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

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo1	Linux (Ubuntu 24.04.3 LTS)	x86_64	R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"	4821
Click on any hostname to see more info about the system (e.g. compilers) () as reported by 'uname -p', except on Windows and Mac OS X*

CHECK results for singleCellTK on nebbiolo1

To the developers/maintainers of the singleCellTK package:
- Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/singleCellTK.git to reflect on this report. See Troubleshooting Build Report for more information.
- Use the following Renviron settings to reproduce errors and warnings.
- If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information.

raw results

Summary

Package: singleCellTK

Version: 2.21.0

Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings singleCellTK_2.21.0.tar.gz

StartedAt: 2025-11-08 04:00:16 -0500 (Sat, 08 Nov 2025)

EndedAt: 2025-11-08 04:17:18 -0500 (Sat, 08 Nov 2025)

EllapsedTime: 1022.1 seconds

RetCode: 0

Status: OK

CheckDir: singleCellTK.Rcheck

Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings singleCellTK_2.21.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck’
* using R Under development (unstable) (2025-10-20 r88955)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.21.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 80 non-default packages.
Importing from so many packages makes the package vulnerable to any of
them becoming unavailable.  Move as many as possible to Suggests and
use conditionally.
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘singleCellTK’ can be installed ... OK
* checking installed package size ... INFO
  installed size is  5.6Mb
  sub-directories of 1Mb or more:
    shiny   2.3Mb
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... 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
  plotEnrichR.Rd: SingleCellExperiment-class
  plotFindMarkerHeatmap.Rd: SingleCellExperiment-class
  plotPCA.Rd: SingleCellExperiment-class
  plotPathway.Rd: SingleCellExperiment-class
  plotRunPerCellQCResults.Rd: SingleCellExperiment-class
  plotSCEBarAssayData.Rd: SingleCellExperiment-class
  plotSCEBarColData.Rd: SingleCellExperiment-class
  plotSCEBatchFeatureMean.Rd: SingleCellExperiment-class
  plotSCEDensity.Rd: SingleCellExperiment-class
  plotSCEDensityAssayData.Rd: SingleCellExperiment-class
  plotSCEDensityColData.Rd: SingleCellExperiment-class
  plotSCEDimReduceColData.Rd: SingleCellExperiment-class
  plotSCEDimReduceFeatures.Rd: SingleCellExperiment-class
  plotSCEHeatmap.Rd: SingleCellExperiment-class
  plotSCEScatter.Rd: SingleCellExperiment-class
  plotSCEViolin.Rd: SingleCellExperiment-class
  plotSCEViolinAssayData.Rd: SingleCellExperiment-class
  plotSCEViolinColData.Rd: SingleCellExperiment-class
  plotScDblFinderResults.Rd: SingleCellExperiment-class
  plotScdsHybridResults.Rd: SingleCellExperiment-class
  plotScrubletResults.Rd: SingleCellExperiment-class
  plotSoupXResults.Rd: SingleCellExperiment-class
  plotTSCANClusterDEG.Rd: SingleCellExperiment-class
  plotTSCANClusterPseudo.Rd: SingleCellExperiment-class
  plotTSCANDimReduceFeatures.Rd: SingleCellExperiment-class
  plotTSCANPseudotimeGenes.Rd: SingleCellExperiment-class
  plotTSCANPseudotimeHeatmap.Rd: SingleCellExperiment-class
  plotTSCANResults.Rd: SingleCellExperiment-class
  plotTSNE.Rd: SingleCellExperiment-class
  plotUMAP.Rd: SingleCellExperiment-class
  readSingleCellMatrix.Rd: DelayedArray
  reportCellQC.Rd: SingleCellExperiment-class
  reportClusterAbundance.Rd: colData
  reportDiffAbundanceFET.Rd: colData
  retrieveSCEIndex.Rd: SingleCellExperiment-class
  runBBKNN.Rd: SingleCellExperiment-class
  runBarcodeRankDrops.Rd: SingleCellExperiment-class, colData
  runBcds.Rd: SingleCellExperiment-class, colData
