Back to Multiple platform build/check report for BioC 3.21:   simplified   long
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This page was generated on 2025-04-22 13:17 -0400 (Tue, 22 Apr 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.1 LTS)x86_644.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six" 4831
palomino7Windows Server 2022 Datacenterx644.5.0 RC (2025-04-04 r88126 ucrt) -- "How About a Twenty-Six" 4573
lconwaymacOS 12.7.1 Montereyx86_644.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six" 4599
kjohnson3macOS 13.7.1 Venturaarm644.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six" 4553
kunpeng2Linux (openEuler 24.03 LTS)aarch64R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" 4570
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 2013/2341HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.18.0  (landing page)
Joshua David Campbell
Snapshot Date: 2025-04-21 13:40 -0400 (Mon, 21 Apr 2025)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_21
git_last_commit: e453fa1
git_last_commit_date: 2025-04-15 13:34:17 -0400 (Tue, 15 Apr 2025)
nebbiolo1Linux (Ubuntu 24.04.1 LTS) / x86_64  OK    OK    OK  NO, package depends on 'MAST' which is not available
palomino7Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  NO, package depends on 'batchelor' which is only available as a source package that needs compilation
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 'DelayedArray' which is only available as a source package that needs compilation
kunpeng2Linux (openEuler 24.03 LTS) / aarch64  OK    OK    OK  


CHECK results for singleCellTK on lconway

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: 2.18.0
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_2.18.0.tar.gz
StartedAt: 2025-04-21 23:37:16 -0400 (Mon, 21 Apr 2025)
EndedAt: 2025-04-21 23:52:54 -0400 (Mon, 21 Apr 2025)
EllapsedTime: 938.1 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_2.18.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/singleCellTK.Rcheck’
* using R version 4.5.0 RC (2025-04-04 r88126)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.18.0’
* 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  6.8Mb
  sub-directories of 1Mb or more:
    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
  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 34.764  0.236  35.168
plotScDblFinderResults   31.829  0.803  32.806
runDoubletFinder         31.301  0.204  31.634
runScDblFinder           20.880  0.519  21.549
importExampleData        15.100  1.812  17.529
plotBatchCorrCompare     11.329  0.119  11.501
plotScdsHybridResults     8.577  0.112   8.729
plotBcdsResults           7.903  0.155   8.094
plotDecontXResults        7.286  0.053   7.368
plotUMAP                  6.680  0.076   6.784
runDecontX                6.520  0.069   6.618
plotCxdsResults           6.256  0.054   6.332
runUMAP                   6.229  0.068   6.331
plotEmptyDropsScatter     6.119  0.035   6.190
plotEmptyDropsResults     6.061  0.033   6.121
runEmptyDrops             5.574  0.032   5.632
detectCellOutlier         5.436  0.149   5.623
runSeuratSCTransform      5.345  0.087   5.467
getEnrichRResult          0.351  0.043   9.463
* 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-3.21-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/4.5-x86_64/Resources/library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.18.0’
** using staged installation
** R
** data
** exec
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (singleCellTK)

Tests output

singleCellTK.Rcheck/tests/spelling.Rout


R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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 
  0.187   0.074   0.250 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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: GenomeInfoDb
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
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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  |======================================================================| 100%
Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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

Number of nodes: 390
Number of edges: 9849

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

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

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

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

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

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

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

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  |======================================================================| 100%
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]

