rd: SingleCellExperiment-class
  plotTSCANResults.Rd: SingleCellExperiment-class
  plotTSNE.Rd: SingleCellExperiment-class
  plotUMAP.Rd: SingleCellExperiment-class
  readSingleCellMatrix.Rd: DelayedArray
  reportCellQC.Rd: SingleCellExperiment-class
  reportClusterAbundance.Rd: colData
  reportDiffAbundanceFET.Rd: colData
  retrieveSCEIndex.Rd: SingleCellExperiment-class
  runBBKNN.Rd: SingleCellExperiment-class
  runBarcodeRankDrops.Rd: SingleCellExperiment-class, colData
  runBcds.Rd: SingleCellExperiment-class, colData
  runCellQC.Rd: colData
  runComBatSeq.Rd: SingleCellExperiment-class
  runCxds.Rd: SingleCellExperiment-class, colData
  runCxdsBcdsHybrid.Rd: colData
  runDEAnalysis.Rd: SingleCellExperiment-class
  runDecontX.Rd: colData
  runDimReduce.Rd: SingleCellExperiment-class
  runDoubletFinder.Rd: SingleCellExperiment-class
  runDropletQC.Rd: colData
  runEmptyDrops.Rd: SingleCellExperiment-class, colData
  runEnrichR.Rd: SingleCellExperiment-class
  runFastMNN.Rd: SingleCellExperiment-class, BiocParallelParam-class
  runFeatureSelection.Rd: SingleCellExperiment-class
  runFindMarker.Rd: SingleCellExperiment-class
  runGSVA.Rd: SingleCellExperiment-class
  runHarmony.Rd: SingleCellExperiment-class
  runKMeans.Rd: SingleCellExperiment-class, colData
  runLimmaBC.Rd: SingleCellExperiment-class, assay
  runMNNCorrect.Rd: SingleCellExperiment-class, assay,
    BiocParallelParam-class
  runModelGeneVar.Rd: SingleCellExperiment-class
  runPerCellQC.Rd: SingleCellExperiment-class, BiocParallelParam,
    colData
  runSCANORAMA.Rd: SingleCellExperiment-class, assay
  runSCMerge.Rd: SingleCellExperiment-class, colData, assay,
    BiocParallelParam-class
  runScDblFinder.Rd: SingleCellExperiment-class, colData
  runScranSNN.Rd: SingleCellExperiment-class, reducedDim, assay,
    altExp, colData, igraph
  runScrublet.Rd: SingleCellExperiment-class, colData
  runSingleR.Rd: SingleCellExperiment-class
  runSoupX.Rd: SingleCellExperiment-class
  runTSCAN.Rd: SingleCellExperiment-class
  runTSCANClusterDEAnalysis.Rd: SingleCellExperiment-class
  runTSCANDEG.Rd: SingleCellExperiment-class
  runTSNE.Rd: SingleCellExperiment-class
  runUMAP.Rd: SingleCellExperiment-class, BiocParallelParam-class
  runVAM.Rd: SingleCellExperiment-class
  runZINBWaVE.Rd: SingleCellExperiment-class, colData,
    BiocParallelParam-class
  sampleSummaryStats.Rd: SingleCellExperiment-class, assay, colData
  scaterPCA.Rd: SingleCellExperiment-class, BiocParallelParam-class
  scaterlogNormCounts.Rd: logNormCounts
  sctkListGeneSetCollections.Rd: GeneSetCollection-class
  sctkPythonInstallConda.Rd: conda_install, reticulate, conda_create
  sctkPythonInstallVirtualEnv.Rd: virtualenv_install, reticulate,
    virtualenv_create
  selectSCTKConda.Rd: reticulate
  selectSCTKVirtualEnvironment.Rd: reticulate
  setRowNames.Rd: SingleCellExperiment-class
  setSCTKDisplayRow.Rd: SingleCellExperiment-class
  singleCellTK.Rd: SingleCellExperiment-class
  subsetSCECols.Rd: SingleCellExperiment-class
  subsetSCERows.Rd: SingleCellExperiment-class, altExp
  summarizeSCE.Rd: SingleCellExperiment-class
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... WARNING
Found the following significant warnings:

