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This page was generated on 2026-02-21 11:32 -0500 (Sat, 21 Feb 2026).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.3 LTS)x86_64R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences" 4871
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Package 2027/2354HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.21.1  (landing page)
Joshua David Campbell
Snapshot Date: 2026-02-20 13:40 -0500 (Fri, 20 Feb 2026)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: devel
git_last_commit: 15d4a13
git_last_commit_date: 2026-01-11 08:42:53 -0500 (Sun, 11 Jan 2026)
nebbiolo1Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    OK  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: 2.21.1
Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings singleCellTK_2.21.1.tar.gz
StartedAt: 2026-02-21 04:11:02 -0500 (Sat, 21 Feb 2026)
EndedAt: 2026-02-21 04:28:05 -0500 (Sat, 21 Feb 2026)
EllapsedTime: 1023.1 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_2.21.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck’
* using R Under development (unstable) (2026-01-15 r89304)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.21.1’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 80 non-default packages.
Importing from so many packages makes the package vulnerable to any of
them becoming unavailable.  Move as many as possible to Suggests and
use conditionally.
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘singleCellTK’ can be installed ... OK
* checking installed package size ... INFO
  installed size is  5.6Mb
  sub-directories of 1Mb or more:
    R       1.0Mb
    shiny   2.3Mb
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
  dedupRowNames.Rd: SingleCellExperiment-class
  detectCellOutlier.Rd: colData
  diffAbundanceFET.Rd: colData
  downSampleCells.Rd: SingleCellExperiment-class
  downSampleDepth.Rd: SingleCellExperiment-class
  featureIndex.Rd: SummarizedExperiment-class,
    SingleCellExperiment-class
  getBiomarker.Rd: SingleCellExperiment-class
  getDEGTopTable.Rd: SingleCellExperiment-class
  getEnrichRResult.Rd: SingleCellExperiment-class
  getFindMarkerTopTable.Rd: SingleCellExperiment-class
  getGenesetNamesFromCollection.Rd: SingleCellExperiment-class
  getPathwayResultNames.Rd: SingleCellExperiment-class
  getSampleSummaryStatsTable.Rd: SingleCellExperiment-class, assay,
    colData
  getSoupX.Rd: SingleCellExperiment-class
  getTSCANResults.Rd: SingleCellExperiment-class
  getTopHVG.Rd: SingleCellExperiment-class
  importAlevin.Rd: DelayedArray, readMM
  importAnnData.Rd: DelayedArray, readMM
  importBUStools.Rd: readMM
  importCellRanger.Rd: readMM, DelayedArray
  importCellRangerV2Sample.Rd: readMM, DelayedArray
  importCellRangerV3Sample.Rd: readMM, DelayedArray
  importDropEst.Rd: DelayedArray, readMM
  importExampleData.Rd: scRNAseq, Matrix, DelayedArray,
    ReprocessedFluidigmData, ReprocessedAllenData, NestorowaHSCData
  importFromFiles.Rd: readMM, DelayedArray, SingleCellExperiment-class
  importGeneSetsFromCollection.Rd: GeneSetCollection-class,
    SingleCellExperiment-class, GeneSetCollection, GSEABase, metadata
  importGeneSetsFromGMT.Rd: GeneSetCollection-class,
    SingleCellExperiment-class, getGmt, GSEABase, metadata
  importGeneSetsFromList.Rd: GeneSetCollection-class,
    SingleCellExperiment-class, GSEABase, metadata
  importGeneSetsFromMSigDB.Rd: SingleCellExperiment-class, msigdbr,
