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: 2026-01-23 04:10:58 -0500 (Fri, 23 Jan 2026)

EndedAt: 2026-01-23 04:28:09 -0500 (Fri, 23 Jan 2026)

EllapsedTime: 1031.8 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 44.999  0.795  45.795
plotDoubletFinderResults 39.865  0.292  40.238
runDoubletFinder         35.851  0.334  36.187
runSeuratSCTransform     29.768  0.234  30.007
plotScDblFinderResults   28.539  0.683  29.265
runScDblFinder           18.239  0.392  18.595
plotBatchCorrCompare     13.344  0.079  13.608
importExampleData        10.960  0.347  11.753
plotDecontXResults        8.703  0.059   8.762
runUMAP                   8.512  0.141   8.730
plotUMAP                  7.598  0.138   7.813
runDecontX                7.539  0.066   7.606
plotCxdsResults           7.387  0.089   7.570
plotScdsHybridResults     7.347  0.069   7.495
detectCellOutlier         6.648  0.202   6.854
plotDEGViolin             6.657  0.139   6.790
plotEmptyDropsResults     6.644  0.035   6.679
plotEmptyDropsScatter     6.548  0.048   6.596
runEmptyDrops             6.237  0.010   6.248
plotBcdsResults           5.799  0.068   5.947
* 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 
  0.152   0.033   0.173

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 
332.514   5.794 338.855

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.002	0.001	0.003
SEG	0.001	0.001	0.002
calcEffectSizes	0.182	0.007	0.189
combineSCE	0.737	0.003	0.739
computeZScore	0.240	0.008	0.248
convertSCEToSeurat	4.656	0.100	4.757
convertSeuratToSCE	0.333	0.005	0.338
dedupRowNames	0.054	0.000	0.054
detectCellOutlier	6.648	0.202	6.854
diffAbundanceFET	0.054	0.000	0.054
discreteColorPalette	0.006	0.000	0.006
distinctColors	0.002	0.000	0.002
downSampleCells	0.490	0.087	0.576
downSampleDepth	0.417	0.010	0.427
expData-ANY-character-method	0.125	0.001	0.126
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.161	0.002	0.164
expData-set	0.157	0.001	0.158
expData	0.126	0.004	0.130
expDataNames-ANY-method	0.123	0.003	0.126
expDataNames	0.119	0.010	0.129
expDeleteDataTag	0.035	0.001	0.036
expSetDataTag	0.025	0.001	0.026
expTaggedData	0.028	0.000	0.029
exportSCE	0.023	0.000	0.023
exportSCEtoAnnData	0.091	0.008	0.099
exportSCEtoFlatFile	0.092	0.007	0.099
featureIndex	0.036	0.002	0.038
generateSimulatedData	0.075	0.003	0.078
getBiomarker	0.058	0.001	0.059
getDEGTopTable	0.658	0.004	0.663
getDiffAbundanceResults	0.047	0.000	0.047
getEnrichRResult	0.516	0.038	3.120
getFindMarkerTopTable	1.562	0.038	1.600
getMSigDBTable	0.003	0.000	0.003
getPathwayResultNames	0.019	0.003	0.021
getSampleSummaryStatsTable	0.197	0.001	0.198
getSoupX	0	0	0
getTSCANResults	0.973	0.024	0.997
getTopHVG	0.832	0.012	0.845
importAnnData	0.001	0.000	0.002
importBUStools	0.154	0.000	0.155
importCellRanger	0.727	0.004	0.731
