Multiple platform build/check report for BioC 3.22 - CHECK results for singleCellTK on kjohnson3

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo2	Linux (Ubuntu 24.04.3 LTS)	x86_64	4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"	4902
kjohnson3	macOS 13.7.7 Ventura	arm64	4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"	4638
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 kjohnson3

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

raw results

Summary

Package: singleCellTK

Version: 2.20.0

Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.20.0.tar.gz

StartedAt: 2025-11-10 22:25:14 -0500 (Mon, 10 Nov 2025)

EndedAt: 2025-11-10 22:31:58 -0500 (Mon, 10 Nov 2025)

EllapsedTime: 403.6 seconds

RetCode: 0

Status: OK

CheckDir: singleCellTK.Rcheck

Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.20.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.1 Patched (2025-09-10 r88807)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 16.0.0 (clang-1600.0.26.6)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.7
* 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  6.8Mb
  sub-directories of 1Mb or more:
    R         1.0Mb
    extdata   1.5Mb
    shiny     2.9Mb
* 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 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 17.888  0.080  17.971
plotDoubletFinderResults 17.847  0.087  18.008
runDoubletFinder         15.697  0.054  15.803
plotScDblFinderResults   13.703  0.267  14.002
runScDblFinder            9.252  0.145   9.400
plotBatchCorrCompare      5.982  0.040   6.098
importExampleData         4.826  0.417   5.779
* 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
  ‘/Users/biocbuild/bbs-3.22-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.

Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/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 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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 
  0.070   0.021   0.085

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(testthat)
> library(singleCellTK)
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats

Attaching package: 'MatrixGenerics'

The following objects are masked from 'package:matrixStats':

    colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
    colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
    colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
    colWeightedMeans, colWeightedMedians, colWeightedSds,
    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
    rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
    rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
    rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
    rowWeightedSds, rowWeightedVars

Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: generics

Attaching package: 'generics'

The following objects are masked from 'package:base':

    as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
    setequal, union


Attaching package: 'BiocGenerics'

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
    mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
    rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
    unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:utils':

    findMatches

The following objects are masked from 'package:base':

    I, expand.grid, unname

Loading required package: IRanges
Loading required package: Seqinfo
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'Biobase'

The following object is masked from 'package:MatrixGenerics':

    rowMedians

The following objects are masked from 'package:matrixStats':

    anyMissing, rowMedians

Loading required package: SingleCellExperiment
Loading required package: DelayedArray
Loading required package: Matrix

Attaching package: 'Matrix'

The following object is masked from 'package:S4Vectors':

    expand

Loading required package: S4Arrays
Loading required package: abind

Attaching package: 'S4Arrays'

The following object is masked from 'package:abind':

    abind

The following object is masked from 'package:base':

    rowsum

Loading required package: SparseArray

Attaching package: 'DelayedArray'

The following objects are masked from 'package:base':

    apply, scale, sweep


Attaching package: 'singleCellTK'

The following object is masked from 'package:BiocGenerics':

    plotPCA

> 
> test_check("singleCellTK")
Found 2 batches
Using null model in ComBat-seq.
Adjusting for 0 covariate(s) or covariate level(s)
Estimating dispersions
Fitting the GLM model
Shrinkage off - using GLM estimates for parameters
Adjusting the data
Found 2 batches
Using null model in ComBat-seq.
Adjusting for 1 covariate(s) or covariate level(s)
Estimating dispersions
Fitting the GLM model
Shrinkage off - using GLM estimates for parameters
Adjusting the data
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Uploading data to Enrichr... Done.
  Querying HDSigDB_Human_2021... Done.
Parsing results... Done.
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

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

  |                                                                            
  |                                                                      |   0%
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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 
120.808   2.274 128.821

