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: 2026-03-25 03:57:07 -0400 (Wed, 25 Mar 2026)

EndedAt: 2026-03-25 04:12:01 -0400 (Wed, 25 Mar 2026)

EllapsedTime: 894.8 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 33.215  0.238  33.454
runDoubletFinder         30.117  0.240  30.357
runSeuratSCTransform     28.789  0.773  29.565
plotScDblFinderResults   28.608  0.462  26.095
runScDblFinder           15.924  0.698  13.632
plotBatchCorrCompare     12.952  0.349  13.300
importExampleData        10.381  0.958  11.817
plotDecontXResults        7.549  0.107   7.656
plotCxdsResults           6.854  0.143   6.998
plotEmptyDropsResults     6.594  0.001   6.597
runUMAP                   6.415  0.165   6.580
plotEmptyDropsScatter     6.560  0.012   6.572
runDecontX                6.357  0.073   6.430
plotUMAP                  6.264  0.011   6.275
runEmptyDrops             6.248  0.001   6.249
plotScdsHybridResults     6.132  0.019   6.151
detectCellOutlier         5.848  0.157   6.006
plotDEGViolin             5.231  0.057   5.281
plotBcdsResults           5.095  0.117   5.212
* 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 
  0.142   0.035   0.168

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%
[04:09:56] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

[04:09:57] 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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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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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 
270.483  10.720 282.641