    GeneSetCollection-class, GSEABase, metadata
  importMitoGeneSet.Rd: SingleCellExperiment-class,
    GeneSetCollection-class, GSEABase, metadata
  importMultipleSources.Rd: DelayedArray
  importOptimus.Rd: readMM, DelayedArray
  importSEQC.Rd: readMM, DelayedArray
  importSTARsolo.Rd: readMM, DelayedArray
  iterateSimulations.Rd: SingleCellExperiment-class
  listSampleSummaryStatsTables.Rd: SingleCellExperiment-class, metadata
  plotBarcodeRankDropsResults.Rd: SingleCellExperiment-class
  plotBarcodeRankScatter.Rd: SingleCellExperiment-class
  plotBatchCorrCompare.Rd: SingleCellExperiment-class
  plotBatchVariance.Rd: SingleCellExperiment-class
  plotBcdsResults.Rd: SingleCellExperiment-class
  plotClusterAbundance.Rd: colData
  plotCxdsResults.Rd: SingleCellExperiment-class
  plotDEGHeatmap.Rd: SingleCellExperiment-class
  plotDEGRegression.Rd: SingleCellExperiment-class
  plotDEGViolin.Rd: SingleCellExperiment-class
  plotDEGVolcano.Rd: SingleCellExperiment-class
  plotDecontXResults.Rd: SingleCellExperiment-class
  plotDoubletFinderResults.Rd: SingleCellExperiment-class
  plotEmptyDropsResults.Rd: SingleCellExperiment-class
  plotEmptyDropsScatter.Rd: SingleCellExperiment-class
  plotEnrichR.Rd: SingleCellExperiment-class
  plotFindMarkerHeatmap.Rd: SingleCellExperiment-class
  plotPCA.Rd: SingleCellExperiment-class
  plotPathway.Rd: SingleCellExperiment-class
  plotRunPerCellQCResults.Rd: SingleCellExperiment-class
  plotSCEBarAssayData.Rd: SingleCellExperiment-class
  plotSCEBarColData.Rd: SingleCellExperiment-class
  plotSCEBatchFeatureMean.Rd: SingleCellExperiment-class
  plotSCEDensity.Rd: SingleCellExperiment-class
  plotSCEDensityAssayData.Rd: SingleCellExperiment-class
  plotSCEDensityColData.Rd: SingleCellExperiment-class
  plotSCEDimReduceColData.Rd: SingleCellExperiment-class
  plotSCEDimReduceFeatures.Rd: SingleCellExperiment-class
  plotSCEHeatmap.Rd: SingleCellExperiment-class
  plotSCEScatter.Rd: SingleCellExperiment-class
  plotSCEViolin.Rd: SingleCellExperiment-class
  plotSCEViolinAssayData.Rd: SingleCellExperiment-class
  plotSCEViolinColData.Rd: SingleCellExperiment-class
  plotScDblFinderResults.Rd: SingleCellExperiment-class
  plotScdsHybridResults.Rd: SingleCellExperiment-class
  plotScrubletResults.Rd: SingleCellExperiment-class
  plotSoupXResults.Rd: SingleCellExperiment-class
  plotTSCANClusterDEG.Rd: SingleCellExperiment-class
  plotTSCANClusterPseudo.Rd: SingleCellExperiment-class
  plotTSCANDimReduceFeatures.Rd: SingleCellExperiment-class
  plotTSCANPseudotimeGenes.Rd: SingleCellExperiment-class
  plotTSCANPseudotimeHeatmap.Rd: SingleCellExperiment-class
  plotTSCANResults.Rd: SingleCellExperiment-class
  plotTSNE.Rd: SingleCellExperiment-class
  plotUMAP.Rd: SingleCellExperiment-class
  readSingleCellMatrix.Rd: DelayedArray
  reportCellQC.Rd: SingleCellExperiment-class
  reportClusterAbundance.Rd: colData
  reportDiffAbundanceFET.Rd: colData
  retrieveSCEIndex.Rd: SingleCellExperiment-class
  runBBKNN.Rd: SingleCellExperiment-class
  runBarcodeRankDrops.Rd: SingleCellExperiment-class, colData
  runBcds.Rd: SingleCellExperiment-class, colData
  runCellQC.Rd: colData
  runComBatSeq.Rd: SingleCellExperiment-class
  runCxds.Rd: SingleCellExperiment-class, colData
  runCxdsBcdsHybrid.Rd: colData
  runDEAnalysis.Rd: SingleCellExperiment-class
  runDecontX.Rd: colData
  runDimReduce.Rd: SingleCellExperiment-class
  runDoubletFinder.Rd: SingleCellExperiment-class
  runDropletQC.Rd: colData
