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: 2026-05-13 05:02:43 -0400 (Wed, 13 May 2026)

EndedAt: 2026-05-13 05:18:45 -0400 (Wed, 13 May 2026)

EllapsedTime: 962.1 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_2.22.0.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: 2026-05-13 09:02:44 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 33.520  0.594  34.116
plotScDblFinderResults   30.663  0.746  29.744
runDoubletFinder         29.819  0.259  30.079
runSeuratSCTransform     28.483  0.242  28.735
runScDblFinder           16.017  0.776  13.825
plotBatchCorrCompare     11.947  0.652  12.600
importExampleData        10.165  1.323  11.823
plotScdsHybridResults     9.058  0.067   8.548
plotBcdsResults           8.206  0.504   8.086
plotDecontXResults        7.971  0.273   8.245
runUMAP                   7.295  0.142   7.437
plotCxdsResults           6.753  0.381   7.135
plotEmptyDropsScatter     6.688  0.042   6.730
plotEmptyDropsResults     6.684  0.031   6.715
runDecontX                6.610  0.101   6.712
runEmptyDrops             6.317  0.009   6.326
plotTSCANClusterDEG       6.110  0.005   6.116
plotUMAP                  5.901  0.147   6.047
detectCellOutlier         5.637  0.113   5.752
plotDEGViolin             5.359  0.231   5.584
* 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%
[05:16:30] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

[05:16:31] 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 
282.746   9.510 290.308

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.002	0.000	0.002
SEG	0.003	0.000	0.003
calcEffectSizes	0.156	0.004	0.160
combineSCE	0.783	0.086	0.869
computeZScore	0.291	0.014	0.306
convertSCEToSeurat	4.579	0.280	4.859
convertSeuratToSCE	0.300	0.001	0.302
dedupRowNames	0.058	0.000	0.059
detectCellOutlier	5.637	0.113	5.752
diffAbundanceFET	0.053	0.001	0.054
discreteColorPalette	0.004	0.000	0.005
distinctColors	0.002	0.000	0.002
downSampleCells	0.499	0.014	0.514
downSampleDepth	0.403	0.004	0.408
expData-ANY-character-method	0.117	0.003	0.118
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.151	0.018	0.170
expData-set	0.152	0.007	0.160
expData	0.126	0.000	0.128
expDataNames-ANY-method	0.111	0.001	0.112
expDataNames	0.117	0.000	0.117
expDeleteDataTag	0.033	0.002	0.033
expSetDataTag	0.024	0.000	0.024
expTaggedData	0.022	0.001	0.025
exportSCE	0.021	0.001	0.021
exportSCEtoAnnData	0.092	0.004	0.097
exportSCEtoFlatFile	0.092	0.003	0.095
featureIndex	0.035	0.000	0.035
generateSimulatedData	0.048	0.001	0.050
getBiomarker	0.056	0.000	0.057
getDEGTopTable	0.687	0.068	0.754
getDiffAbundanceResults	0.045	0.000	0.045
getEnrichRResult	0.528	0.035	2.717
getFindMarkerTopTable	1.571	0.113	1.684
getMSigDBTable	0.003	0.002	0.005
getPathwayResultNames	0.023	0.000	0.023
getSampleSummaryStatsTable	0.270	0.028	0.298
getSoupX	0	0	0
getTSCANResults	1.167	0.083	1.250
getTopHVG	0.728	0.056	0.784