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.001	0.001	0.002
SEG	0.001	0.001	0.002
calcEffectSizes	0.071	0.003	0.074
combineSCE	0.225	0.004	0.230
computeZScore	0.093	0.003	0.100
convertSCEToSeurat	1.690	0.061	1.757
convertSeuratToSCE	0.118	0.002	0.121
dedupRowNames	0.021	0.001	0.023
detectCellOutlier	2.742	0.029	2.814
diffAbundanceFET	0.025	0.002	0.027
discreteColorPalette	0.002	0.000	0.003
distinctColors	0.000	0.000	0.001
downSampleCells	0.205	0.020	0.225
downSampleDepth	0.151	0.016	0.170
expData-ANY-character-method	0.042	0.002	0.043
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.056	0.001	0.056
expData-set	0.048	0.002	0.050
expData	0.042	0.001	0.043
expDataNames-ANY-method	0.039	0.002	0.041
expDataNames	0.040	0.003	0.043
expDeleteDataTag	0.017	0.001	0.018
expSetDataTag	0.013	0.001	0.013
expTaggedData	0.012	0.000	0.012
exportSCE	0.011	0.001	0.011
exportSCEtoAnnData	0.042	0.001	0.043
exportSCEtoFlatFile	0.041	0.001	0.042
featureIndex	0.016	0.002	0.018
generateSimulatedData	0.022	0.002	0.025
getBiomarker	0.025	0.002	0.028
getDEGTopTable	0.227	0.016	0.242
getDiffAbundanceResults	0.022	0.002	0.023
getEnrichRResult	0.132	0.018	3.390
getFindMarkerTopTable	0.456	0.013	0.474
getMSigDBTable	0.002	0.001	0.003
getPathwayResultNames	0.012	0.002	0.015
getSampleSummaryStatsTable	0.063	0.001	0.068
getSoupX	0	0	0
getTSCANResults	0.369	0.013	0.391
getTopHVG	0.286	0.005	0.300
importAnnData	0.001	0.000	0.001
importBUStools	0.045	0.001	0.047
importCellRanger	0.224	0.010	0.236
importCellRangerV2Sample	0.041	0.000	0.042
importCellRangerV3Sample	0.083	0.005	0.090
importDropEst	0.068	0.001	0.074
importExampleData	4.826	0.417	5.779
importGeneSetsFromCollection	0.768	0.029	0.797
importGeneSetsFromGMT	0.025	0.002	0.027
importGeneSetsFromList	0.042	0.002	0.044
importGeneSetsFromMSigDB	17.888	0.080	17.971
importMitoGeneSet	0.020	0.004	0.023
importOptimus	0.001	0.000	0.000
importSEQC	0.047	0.004	0.051
importSTARsolo	0.044	0.004	0.049
iterateSimulations	0.067	0.005	0.072
listSampleSummaryStatsTables	0.093	0.005	0.100
mergeSCEColData	0.135	0.009	0.144
mouseBrainSubsetSCE	0.018	0.002	0.020
msigdb_table	0.001	0.001	0.001
plotBarcodeRankDropsResults	0.283	0.009	0.291
plotBarcodeRankScatter	0.285	0.004	0.290
plotBatchCorrCompare	5.982	0.040	6.098
plotBatchVariance	0.174	0.004	0.187
plotBcdsResults	3.964	0.067	4.033
plotBubble	0.260	0.004	0.265
plotClusterAbundance	0.453	0.005	0.459
plotCxdsResults	3.203	0.040	3.278
plotDEGHeatmap	0.701	0.009	0.711
plotDEGRegression	2.170	0.021	2.193
plotDEGViolin	1.701	0.040	1.757
plotDEGVolcano	0.331	0.004	0.336
plotDecontXResults	3.784	0.028	3.819
plotDimRed	0.099	0.002	0.102
plotDoubletFinderResults	17.847	0.087	18.008
plotEmptyDropsResults	2.160	0.008	2.175
plotEmptyDropsScatter	2.110	0.003	2.114
plotFindMarkerHeatmap	1.226	0.009	1.236
plotMASTThresholdGenes	0.430	0.010	0.441
plotPCA	0.130	0.004	0.134
plotPathway	0.239	0.005	0.245
plotRunPerCellQCResults	0.984	0.006	1.007
plotSCEBarAssayData	0.126	0.005	0.131
plotSCEBarColData	0.079	0.003	0.081
plotSCEBatchFeatureMean	0.121	0.001	0.125
plotSCEDensity	0.103	0.002	0.105
plotSCEDensityAssayData	0.112	0.003	0.115
plotSCEDensityColData	0.100	0.003	0.102
plotSCEDimReduceColData	0.260	0.006	0.267
plotSCEDimReduceFeatures	0.123	0.005	0.129
plotSCEHeatmap	0.132	0.003	0.136
plotSCEScatter	0.121	0.003	0.125
plotSCEViolin	0.139	0.002	0.141
plotSCEViolinAssayData	0.123	0.003	0.126
plotSCEViolinColData	0.122	0.004	0.126
plotScDblFinderResults	13.703	0.267	14.002
plotScanpyDotPlot	0.011	0.002	0.014
plotScanpyEmbedding	0.010	0.001	0.012
plotScanpyHVG	0.010	0.001	0.012
