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This page was generated on 2026-03-24 11:35 -0400 (Tue, 24 Mar 2026).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.3 LTS)x86_64R Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences" 4869
kjohnson3macOS 13.7.7 Venturaarm64R Under development (unstable) (2026-03-20 r89666) -- "Unsuffered Consequences" 4567
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 2038/2368HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.21.1  (landing page)
Joshua David Campbell
Snapshot Date: 2026-03-23 13:40 -0400 (Mon, 23 Mar 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 -0400 (Sun, 11 Jan 2026)
nebbiolo1Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    ERROR  
kjohnson3macOS 13.7.7 Ventura / arm64  OK    OK    OK    OK  NO, package depends on 'batchelor' which is only available as a source package that needs compilation
See other builds for singleCellTK in R Universe.


CHECK results for singleCellTK on kjohnson3

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: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.21.1.tar.gz
StartedAt: 2026-03-23 22:46:51 -0400 (Mon, 23 Mar 2026)
EndedAt: 2026-03-23 22:53:52 -0400 (Mon, 23 Mar 2026)
EllapsedTime: 421.2 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.21.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck’
* using R Under development (unstable) (2026-03-20 r89666)
* using platform: aarch64-apple-darwin23
* R was compiled by
    Apple clang version 17.0.0 (clang-1700.3.19.1)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-03-24 02:46:52 UTC
* using option ‘--no-vignettes’
* 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  6.8Mb
  sub-directories of 1Mb or more:
    R         1.0Mb
    extdata   1.5Mb
    shiny     2.9Mb
* 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 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
plotDoubletFinderResults 16.559  0.242  17.541
runDoubletFinder         15.081  0.196  15.944
plotScDblFinderResults   13.159  0.343  14.104
runScDblFinder            8.044  0.150   8.513
importExampleData         5.294  0.823   6.989
plotBatchCorrCompare      5.696  0.114   6.173
* 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
  ‘/Users/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.


Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.6/Resources/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) (2026-03-20 r89666) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23

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 
  0.093   0.034   0.129 

singleCellTK.Rcheck/tests/testthat.Rout


R Under development (unstable) (2026-03-20 r89666) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23

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%
[22:52:55] WARNING: src/learner.cc:782: 
Parameters: { "nthreads" } are not used.

[22:52:55] 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
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 390
Number of edges: 9849

Running Louvain algorithm...
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Maximum modularity in 10 random starts: 0.8351
Number of communities: 7
Elapsed time: 0 seconds
Using method 'umap'
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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  |======================================================================| 100%
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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

