Multiple platform build/check report for BioC 3.22 - CHECK results for singleCellTK on kjohnson1

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo2	Linux (Ubuntu 24.04.3 LTS)	x86_64	4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"	4615
merida1	macOS 12.7.6 Monterey	x86_64	4.5.2 Patched (2025-11-05 r88990) -- "[Not] Part in a Rumble"	4610
kjohnson1	macOS 13.7.5 Ventura	arm64	4.5.2 Patched (2025-11-04 r88984) -- "[Not] Part in a Rumble"	4598
taishan	Linux (openEuler 24.03 LTS)	aarch64	4.5.0 (2025-04-11) -- "How About a Twenty-Six"	4668
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 kjohnson1

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: 2025-11-18 13:09:41 -0500 (Tue, 18 Nov 2025)

EndedAt: 2025-11-18 13:18:20 -0500 (Tue, 18 Nov 2025)

EllapsedTime: 519.2 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_2.20.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.2 Patched (2025-11-04 r88984)
* 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 13.7.8
* 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 22.428  0.156  25.557
plotDoubletFinderResults 18.684  0.080  22.356
runDoubletFinder         16.394  0.062  17.689
plotScDblFinderResults   15.119  0.245  17.312
runScDblFinder           10.811  0.172  12.401
importExampleData         7.189  0.592  11.323
plotBatchCorrCompare      6.561  0.052   7.939
plotScdsHybridResults     4.618  0.075   5.035
plotBcdsResults           4.165  0.060   5.006
* 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 4.5.2 Patched (2025-11-04 r88984) -- "[Not] Part in a Rumble"
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 
  0.095   0.031   0.145

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.2 Patched (2025-11-04 r88984) -- "[Not] Part in a Rumble"
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...
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[----|----|----|----|----|----|----|----|----|----|
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Maximum modularity in 10 random starts: 0.8351
Number of communities: 7
Elapsed time: 0 seconds
Using method 'umap'
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**************************************************|

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

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Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
139.765   2.582 169.722

