Multiple platform build/check report for BioC 3.21 - CHECK results for singleCellTK on kjohnson3

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo1	Linux (Ubuntu 24.04.1 LTS)	x86_64	4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"	4831
palomino7	Windows Server 2022 Datacenter	x64	4.5.0 RC (2025-04-04 r88126 ucrt) -- "How About a Twenty-Six"	4573
lconway	macOS 12.7.1 Monterey	x86_64	4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"	4599
kjohnson3	macOS 13.7.1 Ventura	arm64	4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"	4553
kunpeng2	Linux (openEuler 24.03 LTS)	aarch64	R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"	4570
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: 2.18.0

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_2.18.0.tar.gz

StartedAt: 2025-04-21 21:43:21 -0400 (Mon, 21 Apr 2025)

EndedAt: 2025-04-21 21:49:19 -0400 (Mon, 21 Apr 2025)

EllapsedTime: 358.2 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_2.18.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.0 RC (2025-04-04 r88126)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.18.0’
* 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  6.8Mb
  sub-directories of 1Mb or more:
    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
  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
plotDoubletFinderResults 15.906  0.081  16.067
runDoubletFinder         14.975  0.067  15.194
plotScDblFinderResults   14.751  0.240  15.070
runScDblFinder            9.992  0.180  10.239
importExampleData         5.142  0.441   6.062
plotBatchCorrCompare      4.978  0.045   5.100
* 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-3.21-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 ‘2.18.0’
** 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 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
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)
NULL
> 
> proc.time()
   user  system elapsed 
  0.071   0.021   0.088

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
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: 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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

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

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

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

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 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 
100.513   2.509 105.726

