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"	4825
kjohnson3	macOS 13.7.7 Ventura	arm64	R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"	4547
Click on any hostname to see more info about the system (e.g. compilers) () as reported by 'uname -p', except on Windows and Mac OS X*

CHECK results for singleCellTK on nebbiolo1

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

raw results

Summary

Package: singleCellTK

Version: 2.21.0

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

StartedAt: 2025-11-14 04:03:02 -0500 (Fri, 14 Nov 2025)

EndedAt: 2025-11-14 04:20:19 -0500 (Fri, 14 Nov 2025)

EllapsedTime: 1037.2 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 45.064  1.026  46.094
plotDoubletFinderResults 39.688  0.577  40.269
runDoubletFinder         35.676  0.266  35.952
plotScDblFinderResults   30.490  0.833  30.990
runSeuratSCTransform     28.954  1.092  30.053
runScDblFinder           20.452  1.466  21.608
plotBatchCorrCompare     13.443  0.372  13.818
importExampleData        12.038  1.453  13.910
plotScdsHybridResults    10.531  0.149   9.860
plotBcdsResults           9.667  0.238   9.113
plotDecontXResults        9.254  0.297   9.552
runUMAP                   7.953  0.244   8.197
plotCxdsResults           7.561  0.286   7.847
runDecontX                7.474  0.137   7.612
plotUMAP                  7.159  0.148   7.308
plotEmptyDropsResults     6.636  0.015   6.651
plotEmptyDropsScatter     6.563  0.020   6.583
runEmptyDrops             6.244  0.013   6.257
detectCellOutlier         6.019  0.200   6.219
plotDEGViolin             5.199  0.092   5.285
* 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 
  0.136   0.050   0.174