  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'librarySizeFactors' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in fitTrendVar(fm, fv, ...) : 'fitTrendVar' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in fitTrendVar(fm, fv, ...) : 'fitTrendVar' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'sumCountsAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'summarizeAssayByGroup' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in fitTrendVar(fm, fv, ...) : 'fitTrendVar' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'librarySizeFactors' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in fitTrendVar(fm, fv, ...) : 'fitTrendVar' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
Deprecated functions may be defunct as soon as of the next release of
R.
See ?Deprecated.
Examples with CPU (user + system) or elapsed time > 5s
                           user system elapsed
plotDoubletFinderResults 34.876  0.122  35.003
runDoubletFinder         31.066  0.004  32.241
runSeuratSCTransform     29.581  0.897  30.482
plotScDblFinderResults   26.526  0.486  24.090
runScDblFinder           17.954  1.138  16.097
plotBatchCorrCompare     11.834  0.292  12.127
importExampleData        10.632  1.134  12.181
plotScdsHybridResults     8.779  0.090   8.243
plotBcdsResults           8.371  0.254   7.988
plotDecontXResults        8.218  0.154   8.373
plotCxdsResults           6.960  0.017   6.978
runUMAP                   6.820  0.134   6.954
detectCellOutlier         6.578  0.169   6.749
plotEmptyDropsResults     6.647  0.009   6.657
plotEmptyDropsScatter     6.631  0.013   6.646
plotDEGViolin             6.289  0.133   6.415
runEmptyDrops             6.310  0.014   6.326
plotUMAP                  6.141  0.012   6.152
runDecontX                5.963  0.003   5.967
convertSCEToSeurat        5.222  0.256   5.479
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘spelling.R’
  Running ‘testthat.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 3 WARNINGs
See
  ‘/home/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.


Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.21.1’
** using staged installation
** R
** data
** exec
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (singleCellTK)

Tests output

singleCellTK.Rcheck/tests/spelling.Rout


R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> if (requireNamespace('spelling', quietly = TRUE))
+   spelling::spell_check_test(vignettes = TRUE, error = FALSE, skip_on_cran = TRUE)
All Done!
> 
> proc.time()
   user  system elapsed 
  0.155   0.045   0.188 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(testthat)
> library(singleCellTK)
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats

Attaching package: 'MatrixGenerics'

The following objects are masked from 'package:matrixStats':

    colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
    colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
    colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
    colWeightedMeans, colWeightedMedians, colWeightedSds,
    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
    rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
    rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
    rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
    rowWeightedSds, rowWeightedVars

Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: generics

Attaching package: 'generics'

The following objects are masked from 'package:base':

    as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
    setequal, union


Attaching package: 'BiocGenerics'

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
    mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
    rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
    unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:utils':

    findMatches

The following objects are masked from 'package:base':

    I, expand.grid, unname

Loading required package: IRanges
Loading required package: Seqinfo
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'Biobase'

The following object is masked from 'package:MatrixGenerics':

    rowMedians

The following objects are masked from 'package:matrixStats':

    anyMissing, rowMedians

Loading required package: SingleCellExperiment
Loading required package: DelayedArray
Loading required package: Matrix

Attaching package: 'Matrix'

The following object is masked from 'package:S4Vectors':

    expand

Loading required package: S4Arrays
Loading required package: abind

Attaching package: 'S4Arrays'

The following object is masked from 'package:abind':

    abind

The following object is masked from 'package:base':

    rowsum

Loading required package: SparseArray

Attaching package: 'DelayedArray'

The following objects are masked from 'package:base':

    apply, scale, sweep


Attaching package: 'singleCellTK'

The following object is masked from 'package:BiocGenerics':

    plotPCA

> 
> test_check("singleCellTK")
Found 2 batches
Using null model in ComBat-seq.
Adjusting for 0 covariate(s) or covariate level(s)
Estimating dispersions
Fitting the GLM model
Shrinkage off - using GLM estimates for parameters
Adjusting the data
Found 2 batches
Using null model in ComBat-seq.
Adjusting for 1 covariate(s) or covariate level(s)
Estimating dispersions
Fitting the GLM model
Shrinkage off - using GLM estimates for parameters
Adjusting the data
Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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  |======================================================================| 100%

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Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Uploading data to Enrichr... Done.
  Querying HDSigDB_Human_2021... Done.
Parsing results... Done.
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
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  |======================================================================| 100%
[05:04:05] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

[05:04:06] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
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  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
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  |======================================================================| 100%

  |                                                                            
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  |======================================================================| 100%
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 390
Number of edges: 9849

