Build/check report for BioC 3.22 - CHECK results for singleCellTK on nebbiolo2

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo2	Linux (Ubuntu 24.04.3 LTS)	x86_64	4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"	4886
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 nebbiolo2

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: 2.20.1

Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings singleCellTK_2.20.1.tar.gz

StartedAt: 2026-01-27 04:15:58 -0500 (Tue, 27 Jan 2026)

EndedAt: 2026-01-27 04:32:48 -0500 (Tue, 27 Jan 2026)

EllapsedTime: 1009.8 seconds

RetCode: 0

Status: OK

CheckDir: singleCellTK.Rcheck

Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings singleCellTK_2.20.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.2 (2025-10-31)
* 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 ‘2.20.1’
* 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  7.0Mb
  sub-directories of 1Mb or more:
    R         1.0Mb
    extdata   1.6Mb
    shiny     3.0Mb
* 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 44.137  0.468  44.606
plotDoubletFinderResults 38.622  0.217  38.920
runDoubletFinder         37.299  0.154  37.456
runSeuratSCTransform     29.576  0.271  29.848
plotScDblFinderResults   28.926  0.695  29.658
runScDblFinder           17.826  0.442  18.232
plotBatchCorrCompare     13.561  0.171  13.919
importExampleData        10.050  0.402  10.918
plotDecontXResults        8.640  0.092   8.732
runUMAP                   8.114  0.107   8.300
runDecontX                7.766  0.058   7.825
plotScdsHybridResults     7.493  0.073   7.646
plotCxdsResults           7.494  0.067   7.638
plotUMAP                  7.009  0.071   7.156
plotDEGViolin             6.668  0.140   6.803
plotEmptyDropsResults     6.611  0.020   6.631
plotEmptyDropsScatter     6.525  0.011   6.536
runEmptyDrops             6.250  0.013   6.263
detectCellOutlier         6.065  0.166   6.233
plotBcdsResults           6.001  0.037   6.119
* 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-3.22-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.

Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.20.1’
** 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 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
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 
  0.144   0.033   0.166

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
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 46 | SKIP 0 | PASS 223 ]

[ FAIL 0 | WARN 46 | SKIP 0 | PASS 223 ]
> 
> proc.time()
   user  system elapsed 
321.673   5.851 327.917

