Back to Multiple platform build/check report for BioC 3.22:   simplified   long
ABCDEFGHIJKLMNOPQR[S]TUVWXYZ

This page was generated on 2025-08-06 13:53 -0400 (Wed, 06 Aug 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.2 LTS)x86_644.5.1 (2025-06-13) -- "Great Square Root" 4813
palomino8Windows Server 2022 Datacenterx644.5.1 (2025-06-13 ucrt) -- "Great Square Root" 4550
lconwaymacOS 12.7.1 Montereyx86_644.5.1 (2025-06-13) -- "Great Square Root" 4592
kjohnson3macOS 13.7.1 Venturaarm644.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" 4534
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 1993/2315HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.19.1  (landing page)
Joshua David Campbell
Snapshot Date: 2025-08-05 13:25 -0400 (Tue, 05 Aug 2025)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: devel
git_last_commit: 565145a1
git_last_commit_date: 2025-07-01 15:36:15 -0400 (Tue, 01 Jul 2025)
nebbiolo2Linux (Ubuntu 24.04.2 LTS) / x86_64  OK    OK    OK  NO, package depends on 'MAST' which is not available
palomino8Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  NO, package depends on 'MAST' which is not available
lconwaymacOS 12.7.1 Monterey / x86_64  OK    OK    OK    OK  NO, package depends on 'MAST' which is not available
kjohnson3macOS 13.7.1 Ventura / arm64  OK    OK    OK    OK  NO, package depends on 'MAST' which is not available


