Multiple platform 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"	4866
kjohnson3	macOS 13.7.7 Ventura	arm64	R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"	4572
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: 2025-12-01 04:15:30 -0500 (Mon, 01 Dec 2025)

EndedAt: 2025-12-01 04:32:55 -0500 (Mon, 01 Dec 2025)

EllapsedTime: 1045.1 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 45.139  0.828  45.968
plotDoubletFinderResults 40.339  0.376  40.715
runDoubletFinder         35.916  0.190  36.107
plotScDblFinderResults   30.700  0.851  31.263
runSeuratSCTransform     28.876  0.307  29.189
runScDblFinder           20.843  0.461  21.003
plotBatchCorrCompare     13.667  0.171  13.839
importExampleData        10.196  0.539  11.131
plotScdsHybridResults    10.505  0.098   9.791
plotBcdsResults           8.981  0.169   8.402
plotDecontXResults        8.758  0.019   8.776
runUMAP                   8.324  0.146   8.469
plotUMAP                  7.684  0.051   7.734
plotCxdsResults           7.577  0.118   7.696
runDecontX                7.611  0.042   7.653
plotEmptyDropsResults     6.677  0.017   6.693
plotEmptyDropsScatter     6.545  0.014   6.560
runEmptyDrops             6.254  0.012   6.267
detectCellOutlier         5.850  0.195   6.046
plotDEGViolin             5.167  0.059   5.221
* 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 
  0.160   0.040   0.184

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%

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Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 390
Number of edges: 9849

Running Louvain algorithm...
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Maximum modularity in 10 random starts: 0.8351
Number of communities: 7
Elapsed time: 0 seconds
Using method 'umap'
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
335.800   5.932 344.863

