Multiple platform build/check report for BioC 3.22 - CHECK results for singleCellTK on taishan

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"	4879
merida1	macOS 12.7.6 Monterey	x86_64	4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"	4670
kjohnson1	macOS 13.7.5 Ventura	arm64	4.5.2 Patched (2025-11-04 r88984) -- "[Not] Part in a Rumble"	4604
taishan	Linux (openEuler 24.03 LTS)	aarch64	4.5.0 (2025-04-11) -- "How About a Twenty-Six"	4669
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 taishan

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.
- See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host.

raw results

Summary

Package: singleCellTK

Version: 2.20.0

Command: /home/biocbuild/R/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings singleCellTK_2.20.0.tar.gz

StartedAt: 2025-12-09 15:49:44 -0000 (Tue, 09 Dec 2025)

EndedAt: 2025-12-09 16:11:39 -0000 (Tue, 09 Dec 2025)

EllapsedTime: 1315.4 seconds

RetCode: 0

Status: OK

CheckDir: singleCellTK.Rcheck

Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings singleCellTK_2.20.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.0 (2025-04-11)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.20.0’
* 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  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 50.861  0.650  51.625
plotDoubletFinderResults 43.773  0.235  44.242
runSeuratSCTransform     42.696  0.416  43.224
runDoubletFinder         35.449  0.248  35.766
plotScDblFinderResults   33.528  0.422  33.986
runScDblFinder           22.715  0.824  23.441
importExampleData        14.159  1.044  21.137
plotBatchCorrCompare     14.937  0.106  15.425
plotScdsHybridResults    11.102  0.030  10.500
plotBcdsResults          10.690  0.143  10.186
plotDecontXResults       10.488  0.053  10.570
plotCxdsResults           8.777  0.077   9.010
plotDEGViolin             8.260  0.052   8.334
runUMAP                   7.862  0.102   8.111
plotUMAP                  7.300  0.146   7.593
runDecontX                7.303  0.009   7.326
plotTSCANClusterDEG       7.069  0.008   7.098
plotDEGRegression         6.978  0.076   7.075
plotEmptyDropsResults     5.870  0.032   5.912
convertSCEToSeurat        5.581  0.227   5.837
plotFindMarkerHeatmap     5.767  0.036   5.816
plotEmptyDropsScatter     5.671  0.028   5.706
detectCellOutlier         5.194  0.195   5.410
runEmptyDrops             5.241  0.004   5.251
getEnrichRResult          0.450  0.079   9.753
runEnrichR                0.382  0.130  46.386
* 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 running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* 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/R/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-4.5.0/site-library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.20.0’
** 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 version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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 
  0.199   0.031   0.216

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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  |======================================================================| 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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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'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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  |======================================================================| 100%
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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  |======================================================================| 100%
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
381.457   8.065 410.667