CHECK results for singleCellTK on nebbiolo2

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: 2.19.1
Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings singleCellTK_2.19.1.tar.gz
StartedAt: 2025-08-06 02:54:49 -0400 (Wed, 06 Aug 2025)
EndedAt: 2025-08-06 03:11:33 -0400 (Wed, 06 Aug 2025)
EllapsedTime: 1003.8 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings singleCellTK_2.19.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.1 (2025-06-13)
* 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 24.04.2 LTS
* using session charset: UTF-8
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.19.1’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 79 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
  plotFindMarkerHeatmap.Rd: SingleCellExperiment-class
  plotPCA.Rd: SingleCellExperiment-class
  plotPathway.Rd: SingleCellExperiment-class
  plotRunPerCellQCResults.Rd: SingleCellExperiment-class
  plotSCEBarAssayData.Rd: SingleCellExperiment-class
  plotSCEBarColData.Rd: SingleCellExperiment-class
  plotSCEBatchFeatureMean.Rd: SingleCellExperiment-class
  plotSCEDensity.Rd: SingleCellExperiment-class
  plotSCEDensityAssayData.Rd: SingleCellExperiment-class
  plotSCEDensityColData.Rd: SingleCellExperiment-class
  plotSCEDimReduceColData.Rd: SingleCellExperiment-class
  plotSCEDimReduceFeatures.Rd: SingleCellExperiment-class
  plotSCEHeatmap.Rd: SingleCellExperiment-class
  plotSCEScatter.Rd: SingleCellExperiment-class
  plotSCEViolin.Rd: SingleCellExperiment-class
  plotSCEViolinAssayData.Rd: SingleCellExperiment-class
  plotSCEViolinColData.Rd: SingleCellExperiment-class
  plotScDblFinderResults.Rd: SingleCellExperiment-class
  plotScdsHybridResults.Rd: SingleCellExperiment-class
  plotScrubletResults.Rd: SingleCellExperiment-class
  plotSoupXResults.Rd: SingleCellExperiment-class
  plotTSCANClusterDEG.Rd: SingleCellExperiment-class
  plotTSCANClusterPseudo.Rd: SingleCellExperiment-class
  plotTSCANDimReduceFeatures.Rd: SingleCellExperiment-class
  plotTSCANPseudotimeGenes.Rd: SingleCellExperiment-class
  plotTSCANPseudotimeHeatmap.Rd: SingleCellExperiment-class
  plotTSCANResults.Rd: SingleCellExperiment-class
  plotTSNE.Rd: SingleCellExperiment-class
  plotUMAP.Rd: SingleCellExperiment-class
  readSingleCellMatrix.Rd: DelayedArray
  reportCellQC.Rd: SingleCellExperiment-class
  reportClusterAbundance.Rd: colData
  reportDiffAbundanceFET.Rd: colData
  retrieveSCEIndex.Rd: SingleCellExperiment-class
  runBBKNN.Rd: SingleCellExperiment-class
  runBarcodeRankDrops.Rd: SingleCellExperiment-class, colData
  runBcds.Rd: SingleCellExperiment-class, colData
  runCellQC.Rd: colData
  runComBatSeq.Rd: SingleCellExperiment-class
  runCxds.Rd: SingleCellExperiment-class, colData
  runCxdsBcdsHybrid.Rd: colData
  runDEAnalysis.Rd: SingleCellExperiment-class
  runDecontX.Rd: colData
  runDimReduce.Rd: SingleCellExperiment-class
  runDoubletFinder.Rd: SingleCellExperiment-class
  runDropletQC.Rd: colData
  runEmptyDrops.Rd: SingleCellExperiment-class, colData
  runEnrichR.Rd: SingleCellExperiment-class
  runFastMNN.Rd: SingleCellExperiment-class, BiocParallelParam-class
  runFeatureSelection.Rd: SingleCellExperiment-class
  runFindMarker.Rd: SingleCellExperiment-class
  runGSVA.Rd: SingleCellExperiment-class
  runHarmony.Rd: SingleCellExperiment-class
  runKMeans.Rd: SingleCellExperiment-class, colData
  runLimmaBC.Rd: SingleCellExperiment-class, assay
  runMNNCorrect.Rd: SingleCellExperiment-class, assay,
    BiocParallelParam-class
  runModelGeneVar.Rd: SingleCellExperiment-class
  runPerCellQC.Rd: SingleCellExperiment-class, BiocParallelParam,
    colData
  runSCANORAMA.Rd: SingleCellExperiment-class, assay
  runSCMerge.Rd: SingleCellExperiment-class, colData, assay,
    BiocParallelParam-class
  runScDblFinder.Rd: SingleCellExperiment-class, colData
  runScranSNN.Rd: SingleCellExperiment-class, reducedDim, assay,
    altExp, colData, igraph
  runScrublet.Rd: SingleCellExperiment-class, colData
  runSingleR.Rd: SingleCellExperiment-class
  runSoupX.Rd: SingleCellExperiment-class
  runTSCAN.Rd: SingleCellExperiment-class
  runTSCANClusterDEAnalysis.Rd: SingleCellExperiment-class
  runTSCANDEG.Rd: SingleCellExperiment-class
  runTSNE.Rd: SingleCellExperiment-class
  runUMAP.Rd: SingleCellExperiment-class, BiocParallelParam-class
  runVAM.Rd: SingleCellExperiment-class
  runZINBWaVE.Rd: SingleCellExperiment-class, colData,
    BiocParallelParam-class
  sampleSummaryStats.Rd: SingleCellExperiment-class, assay, colData
  scaterPCA.Rd: SingleCellExperiment-class, BiocParallelParam-class
  scaterlogNormCounts.Rd: logNormCounts
  sctkListGeneSetCollections.Rd: GeneSetCollection-class
  sctkPythonInstallConda.Rd: conda_install, reticulate, conda_create
  sctkPythonInstallVirtualEnv.Rd: virtualenv_install, reticulate,
    virtualenv_create
  selectSCTKConda.Rd: reticulate
  selectSCTKVirtualEnvironment.Rd: reticulate
  setRowNames.Rd: SingleCellExperiment-class
  setSCTKDisplayRow.Rd: SingleCellExperiment-class
  singleCellTK.Rd: SingleCellExperiment-class
  subsetSCECols.Rd: SingleCellExperiment-class
  subsetSCERows.Rd: SingleCellExperiment-class, altExp
  summarizeSCE.Rd: SingleCellExperiment-class
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                           user system elapsed
importGeneSetsFromMSigDB 45.199  0.555  45.754
plotDoubletFinderResults 40.263  0.296  40.642
runDoubletFinder         36.408  0.300  36.714
plotScDblFinderResults   30.118  0.539  30.383
runSeuratSCTransform     28.560  0.166  28.728
runScDblFinder           20.397  0.378  20.428
plotBatchCorrCompare     12.787  0.106  13.071
importExampleData         9.997  0.363  10.727
plotScdsHybridResults     9.214  0.022   8.569
plotBcdsResults           8.867  0.125   8.315
plotDecontXResults        8.248  0.089   8.338
runUMAP                   8.093  0.127   8.300
runDecontX                7.390  0.111   7.503
plotUMAP                  7.211  0.112   7.401
plotCxdsResults           6.984  0.117   7.179
plotEmptyDropsResults     6.626  0.058   6.683
plotEmptyDropsScatter     6.427  0.014   6.442
runEmptyDrops             6.264  0.026   6.291
* 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-3.22-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.


Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.19.1’
** 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 version 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

> if (requireNamespace('spelling', quietly = TRUE))
+   spelling::spell_check_test(vignettes = TRUE, error = FALSE, skip_on_cran = TRUE)
NULL
> 
> proc.time()
   user  system elapsed 
  0.153   0.040   0.179 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

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

Attaching package: 'MatrixGenerics'

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

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

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

Attaching package: 'generics'

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

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


Attaching package: 'BiocGenerics'

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

    IQR, mad, sd, var, xtabs

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

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

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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

    findMatches

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

    I, expand.grid, unname

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

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


Attaching package: 'Biobase'

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

    rowMedians

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

    anyMissing, rowMedians

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

Attaching package: 'Matrix'

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

    expand

Loading required package: S4Arrays
Loading required package: abind

Attaching package: 'S4Arrays'

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

    abind

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

    rowsum

Loading required package: SparseArray

Attaching package: 'DelayedArray'

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

    apply, scale, sweep


Attaching package: 'singleCellTK'

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

    plotPCA

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

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

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

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
[1]	train-logloss:0.452540 
Will train until train_logloss hasn't improved in 2 rounds.

[2]	train-logloss:0.320237 
[3]	train-logloss:0.237326 
[4]	train-logloss:0.182355 
[5]	train-logloss:0.144099 
[6]	train-logloss:0.117553 
[7]	train-logloss:0.098814 
[8]	train-logloss:0.084978 
[9]	train-logloss:0.075063 
[10]	train-logloss:0.067483 
[11]	train-logloss:0.061861 
[12]	train-logloss:0.057362 
[13]	train-logloss:0.053725 
[14]	train-logloss:0.050620 
[15]	train-logloss:0.047937 
[16]	train-logloss:0.045355 
[17]	train-logloss:0.043608 
[18]	train-logloss:0.042678 
[1]	train-logloss:0.452932 
Will train until train_logloss hasn't improved in 2 rounds.

[2]	train-logloss:0.320861 
[3]	train-logloss:0.238138 
[4]	train-logloss:0.183327 
[5]	train-logloss:0.145234 
[6]	train-logloss:0.118471 
[7]	train-logloss:0.099668 
[8]	train-logloss:0.085972 
[9]	train-logloss:0.076338 
[10]	train-logloss:0.068629 
[11]	train-logloss:0.062967 
[12]	train-logloss:0.057971 
[13]	train-logloss:0.053386 
[14]	train-logloss:0.050623 
[1]	train-logloss:0.453030 
Will train until train_logloss hasn't improved in 2 rounds.

[2]	train-logloss:0.321019 
[3]	train-logloss:0.238344 
[4]	train-logloss:0.183572 
[5]	train-logloss:0.145515 
[6]	train-logloss:0.118784 
[7]	train-logloss:0.100283 
[8]	train-logloss:0.086178 
[9]	train-logloss:0.076766 
[10]	train-logloss:0.069198 
[11]	train-logloss:0.063614 
[12]	train-logloss:0.059085 
[13]	train-logloss:0.055346 
[14]	train-logloss:0.052474 
[15]	train-logloss:0.049706 
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 390
Number of edges: 9849

Running Louvain algorithm...
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Maximum modularity in 10 random starts: 0.8351
Number of communities: 7
Elapsed time: 0 seconds
Using method 'umap'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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

