Multiple platform build/check report for BioC 3.21 - CHECK results for singleCellTK on kunpeng2

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo1	Linux (Ubuntu 24.04.3 LTS)	x86_64	4.5.1 (2025-06-13) -- "Great Square Root"	4832
merida1	macOS 12.7.5 Monterey	x86_64	4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"	4613
kjohnson1	macOS 13.6.6 Ventura	arm64	4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"	4554
kunpeng2	Linux (openEuler 24.03 LTS)	aarch64	R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"	4585
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 kunpeng2

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: 2.18.2

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_2.18.2.tar.gz

StartedAt: 2025-10-03 14:28:35 -0000 (Fri, 03 Oct 2025)

EndedAt: 2025-10-03 14:50:59 -0000 (Fri, 03 Oct 2025)

EllapsedTime: 1343.6 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_2.18.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/singleCellTK.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* 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-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.18.2’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 79 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
  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
runSeuratSCTransform     45.653  0.323  50.463
plotDoubletFinderResults 42.752  0.163  47.300
plotScDblFinderResults   42.467  0.284  48.901
runDoubletFinder         37.484  0.465  41.874
runScDblFinder           30.623  0.615  34.752
importExampleData        15.995  1.009  24.994
plotBatchCorrCompare     13.979  0.200  17.092
plotScdsHybridResults    12.386  0.097  13.173
plotBcdsResults          10.859  0.179  13.739
plotDecontXResults        9.168  0.077   9.561
runDecontX                7.820  0.240   8.576
plotCxdsResults           7.890  0.051   9.268
runUMAP                   7.786  0.012   8.308
plotUMAP                  7.484  0.264   9.883
plotFindMarkerHeatmap     7.361  0.082   8.374
detectCellOutlier         6.655  0.206   7.274
plotDEGViolin             6.044  0.042   6.530
convertSCEToSeurat        5.573  0.295   6.277
plotEmptyDropsResults     5.565  0.035   6.178
plotEmptyDropsScatter     5.491  0.007   6.210
plotTSCANClusterDEG       5.193  0.127   5.813
runEmptyDrops             5.195  0.004   5.692
plotDEGRegression         4.913  0.020   5.172
getEnrichRResult          0.423  0.039   9.358
runEnrichR                0.375  0.031  10.415
* 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-3.21-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-devel_2025-02-19/site-library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.18.2’
** 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) (2025-02-19 r87757) -- "Unsuffered Consequences"
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)
NULL
> 
> proc.time()
   user  system elapsed 
  0.246   0.016   0.499

singleCellTK.Rcheck/tests/testthat.Rout


R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
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: GenomeInfoDb
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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Calculating gene variances
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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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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 
329.662   6.746 391.652

