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

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo2	Linux (Ubuntu 24.04.3 LTS)	x86_64	4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"	4902
lconway	macOS 12.7.6 Monterey	x86_64	4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"	4692
kjohnson3	macOS 13.7.7 Ventura	arm64	4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"	4638
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 lconway

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

raw results

Summary

Package: singleCellTK

Version: 2.20.0

Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.20.0.tar.gz

StartedAt: 2025-11-04 00:21:17 -0500 (Tue, 04 Nov 2025)

EndedAt: 2025-11-04 00:39:25 -0500 (Tue, 04 Nov 2025)

EllapsedTime: 1088.1 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_2.20.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.1 Patched (2025-09-10 r88807)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.20.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 80 non-default packages.
Importing from so many packages makes the package vulnerable to any of
them becoming unavailable.  Move as many as possible to Suggests and
use conditionally.
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘singleCellTK’ can be installed ... OK
* checking installed package size ... INFO
  installed size is  6.8Mb
  sub-directories of 1Mb or more:
    R         1.0Mb
    extdata   1.5Mb
    shiny     2.9Mb
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
  dedupRowNames.Rd: SingleCellExperiment-class
  detectCellOutlier.Rd: colData
  diffAbundanceFET.Rd: colData
  downSampleCells.Rd: SingleCellExperiment-class
  downSampleDepth.Rd: SingleCellExperiment-class
  featureIndex.Rd: SummarizedExperiment-class,
    SingleCellExperiment-class
  getBiomarker.Rd: SingleCellExperiment-class
  getDEGTopTable.Rd: SingleCellExperiment-class
  getEnrichRResult.Rd: SingleCellExperiment-class
  getFindMarkerTopTable.Rd: SingleCellExperiment-class
  getGenesetNamesFromCollection.Rd: SingleCellExperiment-class
  getPathwayResultNames.Rd: SingleCellExperiment-class
  getSampleSummaryStatsTable.Rd: SingleCellExperiment-class, assay,
    colData
  getSoupX.Rd: SingleCellExperiment-class
  getTSCANResults.Rd: SingleCellExperiment-class
  getTopHVG.Rd: SingleCellExperiment-class
  importAlevin.Rd: DelayedArray, readMM
  importAnnData.Rd: DelayedArray, readMM
  importBUStools.Rd: readMM
  importCellRanger.Rd: readMM, DelayedArray
  importCellRangerV2Sample.Rd: readMM, DelayedArray
  importCellRangerV3Sample.Rd: readMM, DelayedArray
  importDropEst.Rd: DelayedArray, readMM
  importExampleData.Rd: scRNAseq, Matrix, DelayedArray,
    ReprocessedFluidigmData, ReprocessedAllenData, NestorowaHSCData
  importFromFiles.Rd: readMM, DelayedArray, SingleCellExperiment-class
  importGeneSetsFromCollection.Rd: GeneSetCollection-class,
    SingleCellExperiment-class, GeneSetCollection, GSEABase, metadata
  importGeneSetsFromGMT.Rd: GeneSetCollection-class,
    SingleCellExperiment-class, getGmt, GSEABase, metadata
  importGeneSetsFromList.Rd: GeneSetCollection-class,
    SingleCellExperiment-class, GSEABase, metadata
  importGeneSetsFromMSigDB.Rd: SingleCellExperiment-class, msigdbr,
    GeneSetCollection-class, GSEABase, metadata
  importMitoGeneSet.Rd: SingleCellExperiment-class,
    GeneSetCollection-class, GSEABase, metadata
  importMultipleSources.Rd: DelayedArray