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

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

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

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 22 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 22 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
318.091   5.305 326.990 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0020.0010.002
SEG0.0030.0000.002
calcEffectSizes0.1820.0040.188
combineSCE0.6900.0020.694
computeZScore0.2290.0030.233
convertSCEToSeurat4.0170.0624.079
convertSeuratToSCE0.2860.0010.289
dedupRowNames0.0540.0000.054
detectCellOutlier4.7360.1054.844
diffAbundanceFET0.0510.0000.052
discreteColorPalette0.0050.0000.005
distinctColors0.0020.0000.002
downSampleCells0.4580.0420.500
downSampleDepth0.3750.0150.390
expData-ANY-character-method0.1110.0000.111
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1460.0010.146
expData-set0.1370.0000.137
expData0.1110.0030.113
expDataNames-ANY-method0.1100.0050.115
expDataNames0.1080.0050.112
expDeleteDataTag0.0310.0000.031
expSetDataTag0.0220.0010.023
expTaggedData0.0220.0010.024
exportSCE0.0200.0000.021
exportSCEtoAnnData0.0890.0070.095
exportSCEtoFlatFile0.0910.0050.096
featureIndex0.0330.0030.036
generateSimulatedData0.0490.0000.049
getBiomarker0.0560.0010.056
getDEGTopTable0.6480.0730.721
getDiffAbundanceResults0.0460.0000.047
getEnrichRResult0.5260.0142.891
getFindMarkerTopTable1.3940.0331.427
getMSigDBTable0.0020.0010.003
getPathwayResultNames0.0210.0000.021
getSampleSummaryStatsTable0.1670.0010.168
getSoupX000
getTSCANResults0.9740.0130.986
getTopHVG0.7600.0230.783
importAnnData0.0010.0000.001
importBUStools0.1430.0010.144
importCellRanger0.6990.0310.731
importCellRangerV2Sample0.1380.0010.139
importCellRangerV3Sample0.2890.0020.291
importDropEst0.1980.0020.200
importExampleData 9.997 0.36310.727
importGeneSetsFromCollection0.7090.0370.745
importGeneSetsFromGMT0.0640.0020.067
importGeneSetsFromList0.1220.0010.122
importGeneSetsFromMSigDB45.199 0.55545.754
importMitoGeneSet0.0520.0020.054
importOptimus0.0010.0000.001
importSEQC0.1390.0170.157
importSTARsolo0.1430.0240.167
iterateSimulations0.1850.0250.210
listSampleSummaryStatsTables0.2490.0380.287
mergeSCEColData0.3550.0570.412
mouseBrainSubsetSCE0.0350.0010.036
msigdb_table0.0010.0000.001
plotBarcodeRankDropsResults0.5570.0030.560
plotBarcodeRankScatter0.6170.0020.619
plotBatchCorrCompare12.787 0.10613.071
plotBatchVariance0.3210.0000.322
plotBcdsResults8.8670.1258.315
plotBubble0.6930.0070.700
plotClusterAbundance0.7920.0110.804
plotCxdsResults6.9840.1177.179
plotDEGHeatmap2.0260.0062.032
plotDEGRegression3.3410.0503.384
plotDEGViolin3.9240.0783.996
plotDEGVolcano0.8530.0030.856
plotDecontXResults8.2480.0898.338
plotDimRed0.2430.0000.244
plotDoubletFinderResults40.263 0.29640.642
plotEmptyDropsResults6.6260.0586.683
plotEmptyDropsScatter6.4270.0146.442
plotFindMarkerHeatmap3.6760.0163.693
plotMASTThresholdGenes1.2220.0201.241
plotPCA0.3660.0050.372
plotPathway0.5210.0020.523
plotRunPerCellQCResults1.9240.0001.924
plotSCEBarAssayData0.1890.0010.191
plotSCEBarColData0.1440.0000.143
plotSCEBatchFeatureMean0.2730.0000.273
plotSCEDensity0.2130.0000.213
plotSCEDensityAssayData0.1710.0010.171
plotSCEDensityColData0.2060.0010.207
plotSCEDimReduceColData0.5070.0020.510
plotSCEDimReduceFeatures0.2730.0000.274
plotSCEHeatmap0.4910.0010.492
plotSCEScatter0.2650.0010.266
plotSCEViolin0.2580.0010.260
