Back to Multiple platform build/check report for BioC 3.21:   simplified   long
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This page was generated on 2025-10-16 11:41 -0400 (Thu, 16 Oct 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.3 LTS)x86_644.5.1 (2025-06-13) -- "Great Square Root" 4833
merida1macOS 12.7.6 Montereyx86_644.5.1 RC (2025-06-05 r88288) -- "Great Square Root" 4614
kjohnson1macOS 13.7.5 Venturaarm644.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" 4555
kunpeng2Linux (openEuler 24.03 LTS)aarch64R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" 4586
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 2.18.2  (landing page)
Joshua David Campbell
Snapshot Date: 2025-10-13 13:40 -0400 (Mon, 13 Oct 2025)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_21
git_last_commit: 6d6c3dd3
git_last_commit_date: 2025-09-25 17:05:42 -0400 (Thu, 25 Sep 2025)
nebbiolo1Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
merida1macOS 12.7.6 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kjohnson1macOS 13.7.5 Ventura / arm64  OK    OK    OK    OK  UNNEEDED, same version is already published
kunpeng2Linux (openEuler 24.03 LTS) / aarch64  OK    OK    ERROR  


CHECK results for singleCellTK on kunpeng2

To the developers/maintainers of the singleCellTK package:
- Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/singleCellTK.git to reflect on this report. See Troubleshooting Build Report for more information.
- Use the following Renviron settings to reproduce errors and warnings.
- If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information.
- See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host.

raw results


Summary

Package: singleCellTK
Version: 2.18.2
Command: /home/biocbuild/R/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings singleCellTK_2.18.2.tar.gz
StartedAt: 2025-10-14 14:21:49 -0000 (Tue, 14 Oct 2025)
EndedAt: 2025-10-14 14:45:21 -0000 (Tue, 14 Oct 2025)
EllapsedTime: 1412.8 seconds
RetCode: 1
Status:   ERROR  
CheckDir: singleCellTK.Rcheck
Warnings: NA

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings singleCellTK_2.18.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/singleCellTK.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.18.2’
* 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
runSeuratSCTransform     44.176  0.322  49.432
plotScDblFinderResults   43.913  0.317  51.188
plotDoubletFinderResults 43.723  0.204  49.972
runDoubletFinder         38.265  0.122  41.174
runScDblFinder           27.433  0.478  30.353
importExampleData        14.928  0.929  24.414
plotBatchCorrCompare     14.422  0.208  17.062
plotScdsHybridResults    13.346  0.135  14.893
plotBcdsResults          11.493  0.130  14.356
plotDecontXResults       10.181  0.098  11.910
plotCxdsResults           8.728  0.057  10.511
plotDEGViolin             8.267  0.063   9.029
runUMAP                   7.976  0.267  11.461
plotUMAP                  7.786  0.079   8.573
runDecontX                7.830  0.019   8.804
plotTSCANClusterDEG       7.305  0.095   7.960
detectCellOutlier         6.487  0.164   7.746
plotDEGRegression         6.579  0.064   7.789
convertSCEToSeurat        5.886  0.167   6.569
plotFindMarkerHeatmap     5.760  0.071   6.118
plotEmptyDropsResults     5.760  0.011   6.318
plotEmptyDropsScatter     5.704  0.020   6.299
runEmptyDrops             5.206  0.008   6.157
plotRunPerCellQCResults   4.691  0.043   5.217
runEnrichR                0.412  0.088  16.731
getEnrichRResult          0.408  0.052  10.801
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘spelling.R’
  Running ‘testthat.R’
 ERROR
Running the tests in ‘tests/testthat.R’ failed.
Last 13 lines of output:
  ── Error ('test-seuratFunctions.R:91:3'): Testing standard seurat workflow ─────
  <S7_error_method_not_found/error/error/condition>
  Error: Can't find method for generic `&(e1, e2)`:
  - e1: <patchwork>
  - e2: <theme>
  Backtrace:
      ▆
   1. └─singleCellTK::plotSeuratGenes(...) at test-seuratFunctions.R:91:3
   2.   └─Seurat::RidgePlot(...)
   3.     └─Seurat:::ExIPlot(...)
   4.       └─S7:::Ops.S7_object(plots, NoLegend())
  
  [ FAIL 1 | WARN 21 | SKIP 0 | PASS 220 ]
  Error: Test failures
  Execution halted
* 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 ERROR, 1 NOTE
See
  ‘/home/biocbuild/bbs-3.21-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.