[ FAIL 0 | WARN 21 | SKIP 0 | PASS 225 ]
> 
> proc.time()
   user  system elapsed 
251.727   7.208 269.465 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0020.0030.006
SEG0.0030.0020.005
calcEffectSizes0.2160.0170.235
combineSCE0.8990.0240.928
computeZScore0.2420.0090.261
convertSCEToSeurat4.6470.2624.950
convertSeuratToSCE0.3980.0110.411
dedupRowNames0.0670.0030.071
detectCellOutlier5.4360.1495.623
diffAbundanceFET0.0610.0040.066
discreteColorPalette0.0070.0010.008
distinctColors0.0020.0000.003
downSampleCells0.5830.0560.647
downSampleDepth0.4880.0390.530
expData-ANY-character-method0.1560.0080.164
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1930.0080.204
expData-set0.1790.0070.187
expData0.1460.0060.152
expDataNames-ANY-method0.1330.0060.138
expDataNames0.1380.0070.147
expDeleteDataTag0.0480.0030.052
expSetDataTag0.0330.0030.037
expTaggedData0.0380.0030.042
exportSCE0.0310.0050.036
exportSCEtoAnnData0.0650.0030.068
exportSCEtoFlatFile0.0740.0020.077
featureIndex0.0480.0060.055
generateSimulatedData0.0630.0080.070
getBiomarker0.0750.0070.083
getDEGTopTable0.8060.0700.881
getDiffAbundanceResults0.0550.0040.060
getEnrichRResult0.3510.0439.463
getFindMarkerTopTable1.7080.0511.771
getMSigDBTable0.0040.0040.009
getPathwayResultNames0.0310.0040.036
getSampleSummaryStatsTable0.2500.0090.261
getSoupX0.0000.0000.001
getTSCANResults1.1530.0541.216
getTopHVG0.9620.0200.988
importAnnData0.0020.0000.003
importBUStools0.1830.0070.198
importCellRanger0.9730.0411.034
importCellRangerV2Sample0.1880.0040.196
importCellRangerV3Sample0.4070.0190.432
importDropEst0.2490.0040.256
importExampleData15.100 1.81217.529
importGeneSetsFromCollection0.7910.1320.938
importGeneSetsFromGMT0.0760.0050.080
importGeneSetsFromList0.1520.0060.158
importGeneSetsFromMSigDB1.1530.0601.221
importMitoGeneSet0.0550.0050.061
importOptimus0.0010.0000.002
importSEQC0.1490.0040.156
importSTARsolo0.1680.0040.172
iterateSimulations0.1850.0110.199
listSampleSummaryStatsTables0.2680.0050.274
mergeSCEColData0.4070.0350.451
mouseBrainSubsetSCE0.0430.0060.050
msigdb_table0.0010.0020.003
plotBarcodeRankDropsResults0.6770.0290.709
plotBarcodeRankScatter0.7140.0100.727
plotBatchCorrCompare11.329 0.11911.501
plotBatchVariance0.3470.0160.364
plotBcdsResults7.9030.1558.094
plotBubble0.8150.0470.870
plotClusterAbundance0.9250.0090.940
plotCxdsResults6.2560.0546.332
plotDEGHeatmap2.3710.0442.430
plotDEGRegression3.8020.0623.888
plotDEGViolin4.6960.0884.808
plotDEGVolcano0.9660.0190.992
plotDecontXResults7.2860.0537.368
plotDimRed0.2090.0070.217
plotDoubletFinderResults34.764 0.23635.168
plotEmptyDropsResults6.0610.0336.121
plotEmptyDropsScatter6.1190.0356.190
plotFindMarkerHeatmap4.4420.0404.498
plotMASTThresholdGenes1.4300.0331.467
plotPCA0.3250.0090.336
plotPathway0.5730.0100.586
plotRunPerCellQCResults2.2200.0212.250
plotSCEBarAssayData0.2130.0060.220
plotSCEBarColData0.1440.0050.151
plotSCEBatchFeatureMean0.2120.0020.215
plotSCEDensity0.2300.0060.240
plotSCEDensityAssayData0.2080.0090.218
plotSCEDensityColData0.2600.0070.270
plotSCEDimReduceColData0.6650.0120.681
plotSCEDimReduceFeatures0.3320.0100.344
plotSCEHeatmap0.4980.0090.510
plotSCEScatter0.3060.0100.321
plotSCEViolin0.2760.0070.284
plotSCEViolinAssayData0.3550.0080.367
plotSCEViolinColData0.3010.0080.312
plotScDblFinderResults31.829 0.80332.806
plotScanpyDotPlot0.0280.0050.032
plotScanpyEmbedding0.0270.0030.030