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.002	0.000	0.002
SEG	0.003	0.001	0.003
calcEffectSizes	0.188	0.001	0.189
combineSCE	0.733	0.000	0.734
computeZScore	0.233	0.010	0.243
convertSCEToSeurat	4.376	0.094	4.471
convertSeuratToSCE	0.331	0.013	0.345
dedupRowNames	0.054	0.003	0.056
detectCellOutlier	6.065	0.166	6.233
diffAbundanceFET	0.051	0.000	0.052
discreteColorPalette	0.006	0.000	0.005
distinctColors	0.002	0.000	0.002
downSampleCells	0.486	0.046	0.532
downSampleDepth	0.398	0.003	0.402
expData-ANY-character-method	0.116	0.000	0.116
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.152	0.000	0.152
expData-set	0.144	0.001	0.145
expData	0.119	0.000	0.119
expDataNames-ANY-method	0.108	0.001	0.108
expDataNames	0.111	0.004	0.114
expDeleteDataTag	0.031	0.001	0.032
expSetDataTag	0.022	0.002	0.024
expTaggedData	0.022	0.001	0.023
exportSCE	0.021	0.000	0.021
exportSCEtoAnnData	0.091	0.005	0.097
exportSCEtoFlatFile	0.089	0.008	0.097
featureIndex	0.030	0.004	0.035
generateSimulatedData	0.063	0.004	0.067
getBiomarker	0.054	0.001	0.054
getDEGTopTable	0.633	0.041	0.674
getDiffAbundanceResults	0.045	0.001	0.046
getEnrichRResult	0.605	0.047	2.996
getFindMarkerTopTable	1.505	0.079	1.584
getMSigDBTable	0.002	0.001	0.003
getPathwayResultNames	0.021	0.001	0.023
getSampleSummaryStatsTable	0.195	0.003	0.198
getSoupX	0	0	0
getTSCANResults	0.967	0.009	0.976
getTopHVG	0.815	0.009	0.824
importAnnData	0.001	0.000	0.002
importBUStools	0.142	0.001	0.144
importCellRanger	0.734	0.014	0.748
importCellRangerV2Sample	0.134	0.002	0.136
importCellRangerV3Sample	0.265	0.005	0.271
importDropEst	1.445	0.016	1.462
importExampleData	10.050	0.402	10.918
importGeneSetsFromCollection	1.822	0.020	1.842
importGeneSetsFromGMT	0.064	0.001	0.065
importGeneSetsFromList	0.122	0.002	0.124
importGeneSetsFromMSigDB	44.137	0.468	44.606
importMitoGeneSet	0.049	0.003	0.052
importOptimus	0.001	0.000	0.002
importSEQC	0.140	0.017	0.157
importSTARsolo	0.142	0.020	0.162
iterateSimulations	0.171	0.029	0.200
listSampleSummaryStatsTables	0.251	0.027	0.278
mergeSCEColData	0.396	0.013	0.410
mouseBrainSubsetSCE	0.037	0.000	0.037
msigdb_table	0.001	0.001	0.001
plotBarcodeRankDropsResults	0.855	0.008	0.863
plotBarcodeRankScatter	0.836	0.014	0.851
plotBatchCorrCompare	13.561	0.171	13.919
plotBatchVariance	0.463	0.025	0.488
plotBcdsResults	6.001	0.037	6.119
plotBubble	0.775	0.001	0.776
plotClusterAbundance	1.314	0.000	1.314
plotCxdsResults	7.494	0.067	7.638
plotDEGHeatmap	1.980	0.006	1.986
plotDEGRegression	4.267	0.032	4.291
plotDEGViolin	6.668	0.140	6.803
plotDEGVolcano	0.946	0.005	0.951
plotDecontXResults	8.640	0.092	8.732
plotDimRed	0.29	0.00	0.29
plotDoubletFinderResults	38.622	0.217	38.920
plotEmptyDropsResults	6.611	0.020	6.631
plotEmptyDropsScatter	6.525	0.011	6.536
plotFindMarkerHeatmap	3.684	0.018	3.702
plotMASTThresholdGenes	1.245	0.008	1.253
plotPCA	0.367	0.004	0.372
plotPathway	0.698	0.002	0.700
plotRunPerCellQCResults	3.012	0.045	3.057
plotSCEBarAssayData	0.314	0.003	0.317
plotSCEBarColData	0.223	0.000	0.223
plotSCEBatchFeatureMean	0.384	0.003	0.387
plotSCEDensity	0.312	0.001	0.313
plotSCEDensityAssayData	0.326	0.000	0.326
plotSCEDensityColData	0.294	0.003	0.297
plotSCEDimReduceColData	0.752	0.001	0.753
plotSCEDimReduceFeatures	0.434	0.002	0.435
plotSCEHeatmap	0.419	0.000	0.420
plotSCEScatter	0.347	0.002	0.349
plotSCEViolin	0.407	0.020	0.426
plotSCEViolinAssayData	0.375	0.013	0.388
plotSCEViolinColData	0.377	0.007	0.383
plotScDblFinderResults	28.926	0.695	29.658
plotScanpyDotPlot	0.022	0.001	0.022
plotScanpyEmbedding	0.022	0.000	0.021
plotScanpyHVG	0.020	0.002	0.021
