Build/check report for BioC 3.23 - CHECK results for singleCellTK on nebbiolo1

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo1	Linux (Ubuntu 24.04.3 LTS)	x86_64	R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"	4851
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 nebbiolo1

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: 2.21.1

Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings singleCellTK_2.21.1.tar.gz

StartedAt: 2026-01-29 05:02:05 -0500 (Thu, 29 Jan 2026)

EndedAt: 2026-01-29 05:25:14 -0500 (Thu, 29 Jan 2026)

EllapsedTime: 1389.7 seconds

RetCode: 0

Status: OK

CheckDir: singleCellTK.Rcheck

Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings singleCellTK_2.21.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck’
* using R Under development (unstable) (2026-01-15 r89304)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.21.1’
* 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  5.6Mb
  sub-directories of 1Mb or more:
    R       1.0Mb
    shiny   2.3Mb
* 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 loading without being on the library search path ... 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 45.550  1.407  46.958
plotDoubletFinderResults 40.621  0.416  41.039
runDoubletFinder         36.796  0.164  36.960
runSeuratSCTransform     30.432  1.082  31.515
plotScDblFinderResults   28.470  0.698  29.129
runScDblFinder           18.244  1.362  19.570
plotBatchCorrCompare     13.315  0.265  13.580
importExampleData        11.332  1.037  12.724
plotScdsHybridResults    10.034  0.114   9.578
plotDecontXResults        8.700  0.082   8.782
plotBcdsResults           8.608  0.138   8.181
plotUMAP                  8.079  0.103   8.182
runUMAP                   7.572  0.250   7.821
plotCxdsResults           7.582  0.134   7.716
runDecontX                7.475  0.053   7.530
plotEmptyDropsResults     6.642  0.020   6.662
plotEmptyDropsScatter     6.559  0.011   6.570
runEmptyDrops             6.258  0.012   6.271
plotDEGViolin             5.293  0.067   5.354
detectCellOutlier         5.151  0.194   5.347
runEnrichR                0.599  0.105 152.854
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/home/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.

Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.21.1’
** 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 Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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 
  0.141   0.053   0.182

singleCellTK.Rcheck/tests/testthat.Rout


R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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%
[05:23:02] WARNING: src/learner.cc:790: 
Parameters: { "nthreads" } are not used.

[05:23:03] WARNING: src/learner.cc:790: 
Parameters: { "nthreads" } are not used.

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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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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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Performing log-normalization
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[ FAIL 0 | WARN 19 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 19 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
306.470   8.400 544.522