  importOptimus.Rd: readMM, DelayedArray
  importSEQC.Rd: readMM, DelayedArray
  importSTARsolo.Rd: readMM, DelayedArray
  iterateSimulations.Rd: SingleCellExperiment-class
  listSampleSummaryStatsTables.Rd: SingleCellExperiment-class, metadata
  plotBarcodeRankDropsResults.Rd: SingleCellExperiment-class
  plotBarcodeRankScatter.Rd: SingleCellExperiment-class
  plotBatchCorrCompare.Rd: SingleCellExperiment-class
  plotBatchVariance.Rd: SingleCellExperiment-class
  plotBcdsResults.Rd: SingleCellExperiment-class
  plotClusterAbundance.Rd: colData
  plotCxdsResults.Rd: SingleCellExperiment-class
  plotDEGHeatmap.Rd: SingleCellExperiment-class
  plotDEGRegression.Rd: SingleCellExperiment-class
  plotDEGViolin.Rd: SingleCellExperiment-class
  plotDEGVolcano.Rd: SingleCellExperiment-class
  plotDecontXResults.Rd: SingleCellExperiment-class
  plotDoubletFinderResults.Rd: SingleCellExperiment-class
  plotEmptyDropsResults.Rd: SingleCellExperiment-class
  plotEmptyDropsScatter.Rd: SingleCellExperiment-class
  plotEnrichR.Rd: SingleCellExperiment-class
  plotFindMarkerHeatmap.Rd: SingleCellExperiment-class
  plotPCA.Rd: SingleCellExperiment-class
  plotPathway.Rd: SingleCellExperiment-class
  plotRunPerCellQCResults.Rd: SingleCellExperiment-class
  plotSCEBarAssayData.Rd: SingleCellExperiment-class
  plotSCEBarColData.Rd: SingleCellExperiment-class
  plotSCEBatchFeatureMean.Rd: SingleCellExperiment-class
  plotSCEDensity.Rd: SingleCellExperiment-class
  plotSCEDensityAssayData.Rd: SingleCellExperiment-class
  plotSCEDensityColData.Rd: SingleCellExperiment-class
  plotSCEDimReduceColData.Rd: SingleCellExperiment-class
  plotSCEDimReduceFeatures.Rd: SingleCellExperiment-class
  plotSCEHeatmap.Rd: SingleCellExperiment-class
  plotSCEScatter.Rd: SingleCellExperiment-class
  plotSCEViolin.Rd: SingleCellExperiment-class
  plotSCEViolinAssayData.Rd: SingleCellExperiment-class
  plotSCEViolinColData.Rd: SingleCellExperiment-class
  plotScDblFinderResults.Rd: SingleCellExperiment-class
  plotScdsHybridResults.Rd: SingleCellExperiment-class
  plotScrubletResults.Rd: SingleCellExperiment-class
  plotSoupXResults.Rd: SingleCellExperiment-class
  plotTSCANClusterDEG.Rd: SingleCellExperiment-class
  plotTSCANClusterPseudo.Rd: SingleCellExperiment-class
  plotTSCANDimReduceFeatures.Rd: SingleCellExperiment-class
  plotTSCANPseudotimeGenes.Rd: SingleCellExperiment-class
  plotTSCANPseudotimeHeatmap.Rd: SingleCellExperiment-class
  plotTSCANResults.Rd: SingleCellExperiment-class
  plotTSNE.Rd: SingleCellExperiment-class
  plotUMAP.Rd: SingleCellExperiment-class
  readSingleCellMatrix.Rd: DelayedArray
  reportCellQC.Rd: SingleCellExperiment-class
  reportClusterAbundance.Rd: colData
  reportDiffAbundanceFET.Rd: colData
  retrieveSCEIndex.Rd: SingleCellExperiment-class
  runBBKNN.Rd: SingleCellExperiment-class
  runBarcodeRankDrops.Rd: SingleCellExperiment-class, colData
  runBcds.Rd: SingleCellExperiment-class, colData
  runCellQC.Rd: colData
  runComBatSeq.Rd: SingleCellExperiment-class
  runCxds.Rd: SingleCellExperiment-class, colData
  runCxdsBcdsHybrid.Rd: colData
  runDEAnalysis.Rd: SingleCellExperiment-class
  runDecontX.Rd: colData
  runDimReduce.Rd: SingleCellExperiment-class
  runDoubletFinder.Rd: SingleCellExperiment-class
  runDropletQC.Rd: colData
  runEmptyDrops.Rd: SingleCellExperiment-class, colData
  runEnrichR.Rd: SingleCellExperiment-class
