| Back to Multiple platform build/check report for BioC 3.21: simplified long | 
 | 
This page was generated on 2025-10-16 11:39 -0400 (Thu, 16 Oct 2025).
| 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" | 4833 | 
| merida1 | macOS 12.7.6 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4614 | 
| kjohnson1 | macOS 13.7.5 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4555 | 
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4586 | 
| 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 2013/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| singleCellTK 2.18.2  (landing page) Joshua David Campbell 
 | nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| merida1 | macOS 12.7.6 Monterey / x86_64 | OK | OK | OK | OK |  | ||||||||
| kjohnson1 | macOS 13.7.5 Ventura / arm64 | OK | OK | OK | OK |  | ||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | ERROR | ||||||||||
| 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. | 
| 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: 2025-10-14 10:32:03 -0400 (Tue, 14 Oct 2025) | 
| EndedAt: 2025-10-14 11:03:29 -0400 (Tue, 14 Oct 2025) | 
| EllapsedTime: 1885.9 seconds | 
| RetCode: 0 | 
| Status: OK | 
| CheckDir: singleCellTK.Rcheck | 
| Warnings: 0 | 
##############################################################################
##############################################################################
###
### 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 88.701  0.758  89.899
plotDoubletFinderResults 54.696  0.254  56.414
plotScDblFinderResults   50.379  1.000  54.172
runDoubletFinder         46.626  0.186  47.700
runScDblFinder           32.658  0.398  33.129
importExampleData        22.345  2.115  25.460
plotBatchCorrCompare     18.826  0.163  19.106
plotScdsHybridResults    15.495  0.217  16.984
plotBcdsResults          14.227  0.252  14.570
plotDecontXResults       13.307  0.099  13.580
plotDEGViolin            13.143  0.207  13.928
plotTSCANClusterDEG      12.310  0.116  13.552
plotCxdsResults          11.771  0.087  12.054
plotDEGRegression        11.371  0.201  12.810
plotEmptyDropsScatter    10.234  0.043  11.094
plotEmptyDropsResults    10.175  0.035  10.587
plotFindMarkerHeatmap     9.656  0.043  10.112
runDecontX                9.404  0.071   9.637
runUMAP                   9.312  0.106   9.637
runEmptyDrops             9.321  0.029   9.696
plotUMAP                  9.142  0.081   9.837
convertSCEToSeurat        8.794  0.316   9.176
detectCellOutlier         7.702  0.171   7.905
plotRunPerCellQCResults   7.366  0.037   7.429
runSeuratSCTransform      7.119  0.123   7.303
plotDEGHeatmap            5.382  0.080   6.045
getEnrichRResult          0.666  0.058  14.287
* 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.
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)
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 
  0.336   0.112   0.417 
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%
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**************************************************|
Calculating feature variances of standardized and clipped values
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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Performing log-normalization
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**************************************************|