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.000	0.003	0.003
SEG	0.003	0.000	0.003
calcEffectSizes	0.295	0.024	0.319
combineSCE	1.124	0.012	1.141
computeZScore	0.298	0.031	0.657
convertSCEToSeurat	5.573	0.295	6.277
convertSeuratToSCE	0.489	0.004	0.500
dedupRowNames	0.081	0.000	0.081
detectCellOutlier	6.655	0.206	7.274
diffAbundanceFET	0.070	0.008	0.078
discreteColorPalette	0.005	0.003	0.008
distinctColors	0.003	0.000	0.003
downSampleCells	0.748	0.072	0.930
downSampleDepth	0.633	0.000	0.808
expData-ANY-character-method	0.185	0.004	0.313
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.221	0.004	0.226
expData-set	0.206	0.032	0.238
expData	0.179	0.004	0.183
expDataNames-ANY-method	0.161	0.012	0.174
expDataNames	0.175	0.000	0.177
expDeleteDataTag	0.037	0.008	0.045
expSetDataTag	0.030	0.003	0.033
expTaggedData	0.034	0.000	0.035
exportSCE	0.03	0.00	0.03
exportSCEtoAnnData	0.075	0.004	0.080
exportSCEtoFlatFile	0.079	0.000	0.080
featureIndex	0.051	0.000	0.052
generateSimulatedData	0.072	0.000	0.076
getBiomarker	0.077	0.000	0.078
getDEGTopTable	0.949	0.083	1.043
getDiffAbundanceResults	0.062	0.000	0.062
getEnrichRResult	0.423	0.039	9.358
getFindMarkerTopTable	2.101	0.223	2.698
getMSigDBTable	0.004	0.000	0.005
getPathwayResultNames	0.029	0.000	0.029
getSampleSummaryStatsTable	0.254	0.016	0.270
getSoupX	0.000	0.000	0.001
getTSCANResults	1.441	0.060	1.513
getTopHVG	1.193	0.028	1.251
importAnnData	0.001	0.000	0.001
importBUStools	0.230	0.004	0.468
importCellRanger	1.114	0.040	1.438
importCellRangerV2Sample	0.201	0.040	0.242
importCellRangerV3Sample	0.416	0.035	0.478
importDropEst	0.368	0.016	0.728
importExampleData	15.995	1.009	24.994
importGeneSetsFromCollection	2.360	0.088	2.636
importGeneSetsFromGMT	0.088	0.000	0.143
importGeneSetsFromList	0.175	0.000	0.175
importGeneSetsFromMSigDB	1.451	0.108	1.770
importMitoGeneSet	0.059	0.012	0.071
importOptimus	0.002	0.000	0.002
importSEQC	0.195	0.028	0.409
importSTARsolo	0.268	0.036	0.380
iterateSimulations	0.246	0.008	0.254
listSampleSummaryStatsTables	0.347	0.000	0.348
mergeSCEColData	0.498	0.004	0.539
mouseBrainSubsetSCE	0.045	0.000	0.045
msigdb_table	0.002	0.000	0.001
plotBarcodeRankDropsResults	0.876	0.016	1.078
plotBarcodeRankScatter	1.038	0.032	1.360
plotBatchCorrCompare	13.979	0.200	17.092
plotBatchVariance	0.461	0.008	0.470
plotBcdsResults	10.859	0.179	13.739
plotBubble	1.047	0.028	1.612
plotClusterAbundance	1.270	0.004	1.321
plotCxdsResults	7.890	0.051	9.268
plotDEGHeatmap	3.098	0.000	3.172
plotDEGRegression	4.913	0.020	5.172
plotDEGViolin	6.044	0.042	6.530
plotDEGVolcano	1.133	0.004	1.139
plotDecontXResults	9.168	0.077	9.561
plotDimRed	0.278	0.000	0.366
plotDoubletFinderResults	42.752	0.163	47.300
plotEmptyDropsResults	5.565	0.035	6.178
plotEmptyDropsScatter	5.491	0.007	6.210
plotFindMarkerHeatmap	7.361	0.082	8.374
plotMASTThresholdGenes	1.846	0.016	2.005
plotPCA	0.411	0.008	0.421
plotPathway	0.729	0.008	0.878
plotRunPerCellQCResults	2.798	0.016	3.285
plotSCEBarAssayData	0.276	0.000	0.277
plotSCEBarColData	0.256	0.003	0.440
plotSCEBatchFeatureMean	0.321	0.004	0.324
plotSCEDensity	0.305	0.003	0.311
plotSCEDensityAssayData	0.244	0.001	0.244
plotSCEDensityColData	0.318	0.000	0.430
plotSCEDimReduceColData	0.742	0.007	0.751
plotSCEDimReduceFeatures	0.413	0.000	0.413
plotSCEHeatmap	0.629	0.000	0.690
plotSCEScatter	0.358	0.000	0.358
plotSCEViolin	0.347	0.000	0.348
plotSCEViolinAssayData	0.392	0.000	0.622
plotSCEViolinColData	0.367	0.012	0.391
plotScDblFinderResults	42.467	0.284	48.901
plotScanpyDotPlot	0.025	0.003	0.028
plotScanpyEmbedding	0.029	0.000	0.028
plotScanpyHVG	0.028	0.000	0.028
