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"	4883
taishan	Linux (openEuler 24.03 LTS)	aarch64	4.5.0 (2025-04-11) -- "How About a Twenty-Six"	4671
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: 2025-12-26 15:09:04 -0000 (Fri, 26 Dec 2025)

EndedAt: 2025-12-26 15:34:51 -0000 (Fri, 26 Dec 2025)

EllapsedTime: 1546.7 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 49.634  0.849  60.401
runSeuratSCTransform     43.871  0.609  51.016
plotDoubletFinderResults 40.385  0.218  50.272
runDoubletFinder         33.799  0.195  42.581
plotScDblFinderResults   32.704  0.404  43.736
runScDblFinder           21.375  0.624  27.831
importExampleData        13.872  1.058  25.373
plotBatchCorrCompare     14.258  0.181  17.365
plotScdsHybridResults    11.616  0.044  14.673
plotBcdsResults          11.073  0.161  14.408
plotDecontXResults        9.654  0.072  12.187
plotCxdsResults           8.027  0.138   9.488
plotDEGViolin             8.012  0.075   8.972
plotTSCANClusterDEG       7.250  0.040   9.199
plotUMAP                  7.076  0.136  11.293
runDecontX                7.089  0.028   7.600
plotDEGRegression         6.916  0.097  13.280
runUMAP                   6.775  0.084   9.992
convertSCEToSeurat        5.662  0.279   7.119
plotEmptyDropsResults     5.877  0.016   9.173
plotEmptyDropsScatter     5.723  0.016   8.000
plotFindMarkerHeatmap     5.639  0.076   5.910
detectCellOutlier         5.422  0.164   6.628
runEmptyDrops             5.259  0.000   7.610
runEnrichR                0.408  0.096  39.824
getEnrichRResult          0.426  0.030   9.720
* 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 
  0.194   0.028   0.415

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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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 
361.360   7.654 471.543

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.003	0.000	0.008
SEG	0.003	0.000	0.003
calcEffectSizes	0.241	0.008	0.500
combineSCE	1.085	0.024	1.652
computeZScore	0.266	0.015	0.283
convertSCEToSeurat	5.662	0.279	7.119
convertSeuratToSCE	0.436	0.007	0.453
dedupRowNames	0.083	0.000	0.123
detectCellOutlier	5.422	0.164	6.628
diffAbundanceFET	0.063	0.004	0.068
discreteColorPalette	0.009	0.000	0.009
distinctColors	0.003	0.000	0.003
downSampleCells	0.764	0.048	1.013
downSampleDepth	0.590	0.000	0.804
expData-ANY-character-method	0.173	0.000	0.346
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.211	0.000	0.427
expData-set	0.218	0.012	0.457
expData	0.158	0.021	0.354
expDataNames-ANY-method	0.161	0.000	0.325
expDataNames	0.151	0.000	0.303
expDeleteDataTag	0.039	0.000	0.079
expSetDataTag	0.027	0.000	0.055
expTaggedData	0.029	0.000	0.063
exportSCE	0.020	0.004	0.049
exportSCEtoAnnData	0.077	0.000	0.153
exportSCEtoFlatFile	0.072	0.004	0.157
featureIndex	0.046	0.000	0.086
generateSimulatedData	0.064	0.004	0.136
getBiomarker	0.072	0.004	0.151
getDEGTopTable	1.019	0.092	2.231
getDiffAbundanceResults	0.056	0.000	0.112
getEnrichRResult	0.426	0.030	9.720
