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This page was generated on 2026-02-27 11:32 -0500 (Fri, 27 Feb 2026).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.3 LTS)x86_64R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences" 4877
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Package 2028/2357HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.21.1  (landing page)
Joshua David Campbell
Snapshot Date: 2026-02-26 13:40 -0500 (Thu, 26 Feb 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
See other builds for singleCellTK in R Universe.


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: 2026-02-27 04:23:19 -0500 (Fri, 27 Feb 2026)
EndedAt: 2026-02-27 04:40:27 -0500 (Fri, 27 Feb 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) (2026-01-15 r89304)
* 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 44.805  0.946  45.755
plotDoubletFinderResults 40.406  0.332  40.739
runDoubletFinder         34.858  0.138  34.998
runSeuratSCTransform     30.178  1.332  31.512
plotScDblFinderResults   27.010  0.760  24.834
runScDblFinder           16.520  1.366  14.912
importExampleData        11.192  1.584  13.168
plotBatchCorrCompare     12.546  0.123  12.669
plotDecontXResults       11.804  0.061  11.866
plotScdsHybridResults     9.719  0.092   9.217
plotBcdsResults           8.620  0.157   8.204
runUMAP                   7.903  0.169   8.073
plotUMAP                  7.561  0.152   7.714
plotCxdsResults           7.617  0.059   7.677
runDecontX                7.257  0.103   7.360
plotEmptyDropsResults     6.707  0.010   6.717
plotEmptyDropsScatter     6.621  0.011   6.631
runEmptyDrops             6.317  0.011   6.330
plotDEGViolin             5.500  0.057   5.552
detectCellOutlier         5.077  0.177   5.254
* 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) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

> if (requireNamespace('spelling', quietly = TRUE))
+   spelling::spell_check_test(vignettes = TRUE, error = FALSE, skip_on_cran = TRUE)
All Done!
> 
> proc.time()
   user  system elapsed 
  0.143   0.040   0.171 

singleCellTK.Rcheck/tests/testthat.Rout


R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 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%
[04:38:12] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

[04:38:13] WARNING: src/learner.cc:782: 
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
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
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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 225 ]

