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"	4833
merida1	macOS 12.7.6 Monterey	x86_64	4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"	4614
kjohnson1	macOS 13.7.5 Ventura	arm64	4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"	4555
kunpeng2	Linux (openEuler 24.03 LTS)	aarch64	R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"	4586
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: 2.18.2

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_2.18.2.tar.gz

StartedAt: 2025-10-14 10:32:03 -0400 (Tue, 14 Oct 2025)

EndedAt: 2025-10-14 11:03:29 -0400 (Tue, 14 Oct 2025)

EllapsedTime: 1885.9 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_2.18.2.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 ‘2.18.2’
* 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 88.701  0.758  89.899
plotDoubletFinderResults 54.696  0.254  56.414
plotScDblFinderResults   50.379  1.000  54.172
runDoubletFinder         46.626  0.186  47.700
runScDblFinder           32.658  0.398  33.129
importExampleData        22.345  2.115  25.460
plotBatchCorrCompare     18.826  0.163  19.106
plotScdsHybridResults    15.495  0.217  16.984
plotBcdsResults          14.227  0.252  14.570
plotDecontXResults       13.307  0.099  13.580
plotDEGViolin            13.143  0.207  13.928
plotTSCANClusterDEG      12.310  0.116  13.552
plotCxdsResults          11.771  0.087  12.054
plotDEGRegression        11.371  0.201  12.810
plotEmptyDropsScatter    10.234  0.043  11.094
plotEmptyDropsResults    10.175  0.035  10.587
plotFindMarkerHeatmap     9.656  0.043  10.112
runDecontX                9.404  0.071   9.637
runUMAP                   9.312  0.106   9.637
runEmptyDrops             9.321  0.029   9.696
plotUMAP                  9.142  0.081   9.837
convertSCEToSeurat        8.794  0.316   9.176
detectCellOutlier         7.702  0.171   7.905
plotRunPerCellQCResults   7.366  0.037   7.429
runSeuratSCTransform      7.119  0.123   7.303
plotDEGHeatmap            5.382  0.080   6.045
getEnrichRResult          0.666  0.058  14.287
* 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 ‘2.18.2’
** 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 
  0.336   0.112   0.417