  runCellQC.Rd: colData
  runComBatSeq.Rd: SingleCellExperiment-class
  runCxds.Rd: SingleCellExperiment-class, colData
  runCxdsBcdsHybrid.Rd: colData
  runDEAnalysis.Rd: SingleCellExperiment-class
  runDecontX.Rd: colData
  runDimReduce.Rd: SingleCellExperiment-class
  runDoubletFinder.Rd: SingleCellExperiment-class
  runDropletQC.Rd: colData
  runEmptyDrops.Rd: SingleCellExperiment-class, colData
  runEnrichR.Rd: SingleCellExperiment-class
  runFastMNN.Rd: SingleCellExperiment-class, BiocParallelParam-class
  runFeatureSelection.Rd: SingleCellExperiment-class
  runFindMarker.Rd: SingleCellExperiment-class
  runGSVA.Rd: SingleCellExperiment-class
  runHarmony.Rd: SingleCellExperiment-class
  runKMeans.Rd: SingleCellExperiment-class, colData
  runLimmaBC.Rd: SingleCellExperiment-class, assay
  runMNNCorrect.Rd: SingleCellExperiment-class, assay,
    BiocParallelParam-class
  runModelGeneVar.Rd: SingleCellExperiment-class
  runPerCellQC.Rd: SingleCellExperiment-class, BiocParallelParam,
    colData
  runSCANORAMA.Rd: SingleCellExperiment-class, assay
  runSCMerge.Rd: SingleCellExperiment-class, colData, assay,
    BiocParallelParam-class
  runScDblFinder.Rd: SingleCellExperiment-class, colData
  runScranSNN.Rd: SingleCellExperiment-class, reducedDim, assay,
    altExp, colData, igraph
  runScrublet.Rd: SingleCellExperiment-class, colData
  runSingleR.Rd: SingleCellExperiment-class
  runSoupX.Rd: SingleCellExperiment-class
  runTSCAN.Rd: SingleCellExperiment-class
  runTSCANClusterDEAnalysis.Rd: SingleCellExperiment-class
  runTSCANDEG.Rd: SingleCellExperiment-class
  runTSNE.Rd: SingleCellExperiment-class
  runUMAP.Rd: SingleCellExperiment-class, BiocParallelParam-class
  runVAM.Rd: SingleCellExperiment-class
  runZINBWaVE.Rd: SingleCellExperiment-class, colData,
    BiocParallelParam-class
  sampleSummaryStats.Rd: SingleCellExperiment-class, assay, colData
  scaterPCA.Rd: SingleCellExperiment-class, BiocParallelParam-class
  scaterlogNormCounts.Rd: logNormCounts
  sctkListGeneSetCollections.Rd: GeneSetCollection-class
  sctkPythonInstallConda.Rd: conda_install, reticulate, conda_create
  sctkPythonInstallVirtualEnv.Rd: virtualenv_install, reticulate,
    virtualenv_create
  selectSCTKConda.Rd: reticulate
  selectSCTKVirtualEnvironment.Rd: reticulate
  setRowNames.Rd: SingleCellExperiment-class
  setSCTKDisplayRow.Rd: SingleCellExperiment-class
  singleCellTK.Rd: SingleCellExperiment-class
  subsetSCECols.Rd: SingleCellExperiment-class
  subsetSCERows.Rd: SingleCellExperiment-class, altExp
  summarizeSCE.Rd: SingleCellExperiment-class
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                           user system elapsed
importGeneSetsFromMSigDB 45.720  0.793  46.515
plotDoubletFinderResults 38.834  0.343  39.179
runDoubletFinder         34.760  0.203  34.964
plotScDblFinderResults   30.654  0.727  31.070
runSeuratSCTransform     28.384  0.633  29.020
runScDblFinder           20.596  1.251  21.566
importExampleData        12.481  1.155  13.983
plotBatchCorrCompare     13.449  0.165  13.614
plotScdsHybridResults    10.634  0.081   9.962
plotBcdsResults           9.304  0.125   8.651
plotDecontXResults        8.627  0.064   8.691
runUMAP                   7.806  0.156   7.960
plotCxdsResults           7.322  0.051   7.373
runDecontX                6.952  0.102   7.054
plotUMAP                  6.861  0.073   6.934
plotEmptyDropsResults     6.624  0.010   6.634
plotEmptyDropsScatter     6.517  0.004   6.522
runEmptyDrops             6.249  0.001   6.251
detectCellOutlier         5.214  0.159   5.372
plotDEGViolin             5.045  0.060   5.098
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘spelling.R’
  Running ‘testthat.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/home/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.

Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.21.0’
** using staged installation
** R
** data
** exec
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (singleCellTK)

Tests output

singleCellTK.Rcheck/tests/spelling.Rout


R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> if (requireNamespace('spelling', quietly = TRUE))
+   spelling::spell_check_test(vignettes = TRUE, error = FALSE, skip_on_cran = TRUE)
All Done!
> 
> proc.time()
   user  system elapsed 
  0.142   0.046   0.173

singleCellTK.Rcheck/tests/testthat.Rout


R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(testthat)
> library(singleCellTK)
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats

Attaching package: 'MatrixGenerics'

The following objects are masked from 'package:matrixStats':

    colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
    colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
    colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
    colWeightedMeans, colWeightedMedians, colWeightedSds,
    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
    rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
    rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
    rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
    rowWeightedSds, rowWeightedVars

Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: generics

Attaching package: 'generics'

The following objects are masked from 'package:base':

    as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
    setequal, union


Attaching package: 'BiocGenerics'

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
    mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
    rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
    unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:utils':

    findMatches

The following objects are masked from 'package:base':

    I, expand.grid, unname

Loading required package: IRanges
Loading required package: Seqinfo
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'Biobase'

The following object is masked from 'package:MatrixGenerics':

    rowMedians

The following objects are masked from 'package:matrixStats':

    anyMissing, rowMedians

Loading required package: SingleCellExperiment
Loading required package: DelayedArray
Loading required package: Matrix

Attaching package: 'Matrix'

The following object is masked from 'package:S4Vectors':

    expand

Loading required package: S4Arrays
Loading required package: abind

Attaching package: 'S4Arrays'

The following object is masked from 'package:abind':

    abind

The following object is masked from 'package:base':

    rowsum

Loading required package: SparseArray

Attaching package: 'DelayedArray'

The following objects are masked from 'package:base':

    apply, scale, sweep


Attaching package: 'singleCellTK'

The following object is masked from 'package:BiocGenerics':

    plotPCA

> 
> test_check("singleCellTK")
Found 2 batches
Using null model in ComBat-seq.
Adjusting for 0 covariate(s) or covariate level(s)
Estimating dispersions
Fitting the GLM model
Shrinkage off - using GLM estimates for parameters
Adjusting the data
Found 2 batches
Using null model in ComBat-seq.
Adjusting for 1 covariate(s) or covariate level(s)
Estimating dispersions
Fitting the GLM model
Shrinkage off - using GLM estimates for parameters
Adjusting the data
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Uploading data to Enrichr... Done.
  Querying HDSigDB_Human_2021... Done.
Parsing results... Done.
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
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%
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  |======================================================================| 100%
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 390
Number of edges: 9849

Running Louvain algorithm...
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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 21 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
316.375   7.869 328.130