plotScanpyHeatmap	0.021	0.000	0.021
plotScanpyMarkerGenes	0.021	0.000	0.021
plotScanpyMarkerGenesDotPlot	0.021	0.000	0.022
plotScanpyMarkerGenesHeatmap	0.020	0.003	0.022
plotScanpyMarkerGenesMatrixPlot	0.020	0.000	0.021
plotScanpyMarkerGenesViolin	0.021	0.000	0.021
plotScanpyMatrixPlot	0.020	0.001	0.021
plotScanpyPCA	0.020	0.001	0.020
plotScanpyPCAGeneRanking	0.020	0.002	0.022
plotScanpyPCAVariance	0.020	0.000	0.021
plotScanpyViolin	0.020	0.001	0.021
plotScdsHybridResults	7.493	0.073	7.646
plotScrubletResults	0.022	0.000	0.023
plotSeuratElbow	0.021	0.000	0.022
plotSeuratHVG	0.021	0.000	0.022
plotSeuratJackStraw	0.021	0.000	0.022
plotSeuratReduction	0.021	0.000	0.021
plotSoupXResults	0	0	0
plotTSCANClusterDEG	4.823	0.010	4.834
plotTSCANClusterPseudo	1.425	0.003	1.429
plotTSCANDimReduceFeatures	1.358	0.004	1.362
plotTSCANPseudotimeGenes	1.623	0.000	1.623
plotTSCANPseudotimeHeatmap	1.377	0.005	1.383
plotTSCANResults	1.157	0.003	1.161
plotTSNE	0.358	0.000	0.359
plotTopHVG	0.637	0.004	0.641
plotUMAP	7.009	0.071	7.156
readSingleCellMatrix	0.004	0.000	0.005
reportCellQC	0.078	0.000	0.078
reportDropletQC	0.022	0.000	0.022
reportQCTool	0.079	0.000	0.079
retrieveSCEIndex	0.027	0.001	0.029
runBBKNN	0	0	0
runBarcodeRankDrops	0.226	0.000	0.225
runBcds	0.076	0.001	0.078
runCellQC	0.078	0.000	0.079
runClusterSummaryMetrics	0.37	0.00	0.37
runComBatSeq	0.434	0.002	0.435
runCxds	0.353	0.001	0.354
runCxdsBcdsHybrid	0.079	0.001	0.080
runDEAnalysis	0.377	0.001	0.378
runDecontX	7.766	0.058	7.825
runDimReduce	0.278	0.000	0.278
runDoubletFinder	37.299	0.154	37.456
runDropletQC	0.022	0.000	0.022
runEmptyDrops	6.250	0.013	6.263
runEnrichR	0.555	0.047	2.751
runFastMNN	1.657	0.026	1.682
runFeatureSelection	0.206	0.002	0.208
runFindMarker	1.368	0.016	1.385
runGSVA	0.830	0.009	0.839
runHarmony	0.039	0.001	0.040
runKMeans	0.174	0.006	0.180
runLimmaBC	0.081	0.001	0.082
runMNNCorrect	0.392	0.012	0.404
runModelGeneVar	0.306	0.012	0.318
runNormalization	2.517	0.131	2.647
runPerCellQC	0.319	0.001	0.320
runSCANORAMA	0	0	0
runSCMerge	0.004	0.000	0.004
runScDblFinder	17.826	0.442	18.232
runScanpyFindClusters	0.021	0.002	0.023
runScanpyFindHVG	0.022	0.001	0.022
runScanpyFindMarkers	0.023	0.000	0.022
runScanpyNormalizeData	0.095	0.000	0.095
runScanpyPCA	0.022	0.000	0.023
runScanpyScaleData	0.020	0.002	0.022
runScanpyTSNE	0.021	0.001	0.022
runScanpyUMAP	0.023	0.001	0.023
runScranSNN	0.283	0.013	0.295
runScrublet	0.023	0.000	0.023
runSeuratFindClusters	0.023	0.000	0.022
runSeuratFindHVG	0.464	0.002	0.467
runSeuratHeatmap	0.023	0.000	0.023
runSeuratICA	0.021	0.001	0.023
runSeuratJackStraw	0.022	0.000	0.023
runSeuratNormalizeData	0.022	0.000	0.022
runSeuratPCA	0.022	0.000	0.022
runSeuratSCTransform	29.576	0.271	29.848
runSeuratScaleData	0.023	0.001	0.024
runSeuratUMAP	0.023	0.001	0.024
runSingleR	0.038	0.001	0.039
runSoupX	0	0	0
runTSCAN	0.684	0.004	0.688
runTSCANClusterDEAnalysis	0.792	0.003	0.795
runTSCANDEG	0.809	0.013	0.821
runTSNE	0.730	0.011	0.741
runUMAP	8.114	0.107	8.300
runVAM	0.296	0.002	0.298
runZINBWaVE	0.004	0.000	0.004
sampleSummaryStats	0.153	0.000	0.153
scaterCPM	0.138	0.002	0.141
scaterPCA	0.437	0.001	0.438
scaterlogNormCounts	0.228	0.008	0.235
sce	0.022	0.000	0.021
sctkListGeneSetCollections	0.08	0.00	0.08
sctkPythonInstallConda	0	0	0
sctkPythonInstallVirtualEnv	0.001	0.000	0.000
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.085	0.000	0.084
setSCTKDisplayRow	0.416	0.000	0.416
singleCellTK	0	0	0
subDiffEx	0.322	0.000	0.323
subsetSCECols	0.078	0.001	0.078
subsetSCERows	0.262	0.001	0.262
summarizeSCE	0.068	0.001	0.068
trimCounts	0.198	0.006	0.204