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.001	0.001	0.002
SEG	0.003	0.000	0.003
calcEffectSizes	0.177	0.006	0.184
combineSCE	0.693	0.000	0.694
computeZScore	0.227	0.010	0.237
convertSCEToSeurat	4.291	0.082	4.374
convertSeuratToSCE	0.313	0.004	0.319
dedupRowNames	0.052	0.012	0.065
detectCellOutlier	5.848	0.157	6.006
diffAbundanceFET	0.052	0.002	0.055
discreteColorPalette	0.005	0.001	0.006
distinctColors	0.001	0.000	0.002
downSampleCells	0.487	0.054	0.542
downSampleDepth	0.388	0.008	0.397
expData-ANY-character-method	0.113	0.002	0.116
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.149	0.001	0.151
expData-set	0.142	0.001	0.143
expData	0.114	0.001	0.116
expDataNames-ANY-method	0.110	0.000	0.111
expDataNames	0.111	0.006	0.117
expDeleteDataTag	0.030	0.000	0.032
expSetDataTag	0.024	0.001	0.024
expTaggedData	0.025	0.000	0.024
exportSCE	0.019	0.003	0.022
exportSCEtoAnnData	0.092	0.007	0.098
exportSCEtoFlatFile	0.087	0.010	0.098
featureIndex	0.034	0.003	0.037
generateSimulatedData	0.066	0.002	0.068
getBiomarker	0.055	0.000	0.056
getDEGTopTable	0.628	0.030	0.657
getDiffAbundanceResults	0.045	0.002	0.046
getEnrichRResult	0.592	0.069	3.906
getFindMarkerTopTable	1.571	0.118	1.689
getMSigDBTable	0.003	0.000	0.004
getPathwayResultNames	0.017	0.005	0.023
getSampleSummaryStatsTable	0.221	0.021	0.242
getSoupX	0.000	0.000	0.001
getTSCANResults	0.94	0.03	0.97
getTopHVG	0.816	0.016	0.831
importAnnData	0.001	0.000	0.001
importBUStools	0.143	0.015	0.159
importCellRanger	0.737	0.099	0.838
importCellRangerV2Sample	0.133	0.001	0.133
importCellRangerV3Sample	0.267	0.012	0.279
importDropEst	1.321	0.206	1.528
importExampleData	10.381	0.958	11.817
importGeneSetsFromCollection	1.844	0.129	1.973
importGeneSetsFromGMT	0.061	0.002	0.063
importGeneSetsFromList	0.124	0.000	0.124
importGeneSetsFromMSigDB	0.998	0.084	1.081
importMitoGeneSet	0.052	0.005	0.057
importOptimus	0.001	0.001	0.001
importSEQC	0.143	0.012	0.155
importSTARsolo	0.192	0.004	0.197
iterateSimulations	0.185	0.014	0.200
listSampleSummaryStatsTables	0.263	0.002	0.265
mergeSCEColData	0.356	0.005	0.361
mouseBrainSubsetSCE	0.035	0.001	0.037
msigdb_table	0.000	0.001	0.001
plotBarcodeRankDropsResults	0.879	0.013	0.892
plotBarcodeRankScatter	0.831	0.023	0.855
plotBatchCorrCompare	12.952	0.349	13.300
plotBatchVariance	0.456	0.019	0.475
plotBcdsResults	5.095	0.117	5.212
plotBubble	0.779	0.032	0.811
plotClusterAbundance	1.325	0.007	1.332
plotCxdsResults	6.854	0.143	6.998
plotDEGHeatmap	2.013	0.013	2.026
plotDEGRegression	4.205	0.047	4.246
plotDEGViolin	5.231	0.057	5.281
plotDEGVolcano	0.906	0.002	0.909
plotDecontXResults	7.549	0.107	7.656
plotDimRed	0.277	0.001	0.278
plotDoubletFinderResults	33.215	0.238	33.454
plotEmptyDropsResults	6.594	0.001	6.597
plotEmptyDropsScatter	6.560	0.012	6.572
plotFindMarkerHeatmap	3.583	0.027	3.609
plotMASTThresholdGenes	1.193	0.012	1.205
plotPCA	0.359	0.004	0.363
plotPathway	0.637	0.003	0.639
plotRunPerCellQCResults	2.964	0.002	2.966
plotSCEBarAssayData	0.267	0.001	0.268
plotSCEBarColData	0.221	0.001	0.221
plotSCEBatchFeatureMean	0.381	0.002	0.383
plotSCEDensity	0.328	0.001	0.329
plotSCEDensityAssayData	0.26	0.00	0.26
plotSCEDensityColData	0.302	0.001	0.303
plotSCEDimReduceColData	0.764	0.000	0.764
plotSCEDimReduceFeatures	0.368	0.014	0.382
plotSCEHeatmap	0.419	0.032	0.451
plotSCEScatter	0.378	0.006	0.385
plotSCEViolin	0.347	0.001	0.348
plotSCEViolinAssayData	0.369	0.001	0.370
plotSCEViolinColData	0.355	0.000	0.355
plotScDblFinderResults	28.608	0.462	26.095
plotScanpyDotPlot	0.022	0.001	0.023
plotScanpyEmbedding	0.021	0.000	0.021
plotScanpyHVG	0.021	0.000	0.022