getFindMarkerTopTable	2.229	0.140	4.000
getMSigDBTable	0.005	0.000	0.008
getPathwayResultNames	0.020	0.004	0.054
getSampleSummaryStatsTable	0.242	0.020	0.322
getSoupX	0	0	0
getTSCANResults	1.442	0.111	1.671
getTopHVG	1.178	0.044	1.292
importAnnData	0.002	0.000	0.002
importBUStools	0.424	0.036	0.536
importCellRanger	1.052	0.080	1.253
importCellRangerV2Sample	0.208	0.012	0.220
importCellRangerV3Sample	0.446	0.020	0.891
importDropEst	0.267	0.000	0.292
importExampleData	13.872	1.058	25.373
importGeneSetsFromCollection	2.014	0.167	2.311
importGeneSetsFromGMT	0.084	0.004	0.147
importGeneSetsFromList	0.173	0.000	0.174
importGeneSetsFromMSigDB	49.634	0.849	60.401
importMitoGeneSet	0.073	0.004	0.078
importOptimus	0.002	0.000	0.002
importSEQC	0.204	0.021	0.243
importSTARsolo	0.225	0.044	0.541
iterateSimulations	0.256	0.032	0.576
listSampleSummaryStatsTables	0.352	0.051	0.617
mergeSCEColData	0.604	0.012	0.618
mouseBrainSubsetSCE	0.046	0.000	0.046
msigdb_table	0.001	0.000	0.001
plotBarcodeRankDropsResults	1.241	0.000	1.280
plotBarcodeRankScatter	1.312	0.001	2.158
plotBatchCorrCompare	14.258	0.181	17.365
plotBatchVariance	0.699	0.000	0.806
plotBcdsResults	11.073	0.161	14.408
plotBubble	1.137	0.012	1.217
plotClusterAbundance	1.990	0.004	2.099
plotCxdsResults	8.027	0.138	9.488
plotDEGHeatmap	2.926	0.016	3.002
plotDEGRegression	6.916	0.097	13.280
plotDEGViolin	8.012	0.075	8.972
plotDEGVolcano	1.296	0.008	1.438
plotDecontXResults	9.654	0.072	12.187
plotDimRed	0.399	0.000	0.408
plotDoubletFinderResults	40.385	0.218	50.272
plotEmptyDropsResults	5.877	0.016	9.173
plotEmptyDropsScatter	5.723	0.016	8.000
plotFindMarkerHeatmap	5.639	0.076	5.910
plotMASTThresholdGenes	1.847	0.004	2.414
plotPCA	0.507	0.000	0.590
plotPathway	1.038	0.008	1.689
plotRunPerCellQCResults	4.537	0.060	4.878
plotSCEBarAssayData	0.462	0.000	0.495
plotSCEBarColData	0.311	0.000	0.312
plotSCEBatchFeatureMean	0.551	0.000	0.570
plotSCEDensity	0.429	0.000	0.439
plotSCEDensityAssayData	0.451	0.000	0.527
plotSCEDensityColData	0.408	0.003	0.411
plotSCEDimReduceColData	1.031	0.004	1.221
plotSCEDimReduceFeatures	0.601	0.008	1.222
plotSCEHeatmap	0.599	0.000	0.845
plotSCEScatter	0.495	0.000	0.496
plotSCEViolin	0.584	0.000	0.586
plotSCEViolinAssayData	0.533	0.000	0.534
plotSCEViolinColData	0.504	0.004	0.773
plotScDblFinderResults	32.704	0.404	43.736
plotScanpyDotPlot	0.023	0.000	0.023
plotScanpyEmbedding	0.023	0.000	0.024
plotScanpyHVG	0.023	0.000	0.022
plotScanpyHeatmap	0.024	0.000	0.025
plotScanpyMarkerGenes	0.025	0.000	0.025
plotScanpyMarkerGenesDotPlot	0.022	0.000	0.023
plotScanpyMarkerGenesHeatmap	0.025	0.000	0.025
plotScanpyMarkerGenesMatrixPlot	0.026	0.000	0.026
plotScanpyMarkerGenesViolin	0.026	0.000	0.027
plotScanpyMatrixPlot	0.028	0.000	0.028
plotScanpyPCA	0.023	0.000	0.024
plotScanpyPCAGeneRanking	0.023	0.000	0.023
plotScanpyPCAVariance	0.023	0.000	0.035
plotScanpyViolin	0.022	0.000	0.031
plotScdsHybridResults	11.616	0.044	14.673
plotScrubletResults	0.022	0.000	0.047
plotSeuratElbow	0.023	0.000	0.048
plotSeuratHVG	0.023	0.000	0.047
