Back to Multiple platform build/check report for BioC 3.23:   simplified   long
ABCDEFGHIJKLMNOPQR[S]TUVWXYZ

This page was generated on 2026-01-15 11:35 -0500 (Thu, 15 Jan 2026).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.3 LTS)x86_64R Under development (unstable) (2025-12-22 r89219) -- "Unsuffered Consequences" 4848
kjohnson3macOS 13.7.7 Venturaarm64R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" 4628
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 2016/2343HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.21.1  (landing page)
Joshua David Campbell
Snapshot Date: 2026-01-14 13:40 -0500 (Wed, 14 Jan 2026)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: devel
git_last_commit: 15d4a13
git_last_commit_date: 2026-01-11 08:42:53 -0500 (Sun, 11 Jan 2026)
nebbiolo1Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
kjohnson3macOS 13.7.7 Ventura / arm64  OK    OK    OK    OK  NO, package depends on 'batchelor' which is only available as a source package that needs compilation


CHECK results for singleCellTK on nebbiolo1

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: 2.21.1
Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings singleCellTK_2.21.1.tar.gz
StartedAt: 2026-01-15 04:12:57 -0500 (Thu, 15 Jan 2026)
EndedAt: 2026-01-15 04:30:05 -0500 (Thu, 15 Jan 2026)
EllapsedTime: 1028.1 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings singleCellTK_2.21.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck’
* using R Under development (unstable) (2025-12-22 r89219)
* 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 ‘2.21.1’
* 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  5.6Mb
  sub-directories of 1Mb or more:
    R       1.0Mb
    shiny   2.3Mb
* 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 45.148  0.717  45.868
plotDoubletFinderResults 38.613  0.349  38.963
runDoubletFinder         33.836  0.187  34.028
runSeuratSCTransform     29.373  0.272  29.646
plotScDblFinderResults   27.617  0.808  28.394
runScDblFinder           17.506  0.493  17.964
plotBatchCorrCompare     13.779  0.167  13.946
importExampleData        11.023  0.549  11.936
plotScdsHybridResults    10.211  0.079   9.712
plotBcdsResults           8.797  0.159   8.412
plotDecontXResults        8.803  0.068   8.872
runUMAP                   7.961  0.127   8.089
runDecontX                7.748  0.112   7.862
plotCxdsResults           7.437  0.105   7.541
plotUMAP                  7.069  0.083   7.154
plotEmptyDropsResults     6.627  0.011   6.637
plotEmptyDropsScatter     6.544  0.005   6.549
detectCellOutlier         6.261  0.199   6.461
runEmptyDrops             6.250  0.016   6.265
plotDEGViolin             5.272  0.062   5.329
* 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-3.23-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.


Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.21.1’
** 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 Under development (unstable) (2025-12-22 r89219) -- "Unsuffered Consequences"
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 
  0.146   0.045   0.178 

singleCellTK.Rcheck/tests/testthat.Rout


R Under development (unstable) (2025-12-22 r89219) -- "Unsuffered Consequences"
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%
[04:27:50] WARNING: src/learner.cc:790: 
Parameters: { "nthreads" } are not used.

[04:27:51] WARNING: src/learner.cc:790: 
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 390
Number of edges: 9849

