Multiple platform build/check report for BioC 3.22 - CHECK results for singleCellTK on merida1

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo2	Linux (Ubuntu 24.04.3 LTS)	x86_64	4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"	4615
merida1	macOS 12.7.6 Monterey	x86_64	4.5.2 Patched (2025-11-05 r88990) -- "[Not] Part in a Rumble"	4610
kjohnson1	macOS 13.7.5 Ventura	arm64	4.5.2 Patched (2025-11-04 r88984) -- "[Not] Part in a Rumble"	4598
taishan	Linux (openEuler 24.03 LTS)	aarch64	4.5.0 (2025-04-11) -- "How About a Twenty-Six"	4668
Click on any hostname to see more info about the system (e.g. compilers) () as reported by 'uname -p', except on Windows and Mac OS X*

CHECK results for singleCellTK on merida1

To the developers/maintainers of the singleCellTK package:
- Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/singleCellTK.git to reflect on this report. See Troubleshooting Build Report for more information.
- Use the following Renviron settings to reproduce errors and warnings.
- If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information.

raw results

Summary

Package: singleCellTK

Version: 2.20.0

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_2.20.0.tar.gz

StartedAt: 2025-11-18 14:50:20 -0500 (Tue, 18 Nov 2025)

EndedAt: 2025-11-18 15:21:54 -0500 (Tue, 18 Nov 2025)

EllapsedTime: 1894.3 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_2.20.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.2 Patched (2025-11-05 r88990)
* 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 Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.20.0’
* 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 97.704  0.734  98.773
plotDoubletFinderResults 54.480  0.287  56.656
plotScDblFinderResults   51.395  1.048  54.574
runDoubletFinder         46.623  0.158  47.297
runScDblFinder           33.987  0.474  34.728
importExampleData        21.645  2.742  26.348
plotBatchCorrCompare     19.154  0.192  19.464
plotScdsHybridResults    15.377  0.200  16.757
plotBcdsResults          13.959  0.257  14.283
plotDecontXResults       13.715  0.107  14.554
plotDEGViolin            12.993  0.164  13.697
plotDEGRegression        12.133  0.080  12.253
plotTSCANClusterDEG      11.841  0.113  11.992
plotCxdsResults          11.741  0.080  12.014
plotEmptyDropsResults    10.370  0.042  10.716
plotEmptyDropsScatter    10.225  0.041  10.852
plotFindMarkerHeatmap     9.783  0.047  10.145
convertSCEToSeurat        9.282  0.372   9.793
runUMAP                   9.550  0.099   9.748
runEmptyDrops             9.487  0.030   9.710
plotUMAP                  9.169  0.100   9.714
runDecontX                9.195  0.067   9.336
detectCellOutlier         8.066  0.152   8.366
plotRunPerCellQCResults   7.641  0.037   7.902
runSeuratSCTransform      7.063  0.080   7.274
plotDEGHeatmap            5.045  0.037   5.118
getEnrichRResult          0.699  0.060   8.590
* 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-3.22-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/4.5-x86_64/Resources/library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.20.0’
** 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 version 4.5.2 Patched (2025-11-05 r88990) -- "[Not] Part in a Rumble"
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 
  0.353   0.119   0.435

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.2 Patched (2025-11-05 r88990) -- "[Not] Part in a Rumble"
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
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%
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%
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  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 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 
551.085  10.272 583.652