[ FAIL 0 | WARN 19 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
112.046   3.095 126.742 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0010.0010.001
SEG0.0010.0010.001
calcEffectSizes0.0590.0020.062
combineSCE0.2370.0070.250
computeZScore0.1130.0040.125
convertSCEToSeurat2.0440.1312.277
convertSeuratToSCE0.1400.0030.150
dedupRowNames0.0370.0010.041
detectCellOutlier2.6930.0762.882
diffAbundanceFET0.0310.0010.033
discreteColorPalette0.0020.0000.003
distinctColors0.0000.0000.001
downSampleCells0.2850.0220.317
downSampleDepth0.1840.0130.204
expData-ANY-character-method0.0460.0020.048
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.0540.0010.059
expData-set0.0490.0010.052
expData0.0410.0020.043
expDataNames-ANY-method0.0400.0010.041
expDataNames0.0410.0030.043
expDeleteDataTag0.0170.0010.017
expSetDataTag0.0130.0010.013
expTaggedData0.0130.0010.013
exportSCE0.0110.0010.011
exportSCEtoAnnData0.0420.0010.052
exportSCEtoFlatFile0.0420.0020.042
featureIndex0.0180.0010.019
generateSimulatedData0.0220.0020.024
getBiomarker0.0250.0010.027
getDEGTopTable0.3100.0250.354
getDiffAbundanceResults0.0300.0010.032
getEnrichRResult0.2030.0413.298
getFindMarkerTopTable0.6330.0260.687
getMSigDBTable0.0020.0010.003
getPathwayResultNames0.0120.0010.013
getSampleSummaryStatsTable0.0690.0010.072
getSoupX000
getTSCANResults0.4460.0250.481
getTopHVG0.3700.0120.401
importAnnData0.0010.0000.001
importBUStools0.0440.0030.048
importCellRanger0.3850.0240.432
importCellRangerV2Sample0.0560.0020.060
importCellRangerV3Sample0.0940.0070.105
importDropEst0.0830.0030.094
importExampleData5.2940.8236.989
importGeneSetsFromCollection0.3370.0510.402
importGeneSetsFromGMT0.0420.0040.051
importGeneSetsFromList0.0420.0010.044
importGeneSetsFromMSigDB0.4000.0250.433
importMitoGeneSet0.0240.0020.026
importOptimus0.0010.0010.001
importSEQC0.0620.0020.068
importSTARsolo0.0510.0020.054
iterateSimulations0.0620.0020.064
listSampleSummaryStatsTables0.1430.0080.164
mergeSCEColData0.1220.0090.134
mouseBrainSubsetSCE0.0180.0010.018
msigdb_table0.0010.0020.003
plotBarcodeRankDropsResults0.3590.0180.392
plotBarcodeRankScatter0.3020.0060.317
plotBatchCorrCompare5.6960.1146.173
plotBatchVariance0.2030.0060.217
plotBcdsResults3.7090.0793.926
plotBubble0.2880.0060.304
plotClusterAbundance0.5520.0060.572
plotCxdsResults3.0830.0483.329
plotDEGHeatmap0.8120.0170.846
plotDEGRegression1.5610.0381.676
plotDEGViolin1.8610.0411.969
plotDEGVolcano0.4380.0090.463
plotDecontXResults3.5670.0463.758
plotDimRed0.1000.0020.103
plotDoubletFinderResults16.559 0.24217.541
plotEmptyDropsResults2.3630.0322.478
plotEmptyDropsScatter2.3940.0502.535
plotFindMarkerHeatmap1.3320.0161.372
plotMASTThresholdGenes0.3990.0110.417
plotPCA0.1360.0030.140
plotPathway0.2530.0090.273
plotRunPerCellQCResults1.0860.0171.140
plotSCEBarAssayData0.1050.0020.109
plotSCEBarColData0.0750.0020.076
plotSCEBatchFeatureMean0.1410.0020.147
plotSCEDensity0.1110.0020.114
plotSCEDensityAssayData0.1430.0050.155
plotSCEDensityColData0.1170.0020.122
plotSCEDimReduceColData0.2730.0080.290
plotSCEDimReduceFeatures0.1570.0040.166
plotSCEHeatmap0.1330.0020.136
plotSCEScatter0.1300.0030.135
plotSCEViolin0.1340.0020.139
plotSCEViolinAssayData0.1600.0060.176
plotSCEViolinColData0.1220.0020.136
plotScDblFinderResults13.159 0.34314.104
