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This page was generated on 2026-02-12 11:58 -0500 (Thu, 12 Feb 2026).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.3 LTS)x86_644.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 4889
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

Package 2033/2361HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.20.1  (landing page)
Joshua David Campbell
Snapshot Date: 2026-02-09 13:45 -0500 (Mon, 09 Feb 2026)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_22
git_last_commit: 3249a1d3
git_last_commit_date: 2026-01-22 12:16:03 -0500 (Thu, 22 Jan 2026)
nebbiolo2Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
See other builds for singleCellTK in R Universe.


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: 2026-02-10 04:35:31 -0500 (Tue, 10 Feb 2026)
EndedAt: 2026-02-10 04:58:53 -0500 (Tue, 10 Feb 2026)
EllapsedTime: 1402.2 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
importGeneSetsFromMSigDB 44.531  0.966  45.497
plotDoubletFinderResults 42.459  0.394  42.932
runDoubletFinder         37.990  0.298  38.290
runSeuratSCTransform     31.342  0.681  32.026
plotScDblFinderResults   28.652  0.752  29.445
runScDblFinder           18.895  1.262  20.100
plotBatchCorrCompare     13.323  0.148  13.653
importExampleData        10.899  1.018  12.326
runUMAP                   9.716  0.147   9.942
plotDecontXResults        9.098  0.075   9.173
plotCxdsResults           7.958  0.076   8.112
runDecontX                7.878  0.131   8.010
detectCellOutlier         7.186  0.185   7.372
plotScdsHybridResults     7.246  0.110   7.430
plotUMAP                  7.092  0.080   7.248
plotDEGViolin             7.016  0.068   7.079
plotEmptyDropsResults     6.615  0.009   6.625
plotEmptyDropsScatter     6.524  0.004   6.528
runEmptyDrops             6.258  0.013   6.272
plotBcdsResults           6.108  0.078   6.264
runEnrichR                0.545  0.118 153.016
getEnrichRResult          0.501  0.049  77.913
* 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 
  0.159   0.040   0.186 

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%
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  |======================================================================| 100%
[04:56:46] WARNING: src/learner.cc:790: 
Parameters: { "nthreads" } are not used.

[04:56:47] WARNING: src/learner.cc:790: 
Parameters: { "nthreads" } are not used.

Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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  |======================================================================| 100%
Calculating gene variances
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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  |======================================================================| 100%
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 390
Number of edges: 9849

Running Louvain algorithm...
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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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  |======================================================================| 100%

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

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

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  |======================================================================| 100%
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 19 | SKIP 0 | PASS 223 ]

