Back to Multiple platform build/check report for BioC 3.21:   simplified   long
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This page was generated on 2025-08-04 11:47 -0400 (Mon, 04 Aug 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.2 LTS)x86_644.5.1 (2025-06-13) -- "Great Square Root" 4823
palomino7Windows Server 2022 Datacenterx644.5.1 (2025-06-13 ucrt) -- "Great Square Root" 4565
merida1macOS 12.7.5 Montereyx86_644.5.1 RC (2025-06-05 r88288) -- "Great Square Root" 4603
kjohnson1macOS 13.6.6 Venturaarm644.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" 4544
kunpeng2Linux (openEuler 24.03 LTS)aarch64R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" 4579
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 2013/2341HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.18.1  (landing page)
Joshua David Campbell
Snapshot Date: 2025-07-31 13:40 -0400 (Thu, 31 Jul 2025)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_21
git_last_commit: f519d00e
git_last_commit_date: 2025-07-01 15:40:07 -0400 (Tue, 01 Jul 2025)
nebbiolo1Linux (Ubuntu 24.04.2 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino7Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
merida1macOS 12.7.5 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kjohnson1macOS 13.6.6 Ventura / arm64  OK    OK    OK    OK  UNNEEDED, same version is already published
kunpeng2Linux (openEuler 24.03 LTS) / aarch64  OK    OK    OK  


CHECK results for singleCellTK on kjohnson1

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: 2.18.1
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_2.18.1.tar.gz
StartedAt: 2025-08-02 11:05:50 -0400 (Sat, 02 Aug 2025)
EndedAt: 2025-08-02 11:25:24 -0400 (Sat, 02 Aug 2025)
EllapsedTime: 1174.1 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_2.18.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.1 Patched (2025-06-14 r88325)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 16.0.0 (clang-1600.0.26.6)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.5
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.18.1’
* 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:
    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 57.810  0.817  59.107
plotDoubletFinderResults 49.741  0.429  50.398
runDoubletFinder         44.387  0.170  44.598
plotScDblFinderResults   36.326  0.895  37.567
runScDblFinder           28.227  0.494  28.756
importExampleData        19.031  1.350  22.540
plotBatchCorrCompare     16.584  0.158  16.826
plotScdsHybridResults    11.834  0.175  12.074
plotBcdsResults          10.625  0.184  10.838
plotDecontXResults       10.339  0.190  10.595
runDecontX                9.457  0.045   9.513
runUMAP                   9.420  0.082   9.513
plotUMAP                  9.164  0.064   9.255
plotCxdsResults           8.969  0.070   9.075
detectCellOutlier         6.864  0.149   7.081
plotEmptyDropsResults     6.713  0.036   6.845
runEmptyDrops             6.353  0.015   6.374
plotEmptyDropsScatter     6.075  0.025   6.126
convertSCEToSeurat        4.738  0.262   5.093
* 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-arm64/Resources/library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.18.1’
** using staged installation
** R
** data
** exec
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (singleCellTK)

Tests output

singleCellTK.Rcheck/tests/spelling.Rout


R version 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-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)
NULL
> 
> proc.time()
   user  system elapsed 
  0.208   0.062   0.266 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-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
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
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  |======================================================================| 100%
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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  |======================================================================| 100%

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  |======================================================================| 100%
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 390
Number of edges: 9849

Running Louvain algorithm...
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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  |======================================================================| 100%

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  |======================================================================| 100%
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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  |======================================================================| 100%

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  |======================================================================| 100%

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  |======================================================================| 100%

