Back to Build/check report for BioC 3.23:   simplified   long
ABCDEFGHIJKLMNOPQR[S]TUVWXYZ

This page was generated on 2025-11-05 11:32 -0500 (Wed, 05 Nov 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.3 LTS)x86_64R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences" 4818
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 1999/2323HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.21.0  (landing page)
Joshua David Campbell
Snapshot Date: 2025-11-04 13:40 -0500 (Tue, 04 Nov 2025)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: devel
git_last_commit: 4895b66
git_last_commit_date: 2025-10-29 11:29:49 -0500 (Wed, 29 Oct 2025)
nebbiolo1Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    OK  YES


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: 2.21.0
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_2.21.0.tar.gz
StartedAt: 2025-11-05 03:51:12 -0500 (Wed, 05 Nov 2025)
EndedAt: 2025-11-05 04:08:22 -0500 (Wed, 05 Nov 2025)
EllapsedTime: 1030.1 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_2.21.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck’
* using R Under development (unstable) (2025-10-20 r88955)
* 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 ‘2.21.0’
* 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  5.6Mb
  sub-directories of 1Mb or more:
    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 45.933  1.886  47.822
plotDoubletFinderResults 40.637  0.524  41.163
runDoubletFinder         38.437  0.214  38.660
plotScDblFinderResults   30.868  0.796  31.303
runSeuratSCTransform     28.992  0.233  29.227
runScDblFinder           20.736  0.579  20.984
importExampleData        12.213  2.382  14.927
plotBatchCorrCompare     13.523  0.274  13.797
plotScdsHybridResults    11.563  0.127  10.870
plotBcdsResults           9.187  0.270   8.662
plotDecontXResults        8.863  0.209   9.073
runUMAP                   8.566  0.117   8.685
plotUMAP                  7.866  0.135   8.002
plotCxdsResults           7.879  0.110   7.990
runDecontX                7.832  0.098   7.931
plotEmptyDropsResults     6.663  0.027   6.691
plotEmptyDropsScatter     6.551  0.028   6.580
runEmptyDrops             6.275  0.006   6.281
plotDEGViolin             5.508  0.170   5.672
detectCellOutlier         5.243  0.167   5.412
* 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 ‘2.21.0’
** 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 Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
Copyright (C) 2025 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 
  0.152   0.036   0.176 

singleCellTK.Rcheck/tests/testthat.Rout


R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
Copyright (C) 2025 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%
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%
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
311.729   7.204 322.653 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0030.0000.002
SEG0.0000.0010.003
calcEffectSizes0.1570.0110.166
combineSCE0.7220.0330.755
computeZScore0.2340.0080.243
convertSCEToSeurat4.1810.1274.310
convertSeuratToSCE0.3060.0110.318
dedupRowNames0.0580.0010.059
detectCellOutlier5.2430.1675.412