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 
547.876  10.769 573.845

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.002	0.002	0.005
SEG	0.005	0.005	0.010
calcEffectSizes	0.430	0.031	0.464
combineSCE	1.624	0.026	1.654
computeZScore	0.390	0.017	0.408
convertSCEToSeurat	8.794	0.316	9.176
convertSeuratToSCE	0.696	0.012	0.710
dedupRowNames	0.115	0.003	0.119
detectCellOutlier	7.702	0.171	7.905
diffAbundanceFET	0.097	0.004	0.102
discreteColorPalette	0.011	0.001	0.011
distinctColors	0.004	0.001	0.004
downSampleCells	1.039	0.103	1.148
downSampleDepth	0.852	0.055	0.909
expData-ANY-character-method	0.278	0.007	0.286
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.363	0.008	0.372
expData-set	0.351	0.007	0.359
expData	0.283	0.006	0.291
expDataNames-ANY-method	0.253	0.010	0.263
expDataNames	0.268	0.027	0.296
expDeleteDataTag	0.059	0.004	0.063
expSetDataTag	0.042	0.005	0.046
expTaggedData	0.045	0.004	0.049
exportSCE	0.039	0.006	0.046
exportSCEtoAnnData	0.123	0.011	0.134
exportSCEtoFlatFile	0.112	0.008	0.122
featureIndex	0.063	0.010	0.074
generateSimulatedData	0.089	0.010	0.099
getBiomarker	0.104	0.014	0.119
getDEGTopTable	1.548	0.111	1.664
getDiffAbundanceResults	0.085	0.003	0.088
getEnrichRResult	0.666	0.058	14.287
getFindMarkerTopTable	3.246	0.049	3.298
getMSigDBTable	0.007	0.007	0.014
getPathwayResultNames	0.045	0.006	0.050
getSampleSummaryStatsTable	0.393	0.006	0.399
getSoupX	0.000	0.000	0.001
getTSCANResults	2.295	0.071	2.398
getTopHVG	1.688	0.025	1.786
importAnnData	0.003	0.000	0.004
importBUStools	0.433	0.009	0.458
importCellRanger	1.665	0.046	1.833
importCellRangerV2Sample	0.332	0.003	0.335
importCellRangerV3Sample	0.633	0.019	0.653
importDropEst	0.432	0.005	0.438
importExampleData	22.345	2.115	25.460
importGeneSetsFromCollection	1.598	0.132	1.736
importGeneSetsFromGMT	0.133	0.010	0.146
importGeneSetsFromList	0.274	0.019	0.293
importGeneSetsFromMSigDB	88.701	0.758	89.899
importMitoGeneSet	0.102	0.014	0.117
importOptimus	0.003	0.001	0.004
importSEQC	0.327	0.031	0.361
importSTARsolo	0.355	0.038	0.393
iterateSimulations	0.395	0.041	0.437
listSampleSummaryStatsTables	0.587	0.066	0.659
mergeSCEColData	0.913	0.125	1.050
mouseBrainSubsetSCE	0.063	0.009	0.072
msigdb_table	0.002	0.004	0.006
plotBarcodeRankDropsResults	1.955	0.040	1.999
plotBarcodeRankScatter	2.022	0.022	2.049
plotBatchCorrCompare	18.826	0.163	19.106
plotBatchVariance	1.084	0.034	1.121
plotBcdsResults	14.227	0.252	14.570
plotBubble	1.824	0.016	1.843
plotClusterAbundance	3.350	0.017	3.386
plotCxdsResults	11.771	0.087	12.054
plotDEGHeatmap	5.382	0.080	6.045
plotDEGRegression	11.371	0.201	12.810
plotDEGViolin	13.143	0.207	13.928
plotDEGVolcano	2.043	0.020	2.070
plotDecontXResults	13.307	0.099	13.580
plotDimRed	0.680	0.011	0.742
plotDoubletFinderResults	54.696	0.254	56.414
plotEmptyDropsResults	10.175	0.035	10.587
plotEmptyDropsScatter	10.234	0.043	11.094
plotFindMarkerHeatmap	9.656	0.043	10.112
plotMASTThresholdGenes	3.020	0.037	3.060
plotPCA	0.960	0.015	0.976
plotPathway	1.526	0.014	1.546
plotRunPerCellQCResults	7.366	0.037	7.429
plotSCEBarAssayData	0.611	0.009	0.625
plotSCEBarColData	0.533	0.008	0.544
plotSCEBatchFeatureMean	0.952	0.005	0.961
plotSCEDensity	0.707	0.009	0.718
plotSCEDensityAssayData	0.697	0.010	0.708
plotSCEDensityColData	0.678	0.010	0.689
plotSCEDimReduceColData	1.695	0.016	1.772
plotSCEDimReduceFeatures	0.895	0.010	0.907
plotSCEHeatmap	0.913	0.008	0.923
plotSCEScatter	0.776	0.013	0.789
plotSCEViolin	0.883	0.012	0.897
plotSCEViolinAssayData	0.861	0.010	0.872
plotSCEViolinColData	0.864	0.014	0.884
plotScDblFinderResults	50.379	1.000	54.172
plotScanpyDotPlot	0.038	0.005	0.050
plotScanpyEmbedding	0.039	0.005	0.049
plotScanpyHVG	0.041	0.005	0.049