plotScanpyHVG0.0300.0040.035
plotScanpyHeatmap0.0250.0040.029
plotScanpyMarkerGenes0.0280.0050.034
plotScanpyMarkerGenesDotPlot0.0270.0030.031
plotScanpyMarkerGenesHeatmap0.0290.0040.033
plotScanpyMarkerGenesMatrixPlot0.0270.0030.030
plotScanpyMarkerGenesViolin0.0300.0030.033
plotScanpyMatrixPlot0.0260.0030.030
plotScanpyPCA0.0270.0040.031
plotScanpyPCAGeneRanking0.0300.0040.034
plotScanpyPCAVariance0.0260.0040.030
plotScanpyViolin0.0280.0050.033
plotScdsHybridResults8.5770.1128.729
plotScrubletResults0.0240.0030.028
plotSeuratElbow0.0220.0030.025
plotSeuratHVG0.0280.0040.031
plotSeuratJackStraw0.0240.0020.027
plotSeuratReduction0.0290.0020.031
plotSoupXResults0.0000.0010.000
plotTSCANClusterDEG4.2290.1254.377
plotTSCANClusterPseudo1.4900.0281.526
plotTSCANDimReduceFeatures1.4400.0251.471
plotTSCANPseudotimeGenes1.5660.0231.595
plotTSCANPseudotimeHeatmap1.5950.0281.628
plotTSCANResults1.3490.0311.386
plotTSNE0.3800.0140.396
plotTopHVG0.6040.0180.624
plotUMAP6.6800.0766.784
readSingleCellMatrix0.0060.0020.008
reportCellQC0.1050.0050.111
reportDropletQC0.0290.0050.033
reportQCTool0.0980.0060.104
retrieveSCEIndex0.0320.0030.036
runBBKNN000
runBarcodeRankDrops0.2510.0090.265
runBcds1.8130.0611.883
runCellQC0.1060.0050.112
runClusterSummaryMetrics0.4300.0100.442
runComBatSeq0.4800.0200.502
runCxds0.3680.0140.386
runCxdsBcdsHybrid1.9230.1122.042
runDEAnalysis0.4170.0090.427
runDecontX6.5200.0696.618
runDimReduce0.3120.0070.321
runDoubletFinder31.301 0.20431.634
runDropletQC0.0300.0040.034
runEmptyDrops5.5740.0325.632
runEnrichR0.2970.0372.897
runFastMNN1.8290.0481.887
runFeatureSelection0.2360.0070.244
runFindMarker1.6610.0391.707
runGSVA2.3660.0832.469
runHarmony0.0530.0020.054
runKMeans0.2180.0120.231
runLimmaBC0.0990.0020.102
runMNNCorrect0.4770.0060.486
runModelGeneVar0.4010.0080.412
runNormalization2.3460.0402.404
runPerCellQC0.3740.0140.391
runSCANORAMA0.0000.0010.001
runSCMerge0.0040.0020.005
runScDblFinder20.880 0.51921.549
runScanpyFindClusters0.0230.0030.026
runScanpyFindHVG0.0270.0050.031
runScanpyFindMarkers0.0290.0050.033
runScanpyNormalizeData0.1200.0060.126
runScanpyPCA0.0270.0040.030
runScanpyScaleData0.0250.0040.028
runScanpyTSNE0.0280.0050.032
runScanpyUMAP0.0240.0030.027
runScranSNN0.3230.0140.338
runScrublet0.0260.0050.031
runSeuratFindClusters0.0320.0020.034
runSeuratFindHVG0.5200.0110.533
runSeuratHeatmap0.0250.0060.031
runSeuratICA0.0280.0030.031
runSeuratJackStraw0.0280.0040.033
runSeuratNormalizeData0.0240.0030.028
runSeuratPCA0.0280.0030.031
runSeuratSCTransform5.3450.0875.467
runSeuratScaleData0.0230.0050.026
runSeuratUMAP0.0210.0030.025
runSingleR0.0470.0010.049
runSoupX0.0010.0000.001
runTSCAN0.7420.0180.763
runTSCANClusterDEAnalysis0.9030.0230.929
runTSCANDEG0.8930.0200.918
runTSNE0.7110.0140.728
runUMAP6.2290.0686.331
runVAM0.3490.0080.361
runZINBWaVE0.0050.0010.006
sampleSummaryStats0.1960.0070.205
scaterCPM0.1200.0020.124
scaterPCA0.5260.0100.538
scaterlogNormCounts0.2060.0030.211
sce0.0260.0040.031
sctkListGeneSetCollections0.0880.0040.092
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv000
selectSCTKConda0.0010.0010.000
selectSCTKVirtualEnvironment000
setRowNames0.0980.0050.105
setSCTKDisplayRow0.3240.0070.332
singleCellTK0.0000.0000.001
subDiffEx0.3570.0200.382
subsetSCECols0.0970.0070.103
subsetSCERows0.2990.0240.326
summarizeSCE0.0720.0050.078
trimCounts0.1880.0070.196