Build/check report for BioC 3.23 - CHECK results for singleCellTK on nebbiolo1

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo1	Linux (Ubuntu 24.04.4 LTS)	x86_64	4.6.0 RC (2026-04-17 r89917) -- "Because it was There"	4994
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*

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: 2.22.0

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_2.22.0.tar.gz

StartedAt: 2026-05-16 04:54:39 -0400 (Sat, 16 May 2026)

EndedAt: 2026-05-16 05:11:08 -0400 (Sat, 16 May 2026)

EllapsedTime: 989.3 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_2.22.0.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: 2026-05-16 08:54:40 UTC
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.22.0’
* 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 35.421  0.221  35.646
runDoubletFinder         30.790  0.009  30.801
runSeuratSCTransform     29.317  0.515  29.840
plotScDblFinderResults   28.565  0.447  26.071
runScDblFinder           16.687  1.037  14.728
plotBatchCorrCompare     11.925  0.288  12.215
importExampleData        10.271  1.034  11.730
plotScdsHybridResults     9.116  0.122   8.600
plotDecontXResults        8.625  0.179   8.805
plotBcdsResults           8.297  0.300   7.954
plotCxdsResults           6.940  0.028   6.969
plotEmptyDropsResults     6.631  0.016   6.647
plotEmptyDropsScatter     6.619  0.003   6.622
runUMAP                   6.460  0.156   6.615
runEmptyDrops             6.329  0.017   6.347
plotUMAP                  6.312  0.009   6.321
plotTSCANClusterDEG       6.256  0.005   6.262
runDecontX                6.161  0.008   6.171
detectCellOutlier         5.983  0.101   6.084
plotDEGViolin             5.236  0.071   5.301
* 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 ‘2.22.0’
** 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 
  0.153   0.040   0.178

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
[05:08:55] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

[05:08:56] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 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 
287.185   7.939 292.991