importAnnData	0.001	0.001	0.002
importBUStools	0.149	0.006	0.156
importCellRanger	0.782	0.085	0.868
importCellRangerV2Sample	0.149	0.004	0.153
importCellRangerV3Sample	0.308	0.008	0.316
importDropEst	0.201	0.002	0.204
importExampleData	10.165	1.323	11.823
importGeneSetsFromCollection	0.074	0.009	0.082
importGeneSetsFromGMT	0.062	0.005	0.066
importGeneSetsFromList	0.120	0.005	0.124
importGeneSetsFromMSigDB	2.15	0.26	2.41
importMitoGeneSet	0.053	0.000	0.053
importOptimus	0.002	0.000	0.002
importSEQC	0.108	0.000	0.110
importSTARsolo	0.138	0.001	0.141
iterateSimulations	0.175	0.005	0.181
listSampleSummaryStatsTables	0.339	0.002	0.341
mergeSCEColData	0.332	0.006	0.338
mouseBrainSubsetSCE	0.034	0.002	0.037
msigdb_table	0.001	0.001	0.001
plotBarcodeRankDropsResults	0.873	0.033	0.905
plotBarcodeRankScatter	0.827	0.036	0.863
plotBatchCorrCompare	11.947	0.652	12.600
plotBatchVariance	0.444	0.073	0.516
plotBcdsResults	8.206	0.504	8.086
plotBubble	0.787	0.021	0.808
plotClusterAbundance	1.302	0.021	1.323
plotCxdsResults	6.753	0.381	7.135
plotDEGHeatmap	2.044	0.038	2.082
plotDEGRegression	4.197	0.072	4.264
plotDEGViolin	5.359	0.231	5.584
plotDEGVolcano	0.913	0.013	0.926
plotDecontXResults	7.971	0.273	8.245
plotDimRed	0.270	0.004	0.274
plotDoubletFinderResults	33.520	0.594	34.116
plotEmptyDropsResults	6.684	0.031	6.715
plotEmptyDropsScatter	6.688	0.042	6.730
plotFindMarkerHeatmap	3.869	0.177	4.048
plotMASTThresholdGenes	1.197	0.042	1.238
plotPCA	0.375	0.002	0.377
plotPathway	0.659	0.005	0.665
plotRunPerCellQCResults	3.030	0.020	3.049
plotSCEBarAssayData	0.265	0.003	0.269
plotSCEBarColData	0.215	0.002	0.217
plotSCEBatchFeatureMean	0.373	0.000	0.373
plotSCEDensity	0.301	0.002	0.304
plotSCEDensityAssayData	0.265	0.001	0.266
plotSCEDensityColData	0.328	0.002	0.330
plotSCEDimReduceColData	0.752	0.003	0.756
plotSCEDimReduceFeatures	0.370	0.002	0.372
plotSCEHeatmap	0.438	0.000	0.438
plotSCEScatter	0.338	0.002	0.341
plotSCEViolin	0.344	0.007	0.351
plotSCEViolinAssayData	0.364	0.007	0.371
plotSCEViolinColData	0.349	0.001	0.350
plotScDblFinderResults	30.663	0.746	29.744
plotScanpyDotPlot	0.024	0.000	0.024
plotScanpyEmbedding	0.021	0.002	0.023
plotScanpyHVG	0.022	0.002	0.024
plotScanpyHeatmap	0.021	0.002	0.023
plotScanpyMarkerGenes	0.022	0.002	0.023
plotScanpyMarkerGenesDotPlot	0.021	0.001	0.022
plotScanpyMarkerGenesHeatmap	0.022	0.001	0.023
plotScanpyMarkerGenesMatrixPlot	0.021	0.002	0.022
plotScanpyMarkerGenesViolin	0.022	0.001	0.023
plotScanpyMatrixPlot	0.023	0.000	0.023
plotScanpyPCA	0.023	0.000	0.023
plotScanpyPCAGeneRanking	0.022	0.001	0.023
plotScanpyPCAVariance	0.021	0.001	0.022
plotScanpyViolin	0.022	0.000	0.023
plotScdsHybridResults	9.058	0.067	8.548
plotScrubletResults	0.023	0.000	0.023
plotSeuratElbow	0.022	0.001	0.023
plotSeuratHVG	0.022	0.001	0.024
plotSeuratJackStraw	0.023	0.000	0.022
plotSeuratReduction	0.023	0.000	0.023
plotSoupXResults	0.000	0.000	0.001
