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"	4606
kjohnson1	macOS 13.6.6 Ventura	arm64	4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"	4547
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: 2025-08-29 10:15:30 -0400 (Fri, 29 Aug 2025)

EndedAt: 2025-08-29 10:45:52 -0400 (Fri, 29 Aug 2025)

EllapsedTime: 1822.4 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 89.717  0.722  91.168
plotDoubletFinderResults 51.488  0.272  54.375
plotScDblFinderResults   48.379  0.937  53.833
runDoubletFinder         45.272  0.191  47.135
runScDblFinder           33.997  0.479  35.030
importExampleData        21.972  2.129  24.914
plotBatchCorrCompare     17.809  0.269  18.889
plotScdsHybridResults    13.593  0.132  15.001
plotBcdsResults          12.939  0.226  13.328
plotDecontXResults       11.538  0.092  11.678
plotEmptyDropsResults     9.927  0.035  10.015
plotEmptyDropsScatter     9.901  0.042  10.489
plotFindMarkerHeatmap     9.824  0.066  11.356
plotDEGViolin             9.634  0.180   9.935
plotCxdsResults           9.700  0.066   9.817
runEmptyDrops             9.453  0.026   9.555
runDecontX                9.178  0.055   9.886
convertSCEToSeurat        8.723  0.418   9.180
plotTSCANClusterDEG       8.740  0.233  10.304
plotUMAP                  8.871  0.095   9.819
runUMAP                   8.823  0.100   8.983
plotDEGRegression         7.636  0.070   7.790
detectCellOutlier         7.236  0.155   7.423
runSeuratSCTransform      7.025  0.096   7.206
plotRunPerCellQCResults   4.624  0.036   5.249
getEnrichRResult          0.658  0.049   8.962
runEnrichR                0.629  0.045   8.722
* 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)
All Done!
> 
> proc.time()
   user  system elapsed 
  0.348   0.113   0.440

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
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 22 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 22 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
516.042  10.329 552.017

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.004	0.005	0.009
SEG	0.004	0.005	0.010
calcEffectSizes	0.431	0.032	0.464
combineSCE	1.681	0.026	1.710
computeZScore	0.391	0.017	0.408
convertSCEToSeurat	8.723	0.418	9.180
convertSeuratToSCE	0.764	0.013	0.781
dedupRowNames	0.116	0.004	0.122
detectCellOutlier	7.236	0.155	7.423
diffAbundanceFET	0.105	0.004	0.109
discreteColorPalette	0.010	0.001	0.011
distinctColors	0.004	0.001	0.004
downSampleCells	1.066	0.115	1.185
downSampleDepth	0.878	0.052	0.933
expData-ANY-character-method	0.282	0.009	0.295
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.352	0.011	0.365
expData-set	0.348	0.013	0.363
expData	0.285	0.009	0.295
expDataNames-ANY-method	0.272	0.008	0.282
expDataNames	0.268	0.011	0.279
expDeleteDataTag	0.060	0.005	0.066
expSetDataTag	0.047	0.005	0.051
expTaggedData	0.046	0.002	0.049
exportSCE	0.036	0.005	0.042
exportSCEtoAnnData	0.120	0.009	0.129
exportSCEtoFlatFile	0.111	0.008	0.119
featureIndex	0.070	0.006	0.077
generateSimulatedData	0.096	0.011	0.107
getBiomarker	0.118	0.015	0.133
getDEGTopTable	1.576	0.112	1.694
