Multiple platform build/check report for BioC 3.21 - CHECK results for singleCellTK on merida1

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo1	Linux (Ubuntu 24.04.3 LTS)	x86_64	4.5.1 (2025-06-13) -- "Great Square Root"	4824
merida1	macOS 12.7.5 Monterey	x86_64	4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"	4604
kjohnson1	macOS 13.6.6 Ventura	arm64	4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"	4545
kunpeng2	Linux (openEuler 24.03 LTS)	aarch64	R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"	4579
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 merida1

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: 2.18.1

Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.18.1.tar.gz

StartedAt: 2025-08-19 11:27:09 -0400 (Tue, 19 Aug 2025)

EndedAt: 2025-08-19 11:58:55 -0400 (Tue, 19 Aug 2025)

EllapsedTime: 1905.9 seconds

RetCode: 0

Status: OK

CheckDir: singleCellTK.Rcheck

Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.18.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.1 RC (2025-06-05 r88288)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.18.1’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 79 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  6.8Mb
  sub-directories of 1Mb or more:
    R         1.0Mb
    extdata   1.5Mb
    shiny     2.9Mb
* 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 whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* 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 ... NOTE
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
  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 ... OK
Examples with CPU (user + system) or elapsed time > 5s
                           user system elapsed
importGeneSetsFromMSigDB 91.162  0.868  96.542
plotDoubletFinderResults 53.112  0.257  57.586
plotScDblFinderResults   48.159  0.916  56.117
runDoubletFinder         45.245  0.210  49.076
runScDblFinder           34.232  0.465  36.379
importExampleData        23.365  2.268  27.491
plotBatchCorrCompare     17.849  0.130  18.574
plotScdsHybridResults    13.544  0.136  15.592
plotBcdsResults          13.125  0.196  13.730
plotDecontXResults       11.636  0.076  11.805
plotFindMarkerHeatmap    10.442  0.073  12.110
plotCxdsResults          10.355  0.097  11.147
plotEmptyDropsScatter    10.155  0.051  11.114
plotDEGViolin            10.006  0.174  10.954
plotEmptyDropsResults    10.034  0.041  10.784
runEmptyDrops             9.394  0.036   9.904
convertSCEToSeurat        8.866  0.427   9.749
runDecontX                9.073  0.059  10.174
plotUMAP                  9.023  0.097  10.371
plotTSCANClusterDEG       8.745  0.235  10.245
runUMAP                   8.869  0.095   9.382
plotDEGRegression         8.100  0.079   8.395
detectCellOutlier         7.236  0.169   7.794
runSeuratSCTransform      7.129  0.076   7.561
plotDEGHeatmap            5.366  0.073   5.696
plotRunPerCellQCResults   4.692  0.030   5.470
runEnrichR                0.638  0.047   8.462
* 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 running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.21-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.

Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.18.1’
** 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 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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)
NULL
> 
> proc.time()
   user  system elapsed 
  0.349   0.123   0.441

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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Calculating gene variances
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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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...
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 22 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 22 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
520.579  10.617 582.863