diffAbundanceFET0.0520.0020.056
discreteColorPalette0.0060.0000.006
distinctColors0.0030.0000.002
downSampleCells0.4940.0690.563
downSampleDepth0.3860.0080.394
expData-ANY-character-method0.120.000.12
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1580.0000.157
expData-set0.1460.0000.146
expData0.1210.0030.123
expDataNames-ANY-method0.1140.0010.116
expDataNames0.1170.0020.119
expDeleteDataTag0.0320.0000.033
expSetDataTag0.0240.0000.026
expTaggedData0.0260.0020.027
exportSCE0.0220.0000.023
exportSCEtoAnnData0.0910.0060.098
exportSCEtoFlatFile0.0920.0050.098
featureIndex0.0370.0010.037
generateSimulatedData0.0500.0050.054
getBiomarker0.0550.0060.062
getDEGTopTable0.7000.0890.791
getDiffAbundanceResults0.050.000.05
getEnrichRResult0.5830.0493.364
getFindMarkerTopTable1.4950.0901.586
getMSigDBTable0.0030.0010.004
getPathwayResultNames0.0220.0010.022
getSampleSummaryStatsTable0.1760.0060.182
getSoupX000
getTSCANResults1.0520.0431.095
getTopHVG0.8280.0110.841
importAnnData0.0020.0000.002
importBUStools0.1890.0020.193
importCellRanger0.7050.0520.757
importCellRangerV2Sample0.1400.0120.153
importCellRangerV3Sample0.3640.0320.397
importDropEst0.1880.0010.190
importExampleData12.213 2.38214.927
importGeneSetsFromCollection0.7060.0290.735
importGeneSetsFromGMT0.0630.0010.065
importGeneSetsFromList0.1270.0020.130
importGeneSetsFromMSigDB45.933 1.88647.822
importMitoGeneSet0.0510.0030.054
importOptimus0.0020.0000.002
importSEQC0.1380.0160.156
importSTARsolo0.1450.0200.166
iterateSimulations0.1800.0210.201
listSampleSummaryStatsTables0.2490.0380.287
mergeSCEColData0.3730.0290.402
mouseBrainSubsetSCE0.0360.0010.037
msigdb_table0.0020.0000.002
plotBarcodeRankDropsResults0.8570.0480.905
plotBarcodeRankScatter0.8410.0180.859
plotBatchCorrCompare13.523 0.27413.797
plotBatchVariance0.4720.0040.476
plotBcdsResults9.1870.2708.662
plotBubble0.7790.0070.786
plotClusterAbundance1.3710.0021.373
plotCxdsResults7.8790.1107.990
plotDEGHeatmap2.1670.0482.214
plotDEGRegression4.5600.0334.589
plotDEGViolin5.5080.1705.672
plotDEGVolcano1.0360.0201.055
plotDecontXResults8.8630.2099.073
plotDimRed0.3090.0010.310
plotDoubletFinderResults40.637 0.52441.163
plotEmptyDropsResults6.6630.0276.691
plotEmptyDropsScatter6.5510.0286.580
plotFindMarkerHeatmap3.6650.0623.727
plotMASTThresholdGenes1.2780.0551.334
plotPCA0.3600.0340.394
plotPathway0.7040.0480.752
plotRunPerCellQCResults3.0680.0613.129
plotSCEBarAssayData0.2720.0020.274
plotSCEBarColData0.2700.0020.272
plotSCEBatchFeatureMean0.3740.0000.374
plotSCEDensity0.2950.0040.299
plotSCEDensityAssayData0.2620.0030.265
plotSCEDensityColData0.3340.0030.337
plotSCEDimReduceColData0.7210.0040.724
plotSCEDimReduceFeatures0.4050.0120.417
plotSCEHeatmap0.4140.0100.425
plotSCEScatter0.3480.0030.352
plotSCEViolin0.3620.0180.381
plotSCEViolinAssayData0.4090.0040.412
plotSCEViolinColData0.3480.0010.349
plotScDblFinderResults30.868 0.79631.303
plotScanpyDotPlot0.0220.0000.022
plotScanpyEmbedding0.0230.0080.031
plotScanpyHVG0.0220.0000.022
plotScanpyHeatmap0.0220.0000.022
plotScanpyMarkerGenes0.0220.0000.022
plotScanpyMarkerGenesDotPlot0.0220.0000.022
plotScanpyMarkerGenesHeatmap0.0220.0000.022