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 
316.439   8.108 328.732

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.003	0.000	0.003
SEG	0.001	0.002	0.003
calcEffectSizes	0.157	0.011	0.168
combineSCE	0.728	0.028	0.756
computeZScore	0.244	0.013	0.258
convertSCEToSeurat	4.718	0.148	4.868
convertSeuratToSCE	0.345	0.007	0.352
dedupRowNames	0.058	0.004	0.062
detectCellOutlier	6.019	0.200	6.219
diffAbundanceFET	0.055	0.002	0.057
discreteColorPalette	0.006	0.000	0.006
distinctColors	0.002	0.000	0.003
downSampleCells	0.518	0.062	0.580
downSampleDepth	0.447	0.050	0.497
expData-ANY-character-method	0.127	0.004	0.131
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.155	0.002	0.157
expData-set	0.145	0.002	0.148
expData	0.128	0.002	0.131
expDataNames-ANY-method	0.123	0.008	0.131
expDataNames	0.125	0.004	0.129
expDeleteDataTag	0.033	0.002	0.035
expSetDataTag	0.024	0.000	0.025
expTaggedData	0.025	0.002	0.027
exportSCE	0.021	0.000	0.021
exportSCEtoAnnData	0.090	0.009	0.100
exportSCEtoFlatFile	0.085	0.014	0.099
featureIndex	0.037	0.001	0.038
generateSimulatedData	0.051	0.004	0.055
getBiomarker	0.060	0.003	0.063
getDEGTopTable	0.743	0.076	0.819
getDiffAbundanceResults	0.048	0.001	0.049
getEnrichRResult	0.505	0.038	3.595
getFindMarkerTopTable	1.450	0.115	1.566
getMSigDBTable	0.003	0.001	0.005
getPathwayResultNames	0.022	0.002	0.023
getSampleSummaryStatsTable	0.180	0.015	0.194
getSoupX	0	0	0
getTSCANResults	1.071	0.109	1.180
getTopHVG	0.783	0.080	0.863
importAnnData	0.002	0.000	0.002
importBUStools	0.178	0.021	0.200
importCellRanger	0.706	0.024	0.731
importCellRangerV2Sample	0.150	0.009	0.159
importCellRangerV3Sample	0.411	0.038	0.449
importDropEst	0.189	0.025	0.216
importExampleData	12.038	1.453	13.910
importGeneSetsFromCollection	0.710	0.031	0.742
importGeneSetsFromGMT	0.061	0.002	0.063
importGeneSetsFromList	0.127	0.000	0.127
importGeneSetsFromMSigDB	45.064	1.026	46.094
importMitoGeneSet	0.050	0.005	0.055
importOptimus	0.002	0.000	0.001
importSEQC	0.143	0.013	0.156
importSTARsolo	0.151	0.028	0.180
iterateSimulations	0.182	0.029	0.211
listSampleSummaryStatsTables	0.264	0.027	0.291
mergeSCEColData	0.386	0.030	0.416
mouseBrainSubsetSCE	0.036	0.002	0.038
msigdb_table	0.001	0.000	0.001
plotBarcodeRankDropsResults	0.860	0.034	0.894
plotBarcodeRankScatter	0.826	0.043	0.869
plotBatchCorrCompare	13.443	0.372	13.818
plotBatchVariance	0.498	0.014	0.514
plotBcdsResults	9.667	0.238	9.113
plotBubble	0.819	0.017	0.836
plotClusterAbundance	1.315	0.002	1.316
plotCxdsResults	7.561	0.286	7.847
plotDEGHeatmap	1.981	0.069	2.050
plotDEGRegression	4.194	0.023	4.212
plotDEGViolin	5.199	0.092	5.285
plotDEGVolcano	0.931	0.006	0.938
plotDecontXResults	9.254	0.297	9.552
plotDimRed	0.282	0.014	0.296
plotDoubletFinderResults	39.688	0.577	40.269
plotEmptyDropsResults	6.636	0.015	6.651
plotEmptyDropsScatter	6.563	0.020	6.583
plotFindMarkerHeatmap	3.745	0.017	3.762
plotMASTThresholdGenes	1.272	0.031	1.303
plotPCA	0.360	0.003	0.362
plotPathway	0.712	0.006	0.718
plotRunPerCellQCResults	3.025	0.011	3.036
plotSCEBarAssayData	0.286	0.011	0.298
plotSCEBarColData	0.303	0.011	0.315
plotSCEBatchFeatureMean	0.393	0.002	0.396
plotSCEDensity	0.312	0.008	0.320
plotSCEDensityAssayData	0.279	0.001	0.280
plotSCEDensityColData	0.347	0.001	0.348
plotSCEDimReduceColData	0.715	0.003	0.718
plotSCEDimReduceFeatures	0.414	0.002	0.416
plotSCEHeatmap	0.415	0.001	0.417
plotSCEScatter	0.347	0.002	0.349
plotSCEViolin	0.360	0.001	0.361
plotSCEViolinAssayData	0.405	0.003	0.408
plotSCEViolinColData	0.358	0.020	0.378
plotScDblFinderResults	30.490	0.833	30.990
plotScanpyDotPlot	0.024	0.000	0.024
plotScanpyEmbedding	0.022	0.001	0.023
plotScanpyHVG	0.020	0.001	0.021