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0.002	0.001	0.003
SEG	0.003	0.001	0.003
calcEffectSizes	0.153	0.008	0.161
combineSCE	0.692	0.040	0.732
computeZScore	0.23	0.01	0.24
convertSCEToSeurat	4.221	0.162	4.385
convertSeuratToSCE	0.331	0.007	0.339
dedupRowNames	0.054	0.000	0.054
detectCellOutlier	5.151	0.194	5.347
diffAbundanceFET	0.056	0.000	0.056
discreteColorPalette	0.004	0.002	0.006
distinctColors	0.002	0.000	0.003
downSampleCells	0.479	0.039	0.518
downSampleDepth	0.395	0.008	0.402
expData-ANY-character-method	0.121	0.001	0.121
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.154	0.004	0.158
expData-set	0.144	0.001	0.145
expData	0.116	0.002	0.120
expDataNames-ANY-method	0.110	0.001	0.112
expDataNames	0.110	0.008	0.120
expDeleteDataTag	0.034	0.002	0.036
expSetDataTag	0.021	0.003	0.024
expTaggedData	0.024	0.001	0.025
exportSCE	0.019	0.001	0.021
exportSCEtoAnnData	0.090	0.011	0.101
exportSCEtoFlatFile	0.092	0.005	0.097
featureIndex	0.032	0.003	0.035
generateSimulatedData	0.050	0.002	0.052
getBiomarker	0.061	0.003	0.063
getDEGTopTable	0.676	0.109	0.785
getDiffAbundanceResults	0.048	0.000	0.049
getEnrichRResult	0.542	0.037	3.429
getFindMarkerTopTable	1.575	0.074	1.649
getMSigDBTable	0.002	0.003	0.005
getPathwayResultNames	0.021	0.001	0.022
getSampleSummaryStatsTable	0.197	0.007	0.204
getSoupX	0.001	0.000	0.000
getTSCANResults	1.026	0.047	1.073
getTopHVG	0.968	0.011	0.979
importAnnData	0.000	0.001	0.001
importBUStools	0.146	0.003	0.150
importCellRanger	0.893	0.068	0.962
importCellRangerV2Sample	0.159	0.010	0.168
importCellRangerV3Sample	0.278	0.008	0.286
importDropEst	0.217	0.007	0.225
importExampleData	11.332	1.037	12.724
importGeneSetsFromCollection	1.745	0.139	1.883
importGeneSetsFromGMT	0.066	0.002	0.068
importGeneSetsFromList	0.119	0.004	0.121
importGeneSetsFromMSigDB	45.550	1.407	46.958
importMitoGeneSet	0.048	0.007	0.054
importOptimus	0.001	0.001	0.002
importSEQC	0.132	0.023	0.156
importSTARsolo	0.137	0.026	0.163
iterateSimulations	0.167	0.027	0.193
listSampleSummaryStatsTables	0.247	0.036	0.282
mergeSCEColData	0.363	0.022	0.385
mouseBrainSubsetSCE	0.035	0.000	0.036
msigdb_table	0.001	0.000	0.001
plotBarcodeRankDropsResults	0.822	0.013	0.835
plotBarcodeRankScatter	0.854	0.001	0.855
plotBatchCorrCompare	13.315	0.265	13.580
plotBatchVariance	0.463	0.010	0.473
plotBcdsResults	8.608	0.138	8.181
plotBubble	0.832	0.021	0.852
plotClusterAbundance	1.291	0.005	1.297
plotCxdsResults	7.582	0.134	7.716
plotDEGHeatmap	2.070	0.016	2.086
plotDEGRegression	4.501	0.072	4.568
plotDEGViolin	5.293	0.067	5.354
plotDEGVolcano	0.967	0.004	0.972
plotDecontXResults	8.700	0.082	8.782
plotDimRed	0.274	0.010	0.284
plotDoubletFinderResults	40.621	0.416	41.039
plotEmptyDropsResults	6.642	0.020	6.662
plotEmptyDropsScatter	6.559	0.011	6.570
plotFindMarkerHeatmap	3.832	0.049	3.882
plotMASTThresholdGenes	1.249	0.017	1.265
plotPCA	0.357	0.002	0.360
plotPathway	0.688	0.002	0.691
plotRunPerCellQCResults	3.098	0.025	3.124
plotSCEBarAssayData	0.279	0.006	0.285
plotSCEBarColData	0.273	0.014	0.287
plotSCEBatchFeatureMean	0.375	0.001	0.376
plotSCEDensity	0.296	0.000	0.296
plotSCEDensityAssayData	0.272	0.000	0.272
plotSCEDensityColData	0.354	0.000	0.354
plotSCEDimReduceColData	0.731	0.002	0.733
plotSCEDimReduceFeatures	0.369	0.000	0.369
plotSCEHeatmap	0.436	0.002	0.438
plotSCEScatter	0.338	0.002	0.340
plotSCEViolin	0.382	0.000	0.382
plotSCEViolinAssayData	0.435	0.003	0.438
plotSCEViolinColData	0.355	0.001	0.357
plotScDblFinderResults	28.470	0.698	29.129
plotScanpyDotPlot	0.023	0.000	0.023
plotScanpyEmbedding	0.022	0.000	0.022
plotScanpyHVG	0.022	0.000	0.022