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.001	0.002	0.002
SEG	0.003	0.000	0.003
calcEffectSizes	0.159	0.013	0.173
combineSCE	0.724	0.033	0.756
computeZScore	0.230	0.015	0.245
convertSCEToSeurat	4.652	0.121	4.773
convertSeuratToSCE	0.313	0.010	0.323
dedupRowNames	0.054	0.002	0.058
detectCellOutlier	5.850	0.195	6.046
diffAbundanceFET	0.055	0.002	0.057
discreteColorPalette	0.006	0.000	0.007
distinctColors	0.003	0.000	0.002
downSampleCells	0.491	0.065	0.556
downSampleDepth	0.404	0.005	0.409
expData-ANY-character-method	0.128	0.002	0.130
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.168	0.001	0.169
expData-set	0.156	0.001	0.156
expData	0.137	0.008	0.145
expDataNames-ANY-method	0.122	0.014	0.136
expDataNames	0.124	0.008	0.133
expDeleteDataTag	0.037	0.001	0.037
expSetDataTag	0.022	0.003	0.026
expTaggedData	0.023	0.002	0.026
exportSCE	0.022	0.001	0.023
exportSCEtoAnnData	0.089	0.012	0.101
exportSCEtoFlatFile	0.090	0.009	0.100
featureIndex	0.034	0.005	0.039
generateSimulatedData	0.049	0.008	0.057
getBiomarker	0.058	0.005	0.065
getDEGTopTable	0.750	0.099	0.848
getDiffAbundanceResults	0.048	0.000	0.049
getEnrichRResult	0.488	0.025	3.272
getFindMarkerTopTable	1.438	0.011	1.454
getMSigDBTable	0.004	0.001	0.004
getPathwayResultNames	0.022	0.000	0.022
getSampleSummaryStatsTable	0.169	0.001	0.170
getSoupX	0	0	0
getTSCANResults	1.003	0.012	1.015
getTopHVG	0.771	0.006	0.777
importAnnData	0.002	0.000	0.002
importBUStools	0.268	0.002	0.271
importCellRanger	0.673	0.007	0.682
importCellRangerV2Sample	0.136	0.002	0.139
importCellRangerV3Sample	0.274	0.004	0.278
importDropEst	0.186	0.002	0.189
importExampleData	10.196	0.539	11.131
importGeneSetsFromCollection	0.703	0.038	0.741
importGeneSetsFromGMT	0.060	0.004	0.065
importGeneSetsFromList	0.119	0.002	0.122
importGeneSetsFromMSigDB	45.139	0.828	45.968
importMitoGeneSet	0.048	0.009	0.058
importOptimus	0.002	0.000	0.001
importSEQC	0.135	0.017	0.152
importSTARsolo	0.137	0.031	0.168
iterateSimulations	0.178	0.026	0.204
listSampleSummaryStatsTables	0.251	0.034	0.284
mergeSCEColData	0.363	0.020	0.384
mouseBrainSubsetSCE	0.036	0.001	0.037
msigdb_table	0.000	0.001	0.002
plotBarcodeRankDropsResults	0.844	0.010	0.855
plotBarcodeRankScatter	0.827	0.003	0.830
plotBatchCorrCompare	13.667	0.171	13.839
plotBatchVariance	0.498	0.026	0.524
plotBcdsResults	8.981	0.169	8.402
plotBubble	0.756	0.001	0.757
plotClusterAbundance	1.286	0.002	1.288
plotCxdsResults	7.577	0.118	7.696
plotDEGHeatmap	2.041	0.015	2.056
plotDEGRegression	4.550	0.060	4.604
plotDEGViolin	5.167	0.059	5.221
plotDEGVolcano	0.935	0.006	0.941
plotDecontXResults	8.758	0.019	8.776
plotDimRed	0.29	0.00	0.29
plotDoubletFinderResults	40.339	0.376	40.715
plotEmptyDropsResults	6.677	0.017	6.693
plotEmptyDropsScatter	6.545	0.014	6.560
plotFindMarkerHeatmap	3.798	0.012	3.811
plotMASTThresholdGenes	1.261	0.012	1.273
plotPCA	0.380	0.004	0.385
plotPathway	0.753	0.003	0.756
plotRunPerCellQCResults	3.115	0.002	3.118
plotSCEBarAssayData	0.290	0.000	0.291
plotSCEBarColData	0.283	0.000	0.282
plotSCEBatchFeatureMean	0.383	0.001	0.384
plotSCEDensity	0.307	0.001	0.309
plotSCEDensityAssayData	0.276	0.001	0.276
plotSCEDensityColData	0.351	0.001	0.352
plotSCEDimReduceColData	0.764	0.003	0.768
plotSCEDimReduceFeatures	0.452	0.002	0.455
plotSCEHeatmap	0.428	0.000	0.429
plotSCEScatter	0.363	0.002	0.366
plotSCEViolin	0.371	0.000	0.371
plotSCEViolinAssayData	0.444	0.000	0.444
plotSCEViolinColData	0.369	0.001	0.370
plotScDblFinderResults	30.700	0.851	31.263
plotScanpyDotPlot	0.023	0.000	0.023
plotScanpyEmbedding	0.022	0.001	0.023
plotScanpyHVG	0.021	0.001	0.022