Running Louvain algorithm...
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Maximum modularity in 10 random starts: 0.8351
Number of communities: 7
Elapsed time: 0 seconds
Using method 'umap'
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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  |======================================================================| 100%

  |                                                                            
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  |======================================================================| 100%
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
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  |                                                                            
  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 84 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 84 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
275.081  10.214 283.130 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0010.0000.002
SEG0.0020.0020.003
calcEffectSizes0.1540.0060.160
combineSCE0.7820.0970.880
computeZScore0.2920.0140.306
convertSCEToSeurat5.2220.2565.479
convertSeuratToSCE0.3280.0090.337
dedupRowNames0.0590.0010.061
detectCellOutlier6.5780.1696.749
diffAbundanceFET0.0560.0010.058
discreteColorPalette0.0060.0000.006
distinctColors0.0020.0000.002
downSampleCells0.5240.0160.541
downSampleDepth0.4180.0050.424
expData-ANY-character-method0.1250.0010.127
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1660.0020.167
expData-set0.1540.0000.154
expData0.1250.0010.126
expDataNames-ANY-method0.1190.0010.120
expDataNames0.1220.0010.122
expDeleteDataTag0.0340.0010.034
expSetDataTag0.0250.0000.025
expTaggedData0.0270.0000.027
exportSCE0.0230.0000.024
exportSCEtoAnnData0.0960.0030.098
exportSCEtoFlatFile0.0910.0060.098
featureIndex0.0370.0000.038
generateSimulatedData0.0530.0000.052
getBiomarker0.0590.0030.061
getDEGTopTable0.7370.0640.802
getDiffAbundanceResults0.0520.0000.053
getEnrichRResult0.5850.0522.804
getFindMarkerTopTable1.6070.1201.728
getMSigDBTable0.0030.0020.005
getPathwayResultNames0.0210.0030.024
getSampleSummaryStatsTable0.2800.0150.294
getSoupX000
getTSCANResults1.1550.1331.289
getTopHVG0.7720.0600.832
importAnnData0.0020.0010.001
importBUStools0.1540.0130.168
importCellRanger0.7720.0630.838
importCellRangerV2Sample0.1590.0110.170
importCellRangerV3Sample0.3070.0150.322
importDropEst0.1930.0020.195
importExampleData10.632 1.13412.181
importGeneSetsFromCollection0.0760.0010.078
importGeneSetsFromGMT0.0650.0010.066
importGeneSetsFromList0.1300.0070.137
importGeneSetsFromMSigDB2.2050.0712.277
importMitoGeneSet0.0520.0020.053
importOptimus0.0010.0000.002
importSEQC0.1080.0030.110
importSTARsolo0.1420.0010.143
iterateSimulations0.1660.0040.170
listSampleSummaryStatsTables0.2910.0020.292
mergeSCEColData0.3330.0030.335
mouseBrainSubsetSCE0.0370.0000.038
msigdb_table0.0000.0010.002
plotBarcodeRankDropsResults0.9050.0130.919
plotBarcodeRankScatter0.7990.0020.802
plotBatchCorrCompare11.834 0.29212.127
plotBatchVariance0.4520.0890.541
plotBcdsResults8.3710.2547.988
plotBubble0.8090.0050.813
plotClusterAbundance1.3700.0011.372
plotCxdsResults6.9600.0176.978
plotDEGHeatmap2.0220.0042.026
plotDEGRegression4.1510.0414.185
plotDEGViolin6.2890.1336.415
plotDEGVolcano0.8850.0080.894
plotDecontXResults8.2180.1548.373
plotDimRed0.2970.0040.301
plotDoubletFinderResults34.876 0.12235.003
plotEmptyDropsResults6.6470.0096.657
plotEmptyDropsScatter6.6310.0136.646
plotFindMarkerHeatmap3.7200.0263.746
plotMASTThresholdGenes1.2460.0441.291
plotPCA0.3580.0160.374
plotPathway0.6560.0100.666
plotRunPerCellQCResults2.9270.0072.934
plotSCEBarAssayData0.2580.0020.261
plotSCEBarColData0.2190.0010.220
plotSCEBatchFeatureMean0.3860.0000.385
plotSCEDensity0.2980.0030.301
