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

This page was generated on 2026-05-19 11:33 -0400 (Tue, 19 May 2026).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.4 LTS)x86_644.6.0 RC (2026-04-17 r89917) -- "Because it was There" 4995
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 2081/2418HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.22.0  (landing page)
Joshua David Campbell
Snapshot Date: 2026-05-18 13:40 -0400 (Mon, 18 May 2026)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_23
git_last_commit: 1867491
git_last_commit_date: 2026-04-28 09:03:00 -0400 (Tue, 28 Apr 2026)
nebbiolo1Linux (Ubuntu 24.04.4 LTS) / x86_64  OK    OK    WARNINGS  UNNEEDED, same version is already published
See other builds for singleCellTK in R Universe.


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: 2.22.0
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_2.22.0.tar.gz
StartedAt: 2026-05-19 04:58:08 -0400 (Tue, 19 May 2026)
EndedAt: 2026-05-19 05:14:11 -0400 (Tue, 19 May 2026)
EllapsedTime: 963.2 seconds
RetCode: 0
Status:   WARNINGS  
CheckDir: singleCellTK.Rcheck
Warnings: 3

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_2.22.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-05-19 08:58:08 UTC
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.22.0’
* 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:
    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 ... WARNING
Missing or unexported object: 'harmony::HarmonyMatrix'
* 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 ... WARNING
Missing link(s) in Rd file 'runHarmony.Rd':
  ‘[harmony]{HarmonyMatrix}’

See section 'Cross-references' in the 'Writing R Extensions' manual.

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 ... WARNING
Found the following significant warnings:

  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'librarySizeFactors' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in fitTrendVar(fm, fv, ...) : 'fitTrendVar' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in fitTrendVar(fm, fv, ...) : 'fitTrendVar' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'pairwiseWilcox' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'sumCountsAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'summarizeAssayByGroup' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in fitTrendVar(fm, fv, ...) : 'fitTrendVar' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'librarySizeFactors' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'aggregateAcrossCells' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
  Warning in fitTrendVar(fm, fv, ...) : 'fitTrendVar' is deprecated.
  Warning in .local(x, ...) : 'normalizeCounts' is deprecated.
Deprecated functions may be defunct as soon as of the next release of
R.
See ?Deprecated.
Examples with CPU (user + system) or elapsed time > 5s
                           user system elapsed
plotDoubletFinderResults 32.727  0.192  32.923
runDoubletFinder         32.306  0.115  32.424
runSeuratSCTransform     29.280  0.289  29.571
plotScDblFinderResults   28.562  0.436  26.058
runScDblFinder           15.829  0.804  13.706
importExampleData        10.816  2.117  13.265
plotBatchCorrCompare     11.867  0.363  12.231
plotScdsHybridResults     9.327  0.086   8.839
plotBcdsResults           8.355  0.265   8.000
plotDecontXResults        7.412  0.141   7.553
runUMAP                   7.079  0.133   7.211
plotCxdsResults           6.948  0.092   7.042
plotEmptyDropsScatter     6.649  0.002   6.652
plotEmptyDropsResults     6.625  0.001   6.627
runDecontX                6.380  0.002   6.383
plotUMAP                  6.356  0.015   6.371
runEmptyDrops             6.312  0.012   6.324
detectCellOutlier         5.946  0.159   6.106
plotTSCANClusterDEG       6.059  0.004   6.065
plotDEGViolin             5.114  0.044   5.306
convertSCEToSeurat        4.781  0.312   5.092
* 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: 3 WARNINGs
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 ‘2.22.0’
** 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 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
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 
  0.147   0.035   0.171 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
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%
[05:11:57] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