importCellRangerV2Sample	0.138	0.000	0.137
importCellRangerV3Sample	0.276	0.002	0.277
importDropEst	1.616	0.102	1.718
importExampleData	10.960	0.347	11.753
importGeneSetsFromCollection	1.891	0.034	1.925
importGeneSetsFromGMT	0.063	0.002	0.066
importGeneSetsFromList	0.128	0.001	0.130
importGeneSetsFromMSigDB	44.999	0.795	45.795
importMitoGeneSet	0.052	0.005	0.057
importOptimus	0.001	0.000	0.002
importSEQC	0.136	0.019	0.155
importSTARsolo	0.134	0.026	0.161
iterateSimulations	0.170	0.026	0.195
listSampleSummaryStatsTables	0.237	0.037	0.275
mergeSCEColData	0.358	0.012	0.370
mouseBrainSubsetSCE	0.036	0.000	0.035
msigdb_table	0.002	0.000	0.001
plotBarcodeRankDropsResults	0.867	0.006	0.874
plotBarcodeRankScatter	0.844	0.001	0.845
plotBatchCorrCompare	13.344	0.079	13.608
plotBatchVariance	0.463	0.003	0.466
plotBcdsResults	5.799	0.068	5.947
plotBubble	0.757	0.002	0.760
plotClusterAbundance	1.301	0.001	1.301
plotCxdsResults	7.387	0.089	7.570
plotDEGHeatmap	2.013	0.046	2.059
plotDEGRegression	4.324	0.010	4.328
plotDEGViolin	6.657	0.139	6.790
plotDEGVolcano	0.911	0.020	0.931
plotDecontXResults	8.703	0.059	8.762
plotDimRed	0.280	0.003	0.283
plotDoubletFinderResults	39.865	0.292	40.238
plotEmptyDropsResults	6.644	0.035	6.679
plotEmptyDropsScatter	6.548	0.048	6.596
plotFindMarkerHeatmap	3.886	0.044	3.931
plotMASTThresholdGenes	1.254	0.011	1.265
plotPCA	0.369	0.001	0.370
plotPathway	0.733	0.020	0.754
plotRunPerCellQCResults	3.062	0.031	3.093
plotSCEBarAssayData	0.343	0.001	0.345
plotSCEBarColData	0.242	0.000	0.241
plotSCEBatchFeatureMean	0.391	0.001	0.392
plotSCEDensity	0.328	0.001	0.329
plotSCEDensityAssayData	0.331	0.000	0.330
plotSCEDensityColData	0.302	0.002	0.304
plotSCEDimReduceColData	0.734	0.003	0.738
plotSCEDimReduceFeatures	0.415	0.002	0.417
plotSCEHeatmap	0.405	0.007	0.412
plotSCEScatter	0.353	0.003	0.356
plotSCEViolin	0.408	0.001	0.409
plotSCEViolinAssayData	0.358	0.002	0.360
plotSCEViolinColData	0.345	0.001	0.347
plotScDblFinderResults	28.539	0.683	29.265
plotScanpyDotPlot	0.022	0.000	0.023
plotScanpyEmbedding	0.022	0.000	0.023
plotScanpyHVG	0.022	0.000	0.022
plotScanpyHeatmap	0.021	0.000	0.022
plotScanpyMarkerGenes	0.022	0.000	0.021
plotScanpyMarkerGenesDotPlot	0.021	0.000	0.021
plotScanpyMarkerGenesHeatmap	0.022	0.000	0.022
plotScanpyMarkerGenesMatrixPlot	0.022	0.000	0.022
plotScanpyMarkerGenesViolin	0.022	0.000	0.022
plotScanpyMatrixPlot	0.022	0.000	0.022
plotScanpyPCA	0.020	0.001	0.022
plotScanpyPCAGeneRanking	0.022	0.000	0.022
plotScanpyPCAVariance	0.023	0.000	0.022
plotScanpyViolin	0.023	0.000	0.023
plotScdsHybridResults	7.347	0.069	7.495
plotScrubletResults	0.022	0.000	0.022
plotSeuratElbow	0.022	0.000	0.021
plotSeuratHVG	0.021	0.000	0.022
plotSeuratJackStraw	0.023	0.000	0.023
plotSeuratReduction	0.022	0.000	0.021
plotSoupXResults	0	0	0
plotTSCANClusterDEG	4.696	0.014	4.709
