Back to Multiple platform build/check report for BioC 3.22:   simplified   long
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This page was generated on 2025-12-22 12:07 -0500 (Mon, 22 Dec 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.3 LTS)x86_644.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 4883
merida1macOS 12.7.6 Montereyx86_644.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 4673
kjohnson1macOS 13.7.5 Venturaarm644.5.2 Patched (2025-11-04 r88984) -- "[Not] Part in a Rumble" 4607
taishanLinux (openEuler 24.03 LTS)aarch644.5.0 (2025-04-11) -- "How About a Twenty-Six" 4671
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 2033/2361HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.20.0  (landing page)
Joshua David Campbell
Snapshot Date: 2025-12-18 13:45 -0500 (Thu, 18 Dec 2025)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_22
git_last_commit: e2bff7b
git_last_commit_date: 2025-10-29 11:29:49 -0500 (Wed, 29 Oct 2025)
nebbiolo2Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    ERROR  
merida1macOS 12.7.6 Monterey / x86_64  OK    OK    ERROR    OK  
kjohnson1macOS 13.7.5 Ventura / arm64  OK    OK    ERROR    OK  
taishanLinux (openEuler 24.03 LTS) / aarch64  OK    OK    OK  


CHECK results for singleCellTK on taishan

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.
- See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host.

raw results


Summary

Package: singleCellTK
Version: 2.20.0
Command: /home/biocbuild/R/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings singleCellTK_2.20.0.tar.gz
StartedAt: 2025-12-19 14:45:52 -0000 (Fri, 19 Dec 2025)
EndedAt: 2025-12-19 15:07:45 -0000 (Fri, 19 Dec 2025)
EllapsedTime: 1313.6 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings singleCellTK_2.20.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.0 (2025-04-11)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.20.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 80 non-default packages.
Importing from so many packages makes the package vulnerable to any of
them becoming unavailable.  Move as many as possible to Suggests and
use conditionally.
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘singleCellTK’ can be installed ... OK
* checking installed package size ... INFO
  installed size is  7.0Mb
  sub-directories of 1Mb or more:
    R         1.0Mb
    extdata   1.6Mb
    shiny     3.0Mb
* 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 50.677  1.089  51.887
plotDoubletFinderResults 44.752  0.489  45.726
runSeuratSCTransform     43.726  0.914  44.781
plotScDblFinderResults   37.583  0.523  38.271
runDoubletFinder         37.750  0.224  38.088
runScDblFinder           23.096  0.679  23.666
importExampleData        15.562  1.121  22.503
plotBatchCorrCompare     14.485  0.226  15.106
plotScdsHybridResults    11.586  0.038  11.053
plotBcdsResults          11.002  0.486  11.026
plotDecontXResults       10.509  0.267  10.882
plotCxdsResults           9.289  0.574   9.892
plotDEGViolin             8.366  0.151   9.117
runUMAP                   7.927  0.144   8.168
plotUMAP                  7.455  0.140   7.746
runDecontX                7.418  0.021   7.458
plotTSCANClusterDEG       7.398  0.024   7.445
plotDEGRegression         7.001  0.303   7.455
detectCellOutlier         6.693  0.231   6.943
convertSCEToSeurat        5.827  0.200   6.041
plotFindMarkerHeatmap     5.859  0.119   5.997
plotEmptyDropsResults     5.911  0.013   5.993
plotEmptyDropsScatter     5.710  0.024   5.851
runEmptyDrops             5.269  0.004   5.285
getEnrichRResult          0.438  0.085  21.084
runEnrichR                0.413  0.028   8.399
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘spelling.R’
  Running ‘testthat.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

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


Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-4.5.0/site-library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.20.0’
** using staged installation
** R
** data
** exec
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (singleCellTK)

Tests output

singleCellTK.Rcheck/tests/spelling.Rout


R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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 
  0.184   0.038   0.208 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