  runEmptyDrops.Rd: SingleCellExperiment-class, colData
  runEnrichR.Rd: SingleCellExperiment-class
  runFastMNN.Rd: SingleCellExperiment-class, BiocParallelParam-class
  runFeatureSelection.Rd: SingleCellExperiment-class
  runFindMarker.Rd: SingleCellExperiment-class
  runGSVA.Rd: SingleCellExperiment-class
  runHarmony.Rd: SingleCellExperiment-class
  runKMeans.Rd: SingleCellExperiment-class, colData
  runLimmaBC.Rd: SingleCellExperiment-class, assay
  runMNNCorrect.Rd: SingleCellExperiment-class, assay,
    BiocParallelParam-class
  runModelGeneVar.Rd: SingleCellExperiment-class
  runPerCellQC.Rd: SingleCellExperiment-class, BiocParallelParam,
    colData
  runSCANORAMA.Rd: SingleCellExperiment-class, assay
  runSCMerge.Rd: SingleCellExperiment-class, colData, assay,
    BiocParallelParam-class
  runScDblFinder.Rd: SingleCellExperiment-class, colData
  runScranSNN.Rd: SingleCellExperiment-class, reducedDim, assay,
    altExp, colData, igraph
  runScrublet.Rd: SingleCellExperiment-class, colData
  runSingleR.Rd: SingleCellExperiment-class
  runSoupX.Rd: SingleCellExperiment-class
  runTSCAN.Rd: SingleCellExperiment-class
  runTSCANClusterDEAnalysis.Rd: SingleCellExperiment-class
  runTSCANDEG.Rd: SingleCellExperiment-class
  runTSNE.Rd: SingleCellExperiment-class
  runUMAP.Rd: SingleCellExperiment-class, BiocParallelParam-class
  runVAM.Rd: SingleCellExperiment-class
  runZINBWaVE.Rd: SingleCellExperiment-class, colData,
    BiocParallelParam-class
  sampleSummaryStats.Rd: SingleCellExperiment-class, assay, colData
  scaterPCA.Rd: SingleCellExperiment-class, BiocParallelParam-class
  scaterlogNormCounts.Rd: logNormCounts
  sctkListGeneSetCollections.Rd: GeneSetCollection-class
  sctkPythonInstallConda.Rd: conda_install, reticulate, conda_create
  sctkPythonInstallVirtualEnv.Rd: virtualenv_install, reticulate,
    virtualenv_create
  selectSCTKConda.Rd: reticulate
  selectSCTKVirtualEnvironment.Rd: reticulate
  setRowNames.Rd: SingleCellExperiment-class
  setSCTKDisplayRow.Rd: SingleCellExperiment-class
  singleCellTK.Rd: SingleCellExperiment-class
  subsetSCECols.Rd: SingleCellExperiment-class
  subsetSCERows.Rd: SingleCellExperiment-class, altExp
  summarizeSCE.Rd: SingleCellExperiment-class
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                           user system elapsed
importGeneSetsFromMSigDB 44.885  1.070  45.959
plotDoubletFinderResults 40.273  0.333  40.607
runDoubletFinder         34.739  0.397  35.136
runSeuratSCTransform     30.064  0.804  30.877
plotScDblFinderResults   27.062  0.870  24.950
runScDblFinder           16.791  1.322  15.124
plotBatchCorrCompare     12.947  0.170  13.116
importExampleData        11.259  1.447  13.063
plotScdsHybridResults     9.766  1.001  10.190
plotDecontXResults        8.830  0.068   8.899
plotBcdsResults           8.496  0.134   8.050
runUMAP                   8.116  0.122   8.239
runDecontX                7.743  0.151   7.895
plotUMAP                  6.893  0.510   7.404
plotCxdsResults           7.270  0.057   7.328
plotEmptyDropsResults     6.633  0.010   6.644
plotEmptyDropsScatter     6.522  0.009   6.531
plotRunPerCellQCResults   6.243  0.029   6.283
runEmptyDrops             6.238  0.030   6.268
detectCellOutlier         5.945  0.185   6.132
plotDEGViolin             5.104  0.054   5.152
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘spelling.R’
  Running ‘testthat.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

