Back to Multiple platform build/check report for BioC 3.23:   simplified   long
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This page was generated on 2025-11-19 10:14 -0500 (Wed, 19 Nov 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.3 LTS)x86_64R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences" 4827
lconwaymacOS 12.7.6 Montereyx86_64R Under development (unstable) (2025-10-21 r88958) -- "Unsuffered Consequences" 4600
kjohnson3macOS 13.7.7 Venturaarm64R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" 4564
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 2001/2325HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.21.0  (landing page)
Joshua David Campbell
Snapshot Date: 2025-11-18 13:40 -0500 (Tue, 18 Nov 2025)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: devel
git_last_commit: 4895b66
git_last_commit_date: 2025-10-29 11:29:49 -0500 (Wed, 29 Oct 2025)
nebbiolo1Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
lconwaymacOS 12.7.6 Monterey / x86_64  OK    OK    OK    OK  NO, package depends on 'batchelor' which is only available as a source package that needs compilation
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 lconway

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: 2.21.0
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.21.0.tar.gz
StartedAt: 2025-11-19 00:09:11 -0500 (Wed, 19 Nov 2025)
EndedAt: 2025-11-19 00:30:18 -0500 (Wed, 19 Nov 2025)
EllapsedTime: 1266.9 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.21.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck’
* using R Under development (unstable) (2025-10-21 r88958)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.8
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.21.0’
* 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  6.8Mb
  sub-directories of 1Mb or more:
    R         1.0Mb
    extdata   1.5Mb
    shiny     2.9Mb
* 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 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 49.966  0.658  51.306
plotDoubletFinderResults 40.957  0.378  41.741
runDoubletFinder         36.973  0.219  37.349
plotScDblFinderResults   30.384  0.949  32.041
runScDblFinder           20.830  0.473  21.405
importExampleData        15.240  2.636 128.734
plotBatchCorrCompare     14.187  0.174  14.493
plotScdsHybridResults    10.824  0.151  11.027
plotBcdsResults           9.675  0.209  10.053
plotDecontXResults        9.641  0.104   9.842
plotCxdsResults           8.372  0.102   8.533
runUMAP                   8.088  0.077   8.195
runDecontX                7.630  0.062   7.714
plotUMAP                  7.583  0.081   7.698
plotDEGViolin             6.203  0.123   6.380
plotEmptyDropsResults     6.168  0.051   6.267
plotEmptyDropsScatter     5.932  0.045   6.018
runEmptyDrops             5.907  0.033   5.972
plotTSCANClusterDEG       5.723  0.095   5.842
detectCellOutlier         5.637  0.161   6.075
convertSCEToSeurat        5.071  0.325   5.459
plotDEGRegression         5.293  0.092   5.442
getEnrichRResult          0.326  0.048   5.028
* 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 running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.


Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.6-x86_64/Resources/library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.21.0’
** 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) (2025-10-21 r88958) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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 
  0.197   0.090   0.300 

singleCellTK.Rcheck/tests/testthat.Rout