[05:11:58] WARNING: src/learner.cc:782: 
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   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 84 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 84 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
275.514   8.318 282.227 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0010.0010.003
SEG0.0020.0000.003
calcEffectSizes0.1550.0050.159
combineSCE0.7590.0960.855
computeZScore0.2810.0110.291
convertSCEToSeurat4.7810.3125.092
convertSeuratToSCE0.3120.0020.314
dedupRowNames0.0550.0010.056
detectCellOutlier5.9460.1596.106
diffAbundanceFET0.0520.0020.055
discreteColorPalette0.0060.0000.006
distinctColors0.0010.0010.003
downSampleCells0.5090.0100.519
downSampleDepth0.4040.0330.437
expData-ANY-character-method0.1190.0030.123
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1560.0070.163
expData-set0.1480.0030.152
expData0.1190.0000.119
expDataNames-ANY-method0.1120.0000.112
expDataNames0.1110.0020.112
expDeleteDataTag0.0320.0010.033
expSetDataTag0.0230.0000.024
expTaggedData0.0240.0010.026
exportSCE0.0200.0010.022
exportSCEtoAnnData0.0900.0070.097
exportSCEtoFlatFile0.0910.0050.095
featureIndex0.0340.0020.036
generateSimulatedData0.0500.0010.051
getBiomarker0.0580.0010.059
getDEGTopTable0.690.060.75
getDiffAbundanceResults0.0450.0010.046
getEnrichRResult0.5390.0312.808
getFindMarkerTopTable1.5690.1131.682
getMSigDBTable0.0020.0020.004
getPathwayResultNames0.0220.0010.024
getSampleSummaryStatsTable0.2790.0190.297
getSoupX0.0010.0000.000
getTSCANResults1.1430.0951.239
getTopHVG0.7310.0560.787
importAnnData0.0020.0000.001
importBUStools0.1570.0210.178
importCellRanger0.8410.0720.915
importCellRangerV2Sample0.1560.0060.161
importCellRangerV3Sample0.2930.0160.309
importDropEst0.1940.0040.198
importExampleData10.816 2.11713.265
importGeneSetsFromCollection0.0740.0020.075
importGeneSetsFromGMT0.0610.0020.063
importGeneSetsFromList0.1210.0020.123
importGeneSetsFromMSigDB2.2360.1412.376
importMitoGeneSet0.0480.0020.050
importOptimus0.0010.0000.002
importSEQC0.1050.0020.108
importSTARsolo0.1350.0010.137
iterateSimulations0.1700.0020.171
listSampleSummaryStatsTables0.2900.0010.290
mergeSCEColData0.3270.0030.330
mouseBrainSubsetSCE0.0350.0010.036
msigdb_table0.0010.0010.001
plotBarcodeRankDropsResults0.8830.0090.893
plotBarcodeRankScatter0.8130.0240.838
plotBatchCorrCompare11.867 0.36312.231
plotBatchVariance0.4500.0780.528
plotBcdsResults8.3550.2658.000
plotBubble0.8390.0040.844
plotClusterAbundance1.3150.0031.317
plotCxdsResults6.9480.0927.042
plotDEGHeatmap2.1090.0072.116
plotDEGRegression4.2530.0454.290
plotDEGViolin5.1140.0445.306
plotDEGVolcano0.9040.0160.920
plotDecontXResults7.4120.1417.553
plotDimRed0.2700.0090.279
plotDoubletFinderResults32.727 0.19232.923
plotEmptyDropsResults6.6250.0016.627
plotEmptyDropsScatter6.6490.0026.652
plotFindMarkerHeatmap3.6780.0203.697
plotMASTThresholdGenes1.1660.0171.183
plotPCA0.3580.0040.362
plotPathway0.6520.0020.655
plotRunPerCellQCResults2.8890.0042.893
plotSCEBarAssayData0.2660.0010.267
plotSCEBarColData0.2110.0010.212
plotSCEBatchFeatureMean0.3730.0020.375
plotSCEDensity0.2920.0010.293
plotSCEDensityAssayData0.2640.0010.265
plotSCEDensityColData0.3160.0010.318
plotSCEDimReduceColData0.6980.0090.708
plotSCEDimReduceFeatures0.3660.0040.369
plotSCEHeatmap0.4420.0040.447
plotSCEScatter0.3450.0070.352
plotSCEViolin0.3390.0020.341
plotSCEViolinAssayData0.3710.0140.385
plotSCEViolinColData0.3500.0030.352
