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"	4893
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: 2026-03-27 04:58:36 -0400 (Fri, 27 Mar 2026)

EndedAt: 2026-03-27 05:13:39 -0400 (Fri, 27 Mar 2026)

EllapsedTime: 902.7 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 24.04.4 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 33.430  0.317  33.747
runDoubletFinder         31.194  0.150  31.344
runSeuratSCTransform     29.376  1.735  31.112
plotScDblFinderResults   29.182  0.329  26.503
runScDblFinder           16.356  0.268  13.643
plotBatchCorrCompare     11.977  0.088  12.064
importExampleData        10.475  0.355  11.344
plotDecontXResults        7.376  0.010   7.386
plotUMAP                  7.141  0.087   7.228
runUMAP                   6.460  0.354   6.815
plotScdsHybridResults     6.617  0.149   6.765
runDecontX                6.722  0.043   6.764
plotCxdsResults           6.671  0.087   6.758
plotEmptyDropsScatter     6.586  0.097   6.683
plotEmptyDropsResults     6.616  0.025   6.641
detectCellOutlier         6.245  0.163   6.408
runEmptyDrops             6.270  0.010   6.280
plotDEGViolin             5.247  0.095   5.337
plotBcdsResults           5.121  0.084   5.204
* 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 
  0.143   0.046   0.176

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%
[05:11:27] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

[05:11:28] 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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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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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 
278.305   7.525 286.748