R Under development (unstable) (2025-10-21 r88958) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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  |======================================================================| 100%
Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
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  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
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  |======================================================================| 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 21 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
331.171   7.581 357.334 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0020.0030.005
SEG0.0030.0040.007
calcEffectSizes0.1750.0170.194
combineSCE0.8110.0360.853
computeZScore0.2320.0150.384
convertSCEToSeurat5.0710.3255.459
convertSeuratToSCE0.3350.0100.346
dedupRowNames0.0630.0040.068
detectCellOutlier5.6370.1616.075
diffAbundanceFET0.0650.0040.070
discreteColorPalette0.0070.0010.007
distinctColors0.0030.0010.003
downSampleCells0.5430.0700.619
downSampleDepth0.4800.1160.675
expData-ANY-character-method0.1440.0070.152
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1780.0080.187
expData-set0.1630.0070.174
expData0.1470.0070.156
expDataNames-ANY-method0.1310.0070.141
expDataNames0.1310.0140.145
expDeleteDataTag0.0410.0050.045
expSetDataTag0.0320.0030.035
expTaggedData0.0310.0050.037
exportSCE0.0290.0060.034
exportSCEtoAnnData0.0650.0030.091
exportSCEtoFlatFile0.0670.0040.073
featureIndex0.0390.0080.049
generateSimulatedData0.0600.0060.067
getBiomarker0.0710.0080.080
getDEGTopTable0.7910.1000.904
getDiffAbundanceResults0.0570.0050.063
getEnrichRResult0.3260.0485.028
getFindMarkerTopTable1.6600.0481.722
getMSigDBTable0.0040.0050.008
getPathwayResultNames0.0290.0050.035
getSampleSummaryStatsTable0.2170.0060.227
getSoupX000
getTSCANResults1.1700.0581.247
getTopHVG0.8530.0170.880
importAnnData0.0020.0000.002
importBUStools0.2040.0120.299
importCellRanger0.8100.0381.181
importCellRangerV2Sample0.1560.0030.161
importCellRangerV3Sample0.4150.0180.523
importDropEst0.2270.0050.327
importExampleData 15.240 2.636128.734
importGeneSetsFromCollection0.8090.1350.955
importGeneSetsFromGMT0.0730.0070.104
importGeneSetsFromList0.1370.0070.164
importGeneSetsFromMSigDB49.966 0.65851.306
importMitoGeneSet0.0600.0090.070
importOptimus0.0010.0000.002
importSEQC0.1500.0040.232
importSTARsolo0.1730.0040.225
iterateSimulations0.2020.0100.214
listSampleSummaryStatsTables0.2760.0080.287
mergeSCEColData0.3540.0240.466
mouseBrainSubsetSCE0.0400.0050.045
msigdb_table0.0010.0030.005
plotBarcodeRankDropsResults2.5680.0642.648
plotBarcodeRankScatter1.0120.0691.094
plotBatchCorrCompare14.187 0.17414.493
plotBatchVariance0.5410.0140.562
plotBcdsResults 9.675 0.20910.053
plotBubble0.9140.0170.965
plotClusterAbundance1.4830.0171.512
plotCxdsResults8.3720.1028.533
plotDEGHeatmap2.4810.0452.546
plotDEGRegression5.2930.0925.442
plotDEGViolin6.2030.1236.380
plotDEGVolcano1.0230.0211.053
plotDecontXResults9.6410.1049.842
plotDimRed0.3050.0080.430
plotDoubletFinderResults40.957 0.37841.741
plotEmptyDropsResults6.1680.0516.267
plotEmptyDropsScatter5.9320.0456.018
plotFindMarkerHeatmap4.5720.0534.672
plotMASTThresholdGenes1.4430.0401.499
plotPCA0.4190.0110.461
plotPathway0.8280.0161.051
plotRunPerCellQCResults3.7580.0443.839
plotSCEBarAssayData0.3740.0080.384
plotSCEBarColData0.2510.0060.261
plotSCEBatchFeatureMean0.4360.0060.445
plotSCEDensity0.3450.0080.355
plotSCEDensityAssayData0.3020.0090.313
plotSCEDensityColData0.3850.0070.394
plotSCEDimReduceColData0.8340.0160.857
plotSCEDimReduceFeatures0.4610.0090.473
plotSCEHeatmap0.4760.0070.487