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.001	0.002	0.004
SEG	0.002	0.001	0.003
calcEffectSizes	0.077	0.003	0.090
combineSCE	0.273	0.004	0.298
computeZScore	0.106	0.003	0.115
convertSCEToSeurat	1.817	0.069	2.122
convertSeuratToSCE	0.148	0.004	0.195
dedupRowNames	0.025	0.001	0.031
detectCellOutlier	2.864	0.034	3.146
diffAbundanceFET	0.038	0.002	0.039
discreteColorPalette	0.002	0.000	0.003
distinctColors	0.001	0.000	0.001
downSampleCells	0.238	0.019	0.316
downSampleDepth	0.172	0.012	0.195
expData-ANY-character-method	0.053	0.002	0.068
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.065	0.002	0.068
expData-set	0.062	0.002	0.069
expData	0.051	0.002	0.063
expDataNames-ANY-method	0.048	0.002	0.054
expDataNames	0.048	0.005	0.052
expDeleteDataTag	0.017	0.001	0.019
expSetDataTag	0.013	0.001	0.015
expTaggedData	0.013	0.000	0.015
exportSCE	0.012	0.001	0.022
exportSCEtoAnnData	0.053	0.002	0.060
exportSCEtoFlatFile	0.046	0.003	0.048
featureIndex	0.019	0.002	0.022
generateSimulatedData	0.027	0.003	0.030
getBiomarker	0.029	0.003	0.032
getDEGTopTable	0.278	0.017	0.333
getDiffAbundanceResults	0.025	0.000	0.026
getEnrichRResult	0.157	0.018	4.466
getFindMarkerTopTable	0.621	0.017	0.737
getMSigDBTable	0.002	0.002	0.003
getPathwayResultNames	0.014	0.003	0.016
getSampleSummaryStatsTable	0.070	0.002	0.079
getSoupX	0	0	0
getTSCANResults	0.469	0.017	0.590
getTopHVG	0.360	0.006	0.471
importAnnData	0.001	0.001	0.001
importBUStools	0.054	0.001	0.080
importCellRanger	0.285	0.013	0.436
importCellRangerV2Sample	0.052	0.001	0.110
importCellRangerV3Sample	0.102	0.006	0.148
importDropEst	0.073	0.001	0.089
importExampleData	7.189	0.592	11.323
importGeneSetsFromCollection	0.810	0.029	0.917
importGeneSetsFromGMT	0.031	0.002	0.033
importGeneSetsFromList	0.054	0.002	0.060
importGeneSetsFromMSigDB	22.428	0.156	25.557
importMitoGeneSet	0.027	0.004	0.036
importOptimus	0.000	0.000	0.001
importSEQC	0.059	0.004	0.072
importSTARsolo	0.057	0.003	0.084
iterateSimulations	0.081	0.006	0.090
listSampleSummaryStatsTables	0.110	0.007	0.118
mergeSCEColData	0.161	0.010	0.180
mouseBrainSubsetSCE	0.020	0.003	0.023
msigdb_table	0.001	0.001	0.002
plotBarcodeRankDropsResults	0.344	0.011	0.394
plotBarcodeRankScatter	0.327	0.005	0.355
plotBatchCorrCompare	6.561	0.052	7.939
plotBatchVariance	0.198	0.004	0.319
plotBcdsResults	4.165	0.060	5.006
plotBubble	0.313	0.006	0.420
plotClusterAbundance	0.515	0.003	0.578
plotCxdsResults	3.627	0.027	4.240
plotDEGHeatmap	0.835	0.010	0.876
plotDEGRegression	2.373	0.018	2.661
plotDEGViolin	2.044	0.029	2.347
plotDEGVolcano	0.402	0.006	0.480
plotDecontXResults	4.022	0.027	4.622
plotDimRed	0.114	0.003	0.136
plotDoubletFinderResults	18.684	0.080	22.356
plotEmptyDropsResults	2.816	0.014	3.407
plotEmptyDropsScatter	2.700	0.013	3.107
plotFindMarkerHeatmap	1.463	0.008	1.717
plotMASTThresholdGenes	0.484	0.011	0.594
plotPCA	0.150	0.004	0.163
plotPathway	0.278	0.003	0.294
plotRunPerCellQCResults	1.151	0.005	1.232
plotSCEBarAssayData	0.140	0.002	0.162
plotSCEBarColData	0.097	0.003	0.120
plotSCEBatchFeatureMean	0.151	0.002	0.218
plotSCEDensity	0.124	0.003	0.128
plotSCEDensityAssayData	0.135	0.003	0.170
plotSCEDensityColData	0.123	0.003	0.148
plotSCEDimReduceColData	0.312	0.006	0.373
plotSCEDimReduceFeatures	0.154	0.003	0.207
plotSCEHeatmap	0.162	0.002	0.191
plotSCEScatter	0.138	0.003	0.149
plotSCEViolin	0.161	0.004	0.175
plotSCEViolinAssayData	0.146	0.003	0.156
plotSCEViolinColData	0.138	0.004	0.191
plotScDblFinderResults	15.119	0.245	17.312
plotScanpyDotPlot	0.012	0.002	0.013
plotScanpyEmbedding	0.013	0.001	0.014
plotScanpyHVG	0.013	0.001	0.014
plotScanpyHeatmap	0.013	0.002	0.014