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.001	0.002	0.003
SEG	0.001	0.001	0.002
calcEffectSizes	0.075	0.005	0.079
combineSCE	0.238	0.005	0.243
computeZScore	0.093	0.002	0.095
convertSCEToSeurat	1.506	0.063	1.573
convertSeuratToSCE	0.124	0.003	0.127
dedupRowNames	0.022	0.001	0.022
detectCellOutlier	2.301	0.037	2.354
diffAbundanceFET	0.024	0.001	0.026
discreteColorPalette	0.002	0.000	0.002
distinctColors	0.000	0.000	0.001
downSampleCells	0.207	0.019	0.231
downSampleDepth	0.150	0.011	0.162
expData-ANY-character-method	0.041	0.002	0.044
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.054	0.002	0.055
expData-set	0.046	0.001	0.047
expData	0.042	0.002	0.043
expDataNames-ANY-method	0.038	0.002	0.040
expDataNames	0.040	0.002	0.042
expDeleteDataTag	0.018	0.001	0.019
expSetDataTag	0.013	0.001	0.014
expTaggedData	0.012	0.001	0.013
exportSCE	0.011	0.002	0.013
exportSCEtoAnnData	0.042	0.002	0.043
exportSCEtoFlatFile	0.041	0.001	0.042
featureIndex	0.017	0.003	0.018
generateSimulatedData	0.023	0.002	0.025
getBiomarker	0.025	0.002	0.027
getDEGTopTable	0.232	0.017	0.249
getDiffAbundanceResults	0.021	0.002	0.022
getEnrichRResult	0.113	0.020	3.032
getFindMarkerTopTable	0.448	0.011	0.459
getMSigDBTable	0.002	0.001	0.003
getPathwayResultNames	0.012	0.002	0.015
getSampleSummaryStatsTable	0.075	0.002	0.078
getSoupX	0	0	0
getTSCANResults	0.343	0.013	0.358
getTopHVG	0.284	0.005	0.306
importAnnData	0.001	0.000	0.001
importBUStools	0.044	0.001	0.047
importCellRanger	0.251	0.010	0.263
importCellRangerV2Sample	0.043	0.001	0.044
importCellRangerV3Sample	0.101	0.004	0.106
importDropEst	0.064	0.001	0.065
importExampleData	5.142	0.441	6.062
importGeneSetsFromCollection	0.253	0.033	0.288
importGeneSetsFromGMT	0.026	0.003	0.029
importGeneSetsFromList	0.040	0.004	0.044
importGeneSetsFromMSigDB	0.310	0.018	0.329
importMitoGeneSet	0.019	0.003	0.023
importOptimus	0.001	0.000	0.001
importSEQC	0.044	0.000	0.045
importSTARsolo	0.041	0.001	0.043
iterateSimulations	0.062	0.004	0.067
listSampleSummaryStatsTables	0.086	0.003	0.089
mergeSCEColData	0.110	0.011	0.124
mouseBrainSubsetSCE	0.019	0.002	0.022
msigdb_table	0.001	0.002	0.002
plotBarcodeRankDropsResults	0.233	0.008	0.241
plotBarcodeRankScatter	0.194	0.003	0.197
plotBatchCorrCompare	4.978	0.045	5.100
plotBatchVariance	0.112	0.008	0.121
plotBcdsResults	3.408	0.073	3.508
plotBubble	0.249	0.018	0.267
plotClusterAbundance	0.261	0.002	0.263
plotCxdsResults	2.689	0.029	2.745
plotDEGHeatmap	0.723	0.025	0.748
plotDEGRegression	1.171	0.038	1.019
plotDEGViolin	1.397	0.065	1.290
plotDEGVolcano	0.295	0.005	0.299
plotDecontXResults	3.206	0.025	3.234
plotDimRed	0.069	0.002	0.070
plotDoubletFinderResults	15.906	0.081	16.067
plotEmptyDropsResults	2.115	0.007	2.123
plotEmptyDropsScatter	2.072	0.005	2.078
plotFindMarkerHeatmap	1.226	0.009	1.251
plotMASTThresholdGenes	0.405	0.010	0.419
plotPCA	0.100	0.003	0.104
plotPathway	0.164	0.003	0.169
plotRunPerCellQCResults	0.624	0.008	0.637
plotSCEBarAssayData	0.074	0.004	0.078
plotSCEBarColData	0.050	0.003	0.056
plotSCEBatchFeatureMean	0.067	0.001	0.069
plotSCEDensity	0.078	0.004	0.084
plotSCEDensityAssayData	0.060	0.003	0.063
plotSCEDensityColData	0.072	0.003	0.075
plotSCEDimReduceColData	0.177	0.005	0.183
plotSCEDimReduceFeatures	0.088	0.004	0.092
plotSCEHeatmap	0.127	0.003	0.130
plotSCEScatter	0.088	0.004	0.092
plotSCEViolin	0.088	0.003	0.090
plotSCEViolinAssayData	0.099	0.003	0.102
plotSCEViolinColData	0.083	0.004	0.086
plotScDblFinderResults	14.751	0.240	15.070
plotScanpyDotPlot	0.013	0.002	0.014
plotScanpyEmbedding	0.012	0.001	0.012
plotScanpyHVG	0.012	0.001	0.013
