Build/check report for BioC 3.22 - CHECK results for singleCellTK on nebbiolo2

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"	4892
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 nebbiolo2

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: 2.20.1

Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings singleCellTK_2.20.1.tar.gz

StartedAt: 2026-03-20 04:05:35 -0400 (Fri, 20 Mar 2026)

EndedAt: 2026-03-20 04:28:06 -0400 (Fri, 20 Mar 2026)

EllapsedTime: 1350.1 seconds

RetCode: 0

Status: OK

CheckDir: singleCellTK.Rcheck

Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings singleCellTK_2.20.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.2 (2025-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.20.1’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 80 non-default packages.
Importing from so many packages makes the package vulnerable to any of
them becoming unavailable.  Move as many as possible to Suggests and
use conditionally.
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘singleCellTK’ can be installed ... OK
* checking installed package size ... INFO
  installed size is  7.0Mb
  sub-directories of 1Mb or more:
    R         1.0Mb
    extdata   1.6Mb
    shiny     3.0Mb
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
  dedupRowNames.Rd: SingleCellExperiment-class
  detectCellOutlier.Rd: colData
  diffAbundanceFET.Rd: colData
  downSampleCells.Rd: SingleCellExperiment-class
  downSampleDepth.Rd: SingleCellExperiment-class
  featureIndex.Rd: SummarizedExperiment-class,
    SingleCellExperiment-class
  getBiomarker.Rd: SingleCellExperiment-class
  getDEGTopTable.Rd: SingleCellExperiment-class
  getEnrichRResult.Rd: SingleCellExperiment-class
  getFindMarkerTopTable.Rd: SingleCellExperiment-class
  getGenesetNamesFromCollection.Rd: SingleCellExperiment-class
  getPathwayResultNames.Rd: SingleCellExperiment-class
  getSampleSummaryStatsTable.Rd: SingleCellExperiment-class, assay,
    colData
  getSoupX.Rd: SingleCellExperiment-class
  getTSCANResults.Rd: SingleCellExperiment-class
  getTopHVG.Rd: SingleCellExperiment-class
  importAlevin.Rd: DelayedArray, readMM
  importAnnData.Rd: DelayedArray, readMM
  importBUStools.Rd: readMM
  importCellRanger.Rd: readMM, DelayedArray
  importCellRangerV2Sample.Rd: readMM, DelayedArray
  importCellRangerV3Sample.Rd: readMM, DelayedArray
  importDropEst.Rd: DelayedArray, readMM
  importExampleData.Rd: scRNAseq, Matrix, DelayedArray,
    ReprocessedFluidigmData, ReprocessedAllenData, NestorowaHSCData
  importFromFiles.Rd: readMM, DelayedArray, SingleCellExperiment-class
  importGeneSetsFromCollection.Rd: GeneSetCollection-class,
    SingleCellExperiment-class, GeneSetCollection, GSEABase, metadata
  importGeneSetsFromGMT.Rd: GeneSetCollection-class,
    SingleCellExperiment-class, getGmt, GSEABase, metadata
  importGeneSetsFromList.Rd: GeneSetCollection-class,
    SingleCellExperiment-class, GSEABase, metadata
  importGeneSetsFromMSigDB.Rd: SingleCellExperiment-class, msigdbr,
    GeneSetCollection-class, GSEABase, metadata
  importMitoGeneSet.Rd: SingleCellExperiment-class,
    GeneSetCollection-class, GSEABase, metadata
  importMultipleSources.Rd: DelayedArray
  importOptimus.Rd: readMM, DelayedArray
  importSEQC.Rd: readMM, DelayedArray
  importSTARsolo.Rd: readMM, DelayedArray