plotTSCANClusterPseudo	1.396	0.002	1.399
plotTSCANDimReduceFeatures	1.342	0.003	1.345
plotTSCANPseudotimeGenes	1.618	0.004	1.623
plotTSCANPseudotimeHeatmap	1.367	0.007	1.373
plotTSCANResults	1.250	0.003	1.253
plotTSNE	0.384	0.000	0.384
plotTopHVG	0.676	0.002	0.678
plotUMAP	7.598	0.138	7.813
readSingleCellMatrix	0.005	0.000	0.004
reportCellQC	0.077	0.000	0.076
reportDropletQC	0.022	0.000	0.021
reportQCTool	0.078	0.000	0.077
retrieveSCEIndex	0.028	0.000	0.029
runBBKNN	0	0	0
runBarcodeRankDrops	0.223	0.002	0.224
runBcds	0.079	0.000	0.079
runCellQC	0.078	0.001	0.079
runClusterSummaryMetrics	0.367	0.001	0.368
runComBatSeq	0.421	0.003	0.424
runCxds	0.341	0.001	0.342
runCxdsBcdsHybrid	0.077	0.001	0.078
runDEAnalysis	0.365	0.000	0.365
runDecontX	7.539	0.066	7.606
runDimReduce	0.28	0.00	0.28
runDoubletFinder	35.851	0.334	36.187
runDropletQC	0.022	0.000	0.022
runEmptyDrops	6.237	0.010	6.248
runEnrichR	0.563	0.035	2.807
runFastMNN	1.692	0.075	1.767
runFeatureSelection	0.209	0.001	0.210
runFindMarker	1.375	0.005	1.380
runGSVA	0.842	0.013	0.856
runHarmony	0.042	0.000	0.042
runKMeans	0.178	0.001	0.180
runLimmaBC	0.081	0.000	0.081
runMNNCorrect	0.415	0.000	0.415
runModelGeneVar	0.304	0.001	0.305
runNormalization	2.648	0.064	2.712
runPerCellQC	0.336	0.000	0.336
runSCANORAMA	0	0	0
runSCMerge	0.003	0.000	0.003
runScDblFinder	18.239	0.392	18.595
runScanpyFindClusters	0.023	0.000	0.023
runScanpyFindHVG	0.022	0.000	0.022
runScanpyFindMarkers	0.021	0.001	0.022
runScanpyNormalizeData	0.097	0.001	0.098
runScanpyPCA	0.022	0.000	0.022
runScanpyScaleData	0.021	0.000	0.021
runScanpyTSNE	0.022	0.000	0.021
runScanpyUMAP	0.021	0.000	0.022
runScranSNN	0.292	0.002	0.295
runScrublet	0.022	0.000	0.022
runSeuratFindClusters	0.021	0.000	0.022
runSeuratFindHVG	0.471	0.001	0.471
runSeuratHeatmap	0.022	0.000	0.023
runSeuratICA	0.021	0.000	0.022
runSeuratJackStraw	0.021	0.000	0.022
runSeuratNormalizeData	0.021	0.000	0.022
runSeuratPCA	0.020	0.001	0.022
runSeuratSCTransform	29.768	0.234	30.007
runSeuratScaleData	0.021	0.001	0.022
runSeuratUMAP	0.021	0.001	0.021
runSingleR	0.037	0.000	0.037
runSoupX	0	0	0
runTSCAN	0.669	0.001	0.671
runTSCANClusterDEAnalysis	0.760	0.003	0.764
runTSCANDEG	0.749	0.002	0.751
runTSNE	0.730	0.002	0.732
runUMAP	8.512	0.141	8.730
runVAM	0.293	0.001	0.294
runZINBWaVE	0.003	0.001	0.004
sampleSummaryStats	0.151	0.001	0.152
scaterCPM	0.140	0.004	0.144
scaterPCA	0.463	0.002	0.464
scaterlogNormCounts	0.237	0.007	0.244
sce	0.021	0.000	0.021
sctkListGeneSetCollections	0.084	0.000	0.084
sctkPythonInstallConda	0.000	0.000	0.001
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.090	0.000	0.091
setSCTKDisplayRow	0.433	0.001	0.435
singleCellTK	0	0	0
subDiffEx	0.325	0.001	0.326
subsetSCECols	0.084	0.000	0.084
subsetSCERows	0.271	0.001	0.273
summarizeSCE	0.068	0.001	0.069
trimCounts	0.206	0.007	0.212