plotScanpyHeatmap	0.020	0.001	0.021
plotScanpyMarkerGenes	0.020	0.002	0.022
plotScanpyMarkerGenesDotPlot	0.021	0.001	0.022
plotScanpyMarkerGenesHeatmap	0.020	0.002	0.023
plotScanpyMarkerGenesMatrixPlot	0.022	0.000	0.022
plotScanpyMarkerGenesViolin	0.021	0.001	0.022
plotScanpyMatrixPlot	0.021	0.001	0.022
plotScanpyPCA	0.021	0.000	0.021
plotScanpyPCAGeneRanking	0.022	0.001	0.023
plotScanpyPCAVariance	0.021	0.001	0.022
plotScanpyViolin	0.021	0.000	0.022
plotScdsHybridResults	10.531	0.149	9.860
plotScrubletResults	0.023	0.000	0.024
plotSeuratElbow	0.022	0.000	0.022
plotSeuratHVG	0.020	0.001	0.022
plotSeuratJackStraw	0.022	0.000	0.021
plotSeuratReduction	0.020	0.001	0.022
plotSoupXResults	0	0	0
plotTSCANClusterDEG	4.884	0.013	4.898
plotTSCANClusterPseudo	1.349	0.005	1.354
plotTSCANDimReduceFeatures	1.367	0.002	1.369
plotTSCANPseudotimeGenes	1.638	0.011	1.650
plotTSCANPseudotimeHeatmap	1.327	0.002	1.329
plotTSCANResults	1.255	0.002	1.259
plotTSNE	0.373	0.000	0.373
plotTopHVG	0.606	0.004	0.610
plotUMAP	7.159	0.148	7.308
readSingleCellMatrix	0.005	0.000	0.005
reportCellQC	0.075	0.002	0.077
reportDropletQC	0.021	0.000	0.022
reportQCTool	0.076	0.001	0.077
retrieveSCEIndex	0.027	0.001	0.028
runBBKNN	0.000	0.000	0.001
runBarcodeRankDrops	0.210	0.001	0.211
runBcds	1.990	0.013	1.192
runCellQC	0.089	0.000	0.089
runClusterSummaryMetrics	0.369	0.001	0.371
runComBatSeq	0.424	0.006	0.430
runCxds	0.304	0.001	0.305
runCxdsBcdsHybrid	1.982	0.066	1.239
runDEAnalysis	0.453	0.004	0.457
runDecontX	7.474	0.137	7.612
runDimReduce	0.281	0.002	0.283
runDoubletFinder	35.676	0.266	35.952
runDropletQC	0.021	0.002	0.023
runEmptyDrops	6.244	0.013	6.257
runEnrichR	0.527	0.123	2.853
runFastMNN	1.702	0.153	1.855
runFeatureSelection	0.203	0.015	0.219
runFindMarker	1.432	0.096	1.529
runGSVA	0.711	0.110	0.821
runHarmony	0.038	0.003	0.042
runKMeans	0.259	0.063	0.321
runLimmaBC	0.074	0.009	0.084
runMNNCorrect	0.415	0.050	0.466
runModelGeneVar	0.296	0.052	0.347
runNormalization	2.576	0.649	3.226
runPerCellQC	0.315	0.010	0.325
runSCANORAMA	0	0	0
runSCMerge	0.004	0.001	0.004
runScDblFinder	20.452	1.466	21.608
runScanpyFindClusters	0.022	0.001	0.022
runScanpyFindHVG	0.021	0.000	0.022
runScanpyFindMarkers	0.020	0.001	0.022
runScanpyNormalizeData	0.090	0.009	0.100
runScanpyPCA	0.022	0.001	0.022
runScanpyScaleData	0.022	0.000	0.022
runScanpyTSNE	0.022	0.000	0.022
runScanpyUMAP	0.021	0.001	0.022
runScranSNN	0.282	0.002	0.283
runScrublet	0.021	0.001	0.022
runSeuratFindClusters	0.022	0.000	0.021
runSeuratFindHVG	0.455	0.010	0.464
runSeuratHeatmap	0.022	0.001	0.023
runSeuratICA	0.022	0.001	0.022
runSeuratJackStraw	0.022	0.000	0.022
runSeuratNormalizeData	0.022	0.000	0.022
runSeuratPCA	0.022	0.000	0.022
runSeuratSCTransform	28.954	1.092	30.053
runSeuratScaleData	0.021	0.002	0.023
runSeuratUMAP	0.023	0.000	0.024
runSingleR	0.037	0.004	0.041
runSoupX	0.001	0.000	0.001
runTSCAN	0.692	0.018	0.711
runTSCANClusterDEAnalysis	0.780	0.035	0.815
runTSCANDEG	0.777	0.051	0.829
runTSNE	0.725	0.017	0.744
runUMAP	7.953	0.244	8.197
runVAM	0.286	0.004	0.290
runZINBWaVE	0.004	0.000	0.005
sampleSummaryStats	0.156	0.002	0.157
scaterCPM	0.135	0.009	0.144
scaterPCA	0.445	0.000	0.445
scaterlogNormCounts	0.236	0.013	0.249
sce	0.021	0.002	0.023
sctkListGeneSetCollections	0.081	0.003	0.085
sctkPythonInstallConda	0.000	0.000	0.001
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0.001	0.000	0.000
selectSCTKVirtualEnvironment	0.000	0.001	0.000
setRowNames	0.093	0.000	0.093
setSCTKDisplayRow	0.464	0.019	0.483
singleCellTK	0	0	0
subDiffEx	0.333	0.006	0.340
subsetSCECols	0.080	0.000	0.079
subsetSCERows	0.277	0.006	0.282
summarizeSCE	0.072	0.001	0.072
trimCounts	0.211	0.011	0.221