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.002	0.001	0.002
SEG	0.001	0.001	0.003
calcEffectSizes	0.157	0.005	0.162
combineSCE	0.771	0.086	0.858
computeZScore	0.310	0.012	0.323
convertSCEToSeurat	4.803	0.168	4.971
convertSeuratToSCE	0.320	0.001	0.322
dedupRowNames	0.062	0.001	0.063
detectCellOutlier	5.983	0.101	6.084
diffAbundanceFET	0.053	0.001	0.054
discreteColorPalette	0.006	0.000	0.005
distinctColors	0.000	0.001	0.002
downSampleCells	0.520	0.003	0.522
downSampleDepth	0.420	0.006	0.425
expData-ANY-character-method	0.12	0.00	0.12
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.159	0.001	0.160
expData-set	0.151	0.002	0.153
expData	0.128	0.000	0.128
expDataNames-ANY-method	0.115	0.001	0.117
expDataNames	0.119	0.001	0.119
expDeleteDataTag	0.033	0.000	0.034
expSetDataTag	0.025	0.000	0.025
expTaggedData	0.026	0.000	0.026
exportSCE	0.022	0.001	0.023
exportSCEtoAnnData	0.092	0.005	0.098
exportSCEtoFlatFile	0.094	0.003	0.097
featureIndex	0.034	0.002	0.037
generateSimulatedData	0.053	0.001	0.054
getBiomarker	0.061	0.000	0.060
getDEGTopTable	0.693	0.066	0.759
getDiffAbundanceResults	0.047	0.001	0.047
getEnrichRResult	0.477	0.025	2.846
getFindMarkerTopTable	1.578	0.096	1.675
getMSigDBTable	0.002	0.002	0.005
getPathwayResultNames	0.022	0.000	0.022
getSampleSummaryStatsTable	0.258	0.035	0.292
getSoupX	0.001	0.000	0.000
getTSCANResults	1.060	0.115	1.174
getTopHVG	0.729	0.058	0.787
importAnnData	0.002	0.000	0.001
importBUStools	0.162	0.018	0.181
importCellRanger	0.752	0.079	0.833
importCellRangerV2Sample	0.150	0.001	0.152
importCellRangerV3Sample	0.296	0.006	0.303
importDropEst	0.197	0.001	0.200
importExampleData	10.271	1.034	11.730
importGeneSetsFromCollection	0.075	0.002	0.077
importGeneSetsFromGMT	0.064	0.002	0.066
importGeneSetsFromList	0.124	0.002	0.125
importGeneSetsFromMSigDB	2.210	0.073	2.283
importMitoGeneSet	0.050	0.003	0.053
importOptimus	0.001	0.001	0.001
importSEQC	0.109	0.002	0.112
importSTARsolo	0.145	0.000	0.146
iterateSimulations	0.170	0.002	0.172
listSampleSummaryStatsTables	0.289	0.001	0.290
mergeSCEColData	0.340	0.001	0.340
mouseBrainSubsetSCE	0.036	0.002	0.039
msigdb_table	0.001	0.001	0.002
plotBarcodeRankDropsResults	0.914	0.009	0.925
plotBarcodeRankScatter	0.812	0.001	0.814
plotBatchCorrCompare	11.925	0.288	12.215
plotBatchVariance	0.434	0.078	0.512
plotBcdsResults	8.297	0.300	7.954
plotBubble	0.828	0.007	0.836
plotClusterAbundance	1.387	0.003	1.390
plotCxdsResults	6.940	0.028	6.969
plotDEGHeatmap	2.074	0.021	2.096
plotDEGRegression	4.121	0.043	4.159
plotDEGViolin	5.236	0.071	5.301
plotDEGVolcano	0.942	0.009	0.952
plotDecontXResults	8.625	0.179	8.805
plotDimRed	0.268	0.000	0.269
plotDoubletFinderResults	35.421	0.221	35.646
plotEmptyDropsResults	6.631	0.016	6.647
plotEmptyDropsScatter	6.619	0.003	6.622
plotFindMarkerHeatmap	3.950	0.045	3.995
plotMASTThresholdGenes	1.21	0.01	1.22
plotPCA	0.379	0.006	0.385
plotPathway	0.697	0.006	0.704
plotRunPerCellQCResults	2.934	0.003	2.937
plotSCEBarAssayData	0.271	0.000	0.271
plotSCEBarColData	0.215	0.001	0.216
plotSCEBatchFeatureMean	0.373	0.002	0.376
plotSCEDensity	0.298	0.003	0.302
plotSCEDensityAssayData	0.257	0.002	0.259
plotSCEDensityColData	0.306	0.019	0.325
plotSCEDimReduceColData	0.743	0.022	0.764
plotSCEDimReduceFeatures	0.376	0.006	0.383
plotSCEHeatmap	0.442	0.013	0.455
plotSCEScatter	0.356	0.001	0.357
plotSCEViolin	0.371	0.002	0.373
plotSCEViolinAssayData	0.378	0.003	0.381
plotSCEViolinColData	0.343	0.002	0.345
plotScDblFinderResults	28.565	0.447	26.071
plotScanpyDotPlot	0.022	0.001	0.023
plotScanpyEmbedding	0.022	0.000	0.022
plotScanpyHVG	0.020	0.001	0.022