plotScanpyMarkerGenes	0.013	0.001	0.015
plotScanpyMarkerGenesDotPlot	0.013	0.001	0.014
plotScanpyMarkerGenesHeatmap	0.013	0.001	0.014
plotScanpyMarkerGenesMatrixPlot	0.013	0.001	0.013
plotScanpyMarkerGenesViolin	0.013	0.001	0.015
plotScanpyMatrixPlot	0.014	0.000	0.016
plotScanpyPCA	0.013	0.001	0.016
plotScanpyPCAGeneRanking	0.013	0.000	0.014
plotScanpyPCAVariance	0.013	0.001	0.020
plotScanpyViolin	0.014	0.001	0.018
plotScdsHybridResults	4.618	0.075	5.035
plotScrubletResults	0.013	0.001	0.015
plotSeuratElbow	0.013	0.001	0.015
plotSeuratHVG	0.013	0.002	0.014
plotSeuratJackStraw	0.013	0.001	0.013
plotSeuratReduction	0.013	0.001	0.015
plotSoupXResults	0	0	0
plotTSCANClusterDEG	1.952	0.035	2.394
plotTSCANClusterPseudo	0.520	0.010	0.637
plotTSCANDimReduceFeatures	0.550	0.008	0.767
plotTSCANPseudotimeGenes	0.693	0.010	1.021
plotTSCANPseudotimeHeatmap	0.511	0.009	0.632
plotTSCANResults	0.549	0.009	0.680
plotTSNE	0.160	0.004	0.312
plotTopHVG	0.258	0.006	0.332
plotUMAP	3.546	0.035	4.309
readSingleCellMatrix	0.002	0.001	0.002
reportCellQC	0.033	0.001	0.035
reportDropletQC	0.012	0.001	0.013
reportQCTool	0.033	0.001	0.039
retrieveSCEIndex	0.015	0.001	0.018
runBBKNN	0	0	0
runBarcodeRankDrops	0.094	0.002	0.100
runBcds	0.684	0.033	0.803
runCellQC	0.036	0.002	0.037
runClusterSummaryMetrics	0.160	0.004	0.207
runComBatSeq	0.179	0.006	0.227
runCxds	0.141	0.006	0.178
runCxdsBcdsHybrid	0.695	0.037	0.840
runDEAnalysis	0.205	0.017	0.241
runDecontX	3.459	0.016	3.693
runDimReduce	0.119	0.003	0.128
runDoubletFinder	16.394	0.062	17.689
runDropletQC	0.014	0.002	0.015
runEmptyDrops	2.476	0.007	2.588
runEnrichR	0.149	0.016	4.048
runFastMNN	0.664	0.022	0.708
runFeatureSelection	0.095	0.003	0.113
runFindMarker	0.562	0.012	0.667
runGSVA	0.281	0.011	0.330
runHarmony	0.016	0.001	0.017
runKMeans	0.118	0.006	0.131
runLimmaBC	0.034	0.000	0.035
runMNNCorrect	0.164	0.002	0.176
runModelGeneVar	0.120	0.002	0.132
runNormalization	1.189	0.018	1.442
runPerCellQC	0.135	0.004	0.205
runSCANORAMA	0	0	0
runSCMerge	0.002	0.000	0.002
runScDblFinder	10.811	0.172	12.401
runScanpyFindClusters	0.013	0.001	0.016
runScanpyFindHVG	0.014	0.004	0.024
runScanpyFindMarkers	0.012	0.002	0.015
runScanpyNormalizeData	0.042	0.001	0.054
runScanpyPCA	0.014	0.001	0.016
runScanpyScaleData	0.013	0.004	0.020
runScanpyTSNE	0.013	0.001	0.014
runScanpyUMAP	0.013	0.001	0.014
runScranSNN	0.108	0.005	0.122
runScrublet	0.013	0.003	0.016
runSeuratFindClusters	0.013	0.003	0.018
runSeuratFindHVG	0.186	0.004	0.214
runSeuratHeatmap	0.013	0.001	0.015
runSeuratICA	0.014	0.003	0.023
runSeuratJackStraw	0.013	0.002	0.015
runSeuratNormalizeData	0.013	0.001	0.014
runSeuratPCA	0.014	0.002	0.016
runSeuratSCTransform	1.682	0.023	1.816
runSeuratScaleData	0.012	0.002	0.015
runSeuratUMAP	0.012	0.001	0.014
runSingleR	0.014	0.001	0.018
runSoupX	0.000	0.001	0.000
runTSCAN	0.265	0.008	0.319
runTSCANClusterDEAnalysis	0.295	0.005	0.316
runTSCANDEG	0.310	0.005	0.338
runTSNE	0.314	0.008	0.349
runUMAP	3.576	0.019	3.792
runVAM	0.120	0.005	0.152
runZINBWaVE	0.002	0.000	0.002
sampleSummaryStats	0.064	0.001	0.072
scaterCPM	0.065	0.004	0.092
scaterPCA	0.172	0.003	0.232
scaterlogNormCounts	0.097	0.004	0.102
sce	0.012	0.002	0.015
sctkListGeneSetCollections	0.034	0.001	0.035
sctkPythonInstallConda	0	0	0
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0.000	0.000	0.001
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.035	0.002	0.037
setSCTKDisplayRow	0.175	0.006	0.197
singleCellTK	0	0	0
subDiffEx	0.153	0.014	0.171
subsetSCECols	0.037	0.004	0.050
subsetSCERows	0.112	0.006	0.119
summarizeSCE	0.032	0.005	0.042
trimCounts	0.095	0.008	0.137