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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 
547.876  10.769 573.845 
singleCellTK.Rcheck/singleCellTK-Ex.timings
| name | user | system | elapsed | |
| MitoGenes | 0.002 | 0.002 | 0.005 | |
| SEG | 0.005 | 0.005 | 0.010 | |
| calcEffectSizes | 0.430 | 0.031 | 0.464 | |
| combineSCE | 1.624 | 0.026 | 1.654 | |
| computeZScore | 0.390 | 0.017 | 0.408 | |
| convertSCEToSeurat | 8.794 | 0.316 | 9.176 | |
| convertSeuratToSCE | 0.696 | 0.012 | 0.710 | |
| dedupRowNames | 0.115 | 0.003 | 0.119 | |
| detectCellOutlier | 7.702 | 0.171 | 7.905 | |
| diffAbundanceFET | 0.097 | 0.004 | 0.102 | |
| discreteColorPalette | 0.011 | 0.001 | 0.011 | |
| distinctColors | 0.004 | 0.001 | 0.004 | |
| downSampleCells | 1.039 | 0.103 | 1.148 | |
| downSampleDepth | 0.852 | 0.055 | 0.909 | |
| expData-ANY-character-method | 0.278 | 0.007 | 0.286 | |
| expData-set-ANY-character-CharacterOrNullOrMissing-logical-method | 0.363 | 0.008 | 0.372 | |
| expData-set | 0.351 | 0.007 | 0.359 | |
| expData | 0.283 | 0.006 | 0.291 | |
| expDataNames-ANY-method | 0.253 | 0.010 | 0.263 | |
| expDataNames | 0.268 | 0.027 | 0.296 | |
| expDeleteDataTag | 0.059 | 0.004 | 0.063 | |
| expSetDataTag | 0.042 | 0.005 | 0.046 | |
| expTaggedData | 0.045 | 0.004 | 0.049 | |
| exportSCE | 0.039 | 0.006 | 0.046 | |
| exportSCEtoAnnData | 0.123 | 0.011 | 0.134 | |
| exportSCEtoFlatFile | 0.112 | 0.008 | 0.122 | |
| featureIndex | 0.063 | 0.010 | 0.074 | |
| generateSimulatedData | 0.089 | 0.010 | 0.099 | |
| getBiomarker | 0.104 | 0.014 | 0.119 | |
| getDEGTopTable | 1.548 | 0.111 | 1.664 | |
| getDiffAbundanceResults | 0.085 | 0.003 | 0.088 | |
| getEnrichRResult | 0.666 | 0.058 | 14.287 | |
| getFindMarkerTopTable | 3.246 | 0.049 | 3.298 | |
| getMSigDBTable | 0.007 | 0.007 | 0.014 | |
| getPathwayResultNames | 0.045 | 0.006 | 0.050 | |
| getSampleSummaryStatsTable | 0.393 | 0.006 | 0.399 | |
| getSoupX | 0.000 | 0.000 | 0.001 | |
| getTSCANResults | 2.295 | 0.071 | 2.398 | |
| getTopHVG | 1.688 | 0.025 | 1.786 | |
| importAnnData | 0.003 | 0.000 | 0.004 | |
| importBUStools | 0.433 | 0.009 | 0.458 | |
| importCellRanger | 1.665 | 0.046 | 1.833 | |
| importCellRangerV2Sample | 0.332 | 0.003 | 0.335 | |
| importCellRangerV3Sample | 0.633 | 0.019 | 0.653 | |
| importDropEst | 0.432 | 0.005 | 0.438 | |
| importExampleData | 22.345 | 2.115 | 25.460 | |
| importGeneSetsFromCollection | 1.598 | 0.132 | 1.736 | |
| importGeneSetsFromGMT | 0.133 | 0.010 | 0.146 | |
| importGeneSetsFromList | 0.274 | 0.019 | 0.293 | |
| importGeneSetsFromMSigDB | 88.701 | 0.758 | 89.899 | |
| importMitoGeneSet | 0.102 | 0.014 | 0.117 | |
| importOptimus | 0.003 | 0.001 | 0.004 | |
| importSEQC | 0.327 | 0.031 | 0.361 | |
| importSTARsolo | 0.355 | 0.038 | 0.393 | |
| iterateSimulations | 0.395 | 0.041 | 0.437 | |
| listSampleSummaryStatsTables | 0.587 | 0.066 | 0.659 | |
| mergeSCEColData | 0.913 | 0.125 | 1.050 | |
| mouseBrainSubsetSCE | 0.063 | 0.009 | 0.072 | |
| msigdb_table | 0.002 | 0.004 | 0.006 | |
| plotBarcodeRankDropsResults | 1.955 | 0.040 | 1.999 | |
| plotBarcodeRankScatter | 2.022 | 0.022 | 2.049 | |
| plotBatchCorrCompare | 18.826 | 0.163 | 19.106 | |
| plotBatchVariance | 1.084 | 0.034 | 1.121 | |
| plotBcdsResults | 14.227 | 0.252 | 14.570 | |