plotScDblFinderResults28.562 0.43626.058
plotScanpyDotPlot0.0220.0010.022
plotScanpyEmbedding0.0210.0010.022
plotScanpyHVG0.0220.0010.023
plotScanpyHeatmap0.0220.0000.022
plotScanpyMarkerGenes0.0220.0000.022
plotScanpyMarkerGenesDotPlot0.0210.0010.021
plotScanpyMarkerGenesHeatmap0.0210.0000.022
plotScanpyMarkerGenesMatrixPlot0.0220.0000.022
plotScanpyMarkerGenesViolin0.0210.0010.022
plotScanpyMatrixPlot0.0220.0000.021
plotScanpyPCA0.0200.0010.021
plotScanpyPCAGeneRanking0.0200.0010.022
plotScanpyPCAVariance0.0220.0000.022
plotScanpyViolin0.0210.0000.021
plotScdsHybridResults9.3270.0868.839
plotScrubletResults0.0220.0010.023
plotSeuratElbow0.0210.0010.022
plotSeuratHVG0.0210.0000.022
plotSeuratJackStraw0.0220.0000.022
plotSeuratReduction0.0220.0000.022
plotSoupXResults0.0000.0000.001
plotTSCANClusterDEG6.0590.0046.065
plotTSCANClusterPseudo1.3010.0071.308
plotTSCANDimReduceFeatures1.3480.0041.352
plotTSCANPseudotimeGenes1.5760.0021.578
plotTSCANPseudotimeHeatmap1.2580.0121.270
plotTSCANResults1.2160.0031.218
plotTSNE0.3570.0020.359
plotTopHVG0.6260.0020.629
plotUMAP6.3560.0156.371
readSingleCellMatrix0.0050.0000.006
reportCellQC0.0800.0010.080
reportDropletQC0.0220.0000.023
reportQCTool0.0780.0020.079
retrieveSCEIndex0.0270.0010.028
runBBKNN0.0010.0000.000
runBarcodeRankDrops0.2100.0040.214
runBcds1.4650.0540.951
runCellQC0.0760.0020.078
runClusterSummaryMetrics0.3740.0040.378
runComBatSeq0.4600.0050.465
runCxds0.3050.0030.308
runCxdsBcdsHybrid1.4610.0450.948
runDEAnalysis0.3700.0030.373
runDecontX6.3800.0026.383
runDimReduce0.2770.0030.281
runDoubletFinder32.306 0.11532.424
runDropletQC0.0220.0020.024
runEmptyDrops6.3120.0126.324
runEnrichR0.4410.0292.604
runFastMNN1.6330.0261.659
runFeatureSelection0.2120.0010.213
runFindMarker1.4340.0061.440
runGSVA0.6460.0470.693
runHarmony0.0370.0030.040
runKMeans0.1990.0270.226
runLimmaBC0.0800.0160.097
runMNNCorrect0.3930.0330.426
runModelGeneVar0.2770.0320.309
runNormalization2.1980.4002.598
runPerCellQC0.3220.0270.348
runSCANORAMA000
runSCMerge0.0040.0000.004
runScDblFinder15.829 0.80413.706
runScanpyFindClusters0.0200.0020.023
runScanpyFindHVG0.0210.0010.022
runScanpyFindMarkers0.0210.0010.021
runScanpyNormalizeData0.0910.0010.092
runScanpyPCA0.0210.0000.021
runScanpyScaleData0.0220.0000.022
runScanpyTSNE0.0200.0020.022
runScanpyUMAP0.0210.0000.021
runScranSNN0.2740.0020.276
runScrublet0.0220.0000.022
runSeuratFindClusters0.0200.0010.021
runSeuratFindHVG0.4300.0070.437
runSeuratHeatmap0.0190.0020.022
runSeuratICA0.0200.0010.022
runSeuratJackStraw0.0200.0010.021
runSeuratNormalizeData0.0190.0020.022
runSeuratPCA0.0210.0010.022
runSeuratSCTransform29.280 0.28929.571
runSeuratScaleData0.0220.0020.023
runSeuratUMAP0.0210.0010.022
runSingleR0.0380.0000.038
runSoupX0.0010.0000.000
runTSCAN0.6400.0020.642
runTSCANClusterDEAnalysis0.7760.0160.793
runTSCANDEG0.6780.0030.682
runTSNE0.7250.0100.736
runUMAP7.0790.1337.211
runVAM0.2800.0010.281
runZINBWaVE0.0030.0010.004
sampleSummaryStats0.1580.0000.158
scaterCPM0.1490.0040.153
scaterPCA0.4440.0030.446
scaterlogNormCounts0.2400.0060.245
sce0.0220.0010.023
sctkListGeneSetCollections0.0820.0000.082
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv0.0010.0000.001
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.0830.0020.084
setSCTKDisplayRow0.4380.0010.438
singleCellTK0.0000.0000.001
subDiffEx0.3280.0030.331
subsetSCECols0.0780.0000.078
subsetSCERows0.2060.0140.220
summarizeSCE0.0670.0010.069
trimCounts0.1930.0080.201