plotScanpyHeatmap	0.011	0.001	0.012
plotScanpyMarkerGenes	0.011	0.001	0.012
plotScanpyMarkerGenesDotPlot	0.011	0.001	0.012
plotScanpyMarkerGenesHeatmap	0.012	0.001	0.013
plotScanpyMarkerGenesMatrixPlot	0.011	0.001	0.012
plotScanpyMarkerGenesViolin	0.011	0.001	0.012
plotScanpyMatrixPlot	0.011	0.001	0.012
plotScanpyPCA	0.010	0.001	0.012
plotScanpyPCAGeneRanking	0.011	0.002	0.012
plotScanpyPCAVariance	0.011	0.001	0.013
plotScanpyViolin	0.011	0.002	0.013
plotScdsHybridResults	4.361	0.081	4.442
plotScrubletResults	0.013	0.003	0.015
plotSeuratElbow	0.012	0.001	0.012
plotSeuratHVG	0.011	0.001	0.012
plotSeuratJackStraw	0.011	0.001	0.012
plotSeuratReduction	0.011	0.002	0.012
plotSoupXResults	0.000	0.000	0.001
plotTSCANClusterDEG	1.580	0.017	1.610
plotTSCANClusterPseudo	0.413	0.006	0.419
plotTSCANDimReduceFeatures	0.449	0.007	0.464
plotTSCANPseudotimeGenes	0.527	0.006	0.560
plotTSCANPseudotimeHeatmap	0.410	0.006	0.419
plotTSCANResults	0.387	0.006	0.393
plotTSNE	0.120	0.002	0.123
plotTopHVG	0.201	0.004	0.205
plotUMAP	3.402	0.018	3.464
readSingleCellMatrix	0.002	0.000	0.002
reportCellQC	0.029	0.001	0.030
reportDropletQC	0.011	0.001	0.012
reportQCTool	0.028	0.001	0.029
retrieveSCEIndex	0.013	0.001	0.014
runBBKNN	0	0	0
runBarcodeRankDrops	0.075	0.002	0.077
runBcds	0.591	0.014	0.605
runCellQC	0.030	0.001	0.031
runClusterSummaryMetrics	0.122	0.008	0.129
runComBatSeq	0.160	0.011	0.171
runCxds	0.117	0.009	0.125
runCxdsBcdsHybrid	0.626	0.024	0.656
runDEAnalysis	0.181	0.014	0.205
runDecontX	3.332	0.016	3.384
runDimReduce	0.094	0.003	0.098
runDoubletFinder	15.697	0.054	15.803
runDropletQC	0.011	0.001	0.013
runEmptyDrops	2.010	0.002	2.012
runEnrichR	0.114	0.014	2.055
runFastMNN	0.552	0.032	0.588
runFeatureSelection	0.077	0.001	0.078
runFindMarker	0.418	0.008	0.426
runGSVA	0.236	0.010	0.246
runHarmony	0.014	0.001	0.014
runKMeans	0.099	0.004	0.103
runLimmaBC	0.024	0.000	0.025
runMNNCorrect	0.132	0.001	0.134
runModelGeneVar	0.098	0.002	0.100
runNormalization	1.091	0.020	1.111
runPerCellQC	0.108	0.006	0.114
runSCANORAMA	0	0	0
runSCMerge	0.002	0.001	0.002
runScDblFinder	9.252	0.145	9.400
runScanpyFindClusters	0.013	0.001	0.015
runScanpyFindHVG	0.012	0.001	0.013
runScanpyFindMarkers	0.012	0.001	0.013
runScanpyNormalizeData	0.033	0.001	0.035
runScanpyPCA	0.011	0.002	0.014
runScanpyScaleData	0.012	0.002	0.013
runScanpyTSNE	0.012	0.001	0.013
runScanpyUMAP	0.011	0.002	0.012
runScranSNN	0.091	0.003	0.094
runScrublet	0.012	0.001	0.014
runSeuratFindClusters	0.012	0.001	0.013
runSeuratFindHVG	0.144	0.003	0.147
runSeuratHeatmap	0.011	0.001	0.012
runSeuratICA	0.011	0.001	0.012
runSeuratJackStraw	0.011	0.001	0.012
runSeuratNormalizeData	0.011	0.001	0.012
runSeuratPCA	0.011	0.001	0.012
runSeuratSCTransform	1.553	0.040	1.614
runSeuratScaleData	0.013	0.002	0.014
runSeuratUMAP	0.012	0.001	0.013
runSingleR	0.013	0.001	0.013
runSoupX	0	0	0
runTSCAN	0.211	0.005	0.220
runTSCANClusterDEAnalysis	0.238	0.005	0.243
runTSCANDEG	0.258	0.007	0.267
runTSNE	0.289	0.015	0.315
runUMAP	3.543	0.020	3.618
runVAM	0.097	0.002	0.100
runZINBWaVE	0.001	0.000	0.003
sampleSummaryStats	0.053	0.002	0.055
scaterCPM	0.059	0.004	0.063
scaterPCA	0.136	0.002	0.138
scaterlogNormCounts	0.087	0.004	0.092
sce	0.012	0.001	0.014
sctkListGeneSetCollections	0.029	0.002	0.031
sctkPythonInstallConda	0	0	0
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.033	0.002	0.036
setSCTKDisplayRow	0.148	0.006	0.154
singleCellTK	0	0	0
subDiffEx	0.123	0.013	0.137
subsetSCECols	0.035	0.006	0.039
subsetSCERows	0.098	0.007	0.106
summarizeSCE	0.028	0.004	0.032
trimCounts	0.084	0.008	0.092