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.004	0.005	0.009
SEG	0.004	0.006	0.010
calcEffectSizes	0.470	0.032	0.537
combineSCE	1.706	0.026	1.840
computeZScore	0.415	0.016	0.454
convertSCEToSeurat	8.866	0.427	9.749
convertSeuratToSCE	0.731	0.012	0.748
dedupRowNames	0.113	0.006	0.119
detectCellOutlier	7.236	0.169	7.794
diffAbundanceFET	0.109	0.005	0.121
discreteColorPalette	0.011	0.001	0.013
distinctColors	0.004	0.000	0.005
downSampleCells	1.070	0.102	1.238
downSampleDepth	0.912	0.042	0.999
expData-ANY-character-method	0.285	0.009	0.312
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.364	0.009	0.390
expData-set	0.344	0.007	0.374
expData	0.284	0.006	0.299
expDataNames-ANY-method	0.281	0.008	0.302
expDataNames	0.262	0.009	0.281
expDeleteDataTag	0.059	0.005	0.069
expSetDataTag	0.043	0.004	0.048
expTaggedData	0.049	0.005	0.057
exportSCE	0.042	0.007	0.050
exportSCEtoAnnData	0.123	0.010	0.143
exportSCEtoFlatFile	0.120	0.011	0.146
featureIndex	0.070	0.008	0.082
generateSimulatedData	0.099	0.011	0.116
getBiomarker	0.127	0.017	0.158
getDEGTopTable	1.650	0.119	1.854
getDiffAbundanceResults	0.105	0.004	0.112
getEnrichRResult	0.682	0.053	2.782
getFindMarkerTopTable	3.491	0.063	3.699
getMSigDBTable	0.008	0.007	0.015
getPathwayResultNames	0.045	0.006	0.053
getSampleSummaryStatsTable	0.449	0.007	0.475
getSoupX	0.000	0.000	0.001
getTSCANResults	2.298	0.063	2.456
getTopHVG	1.863	0.022	1.984
importAnnData	0.003	0.001	0.004
importBUStools	0.390	0.008	0.459
importCellRanger	1.787	0.059	1.941
importCellRangerV2Sample	0.336	0.004	0.373
importCellRangerV3Sample	0.712	0.022	0.775
importDropEst	0.467	0.005	0.496
importExampleData	23.365	2.268	27.491
importGeneSetsFromCollection	1.611	0.137	1.919
importGeneSetsFromGMT	0.137	0.010	0.148
importGeneSetsFromList	0.281	0.008	0.290
importGeneSetsFromMSigDB	91.162	0.868	96.542
importMitoGeneSet	0.110	0.017	0.133
importOptimus	0.003	0.001	0.004
importSEQC	0.322	0.028	0.368
importSTARsolo	0.375	0.039	0.436
iterateSimulations	0.402	0.049	0.478
listSampleSummaryStatsTables	0.584	0.067	0.683
mergeSCEColData	0.92	0.09	1.03
mouseBrainSubsetSCE	0.060	0.007	0.067
msigdb_table	0.002	0.005	0.007
plotBarcodeRankDropsResults	1.339	0.037	1.525
plotBarcodeRankScatter	1.625	0.019	1.712
plotBatchCorrCompare	17.849	0.130	18.574
plotBatchVariance	0.740	0.039	0.781
plotBcdsResults	13.125	0.196	13.730
plotBubble	1.681	0.053	1.807
plotClusterAbundance	2.021	0.012	2.128
plotCxdsResults	10.355	0.097	11.147
plotDEGHeatmap	5.366	0.073	5.696
plotDEGRegression	8.100	0.079	8.395
plotDEGViolin	10.006	0.174	10.954
plotDEGVolcano	1.803	0.020	1.839
plotDecontXResults	11.636	0.076	11.805
plotDimRed	0.406	0.007	0.416
plotDoubletFinderResults	53.112	0.257	57.586
plotEmptyDropsResults	10.034	0.041	10.784
plotEmptyDropsScatter	10.155	0.051	11.114
plotFindMarkerHeatmap	10.442	0.073	12.110
plotMASTThresholdGenes	3.217	0.043	3.812
plotPCA	0.712	0.013	0.856
plotPathway	1.360	0.016	1.613
plotRunPerCellQCResults	4.692	0.030	5.470
plotSCEBarAssayData	0.403	0.010	0.489
plotSCEBarColData	0.329	0.009	0.392
plotSCEBatchFeatureMean	0.525	0.005	0.608
plotSCEDensity	0.573	0.010	0.674
plotSCEDensityAssayData	0.373	0.009	0.414
plotSCEDensityColData	0.475	0.009	0.551
plotSCEDimReduceColData	1.189	0.019	1.479
plotSCEDimReduceFeatures	0.610	0.014	0.753
plotSCEHeatmap	1.084	0.015	1.269
plotSCEScatter	0.553	0.012	0.652
plotSCEViolin	0.543	0.009	0.660
plotSCEViolinAssayData	0.585	0.012	0.718
plotSCEViolinColData	0.557	0.011	0.641
plotScDblFinderResults	48.159	0.916	56.117
plotScanpyDotPlot	0.039	0.004	0.051
plotScanpyEmbedding	0.041	0.006	0.055
plotScanpyHVG	0.042	0.004	0.049
plotScanpyHeatmap	0.042	0.006	0.053