plotScanpyMarkerGenesMatrixPlot0.0220.0010.023
plotScanpyMarkerGenesViolin0.0220.0010.022
plotScanpyMatrixPlot0.0220.0000.022
plotScanpyPCA0.0220.0000.022
plotScanpyPCAGeneRanking0.0230.0000.023
plotScanpyPCAVariance0.0210.0010.023
plotScanpyViolin0.0210.0010.023
plotScdsHybridResults11.563 0.12710.870
plotScrubletResults0.0220.0010.023
plotSeuratElbow0.0220.0010.023
plotSeuratHVG0.0220.0000.022
plotSeuratJackStraw0.0220.0000.022
plotSeuratReduction0.0220.0000.022
plotSoupXResults0.0000.0000.001
plotTSCANClusterDEG4.9480.0144.963
plotTSCANClusterPseudo1.3080.0071.315
plotTSCANDimReduceFeatures1.4440.0071.451
plotTSCANPseudotimeGenes1.7290.0011.731
plotTSCANPseudotimeHeatmap1.3710.0021.373
plotTSCANResults1.2760.0231.299
plotTSNE0.3720.0020.374
plotTopHVG0.6290.0000.629
plotUMAP7.8660.1358.002
readSingleCellMatrix0.0060.0000.005
reportCellQC0.0850.0010.087
reportDropletQC0.0220.0000.023
reportQCTool0.0810.0010.081
retrieveSCEIndex0.0290.0010.029
runBBKNN000
runBarcodeRankDrops0.2290.0010.230
runBcds1.9880.0201.204
runCellQC0.0830.0000.082
runClusterSummaryMetrics0.3960.0260.422
runComBatSeq0.4410.0060.447
runCxds0.3200.0020.322
runCxdsBcdsHybrid2.0430.0631.277
runDEAnalysis0.4280.0120.440
runDecontX7.8320.0987.931
runDimReduce0.2860.0010.287
runDoubletFinder38.437 0.21438.660
runDropletQC0.0230.0000.023
runEmptyDrops6.2750.0066.281
runEnrichR0.5510.0162.662
runFastMNN1.6880.0091.698
runFeatureSelection0.2100.0030.212
runFindMarker1.4080.0131.422
runGSVA0.6720.0090.681
runHarmony0.040.000.04
runKMeans0.2480.0020.249
runLimmaBC0.0780.0000.078
runMNNCorrect0.4020.0020.404
runModelGeneVar0.3010.0140.315
runNormalization2.5420.0582.599
runPerCellQC0.3190.0010.320
runSCANORAMA0.0010.0000.000
runSCMerge0.0030.0010.005
runScDblFinder20.736 0.57920.984
runScanpyFindClusters0.0230.0010.023
runScanpyFindHVG0.0220.0010.023
runScanpyFindMarkers0.0220.0000.022
runScanpyNormalizeData0.0900.0040.095
runScanpyPCA0.0220.0010.023
runScanpyScaleData0.0220.0000.023
runScanpyTSNE0.0200.0020.023
runScanpyUMAP0.0210.0020.022
runScranSNN0.2910.0030.294
runScrublet0.0210.0010.022
runSeuratFindClusters0.0220.0010.023
runSeuratFindHVG0.4590.0030.461
runSeuratHeatmap0.0220.0000.023
runSeuratICA0.0230.0000.022
runSeuratJackStraw0.0210.0010.022
runSeuratNormalizeData0.0220.0000.022
runSeuratPCA0.0230.0000.023
runSeuratSCTransform28.992 0.23329.227
runSeuratScaleData0.0200.0040.025
runSeuratUMAP0.0220.0010.023
runSingleR0.0380.0010.040
runSoupX000
runTSCAN0.6690.0070.676
runTSCANClusterDEAnalysis0.7660.0080.774
runTSCANDEG0.7890.0210.811
runTSNE0.7160.0100.726
runUMAP8.5660.1178.685
runVAM0.2940.0020.295
runZINBWaVE0.0050.0000.005
sampleSummaryStats0.1530.0010.154
scaterCPM0.1300.0070.136
scaterPCA0.4330.0020.435
scaterlogNormCounts0.2300.0060.237
sce0.0220.0000.022
sctkListGeneSetCollections0.0830.0000.083
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv0.0000.0000.001
selectSCTKConda0.0000.0010.000
selectSCTKVirtualEnvironment000
setRowNames0.0840.0010.084
setSCTKDisplayRow0.4400.0030.443
singleCellTK000
subDiffEx0.3370.0030.341
subsetSCECols0.0790.0040.084
subsetSCERows0.2860.0240.310
summarizeSCE0.0690.0030.073
trimCounts0.2170.0090.226