plotScanpyHeatmap	0.022	0.000	0.022
plotScanpyMarkerGenes	0.021	0.001	0.022
plotScanpyMarkerGenesDotPlot	0.022	0.000	0.021
plotScanpyMarkerGenesHeatmap	0.021	0.000	0.022
plotScanpyMarkerGenesMatrixPlot	0.022	0.000	0.022
plotScanpyMarkerGenesViolin	0.022	0.000	0.022
plotScanpyMatrixPlot	0.022	0.000	0.023
plotScanpyPCA	0.023	0.000	0.023
plotScanpyPCAGeneRanking	0.021	0.001	0.022
plotScanpyPCAVariance	0.021	0.001	0.022
plotScanpyViolin	0.023	0.000	0.023
plotScdsHybridResults	6.132	0.019	6.151
plotScrubletResults	0.022	0.000	0.022
plotSeuratElbow	0.022	0.000	0.022
plotSeuratHVG	0.022	0.000	0.022
plotSeuratJackStraw	0.022	0.000	0.022
plotSeuratReduction	0.022	0.000	0.022
plotSoupXResults	0.001	0.000	0.000
plotTSCANClusterDEG	4.714	0.007	4.720
plotTSCANClusterPseudo	1.360	0.002	1.361
plotTSCANDimReduceFeatures	1.317	0.004	1.320
plotTSCANPseudotimeGenes	1.617	0.002	1.619
plotTSCANPseudotimeHeatmap	1.313	0.004	1.317
plotTSCANResults	1.219	0.010	1.230
plotTSNE	0.367	0.001	0.368
plotTopHVG	0.608	0.004	0.612
plotUMAP	6.264	0.011	6.275
readSingleCellMatrix	0.005	0.000	0.005
reportCellQC	0.075	0.002	0.078
reportDropletQC	0.020	0.001	0.021
reportQCTool	0.075	0.001	0.076
retrieveSCEIndex	0.027	0.000	0.027
runBBKNN	0	0	0
runBarcodeRankDrops	0.222	0.000	0.222
runBcds	0.076	0.001	0.077
runCellQC	0.077	0.001	0.077
runClusterSummaryMetrics	0.365	0.001	0.366
runComBatSeq	0.428	0.003	0.430
runCxds	0.354	0.000	0.354
runCxdsBcdsHybrid	0.079	0.000	0.079
runDEAnalysis	0.366	0.002	0.368
runDecontX	6.357	0.073	6.430
runDimReduce	0.272	0.001	0.273
runDoubletFinder	30.117	0.240	30.357
runDropletQC	0.021	0.000	0.021
runEmptyDrops	6.248	0.001	6.249
runEnrichR	0.524	0.066	2.760
runFastMNN	1.632	0.135	1.767
runFeatureSelection	0.202	0.011	0.214
runFindMarker	1.425	0.128	1.553
runGSVA	0.842	0.093	0.935
runHarmony	0.041	0.001	0.041
runKMeans	0.168	0.014	0.181
runLimmaBC	0.078	0.009	0.087
runMNNCorrect	0.398	0.012	0.410
runModelGeneVar	0.314	0.024	0.339
runNormalization	2.356	0.382	2.738
runPerCellQC	0.313	0.018	0.331
runSCANORAMA	0	0	0
runSCMerge	0.004	0.000	0.004
runScDblFinder	15.924	0.698	13.632
runScanpyFindClusters	0.021	0.001	0.022
runScanpyFindHVG	0.021	0.000	0.021
runScanpyFindMarkers	0.022	0.000	0.021
runScanpyNormalizeData	0.093	0.000	0.092
runScanpyPCA	0.022	0.000	0.022
runScanpyScaleData	0.021	0.001	0.022
runScanpyTSNE	0.022	0.000	0.023
runScanpyUMAP	0.021	0.000	0.022
runScranSNN	0.280	0.002	0.282
runScrublet	0.022	0.000	0.022
runSeuratFindClusters	0.020	0.001	0.022
runSeuratFindHVG	0.451	0.003	0.453
runSeuratHeatmap	0.021	0.001	0.021
runSeuratICA	0.022	0.000	0.021
runSeuratJackStraw	0.022	0.000	0.022
runSeuratNormalizeData	0.021	0.000	0.022
runSeuratPCA	0.021	0.001	0.021
runSeuratSCTransform	28.789	0.773	29.565
runSeuratScaleData	0.022	0.001	0.022
runSeuratUMAP	0.022	0.000	0.021
runSingleR	0.036	0.000	0.036
runSoupX	0.000	0.000	0.001
runTSCAN	0.637	0.012	0.649
runTSCANClusterDEAnalysis	0.711	0.011	0.722
runTSCANDEG	0.688	0.012	0.700
runTSNE	0.725	0.000	0.725
runUMAP	6.415	0.165	6.580
runVAM	0.273	0.000	0.274
runZINBWaVE	0.004	0.000	0.004
sampleSummaryStats	0.146	0.000	0.145
scaterCPM	0.130	0.002	0.131
scaterPCA	0.412	0.000	0.412
scaterlogNormCounts	0.222	0.009	0.232
sce	0.020	0.001	0.021
sctkListGeneSetCollections	0.075	0.001	0.076
sctkPythonInstallConda	0	0	0
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.08	0.00	0.08
setSCTKDisplayRow	0.402	0.000	0.402
singleCellTK	0	0	0
subDiffEx	0.326	0.001	0.328
subsetSCECols	0.075	0.000	0.075
subsetSCERows	0.202	0.011	0.213
summarizeSCE	0.064	0.001	0.065
trimCounts	0.194	0.006	0.200