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.004	0.005	0.010
SEG	0.004	0.005	0.010
calcEffectSizes	0.453	0.023	0.478
combineSCE	1.671	0.026	1.703
computeZScore	0.415	0.019	0.455
convertSCEToSeurat	9.282	0.372	9.793
convertSeuratToSCE	0.741	0.013	0.761
dedupRowNames	0.114	0.004	0.120
detectCellOutlier	8.066	0.152	8.366
diffAbundanceFET	0.096	0.006	0.125
discreteColorPalette	0.010	0.001	0.012
distinctColors	0.004	0.000	0.004
downSampleCells	1.065	0.127	1.233
downSampleDepth	0.881	0.059	0.950
expData-ANY-character-method	0.275	0.008	0.283
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.356	0.008	0.367
expData-set	0.336	0.008	0.346
expData	0.284	0.007	0.298
expDataNames-ANY-method	0.270	0.016	0.307
expDataNames	0.272	0.028	0.309
expDeleteDataTag	0.059	0.007	0.067
expSetDataTag	0.044	0.003	0.069
expTaggedData	0.044	0.004	0.049
exportSCE	0.039	0.007	0.069
exportSCEtoAnnData	0.122	0.007	0.145
exportSCEtoFlatFile	0.118	0.009	0.128
featureIndex	0.070	0.011	0.081
generateSimulatedData	0.095	0.010	0.106
getBiomarker	0.116	0.016	0.134
getDEGTopTable	1.664	0.137	1.818
getDiffAbundanceResults	0.089	0.004	0.092
getEnrichRResult	0.699	0.060	8.590
getFindMarkerTopTable	3.349	0.098	3.505
getMSigDBTable	0.008	0.008	0.016
getPathwayResultNames	0.039	0.006	0.048
getSampleSummaryStatsTable	0.413	0.014	0.438
getSoupX	0.000	0.001	0.001
getTSCANResults	2.309	0.075	2.418
getTopHVG	1.797	0.026	1.839
importAnnData	0.003	0.001	0.004
importBUStools	0.351	0.006	0.368
importCellRanger	1.704	0.053	1.804
importCellRangerV2Sample	0.333	0.004	0.365
importCellRangerV3Sample	0.634	0.021	0.660
importDropEst	0.438	0.006	0.445
importExampleData	21.645	2.742	26.348
importGeneSetsFromCollection	2.994	0.161	3.173
importGeneSetsFromGMT	0.133	0.009	0.144
importGeneSetsFromList	0.293	0.007	0.301
importGeneSetsFromMSigDB	97.704	0.734	98.773
importMitoGeneSet	0.111	0.015	0.129
importOptimus	0.003	0.001	0.003
importSEQC	0.319	0.021	0.354
importSTARsolo	0.355	0.037	0.392
iterateSimulations	0.386	0.040	0.427
listSampleSummaryStatsTables	0.611	0.068	0.680
mergeSCEColData	0.832	0.053	0.887
mouseBrainSubsetSCE	0.061	0.006	0.068
msigdb_table	0.002	0.003	0.005
plotBarcodeRankDropsResults	1.981	0.043	2.027
plotBarcodeRankScatter	2.123	0.026	2.225
plotBatchCorrCompare	19.154	0.192	19.464
plotBatchVariance	1.194	0.022	1.254
plotBcdsResults	13.959	0.257	14.283
plotBubble	1.800	0.019	1.824
plotClusterAbundance	3.299	0.015	3.377
plotCxdsResults	11.741	0.080	12.014
plotDEGHeatmap	5.045	0.037	5.118
plotDEGRegression	12.133	0.080	12.253
plotDEGViolin	12.993	0.164	13.697
plotDEGVolcano	2.020	0.019	2.052
plotDecontXResults	13.715	0.107	14.554
plotDimRed	0.686	0.012	0.788
plotDoubletFinderResults	54.480	0.287	56.656
plotEmptyDropsResults	10.370	0.042	10.716
plotEmptyDropsScatter	10.225	0.041	10.852
plotFindMarkerHeatmap	9.783	0.047	10.145
plotMASTThresholdGenes	3.172	0.040	3.402
plotPCA	0.882	0.015	0.967
plotPathway	1.657	0.017	1.789
plotRunPerCellQCResults	7.641	0.037	7.902
plotSCEBarAssayData	0.735	0.012	0.787
plotSCEBarColData	0.555	0.010	0.567
plotSCEBatchFeatureMean	0.996	0.006	1.009
plotSCEDensity	0.755	0.010	0.767
plotSCEDensityAssayData	0.731	0.010	0.744
plotSCEDensityColData	0.717	0.010	0.732
plotSCEDimReduceColData	1.944	0.024	1.991
plotSCEDimReduceFeatures	0.911	0.011	0.929
plotSCEHeatmap	1.002	0.010	1.028
plotSCEScatter	0.894	0.011	0.911
plotSCEViolin	0.971	0.011	0.993
plotSCEViolinAssayData	0.942	0.013	0.963
plotSCEViolinColData	0.871	0.013	0.894
plotScDblFinderResults	51.395	1.048	54.574
plotScanpyDotPlot	0.039	0.005	0.044
plotScanpyEmbedding	0.039	0.004	0.044
plotScanpyHVG	0.039	0.005	0.045
plotScanpyHeatmap	0.038	0.005	0.043