  iterateSimulations.Rd: SingleCellExperiment-class
  listSampleSummaryStatsTables.Rd: SingleCellExperiment-class, metadata
  plotBarcodeRankDropsResults.Rd: SingleCellExperiment-class
  plotBarcodeRankScatter.Rd: SingleCellExperiment-class
  plotBatchCorrCompare.Rd: SingleCellExperiment-class
  plotBatchVariance.Rd: SingleCellExperiment-class
  plotBcdsResults.Rd: SingleCellExperiment-class
  plotClusterAbundance.Rd: colData
  plotCxdsResults.Rd: SingleCellExperiment-class
  plotDEGHeatmap.Rd: SingleCellExperiment-class
  plotDEGRegression.Rd: SingleCellExperiment-class
  plotDEGViolin.Rd: SingleCellExperiment-class
  plotDEGVolcano.Rd: SingleCellExperiment-class
  plotDecontXResults.Rd: SingleCellExperiment-class
  plotDoubletFinderResults.Rd: SingleCellExperiment-class
  plotEmptyDropsResults.Rd: SingleCellExperiment-class
  plotEmptyDropsScatter.Rd: SingleCellExperiment-class
  plotEnrichR.Rd: SingleCellExperiment-class
  plotFindMarkerHeatmap.Rd: SingleCellExperiment-class
  plotPCA.Rd: SingleCellExperiment-class
  plotPathway.Rd: SingleCellExperiment-class
  plotRunPerCellQCResults.Rd: SingleCellExperiment-class
  plotSCEBarAssayData.Rd: SingleCellExperiment-class
  plotSCEBarColData.Rd: SingleCellExperiment-class
  plotSCEBatchFeatureMean.Rd: SingleCellExperiment-class
  plotSCEDensity.Rd: SingleCellExperiment-class
  plotSCEDensityAssayData.Rd: SingleCellExperiment-class
  plotSCEDensityColData.Rd: SingleCellExperiment-class
  plotSCEDimReduceColData.Rd: SingleCellExperiment-class
  plotSCEDimReduceFeatures.Rd: SingleCellExperiment-class
  plotSCEHeatmap.Rd: SingleCellExperiment-class
  plotSCEScatter.Rd: SingleCellExperiment-class
  plotSCEViolin.Rd: SingleCellExperiment-class
  plotSCEViolinAssayData.Rd: SingleCellExperiment-class
  plotSCEViolinColData.Rd: SingleCellExperiment-class
  plotScDblFinderResults.Rd: SingleCellExperiment-class
  plotScdsHybridResults.Rd: SingleCellExperiment-class
  plotScrubletResults.Rd: SingleCellExperiment-class
  plotSoupXResults.Rd: SingleCellExperiment-class
  plotTSCANClusterDEG.Rd: SingleCellExperiment-class
  plotTSCANClusterPseudo.Rd: SingleCellExperiment-class
  plotTSCANDimReduceFeatures.Rd: SingleCellExperiment-class
  plotTSCANPseudotimeGenes.Rd: SingleCellExperiment-class
  plotTSCANPseudotimeHeatmap.Rd: SingleCellExperiment-class
  plotTSCANResults.Rd: SingleCellExperiment-class
  plotTSNE.Rd: SingleCellExperiment-class
  plotUMAP.Rd: SingleCellExperiment-class
  readSingleCellMatrix.Rd: DelayedArray
  reportCellQC.Rd: SingleCellExperiment-class
  reportClusterAbundance.Rd: colData
  reportDiffAbundanceFET.Rd: colData
  retrieveSCEIndex.Rd: SingleCellExperiment-class
  runBBKNN.Rd: SingleCellExperiment-class
  runBarcodeRankDrops.Rd: SingleCellExperiment-class, colData
  runBcds.Rd: SingleCellExperiment-class, colData
  runCellQC.Rd: colData
  runComBatSeq.Rd: SingleCellExperiment-class
  runCxds.Rd: SingleCellExperiment-class, colData
  runCxdsBcdsHybrid.Rd: colData
  runDEAnalysis.Rd: SingleCellExperiment-class
  runDecontX.Rd: colData
  runDimReduce.Rd: SingleCellExperiment-class
  runDoubletFinder.Rd: SingleCellExperiment-class
  runDropletQC.Rd: colData
  runEmptyDrops.Rd: SingleCellExperiment-class, colData
  runEnrichR.Rd: SingleCellExperiment-class
  runFastMNN.Rd: SingleCellExperiment-class, BiocParallelParam-class