plotSeuratJackStraw	0.023	0.000	0.047
plotSeuratReduction	0.023	0.000	0.048
plotSoupXResults	0.000	0.000	0.001
plotTSCANClusterDEG	7.250	0.040	9.199
plotTSCANClusterPseudo	1.907	0.020	2.054
plotTSCANDimReduceFeatures	2.051	0.016	2.221
plotTSCANPseudotimeGenes	2.440	0.004	2.493
plotTSCANPseudotimeHeatmap	1.872	0.023	1.971
plotTSCANResults	1.836	0.040	2.069
plotTSNE	0.537	0.000	0.626
plotTopHVG	0.975	0.008	1.143
plotUMAP	7.076	0.136	11.293
readSingleCellMatrix	0.007	0.000	0.015
reportCellQC	0.114	0.004	0.239
reportDropletQC	0.024	0.000	0.048
reportQCTool	0.111	0.004	0.232
retrieveSCEIndex	0.032	0.000	0.061
runBBKNN	0	0	0
runBarcodeRankDrops	0.280	0.012	0.409
runBcds	3.151	0.044	3.193
runCellQC	0.101	0.004	0.104
runClusterSummaryMetrics	0.504	0.004	0.509
runComBatSeq	0.641	0.012	0.729
runCxds	0.417	0.004	0.422
runCxdsBcdsHybrid	3.136	0.029	3.273
runDEAnalysis	0.604	0.020	1.131
runDecontX	7.089	0.028	7.600
runDimReduce	0.377	0.000	0.401
runDoubletFinder	33.799	0.195	42.581
runDropletQC	0.024	0.000	0.028
runEmptyDrops	5.259	0.000	7.610
runEnrichR	0.408	0.096	39.824
runFastMNN	2.366	0.172	2.986
runFeatureSelection	0.299	0.004	0.303
runFindMarker	1.984	0.167	2.244
runGSVA	1.270	0.092	1.519
runHarmony	0.053	0.004	0.057
runKMeans	0.246	0.000	0.246
runLimmaBC	0.116	0.004	0.148
runMNNCorrect	0.565	0.032	0.597
runModelGeneVar	0.407	0.032	0.467
runNormalization	2.609	0.271	3.098
runPerCellQC	0.444	0.032	0.535
runSCANORAMA	0	0	0
runSCMerge	0.004	0.000	0.004
runScDblFinder	21.375	0.624	27.831
runScanpyFindClusters	0.024	0.000	0.023
runScanpyFindHVG	0.023	0.000	0.024
runScanpyFindMarkers	0.019	0.004	0.024
runScanpyNormalizeData	0.122	0.000	0.122
runScanpyPCA	0.024	0.000	0.024
runScanpyScaleData	0.024	0.000	0.024
runScanpyTSNE	0.023	0.000	0.023
runScanpyUMAP	0.024	0.000	0.024
runScranSNN	0.377	0.000	0.406
runScrublet	0.023	0.000	0.023
runSeuratFindClusters	0.023	0.000	0.023
runSeuratFindHVG	0.601	0.004	0.639
runSeuratHeatmap	0.023	0.000	0.024
runSeuratICA	0.023	0.000	0.023
runSeuratJackStraw	0.023	0.000	0.023
runSeuratNormalizeData	0.023	0.000	0.023
runSeuratPCA	0.023	0.000	0.023
runSeuratSCTransform	43.871	0.609	51.016
runSeuratScaleData	0.025	0.000	0.025
runSeuratUMAP	0.020	0.004	0.024
runSingleR	0.052	0.000	0.052
runSoupX	0	0	0
runTSCAN	0.938	0.000	0.941
runTSCANClusterDEAnalysis	0.974	0.012	1.057
runTSCANDEG	1.004	0.008	1.071
runTSNE	1.012	0.000	1.180
runUMAP	6.775	0.084	9.992
runVAM	0.392	0.000	0.391
runZINBWaVE	0.005	0.000	0.005
sampleSummaryStats	0.198	0.000	0.199
scaterCPM	0.130	0.000	0.131
scaterPCA	0.603	0.012	0.665
scaterlogNormCounts	0.255	0.008	0.264
sce	0.023	0.000	0.023
sctkListGeneSetCollections	0.101	0.000	0.100
sctkPythonInstallConda	0.001	0.000	0.000
sctkPythonInstallVirtualEnv	0.000	0.000	0.001
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.108	0.000	0.133
setSCTKDisplayRow	0.554	0.004	0.560
singleCellTK	0.000	0.000	0.001
subDiffEx	0.376	0.016	0.393
subsetSCECols	0.098	0.012	0.133
subsetSCERows	0.349	0.020	0.370
summarizeSCE	0.08	0.00	0.08
trimCounts	0.194	0.004	0.197