plotScanpyMarkerGenes	0.038	0.005	0.044
plotScanpyMarkerGenesDotPlot	0.038	0.004	0.043
plotScanpyMarkerGenesHeatmap	0.038	0.005	0.043
plotScanpyMarkerGenesMatrixPlot	0.039	0.005	0.044
plotScanpyMarkerGenesViolin	0.038	0.004	0.042
plotScanpyMatrixPlot	0.039	0.004	0.042
plotScanpyPCA	0.040	0.004	0.044
plotScanpyPCAGeneRanking	0.038	0.004	0.042
plotScanpyPCAVariance	0.039	0.003	0.042
plotScanpyViolin	0.040	0.003	0.043
plotScdsHybridResults	15.377	0.200	16.757
plotScrubletResults	0.040	0.005	0.046
plotSeuratElbow	0.040	0.005	0.045
plotSeuratHVG	0.039	0.006	0.045
plotSeuratJackStraw	0.040	0.004	0.044
plotSeuratReduction	0.039	0.003	0.043
plotSoupXResults	0.000	0.001	0.001
plotTSCANClusterDEG	11.841	0.113	11.992
plotTSCANClusterPseudo	3.183	0.032	3.223
plotTSCANDimReduceFeatures	3.301	0.032	3.348
plotTSCANPseudotimeGenes	4.162	0.036	4.331
plotTSCANPseudotimeHeatmap	3.055	0.029	3.132
plotTSCANResults	3.010	0.028	3.059
plotTSNE	0.889	0.013	0.906
plotTopHVG	1.440	0.025	1.486
plotUMAP	9.169	0.100	9.714
readSingleCellMatrix	0.010	0.001	0.012
reportCellQC	0.181	0.008	0.192
reportDropletQC	0.042	0.004	0.046
reportQCTool	0.187	0.006	0.194
retrieveSCEIndex	0.057	0.006	0.065
runBBKNN	0.001	0.000	0.001
runBarcodeRankDrops	0.481	0.008	0.492
runBcds	3.413	0.053	3.485
runCellQC	0.179	0.006	0.186
runClusterSummaryMetrics	0.897	0.021	0.923
runComBatSeq	0.981	0.027	1.015
runCxds	0.711	0.027	0.742
runCxdsBcdsHybrid	3.438	0.108	3.573
runDEAnalysis	0.907	0.061	1.005
runDecontX	9.195	0.067	9.336
runDimReduce	0.637	0.009	0.659
runDoubletFinder	46.623	0.158	47.297
runDropletQC	0.040	0.005	0.044
runEmptyDrops	9.487	0.030	9.710
runEnrichR	0.644	0.044	2.717
runFastMNN	3.972	0.087	4.083
runFeatureSelection	0.451	0.007	0.460
runFindMarker	3.208	0.041	3.283
runGSVA	1.544	0.049	1.605
runHarmony	0.091	0.002	0.093
runKMeans	0.500	0.027	0.529
runLimmaBC	0.182	0.002	0.186
runMNNCorrect	0.878	0.006	0.890
runModelGeneVar	0.669	0.008	0.680
runNormalization	3.542	0.056	3.620
runPerCellQC	0.740	0.013	0.756
runSCANORAMA	0.000	0.000	0.001
runSCMerge	0.007	0.002	0.008
runScDblFinder	33.987	0.474	34.728
runScanpyFindClusters	0.042	0.005	0.048
runScanpyFindHVG	0.042	0.007	0.050
runScanpyFindMarkers	0.039	0.007	0.046
runScanpyNormalizeData	0.221	0.007	0.227
runScanpyPCA	0.038	0.006	0.044
runScanpyScaleData	0.040	0.003	0.044
runScanpyTSNE	0.042	0.005	0.048
runScanpyUMAP	0.045	0.011	0.055
runScranSNN	0.642	0.015	0.661
runScrublet	0.042	0.005	0.047
runSeuratFindClusters	0.041	0.003	0.044
runSeuratFindHVG	1.046	0.016	1.071
runSeuratHeatmap	0.040	0.007	0.047
runSeuratICA	0.042	0.004	0.046
runSeuratJackStraw	0.041	0.006	0.048
runSeuratNormalizeData	0.043	0.006	0.050
runSeuratPCA	0.041	0.008	0.050
runSeuratSCTransform	7.063	0.080	7.274
runSeuratScaleData	0.040	0.007	0.047
runSeuratUMAP	0.041	0.006	0.049
runSingleR	0.083	0.005	0.089
runSoupX	0.000	0.001	0.000
runTSCAN	1.522	0.021	1.592
runTSCANClusterDEAnalysis	1.712	0.024	1.742
runTSCANDEG	1.683	0.030	1.725
runTSNE	1.312	0.023	1.354
runUMAP	9.550	0.099	9.748
runVAM	0.699	0.009	0.733
runZINBWaVE	0.007	0.002	0.009
sampleSummaryStats	0.356	0.009	0.366
scaterCPM	0.217	0.008	0.225
scaterPCA	1.025	0.011	1.042
scaterlogNormCounts	0.442	0.008	0.451
sce	0.042	0.007	0.053
sctkListGeneSetCollections	0.177	0.009	0.187
sctkPythonInstallConda	0.001	0.000	0.001
sctkPythonInstallVirtualEnv	0.000	0.001	0.001
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0.001	0.001	0.001
setRowNames	0.193	0.006	0.199
setSCTKDisplayRow	1.021	0.024	1.050
singleCellTK	0.000	0.001	0.002
subDiffEx	0.671	0.044	0.721
subsetSCECols	0.181	0.020	0.202
subsetSCERows	0.584	0.028	0.613
summarizeSCE	0.137	0.009	0.147
trimCounts	0.338	0.015	0.353