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


Installation output

singleCellTK.Rcheck/00install.out

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


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.21.1’
** using staged installation
** R
** data
** exec
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (singleCellTK)

Tests output

singleCellTK.Rcheck/tests/spelling.Rout


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

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> if (requireNamespace('spelling', quietly = TRUE))
+   spelling::spell_check_test(vignettes = TRUE, error = FALSE, skip_on_cran = TRUE)
All Done!
> 
> proc.time()
   user  system elapsed 
  0.149   0.035   0.169 

singleCellTK.Rcheck/tests/testthat.Rout


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

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(testthat)
> library(singleCellTK)
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats

Attaching package: 'MatrixGenerics'

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

    colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
    colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
    colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
    colWeightedMeans, colWeightedMedians, colWeightedSds,
    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
    rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
    rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
    rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
    rowWeightedSds, rowWeightedVars

Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: generics

Attaching package: 'generics'

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

    as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
    setequal, union


Attaching package: 'BiocGenerics'

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

    IQR, mad, sd, var, xtabs

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

    Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
    mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
    rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
    unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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

    findMatches

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

    I, expand.grid, unname

Loading required package: IRanges
Loading required package: Seqinfo
Loading required package: Biobase
Welcome to Bioconductor

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


Attaching package: 'Biobase'

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

    rowMedians

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

    anyMissing, rowMedians

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

Attaching package: 'Matrix'

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

    expand

Loading required package: S4Arrays
Loading required package: abind

Attaching package: 'S4Arrays'

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

    abind

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

    rowsum

Loading required package: SparseArray

Attaching package: 'DelayedArray'

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

    apply, scale, sweep


Attaching package: 'singleCellTK'

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

    plotPCA

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

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

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

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
[04:25:53] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