plotSCEViolinAssayData0.2470.0000.247
plotSCEViolinColData0.2440.0010.244
plotScDblFinderResults30.118 0.53930.383
plotScanpyDotPlot0.0220.0000.022
plotScanpyEmbedding0.0200.0010.022
plotScanpyHVG0.0220.0010.021
plotScanpyHeatmap0.0220.0000.022
plotScanpyMarkerGenes0.0210.0000.021
plotScanpyMarkerGenesDotPlot0.0230.0000.023
plotScanpyMarkerGenesHeatmap0.0220.0000.022
plotScanpyMarkerGenesMatrixPlot0.0200.0020.022
plotScanpyMarkerGenesViolin0.0210.0010.022
plotScanpyMatrixPlot0.0210.0010.022
plotScanpyPCA0.0220.0000.022
plotScanpyPCAGeneRanking0.0220.0000.021
plotScanpyPCAVariance0.0210.0000.022
plotScanpyViolin0.0210.0000.022
plotScdsHybridResults9.2140.0228.569
plotScrubletResults0.0220.0000.022
plotSeuratElbow0.0210.0010.022
plotSeuratHVG0.0210.0000.021
plotSeuratJackStraw0.0210.0000.021
plotSeuratReduction0.0220.0000.022
plotSoupXResults000
plotTSCANClusterDEG3.5610.0103.572
plotTSCANClusterPseudo1.2460.0051.251
plotTSCANDimReduceFeatures1.2130.0121.225
plotTSCANPseudotimeGenes1.3460.0051.351
plotTSCANPseudotimeHeatmap1.2940.0051.300
plotTSCANResults1.1080.0021.111
plotTSNE0.3050.0010.306
plotTopHVG0.5080.0020.511
plotUMAP7.2110.1127.401
readSingleCellMatrix0.0040.0010.005
reportCellQC0.0790.0010.080
reportDropletQC0.0210.0010.022
reportQCTool0.0770.0000.077
retrieveSCEIndex0.0280.0000.028
runBBKNN000
runBarcodeRankDrops0.2180.0000.219
runBcds1.9840.0011.186
runCellQC0.0830.0000.083
runClusterSummaryMetrics0.3880.0030.392
runComBatSeq0.4190.0030.422
runCxds0.3090.0010.310
runCxdsBcdsHybrid2.1230.0831.364
runDEAnalysis0.3590.0040.362
runDecontX7.3900.1117.503
runDimReduce0.2740.0010.275
runDoubletFinder36.408 0.30036.714
runDropletQC0.0230.0000.023
runEmptyDrops6.2640.0266.291
runEnrichR0.4900.0702.668
runFastMNN1.7040.0361.740
runFeatureSelection0.2120.0010.213
runFindMarker1.3980.0051.403
runGSVA0.7080.0110.719
runHarmony0.0370.0000.037
runKMeans0.1700.0020.172
runLimmaBC0.0760.0000.076
runMNNCorrect0.3870.0020.389
runModelGeneVar0.2890.0200.309
runNormalization2.4330.0832.516
runPerCellQC0.3150.0020.317
runSCANORAMA000
runSCMerge0.0040.0000.004
runScDblFinder20.397 0.37820.428
runScanpyFindClusters0.0220.0000.022
runScanpyFindHVG0.0190.0030.021
runScanpyFindMarkers0.0220.0000.022
runScanpyNormalizeData0.0970.0000.097
runScanpyPCA0.0220.0000.022
runScanpyScaleData0.0210.0010.022
runScanpyTSNE0.0220.0000.022
runScanpyUMAP0.0210.0000.022
runScranSNN0.2800.0010.281
runScrublet0.0220.0000.022
runSeuratFindClusters0.0210.0000.022
runSeuratFindHVG0.4490.0020.451
runSeuratHeatmap0.0220.0000.022
runSeuratICA0.0220.0000.022
runSeuratJackStraw0.0230.0000.023
runSeuratNormalizeData0.0210.0010.022
runSeuratPCA0.0210.0010.022
runSeuratSCTransform28.560 0.16628.728
runSeuratScaleData0.0220.0000.022
runSeuratUMAP0.0220.0000.023
runSingleR0.0380.0000.039
runSoupX000
runTSCAN0.6760.0030.679
runTSCANClusterDEAnalysis0.7720.0070.779
runTSCANDEG0.7890.0050.794
runTSNE0.7250.0130.738
runUMAP8.0930.1278.300
runVAM0.2960.0000.297
runZINBWaVE0.0040.0000.004
sampleSummaryStats0.1570.0000.157
scaterCPM0.1340.0000.134
scaterPCA0.4380.0020.440
scaterlogNormCounts0.2380.0000.237
sce0.0230.0000.023
sctkListGeneSetCollections0.0850.0000.085
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.0860.0000.086
setSCTKDisplayRow0.3090.0020.311
singleCellTK000
subDiffEx0.3240.0010.325
subsetSCECols0.0810.0010.081
subsetSCERows0.2670.0000.267
summarizeSCE0.0690.0010.070
trimCounts0.2180.0000.218