  runFastMNN.Rd: SingleCellExperiment-class, BiocParallelParam-class
  runFeatureSelection.Rd: SingleCellExperiment-class
  runFindMarker.Rd: SingleCellExperiment-class
  runGSVA.Rd: SingleCellExperiment-class
  runHarmony.Rd: SingleCellExperiment-class
  runKMeans.Rd: SingleCellExperiment-class, colData
  runLimmaBC.Rd: SingleCellExperiment-class, assay
  runMNNCorrect.Rd: SingleCellExperiment-class, assay,
    BiocParallelParam-class
  runModelGeneVar.Rd: SingleCellExperiment-class
  runPerCellQC.Rd: SingleCellExperiment-class, BiocParallelParam,
    colData
  runSCANORAMA.Rd: SingleCellExperiment-class, assay
  runSCMerge.Rd: SingleCellExperiment-class, colData, assay,
    BiocParallelParam-class
  runScDblFinder.Rd: SingleCellExperiment-class, colData
  runScranSNN.Rd: SingleCellExperiment-class, reducedDim, assay,
    altExp, colData, igraph
  runScrublet.Rd: SingleCellExperiment-class, colData
  runSingleR.Rd: SingleCellExperiment-class
  runSoupX.Rd: SingleCellExperiment-class
  runTSCAN.Rd: SingleCellExperiment-class
  runTSCANClusterDEAnalysis.Rd: SingleCellExperiment-class
  runTSCANDEG.Rd: SingleCellExperiment-class
  runTSNE.Rd: SingleCellExperiment-class
  runUMAP.Rd: SingleCellExperiment-class, BiocParallelParam-class
  runVAM.Rd: SingleCellExperiment-class
  runZINBWaVE.Rd: SingleCellExperiment-class, colData,
    BiocParallelParam-class
  sampleSummaryStats.Rd: SingleCellExperiment-class, assay, colData
  scaterPCA.Rd: SingleCellExperiment-class, BiocParallelParam-class
  scaterlogNormCounts.Rd: logNormCounts
  sctkListGeneSetCollections.Rd: GeneSetCollection-class
  sctkPythonInstallConda.Rd: conda_install, reticulate, conda_create
  sctkPythonInstallVirtualEnv.Rd: virtualenv_install, reticulate,
    virtualenv_create
  selectSCTKConda.Rd: reticulate
  selectSCTKVirtualEnvironment.Rd: reticulate
  setRowNames.Rd: SingleCellExperiment-class
  setSCTKDisplayRow.Rd: SingleCellExperiment-class
  singleCellTK.Rd: SingleCellExperiment-class
  subsetSCECols.Rd: SingleCellExperiment-class
  subsetSCERows.Rd: SingleCellExperiment-class, altExp
  summarizeSCE.Rd: SingleCellExperiment-class
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                           user system elapsed
importGeneSetsFromMSigDB 49.936  0.514  50.748
plotDoubletFinderResults 43.284  0.268  43.740
runDoubletFinder         36.868  0.244  37.326
plotScDblFinderResults   32.929  0.844  33.934
runScDblFinder           20.330  0.449  20.910
importExampleData        14.272  1.894  17.255
plotBatchCorrCompare     14.675  0.151  14.903
plotScdsHybridResults    10.896  0.162  11.110
plotBcdsResults           9.918  0.191  10.162
plotDecontXResults        9.386  0.085   9.523
plotCxdsResults           8.143  0.075   8.251
plotUMAP                  7.965  0.097   8.114
runUMAP                   7.681  0.089   7.797
runDecontX                7.640  0.078   7.782
plotDEGRegression         6.966  0.082   7.084
detectCellOutlier         6.313  0.138   6.478
plotDEGViolin             6.192  0.099   6.325
plotEmptyDropsResults     5.995  0.034   6.058
plotEmptyDropsScatter     5.897  0.031   5.953
plotTSCANClusterDEG       5.804  0.096   5.939
runEmptyDrops             5.676  0.026   5.724
convertSCEToSeurat        4.740  0.249   5.014
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘spelling.R’
  Running ‘testthat.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.22-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.