plotScanpyMarkerGenes	0.045	0.003	0.056
plotScanpyMarkerGenesDotPlot	0.041	0.005	0.050
plotScanpyMarkerGenesHeatmap	0.041	0.006	0.055
plotScanpyMarkerGenesMatrixPlot	0.041	0.007	0.055
plotScanpyMarkerGenesViolin	0.040	0.008	0.053
plotScanpyMatrixPlot	0.040	0.003	0.049
plotScanpyPCA	0.040	0.008	0.051
plotScanpyPCAGeneRanking	0.042	0.005	0.054
plotScanpyPCAVariance	0.039	0.005	0.055
plotScanpyViolin	0.038	0.004	0.047
plotScdsHybridResults	13.544	0.136	15.592
plotScrubletResults	0.040	0.006	0.050
plotSeuratElbow	0.041	0.005	0.055
plotSeuratHVG	0.040	0.003	0.048
plotSeuratJackStraw	0.040	0.006	0.056
plotSeuratReduction	0.040	0.004	0.050
plotSoupXResults	0.000	0.000	0.001
plotTSCANClusterDEG	8.745	0.235	10.245
plotTSCANClusterPseudo	2.835	0.034	3.138
plotTSCANDimReduceFeatures	2.906	0.044	3.323
plotTSCANPseudotimeGenes	3.306	0.034	3.723
plotTSCANPseudotimeHeatmap	3.121	0.035	3.602
plotTSCANResults	2.735	0.037	3.115
plotTSNE	0.721	0.014	0.832
plotTopHVG	1.152	0.025	1.318
plotUMAP	9.023	0.097	10.371
readSingleCellMatrix	0.010	0.001	0.015
reportCellQC	0.174	0.007	0.206
reportDropletQC	0.039	0.005	0.048
reportQCTool	0.168	0.007	0.202
retrieveSCEIndex	0.050	0.004	0.059
runBBKNN	0.000	0.001	0.001
runBarcodeRankDrops	0.463	0.009	0.531
runBcds	3.369	0.062	3.868
runCellQC	0.191	0.008	0.218
runClusterSummaryMetrics	0.892	0.017	1.030
runComBatSeq	0.977	0.023	1.097
runCxds	0.679	0.017	0.775
runCxdsBcdsHybrid	3.448	0.137	3.978
runDEAnalysis	0.926	0.071	1.140
runDecontX	9.073	0.059	10.174
runDimReduce	0.632	0.009	0.715
runDoubletFinder	45.245	0.210	49.076
runDropletQC	0.040	0.005	0.048
runEmptyDrops	9.394	0.036	9.904
runEnrichR	0.638	0.047	8.462
runFastMNN	4.043	0.073	4.631
runFeatureSelection	0.445	0.007	0.496
runFindMarker	3.243	0.052	3.643
runGSVA	1.547	0.073	1.820
runHarmony	0.209	0.015	0.260
runKMeans	0.373	0.013	0.393
runLimmaBC	0.176	0.002	0.178
runMNNCorrect	0.896	0.010	0.962
runModelGeneVar	0.680	0.012	0.733
runNormalization	3.432	0.044	3.650
runPerCellQC	0.728	0.016	0.773
runSCANORAMA	0.001	0.000	0.001
runSCMerge	0.007	0.002	0.008
runScDblFinder	34.232	0.465	36.379
runScanpyFindClusters	0.041	0.005	0.048
runScanpyFindHVG	0.041	0.004	0.049
runScanpyFindMarkers	0.040	0.005	0.045
runScanpyNormalizeData	0.214	0.005	0.241
runScanpyPCA	0.044	0.004	0.050
runScanpyScaleData	0.040	0.004	0.051
runScanpyTSNE	0.041	0.005	0.049
runScanpyUMAP	0.041	0.009	0.052
runScranSNN	0.647	0.018	0.710
runScrublet	0.040	0.005	0.048
runSeuratFindClusters	0.039	0.006	0.046
runSeuratFindHVG	1.062	0.015	1.122
runSeuratHeatmap	0.040	0.007	0.048
runSeuratICA	0.042	0.004	0.046
runSeuratJackStraw	0.043	0.007	0.052
runSeuratNormalizeData	0.041	0.004	0.045
runSeuratPCA	0.039	0.005	0.050
runSeuratSCTransform	7.129	0.076	7.561
runSeuratScaleData	0.041	0.006	0.048
runSeuratUMAP	0.040	0.005	0.048
runSingleR	0.084	0.005	0.092
runSoupX	0.000	0.000	0.001
runTSCAN	1.518	0.021	1.634
runTSCANClusterDEAnalysis	1.731	0.046	1.875
runTSCANDEG	1.673	0.034	1.778
runTSNE	1.316	0.017	1.432
runUMAP	8.869	0.095	9.382
runVAM	0.690	0.009	0.738
runZINBWaVE	0.006	0.002	0.008
sampleSummaryStats	0.349	0.008	0.373
scaterCPM	0.214	0.009	0.231
scaterPCA	1.012	0.013	1.144
scaterlogNormCounts	0.434	0.012	0.499
sce	0.037	0.013	0.050
sctkListGeneSetCollections	0.165	0.009	0.186
sctkPythonInstallConda	0.000	0.000	0.001
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0.000	0.000	0.001
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.185	0.006	0.207
setSCTKDisplayRow	0.680	0.013	0.724
singleCellTK	0.000	0.000	0.002
subDiffEx	0.669	0.038	0.746
subsetSCECols	0.175	0.010	0.188
subsetSCERows	0.493	0.026	0.541
summarizeSCE	0.128	0.011	0.148
trimCounts	0.335	0.017	0.365