plotScanpyHeatmap	0.021	0.000	0.021
plotScanpyMarkerGenes	0.022	0.000	0.022
plotScanpyMarkerGenesDotPlot	0.020	0.001	0.021
plotScanpyMarkerGenesHeatmap	0.023	0.000	0.023
plotScanpyMarkerGenesMatrixPlot	0.021	0.000	0.021
plotScanpyMarkerGenesViolin	0.022	0.000	0.022
plotScanpyMatrixPlot	0.020	0.001	0.022
plotScanpyPCA	0.021	0.000	0.021
plotScanpyPCAGeneRanking	0.022	0.001	0.023
plotScanpyPCAVariance	0.022	0.000	0.022
plotScanpyViolin	0.020	0.002	0.022
plotScdsHybridResults	10.034	0.114	9.578
plotScrubletResults	0.022	0.000	0.022
plotSeuratElbow	0.021	0.000	0.022
plotSeuratHVG	0.022	0.000	0.022
plotSeuratJackStraw	0.023	0.000	0.023
plotSeuratReduction	0.023	0.000	0.024
plotSoupXResults	0	0	0
plotTSCANClusterDEG	4.815	0.008	4.823
plotTSCANClusterPseudo	1.341	0.004	1.345
plotTSCANDimReduceFeatures	1.408	0.005	1.413
plotTSCANPseudotimeGenes	1.659	0.004	1.663
plotTSCANPseudotimeHeatmap	1.331	0.004	1.335
plotTSCANResults	1.289	0.007	1.296
plotTSNE	0.370	0.001	0.371
plotTopHVG	0.614	0.000	0.614
plotUMAP	8.079	0.103	8.182
readSingleCellMatrix	0.004	0.001	0.005
reportCellQC	0.085	0.002	0.087
reportDropletQC	0.023	0.000	0.023
reportQCTool	0.077	0.002	0.079
retrieveSCEIndex	0.027	0.000	0.027
runBBKNN	0.000	0.001	0.000
runBarcodeRankDrops	0.214	0.000	0.214
runBcds	1.419	0.013	0.893
runCellQC	0.083	0.000	0.083
runClusterSummaryMetrics	0.395	0.002	0.396
runComBatSeq	0.428	0.003	0.431
runCxds	0.322	0.003	0.326
runCxdsBcdsHybrid	1.479	0.043	0.970
runDEAnalysis	0.496	0.002	0.497
runDecontX	7.475	0.053	7.530
runDimReduce	0.282	0.002	0.283
runDoubletFinder	36.796	0.164	36.960
runDropletQC	0.022	0.001	0.022
runEmptyDrops	6.258	0.012	6.271
runEnrichR	0.599	0.105	152.854
runFastMNN	1.751	0.221	1.973
runFeatureSelection	0.216	0.017	0.233
runFindMarker	1.428	0.149	1.579
runGSVA	0.816	0.125	0.942
runHarmony	0.146	0.045	0.191
runKMeans	0.196	0.018	0.215
runLimmaBC	0.083	0.009	0.093
runMNNCorrect	0.415	0.052	0.467
runModelGeneVar	0.313	0.042	0.356
runNormalization	2.736	0.734	3.471
runPerCellQC	0.329	0.013	0.342
runSCANORAMA	0.000	0.001	0.000
runSCMerge	0.003	0.001	0.004
runScDblFinder	18.244	1.362	19.570
runScanpyFindClusters	0.022	0.001	0.023
runScanpyFindHVG	0.022	0.001	0.022
runScanpyFindMarkers	0.021	0.001	0.022
runScanpyNormalizeData	0.093	0.000	0.093
runScanpyPCA	0.020	0.001	0.022
runScanpyScaleData	0.021	0.001	0.022
runScanpyTSNE	0.021	0.000	0.022
runScanpyUMAP	0.021	0.001	0.022
runScranSNN	0.290	0.002	0.292
runScrublet	0.023	0.001	0.024
runSeuratFindClusters	0.021	0.001	0.023
runSeuratFindHVG	0.477	0.002	0.479
runSeuratHeatmap	0.023	0.000	0.023
runSeuratICA	0.021	0.000	0.022
runSeuratJackStraw	0.022	0.000	0.022
runSeuratNormalizeData	0.019	0.003	0.022
runSeuratPCA	0.022	0.001	0.023
runSeuratSCTransform	30.432	1.082	31.515
runSeuratScaleData	0.021	0.003	0.024
runSeuratUMAP	0.022	0.000	0.022
runSingleR	0.037	0.000	0.037
runSoupX	0	0	0
runTSCAN	0.668	0.014	0.682
runTSCANClusterDEAnalysis	0.762	0.014	0.777
runTSCANDEG	0.762	0.026	0.788
runTSNE	0.721	0.004	0.725
runUMAP	7.572	0.250	7.821
runVAM	0.289	0.003	0.292
runZINBWaVE	0.004	0.000	0.004
sampleSummaryStats	0.152	0.001	0.152
scaterCPM	0.135	0.005	0.140
scaterPCA	0.438	0.004	0.444
scaterlogNormCounts	0.231	0.010	0.241
sce	0.022	0.001	0.023
sctkListGeneSetCollections	0.081	0.002	0.082
sctkPythonInstallConda	0	0	0
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0.001	0.000	0.001
setRowNames	0.081	0.001	0.082
setSCTKDisplayRow	0.421	0.014	0.435
singleCellTK	0.000	0.000	0.001
subDiffEx	0.328	0.007	0.335
subsetSCECols	0.08	0.00	0.08
subsetSCERows	0.262	0.011	0.273
summarizeSCE	0.067	0.001	0.068
trimCounts	0.204	0.005	0.209