  runFeatureSelection.Rd: SingleCellExperiment-class
  runFindMarker.Rd: SingleCellExperiment-class
  runGSVA.Rd: SingleCellExperiment-class
  runHarmony.Rd: SingleCellExperiment-class
  runKMeans.Rd: SingleCellExperiment-class, colData
  runLimmaBC.Rd: SingleCellExperiment-class, assay
  runMNNCorrect.Rd: SingleCellExperiment-class, assay,
    BiocParallelParam-class
  runModelGeneVar.Rd: SingleCellExperiment-class
  runPerCellQC.Rd: SingleCellExperiment-class, BiocParallelParam,
    colData
  runSCANORAMA.Rd: SingleCellExperiment-class, assay
  runSCMerge.Rd: SingleCellExperiment-class, colData, assay,
    BiocParallelParam-class
  runScDblFinder.Rd: SingleCellExperiment-class, colData
  runScranSNN.Rd: SingleCellExperiment-class, reducedDim, assay,
    altExp, colData, igraph
  runScrublet.Rd: SingleCellExperiment-class, colData
  runSingleR.Rd: SingleCellExperiment-class
  runSoupX.Rd: SingleCellExperiment-class
  runTSCAN.Rd: SingleCellExperiment-class
  runTSCANClusterDEAnalysis.Rd: SingleCellExperiment-class
  runTSCANDEG.Rd: SingleCellExperiment-class
  runTSNE.Rd: SingleCellExperiment-class
  runUMAP.Rd: SingleCellExperiment-class, BiocParallelParam-class
  runVAM.Rd: SingleCellExperiment-class
  runZINBWaVE.Rd: SingleCellExperiment-class, colData,
    BiocParallelParam-class
  sampleSummaryStats.Rd: SingleCellExperiment-class, assay, colData
  scaterPCA.Rd: SingleCellExperiment-class, BiocParallelParam-class
  scaterlogNormCounts.Rd: logNormCounts
  sctkListGeneSetCollections.Rd: GeneSetCollection-class
  sctkPythonInstallConda.Rd: conda_install, reticulate, conda_create
  sctkPythonInstallVirtualEnv.Rd: virtualenv_install, reticulate,
    virtualenv_create
  selectSCTKConda.Rd: reticulate
  selectSCTKVirtualEnvironment.Rd: reticulate
  setRowNames.Rd: SingleCellExperiment-class
  setSCTKDisplayRow.Rd: SingleCellExperiment-class
  singleCellTK.Rd: SingleCellExperiment-class
  subsetSCECols.Rd: SingleCellExperiment-class
  subsetSCERows.Rd: SingleCellExperiment-class, altExp
  summarizeSCE.Rd: SingleCellExperiment-class
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                           user system elapsed
plotDoubletFinderResults 34.825  0.265  35.168
runDoubletFinder         33.249  0.874  34.123
runSeuratSCTransform     30.125  1.640  31.768
plotScDblFinderResults   29.552  0.660  27.287
runScDblFinder           17.443  0.671  15.061
plotBatchCorrCompare     11.795  0.071  12.048
importExampleData        10.338  0.326  11.068
plotDecontXResults        8.085  0.013   8.099
runUMAP                   7.561  0.355   7.995
plotScdsHybridResults     6.828  1.012   7.920
runDecontX                7.107  0.397   7.505
plotUMAP                  6.655  0.472   7.204
plotEmptyDropsScatter     6.578  0.048   6.626
plotEmptyDropsResults     6.583  0.038   6.622
detectCellOutlier         6.289  0.163   6.452
plotCxdsResults           6.279  0.085   6.446
runEmptyDrops             6.268  0.036   6.305
plotBcdsResults           5.652  0.069   5.802
plotDEGViolin             5.240  0.080   5.314
plotTSCANClusterDEG       4.893  0.306   5.198
runEnrichR                0.607  0.114 152.868
getEnrichRResult          0.631  0.058 154.099
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/home/biocbuild/bbs-3.22-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.

Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.20.1’
** 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 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

> if (requireNamespace('spelling', quietly = TRUE))
+   spelling::spell_check_test(vignettes = TRUE, error = FALSE, skip_on_cran = TRUE)
All Done!
> 
> proc.time()
   user  system elapsed 
  0.148   0.045   0.183

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

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

Attaching package: 'MatrixGenerics'

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

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

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

Attaching package: 'generics'

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

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


Attaching package: 'BiocGenerics'

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

    IQR, mad, sd, var, xtabs

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

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

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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

    findMatches

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

    I, expand.grid, unname

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

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


Attaching package: 'Biobase'

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

    rowMedians

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

    anyMissing, rowMedians

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

Attaching package: 'Matrix'

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

    expand

Loading required package: S4Arrays
Loading required package: abind

Attaching package: 'S4Arrays'

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

    abind

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

    rowsum

Loading required package: SparseArray

Attaching package: 'DelayedArray'

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

    apply, scale, sweep


Attaching package: 'singleCellTK'

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

    plotPCA

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

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

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

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
[04:26:05] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

[04:26:06] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

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%
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Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 390
Number of edges: 9849

Running Louvain algorithm...
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Maximum modularity in 10 random starts: 0.8351
Number of communities: 7
Elapsed time: 0 seconds
Using method 'umap'
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Performing log-normalization
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[ FAIL 0 | WARN 19 | SKIP 0 | PASS 223 ]

[ FAIL 0 | WARN 19 | SKIP 0 | PASS 223 ]
> 
> proc.time()
   user  system elapsed 
268.940   3.974 421.232