[04:25:54] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

  |                                                                            
  |                                                                      |   0%
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  |======================================================================| 100%
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 19 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 19 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
319.400   8.141 326.580 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0020.0010.002
SEG0.0020.0000.002
calcEffectSizes0.1500.0150.165
combineSCE0.7040.0350.740
computeZScore0.2360.0110.249
convertSCEToSeurat4.5600.1464.708
convertSeuratToSCE0.3460.0040.352
dedupRowNames0.0550.0000.055
detectCellOutlier5.9450.1856.132
diffAbundanceFET0.0550.0000.055
discreteColorPalette0.0050.0010.007
distinctColors0.0020.0000.002
downSampleCells0.5150.0290.544
downSampleDepth0.3890.0560.445
expData-ANY-character-method0.1140.0040.119
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1550.0060.161
expData-set0.1440.0030.146
expData0.1230.0010.124
expDataNames-ANY-method0.1120.0010.113
expDataNames0.1140.0000.114
expDeleteDataTag0.0290.0020.031
expSetDataTag0.0210.0020.024
expTaggedData0.0230.0010.024
exportSCE0.020.000.02
exportSCEtoAnnData0.0880.0090.097
exportSCEtoFlatFile0.0900.0060.096
featureIndex0.0350.0010.036
generateSimulatedData0.0490.0020.051
getBiomarker0.0510.0080.059
getDEGTopTable0.6540.0760.731
getDiffAbundanceResults0.0460.0010.047
getEnrichRResult0.5300.0212.683
getFindMarkerTopTable1.7860.2992.085
getMSigDBTable0.0020.0020.004
getPathwayResultNames0.0230.0000.023
getSampleSummaryStatsTable0.1870.0050.192
getSoupX0.0000.0000.001
getTSCANResults1.0830.1141.196
getTopHVG0.9080.2531.160
importAnnData0.0020.0000.002
importBUStools0.1410.0060.148
importCellRanger0.8560.0950.953
importCellRangerV2Sample0.1470.0060.152
importCellRangerV3Sample0.2650.0020.267
importDropEst0.1950.0080.203
importExampleData11.259 1.44713.063
importGeneSetsFromCollection1.7480.1001.848
importGeneSetsFromGMT0.0610.0020.063
importGeneSetsFromList0.1250.0010.126
importGeneSetsFromMSigDB44.885 1.07045.959
importMitoGeneSet0.0490.0060.054
importOptimus0.0020.0000.002
importSEQC0.1320.0220.153
importSTARsolo0.1400.0230.164
iterateSimulations0.1640.0290.193
listSampleSummaryStatsTables0.2400.0390.279
mergeSCEColData0.3770.0110.388
mouseBrainSubsetSCE0.0340.0010.035
msigdb_table0.0000.0010.001
plotBarcodeRankDropsResults0.8450.0210.866
plotBarcodeRankScatter0.8810.0040.885
plotBatchCorrCompare12.947 0.17013.116
plotBatchVariance0.4680.0140.483
plotBcdsResults8.4960.1348.050
plotBubble0.7660.0000.766
plotClusterAbundance1.3060.0011.307
plotCxdsResults7.2700.0577.328
plotDEGHeatmap2.0130.0092.022
plotDEGRegression4.2000.0114.206
plotDEGViolin5.1040.0545.152
plotDEGVolcano0.9350.0040.939
plotDecontXResults8.8300.0688.899
plotDimRed0.2620.0030.265
plotDoubletFinderResults40.273 0.33340.607
plotEmptyDropsResults6.6330.0106.644
plotEmptyDropsScatter6.5220.0096.531
plotFindMarkerHeatmap3.7280.0073.735
plotMASTThresholdGenes1.2370.0091.246
plotPCA0.3490.0020.351
plotPathway0.6840.0010.685
plotRunPerCellQCResults6.2430.0296.283
plotSCEBarAssayData0.5590.0070.565
plotSCEBarColData0.2590.0030.262
plotSCEBatchFeatureMean0.3620.0040.367
plotSCEDensity0.2920.0000.292
plotSCEDensityAssayData0.2580.0020.260
plotSCEDensityColData0.3410.0150.356
plotSCEDimReduceColData0.6970.0070.704
plotSCEDimReduceFeatures0.3570.0030.361
plotSCEHeatmap0.4370.0020.439
plotSCEScatter0.3350.0020.338