| plotBubble | 1.824 | 0.016 | 1.843 | |
| plotClusterAbundance | 3.350 | 0.017 | 3.386 | |
| plotCxdsResults | 11.771 | 0.087 | 12.054 | |
| plotDEGHeatmap | 5.382 | 0.080 | 6.045 | |
| plotDEGRegression | 11.371 | 0.201 | 12.810 | |
| plotDEGViolin | 13.143 | 0.207 | 13.928 | |
| plotDEGVolcano | 2.043 | 0.020 | 2.070 | |
| plotDecontXResults | 13.307 | 0.099 | 13.580 | |
| plotDimRed | 0.680 | 0.011 | 0.742 | |
| plotDoubletFinderResults | 54.696 | 0.254 | 56.414 | |
| plotEmptyDropsResults | 10.175 | 0.035 | 10.587 | |
| plotEmptyDropsScatter | 10.234 | 0.043 | 11.094 | |
| plotFindMarkerHeatmap | 9.656 | 0.043 | 10.112 | |
| plotMASTThresholdGenes | 3.020 | 0.037 | 3.060 | |
| plotPCA | 0.960 | 0.015 | 0.976 | |
| plotPathway | 1.526 | 0.014 | 1.546 | |
| plotRunPerCellQCResults | 7.366 | 0.037 | 7.429 | |
| plotSCEBarAssayData | 0.611 | 0.009 | 0.625 | |
| plotSCEBarColData | 0.533 | 0.008 | 0.544 | |
| plotSCEBatchFeatureMean | 0.952 | 0.005 | 0.961 | |
| plotSCEDensity | 0.707 | 0.009 | 0.718 | |
| plotSCEDensityAssayData | 0.697 | 0.010 | 0.708 | |
| plotSCEDensityColData | 0.678 | 0.010 | 0.689 | |
| plotSCEDimReduceColData | 1.695 | 0.016 | 1.772 | |
| plotSCEDimReduceFeatures | 0.895 | 0.010 | 0.907 | |
| plotSCEHeatmap | 0.913 | 0.008 | 0.923 | |
| plotSCEScatter | 0.776 | 0.013 | 0.789 | |
| plotSCEViolin | 0.883 | 0.012 | 0.897 | |
| plotSCEViolinAssayData | 0.861 | 0.010 | 0.872 | |
| plotSCEViolinColData | 0.864 | 0.014 | 0.884 | |
| plotScDblFinderResults | 50.379 | 1.000 | 54.172 | |
| plotScanpyDotPlot | 0.038 | 0.005 | 0.050 | |
| plotScanpyEmbedding | 0.039 | 0.005 | 0.049 | |
| plotScanpyHVG | 0.041 | 0.005 | 0.049 | |
| plotScanpyHeatmap | 0.039 | 0.003 | 0.047 | |
| plotScanpyMarkerGenes | 0.039 | 0.005 | 0.052 | |
| plotScanpyMarkerGenesDotPlot | 0.039 | 0.005 | 0.046 | |
| plotScanpyMarkerGenesHeatmap | 0.039 | 0.005 | 0.045 | |
| plotScanpyMarkerGenesMatrixPlot | 0.041 | 0.004 | 0.053 | |
| plotScanpyMarkerGenesViolin | 0.040 | 0.005 | 0.050 | |
| plotScanpyMatrixPlot | 0.040 | 0.004 | 0.045 | |
| plotScanpyPCA | 0.040 | 0.004 | 0.046 | |
| plotScanpyPCAGeneRanking | 0.045 | 0.005 | 0.059 | |
| plotScanpyPCAVariance | 0.043 | 0.004 | 0.054 | |
| plotScanpyViolin | 0.043 | 0.004 | 0.052 | |
| plotScdsHybridResults | 15.495 | 0.217 | 16.984 | |
| plotScrubletResults | 0.042 | 0.004 | 0.052 | |
| plotSeuratElbow | 0.043 | 0.006 | 0.057 | |
| plotSeuratHVG | 0.040 | 0.005 | 0.051 | |
| plotSeuratJackStraw | 0.041 | 0.006 | 0.050 | |
| plotSeuratReduction | 0.044 | 0.003 | 0.053 | |
| plotSoupXResults | 0.000 | 0.001 | 0.001 | |
| plotTSCANClusterDEG | 12.310 | 0.116 | 13.552 | |
| plotTSCANClusterPseudo | 3.335 | 0.034 | 3.673 | |
| plotTSCANDimReduceFeatures | 3.367 | 0.037 | 3.731 | |
| plotTSCANPseudotimeGenes | 4.154 | 0.039 | 4.479 | |
| plotTSCANPseudotimeHeatmap | 3.092 | 0.033 | 3.363 | |
| plotTSCANResults | 3.010 | 0.033 | 3.278 | |
| plotTSNE | 0.919 | 0.018 | 1.014 | |
| plotTopHVG | 1.436 | 0.026 | 1.552 | |
| plotUMAP | 9.142 | 0.081 | 9.837 | |
| readSingleCellMatrix | 0.011 | 0.001 | 0.012 | |
| reportCellQC | 0.180 | 0.007 | 0.195 | |
| reportDropletQC | 0.041 | 0.005 | 0.046 | |
| reportQCTool | 0.175 | 0.007 | 0.192 | |
| retrieveSCEIndex | 0.050 | 0.006 | 0.062 | |
| runBBKNN | 0.000 | 0.000 | 0.001 | |
| runBarcodeRankDrops | 0.471 | 0.010 | 0.536 | |