[ FAIL 0 | WARN 19 | SKIP 0 | PASS 223 ]
> 
> proc.time()
   user  system elapsed 
308.823  10.328 473.513 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0010.0010.003
SEG0.0020.0000.003
calcEffectSizes0.1870.0020.188
combineSCE0.6970.0010.698
computeZScore0.2300.0080.239
convertSCEToSeurat4.5630.1034.667
convertSeuratToSCE0.3710.0050.377
dedupRowNames0.0600.0010.062
detectCellOutlier7.1860.1857.372
diffAbundanceFET0.0550.0010.056
discreteColorPalette0.0060.0000.006
distinctColors0.0020.0000.002
downSampleCells0.5090.0570.565
downSampleDepth0.4390.0540.493
expData-ANY-character-method0.1280.0000.128
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1700.0020.171
expData-set0.1590.0020.161
expData0.1260.0050.131
expDataNames-ANY-method0.1200.0040.123
expDataNames0.1190.0080.126
expDeleteDataTag0.0320.0030.036
expSetDataTag0.0220.0050.026
expTaggedData0.0260.0000.026
exportSCE0.0200.0020.023
exportSCEtoAnnData0.0900.0090.100
exportSCEtoFlatFile0.0910.0070.099
featureIndex0.0350.0010.037
generateSimulatedData0.0690.0020.071
getBiomarker0.060.000.06
getDEGTopTable0.6880.0050.692
getDiffAbundanceResults0.0490.0000.049
getEnrichRResult 0.501 0.04977.913
getFindMarkerTopTable1.5450.0841.628
getMSigDBTable0.0040.0000.003
getPathwayResultNames0.0200.0030.022
getSampleSummaryStatsTable0.2180.0370.254
getSoupX000
getTSCANResults0.9950.0661.061
getTopHVG0.8070.0400.848
importAnnData0.0010.0000.001
importBUStools0.1470.0080.155
importCellRanger0.7100.0410.751
importCellRangerV2Sample0.1450.0210.165
importCellRangerV3Sample0.2860.0160.302
importDropEst1.2700.1441.415
importExampleData10.899 1.01812.326
importGeneSetsFromCollection1.7820.1031.885
importGeneSetsFromGMT0.0620.0010.064
importGeneSetsFromList0.1280.0010.128
importGeneSetsFromMSigDB44.531 0.96645.497
importMitoGeneSet0.0540.0020.056
importOptimus0.0020.0000.002
importSEQC0.1330.0270.161
importSTARsolo0.1380.0290.167
iterateSimulations0.1740.0280.203
listSampleSummaryStatsTables0.2430.0340.277
mergeSCEColData0.3690.0130.382
mouseBrainSubsetSCE0.0340.0010.035
msigdb_table0.0010.0000.001
plotBarcodeRankDropsResults0.8560.0080.865
plotBarcodeRankScatter0.8540.0000.854
plotBatchCorrCompare13.323 0.14813.653
plotBatchVariance0.4660.0030.470
plotBcdsResults6.1080.0786.264
plotBubble0.7790.0020.781
plotClusterAbundance1.3660.0451.412
plotCxdsResults7.9580.0768.112
plotDEGHeatmap2.0640.0072.069
plotDEGRegression4.4440.0804.518
plotDEGViolin7.0160.0687.079
plotDEGVolcano0.9240.0050.930
plotDecontXResults9.0980.0759.173
plotDimRed0.2790.0030.281
plotDoubletFinderResults42.459 0.39442.932
plotEmptyDropsResults6.6150.0096.625
plotEmptyDropsScatter6.5240.0046.528
plotFindMarkerHeatmap3.6890.0033.693
plotMASTThresholdGenes1.2710.0091.281
plotPCA0.3580.0030.361
plotPathway0.7180.0010.720
plotRunPerCellQCResults3.0150.0223.038
plotSCEBarAssayData0.3290.0020.331
plotSCEBarColData0.2260.0010.226
plotSCEBatchFeatureMean0.3800.0000.379
plotSCEDensity0.3080.0010.309
plotSCEDensityAssayData0.3150.0000.316
plotSCEDensityColData0.2980.0020.300
plotSCEDimReduceColData0.7350.0040.739
plotSCEDimReduceFeatures0.4140.0000.414
plotSCEHeatmap0.4180.0010.419
plotSCEScatter0.370.000.37
plotSCEViolin0.4110.0030.414
plotSCEViolinAssayData0.3770.0100.387
plotSCEViolinColData0.3690.0060.375
plotScDblFinderResults28.652 0.75229.445
plotScanpyDotPlot0.0230.0000.022