Running Louvain algorithm...
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Maximum modularity in 10 random starts: 0.8351
Number of communities: 7
Elapsed time: 0 seconds
Using method 'umap'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 19 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 19 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
321.776   9.113 334.926 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0020.0010.002
SEG0.0020.0010.002
calcEffectSizes0.1480.0160.166
combineSCE0.7490.0230.773
computeZScore0.2420.0120.254
convertSCEToSeurat4.5170.1634.684
convertSeuratToSCE0.3470.0100.357
dedupRowNames0.0560.0010.057
detectCellOutlier6.2610.1996.461
diffAbundanceFET0.0540.0020.056
discreteColorPalette0.0050.0000.006
distinctColors0.0010.0010.002
downSampleCells0.5080.0380.546
downSampleDepth0.4220.0030.425
expData-ANY-character-method0.1270.0020.129
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1750.0310.206
expData-set0.1650.0040.169
expData0.1310.0040.135
expDataNames-ANY-method0.1200.0030.122
expDataNames0.1070.0100.117
expDeleteDataTag0.0340.0020.035
expSetDataTag0.0250.0000.024
expTaggedData0.0250.0000.025
exportSCE0.0200.0010.022
exportSCEtoAnnData0.0970.0030.099
exportSCEtoFlatFile0.0900.0070.098
featureIndex0.0370.0020.038
generateSimulatedData0.0490.0040.054
getBiomarker0.0590.0050.063
getDEGTopTable0.7290.0820.811
getDiffAbundanceResults0.0460.0050.052
getEnrichRResult0.3960.0263.335
getFindMarkerTopTable1.5200.0361.557
getMSigDBTable0.0020.0020.004
getPathwayResultNames0.0220.0000.022
getSampleSummaryStatsTable0.180.010.19
getSoupX000
getTSCANResults0.9780.0110.988
getTopHVG0.8470.0040.852
importAnnData0.0010.0010.002
importBUStools0.1450.0020.146
importCellRanger0.8690.0160.886
importCellRangerV2Sample0.1490.0020.152
importCellRangerV3Sample0.2620.0010.263
importDropEst0.2030.0000.204
importExampleData11.023 0.54911.936
importGeneSetsFromCollection1.7280.0691.797
importGeneSetsFromGMT0.0660.0000.065
importGeneSetsFromList0.1180.0040.123
importGeneSetsFromMSigDB45.148 0.71745.868
importMitoGeneSet0.0530.0080.062
importOptimus0.0020.0000.001
importSEQC0.1430.0200.164
importSTARsolo0.1490.0230.173
iterateSimulations0.1900.0180.208
listSampleSummaryStatsTables0.2580.0320.290
mergeSCEColData0.3810.0220.404
mouseBrainSubsetSCE0.0370.0000.036
msigdb_table0.0010.0000.002
plotBarcodeRankDropsResults0.8620.0100.872
plotBarcodeRankScatter0.8560.0030.859
plotBatchCorrCompare13.779 0.16713.946
plotBatchVariance0.5040.0200.524
plotBcdsResults8.7970.1598.412
plotBubble0.7880.0050.793
plotClusterAbundance1.3100.0021.313
plotCxdsResults7.4370.1057.541
plotDEGHeatmap2.0720.0152.087
plotDEGRegression4.2720.0164.282
plotDEGViolin5.2720.0625.329
plotDEGVolcano0.9610.0040.965
plotDecontXResults8.8030.0688.872
plotDimRed0.2700.0030.274
plotDoubletFinderResults38.613 0.34938.963
plotEmptyDropsResults6.6270.0116.637
plotEmptyDropsScatter6.5440.0056.549
plotFindMarkerHeatmap3.8310.0063.837
plotMASTThresholdGenes1.2540.0131.267
plotPCA0.3630.0020.364
plotPathway0.7350.0020.737
plotRunPerCellQCResults2.9910.0002.991
plotSCEBarAssayData0.2870.0010.288
plotSCEBarColData0.2850.0010.287
plotSCEBatchFeatureMean0.3830.0000.384
plotSCEDensity0.3150.0020.318
plotSCEDensityAssayData0.2800.0010.282
plotSCEDensityColData0.3530.0010.355
plotSCEDimReduceColData0.7070.0180.725
plotSCEDimReduceFeatures0.3750.0070.383
plotSCEHeatmap0.4620.0160.478
plotSCEScatter0.3480.0080.356
plotSCEViolin0.3620.0050.368