[ FAIL 0 | WARN 19 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
320.827  10.735 329.226 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0010.0010.002
SEG0.0020.0000.003
calcEffectSizes0.1520.0110.163
combineSCE0.6960.0310.727
computeZScore0.2350.0100.246
convertSCEToSeurat4.5360.1504.686
convertSeuratToSCE0.3670.0020.370
dedupRowNames0.0580.0000.058
detectCellOutlier5.0770.1775.254
diffAbundanceFET0.0520.0010.052
discreteColorPalette0.0060.0000.005
distinctColors0.0020.0000.002
downSampleCells0.4660.0390.505
downSampleDepth0.3740.0050.380
expData-ANY-character-method0.1140.0000.113
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1480.0020.150
expData-set0.1430.0000.142
expData0.1180.0000.117
expDataNames-ANY-method0.1070.0010.107
expDataNames0.1140.0010.116
expDeleteDataTag0.0300.0030.033
expSetDataTag0.0230.0000.023
expTaggedData0.0230.0010.024
exportSCE0.0170.0030.020
exportSCEtoAnnData0.0920.0040.096
exportSCEtoFlatFile0.0910.0040.095
featureIndex0.0340.0010.035
generateSimulatedData0.0500.0110.061
getBiomarker0.0560.0050.061
getDEGTopTable0.6570.1000.757
getDiffAbundanceResults0.0470.0020.049
getEnrichRResult0.5240.0292.870
getFindMarkerTopTable1.5070.0741.582
getMSigDBTable0.0030.0010.005
getPathwayResultNames0.0220.0070.029
getSampleSummaryStatsTable0.1790.0080.187
getSoupX0.0000.0000.001
getTSCANResults0.9410.1001.041
getTopHVG0.810.010.82
importAnnData0.0020.0000.001
importBUStools0.1330.0020.135
importCellRanger0.7670.0090.777
importCellRangerV2Sample0.1330.0040.138
importCellRangerV3Sample0.2490.0060.256
importDropEst0.2030.0010.205
importExampleData11.192 1.58413.168
importGeneSetsFromCollection1.9050.1642.070
importGeneSetsFromGMT0.0670.0010.069
importGeneSetsFromList0.1190.0010.121
importGeneSetsFromMSigDB44.805 0.94645.755
importMitoGeneSet0.0500.0060.055
importOptimus0.0010.0010.002
importSEQC0.1410.0200.161
importSTARsolo0.1420.0300.173
iterateSimulations0.1790.0280.208
listSampleSummaryStatsTables0.2460.0400.285
mergeSCEColData0.3890.0130.401
mouseBrainSubsetSCE0.0350.0010.036
msigdb_table0.0010.0010.001
plotBarcodeRankDropsResults0.8500.0110.861
plotBarcodeRankScatter0.8740.0120.887
plotBatchCorrCompare12.546 0.12312.669
plotBatchVariance0.4600.0020.462
plotBcdsResults8.6200.1578.204
plotBubble0.7510.0140.765
plotClusterAbundance1.2700.0031.272
plotCxdsResults7.6170.0597.677
plotDEGHeatmap2.0530.0062.059
plotDEGRegression4.4880.0754.557
plotDEGViolin5.5000.0575.552
plotDEGVolcano0.9410.0050.947
plotDecontXResults11.804 0.06111.866
plotDimRed0.3000.0020.302
plotDoubletFinderResults40.406 0.33240.739
plotEmptyDropsResults6.7070.0106.717
plotEmptyDropsScatter6.6210.0116.631
plotFindMarkerHeatmap3.7660.0033.770
plotMASTThresholdGenes1.2700.0151.285
plotPCA0.3610.0050.366
plotPathway0.6850.0020.688
plotRunPerCellQCResults3.0570.0023.059
plotSCEBarAssayData0.2870.0010.288
plotSCEBarColData0.2720.0010.273
plotSCEBatchFeatureMean0.40.00.4
plotSCEDensity0.3070.0010.309
plotSCEDensityAssayData0.2750.0010.276
plotSCEDensityColData0.3470.0020.349
plotSCEDimReduceColData0.7020.0170.719
plotSCEDimReduceFeatures0.3720.0020.374
plotSCEHeatmap0.4470.0090.456
plotSCEScatter0.3380.0010.339
plotSCEViolin0.3470.0000.347
plotSCEViolinAssayData0.4010.0020.403
plotSCEViolinColData0.3300.0030.333
plotScDblFinderResults27.010 0.76024.834
plotScanpyDotPlot0.0220.0000.022