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.002	0.000	0.002
SEG	0.001	0.001	0.003
calcEffectSizes	0.158	0.008	0.166
combineSCE	0.756	0.032	0.788
computeZScore	0.240	0.008	0.248
convertSCEToSeurat	4.240	0.126	4.372
convertSeuratToSCE	0.306	0.008	0.313
dedupRowNames	0.056	0.001	0.058
detectCellOutlier	5.214	0.159	5.372
diffAbundanceFET	0.052	0.003	0.054
discreteColorPalette	0.005	0.001	0.006
distinctColors	0.003	0.000	0.003
downSampleCells	0.463	0.077	0.540
downSampleDepth	0.394	0.004	0.400
expData-ANY-character-method	0.117	0.001	0.119
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.158	0.001	0.159
expData-set	0.144	0.000	0.143
expData	0.116	0.002	0.119
expDataNames-ANY-method	0.112	0.002	0.114
expDataNames	0.110	0.002	0.112
expDeleteDataTag	0.031	0.003	0.033
expSetDataTag	0.023	0.002	0.024
expTaggedData	0.025	0.001	0.026
exportSCE	0.021	0.001	0.023
exportSCEtoAnnData	0.089	0.009	0.098
exportSCEtoFlatFile	0.090	0.008	0.098
featureIndex	0.033	0.004	0.037
generateSimulatedData	0.050	0.004	0.053
getBiomarker	0.054	0.007	0.062
getDEGTopTable	0.665	0.124	0.789
getDiffAbundanceResults	0.048	0.000	0.048
getEnrichRResult	0.520	0.031	3.281
getFindMarkerTopTable	1.648	0.258	1.906
getMSigDBTable	0.003	0.002	0.005
getPathwayResultNames	0.021	0.002	0.024
getSampleSummaryStatsTable	0.206	0.002	0.208
getSoupX	0	0	0
getTSCANResults	1.156	0.046	1.202
getTopHVG	0.864	0.010	0.874
importAnnData	0.001	0.000	0.002
importBUStools	0.194	0.017	0.212
importCellRanger	0.733	0.148	0.882
importCellRangerV2Sample	0.146	0.044	0.190
importCellRangerV3Sample	0.379	0.059	0.437
importDropEst	0.190	0.009	0.199
importExampleData	12.481	1.155	13.983
importGeneSetsFromCollection	0.678	0.036	0.715
importGeneSetsFromGMT	0.062	0.001	0.063
importGeneSetsFromList	0.120	0.002	0.122
importGeneSetsFromMSigDB	45.720	0.793	46.515
importMitoGeneSet	0.051	0.003	0.055
importOptimus	0.002	0.000	0.001
importSEQC	0.142	0.009	0.152
importSTARsolo	0.149	0.018	0.167
iterateSimulations	0.188	0.018	0.207
listSampleSummaryStatsTables	0.248	0.041	0.288
mergeSCEColData	0.369	0.025	0.394
mouseBrainSubsetSCE	0.036	0.000	0.036
msigdb_table	0.000	0.001	0.001
plotBarcodeRankDropsResults	0.847	0.014	0.861
plotBarcodeRankScatter	0.822	0.001	0.822
plotBatchCorrCompare	13.449	0.165	13.614
plotBatchVariance	0.476	0.001	0.495
plotBcdsResults	9.304	0.125	8.651
plotBubble	0.748	0.001	0.750
plotClusterAbundance	1.281	0.015	1.296
plotCxdsResults	7.322	0.051	7.373
plotDEGHeatmap	1.993	0.007	2.000
plotDEGRegression	4.190	0.011	4.195
plotDEGViolin	5.045	0.060	5.098
plotDEGVolcano	0.923	0.015	0.938
plotDecontXResults	8.627	0.064	8.691
plotDimRed	0.279	0.000	0.279
plotDoubletFinderResults	38.834	0.343	39.179
plotEmptyDropsResults	6.624	0.010	6.634
plotEmptyDropsScatter	6.517	0.004	6.522
plotFindMarkerHeatmap	3.580	0.005	3.586
plotMASTThresholdGenes	1.196	0.008	1.204
plotPCA	0.344	0.003	0.346
plotPathway	0.676	0.005	0.681
plotRunPerCellQCResults	3.006	0.003	3.009
plotSCEBarAssayData	0.271	0.002	0.272
plotSCEBarColData	0.262	0.001	0.263
plotSCEBatchFeatureMean	0.376	0.001	0.377
plotSCEDensity	0.294	0.001	0.295
plotSCEDensityAssayData	0.257	0.001	0.259
plotSCEDensityColData	0.330	0.002	0.331
plotSCEDimReduceColData	0.713	0.004	0.718
plotSCEDimReduceFeatures	0.398	0.004	0.402
plotSCEHeatmap	0.410	0.001	0.411
plotSCEScatter	0.362	0.003	0.366
plotSCEViolin	0.374	0.001	0.375
plotSCEViolinAssayData	0.431	0.001	0.431
plotSCEViolinColData	0.373	0.001	0.374
plotScDblFinderResults	30.654	0.727	31.070
plotScanpyDotPlot	0.022	0.000	0.022
plotScanpyEmbedding	0.021	0.001	0.022
plotScanpyHVG	0.020	0.002	0.022
plotScanpyHeatmap	0.022	0.000	0.022