plotSCEViolinAssayData0.4550.0040.460
plotSCEViolinColData0.3500.0010.350
plotScDblFinderResults27.617 0.80828.394
plotScanpyDotPlot0.0210.0000.022
plotScanpyEmbedding0.0220.0000.021
plotScanpyHVG0.0210.0000.021
plotScanpyHeatmap0.0210.0000.022
plotScanpyMarkerGenes0.0210.0000.022
plotScanpyMarkerGenesDotPlot0.0220.0000.022
plotScanpyMarkerGenesHeatmap0.0200.0020.022
plotScanpyMarkerGenesMatrixPlot0.0190.0020.022
plotScanpyMarkerGenesViolin0.0220.0000.022
plotScanpyMatrixPlot0.0210.0010.021
plotScanpyPCA0.0190.0020.022
plotScanpyPCAGeneRanking0.0220.0000.022
plotScanpyPCAVariance0.0200.0010.022
plotScanpyViolin0.0200.0010.021
plotScdsHybridResults10.211 0.079 9.712
plotScrubletResults0.0220.0000.022
plotSeuratElbow0.0200.0010.022
plotSeuratHVG0.0210.0000.022
plotSeuratJackStraw0.0220.0000.021
plotSeuratReduction0.0210.0000.022
plotSoupXResults0.0000.0000.001
plotTSCANClusterDEG4.8120.0174.831
plotTSCANClusterPseudo1.2950.0071.302
plotTSCANDimReduceFeatures1.3660.0061.373
plotTSCANPseudotimeGenes1.6150.0011.616
plotTSCANPseudotimeHeatmap1.3480.0041.351
plotTSCANResults1.2490.0031.252
plotTSNE0.3670.0000.368
plotTopHVG0.6320.0010.633
plotUMAP7.0690.0837.154
readSingleCellMatrix0.0050.0000.005
reportCellQC0.0790.0010.081
reportDropletQC0.0230.0000.022
reportQCTool0.0790.0010.080
retrieveSCEIndex0.0280.0000.027
runBBKNN0.0010.0000.000
runBarcodeRankDrops0.2220.0020.224
runBcds1.4850.0360.948
runCellQC0.0760.0020.079
runClusterSummaryMetrics0.3560.0040.360
runComBatSeq0.4260.0050.430
runCxds0.3140.0010.315
runCxdsBcdsHybrid1.4390.0160.920
runDEAnalysis0.4480.0040.452
runDecontX7.7480.1127.862
runDimReduce0.2810.0080.289
runDoubletFinder33.836 0.18734.028
runDropletQC0.0200.0010.022
runEmptyDrops6.2500.0166.265
runEnrichR0.4570.0252.595
runFastMNN1.6840.0331.717
runFeatureSelection0.210.000.21
runFindMarker1.4060.0081.414
runGSVA0.7910.0290.820
runHarmony0.1160.0160.132
runKMeans0.1670.0040.171
runLimmaBC0.0760.0010.077
runMNNCorrect0.3900.0080.398
runModelGeneVar0.2900.0140.305
runNormalization2.4440.0342.478
runPerCellQC0.3170.0020.319
runSCANORAMA000
runSCMerge0.0030.0000.004
runScDblFinder17.506 0.49317.964
runScanpyFindClusters0.0200.0010.021
runScanpyFindHVG0.0210.0000.021
runScanpyFindMarkers0.0210.0000.021
runScanpyNormalizeData0.0870.0020.090
runScanpyPCA0.0210.0000.022
runScanpyScaleData0.0200.0010.021
runScanpyTSNE0.0200.0010.021
runScanpyUMAP0.0190.0020.021
runScranSNN0.2650.0030.268
runScrublet0.0210.0000.021
runSeuratFindClusters0.0210.0000.022
runSeuratFindHVG0.4370.0120.449
runSeuratHeatmap0.0200.0010.022
runSeuratICA0.0210.0000.022
runSeuratJackStraw0.0210.0000.021
runSeuratNormalizeData0.0210.0010.021
runSeuratPCA0.0220.0000.022
runSeuratSCTransform29.373 0.27229.646
runSeuratScaleData0.0220.0000.021
runSeuratUMAP0.0210.0000.022
runSingleR0.0360.0010.036
runSoupX0.0010.0000.000
runTSCAN0.6380.0060.644
runTSCANClusterDEAnalysis0.7290.0030.733
runTSCANDEG0.7150.0130.729
runTSNE0.7120.0000.712
runUMAP7.9610.1278.089
runVAM0.2880.0000.288
runZINBWaVE0.0040.0000.005
sampleSummaryStats0.1550.0000.155
scaterCPM0.1350.0000.134
scaterPCA0.4360.0000.435
scaterlogNormCounts0.230.000.23
sce0.0200.0010.021
sctkListGeneSetCollections0.0770.0020.079
sctkPythonInstallConda0.0000.0010.000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.0790.0020.081
setSCTKDisplayRow0.4120.0010.413
singleCellTK0.0010.0000.001
subDiffEx0.3140.0030.317
subsetSCECols0.0780.0000.078
subsetSCERows0.2530.0020.255
summarizeSCE0.0660.0020.068
trimCounts0.2000.0030.203