getDiffAbundanceResults	0.087	0.004	0.091
getEnrichRResult	0.658	0.049	8.962
getFindMarkerTopTable	3.277	0.054	3.336
getMSigDBTable	0.008	0.007	0.015
getPathwayResultNames	0.036	0.006	0.042
getSampleSummaryStatsTable	0.428	0.006	0.436
getSoupX	0.001	0.000	0.001
getTSCANResults	2.228	0.066	2.304
getTopHVG	1.769	0.020	1.796
importAnnData	0.003	0.001	0.003
importBUStools	0.374	0.007	0.384
importCellRanger	1.789	0.055	1.998
importCellRangerV2Sample	0.356	0.005	0.386
importCellRangerV3Sample	0.691	0.024	0.746
importDropEst	0.449	0.005	0.456
importExampleData	21.972	2.129	24.914
importGeneSetsFromCollection	1.576	0.141	1.724
importGeneSetsFromGMT	0.132	0.010	0.143
importGeneSetsFromList	0.276	0.012	0.291
importGeneSetsFromMSigDB	89.717	0.722	91.168
importMitoGeneSet	0.108	0.015	0.126
importOptimus	0.003	0.001	0.004
importSEQC	0.338	0.028	0.372
importSTARsolo	0.374	0.039	0.425
iterateSimulations	0.404	0.039	0.478
listSampleSummaryStatsTables	0.595	0.063	0.669
mergeSCEColData	0.862	0.089	0.961
mouseBrainSubsetSCE	0.058	0.007	0.066
msigdb_table	0.002	0.004	0.006
plotBarcodeRankDropsResults	1.338	0.037	1.454
plotBarcodeRankScatter	1.587	0.017	1.628
plotBatchCorrCompare	17.809	0.269	18.889
plotBatchVariance	0.780	0.044	0.893
plotBcdsResults	12.939	0.226	13.328
plotBubble	1.577	0.058	1.640
plotClusterAbundance	2.075	0.025	2.114
plotCxdsResults	9.700	0.066	9.817
plotDEGHeatmap	4.859	0.058	4.943
plotDEGRegression	7.636	0.070	7.790
plotDEGViolin	9.634	0.180	9.935
plotDEGVolcano	1.830	0.027	1.935
plotDecontXResults	11.538	0.092	11.678
plotDimRed	0.394	0.007	0.404
plotDoubletFinderResults	51.488	0.272	54.375
plotEmptyDropsResults	9.927	0.035	10.015
plotEmptyDropsScatter	9.901	0.042	10.489
plotFindMarkerHeatmap	9.824	0.066	11.356
plotMASTThresholdGenes	3.175	0.041	3.672
plotPCA	0.698	0.014	0.848
plotPathway	1.319	0.020	1.486
plotRunPerCellQCResults	4.624	0.036	5.249
plotSCEBarAssayData	0.402	0.009	0.445
plotSCEBarColData	0.321	0.008	0.361
plotSCEBatchFeatureMean	0.525	0.008	0.612
plotSCEDensity	0.576	0.010	0.662
plotSCEDensityAssayData	0.362	0.009	0.418
plotSCEDensityColData	0.471	0.010	0.541
plotSCEDimReduceColData	1.148	0.016	1.279
plotSCEDimReduceFeatures	0.603	0.013	0.675
plotSCEHeatmap	1.071	0.010	1.196
plotSCEScatter	0.547	0.011	0.630
plotSCEViolin	0.541	0.010	0.618
plotSCEViolinAssayData	0.579	0.011	0.687
plotSCEViolinColData	0.547	0.009	0.597
plotScDblFinderResults	48.379	0.937	53.833
plotScanpyDotPlot	0.042	0.004	0.050
plotScanpyEmbedding	0.041	0.004	0.048
plotScanpyHVG	0.040	0.004	0.050
plotScanpyHeatmap	0.045	0.005	0.058
plotScanpyMarkerGenes	0.039	0.008	0.052
plotScanpyMarkerGenesDotPlot	0.041	0.002	0.048
plotScanpyMarkerGenesHeatmap	0.039	0.006	0.047
plotScanpyMarkerGenesMatrixPlot	0.039	0.006	0.049
plotScanpyMarkerGenesViolin	0.039	0.004	0.047
plotScanpyMatrixPlot	0.038	0.004	0.046
plotScanpyPCA	0.043	0.004	0.055
plotScanpyPCAGeneRanking	0.040	0.004	0.048
plotScanpyPCAVariance	0.040	0.004	0.055
plotScanpyViolin	0.038	0.006	0.050
plotScdsHybridResults	13.593	0.132	15.001
plotScrubletResults	0.040	0.005	0.049
plotSeuratElbow	0.039	0.004	0.048
plotSeuratHVG	0.040	0.005	0.047