plotScanpyHeatmap	0.012	0.002	0.013
plotScanpyMarkerGenes	0.012	0.001	0.013
plotScanpyMarkerGenesDotPlot	0.012	0.002	0.013
plotScanpyMarkerGenesHeatmap	0.011	0.001	0.012
plotScanpyMarkerGenesMatrixPlot	0.011	0.001	0.012
plotScanpyMarkerGenesViolin	0.011	0.001	0.012
plotScanpyMatrixPlot	0.011	0.002	0.012
plotScanpyPCA	0.011	0.001	0.012
plotScanpyPCAGeneRanking	0.012	0.001	0.012
plotScanpyPCAVariance	0.011	0.001	0.012
plotScanpyViolin	0.012	0.001	0.012
plotScdsHybridResults	3.615	0.051	3.735
plotScrubletResults	0.012	0.001	0.014
plotSeuratElbow	0.011	0.000	0.012
plotSeuratHVG	0.011	0.001	0.011
plotSeuratJackStraw	0.011	0.001	0.011
plotSeuratReduction	0.011	0.001	0.012
plotSoupXResults	0	0	0
plotTSCANClusterDEG	1.132	0.027	1.162
plotTSCANClusterPseudo	0.367	0.008	0.377
plotTSCANDimReduceFeatures	0.368	0.008	0.378
plotTSCANPseudotimeGenes	0.404	0.006	0.411
plotTSCANPseudotimeHeatmap	0.418	0.008	0.439
plotTSCANResults	0.357	0.007	0.366
plotTSNE	0.108	0.003	0.112
plotTopHVG	0.174	0.006	0.179
plotUMAP	3.124	0.022	3.237
readSingleCellMatrix	0.002	0.000	0.002
reportCellQC	0.029	0.002	0.030
reportDropletQC	0.012	0.001	0.013
reportQCTool	0.028	0.001	0.030
retrieveSCEIndex	0.014	0.001	0.015
runBBKNN	0	0	0
runBarcodeRankDrops	0.075	0.002	0.077
runBcds	0.601	0.032	0.645
runCellQC	0.030	0.002	0.032
runClusterSummaryMetrics	0.117	0.007	0.125
runComBatSeq	0.167	0.009	0.180
runCxds	0.118	0.010	0.128
runCxdsBcdsHybrid	0.666	0.030	0.696
runDEAnalysis	0.134	0.004	0.139
runDecontX	2.981	0.022	3.030
runDimReduce	0.097	0.005	0.110
runDoubletFinder	14.975	0.067	15.194
runDropletQC	0.013	0.002	0.013
runEmptyDrops	2.013	0.002	2.016
runEnrichR	0.113	0.024	2.314
runFastMNN	0.610	0.030	0.645
runFeatureSelection	0.080	0.006	0.088
runFindMarker	0.425	0.011	0.436
runGSVA	0.265	0.014	0.281
runHarmony	0.012	0.001	0.013
runKMeans	0.062	0.004	0.067
runLimmaBC	0.023	0.001	0.027
runMNNCorrect	0.130	0.003	0.135
runModelGeneVar	0.103	0.003	0.110
runNormalization	1.075	0.065	1.184
runPerCellQC	0.107	0.003	0.110
runSCANORAMA	0	0	0
runSCMerge	0.002	0.000	0.002
runScDblFinder	9.992	0.180	10.239
runScanpyFindClusters	0.013	0.002	0.015
runScanpyFindHVG	0.012	0.002	0.013
runScanpyFindMarkers	0.012	0.001	0.013
runScanpyNormalizeData	0.036	0.002	0.038
runScanpyPCA	0.012	0.001	0.013
runScanpyScaleData	0.012	0.002	0.012
runScanpyTSNE	0.013	0.003	0.015
runScanpyUMAP	0.013	0.002	0.015
runScranSNN	0.095	0.004	0.099
runScrublet	0.012	0.001	0.013
runSeuratFindClusters	0.011	0.001	0.013
runSeuratFindHVG	0.153	0.006	0.158
runSeuratHeatmap	0.012	0.003	0.014
runSeuratICA	0.012	0.002	0.013
runSeuratJackStraw	0.013	0.003	0.017
runSeuratNormalizeData	0.013	0.001	0.013
runSeuratPCA	0.011	0.001	0.012
runSeuratSCTransform	2.238	0.061	2.305
runSeuratScaleData	0.012	0.001	0.013
runSeuratUMAP	0.012	0.001	0.012
runSingleR	0.012	0.001	0.013
runSoupX	0	0	0
runTSCAN	0.207	0.005	0.224
runTSCANClusterDEAnalysis	0.240	0.013	0.259
runTSCANDEG	0.227	0.012	0.239
runTSNE	0.283	0.010	0.294
runUMAP	3.071	0.021	3.135
runVAM	0.093	0.002	0.096
runZINBWaVE	0.001	0.001	0.002
sampleSummaryStats	0.053	0.001	0.054
scaterCPM	0.055	0.002	0.058
scaterPCA	0.139	0.004	0.142
scaterlogNormCounts	0.090	0.004	0.094
sce	0.013	0.004	0.016
sctkListGeneSetCollections	0.028	0.003	0.031
sctkPythonInstallConda	0.000	0.000	0.001
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0.000	0.000	0.001
setRowNames	0.031	0.001	0.032
setSCTKDisplayRow	0.115	0.005	0.121
singleCellTK	0	0	0
subDiffEx	0.124	0.012	0.139
subsetSCECols	0.029	0.003	0.032
subsetSCERows	0.088	0.007	0.097
summarizeSCE	0.027	0.001	0.029
trimCounts	0.078	0.003	0.082