plotScanpyHeatmap	0.028	0.000	0.028
plotScanpyMarkerGenes	0.030	0.000	0.029
plotScanpyMarkerGenesDotPlot	0.029	0.000	0.029
plotScanpyMarkerGenesHeatmap	0.029	0.000	0.029
plotScanpyMarkerGenesMatrixPlot	0.029	0.000	0.029
plotScanpyMarkerGenesViolin	0.029	0.000	0.029
plotScanpyMatrixPlot	0.029	0.000	0.029
plotScanpyPCA	0.03	0.00	0.03
plotScanpyPCAGeneRanking	0.029	0.000	0.029
plotScanpyPCAVariance	0.028	0.000	0.028
plotScanpyViolin	0.030	0.000	0.035
plotScdsHybridResults	12.386	0.097	13.173
plotScrubletResults	0.027	0.000	0.027
plotSeuratElbow	0.027	0.000	0.027
plotSeuratHVG	0.026	0.000	0.025
plotSeuratJackStraw	0.026	0.000	0.027
plotSeuratReduction	0.026	0.000	0.026
plotSoupXResults	0	0	0
plotTSCANClusterDEG	5.193	0.127	5.813
plotTSCANClusterPseudo	1.686	0.020	1.846
plotTSCANDimReduceFeatures	1.694	0.004	1.754
plotTSCANPseudotimeGenes	1.988	0.004	2.122
plotTSCANPseudotimeHeatmap	1.898	0.000	1.997
plotTSCANResults	1.618	0.023	2.045
plotTSNE	0.465	0.012	0.925
plotTopHVG	0.716	0.008	0.727
plotUMAP	7.484	0.264	9.883
readSingleCellMatrix	0.007	0.000	0.006
reportCellQC	0.112	0.004	0.117
reportDropletQC	0.034	0.008	0.041
reportQCTool	0.119	0.004	0.123
retrieveSCEIndex	0.044	0.000	0.044
runBBKNN	0	0	0
runBarcodeRankDrops	0.295	0.012	0.388
runBcds	3.929	0.080	4.035
runCellQC	0.111	0.012	0.122
runClusterSummaryMetrics	0.543	0.020	0.563
runComBatSeq	0.689	0.036	1.001
runCxds	0.483	0.020	0.503
runCxdsBcdsHybrid	4.096	0.104	4.385
runDEAnalysis	0.544	0.072	0.619
runDecontX	7.820	0.240	8.576
runDimReduce	0.391	0.008	0.401
runDoubletFinder	37.484	0.465	41.874
runDropletQC	0.025	0.004	0.057
runEmptyDrops	5.195	0.004	5.692
runEnrichR	0.375	0.031	10.415
runFastMNN	2.399	0.200	3.241
runFeatureSelection	0.319	0.016	0.495
runFindMarker	2.014	0.140	2.215
runGSVA	1.223	0.092	1.370
runHarmony	0.052	0.004	0.057
runKMeans	0.250	0.004	0.254
runLimmaBC	0.102	0.028	0.131
runMNNCorrect	0.581	0.060	0.815
runModelGeneVar	0.432	0.032	0.464
runNormalization	2.746	0.228	3.128
runPerCellQC	0.482	0.000	0.483
runSCANORAMA	0	0	0
runSCMerge	0.004	0.000	0.004
runScDblFinder	30.623	0.615	34.752
runScanpyFindClusters	0.032	0.000	0.032
runScanpyFindHVG	0.034	0.000	0.035
runScanpyFindMarkers	0.031	0.000	0.030
runScanpyNormalizeData	0.134	0.004	0.138
runScanpyPCA	0.031	0.000	0.032
runScanpyScaleData	0.031	0.000	0.031
runScanpyTSNE	0.031	0.000	0.031
runScanpyUMAP	0.030	0.000	0.031
runScranSNN	0.399	0.008	0.408
runScrublet	0.031	0.000	0.031
runSeuratFindClusters	0.032	0.000	0.032
runSeuratFindHVG	0.699	0.007	1.194
runSeuratHeatmap	0.035	0.000	0.063
runSeuratICA	0.037	0.000	0.078
runSeuratJackStraw	0.033	0.004	0.078
runSeuratNormalizeData	0.035	0.000	0.067
runSeuratPCA	0.033	0.000	0.070
runSeuratSCTransform	45.653	0.323	50.463
runSeuratScaleData	0.026	0.000	0.026
runSeuratUMAP	0.028	0.000	0.028
runSingleR	0.046	0.004	0.050
runSoupX	0	0	0
runTSCAN	0.971	0.000	1.010
runTSCANClusterDEAnalysis	1.035	0.024	1.061
runTSCANDEG	0.986	0.004	1.002
runTSNE	1.050	0.012	1.076
runUMAP	7.786	0.012	8.308
runVAM	0.436	0.008	0.445
runZINBWaVE	0.004	0.000	0.004
sampleSummaryStats	0.220	0.000	0.221
scaterCPM	0.139	0.000	0.139
scaterPCA	0.659	0.000	0.823
scaterlogNormCounts	0.302	0.010	0.314
sce	0.032	0.004	0.036
sctkListGeneSetCollections	0.122	0.001	0.205
sctkPythonInstallConda	0.000	0.000	0.001
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0.001	0.000	0.000
setRowNames	0.124	0.003	0.260
setSCTKDisplayRow	0.418	0.009	0.487
singleCellTK	0	0	0
subDiffEx	0.433	0.004	0.438
subsetSCECols	0.103	0.000	0.112
subsetSCERows	0.328	0.008	0.380
summarizeSCE	0.084	0.000	0.084
trimCounts	0.243	0.004	0.247