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  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 22 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 22 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
354.230   7.646 372.543 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0020.0040.007
SEG0.0040.0050.011
calcEffectSizes0.2230.0180.246
combineSCE0.8020.0390.842
computeZScore0.2830.0100.293
convertSCEToSeurat4.7380.2625.093
convertSeuratToSCE0.3930.0160.410
dedupRowNames0.0710.0030.073
detectCellOutlier6.8640.1497.081
diffAbundanceFET0.0780.0030.082
discreteColorPalette0.0090.0010.009
distinctColors0.0020.0000.003
downSampleCells0.6800.0620.752
downSampleDepth0.5040.0460.552
expData-ANY-character-method0.1470.0070.154
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1940.0070.201
expData-set0.1670.0060.174
expData0.1430.0060.150
expDataNames-ANY-method0.1430.0100.154
expDataNames0.1360.0070.144
expDeleteDataTag0.0500.0040.054
expSetDataTag0.0390.0030.042
expTaggedData0.0510.0050.055
exportSCE0.0350.0060.042
exportSCEtoAnnData0.1280.0090.138
exportSCEtoFlatFile0.1280.0070.138
featureIndex0.0520.0070.059
generateSimulatedData0.0820.0070.089
getBiomarker0.0740.0070.081
getDEGTopTable0.7810.0610.852
getDiffAbundanceResults0.0670.0040.072
getEnrichRResult0.3480.0404.766
getFindMarkerTopTable1.2900.0471.356
getMSigDBTable0.0050.0030.008
getPathwayResultNames0.0370.0050.042
getSampleSummaryStatsTable0.2480.0070.265
getSoupX000
getTSCANResults1.2140.0551.310
getTopHVG0.9940.0181.032
importAnnData0.0020.0000.003
importBUStools0.1630.0050.171
importCellRanger0.8070.0400.854
importCellRangerV2Sample0.1480.0020.155
importCellRangerV3Sample0.3360.0160.358
importDropEst0.2180.0030.222
importExampleData19.031 1.35022.540
importGeneSetsFromCollection0.7640.0770.843
importGeneSetsFromGMT0.0840.0060.091
importGeneSetsFromList0.1290.0070.136
importGeneSetsFromMSigDB57.810 0.81759.107
importMitoGeneSet0.0630.0120.077
importOptimus0.0020.0010.003
importSEQC0.1690.0120.182
importSTARsolo0.1580.0170.180
iterateSimulations0.2180.0220.267
listSampleSummaryStatsTables0.3070.0240.331
mergeSCEColData0.4620.0460.521
mouseBrainSubsetSCE0.0560.0060.063
msigdb_table0.0010.0030.005
plotBarcodeRankDropsResults0.6420.0270.675
plotBarcodeRankScatter0.6620.0470.734
plotBatchCorrCompare16.584 0.15816.826
plotBatchVariance0.3540.0190.374
plotBcdsResults10.625 0.18410.838
plotBubble0.7740.0330.849
plotClusterAbundance0.8360.0090.850
plotCxdsResults8.9690.0709.075
plotDEGHeatmap2.2520.0562.349
plotDEGRegression3.3290.0663.482
plotDEGViolin4.4630.1384.670
plotDEGVolcano0.9830.0151.002
plotDecontXResults10.339 0.19010.595
plotDimRed0.2280.0070.237
plotDoubletFinderResults49.741 0.42950.398
plotEmptyDropsResults6.7130.0366.845
plotEmptyDropsScatter6.0750.0256.126
plotFindMarkerHeatmap4.0170.0384.066
plotMASTThresholdGenes1.3360.0441.393
plotPCA0.3520.0110.371
plotPathway0.6260.0130.642
plotRunPerCellQCResults2.0800.0262.110
plotSCEBarAssayData0.2470.0090.258
plotSCEBarColData0.1690.0090.177
plotSCEBatchFeatureMean0.2250.0040.229
plotSCEDensity0.3170.0080.326
plotSCEDensityAssayData0.1910.0070.200
plotSCEDensityColData0.2270.0090.238
plotSCEDimReduceColData0.5480.0150.564
plotSCEDimReduceFeatures0.2940.0130.321
plotSCEHeatmap0.5400.0110.551
plotSCEScatter0.2710.0090.280
plotSCEViolin0.2500.0080.258
plotSCEViolinAssayData0.2620.0080.270