plotSCEViolin0.3460.0030.349
plotSCEViolinAssayData0.3990.0000.398
plotSCEViolinColData0.3400.0010.340
plotScDblFinderResults27.062 0.87024.950
plotScanpyDotPlot0.0220.0010.022
plotScanpyEmbedding0.0230.0000.023
plotScanpyHVG0.0210.0010.022
plotScanpyHeatmap0.0210.0010.023
plotScanpyMarkerGenes0.0200.0020.023
plotScanpyMarkerGenesDotPlot0.0220.0000.022
plotScanpyMarkerGenesHeatmap0.0220.0010.022
plotScanpyMarkerGenesMatrixPlot0.0220.0000.022
plotScanpyMarkerGenesViolin0.0210.0000.022
plotScanpyMatrixPlot0.0230.0020.024
plotScanpyPCA0.0220.0000.022
plotScanpyPCAGeneRanking0.0200.0020.022
plotScanpyPCAVariance0.0210.0010.022
plotScanpyViolin0.0220.0000.022
plotScdsHybridResults 9.766 1.00110.190
plotScrubletResults0.0220.0080.029
plotSeuratElbow0.0210.0000.022
plotSeuratHVG0.0210.0000.021
plotSeuratJackStraw0.0200.0010.022
plotSeuratReduction0.0200.0010.021
plotSoupXResults0.0010.0000.000
plotTSCANClusterDEG4.6950.1644.859
plotTSCANClusterPseudo1.2920.0681.360
plotTSCANDimReduceFeatures1.3380.0551.392
plotTSCANPseudotimeGenes1.5640.0431.607
plotTSCANPseudotimeHeatmap1.2570.0141.271
plotTSCANResults1.1810.0201.202
plotTSNE0.3530.0040.356
plotTopHVG0.6000.0050.604
plotUMAP6.8930.5107.404
readSingleCellMatrix0.0050.0000.005
reportCellQC0.0810.0030.083
reportDropletQC0.0210.0010.022
reportQCTool0.080.000.08
retrieveSCEIndex0.0290.0000.029
runBBKNN0.0010.0000.000
runBarcodeRankDrops0.2240.0070.231
runBcds1.5130.0550.963
runCellQC0.0800.0010.080
runClusterSummaryMetrics0.3850.0080.393
runComBatSeq0.4200.0160.435
runCxds0.3260.0080.334
runCxdsBcdsHybrid1.5340.0731.022
runDEAnalysis0.4390.0050.444
runDecontX7.7430.1517.895
runDimReduce0.2700.0040.274
runDoubletFinder34.739 0.39735.136
runDropletQC0.0220.0000.021
runEmptyDrops6.2380.0306.268
runEnrichR0.5000.0832.568
runFastMNN1.6490.0661.714
runFeatureSelection0.2170.0020.219
runFindMarker1.3790.0471.426
runGSVA0.7830.0550.838
runHarmony0.1120.0060.117
runKMeans0.1740.0140.187
runLimmaBC0.0730.0020.076
runMNNCorrect0.3920.0130.405
runModelGeneVar0.2820.0160.297
runNormalization2.4850.5783.063
runPerCellQC0.3140.0010.315
runSCANORAMA0.0010.0000.000
runSCMerge0.0040.0000.005
runScDblFinder16.791 1.32215.124
runScanpyFindClusters0.0230.0010.024
runScanpyFindHVG0.0200.0030.023
runScanpyFindMarkers0.0210.0010.023
runScanpyNormalizeData0.0980.0010.098
runScanpyPCA0.0230.0000.022
runScanpyScaleData0.0220.0000.022
runScanpyTSNE0.0220.0000.022
runScanpyUMAP0.0210.0010.022
runScranSNN0.2790.0040.284
runScrublet0.0220.0000.022
runSeuratFindClusters0.0220.0000.022
runSeuratFindHVG0.4540.0130.467
runSeuratHeatmap0.0210.0010.022
runSeuratICA0.0210.0010.022
runSeuratJackStraw0.0210.0000.021
runSeuratNormalizeData0.0220.0000.022
runSeuratPCA0.0200.0010.021
runSeuratSCTransform30.064 0.80430.877
runSeuratScaleData0.0210.0020.023
runSeuratUMAP0.0220.0000.022
runSingleR0.0370.0020.039
runSoupX0.0010.0000.001
runTSCAN0.6690.0080.677
runTSCANClusterDEAnalysis0.7310.0220.754
runTSCANDEG0.7170.0320.750
runTSNE0.7120.0040.716
runUMAP8.1160.1228.239
runVAM0.2930.0040.297
runZINBWaVE0.0040.0000.005
sampleSummaryStats0.1580.0000.158
scaterCPM0.1340.0160.150
scaterPCA0.4290.0180.446
scaterlogNormCounts0.2420.0100.252
sce0.0230.0000.023
sctkListGeneSetCollections0.0890.0030.092
sctkPythonInstallConda0.0010.0000.000
sctkPythonInstallVirtualEnv000
selectSCTKConda0.0000.0000.001
selectSCTKVirtualEnvironment0.0000.0010.000
setRowNames0.0860.0050.091
setSCTKDisplayRow0.4190.0240.442
singleCellTK0.0000.0000.001
subDiffEx0.3470.0110.359
subsetSCECols0.0860.0030.089
subsetSCERows0.2620.0070.269
summarizeSCE0.0690.0010.070
trimCounts0.2030.0120.214