plotScanpyHeatmap	0.022	0.000	0.022
plotScanpyMarkerGenes	0.022	0.001	0.022
plotScanpyMarkerGenesDotPlot	0.020	0.002	0.022
plotScanpyMarkerGenesHeatmap	0.022	0.000	0.021
plotScanpyMarkerGenesMatrixPlot	0.021	0.000	0.022
plotScanpyMarkerGenesViolin	0.021	0.001	0.022
plotScanpyMatrixPlot	0.021	0.001	0.021
plotScanpyPCA	0.022	0.000	0.022
plotScanpyPCAGeneRanking	0.021	0.000	0.021
plotScanpyPCAVariance	0.022	0.000	0.022
plotScanpyViolin	0.019	0.002	0.022
plotScdsHybridResults	9.116	0.122	8.600
plotScrubletResults	0.022	0.000	0.022
plotSeuratElbow	0.023	0.000	0.022
plotSeuratHVG	0.022	0.000	0.023
plotSeuratJackStraw	0.022	0.001	0.023
plotSeuratReduction	0.023	0.000	0.023
plotSoupXResults	0	0	0
plotTSCANClusterDEG	6.256	0.005	6.262
plotTSCANClusterPseudo	1.349	0.008	1.358
plotTSCANDimReduceFeatures	1.323	0.003	1.325
plotTSCANPseudotimeGenes	1.601	0.002	1.604
plotTSCANPseudotimeHeatmap	1.322	0.008	1.334
plotTSCANResults	1.236	0.006	1.242
plotTSNE	0.410	0.000	0.411
plotTopHVG	0.658	0.004	0.661
plotUMAP	6.312	0.009	6.321
readSingleCellMatrix	0.004	0.001	0.005
reportCellQC	0.078	0.002	0.079
reportDropletQC	0.019	0.003	0.022
reportQCTool	0.077	0.002	0.079
retrieveSCEIndex	0.028	0.001	0.029
runBBKNN	0.000	0.000	0.001
runBarcodeRankDrops	0.222	0.002	0.225
runBcds	1.477	0.063	0.948
runCellQC	0.081	0.000	0.081
runClusterSummaryMetrics	0.386	0.002	0.388
runComBatSeq	0.468	0.006	0.474
runCxds	0.300	0.002	0.302
runCxdsBcdsHybrid	1.517	0.054	0.982
runDEAnalysis	0.361	0.000	0.361
runDecontX	6.161	0.008	6.171
runDimReduce	0.282	0.003	0.286
runDoubletFinder	30.790	0.009	30.801
runDropletQC	0.023	0.000	0.022
runEmptyDrops	6.329	0.017	6.347
runEnrichR	0.501	0.027	2.679
runFastMNN	1.676	0.031	1.707
runFeatureSelection	0.209	0.002	0.210
runFindMarker	1.474	0.004	1.480
runGSVA	0.631	0.022	0.653
runHarmony	0.037	0.002	0.039
runKMeans	0.207	0.027	0.234
runLimmaBC	0.081	0.001	0.081
runMNNCorrect	0.398	0.021	0.419
runModelGeneVar	0.287	0.027	0.314
runNormalization	2.375	0.493	2.870
runPerCellQC	0.331	0.007	0.338
runSCANORAMA	0.001	0.000	0.001
runSCMerge	0.003	0.001	0.004
runScDblFinder	16.687	1.037	14.728
runScanpyFindClusters	0.032	0.008	0.039
runScanpyFindHVG	0.037	0.003	0.042
runScanpyFindMarkers	0.031	0.003	0.034
runScanpyNormalizeData	0.169	0.004	0.173
runScanpyPCA	0.311	0.005	0.321
runScanpyScaleData	0.625	0.012	0.870
runScanpyTSNE	0.623	0.094	0.730
runScanpyUMAP	0.591	0.007	0.599
runScranSNN	1.796	0.044	1.850
runScrublet	0.023	0.000	0.023
runSeuratFindClusters	0.022	0.000	0.022
runSeuratFindHVG	0.452	0.007	0.459
runSeuratHeatmap	0.022	0.000	0.022
runSeuratICA	0.021	0.001	0.022
runSeuratJackStraw	0.023	0.000	0.022
runSeuratNormalizeData	0.019	0.003	0.022
runSeuratPCA	0.021	0.001	0.022
runSeuratSCTransform	29.317	0.515	29.840
runSeuratScaleData	0.023	0.001	0.023
runSeuratUMAP	0.023	0.000	0.023
runSingleR	0.038	0.000	0.038
runSoupX	0	0	0
runTSCAN	0.661	0.025	0.685
runTSCANClusterDEAnalysis	0.796	0.031	0.826
runTSCANDEG	0.688	0.002	0.689
runTSNE	0.741	0.003	0.744
runUMAP	6.460	0.156	6.615
runVAM	0.286	0.000	0.286
runZINBWaVE	0.005	0.000	0.005
sampleSummaryStats	0.150	0.002	0.152
scaterCPM	0.149	0.006	0.154
scaterPCA	0.430	0.001	0.431
scaterlogNormCounts	0.233	0.009	0.242
sce	0.020	0.001	0.021
sctkListGeneSetCollections	0.076	0.006	0.082
sctkPythonInstallConda	0.000	0.001	0.001
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.088	0.003	0.091
setSCTKDisplayRow	0.423	0.004	0.427
singleCellTK	0	0	0
subDiffEx	0.325	0.003	0.328
subsetSCECols	0.083	0.002	0.084
subsetSCERows	0.217	0.002	0.219
summarizeSCE	0.066	0.000	0.066
trimCounts	0.193	0.008	0.200