plotSCEDensityAssayData0.2700.0010.272
plotSCEDensityColData0.3180.0000.317
plotSCEDimReduceColData0.7030.0010.704
plotSCEDimReduceFeatures0.3640.0010.365
plotSCEHeatmap0.4670.0020.470
plotSCEScatter0.3640.0040.369
plotSCEViolin0.3790.0130.392
plotSCEViolinAssayData0.3830.0080.391
plotSCEViolinColData0.3580.0080.365
plotScDblFinderResults26.526 0.48624.090
plotScanpyDotPlot0.0220.0000.022
plotScanpyEmbedding0.0210.0000.021
plotScanpyHVG0.0200.0010.021
plotScanpyHeatmap0.0190.0020.021
plotScanpyMarkerGenes0.0210.0000.021
plotScanpyMarkerGenesDotPlot0.0210.0000.021
plotScanpyMarkerGenesHeatmap0.0190.0020.021
plotScanpyMarkerGenesMatrixPlot0.0200.0010.021
plotScanpyMarkerGenesViolin0.0200.0020.021
plotScanpyMatrixPlot0.0210.0000.021
plotScanpyPCA0.0210.0000.021
plotScanpyPCAGeneRanking0.0190.0020.021
plotScanpyPCAVariance0.0190.0020.021
plotScanpyViolin0.0190.0020.021
plotScdsHybridResults8.7790.0908.243
plotScrubletResults0.0220.0000.022
plotSeuratElbow0.0210.0000.021
plotSeuratHVG0.0210.0000.022
plotSeuratJackStraw0.0210.0000.021
plotSeuratReduction0.0210.0010.021
plotSoupXResults0.0000.0010.000
plotTSCANClusterDEG4.5740.0104.584
plotTSCANClusterPseudo1.3760.0041.381
plotTSCANDimReduceFeatures1.3060.0051.312
plotTSCANPseudotimeGenes1.5640.0071.571
plotTSCANPseudotimeHeatmap1.2960.0041.300
plotTSCANResults1.1900.0071.197
plotTSNE0.3530.0010.353
plotTopHVG0.6260.0010.627
plotUMAP6.1410.0126.152
readSingleCellMatrix0.0060.0000.005
reportCellQC0.0760.0010.076
reportDropletQC0.0210.0010.022
reportQCTool0.0750.0000.076
retrieveSCEIndex0.0260.0010.027
runBBKNN0.0000.0010.000
runBarcodeRankDrops0.2070.0020.209
runBcds1.4210.0470.918
runCellQC0.0770.0010.078
runClusterSummaryMetrics0.3750.0030.378
runComBatSeq0.4590.0050.464
runCxds0.3080.0000.309
runCxdsBcdsHybrid1.4810.0450.966
runDEAnalysis0.3650.0040.369
runDecontX5.9630.0035.967
runDimReduce0.2700.0020.272
runDoubletFinder31.066 0.00432.241
runDropletQC0.0220.0000.022
runEmptyDrops6.3100.0146.326
runEnrichR0.4440.0182.438
runFastMNN1.6660.0111.678
runFeatureSelection0.2080.0020.211
runFindMarker1.4320.0951.528
runGSVA0.6590.0880.747
runHarmony0.0400.0050.044
runKMeans0.2290.0350.263
runLimmaBC0.0770.0130.090
runMNNCorrect0.3790.0300.409
runModelGeneVar0.2770.0170.295
runNormalization2.2210.3432.563
runPerCellQC0.3270.0040.329
runSCANORAMA0.0010.0000.000
runSCMerge0.0030.0000.004
runScDblFinder17.954 1.13816.097
runScanpyFindClusters0.0210.0010.023
runScanpyFindHVG0.0200.0020.022
runScanpyFindMarkers0.0200.0020.022
runScanpyNormalizeData0.0940.0020.096
runScanpyPCA0.0200.0020.023
runScanpyScaleData0.0210.0000.022
runScanpyTSNE0.0220.0000.022
runScanpyUMAP0.0220.0000.022
runScranSNN0.2820.0040.287
runScrublet0.0210.0020.023
runSeuratFindClusters0.0220.0000.021
runSeuratFindHVG0.4640.0050.469
runSeuratHeatmap0.0220.0000.022
runSeuratICA0.0210.0010.022
runSeuratJackStraw0.0220.0000.022
runSeuratNormalizeData0.0220.0000.022
runSeuratPCA0.0220.0000.022
runSeuratSCTransform29.581 0.89730.482
runSeuratScaleData0.0210.0030.025
runSeuratUMAP0.0230.0010.023
runSingleR0.0390.0000.039
runSoupX0.0000.0000.001
runTSCAN0.6520.0050.658
runTSCANClusterDEAnalysis0.7790.0210.800
runTSCANDEG0.6920.0030.696
runTSNE0.7440.0030.747
runUMAP6.8200.1346.954
runVAM0.2780.0000.278
runZINBWaVE0.0040.0000.005
sampleSummaryStats0.1520.0010.153
scaterCPM0.1510.0030.154
scaterPCA0.4360.0010.437
scaterlogNormCounts0.2260.0090.235
sce0.0210.0010.022
sctkListGeneSetCollections0.0790.0010.081
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv0.0010.0000.001
selectSCTKConda0.0000.0010.000
selectSCTKVirtualEnvironment000
setRowNames0.0820.0010.082
setSCTKDisplayRow0.4350.0000.435
singleCellTK0.0000.0010.000
subDiffEx0.3100.0060.316
subsetSCECols0.0750.0010.076
subsetSCERows0.2050.0020.207
summarizeSCE0.0680.0000.068
trimCounts0.2030.0020.205