plotScanpyMarkerGenes	0.020	0.001	0.022
plotScanpyMarkerGenesDotPlot	0.022	0.000	0.022
plotScanpyMarkerGenesHeatmap	0.023	0.000	0.022
plotScanpyMarkerGenesMatrixPlot	0.023	0.000	0.023
plotScanpyMarkerGenesViolin	0.021	0.000	0.022
plotScanpyMatrixPlot	0.021	0.000	0.022
plotScanpyPCA	0.022	0.000	0.022
plotScanpyPCAGeneRanking	0.023	0.000	0.023
plotScanpyPCAVariance	0.020	0.001	0.021
plotScanpyViolin	0.019	0.002	0.022
plotScdsHybridResults	10.634	0.081	9.962
plotScrubletResults	0.022	0.000	0.021
plotSeuratElbow	0.020	0.001	0.022
plotSeuratHVG	0.022	0.000	0.022
plotSeuratJackStraw	0.021	0.001	0.022
plotSeuratReduction	0.022	0.000	0.022
plotSoupXResults	0.001	0.000	0.000
plotTSCANClusterDEG	4.828	0.015	4.844
plotTSCANClusterPseudo	1.321	0.003	1.324
plotTSCANDimReduceFeatures	1.335	0.008	1.343
plotTSCANPseudotimeGenes	1.582	0.006	1.587
plotTSCANPseudotimeHeatmap	1.277	0.003	1.279
plotTSCANResults	1.210	0.007	1.217
plotTSNE	0.371	0.001	0.372
plotTopHVG	0.612	0.000	0.612
plotUMAP	6.861	0.073	6.934
readSingleCellMatrix	0.005	0.000	0.005
reportCellQC	0.084	0.000	0.083
reportDropletQC	0.023	0.000	0.023
reportQCTool	0.080	0.000	0.079
retrieveSCEIndex	0.028	0.001	0.029
runBBKNN	0.000	0.001	0.000
runBarcodeRankDrops	0.222	0.002	0.224
runBcds	1.933	0.031	1.185
runCellQC	0.080	0.002	0.082
runClusterSummaryMetrics	0.366	0.003	0.369
runComBatSeq	0.417	0.007	0.424
runCxds	0.305	0.004	0.309
runCxdsBcdsHybrid	1.936	0.064	1.215
runDEAnalysis	0.411	0.010	0.421
runDecontX	6.952	0.102	7.054
runDimReduce	0.276	0.001	0.277
runDoubletFinder	34.760	0.203	34.964
runDropletQC	0.022	0.001	0.022
runEmptyDrops	6.249	0.001	6.251
runEnrichR	0.585	0.018	2.780
runFastMNN	1.690	0.026	1.717
runFeatureSelection	0.209	0.003	0.213
runFindMarker	1.379	0.069	1.449
runGSVA	0.707	0.055	0.763
runHarmony	0.041	0.000	0.042
runKMeans	0.273	0.051	0.324
runLimmaBC	0.077	0.007	0.083
runMNNCorrect	0.397	0.039	0.436
runModelGeneVar	0.303	0.025	0.327
runNormalization	2.596	0.431	3.027
runPerCellQC	0.326	0.017	0.343
runSCANORAMA	0	0	0
runSCMerge	0.003	0.001	0.004
runScDblFinder	20.596	1.251	21.566
runScanpyFindClusters	0.021	0.000	0.022
runScanpyFindHVG	0.022	0.000	0.022
runScanpyFindMarkers	0.021	0.000	0.022
runScanpyNormalizeData	0.093	0.001	0.094
runScanpyPCA	0.022	0.000	0.023
runScanpyScaleData	0.023	0.000	0.023
runScanpyTSNE	0.022	0.000	0.022
runScanpyUMAP	0.022	0.000	0.022
runScranSNN	0.275	0.002	0.277
runScrublet	0.022	0.000	0.022
runSeuratFindClusters	0.020	0.002	0.022
runSeuratFindHVG	0.456	0.013	0.469
runSeuratHeatmap	0.023	0.000	0.023
runSeuratICA	0.022	0.000	0.022
runSeuratJackStraw	0.022	0.000	0.022
runSeuratNormalizeData	0.020	0.002	0.022
runSeuratPCA	0.022	0.000	0.022
runSeuratSCTransform	28.384	0.633	29.020
runSeuratScaleData	0.020	0.003	0.023
runSeuratUMAP	0.022	0.000	0.022
runSingleR	0.035	0.001	0.036
runSoupX	0	0	0
runTSCAN	0.625	0.006	0.631
runTSCANClusterDEAnalysis	0.739	0.007	0.747
runTSCANDEG	0.762	0.052	0.814
runTSNE	0.715	0.006	0.720
runUMAP	7.806	0.156	7.960
runVAM	0.288	0.002	0.291
runZINBWaVE	0.003	0.001	0.004
sampleSummaryStats	0.149	0.001	0.149
scaterCPM	0.135	0.009	0.143
scaterPCA	0.448	0.000	0.447
scaterlogNormCounts	0.229	0.007	0.236
sce	0.019	0.002	0.021
sctkListGeneSetCollections	0.076	0.002	0.078
sctkPythonInstallConda	0.000	0.000	0.001
sctkPythonInstallVirtualEnv	0.000	0.001	0.000
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.081	0.001	0.083
setSCTKDisplayRow	0.406	0.004	0.411
singleCellTK	0	0	0
subDiffEx	0.318	0.001	0.319
subsetSCECols	0.078	0.001	0.079
subsetSCERows	0.257	0.001	0.258
summarizeSCE	0.066	0.001	0.067
trimCounts	0.197	0.008	0.204