Installation output

singleCellTK.Rcheck/00install.out

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.20.0’
** using staged installation
** R
** data
** exec
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (singleCellTK)

Tests output

singleCellTK.Rcheck/tests/spelling.Rout


R version 4.5.1 Patched (2025-09-10 r88807) -- "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 
  0.208   0.077   0.291

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.1 Patched (2025-09-10 r88807) -- "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: Seqinfo
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'Biobase'

The following object is masked from 'package:MatrixGenerics':

    rowMedians

The following objects are masked from 'package:matrixStats':

    anyMissing, rowMedians

Loading required package: SingleCellExperiment
Loading required package: DelayedArray
Loading required package: Matrix

Attaching package: 'Matrix'

The following object is masked from 'package:S4Vectors':

    expand

Loading required package: S4Arrays
Loading required package: abind

Attaching package: 'S4Arrays'

The following object is masked from 'package:abind':

    abind

The following object is masked from 'package:base':

    rowsum

Loading required package: SparseArray

Attaching package: 'DelayedArray'

The following objects are masked from 'package:base':

    apply, scale, sweep


Attaching package: 'singleCellTK'

The following object is masked from 'package:BiocGenerics':

    plotPCA

> 
> test_check("singleCellTK")
Found 2 batches
Using null model in ComBat-seq.
Adjusting for 0 covariate(s) or covariate level(s)
Estimating dispersions
Fitting the GLM model
Shrinkage off - using GLM estimates for parameters
Adjusting the data
Found 2 batches
Using null model in ComBat-seq.
Adjusting for 1 covariate(s) or covariate level(s)
Estimating dispersions
Fitting the GLM model
Shrinkage off - using GLM estimates for parameters
Adjusting the data
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Uploading data to Enrichr... Done.
  Querying HDSigDB_Human_2021... Done.
Parsing results... Done.
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
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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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[----|----|----|----|----|----|----|----|----|----|
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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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Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
324.038   6.765 338.350