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.003	0.000	0.002
SEG	0.002	0.001	0.002
calcEffectSizes	0.181	0.004	0.184
combineSCE	0.744	0.003	0.747
computeZScore	0.231	0.012	0.243
convertSCEToSeurat	4.551	0.109	4.661
convertSeuratToSCE	0.331	0.004	0.336
dedupRowNames	0.055	0.001	0.056
detectCellOutlier	6.245	0.163	6.408
diffAbundanceFET	0.054	0.000	0.055
discreteColorPalette	0.005	0.000	0.006
distinctColors	0.002	0.000	0.002
downSampleCells	0.511	0.051	0.563
downSampleDepth	0.420	0.003	0.424
expData-ANY-character-method	0.119	0.013	0.131
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.155	0.005	0.160
expData-set	0.141	0.003	0.144
expData	0.119	0.004	0.124
expDataNames-ANY-method	0.113	0.011	0.124
expDataNames	0.120	0.008	0.128
expDeleteDataTag	0.030	0.003	0.033
expSetDataTag	0.022	0.002	0.025
expTaggedData	0.025	0.000	0.025
exportSCE	0.020	0.002	0.023
exportSCEtoAnnData	0.090	0.010	0.101
exportSCEtoFlatFile	0.084	0.015	0.100
featureIndex	0.037	0.001	0.039
generateSimulatedData	0.078	0.007	0.085
getBiomarker	0.057	0.004	0.062
getDEGTopTable	0.692	0.013	0.706
getDiffAbundanceResults	0.05	0.00	0.05
getEnrichRResult	0.390	0.026	3.448
getFindMarkerTopTable	1.540	0.045	1.585
getMSigDBTable	0.001	0.003	0.003
getPathwayResultNames	0.020	0.002	0.022
getSampleSummaryStatsTable	0.204	0.001	0.205
getSoupX	0	0	0
getTSCANResults	0.972	0.006	0.978
getTopHVG	0.837	0.008	0.844
importAnnData	0.001	0.000	0.001
importBUStools	0.155	0.000	0.155
importCellRanger	0.721	0.006	0.727
importCellRangerV2Sample	0.136	0.000	0.136
importCellRangerV3Sample	0.268	0.003	0.271
importDropEst	1.241	0.070	1.313
importExampleData	10.475	0.355	11.344
importGeneSetsFromCollection	1.758	0.024	1.783
importGeneSetsFromGMT	0.059	0.002	0.062
importGeneSetsFromList	0.123	0.000	0.123
importGeneSetsFromMSigDB	1.037	0.087	1.125
importMitoGeneSet	0.051	0.005	0.056
importOptimus	0.001	0.000	0.001
importSEQC	0.134	0.024	0.158
importSTARsolo	0.185	0.005	0.189
iterateSimulations	0.176	0.000	0.176
listSampleSummaryStatsTables	0.249	0.003	0.252
mergeSCEColData	0.335	0.006	0.341
mouseBrainSubsetSCE	0.037	0.000	0.037
msigdb_table	0.002	0.000	0.001
plotBarcodeRankDropsResults	0.878	0.014	0.891
plotBarcodeRankScatter	0.828	0.006	0.834
plotBatchCorrCompare	11.977	0.088	12.064
plotBatchVariance	0.456	0.000	0.457
plotBcdsResults	5.121	0.084	5.204
plotBubble	0.763	0.002	0.765
plotClusterAbundance	1.337	0.033	1.370
plotCxdsResults	6.671	0.087	6.758
plotDEGHeatmap	1.971	0.006	1.978
plotDEGRegression	4.152	0.078	4.224
plotDEGViolin	5.247	0.095	5.337
plotDEGVolcano	0.908	0.005	0.913
plotDecontXResults	7.376	0.010	7.386
plotDimRed	0.265	0.003	0.268
plotDoubletFinderResults	33.430	0.317	33.747
plotEmptyDropsResults	6.616	0.025	6.641
plotEmptyDropsScatter	6.586	0.097	6.683
plotFindMarkerHeatmap	3.663	0.029	3.692
plotMASTThresholdGenes	1.215	0.007	1.222
plotPCA	0.360	0.003	0.363
plotPathway	0.639	0.002	0.642
plotRunPerCellQCResults	3.093	0.003	3.096
plotSCEBarAssayData	0.272	0.000	0.272
plotSCEBarColData	0.219	0.004	0.224
plotSCEBatchFeatureMean	0.393	0.002	0.394
plotSCEDensity	0.341	0.001	0.342
plotSCEDensityAssayData	0.262	0.002	0.264
plotSCEDensityColData	0.294	0.000	0.295
plotSCEDimReduceColData	0.760	0.002	0.762
plotSCEDimReduceFeatures	0.366	0.001	0.368
plotSCEHeatmap	0.429	0.002	0.431
plotSCEScatter	0.379	0.001	0.380
plotSCEViolin	0.361	0.000	0.362
plotSCEViolinAssayData	0.377	0.001	0.378
plotSCEViolinColData	0.367	0.002	0.369
plotScDblFinderResults	29.182	0.329	26.503
plotScanpyDotPlot	0.021	0.000	0.021
plotScanpyEmbedding	0.021	0.000	0.021