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.003	0.000	0.003
SEG	0.000	0.003	0.002
calcEffectSizes	0.231	0.012	0.243
combineSCE	1.086	0.060	1.149
computeZScore	0.253	0.016	0.270
convertSCEToSeurat	5.581	0.227	5.837
convertSeuratToSCE	0.435	0.000	0.439
dedupRowNames	0.075	0.003	0.079
detectCellOutlier	5.194	0.195	5.410
diffAbundanceFET	0.058	0.000	0.058
discreteColorPalette	0.007	0.000	0.007
distinctColors	0.002	0.000	0.003
downSampleCells	0.737	0.036	0.777
downSampleDepth	0.578	0.012	0.591
expData-ANY-character-method	0.157	0.004	0.162
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.207	0.000	0.208
expData-set	0.193	0.004	0.197
expData	0.157	0.004	0.161
expDataNames-ANY-method	0.152	0.000	0.152
expDataNames	0.143	0.000	0.143
expDeleteDataTag	0.036	0.000	0.036
expSetDataTag	0.025	0.000	0.025
expTaggedData	0.028	0.008	0.037
exportSCE	0.017	0.004	0.022
exportSCEtoAnnData	0.075	0.000	0.075
exportSCEtoFlatFile	0.077	0.000	0.077
featureIndex	0.041	0.000	0.040
generateSimulatedData	0.06	0.00	0.06
getBiomarker	0.061	0.008	0.069
getDEGTopTable	0.949	0.064	1.015
getDiffAbundanceResults	0.052	0.000	0.052
getEnrichRResult	0.450	0.079	9.753
getFindMarkerTopTable	2.210	0.184	2.400
getMSigDBTable	0.004	0.000	0.005
getPathwayResultNames	0.027	0.003	0.031
getSampleSummaryStatsTable	0.260	0.028	0.289
getSoupX	0	0	0
getTSCANResults	1.457	0.096	1.558
getTopHVG	1.072	0.004	1.078
importAnnData	0.002	0.000	0.002
importBUStools	0.383	0.024	0.410
importCellRanger	1.023	0.060	1.118
importCellRangerV2Sample	0.202	0.000	0.203
importCellRangerV3Sample	0.447	0.020	0.469
importDropEst	0.263	0.004	0.269
importExampleData	14.159	1.044	21.137
importGeneSetsFromCollection	2.009	0.116	2.130
importGeneSetsFromGMT	0.086	0.000	0.088
importGeneSetsFromList	0.186	0.000	0.186
importGeneSetsFromMSigDB	50.861	0.650	51.625
importMitoGeneSet	0.074	0.004	0.078
importOptimus	0.002	0.000	0.002
importSEQC	0.217	0.008	0.228
importSTARsolo	0.230	0.024	0.257
iterateSimulations	0.249	0.024	0.273
listSampleSummaryStatsTables	0.339	0.032	0.373
mergeSCEColData	0.556	0.016	0.573
mouseBrainSubsetSCE	0.040	0.008	0.048
msigdb_table	0.000	0.001	0.001
plotBarcodeRankDropsResults	1.179	0.053	1.236
plotBarcodeRankScatter	1.236	0.008	1.247
plotBatchCorrCompare	14.937	0.106	15.425
plotBatchVariance	0.733	0.004	0.739
plotBcdsResults	10.690	0.143	10.186
plotBubble	1.171	0.012	1.187
plotClusterAbundance	2.103	0.004	2.114
plotCxdsResults	8.777	0.077	9.010
plotDEGHeatmap	3.029	0.048	3.086
plotDEGRegression	6.978	0.076	7.075
plotDEGViolin	8.260	0.052	8.334
plotDEGVolcano	1.270	0.004	1.277
plotDecontXResults	10.488	0.053	10.570
plotDimRed	0.428	0.000	0.428
plotDoubletFinderResults	43.773	0.235	44.242
plotEmptyDropsResults	5.870	0.032	5.912
plotEmptyDropsScatter	5.671	0.028	5.706
plotFindMarkerHeatmap	5.767	0.036	5.816
plotMASTThresholdGenes	1.810	0.024	1.837
plotPCA	0.523	0.000	0.524
plotPathway	1.095	0.000	1.100
plotRunPerCellQCResults	4.609	0.008	4.629
plotSCEBarAssayData	0.391	0.004	0.396
plotSCEBarColData	0.437	0.000	0.439
plotSCEBatchFeatureMean	0.617	0.000	0.618
plotSCEDensity	0.431	0.000	0.432
plotSCEDensityAssayData	0.385	0.000	0.386
plotSCEDensityColData	0.528	0.008	0.537
plotSCEDimReduceColData	1.064	0.024	1.091
plotSCEDimReduceFeatures	0.616	0.004	0.621
plotSCEHeatmap	0.588	0.004	0.594
plotSCEScatter	0.486	0.004	0.492
plotSCEViolin	0.515	0.000	0.517
plotSCEViolinAssayData	0.619	0.000	0.621
plotSCEViolinColData	0.499	0.000	0.501
plotScDblFinderResults	33.528	0.422	33.986
plotScanpyDotPlot	0.025	0.000	0.025
plotScanpyEmbedding	0.021	0.000	0.022
