Multiple platform build/check report for BioC 3.21 - CHECK results for singleCellTK on merida1

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo1	Linux (Ubuntu 24.04.3 LTS)	x86_64	4.5.1 (2025-06-13) -- "Great Square Root"	4831
merida1	macOS 12.7.5 Monterey	x86_64	4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"	4612
kjohnson1	macOS 13.6.6 Ventura	arm64	4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"	4553
kunpeng2	Linux (openEuler 24.03 LTS)	aarch64	R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"	4584
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: 2.18.2

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_2.18.2.tar.gz

StartedAt: 2025-09-30 10:20:59 -0400 (Tue, 30 Sep 2025)

EndedAt: 2025-09-30 10:53:06 -0400 (Tue, 30 Sep 2025)

EllapsedTime: 1927.0 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_2.18.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.1 RC (2025-06-05 r88288)
* 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 ‘2.18.2’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 79 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
  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 91.735  0.793  93.956
plotDoubletFinderResults 56.741  0.269  59.346
plotScDblFinderResults   50.693  0.993  56.766
runDoubletFinder         47.009  0.196  48.383
runScDblFinder           34.060  0.451  34.899
importExampleData        22.555  2.216  31.984
plotBatchCorrCompare     19.404  0.181  19.982
plotScdsHybridResults    15.508  0.181  17.370
plotBcdsResults          14.607  0.228  15.054
plotDEGViolin            13.428  0.184  14.162
plotDecontXResults       13.405  0.097  13.553
plotTSCANClusterDEG      12.345  0.120  14.204
plotCxdsResults          11.997  0.115  12.260
plotDEGRegression        10.961  0.086  11.196
plotEmptyDropsResults    10.385  0.046  11.456
plotEmptyDropsScatter    10.299  0.050  11.677
plotFindMarkerHeatmap     9.857  0.057  11.004
convertSCEToSeurat        9.398  0.352  10.047
runDecontX                9.375  0.055   9.638
runEmptyDrops             9.333  0.030   9.437
runUMAP                   9.217  0.110   9.420
plotUMAP                  9.112  0.082   9.868
detectCellOutlier         7.696  0.169   8.067
plotRunPerCellQCResults   7.662  0.045   8.396
runSeuratSCTransform      7.030  0.081   7.146
plotDEGHeatmap            5.211  0.043   5.339
* 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-3.21-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 ‘2.18.2’
** 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 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
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 
  0.350   0.117   0.474

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
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: GenomeInfoDb
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
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Calculating gene variances
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
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[----|----|----|----|----|----|----|----|----|----|
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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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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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[----|----|----|----|----|----|----|----|----|----|
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Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 22 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 22 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
558.414  11.017 599.516