plotScanpyHeatmap	0.039	0.003	0.047
plotScanpyMarkerGenes	0.039	0.005	0.052
plotScanpyMarkerGenesDotPlot	0.039	0.005	0.046
plotScanpyMarkerGenesHeatmap	0.039	0.005	0.045
plotScanpyMarkerGenesMatrixPlot	0.041	0.004	0.053
plotScanpyMarkerGenesViolin	0.040	0.005	0.050
plotScanpyMatrixPlot	0.040	0.004	0.045
plotScanpyPCA	0.040	0.004	0.046
plotScanpyPCAGeneRanking	0.045	0.005	0.059
plotScanpyPCAVariance	0.043	0.004	0.054
plotScanpyViolin	0.043	0.004	0.052
plotScdsHybridResults	15.495	0.217	16.984
plotScrubletResults	0.042	0.004	0.052
plotSeuratElbow	0.043	0.006	0.057
plotSeuratHVG	0.040	0.005	0.051
plotSeuratJackStraw	0.041	0.006	0.050
plotSeuratReduction	0.044	0.003	0.053
plotSoupXResults	0.000	0.001	0.001
plotTSCANClusterDEG	12.310	0.116	13.552
plotTSCANClusterPseudo	3.335	0.034	3.673
plotTSCANDimReduceFeatures	3.367	0.037	3.731
plotTSCANPseudotimeGenes	4.154	0.039	4.479
plotTSCANPseudotimeHeatmap	3.092	0.033	3.363
plotTSCANResults	3.010	0.033	3.278
plotTSNE	0.919	0.018	1.014
plotTopHVG	1.436	0.026	1.552
plotUMAP	9.142	0.081	9.837
readSingleCellMatrix	0.011	0.001	0.012
reportCellQC	0.180	0.007	0.195
reportDropletQC	0.041	0.005	0.046
reportQCTool	0.175	0.007	0.192
retrieveSCEIndex	0.050	0.006	0.062
runBBKNN	0.000	0.000	0.001
runBarcodeRankDrops	0.471	0.010	0.536
runBcds	3.341	0.067	3.629
runCellQC	0.171	0.006	0.187
runClusterSummaryMetrics	0.890	0.021	0.928
runComBatSeq	0.977	0.021	1.003
runCxds	0.722	0.015	0.740
runCxdsBcdsHybrid	3.416	0.110	3.539
runDEAnalysis	0.924	0.074	1.009
runDecontX	9.404	0.071	9.637
runDimReduce	0.625	0.011	0.639
runDoubletFinder	46.626	0.186	47.700
runDropletQC	0.044	0.005	0.066
runEmptyDrops	9.321	0.029	9.696
runEnrichR	0.634	0.047	4.628
runFastMNN	3.843	0.065	3.920
runFeatureSelection	0.437	0.009	0.447
runFindMarker	3.104	0.045	3.156
runGSVA	1.414	0.047	1.465
runHarmony	0.084	0.002	0.086
runKMeans	0.474	0.018	0.492
runLimmaBC	0.174	0.003	0.177
runMNNCorrect	0.859	0.006	0.872
runModelGeneVar	0.669	0.009	0.692
runNormalization	3.372	0.041	3.485
runPerCellQC	0.671	0.011	0.683
runSCANORAMA	0.000	0.001	0.001
runSCMerge	0.007	0.002	0.008
runScDblFinder	32.658	0.398	33.129
runScanpyFindClusters	0.038	0.004	0.043
runScanpyFindHVG	0.040	0.004	0.043
runScanpyFindMarkers	0.039	0.005	0.044
runScanpyNormalizeData	0.213	0.006	0.220
runScanpyPCA	0.045	0.004	0.050
runScanpyScaleData	0.040	0.003	0.044
runScanpyTSNE	0.053	0.003	0.056
runScanpyUMAP	0.043	0.003	0.046
runScranSNN	0.652	0.014	0.669
runScrublet	0.041	0.007	0.049
runSeuratFindClusters	0.042	0.005	0.047
runSeuratFindHVG	1.048	0.016	1.069
runSeuratHeatmap	0.040	0.003	0.043
runSeuratICA	0.042	0.003	0.045
runSeuratJackStraw	0.041	0.002	0.044
runSeuratNormalizeData	0.041	0.008	0.049
runSeuratPCA	0.048	0.003	0.050
runSeuratSCTransform	7.119	0.123	7.303
runSeuratScaleData	0.040	0.005	0.045
runSeuratUMAP	0.038	0.005	0.043
runSingleR	0.081	0.004	0.086
runSoupX	0.001	0.001	0.001
runTSCAN	1.534	0.020	1.563
runTSCANClusterDEAnalysis	1.723	0.036	1.779
runTSCANDEG	1.695	0.056	1.762
runTSNE	1.317	0.019	1.360
runUMAP	9.312	0.106	9.637
runVAM	0.689	0.009	0.828
runZINBWaVE	0.007	0.001	0.008
sampleSummaryStats	0.363	0.011	0.412
scaterCPM	0.212	0.008	0.221
scaterPCA	1.004	0.011	1.017
scaterlogNormCounts	0.428	0.008	0.437
sce	0.036	0.005	0.042
sctkListGeneSetCollections	0.161	0.009	0.170
sctkPythonInstallConda	0.000	0.000	0.001
sctkPythonInstallVirtualEnv	0.000	0.000	0.001
selectSCTKConda	0.001	0.001	0.001
selectSCTKVirtualEnvironment	0.000	0.000	0.001
setRowNames	0.177	0.005	0.182
setSCTKDisplayRow	0.979	0.026	1.008
singleCellTK	0.000	0.001	0.001
subDiffEx	0.645	0.031	0.678
subsetSCECols	0.173	0.009	0.183
subsetSCERows	0.549	0.029	0.579
summarizeSCE	0.126	0.012	0.139
trimCounts	0.338	0.017	0.356