plotScanpyHVG	0.021	0.000	0.021
plotScanpyHeatmap	0.021	0.000	0.021
plotScanpyMarkerGenes	0.021	0.000	0.021
plotScanpyMarkerGenesDotPlot	0.021	0.000	0.021
plotScanpyMarkerGenesHeatmap	0.021	0.000	0.021
plotScanpyMarkerGenesMatrixPlot	0.021	0.000	0.021
plotScanpyMarkerGenesViolin	0.017	0.004	0.021
plotScanpyMatrixPlot	0.021	0.000	0.021
plotScanpyPCA	0.022	0.000	0.021
plotScanpyPCAGeneRanking	0.022	0.000	0.021
plotScanpyPCAVariance	0.021	0.000	0.021
plotScanpyViolin	0.021	0.000	0.021
plotScdsHybridResults	11.102	0.030	10.500
plotScrubletResults	0.023	0.000	0.023
plotSeuratElbow	0.023	0.000	0.023
plotSeuratHVG	0.023	0.000	0.022
plotSeuratJackStraw	0.024	0.000	0.024
plotSeuratReduction	0.022	0.000	0.023
plotSoupXResults	0	0	0
plotTSCANClusterDEG	7.069	0.008	7.098
plotTSCANClusterPseudo	1.969	0.008	1.982
plotTSCANDimReduceFeatures	1.987	0.024	2.016
plotTSCANPseudotimeGenes	2.434	0.004	2.444
plotTSCANPseudotimeHeatmap	2.053	0.028	2.085
plotTSCANResults	1.719	0.000	1.723
plotTSNE	0.526	0.000	0.527
plotTopHVG	0.943	0.000	0.946
plotUMAP	7.300	0.146	7.593
readSingleCellMatrix	0.007	0.000	0.006
reportCellQC	0.1	0.0	0.1
reportDropletQC	0.022	0.000	0.022
reportQCTool	0.102	0.000	0.103
retrieveSCEIndex	0.030	0.000	0.029
runBBKNN	0	0	0
runBarcodeRankDrops	0.287	0.000	0.288
runBcds	2.319	0.028	1.578
runCellQC	0.102	0.000	0.102
runClusterSummaryMetrics	0.509	0.004	0.515
runComBatSeq	0.648	0.000	0.649
runCxds	0.408	0.000	0.409
runCxdsBcdsHybrid	2.321	0.052	1.593
runDEAnalysis	0.591	0.008	0.601
runDecontX	7.303	0.009	7.326
runDimReduce	0.370	0.000	0.372
runDoubletFinder	35.449	0.248	35.766
runDropletQC	0.022	0.000	0.023
runEmptyDrops	5.241	0.004	5.251
runEnrichR	0.382	0.130	46.386
runFastMNN	2.397	0.217	2.624
runFeatureSelection	0.293	0.016	0.310
runFindMarker	2.119	0.135	2.260
runGSVA	1.321	0.088	1.413
runHarmony	0.053	0.004	0.057
runKMeans	0.234	0.012	0.246
runLimmaBC	0.102	0.020	0.122
runMNNCorrect	0.619	0.004	0.626
runModelGeneVar	0.432	0.015	0.449
runNormalization	2.812	0.208	3.026
runPerCellQC	0.448	0.020	0.469
runSCANORAMA	0.001	0.000	0.000
runSCMerge	0.004	0.000	0.005
runScDblFinder	22.715	0.824	23.441
runScanpyFindClusters	0.024	0.000	0.024
runScanpyFindHVG	0.024	0.000	0.023
runScanpyFindMarkers	0.023	0.000	0.023
runScanpyNormalizeData	0.131	0.000	0.132
runScanpyPCA	0.023	0.000	0.023
runScanpyScaleData	0.024	0.000	0.023
runScanpyTSNE	0.025	0.000	0.025
runScanpyUMAP	0.023	0.000	0.022
runScranSNN	0.390	0.004	0.395
runScrublet	0.026	0.000	0.026
runSeuratFindClusters	0.021	0.004	0.025
runSeuratFindHVG	0.672	0.008	0.682
runSeuratHeatmap	0.023	0.000	0.023
runSeuratICA	0.023	0.000	0.023
runSeuratJackStraw	0.023	0.000	0.023
runSeuratNormalizeData	0.022	0.000	0.023
runSeuratPCA	0.023	0.000	0.023
runSeuratSCTransform	42.696	0.416	43.224
runSeuratScaleData	0.022	0.000	0.022
runSeuratUMAP	0.021	0.000	0.021
runSingleR	0.05	0.00	0.05
runSoupX	0	0	0
runTSCAN	0.908	0.004	0.914
runTSCANClusterDEAnalysis	1.016	0.004	1.023
runTSCANDEG	1.093	0.020	1.116
runTSNE	1.045	0.000	1.047
runUMAP	7.862	0.102	8.111
runVAM	0.412	0.004	0.417
runZINBWaVE	0.005	0.000	0.005
sampleSummaryStats	0.212	0.000	0.212
scaterCPM	0.136	0.000	0.137
scaterPCA	0.615	0.000	0.616
scaterlogNormCounts	0.267	0.000	0.268
sce	0.023	0.000	0.022
sctkListGeneSetCollections	0.102	0.000	0.102
sctkPythonInstallConda	0	0	0
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.108	0.000	0.108
setSCTKDisplayRow	0.573	0.020	0.594
singleCellTK	0	0	0
subDiffEx	0.397	0.004	0.401
subsetSCECols	0.102	0.000	0.103
subsetSCERows	0.371	0.004	0.376
summarizeSCE	0.086	0.000	0.087
trimCounts	0.206	0.004	0.211