Number of nodes: 390
Number of edges: 9849

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

  |                                                                            
  |                                                                      |   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 
377.052   7.159 403.713 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0000.0030.002
SEG0.0030.0000.003
calcEffectSizes0.2870.0000.288
combineSCE1.0660.0241.092
computeZScore0.2750.0000.276
convertSCEToSeurat5.8270.2006.041
convertSeuratToSCE0.4660.0200.487
dedupRowNames0.0750.0000.075
detectCellOutlier6.6930.2316.943
diffAbundanceFET0.0740.0000.074
discreteColorPalette0.0090.0000.009
distinctColors0.0040.0000.003
downSampleCells0.7780.0480.829
downSampleDepth0.6290.0160.646
expData-ANY-character-method0.1780.0040.183
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.2340.0000.235
expData-set0.2240.0000.225
expData0.1960.0000.196
expDataNames-ANY-method0.1730.0040.177
expDataNames0.1770.0000.178
expDeleteDataTag0.0440.0000.045
expSetDataTag0.0320.0000.032
expTaggedData0.0320.0000.032
exportSCE0.0270.0000.026
exportSCEtoAnnData0.080.000.08
exportSCEtoFlatFile0.0760.0080.085
featureIndex0.0550.0000.054
generateSimulatedData0.0950.0080.103
getBiomarker0.0770.0000.077
getDEGTopTable1.0010.0481.052
getDiffAbundanceResults0.0640.0000.064
getEnrichRResult 0.438 0.08521.084
getFindMarkerTopTable2.3910.2682.714
getMSigDBTable0.0050.0000.005
getPathwayResultNames0.0330.0000.033
getSampleSummaryStatsTable0.3370.0440.384
getSoupX000
getTSCANResults1.6280.1381.785
getTopHVG1.3160.1231.608
importAnnData0.0020.0000.002
importBUStools0.2560.0120.270
importCellRanger1.2450.0791.334
importCellRangerV2Sample0.2340.0040.239
importCellRangerV3Sample0.4530.0200.475
importDropEst0.3040.0090.314
importExampleData15.562 1.12122.503
importGeneSetsFromCollection2.1190.1402.266
importGeneSetsFromGMT0.0870.0040.093
importGeneSetsFromList0.1980.0000.199
importGeneSetsFromMSigDB50.677 1.08951.887
importMitoGeneSet0.0750.0000.075
importOptimus0.0020.0000.002
importSEQC0.2120.0230.238
importSTARsolo0.2330.0160.252
iterateSimulations0.2370.0240.262
listSampleSummaryStatsTables0.3270.0440.371
mergeSCEColData0.5830.0160.600
mouseBrainSubsetSCE0.0420.0000.042
msigdb_table0.0020.0000.002
plotBarcodeRankDropsResults1.2360.0281.268
plotBarcodeRankScatter1.2520.0111.269
plotBatchCorrCompare14.485 0.22615.106
plotBatchVariance0.7030.0600.765
plotBcdsResults11.002 0.48611.026
plotBubble1.1620.0721.238
plotClusterAbundance2.1290.1432.277
plotCxdsResults9.2890.5749.892
plotDEGHeatmap3.2450.0843.339
plotDEGRegression7.0010.3037.455
plotDEGViolin8.3660.1519.117
plotDEGVolcano1.2820.0561.342
plotDecontXResults10.509 0.26710.882
plotDimRed0.4030.0080.412
plotDoubletFinderResults44.752 0.48945.726
plotEmptyDropsResults5.9110.0135.993
plotEmptyDropsScatter5.7100.0245.851
plotFindMarkerHeatmap5.8590.1195.997
plotMASTThresholdGenes1.8640.0241.892
plotPCA0.5480.0240.573
plotPathway1.0290.0361.068
plotRunPerCellQCResults4.6600.0684.739
plotSCEBarAssayData0.4590.0000.460
plotSCEBarColData0.3490.0000.350
plotSCEBatchFeatureMean0.6170.0000.618
plotSCEDensity0.4560.0080.465
plotSCEDensityAssayData0.4870.0000.488
plotSCEDensityColData0.4590.0000.460
plotSCEDimReduceColData1.2420.0041.250
plotSCEDimReduceFeatures0.5350.0000.536
plotSCEHeatmap0.6270.0000.628
plotSCEScatter0.5320.0040.537
plotSCEViolin0.6330.0080.642
plotSCEViolinAssayData0.5940.0040.739