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.003	0.003	0.005
SEG	0.003	0.002	0.005
calcEffectSizes	0.215	0.012	0.227
combineSCE	0.843	0.019	0.869
computeZScore	0.234	0.009	0.245
convertSCEToSeurat	4.740	0.249	5.014
convertSeuratToSCE	0.375	0.011	0.388
dedupRowNames	0.063	0.004	0.068
detectCellOutlier	6.313	0.138	6.478
diffAbundanceFET	0.061	0.004	0.067
discreteColorPalette	0.008	0.001	0.008
distinctColors	0.002	0.000	0.002
downSampleCells	0.552	0.065	0.620
downSampleDepth	0.438	0.037	0.478
expData-ANY-character-method	0.146	0.005	0.152
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.190	0.007	0.199
expData-set	0.167	0.007	0.175
expData	0.143	0.005	0.148
expDataNames-ANY-method	0.158	0.010	0.168
expDataNames	0.149	0.014	0.164
expDeleteDataTag	0.039	0.003	0.043
expSetDataTag	0.031	0.003	0.033
expTaggedData	0.033	0.004	0.037
exportSCE	0.027	0.005	0.032
exportSCEtoAnnData	0.074	0.004	0.079
exportSCEtoFlatFile	0.070	0.004	0.074
featureIndex	0.046	0.005	0.051
generateSimulatedData	0.064	0.006	0.070
getBiomarker	0.062	0.006	0.068
getDEGTopTable	0.736	0.066	0.806
getDiffAbundanceResults	0.052	0.003	0.055
getEnrichRResult	0.317	0.046	3.471
getFindMarkerTopTable	1.688	0.061	1.756
getMSigDBTable	0.005	0.004	0.010
getPathwayResultNames	0.028	0.004	0.031
getSampleSummaryStatsTable	0.219	0.007	0.226
getSoupX	0.000	0.001	0.001
getTSCANResults	1.141	0.052	1.198
getTopHVG	0.931	0.018	0.955
importAnnData	0.002	0.001	0.002
importBUStools	0.165	0.004	0.171
importCellRanger	0.810	0.035	0.858
importCellRangerV2Sample	0.158	0.003	0.161
importCellRangerV3Sample	0.318	0.015	0.337
importDropEst	0.231	0.004	0.235
importExampleData	14.272	1.894	17.255
importGeneSetsFromCollection	1.908	0.144	2.064
importGeneSetsFromGMT	0.071	0.005	0.077
importGeneSetsFromList	0.151	0.005	0.158
importGeneSetsFromMSigDB	49.936	0.514	50.748
importMitoGeneSet	0.059	0.008	0.066
importOptimus	0.003	0.001	0.002
importSEQC	0.160	0.010	0.171
importSTARsolo	0.169	0.017	0.189
iterateSimulations	0.198	0.021	0.224
listSampleSummaryStatsTables	0.286	0.026	0.313
mergeSCEColData	0.437	0.028	0.469
mouseBrainSubsetSCE	0.044	0.005	0.049
msigdb_table	0.002	0.002	0.004
plotBarcodeRankDropsResults	0.954	0.041	1.004
plotBarcodeRankScatter	0.928	0.017	0.950
plotBatchCorrCompare	14.675	0.151	14.903
plotBatchVariance	0.599	0.012	0.614
plotBcdsResults	9.918	0.191	10.162
plotBubble	0.860	0.012	0.875
plotClusterAbundance	1.592	0.013	1.614
plotCxdsResults	8.143	0.075	8.251
plotDEGHeatmap	2.322	0.029	2.359
plotDEGRegression	6.966	0.082	7.084
plotDEGViolin	6.192	0.099	6.325
plotDEGVolcano	1.075	0.015	1.098
plotDecontXResults	9.386	0.085	9.523
plotDimRed	0.330	0.006	0.337
plotDoubletFinderResults	43.284	0.268	43.740
plotEmptyDropsResults	5.995	0.034	6.058
plotEmptyDropsScatter	5.897	0.031	5.953
plotFindMarkerHeatmap	4.416	0.034	4.476
plotMASTThresholdGenes	1.566	0.040	1.618
plotPCA	0.438	0.010	0.452
plotPathway	0.819	0.013	0.838
plotRunPerCellQCResults	3.631	0.031	3.687
plotSCEBarAssayData	0.397	0.009	0.412
plotSCEBarColData	0.276	0.006	0.285
plotSCEBatchFeatureMean	0.477	0.006	0.488
plotSCEDensity	0.372	0.007	0.381
plotSCEDensityAssayData	0.351	0.008	0.361
plotSCEDensityColData	0.346	0.008	0.357
plotSCEDimReduceColData	0.937	0.014	0.967
plotSCEDimReduceFeatures	0.450	0.008	0.461
plotSCEHeatmap	0.491	0.012	0.512
plotSCEScatter	0.480	0.010	0.495
plotSCEViolin	0.491	0.010	0.506
plotSCEViolinAssayData	0.444	0.008	0.454
plotSCEViolinColData	0.437	0.007	0.447
plotScDblFinderResults	32.929	0.844	33.934
plotScanpyDotPlot	0.027	0.003	0.031
plotScanpyEmbedding	0.032	0.004	0.036
plotScanpyHVG	0.029	0.004	0.034