| runBcds | 3.341 | 0.067 | 3.629 | |
| runCellQC | 0.171 | 0.006 | 0.187 | |
| runClusterSummaryMetrics | 0.890 | 0.021 | 0.928 | |
| runComBatSeq | 0.977 | 0.021 | 1.003 | |
| runCxds | 0.722 | 0.015 | 0.740 | |
| runCxdsBcdsHybrid | 3.416 | 0.110 | 3.539 | |
| runDEAnalysis | 0.924 | 0.074 | 1.009 | |
| runDecontX | 9.404 | 0.071 | 9.637 | |
| runDimReduce | 0.625 | 0.011 | 0.639 | |
| runDoubletFinder | 46.626 | 0.186 | 47.700 | |
| runDropletQC | 0.044 | 0.005 | 0.066 | |
| runEmptyDrops | 9.321 | 0.029 | 9.696 | |
| runEnrichR | 0.634 | 0.047 | 4.628 | |
| runFastMNN | 3.843 | 0.065 | 3.920 | |
| runFeatureSelection | 0.437 | 0.009 | 0.447 | |
| runFindMarker | 3.104 | 0.045 | 3.156 | |
| runGSVA | 1.414 | 0.047 | 1.465 | |
| runHarmony | 0.084 | 0.002 | 0.086 | |
| runKMeans | 0.474 | 0.018 | 0.492 | |
| runLimmaBC | 0.174 | 0.003 | 0.177 | |
| runMNNCorrect | 0.859 | 0.006 | 0.872 | |
| runModelGeneVar | 0.669 | 0.009 | 0.692 | |
| runNormalization | 3.372 | 0.041 | 3.485 | |
| runPerCellQC | 0.671 | 0.011 | 0.683 | |
| runSCANORAMA | 0.000 | 0.001 | 0.001 | |
| runSCMerge | 0.007 | 0.002 | 0.008 | |
| runScDblFinder | 32.658 | 0.398 | 33.129 | |
| runScanpyFindClusters | 0.038 | 0.004 | 0.043 | |
| runScanpyFindHVG | 0.040 | 0.004 | 0.043 | |
| runScanpyFindMarkers | 0.039 | 0.005 | 0.044 | |
| runScanpyNormalizeData | 0.213 | 0.006 | 0.220 | |
| runScanpyPCA | 0.045 | 0.004 | 0.050 | |
| runScanpyScaleData | 0.040 | 0.003 | 0.044 | |
| runScanpyTSNE | 0.053 | 0.003 | 0.056 | |
| runScanpyUMAP | 0.043 | 0.003 | 0.046 | |
| runScranSNN | 0.652 | 0.014 | 0.669 | |
| runScrublet | 0.041 | 0.007 | 0.049 | |
| runSeuratFindClusters | 0.042 | 0.005 | 0.047 | |
| runSeuratFindHVG | 1.048 | 0.016 | 1.069 | |
| runSeuratHeatmap | 0.040 | 0.003 | 0.043 | |
| runSeuratICA | 0.042 | 0.003 | 0.045 | |
| runSeuratJackStraw | 0.041 | 0.002 | 0.044 | |
| runSeuratNormalizeData | 0.041 | 0.008 | 0.049 | |
| runSeuratPCA | 0.048 | 0.003 | 0.050 | |
| runSeuratSCTransform | 7.119 | 0.123 | 7.303 | |
| runSeuratScaleData | 0.040 | 0.005 | 0.045 | |
| runSeuratUMAP | 0.038 | 0.005 | 0.043 | |
| runSingleR | 0.081 | 0.004 | 0.086 | |
| runSoupX | 0.001 | 0.001 | 0.001 | |
| runTSCAN | 1.534 | 0.020 | 1.563 | |
| runTSCANClusterDEAnalysis | 1.723 | 0.036 | 1.779 | |
| runTSCANDEG | 1.695 | 0.056 | 1.762 | |
| runTSNE | 1.317 | 0.019 | 1.360 | |
| runUMAP | 9.312 | 0.106 | 9.637 | |
| runVAM | 0.689 | 0.009 | 0.828 | |
| runZINBWaVE | 0.007 | 0.001 | 0.008 | |
| sampleSummaryStats | 0.363 | 0.011 | 0.412 | |
| scaterCPM | 0.212 | 0.008 | 0.221 | |
| scaterPCA | 1.004 | 0.011 | 1.017 | |
| scaterlogNormCounts | 0.428 | 0.008 | 0.437 | |
| sce | 0.036 | 0.005 | 0.042 | |
| sctkListGeneSetCollections | 0.161 | 0.009 | 0.170 | |
| sctkPythonInstallConda | 0.000 | 0.000 | 0.001 | |
| sctkPythonInstallVirtualEnv | 0.000 | 0.000 | 0.001 | |
| selectSCTKConda | 0.001 | 0.001 | 0.001 | |
| selectSCTKVirtualEnvironment | 0.000 | 0.000 | 0.001 | |
| setRowNames | 0.177 | 0.005 | 0.182 | |
| setSCTKDisplayRow | 0.979 | 0.026 | 1.008 | |
| singleCellTK | 0.000 | 0.001 | 0.001 | |
| subDiffEx | 0.645 | 0.031 | 0.678 | |
| subsetSCECols | 0.173 | 0.009 | 0.183 | |
| subsetSCERows | 0.549 | 0.029 | 0.579 | |
| summarizeSCE | 0.126 | 0.012 | 0.139 | |
| trimCounts | 0.338 | 0.017 | 0.356 | |