plotSCEViolinColData0.5430.0000.545
plotScDblFinderResults37.583 0.52338.271
plotScanpyDotPlot0.0230.0000.023
plotScanpyEmbedding0.0220.0000.022
plotScanpyHVG0.0220.0000.022
plotScanpyHeatmap0.0230.0000.023
plotScanpyMarkerGenes0.0240.0000.024
plotScanpyMarkerGenesDotPlot0.0240.0000.025
plotScanpyMarkerGenesHeatmap0.0270.0000.027
plotScanpyMarkerGenesMatrixPlot0.0260.0000.027
plotScanpyMarkerGenesViolin0.0260.0000.026
plotScanpyMatrixPlot0.0280.0000.028
plotScanpyPCA0.0240.0000.024
plotScanpyPCAGeneRanking0.0220.0000.022
plotScanpyPCAVariance0.0220.0000.022
plotScanpyViolin0.0230.0000.023
plotScdsHybridResults11.586 0.03811.053
plotScrubletResults0.0280.0000.027
plotSeuratElbow0.0270.0000.028
plotSeuratHVG0.0280.0000.028
plotSeuratJackStraw0.0280.0000.028
plotSeuratReduction0.0270.0000.028
plotSoupXResults000
plotTSCANClusterDEG7.3980.0247.445
plotTSCANClusterPseudo2.0370.0082.052
plotTSCANDimReduceFeatures2.1310.0082.146
plotTSCANPseudotimeGenes2.4970.0002.505
plotTSCANPseudotimeHeatmap1.9970.0442.048
plotTSCANResults1.8580.0401.903
plotTSNE0.5620.0080.571
plotTopHVG0.8770.0040.883
plotUMAP7.4550.1407.746
readSingleCellMatrix0.0070.0010.007
reportCellQC0.1230.0000.124
reportDropletQC0.0250.0000.025
reportQCTool0.1120.0000.113
retrieveSCEIndex0.0360.0000.036
runBBKNN000
runBarcodeRankDrops0.2980.0000.299
runBcds2.6110.0152.077
runCellQC0.1050.0000.106
runClusterSummaryMetrics0.5170.0080.526
runComBatSeq0.6730.0000.675
runCxds0.4150.0000.416
runCxdsBcdsHybrid2.4020.0471.672
runDEAnalysis0.6030.0040.608
runDecontX7.4180.0217.458
runDimReduce0.3880.0000.388
runDoubletFinder37.750 0.22438.088
runDropletQC0.0260.0000.027
runEmptyDrops5.2690.0045.285
runEnrichR0.4130.0288.399
runFastMNN2.4030.1952.606
runFeatureSelection0.3040.0120.316
runFindMarker2.0020.1642.170
runGSVA1.1570.0821.243
runHarmony0.1910.0280.219
runKMeans0.2370.0160.254
runLimmaBC0.1190.0040.123
runMNNCorrect0.5530.0600.615
runModelGeneVar0.4420.0280.471
runNormalization2.8130.3103.131
runPerCellQC0.4950.0120.508
runSCANORAMA000
runSCMerge0.0040.0000.004
runScDblFinder23.096 0.67923.666
runScanpyFindClusters0.0250.0000.025
runScanpyFindHVG0.0240.0000.025
runScanpyFindMarkers0.0240.0000.024
runScanpyNormalizeData0.1280.0040.132
runScanpyPCA0.0240.0000.024
runScanpyScaleData0.0260.0000.026
runScanpyTSNE0.0250.0000.026
runScanpyUMAP0.0260.0000.026
runScranSNN0.4080.0040.413
runScrublet0.0260.0000.027
runSeuratFindClusters0.0260.0000.025
runSeuratFindHVG0.7040.0000.707
runSeuratHeatmap0.0230.0000.023
runSeuratICA0.0230.0000.024
runSeuratJackStraw0.0230.0000.023
runSeuratNormalizeData0.0240.0000.024
runSeuratPCA0.0230.0000.023
runSeuratSCTransform43.726 0.91444.781
runSeuratScaleData0.0250.0000.025
runSeuratUMAP0.0260.0000.026
runSingleR0.0550.0000.056
runSoupX000
runTSCAN0.9890.0201.012
runTSCANClusterDEAnalysis1.1110.0161.130
runTSCANDEG1.1450.0431.192
runTSNE1.0260.0081.036
runUMAP7.9270.1448.168
runVAM0.4290.0000.429
runZINBWaVE0.0040.0000.005
sampleSummaryStats0.2360.0000.237
scaterCPM0.1420.0000.143
scaterPCA0.6770.0160.694
scaterlogNormCounts0.2720.0000.273
sce0.0200.0040.024
sctkListGeneSetCollections0.110.000.11
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv0.0010.0000.000
selectSCTKConda0.0000.0000.001
selectSCTKVirtualEnvironment000
setRowNames0.1120.0040.117
setSCTKDisplayRow0.6070.0200.628
singleCellTK000
subDiffEx0.4430.0040.448
subsetSCECols0.1000.0040.104
subsetSCERows0.3830.0200.405
summarizeSCE0.0880.0040.092
trimCounts0.2020.0080.210