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.000	0.002	0.002
SEG	0.002	0.001	0.003
calcEffectSizes	0.181	0.003	0.184
combineSCE	0.705	0.002	0.707
computeZScore	0.232	0.006	0.238
convertSCEToSeurat	4.609	0.104	4.714
convertSeuratToSCE	0.342	0.005	0.347
dedupRowNames	0.055	0.000	0.055
detectCellOutlier	6.289	0.163	6.452
diffAbundanceFET	0.052	0.002	0.055
discreteColorPalette	0.005	0.000	0.006
distinctColors	0.001	0.000	0.002
downSampleCells	0.489	0.054	0.543
downSampleDepth	0.394	0.004	0.399
expData-ANY-character-method	0.120	0.001	0.121
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.162	0.017	0.178
expData-set	0.158	0.000	0.157
expData	0.129	0.000	0.129
expDataNames-ANY-method	0.121	0.007	0.128
expDataNames	0.116	0.010	0.126
expDeleteDataTag	0.033	0.002	0.034
expSetDataTag	0.026	0.000	0.026
expTaggedData	0.025	0.002	0.026
exportSCE	0.024	0.000	0.023
exportSCEtoAnnData	0.085	0.015	0.100
exportSCEtoFlatFile	0.084	0.014	0.098
featureIndex	0.034	0.003	0.038
generateSimulatedData	0.070	0.011	0.082
getBiomarker	0.056	0.003	0.060
getDEGTopTable	0.645	0.017	0.663
getDiffAbundanceResults	0.046	0.002	0.048
getEnrichRResult	0.631	0.058	154.099
getFindMarkerTopTable	1.580	0.031	1.610
getMSigDBTable	0.004	0.000	0.003
getPathwayResultNames	0.020	0.003	0.023
getSampleSummaryStatsTable	0.198	0.000	0.198
getSoupX	0	0	0
getTSCANResults	0.968	0.003	0.970
getTopHVG	0.862	0.010	0.872
importAnnData	0.002	0.000	0.002
importBUStools	0.161	0.002	0.164
importCellRanger	0.761	0.009	0.773
importCellRangerV2Sample	0.144	0.000	0.144
importCellRangerV3Sample	0.271	0.007	0.278
importDropEst	1.225	0.073	1.298
importExampleData	10.338	0.326	11.068
importGeneSetsFromCollection	1.808	0.024	1.832
importGeneSetsFromGMT	0.059	0.001	0.060
importGeneSetsFromList	0.119	0.002	0.120
importGeneSetsFromMSigDB	0.956	0.109	1.064
importMitoGeneSet	0.047	0.008	0.055
importOptimus	0.000	0.001	0.001
importSEQC	0.133	0.020	0.154
importSTARsolo	0.192	0.003	0.195
iterateSimulations	0.181	0.000	0.182
listSampleSummaryStatsTables	0.24	0.00	0.24
mergeSCEColData	0.322	0.003	0.324
mouseBrainSubsetSCE	0.034	0.001	0.035
msigdb_table	0.000	0.001	0.002
plotBarcodeRankDropsResults	0.850	0.011	0.862
plotBarcodeRankScatter	0.773	0.004	0.777
plotBatchCorrCompare	11.795	0.071	12.048
plotBatchVariance	0.470	0.003	0.473
plotBcdsResults	5.652	0.069	5.802
plotBubble	0.783	0.031	0.814
plotClusterAbundance	1.310	0.009	1.320
plotCxdsResults	6.279	0.085	6.446
plotDEGHeatmap	1.999	0.003	2.003
plotDEGRegression	4.137	0.077	4.207
plotDEGViolin	5.240	0.080	5.314
plotDEGVolcano	0.929	0.007	0.935
plotDecontXResults	8.085	0.013	8.099
plotDimRed	0.276	0.001	0.278
plotDoubletFinderResults	34.825	0.265	35.168
plotEmptyDropsResults	6.583	0.038	6.622
plotEmptyDropsScatter	6.578	0.048	6.626
plotFindMarkerHeatmap	3.694	0.029	3.722
plotMASTThresholdGenes	1.218	0.004	1.222
plotPCA	0.361	0.004	0.366
plotPathway	0.655	0.002	0.657
plotRunPerCellQCResults	2.974	0.004	2.979
plotSCEBarAssayData	0.266	0.001	0.267
plotSCEBarColData	0.224	0.000	0.225
plotSCEBatchFeatureMean	0.395	0.000	0.396
plotSCEDensity	0.344	0.002	0.346
plotSCEDensityAssayData	0.264	0.000	0.263
plotSCEDensityColData	0.293	0.001	0.293
plotSCEDimReduceColData	0.751	0.002	0.752
plotSCEDimReduceFeatures	0.369	0.001	0.370
plotSCEHeatmap	0.414	0.000	0.415
plotSCEScatter	0.372	0.001	0.372
plotSCEViolin	0.357	0.001	0.358
plotSCEViolinAssayData	0.386	0.000	0.386
plotSCEViolinColData	0.372	0.001	0.373
plotScDblFinderResults	29.552	0.660	27.287
plotScanpyDotPlot	0.023	0.000	0.023
plotScanpyEmbedding	0.023	0.000	0.022