plotSeuratJackStraw	0.042	0.008	0.056
plotSeuratReduction	0.041	0.004	0.048
plotSoupXResults	0.000	0.000	0.001
plotTSCANClusterDEG	8.740	0.233	10.304
plotTSCANClusterPseudo	2.807	0.041	2.980
plotTSCANDimReduceFeatures	2.831	0.035	2.894
plotTSCANPseudotimeGenes	3.260	0.036	3.462
plotTSCANPseudotimeHeatmap	3.037	0.035	3.257
plotTSCANResults	2.682	0.031	2.955
plotTSNE	0.734	0.016	0.809
plotTopHVG	1.168	0.025	1.293
plotUMAP	8.871	0.095	9.819
readSingleCellMatrix	0.009	0.001	0.013
reportCellQC	0.185	0.010	0.220
reportDropletQC	0.043	0.005	0.052
reportQCTool	0.181	0.008	0.205
retrieveSCEIndex	0.058	0.004	0.071
runBBKNN	0.000	0.001	0.001
runBarcodeRankDrops	0.473	0.008	0.518
runBcds	3.395	0.057	3.742
runCellQC	0.181	0.007	0.206
runClusterSummaryMetrics	0.866	0.020	0.964
runComBatSeq	0.982	0.033	1.106
runCxds	0.683	0.021	0.765
runCxdsBcdsHybrid	3.453	0.126	3.848
runDEAnalysis	0.905	0.078	1.062
runDecontX	9.178	0.055	9.886
runDimReduce	0.635	0.011	0.679
runDoubletFinder	45.272	0.191	47.135
runDropletQC	0.039	0.004	0.044
runEmptyDrops	9.453	0.026	9.555
runEnrichR	0.629	0.045	8.722
runFastMNN	3.997	0.086	4.107
runFeatureSelection	0.441	0.006	0.449
runFindMarker	3.179	0.044	3.242
runGSVA	1.551	0.072	1.925
runHarmony	0.217	0.015	0.256
runKMeans	0.365	0.015	0.385
runLimmaBC	0.179	0.003	0.182
runMNNCorrect	0.874	0.006	0.888
runModelGeneVar	0.672	0.009	0.700
runNormalization	3.409	0.037	3.655
runPerCellQC	0.741	0.015	0.805
runSCANORAMA	0.000	0.001	0.003
runSCMerge	0.007	0.002	0.010
runScDblFinder	33.997	0.479	35.030
runScanpyFindClusters	0.041	0.007	0.048
runScanpyFindHVG	0.048	0.009	0.058
runScanpyFindMarkers	0.045	0.009	0.053
runScanpyNormalizeData	0.205	0.007	0.213
runScanpyPCA	0.043	0.005	0.048
runScanpyScaleData	0.039	0.003	0.042
runScanpyTSNE	0.042	0.007	0.048
runScanpyUMAP	0.043	0.008	0.050
runScranSNN	0.623	0.017	0.643
runScrublet	0.038	0.007	0.045
runSeuratFindClusters	0.041	0.006	0.047
runSeuratFindHVG	1.019	0.014	1.037
runSeuratHeatmap	0.039	0.005	0.044
runSeuratICA	0.040	0.005	0.045
runSeuratJackStraw	0.040	0.005	0.046
runSeuratNormalizeData	0.039	0.004	0.043
runSeuratPCA	0.039	0.004	0.045
runSeuratSCTransform	7.025	0.096	7.206
runSeuratScaleData	0.038	0.005	0.044
runSeuratUMAP	0.039	0.004	0.043
runSingleR	0.084	0.006	0.090
runSoupX	0.000	0.000	0.001
runTSCAN	1.501	0.020	1.531
runTSCANClusterDEAnalysis	1.707	0.057	1.787
runTSCANDEG	1.634	0.056	1.714
runTSNE	1.297	0.018	1.330
runUMAP	8.823	0.100	8.983
runVAM	0.683	0.010	0.697
runZINBWaVE	0.007	0.002	0.008
sampleSummaryStats	0.353	0.006	0.360
scaterCPM	0.209	0.006	0.216
scaterPCA	0.989	0.012	1.003
scaterlogNormCounts	0.432	0.008	0.443
sce	0.038	0.009	0.048
sctkListGeneSetCollections	0.180	0.011	0.191
sctkPythonInstallConda	0.000	0.001	0.000
sctkPythonInstallVirtualEnv	0.000	0.001	0.001
selectSCTKConda	0.000	0.000	0.001
selectSCTKVirtualEnvironment	0.000	0.001	0.001
setRowNames	0.196	0.011	0.207
setSCTKDisplayRow	0.669	0.009	0.680
singleCellTK	0.000	0.001	0.001
subDiffEx	0.652	0.034	0.688
subsetSCECols	0.175	0.013	0.191
subsetSCERows	0.481	0.012	0.500
summarizeSCE	0.135	0.014	0.149
trimCounts	0.339	0.018	0.360