plotScanpyHeatmap	0.022	0.000	0.022
plotScanpyMarkerGenes	0.022	0.000	0.022
plotScanpyMarkerGenesDotPlot	0.022	0.000	0.022
plotScanpyMarkerGenesHeatmap	0.020	0.001	0.022
plotScanpyMarkerGenesMatrixPlot	0.020	0.002	0.022
plotScanpyMarkerGenesViolin	0.022	0.000	0.022
plotScanpyMatrixPlot	0.020	0.001	0.022
plotScanpyPCA	0.021	0.001	0.022
plotScanpyPCAGeneRanking	0.021	0.001	0.022
plotScanpyPCAVariance	0.022	0.000	0.022
plotScanpyViolin	0.022	0.000	0.022
plotScdsHybridResults	10.505	0.098	9.791
plotScrubletResults	0.022	0.001	0.023
plotSeuratElbow	0.021	0.001	0.022
plotSeuratHVG	0.022	0.000	0.021
plotSeuratJackStraw	0.019	0.002	0.022
plotSeuratReduction	0.022	0.000	0.022
plotSoupXResults	0	0	0
plotTSCANClusterDEG	4.980	0.016	4.997
plotTSCANClusterPseudo	1.435	0.003	1.439
plotTSCANDimReduceFeatures	1.420	0.005	1.425
plotTSCANPseudotimeGenes	1.644	0.004	1.648
plotTSCANPseudotimeHeatmap	1.392	0.003	1.395
plotTSCANResults	1.268	0.008	1.276
plotTSNE	0.383	0.003	0.387
plotTopHVG	0.637	0.003	0.640
plotUMAP	7.684	0.051	7.734
readSingleCellMatrix	0.006	0.000	0.006
reportCellQC	0.076	0.002	0.078
reportDropletQC	0.022	0.000	0.022
reportQCTool	0.079	0.000	0.079
retrieveSCEIndex	0.028	0.001	0.029
runBBKNN	0	0	0
runBarcodeRankDrops	0.215	0.000	0.215
runBcds	1.929	0.030	1.179
runCellQC	0.077	0.005	0.081
runClusterSummaryMetrics	0.363	0.006	0.370
runComBatSeq	0.427	0.005	0.433
runCxds	0.309	0.002	0.310
runCxdsBcdsHybrid	1.920	0.075	1.215
runDEAnalysis	0.461	0.008	0.469
runDecontX	7.611	0.042	7.653
runDimReduce	0.274	0.000	0.273
runDoubletFinder	35.916	0.190	36.107
runDropletQC	0.022	0.001	0.023
runEmptyDrops	6.254	0.012	6.267
runEnrichR	0.446	0.025	2.542
runFastMNN	1.681	0.045	1.725
runFeatureSelection	0.208	0.000	0.208
runFindMarker	1.390	0.023	1.413
runGSVA	0.879	0.024	0.904
runHarmony	0.037	0.002	0.040
runKMeans	0.172	0.001	0.173
runLimmaBC	0.081	0.000	0.081
runMNNCorrect	0.395	0.003	0.397
runModelGeneVar	0.282	0.002	0.283
runNormalization	2.544	0.124	2.668
runPerCellQC	0.326	0.003	0.329
runSCANORAMA	0.001	0.000	0.001
runSCMerge	0.004	0.000	0.004
runScDblFinder	20.843	0.461	21.003
runScanpyFindClusters	0.022	0.001	0.023
runScanpyFindHVG	0.021	0.001	0.022
runScanpyFindMarkers	0.022	0.000	0.022
runScanpyNormalizeData	0.094	0.000	0.095
runScanpyPCA	0.021	0.001	0.021
runScanpyScaleData	0.022	0.000	0.022
runScanpyTSNE	0.021	0.001	0.022
runScanpyUMAP	0.022	0.000	0.022
runScranSNN	0.284	0.003	0.287
runScrublet	0.022	0.000	0.022
runSeuratFindClusters	0.022	0.000	0.022
runSeuratFindHVG	0.458	0.014	0.472
runSeuratHeatmap	0.023	0.000	0.022
runSeuratICA	0.022	0.000	0.022
runSeuratJackStraw	0.022	0.000	0.022
runSeuratNormalizeData	0.021	0.001	0.022
runSeuratPCA	0.022	0.000	0.022
runSeuratSCTransform	28.876	0.307	29.189
runSeuratScaleData	0.023	0.000	0.023
runSeuratUMAP	0.022	0.000	0.022
runSingleR	0.036	0.001	0.037
runSoupX	0.000	0.000	0.001
runTSCAN	0.703	0.007	0.710
runTSCANClusterDEAnalysis	0.795	0.005	0.801
runTSCANDEG	0.763	0.005	0.769
runTSNE	0.718	0.002	0.720
runUMAP	8.324	0.146	8.469
runVAM	0.303	0.001	0.304
runZINBWaVE	0.004	0.001	0.005
sampleSummaryStats	0.170	0.001	0.172
scaterCPM	0.130	0.011	0.141
scaterPCA	0.468	0.003	0.471
scaterlogNormCounts	0.243	0.005	0.247
sce	0.023	0.000	0.023
sctkListGeneSetCollections	0.081	0.000	0.081
sctkPythonInstallConda	0.000	0.000	0.001
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.087	0.001	0.088
setSCTKDisplayRow	0.430	0.001	0.431
singleCellTK	0	0	0
subDiffEx	0.334	0.005	0.339
subsetSCECols	0.082	0.004	0.086
subsetSCERows	0.26	0.00	0.26
summarizeSCE	0.067	0.003	0.070
trimCounts	0.202	0.006	0.208