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.005	0.005	0.009
SEG	0.004	0.006	0.017
calcEffectSizes	0.471	0.036	0.526
combineSCE	1.742	0.025	1.957
computeZScore	0.423	0.020	0.460
convertSCEToSeurat	9.398	0.352	10.047
convertSeuratToSCE	0.698	0.009	0.709
dedupRowNames	0.117	0.005	0.125
detectCellOutlier	7.696	0.169	8.067
diffAbundanceFET	0.098	0.004	0.102
discreteColorPalette	0.011	0.001	0.011
distinctColors	0.004	0.000	0.006
downSampleCells	1.070	0.121	1.200
downSampleDepth	0.920	0.064	0.991
expData-ANY-character-method	0.281	0.008	0.291
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.362	0.008	0.371
expData-set	0.334	0.008	0.345
expData	0.284	0.010	0.299
expDataNames-ANY-method	0.277	0.012	0.292
expDataNames	0.284	0.032	0.322
expDeleteDataTag	0.064	0.006	0.070
expSetDataTag	0.046	0.003	0.049
expTaggedData	0.049	0.004	0.054
exportSCE	0.044	0.008	0.051
exportSCEtoAnnData	0.122	0.011	0.134
exportSCEtoFlatFile	0.120	0.010	0.131
featureIndex	0.075	0.010	0.085
generateSimulatedData	0.099	0.012	0.110
getBiomarker	0.120	0.014	0.135
getDEGTopTable	1.610	0.122	1.746
getDiffAbundanceResults	0.088	0.004	0.091
getEnrichRResult	0.697	0.054	2.999
getFindMarkerTopTable	3.476	0.087	3.617
getMSigDBTable	0.007	0.006	0.014
getPathwayResultNames	0.039	0.005	0.046
getSampleSummaryStatsTable	0.405	0.007	0.414
getSoupX	0	0	0
getTSCANResults	2.309	0.061	2.382
getTopHVG	1.795	0.025	1.834
importAnnData	0.002	0.001	0.004
importBUStools	0.352	0.007	0.363
importCellRanger	1.754	0.052	1.867
importCellRangerV2Sample	0.345	0.004	0.355
importCellRangerV3Sample	0.646	0.021	0.671
importDropEst	0.463	0.006	0.473
importExampleData	22.555	2.216	31.984
importGeneSetsFromCollection	1.670	0.143	1.837
importGeneSetsFromGMT	0.141	0.008	0.153
importGeneSetsFromList	0.289	0.018	0.314
importGeneSetsFromMSigDB	91.735	0.793	93.956
importMitoGeneSet	0.107	0.016	0.123
importOptimus	0.003	0.001	0.004
importSEQC	0.326	0.027	0.356
importSTARsolo	0.388	0.046	0.447
iterateSimulations	0.399	0.047	0.468
listSampleSummaryStatsTables	0.581	0.065	0.738
mergeSCEColData	0.905	0.124	1.309
mouseBrainSubsetSCE	0.064	0.007	0.071
msigdb_table	0.002	0.004	0.007
plotBarcodeRankDropsResults	2.023	0.048	2.133
plotBarcodeRankScatter	2.073	0.022	2.111
plotBatchCorrCompare	19.404	0.181	19.982
plotBatchVariance	1.121	0.029	1.152
plotBcdsResults	14.607	0.228	15.054
plotBubble	1.915	0.019	1.948
plotClusterAbundance	3.485	0.017	3.518
plotCxdsResults	11.997	0.115	12.260
plotDEGHeatmap	5.211	0.043	5.339
plotDEGRegression	10.961	0.086	11.196
plotDEGViolin	13.428	0.184	14.162
plotDEGVolcano	2.093	0.019	2.126
plotDecontXResults	13.405	0.097	13.553
plotDimRed	0.639	0.008	0.689
plotDoubletFinderResults	56.741	0.269	59.346
plotEmptyDropsResults	10.385	0.046	11.456
plotEmptyDropsScatter	10.299	0.050	11.677
plotFindMarkerHeatmap	9.857	0.057	11.004
plotMASTThresholdGenes	3.145	0.048	3.649
plotPCA	0.967	0.018	1.065
plotPathway	1.591	0.019	1.789
plotRunPerCellQCResults	7.662	0.045	8.396
plotSCEBarAssayData	0.651	0.012	0.874
plotSCEBarColData	0.558	0.012	0.660
plotSCEBatchFeatureMean	0.969	0.010	1.053
plotSCEDensity	0.752	0.012	0.851
plotSCEDensityAssayData	0.706	0.010	0.840
plotSCEDensityColData	0.724	0.010	0.814
plotSCEDimReduceColData	1.821	0.018	2.006
plotSCEDimReduceFeatures	1.005	0.013	1.108
plotSCEHeatmap	0.992	0.010	1.089
plotSCEScatter	0.865	0.013	0.955
plotSCEViolin	0.965	0.012	1.067
plotSCEViolinAssayData	0.900	0.011	1.008
plotSCEViolinColData	0.883	0.012	0.983
plotScDblFinderResults	50.693	0.993	56.766
plotScanpyDotPlot	0.040	0.006	0.052
plotScanpyEmbedding	0.042	0.006	0.053
plotScanpyHVG	0.042	0.004	0.053
plotScanpyHeatmap	0.040	0.007	0.050