plotScanpyEmbedding0.0190.0020.021
plotScanpyHVG0.0210.0000.021
plotScanpyHeatmap0.0210.0000.021
plotScanpyMarkerGenes0.0210.0000.021
plotScanpyMarkerGenesDotPlot0.0200.0010.021
plotScanpyMarkerGenesHeatmap0.0210.0010.022
plotScanpyMarkerGenesMatrixPlot0.0190.0020.021
plotScanpyMarkerGenesViolin0.0190.0020.021
plotScanpyMatrixPlot0.0200.0010.021
plotScanpyPCA0.0210.0000.021
plotScanpyPCAGeneRanking0.0210.0000.021
plotScanpyPCAVariance0.0210.0000.021
plotScanpyViolin0.0210.0000.021
plotScdsHybridResults9.7190.0929.217
plotScrubletResults0.0220.0000.022
plotSeuratElbow0.0220.0000.022
plotSeuratHVG0.0200.0010.021
plotSeuratJackStraw0.0220.0000.022
plotSeuratReduction0.0220.0000.021
plotSoupXResults000
plotTSCANClusterDEG4.8150.0074.822
plotTSCANClusterPseudo1.3750.0051.381
plotTSCANDimReduceFeatures1.3440.0041.347
plotTSCANPseudotimeGenes1.6070.0041.611
plotTSCANPseudotimeHeatmap1.3220.0021.323
plotTSCANResults1.2430.0071.250
plotTSNE0.3620.0020.365
plotTopHVG0.6090.0010.611
plotUMAP7.5610.1527.714
readSingleCellMatrix0.0040.0010.005
reportCellQC0.0720.0030.076
reportDropletQC0.0220.0000.021
reportQCTool0.0750.0010.075
retrieveSCEIndex0.0260.0010.027
runBBKNN000
runBarcodeRankDrops0.2100.0010.212
runBcds1.5180.0030.934
runCellQC0.0810.0010.082
runClusterSummaryMetrics0.3860.0010.388
runComBatSeq0.4320.0050.437
runCxds0.3160.0020.318
runCxdsBcdsHybrid1.5020.0530.987
runDEAnalysis0.4590.0020.461
runDecontX7.2570.1037.360
runDimReduce0.2720.0010.273
runDoubletFinder34.858 0.13834.998
runDropletQC0.0220.0000.022
runEmptyDrops6.3170.0116.330
runEnrichR0.4520.1522.716
runFastMNN1.7370.2101.946
runFeatureSelection0.2120.0090.222
runFindMarker1.4510.1691.619
runGSVA0.7990.1310.930
runHarmony0.1290.0630.192
runKMeans0.1820.0180.199
runLimmaBC0.0800.0080.089
runMNNCorrect0.4040.0510.456
runModelGeneVar0.3010.0370.338
runNormalization2.7030.6313.345
runPerCellQC0.3180.0200.338
runSCANORAMA000
runSCMerge0.0020.0020.004
runScDblFinder16.520 1.36614.912
runScanpyFindClusters0.0220.0010.023
runScanpyFindHVG0.0210.0010.021
runScanpyFindMarkers0.0210.0000.021
runScanpyNormalizeData0.0890.0040.093
runScanpyPCA0.0220.0000.022
runScanpyScaleData0.0220.0000.022
runScanpyTSNE0.0220.0000.021
runScanpyUMAP0.0220.0000.022
runScranSNN0.2760.0100.286
runScrublet0.0210.0010.022
runSeuratFindClusters0.0210.0010.022
runSeuratFindHVG0.4450.0080.455
runSeuratHeatmap0.0190.0020.022
runSeuratICA0.0220.0000.022
runSeuratJackStraw0.0220.0000.022
runSeuratNormalizeData0.0210.0010.021
runSeuratPCA0.0200.0010.022
runSeuratSCTransform30.178 1.33231.512
runSeuratScaleData0.0210.0020.023
runSeuratUMAP0.0210.0010.022
runSingleR0.0370.0000.037
runSoupX0.0000.0000.001
runTSCAN0.6420.0020.645
runTSCANClusterDEAnalysis0.7460.0170.763
runTSCANDEG0.7250.0160.741
runTSNE0.7060.0020.708
runUMAP7.9030.1698.073
runVAM0.2800.0030.283
runZINBWaVE0.0040.0000.004
sampleSummaryStats0.1490.0000.150
scaterCPM0.1280.0080.136
scaterPCA0.4210.0100.432
scaterlogNormCounts0.2370.0080.245
sce0.0210.0010.021
sctkListGeneSetCollections0.0760.0020.078
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv0.0000.0000.001
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.0850.0030.088
setSCTKDisplayRow0.4200.0130.434
singleCellTK0.0000.0000.001
subDiffEx0.3160.0050.321
subsetSCECols0.0770.0010.078
subsetSCERows0.2470.0100.257
summarizeSCE0.0630.0010.064
trimCounts0.1960.0070.202