plotSCEScatter0.4250.0120.441
plotSCEViolin0.5350.0110.555
plotSCEViolinAssayData0.4810.0110.499
plotSCEViolinColData0.4160.0100.429
plotScDblFinderResults30.384 0.94932.041
plotScanpyDotPlot0.0260.0060.032
plotScanpyEmbedding0.0270.0030.031
plotScanpyHVG0.0270.0030.031
plotScanpyHeatmap0.0250.0030.027
plotScanpyMarkerGenes0.0240.0040.029
plotScanpyMarkerGenesDotPlot0.0320.0050.037
plotScanpyMarkerGenesHeatmap0.0280.0040.032
plotScanpyMarkerGenesMatrixPlot0.0270.0030.031
plotScanpyMarkerGenesViolin0.0250.0050.030
plotScanpyMatrixPlot0.0240.0040.028
plotScanpyPCA0.0260.0030.030
plotScanpyPCAGeneRanking0.0280.0040.032
plotScanpyPCAVariance0.0270.0040.030
plotScanpyViolin0.0290.0030.031
plotScdsHybridResults10.824 0.15111.027
plotScrubletResults0.0290.0050.033
plotSeuratElbow0.0250.0050.031
plotSeuratHVG0.0240.0030.028
plotSeuratJackStraw0.0260.0030.029
plotSeuratReduction0.0270.0020.028
plotSoupXResults000
plotTSCANClusterDEG5.7230.0955.842
plotTSCANClusterPseudo1.6160.0311.653
plotTSCANDimReduceFeatures1.6310.0281.667
plotTSCANPseudotimeGenes1.7650.0231.793
plotTSCANPseudotimeHeatmap1.4350.0211.461
plotTSCANResults1.4530.0321.494
plotTSNE0.4790.0130.493
plotTopHVG0.7290.0180.752
plotUMAP7.5830.0817.698
readSingleCellMatrix0.0060.0010.008
reportCellQC0.1080.0070.117
reportDropletQC0.0330.0040.038
reportQCTool0.1010.0050.107
retrieveSCEIndex0.0390.0050.044
runBBKNN000
runBarcodeRankDrops0.2630.0080.273
runBcds1.7480.0341.789
runCellQC0.0900.0050.096
runClusterSummaryMetrics0.4430.0110.456
runComBatSeq0.4690.0200.500
runCxds0.3500.0080.360
runCxdsBcdsHybrid1.7960.0741.877
runDEAnalysis0.4850.0610.549
runDecontX7.6300.0627.714
runDimReduce0.3220.0090.332
runDoubletFinder36.973 0.21937.349
runDropletQC0.0310.0030.034
runEmptyDrops5.9070.0335.972
runEnrichR0.3070.0344.906
runFastMNN1.8080.0551.895
runFeatureSelection0.2400.0060.248
runFindMarker1.6750.0451.736
runGSVA0.8340.0530.895
runHarmony0.0540.0020.055
runKMeans0.3340.0230.358
runLimmaBC0.1050.0030.108
runMNNCorrect0.4890.0070.500
runModelGeneVar0.3490.0080.359
runNormalization2.5570.0332.600
runPerCellQC0.3900.0120.402
runSCANORAMA0.0000.0010.001
runSCMerge0.0040.0020.010
runScDblFinder20.830 0.47321.405
runScanpyFindClusters0.0260.0040.030
runScanpyFindHVG0.0250.0020.028
runScanpyFindMarkers0.0340.0060.040
runScanpyNormalizeData0.1170.0070.126
runScanpyPCA0.0290.0050.034
runScanpyScaleData0.0280.0040.033
runScanpyTSNE0.0230.0040.026
runScanpyUMAP0.0280.0060.034
runScranSNN0.3530.0170.373
runScrublet0.0290.0070.036
runSeuratFindClusters0.0290.0040.032
runSeuratFindHVG0.5750.0130.591
runSeuratHeatmap0.0280.0040.033
runSeuratICA0.0280.0040.032
runSeuratJackStraw0.0270.0020.029
runSeuratNormalizeData0.0320.0030.036
runSeuratPCA0.0300.0040.035
runSeuratSCTransform4.2930.1064.476
runSeuratScaleData0.0250.0030.029
runSeuratUMAP0.0300.0030.032
runSingleR0.0480.0040.052
runSoupX0.0010.0000.000
runTSCAN0.8100.0190.833
runTSCANClusterDEAnalysis0.9540.0320.991
runTSCANDEG0.8830.0300.916
runTSNE0.6590.0200.682
runUMAP8.0880.0778.195
runVAM0.3540.0110.366
runZINBWaVE0.0040.0020.006
sampleSummaryStats0.2000.0080.208
scaterCPM0.1220.0060.130
scaterPCA0.5530.0100.566
scaterlogNormCounts0.2270.0080.236
sce0.0250.0050.032
sctkListGeneSetCollections0.1020.0080.112
sctkPythonInstallConda0.0000.0000.001
sctkPythonInstallVirtualEnv0.0000.0000.001
selectSCTKConda0.0000.0000.001
selectSCTKVirtualEnvironment0.0000.0010.001
setRowNames0.0980.0050.104
setSCTKDisplayRow0.5070.0100.519
singleCellTK0.0000.0010.000
subDiffEx0.4060.0280.438
subsetSCECols0.0840.0080.093
subsetSCERows0.3110.0260.340
summarizeSCE0.0840.0080.092
trimCounts0.2080.0120.220