plotScanpyDotPlot0.0160.0010.017
plotScanpyEmbedding0.0110.0010.012
plotScanpyHVG0.0120.0010.012
plotScanpyHeatmap0.0110.0000.012
plotScanpyMarkerGenes0.0140.0010.015
plotScanpyMarkerGenesDotPlot0.0120.0010.012
plotScanpyMarkerGenesHeatmap0.0140.0010.015
plotScanpyMarkerGenesMatrixPlot0.0110.0010.011
plotScanpyMarkerGenesViolin0.0110.0000.012
plotScanpyMatrixPlot0.0110.0000.012
plotScanpyPCA0.0110.0010.012
plotScanpyPCAGeneRanking0.0120.0010.012
plotScanpyPCAVariance0.0120.0000.012
plotScanpyViolin0.0150.0010.017
plotScdsHybridResults4.0340.0884.291
plotScrubletResults0.0120.0000.012
plotSeuratElbow0.0110.0000.012
plotSeuratHVG0.0140.0010.017
plotSeuratJackStraw0.0120.0010.013
plotSeuratReduction0.0170.0010.018
plotSoupXResults0.0000.0000.001
plotTSCANClusterDEG1.8150.0281.890
plotTSCANClusterPseudo0.4210.0070.435
plotTSCANDimReduceFeatures0.5110.0110.537
plotTSCANPseudotimeGenes0.5960.0120.619
plotTSCANPseudotimeHeatmap0.4830.0110.505
plotTSCANResults0.4450.0120.467
plotTSNE0.1600.0060.175
plotTopHVG0.2100.0090.233
plotUMAP3.1710.0613.424
readSingleCellMatrix0.0010.0000.003
reportCellQC0.0360.0020.039
reportDropletQC0.0200.0020.024
reportQCTool0.0390.0030.044
retrieveSCEIndex0.0200.0010.021
runBBKNN000
runBarcodeRankDrops0.1160.0050.131
runBcds0.6280.0400.701
runCellQC0.0360.0020.058
runClusterSummaryMetrics0.1410.0040.157
runComBatSeq0.1770.0070.192
runCxds0.1180.0030.122
runCxdsBcdsHybrid0.7360.0540.841
runDEAnalysis0.2010.0090.222
runDecontX3.2000.0283.397
runDimReduce0.1230.0030.130
runDoubletFinder15.081 0.19615.944
runDropletQC0.0120.0000.012
runEmptyDrops2.2000.0202.279
runEnrichR0.1830.0282.613
runFastMNN0.6540.0220.695
runFeatureSelection0.0860.0020.089
runFindMarker0.5860.0270.648
runGSVA0.3760.0290.415
runHarmony0.0120.0000.012
runKMeans0.0690.0020.072
runLimmaBC0.0240.0000.025
runMNNCorrect0.2050.0050.217
runModelGeneVar0.1080.0020.111
runNormalization1.0720.0171.118
runPerCellQC0.1310.0040.140
runSCANORAMA0.0000.0010.000
runSCMerge0.0030.0010.005
runScDblFinder8.0440.1508.513
runScanpyFindClusters0.0110.0000.013
runScanpyFindHVG0.0110.0010.011
runScanpyFindMarkers0.0110.0000.012
runScanpyNormalizeData0.0330.0000.034
runScanpyPCA0.0130.0000.013
runScanpyScaleData0.0110.0000.012
runScanpyTSNE0.0100.0000.011
runScanpyUMAP0.0100.0010.011
runScranSNN0.0920.0030.096
runScrublet0.0130.0000.013
runSeuratFindClusters0.0110.0000.012
runSeuratFindHVG0.1450.0040.163
runSeuratHeatmap0.0110.0000.012
runSeuratICA0.0110.0000.012
runSeuratJackStraw0.0120.0010.012
runSeuratNormalizeData0.0110.0000.012
runSeuratPCA0.0120.0000.012
runSeuratSCTransform1.7710.0481.967
runSeuratScaleData0.0130.0010.013
runSeuratUMAP0.0120.0000.012
runSingleR0.0160.0020.019
runSoupX000
runTSCAN0.2300.0070.241
runTSCANClusterDEAnalysis0.2390.0050.246
runTSCANDEG0.2350.0040.239
runTSNE0.2820.0020.292
runUMAP3.1370.0563.426
runVAM0.1010.0020.103
runZINBWaVE0.0020.0010.002
sampleSummaryStats0.0540.0010.054
scaterCPM0.0560.0020.057
scaterPCA0.1630.0050.187
scaterlogNormCounts0.0920.0020.096
sce0.0110.0010.013
sctkListGeneSetCollections0.0300.0010.031
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.0380.0010.042
setSCTKDisplayRow0.1670.0030.177
singleCellTK000
subDiffEx0.1590.0080.176
subsetSCECols0.0300.0020.032
subsetSCERows0.0900.0020.096
summarizeSCE0.0330.0010.035
trimCounts0.0900.0020.096