plotScanpyHVG	0.021	0.000	0.022
plotScanpyHeatmap	0.022	0.000	0.022
plotScanpyMarkerGenes	0.021	0.000	0.022
plotScanpyMarkerGenesDotPlot	0.021	0.001	0.021
plotScanpyMarkerGenesHeatmap	0.022	0.000	0.022
plotScanpyMarkerGenesMatrixPlot	0.022	0.000	0.021
plotScanpyMarkerGenesViolin	0.021	0.000	0.022
plotScanpyMatrixPlot	0.022	0.008	0.030
plotScanpyPCA	0.019	0.002	0.022
plotScanpyPCAGeneRanking	0.022	0.000	0.022
plotScanpyPCAVariance	0.022	0.000	0.022
plotScanpyViolin	0.022	0.000	0.022
plotScdsHybridResults	6.828	1.012	7.920
plotScrubletResults	0.022	0.001	0.023
plotSeuratElbow	0.022	0.006	0.029
plotSeuratHVG	0.022	0.000	0.023
plotSeuratJackStraw	0.021	0.001	0.023
plotSeuratReduction	0.022	0.001	0.022
plotSoupXResults	0	0	0
plotTSCANClusterDEG	4.893	0.306	5.198
plotTSCANClusterPseudo	1.435	0.086	1.520
plotTSCANDimReduceFeatures	1.384	0.080	1.464
plotTSCANPseudotimeGenes	1.650	0.127	1.777
plotTSCANPseudotimeHeatmap	1.322	0.049	1.371
plotTSCANResults	1.233	0.009	1.242
plotTSNE	0.358	0.001	0.358
plotTopHVG	0.627	0.004	0.630
plotUMAP	6.655	0.472	7.204
readSingleCellMatrix	0.004	0.002	0.006
reportCellQC	0.082	0.001	0.082
reportDropletQC	0.023	0.000	0.023
reportQCTool	0.086	0.000	0.086
retrieveSCEIndex	0.029	0.000	0.029
runBBKNN	0	0	0
runBarcodeRankDrops	0.233	0.002	0.235
runBcds	0.082	0.001	0.083
runCellQC	0.087	0.001	0.088
runClusterSummaryMetrics	0.405	0.016	0.421
runComBatSeq	0.447	0.022	0.469
runCxds	0.377	0.014	0.391
runCxdsBcdsHybrid	0.092	0.015	0.107
runDEAnalysis	0.389	0.033	0.422
runDecontX	7.107	0.397	7.505
runDimReduce	0.289	0.001	0.290
runDoubletFinder	33.249	0.874	34.123
runDropletQC	0.023	0.000	0.022
runEmptyDrops	6.268	0.036	6.305
runEnrichR	0.607	0.114	152.868
runFastMNN	1.747	0.153	1.900
runFeatureSelection	0.212	0.010	0.221
runFindMarker	1.409	0.054	1.463
runGSVA	0.835	0.029	0.864
runHarmony	0.038	0.000	0.038
runKMeans	0.166	0.003	0.169
runLimmaBC	0.075	0.000	0.074
runMNNCorrect	0.387	0.000	0.387
runModelGeneVar	0.296	0.001	0.297
runNormalization	2.312	0.150	2.461
runPerCellQC	0.314	0.002	0.316
runSCANORAMA	0	0	0
runSCMerge	0.004	0.000	0.004
runScDblFinder	17.443	0.671	15.061
runScanpyFindClusters	0.023	0.000	0.023
runScanpyFindHVG	0.023	0.000	0.024
runScanpyFindMarkers	0.024	0.000	0.023
runScanpyNormalizeData	0.104	0.000	0.104
runScanpyPCA	0.023	0.000	0.023
runScanpyScaleData	0.022	0.002	0.024
runScanpyTSNE	0.023	0.000	0.023
runScanpyUMAP	0.024	0.000	0.024
runScranSNN	0.313	0.002	0.317
runScrublet	0.025	0.000	0.025
runSeuratFindClusters	0.023	0.000	0.023
runSeuratFindHVG	0.505	0.019	0.524
runSeuratHeatmap	0.023	0.001	0.024
runSeuratICA	0.022	0.000	0.022
runSeuratJackStraw	0.022	0.001	0.023
runSeuratNormalizeData	0.021	0.001	0.023
runSeuratPCA	0.023	0.000	0.023
runSeuratSCTransform	30.125	1.640	31.768
runSeuratScaleData	0.019	0.003	0.023
runSeuratUMAP	0.021	0.000	0.021
runSingleR	0.034	0.003	0.036
runSoupX	0	0	0
runTSCAN	0.663	0.024	0.688
runTSCANClusterDEAnalysis	0.758	0.022	0.781
runTSCANDEG	0.745	0.068	0.813
runTSNE	0.735	0.009	0.744
runUMAP	7.561	0.355	7.995
runVAM	0.290	0.005	0.295
runZINBWaVE	0.004	0.000	0.004
sampleSummaryStats	0.149	0.002	0.151
scaterCPM	0.128	0.008	0.136
scaterPCA	0.466	0.011	0.477
scaterlogNormCounts	0.246	0.015	0.261
sce	0.023	0.000	0.023
sctkListGeneSetCollections	0.085	0.004	0.090
sctkPythonInstallConda	0	0	0
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.089	0.005	0.094
setSCTKDisplayRow	0.435	0.019	0.454
singleCellTK	0	0	0
subDiffEx	0.351	0.023	0.374
subsetSCECols	0.082	0.006	0.088
subsetSCERows	0.225	0.008	0.233
summarizeSCE	0.080	0.002	0.082
trimCounts	0.204	0.016	0.220