plotScanpyHeatmap	0.027	0.006	0.034
plotScanpyMarkerGenes	0.027	0.003	0.032
plotScanpyMarkerGenesDotPlot	0.029	0.005	0.034
plotScanpyMarkerGenesHeatmap	0.029	0.003	0.033
plotScanpyMarkerGenesMatrixPlot	0.031	0.006	0.037
plotScanpyMarkerGenesViolin	0.030	0.004	0.033
plotScanpyMatrixPlot	0.028	0.005	0.034
plotScanpyPCA	0.028	0.003	0.031
plotScanpyPCAGeneRanking	0.027	0.003	0.030
plotScanpyPCAVariance	0.029	0.004	0.032
plotScanpyViolin	0.031	0.004	0.035
plotScdsHybridResults	10.896	0.162	11.110
plotScrubletResults	0.029	0.003	0.031
plotSeuratElbow	0.024	0.005	0.029
plotSeuratHVG	0.032	0.004	0.036
plotSeuratJackStraw	0.030	0.003	0.034
plotSeuratReduction	0.030	0.005	0.035
plotSoupXResults	0	0	0
plotTSCANClusterDEG	5.804	0.096	5.939
plotTSCANClusterPseudo	1.608	0.030	1.648
plotTSCANDimReduceFeatures	1.701	0.029	1.743
plotTSCANPseudotimeGenes	2.041	0.031	2.095
plotTSCANPseudotimeHeatmap	1.602	0.031	1.646
plotTSCANResults	1.524	0.032	1.569
plotTSNE	0.443	0.012	0.458
plotTopHVG	0.685	0.012	0.701
plotUMAP	7.965	0.097	8.114
readSingleCellMatrix	0.007	0.002	0.008
reportCellQC	0.100	0.005	0.106
reportDropletQC	0.028	0.006	0.034
reportQCTool	0.097	0.005	0.104
retrieveSCEIndex	0.035	0.003	0.038
runBBKNN	0	0	0
runBarcodeRankDrops	0.254	0.007	0.263
runBcds	1.825	0.055	1.892
runCellQC	0.095	0.005	0.102
runClusterSummaryMetrics	0.467	0.017	0.486
runComBatSeq	0.517	0.022	0.546
runCxds	0.393	0.013	0.409
runCxdsBcdsHybrid	1.836	0.083	1.933
runDEAnalysis	0.504	0.062	0.571
runDecontX	7.640	0.078	7.782
runDimReduce	0.303	0.009	0.314
runDoubletFinder	36.868	0.244	37.326
runDropletQC	0.028	0.004	0.032
runEmptyDrops	5.676	0.026	5.724
runEnrichR	0.290	0.033	3.484
runFastMNN	1.906	0.048	1.967
runFeatureSelection	0.237	0.005	0.244
runFindMarker	1.654	0.040	1.703
runGSVA	0.766	0.050	0.821
runHarmony	0.049	0.002	0.050
runKMeans	0.312	0.022	0.335
runLimmaBC	0.091	0.002	0.093
runMNNCorrect	0.486	0.006	0.496
runModelGeneVar	0.374	0.008	0.384
runNormalization	2.695	0.049	2.761
runPerCellQC	0.407	0.012	0.421
runSCANORAMA	0	0	0
runSCMerge	0.005	0.002	0.007
runScDblFinder	20.330	0.449	20.910
runScanpyFindClusters	0.028	0.004	0.032
runScanpyFindHVG	0.030	0.002	0.031
runScanpyFindMarkers	0.029	0.004	0.032
runScanpyNormalizeData	0.120	0.007	0.127
runScanpyPCA	0.028	0.003	0.032
runScanpyScaleData	0.030	0.004	0.034
runScanpyTSNE	0.030	0.004	0.033
runScanpyUMAP	0.032	0.003	0.036
runScranSNN	0.349	0.013	0.364
runScrublet	0.027	0.004	0.030
runSeuratFindClusters	0.022	0.004	0.026
runSeuratFindHVG	0.528	0.011	0.542
runSeuratHeatmap	0.026	0.006	0.032
runSeuratICA	0.027	0.003	0.031
runSeuratJackStraw	0.026	0.007	0.032
runSeuratNormalizeData	0.028	0.004	0.031
runSeuratPCA	0.029	0.006	0.035
runSeuratSCTransform	3.995	0.069	4.089
runSeuratScaleData	0.032	0.005	0.038
runSeuratUMAP	0.031	0.005	0.037
runSingleR	0.047	0.002	0.050
runSoupX	0	0	0
runTSCAN	0.778	0.018	0.801
runTSCANClusterDEAnalysis	0.810	0.017	0.830
runTSCANDEG	0.804	0.025	0.834
runTSNE	0.655	0.017	0.675
runUMAP	7.681	0.089	7.797
runVAM	0.324	0.008	0.333
runZINBWaVE	0.003	0.001	0.004
sampleSummaryStats	0.180	0.007	0.187
scaterCPM	0.116	0.006	0.123
scaterPCA	0.515	0.008	0.525
scaterlogNormCounts	0.230	0.009	0.241
sce	0.029	0.004	0.034
sctkListGeneSetCollections	0.090	0.009	0.099
sctkPythonInstallConda	0.001	0.001	0.001
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.089	0.002	0.092
setSCTKDisplayRow	0.460	0.012	0.474
singleCellTK	0.000	0.001	0.000
subDiffEx	0.370	0.024	0.396
subsetSCECols	0.093	0.005	0.098
subsetSCERows	0.300	0.020	0.322
summarizeSCE	0.078	0.006	0.084
trimCounts	0.172	0.012	0.185