plotScanpyMarkerGenes	0.039	0.005	0.051
plotScanpyMarkerGenesDotPlot	0.040	0.004	0.048
plotScanpyMarkerGenesHeatmap	0.040	0.004	0.048
plotScanpyMarkerGenesMatrixPlot	0.040	0.005	0.052
plotScanpyMarkerGenesViolin	0.041	0.005	0.048
plotScanpyMatrixPlot	0.041	0.005	0.050
plotScanpyPCA	0.040	0.005	0.048
plotScanpyPCAGeneRanking	0.040	0.004	0.047
plotScanpyPCAVariance	0.040	0.005	0.049
plotScanpyViolin	0.041	0.005	0.053
plotScdsHybridResults	15.508	0.181	17.370
plotScrubletResults	0.039	0.005	0.051
plotSeuratElbow	0.038	0.005	0.049
plotSeuratHVG	0.039	0.005	0.050
plotSeuratJackStraw	0.038	0.007	0.051
plotSeuratReduction	0.040	0.005	0.055
plotSoupXResults	0.001	0.001	0.001
plotTSCANClusterDEG	12.345	0.120	14.204
plotTSCANClusterPseudo	3.348	0.035	3.805
plotTSCANDimReduceFeatures	3.357	0.035	3.787
plotTSCANPseudotimeGenes	4.147	0.034	4.529
plotTSCANPseudotimeHeatmap	3.115	0.035	3.408
plotTSCANResults	3.075	0.033	3.340
plotTSNE	0.903	0.014	1.009
plotTopHVG	1.461	0.023	1.594
plotUMAP	9.112	0.082	9.868
readSingleCellMatrix	0.010	0.001	0.011
reportCellQC	0.176	0.009	0.194
reportDropletQC	0.042	0.007	0.050
reportQCTool	0.175	0.008	0.197
retrieveSCEIndex	0.051	0.004	0.060
runBBKNN	0.000	0.001	0.001
runBarcodeRankDrops	0.456	0.009	0.487
runBcds	3.372	0.051	3.607
runCellQC	0.174	0.009	0.189
runClusterSummaryMetrics	0.890	0.015	0.955
runComBatSeq	0.994	0.023	1.068
runCxds	0.695	0.019	0.749
runCxdsBcdsHybrid	3.419	0.121	3.591
runDEAnalysis	0.937	0.068	1.024
runDecontX	9.375	0.055	9.638
runDimReduce	0.633	0.010	0.673
runDoubletFinder	47.009	0.196	48.383
runDropletQC	0.039	0.005	0.043
runEmptyDrops	9.333	0.030	9.437
runEnrichR	0.636	0.047	2.744
runFastMNN	3.975	0.060	4.075
runFeatureSelection	0.447	0.006	0.457
runFindMarker	3.199	0.043	3.261
runGSVA	1.522	0.055	1.588
runHarmony	0.088	0.002	0.091
runKMeans	0.514	0.022	0.547
runLimmaBC	0.181	0.002	0.186
runMNNCorrect	0.886	0.006	0.898
runModelGeneVar	0.695	0.008	0.707
runNormalization	3.604	0.053	3.862
runPerCellQC	0.743	0.014	0.759
runSCANORAMA	0.000	0.001	0.001
runSCMerge	0.008	0.002	0.009
runScDblFinder	34.060	0.451	34.899
runScanpyFindClusters	0.038	0.005	0.043
runScanpyFindHVG	0.038	0.006	0.044
runScanpyFindMarkers	0.038	0.004	0.041
runScanpyNormalizeData	0.212	0.008	0.222
runScanpyPCA	0.038	0.003	0.041
runScanpyScaleData	0.039	0.004	0.043
runScanpyTSNE	0.038	0.004	0.043
runScanpyUMAP	0.039	0.006	0.045
runScranSNN	0.615	0.016	0.633
runScrublet	0.040	0.005	0.045
runSeuratFindClusters	0.042	0.003	0.045
runSeuratFindHVG	1.016	0.015	1.034
runSeuratHeatmap	0.039	0.007	0.047
runSeuratICA	0.039	0.004	0.043
runSeuratJackStraw	0.038	0.008	0.047
runSeuratNormalizeData	0.035	0.006	0.040
runSeuratPCA	0.039	0.005	0.044
runSeuratSCTransform	7.030	0.081	7.146
runSeuratScaleData	0.040	0.002	0.042
runSeuratUMAP	0.039	0.005	0.045
runSingleR	0.085	0.005	0.093
runSoupX	0.000	0.001	0.001
runTSCAN	1.531	0.019	1.591
runTSCANClusterDEAnalysis	1.765	0.053	1.835
runTSCANDEG	1.777	0.046	1.844
runTSNE	1.294	0.014	1.324
runUMAP	9.217	0.110	9.420
runVAM	0.696	0.011	0.745
runZINBWaVE	0.007	0.002	0.010
sampleSummaryStats	0.367	0.008	0.401
scaterCPM	0.211	0.007	0.224
scaterPCA	1.077	0.015	1.199
scaterlogNormCounts	0.447	0.011	0.527
sce	0.043	0.009	0.071
sctkListGeneSetCollections	0.174	0.012	0.274
sctkPythonInstallConda	0	0	0
sctkPythonInstallVirtualEnv	0.000	0.000	0.001
selectSCTKConda	0.001	0.001	0.000
selectSCTKVirtualEnvironment	0.000	0.000	0.001
setRowNames	0.188	0.007	0.234
setSCTKDisplayRow	1.016	0.017	1.213
singleCellTK	0.000	0.001	0.001
subDiffEx	0.665	0.032	0.700
subsetSCECols	0.175	0.010	0.189
subsetSCERows	0.565	0.028	0.604
summarizeSCE	0.131	0.010	0.144
trimCounts	0.331	0.013	0.345