plotScanpyHVG	0.022	0.000	0.022
plotScanpyHeatmap	0.023	0.000	0.022
plotScanpyMarkerGenes	0.021	0.001	0.022
plotScanpyMarkerGenesDotPlot	0.022	0.000	0.022
plotScanpyMarkerGenesHeatmap	0.021	0.000	0.021
plotScanpyMarkerGenesMatrixPlot	0.022	0.000	0.021
plotScanpyMarkerGenesViolin	0.022	0.000	0.022
plotScanpyMatrixPlot	0.022	0.000	0.022
plotScanpyPCA	0.021	0.000	0.022
plotScanpyPCAGeneRanking	0.022	0.000	0.022
plotScanpyPCAVariance	0.021	0.000	0.022
plotScanpyViolin	0.021	0.001	0.022
plotScdsHybridResults	6.617	0.149	6.765
plotScrubletResults	0.022	0.000	0.021
plotSeuratElbow	0.022	0.000	0.021
plotSeuratHVG	0.020	0.001	0.021
plotSeuratJackStraw	0.021	0.000	0.021
plotSeuratReduction	0.021	0.000	0.022
plotSoupXResults	0	0	0
plotTSCANClusterDEG	4.795	0.017	4.813
plotTSCANClusterPseudo	1.398	0.024	1.422
plotTSCANDimReduceFeatures	1.378	0.018	1.397
plotTSCANPseudotimeGenes	1.642	0.000	1.642
plotTSCANPseudotimeHeatmap	1.324	0.006	1.330
plotTSCANResults	1.227	0.008	1.234
plotTSNE	0.366	0.015	0.380
plotTopHVG	0.623	0.004	0.627
plotUMAP	7.141	0.087	7.228
readSingleCellMatrix	0.004	0.001	0.005
reportCellQC	0.081	0.001	0.082
reportDropletQC	0.022	0.000	0.022
reportQCTool	0.078	0.004	0.082
retrieveSCEIndex	0.026	0.003	0.029
runBBKNN	0.001	0.000	0.001
runBarcodeRankDrops	0.216	0.004	0.220
runBcds	0.08	0.00	0.08
runCellQC	0.080	0.001	0.081
runClusterSummaryMetrics	0.386	0.002	0.388
runComBatSeq	0.429	0.013	0.442
runCxds	0.363	0.008	0.371
runCxdsBcdsHybrid	0.083	0.002	0.085
runDEAnalysis	0.388	0.010	0.398
runDecontX	6.722	0.043	6.764
runDimReduce	0.305	0.000	0.305
runDoubletFinder	31.194	0.150	31.344
runDropletQC	0.020	0.002	0.023
runEmptyDrops	6.27	0.01	6.28
runEnrichR	0.578	0.047	2.702
runFastMNN	1.720	0.042	1.762
runFeatureSelection	0.208	0.000	0.208
runFindMarker	1.440	0.007	1.447
runGSVA	0.835	0.009	0.844
runHarmony	0.039	0.000	0.039
runKMeans	0.175	0.000	0.175
runLimmaBC	0.08	0.00	0.08
runMNNCorrect	0.409	0.000	0.409
runModelGeneVar	0.32	0.00	0.32
runNormalization	2.418	0.113	2.531
runPerCellQC	0.337	0.000	0.337
runSCANORAMA	0	0	0
runSCMerge	0.004	0.000	0.004
runScDblFinder	16.356	0.268	13.643
runScanpyFindClusters	0.021	0.000	0.021
runScanpyFindHVG	0.019	0.002	0.021
runScanpyFindMarkers	0.022	0.000	0.021
runScanpyNormalizeData	0.094	0.002	0.096
runScanpyPCA	0.021	0.001	0.022
runScanpyScaleData	0.022	0.000	0.021
runScanpyTSNE	0.022	0.000	0.022
runScanpyUMAP	0.022	0.000	0.023
runScranSNN	0.282	0.003	0.285
runScrublet	0.021	0.000	0.021
runSeuratFindClusters	0.021	0.000	0.021
runSeuratFindHVG	0.440	0.002	0.443
runSeuratHeatmap	0.022	0.000	0.022
runSeuratICA	0.023	0.007	0.029
runSeuratJackStraw	0.022	0.000	0.022
runSeuratNormalizeData	0.021	0.000	0.021
runSeuratPCA	0.022	0.000	0.021
runSeuratSCTransform	29.376	1.735	31.112
runSeuratScaleData	0.021	0.003	0.024
runSeuratUMAP	0.022	0.000	0.021
runSingleR	0.036	0.001	0.037
runSoupX	0	0	0
runTSCAN	0.654	0.001	0.655
runTSCANClusterDEAnalysis	0.727	0.026	0.753
runTSCANDEG	0.702	0.025	0.727
runTSNE	0.722	0.013	0.735
runUMAP	6.460	0.354	6.815
runVAM	0.286	0.003	0.289
runZINBWaVE	0.004	0.000	0.004
sampleSummaryStats	0.159	0.001	0.161
scaterCPM	0.135	0.005	0.140
scaterPCA	0.440	0.014	0.454
scaterlogNormCounts	0.235	0.016	0.251
sce	0.021	0.001	0.022
sctkListGeneSetCollections	0.081	0.002	0.083
sctkPythonInstallConda	0	0	0
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.087	0.003	0.089
setSCTKDisplayRow	0.418	0.031	0.449
singleCellTK	0	0	0
subDiffEx	0.346	0.023	0.369
subsetSCECols	0.079	0.000	0.079
subsetSCERows	0.209	0.001	0.211
summarizeSCE	0.064	0.000	0.065
trimCounts	0.189	0.012	0.201