plotSCEViolinColData0.2690.0090.277
plotScDblFinderResults36.326 0.89537.567
plotScanpyDotPlot0.0360.0090.045
plotScanpyEmbedding0.0400.0080.048
plotScanpyHVG0.0380.0050.043
plotScanpyHeatmap0.0360.0030.039
plotScanpyMarkerGenes0.0360.0030.040
plotScanpyMarkerGenesDotPlot0.0370.0030.041
plotScanpyMarkerGenesHeatmap0.0370.0040.041
plotScanpyMarkerGenesMatrixPlot0.0390.0050.044
plotScanpyMarkerGenesViolin0.0390.0040.043
plotScanpyMatrixPlot0.0550.0040.058
plotScanpyPCA0.0370.0030.039
plotScanpyPCAGeneRanking0.0370.0030.039
plotScanpyPCAVariance0.0350.0030.037
plotScanpyViolin0.0420.0030.045
plotScdsHybridResults11.834 0.17512.074
plotScrubletResults0.0410.0040.046
plotSeuratElbow0.0370.0050.042
plotSeuratHVG0.0370.0020.039
plotSeuratJackStraw0.0350.0020.037
plotSeuratReduction0.0350.0020.037
plotSoupXResults0.0010.0010.001
plotTSCANClusterDEG3.0010.1343.153
plotTSCANClusterPseudo1.2130.0231.243
plotTSCANDimReduceFeatures1.3390.0221.364
plotTSCANPseudotimeGenes1.4460.0221.474
plotTSCANPseudotimeHeatmap1.3830.0241.408
plotTSCANResults1.2230.0251.254
plotTSNE0.3260.0100.336
plotTopHVG0.5790.0150.598
plotUMAP9.1640.0649.255
readSingleCellMatrix0.0060.0010.009
reportCellQC0.0910.0070.098
reportDropletQC0.0350.0040.040
reportQCTool0.0930.0040.099
retrieveSCEIndex0.0440.0040.048
runBBKNN000
runBarcodeRankDrops0.2650.0070.275
runBcds1.8010.1001.907
runCellQC0.0830.0100.093
runClusterSummaryMetrics0.3140.0230.339
runComBatSeq0.3260.0180.353
runCxds0.3960.0180.432
runCxdsBcdsHybrid1.9360.1352.094
runDEAnalysis0.5670.0370.610
runDecontX9.4570.0459.513
runDimReduce0.3150.0130.328
runDoubletFinder44.387 0.17044.598
runDropletQC0.0370.0060.043
runEmptyDrops6.3530.0156.374
runEnrichR0.3190.0274.522
runFastMNN1.6660.0641.740
runFeatureSelection0.2500.0110.260
runFindMarker1.5200.0461.567
runGSVA0.7810.0810.874
runHarmony0.1500.0070.157
runKMeans0.2130.0090.223
runLimmaBC0.0840.0020.085
runMNNCorrect0.4330.0060.443
runModelGeneVar0.3210.0070.330
runNormalization3.2840.0613.358
runPerCellQC0.3780.0120.389
runSCANORAMA0.0010.0000.000
runSCMerge0.0060.0020.008
runScDblFinder28.227 0.49428.756
runScanpyFindClusters0.0360.0150.051
runScanpyFindHVG0.0360.0140.051
runScanpyFindMarkers0.0370.0140.051
runScanpyNormalizeData0.1130.0160.131
runScanpyPCA0.0370.0050.043
runScanpyScaleData0.0370.0060.043
runScanpyTSNE0.0360.0060.043
runScanpyUMAP0.0350.0060.042
runScranSNN0.3210.0140.337
runScrublet0.0360.0090.045
runSeuratFindClusters0.0360.0040.040
runSeuratFindHVG0.5030.0130.517
runSeuratHeatmap0.0360.0030.040
runSeuratICA0.0370.0040.041
runSeuratJackStraw0.0350.0030.038
runSeuratNormalizeData0.0340.0040.038
runSeuratPCA0.0380.0040.041
runSeuratSCTransform4.5920.1534.769
runSeuratScaleData0.0570.0030.060
runSeuratUMAP0.0370.0040.042
runSingleR0.0390.0040.043
runSoupX000
runTSCAN0.7040.0200.725
runTSCANClusterDEAnalysis0.8260.0500.876
runTSCANDEG0.8680.0300.898
runTSNE0.9280.0310.961
runUMAP9.4200.0829.513
runVAM0.3260.0150.341
runZINBWaVE0.0060.0010.007
sampleSummaryStats0.1780.0050.183
scaterCPM0.1790.0090.189
scaterPCA0.4680.0110.479
scaterlogNormCounts0.2790.0110.290
sce0.0340.0060.040
sctkListGeneSetCollections0.0930.0070.100
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.0950.0040.099
setSCTKDisplayRow0.3380.0210.360
singleCellTK000
subDiffEx0.4280.0260.455
subsetSCECols0.1060.0150.121
subsetSCERows0.2590.0160.277
summarizeSCE0.0950.0120.108
trimCounts0.2580.0280.287