plotScanpyEmbedding0.0240.0000.023
plotScanpyHVG0.0220.0000.023
plotScanpyHeatmap0.0220.0000.022
plotScanpyMarkerGenes0.0220.0000.022
plotScanpyMarkerGenesDotPlot0.0220.0000.022
plotScanpyMarkerGenesHeatmap0.0220.0000.023
plotScanpyMarkerGenesMatrixPlot0.0210.0000.022
plotScanpyMarkerGenesViolin0.0210.0000.021
plotScanpyMatrixPlot0.0210.0000.021
plotScanpyPCA0.0200.0010.021
plotScanpyPCAGeneRanking0.0220.0000.022
plotScanpyPCAVariance0.0210.0010.021
plotScanpyViolin0.0210.0000.021
plotScdsHybridResults7.2460.1107.430
plotScrubletResults0.0220.0000.021
plotSeuratElbow0.0210.0000.021
plotSeuratHVG0.0200.0020.021
plotSeuratJackStraw0.0210.0000.021
plotSeuratReduction0.020.000.02
plotSoupXResults000
plotTSCANClusterDEG4.6920.0104.703
plotTSCANClusterPseudo1.4320.0021.435
plotTSCANDimReduceFeatures1.2790.0011.281
plotTSCANPseudotimeGenes1.6130.0001.614
plotTSCANPseudotimeHeatmap1.3310.0001.330
plotTSCANResults1.1780.0031.182
plotTSNE0.3750.0010.376
plotTopHVG0.6540.0000.654
plotUMAP7.0920.0807.248
readSingleCellMatrix0.0050.0000.005
reportCellQC0.0810.0000.081
reportDropletQC0.0230.0000.022
reportQCTool0.0790.0000.078
retrieveSCEIndex0.0270.0010.029
runBBKNN000
runBarcodeRankDrops0.2280.0010.229
runBcds0.0760.0010.077
runCellQC0.0950.0010.096
runClusterSummaryMetrics0.3730.0000.374
runComBatSeq0.4160.0050.422
runCxds0.3530.0000.353
runCxdsBcdsHybrid0.0790.0000.078
runDEAnalysis0.3800.0010.381
runDecontX7.8780.1318.010
runDimReduce0.3130.0000.313
runDoubletFinder37.990 0.29838.290
runDropletQC0.0240.0000.024
runEmptyDrops6.2580.0136.272
runEnrichR 0.545 0.118153.016
runFastMNN1.8310.2202.052
runFeatureSelection0.2220.0110.233
runFindMarker1.6170.1691.787
runGSVA0.9860.1651.150
runHarmony0.0530.0000.052
runKMeans0.1950.0220.218
runLimmaBC0.0910.0070.098
runMNNCorrect0.4940.0310.525
runModelGeneVar0.3290.0280.358
runNormalization3.0930.5163.609
runPerCellQC0.3400.0090.349
runSCANORAMA000
runSCMerge0.0040.0000.004
runScDblFinder18.895 1.26220.100
runScanpyFindClusters0.0230.0010.023
runScanpyFindHVG0.0210.0000.021
runScanpyFindMarkers0.0220.0000.022
runScanpyNormalizeData0.1020.0010.103
runScanpyPCA0.0230.0010.024
runScanpyScaleData0.0220.0000.022
runScanpyTSNE0.0220.0000.022
runScanpyUMAP0.0210.0010.022
runScranSNN0.2980.0100.308
runScrublet0.0220.0000.022
runSeuratFindClusters0.0210.0000.021
runSeuratFindHVG0.4830.0030.486
runSeuratHeatmap0.0220.0010.023
runSeuratICA0.0210.0010.022
runSeuratJackStraw0.0210.0010.023
runSeuratNormalizeData0.0230.0000.022
runSeuratPCA0.0210.0020.023
runSeuratSCTransform31.342 0.68132.026
runSeuratScaleData0.0240.0000.024
runSeuratUMAP0.0240.0000.024
runSingleR0.0500.0000.051
runSoupX000
runTSCAN0.7220.0040.727
runTSCANClusterDEAnalysis0.8240.0090.833
runTSCANDEG0.9010.0280.929
runTSNE0.7570.0010.757
runUMAP9.7160.1479.942
runVAM0.2960.0020.297
runZINBWaVE0.0040.0000.004
sampleSummaryStats0.1590.0000.159
scaterCPM0.1340.0100.143
scaterPCA0.4700.0010.470
scaterlogNormCounts0.2410.0020.243
sce0.0200.0010.022
sctkListGeneSetCollections0.0810.0000.081
sctkPythonInstallConda0.0010.0000.000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.0890.0000.088
setSCTKDisplayRow0.4430.0000.443
singleCellTK000
subDiffEx0.3430.0000.344
subsetSCECols0.090.000.09
subsetSCERows0.2880.0010.290
summarizeSCE0.0690.0000.069
trimCounts0.2110.0190.230