plotTSCANClusterDEG	6.110	0.005	6.116
plotTSCANClusterPseudo	1.306	0.025	1.331
plotTSCANDimReduceFeatures	1.290	0.004	1.294
plotTSCANPseudotimeGenes	1.555	0.007	1.562
plotTSCANPseudotimeHeatmap	1.303	0.010	1.313
plotTSCANResults	1.187	0.019	1.206
plotTSNE	0.355	0.002	0.357
plotTopHVG	0.622	0.002	0.624
plotUMAP	5.901	0.147	6.047
readSingleCellMatrix	0.006	0.000	0.006
reportCellQC	0.077	0.000	0.076
reportDropletQC	0.022	0.000	0.021
reportQCTool	0.075	0.000	0.076
retrieveSCEIndex	0.028	0.000	0.028
runBBKNN	0.000	0.001	0.000
runBarcodeRankDrops	0.205	0.001	0.207
runBcds	1.413	0.008	0.881
runCellQC	0.078	0.003	0.081
runClusterSummaryMetrics	0.392	0.000	0.393
runComBatSeq	0.452	0.006	0.458
runCxds	0.301	0.000	0.301
runCxdsBcdsHybrid	1.505	0.022	0.967
runDEAnalysis	0.377	0.025	0.401
runDecontX	6.610	0.101	6.712
runDimReduce	0.269	0.005	0.274
runDoubletFinder	29.819	0.259	30.079
runDropletQC	0.021	0.002	0.022
runEmptyDrops	6.317	0.009	6.326
runEnrichR	0.583	0.050	2.750
runFastMNN	1.681	0.050	1.732
runFeatureSelection	0.209	0.014	0.223
runFindMarker	1.483	0.115	1.598
runGSVA	0.654	0.054	0.708
runHarmony	0.036	0.002	0.038
runKMeans	0.195	0.018	0.213
runLimmaBC	0.080	0.005	0.085
runMNNCorrect	0.388	0.028	0.416
runModelGeneVar	0.291	0.037	0.328
runNormalization	2.234	0.500	2.734
runPerCellQC	0.330	0.009	0.339
runSCANORAMA	0.000	0.001	0.000
runSCMerge	0.003	0.001	0.005
runScDblFinder	16.017	0.776	13.825
runScanpyFindClusters	0.019	0.002	0.021
runScanpyFindHVG	0.020	0.001	0.021
runScanpyFindMarkers	0.021	0.000	0.021
runScanpyNormalizeData	0.093	0.000	0.093
runScanpyPCA	0.021	0.001	0.022
runScanpyScaleData	0.022	0.000	0.022
runScanpyTSNE	0.021	0.001	0.022
runScanpyUMAP	0.021	0.001	0.022
runScranSNN	0.279	0.000	0.279
runScrublet	0.021	0.000	0.022
runSeuratFindClusters	0.017	0.004	0.021
runSeuratFindHVG	0.430	0.002	0.432
runSeuratHeatmap	0.021	0.001	0.022
runSeuratICA	0.020	0.001	0.021
runSeuratJackStraw	0.021	0.001	0.022
runSeuratNormalizeData	0.021	0.000	0.021
runSeuratPCA	0.021	0.000	0.021
runSeuratSCTransform	28.483	0.242	28.735
runSeuratScaleData	0.024	0.000	0.023
runSeuratUMAP	0.022	0.001	0.023
runSingleR	0.038	0.001	0.040
runSoupX	0	0	0
runTSCAN	0.690	0.003	0.694
runTSCANClusterDEAnalysis	0.795	0.009	0.803
runTSCANDEG	0.699	0.007	0.707
runTSNE	0.762	0.014	0.777
runUMAP	7.295	0.142	7.437
runVAM	0.296	0.002	0.298
runZINBWaVE	0.004	0.000	0.004
sampleSummaryStats	0.172	0.001	0.172
scaterCPM	0.159	0.011	0.169
scaterPCA	0.486	0.004	0.490
scaterlogNormCounts	0.241	0.007	0.249
sce	0.022	0.001	0.022
sctkListGeneSetCollections	0.083	0.000	0.084
sctkPythonInstallConda	0.000	0.000	0.001
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0.001	0.000	0.000
setRowNames	0.083	0.003	0.086
setSCTKDisplayRow	0.430	0.005	0.434
singleCellTK	0	0	0
subDiffEx	0.322	0.005	0.327
subsetSCECols	0.076	0.002	0.079
subsetSCERows	0.220	0.001	0.221
summarizeSCE	0.068	0.001	0.070
trimCounts	0.205	0.007	0.214