Installation output

singleCellTK.Rcheck/00install.out

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


* installing to library ‘/home/biocbuild/R/R-devel_2025-02-19/site-library’
* installing *source* package ‘singleCellTK’ ...
** this is package ‘singleCellTK’ version ‘2.18.2’
** 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) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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

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

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

> if (requireNamespace('spelling', quietly = TRUE))
+   spelling::spell_check_test(vignettes = TRUE, error = FALSE, skip_on_cran = TRUE)
NULL
> 
> proc.time()
   user  system elapsed 
  0.218   0.017   0.442 

singleCellTK.Rcheck/tests/testthat.Rout.fail


R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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

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

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

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

Attaching package: 'MatrixGenerics'

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

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

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

Attaching package: 'generics'

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

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


Attaching package: 'BiocGenerics'

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

    IQR, mad, sd, var, xtabs

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

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

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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

    findMatches

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

    I, expand.grid, unname

Loading required package: IRanges
Loading required package: 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
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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  |======================================================================| 100%
Calculating gene variances
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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  |======================================================================| 100%
Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 1 | WARN 21 | SKIP 0 | PASS 220 ]

══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-seuratFunctions.R:91:3'): Testing standard seurat workflow ─────
<S7_error_method_not_found/error/error/condition>
Error: Can't find method for generic `&(e1, e2)`:
- e1: <patchwork>
- e2: <theme>
Backtrace:
    ▆
 1. └─singleCellTK::plotSeuratGenes(...) at test-seuratFunctions.R:91:3
 2.   └─Seurat::RidgePlot(...)
 3.     └─Seurat:::ExIPlot(...)
 4.       └─S7:::Ops.S7_object(plots, NoLegend())

[ FAIL 1 | WARN 21 | SKIP 0 | PASS 220 ]
Error: Test failures
Execution halted

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0030.0000.003
SEG0.0030.0000.003
calcEffectSizes0.2760.0040.282
combineSCE1.0420.0041.106
computeZScore0.2790.0040.288
convertSCEToSeurat5.8860.1676.569
convertSeuratToSCE0.4210.0000.448
dedupRowNames0.0670.0030.070
detectCellOutlier6.4870.1647.746
diffAbundanceFET0.0670.0000.067
discreteColorPalette0.0070.0000.008
distinctColors0.0030.0000.003
downSampleCells0.7080.0480.757
downSampleDepth0.6130.0040.777
expData-ANY-character-method0.1630.0040.168
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.2150.0000.215
expData-set0.2040.0040.208
expData0.1590.0040.163
expDataNames-ANY-method0.1520.0000.153
expDataNames0.1590.0000.324
expDeleteDataTag0.0430.0000.087
expSetDataTag0.0340.0000.071
expTaggedData0.0320.0000.044
exportSCE0.0260.0000.026
exportSCEtoAnnData0.0690.0080.078
exportSCEtoFlatFile0.0700.0080.078
featureIndex0.0450.0040.048
generateSimulatedData0.0660.0000.066
getBiomarker0.0690.0080.077
getDEGTopTable0.9820.0281.232
getDiffAbundanceResults0.0590.0000.059
getEnrichRResult 0.408 0.05210.801
getFindMarkerTopTable2.1840.1262.999
getMSigDBTable0.0040.0000.004
getPathwayResultNames0.0320.0000.032
getSampleSummaryStatsTable0.2930.0440.338
getSoupX000
getTSCANResults1.5200.1181.761
getTopHVG1.1590.0521.213
importAnnData0.0010.0000.002
importBUStools0.2090.0200.307
importCellRanger1.0770.0681.329
importCellRangerV2Sample0.1940.0160.209
importCellRangerV3Sample0.4310.0240.456
importDropEst0.2930.0040.302
importExampleData14.928 0.92924.414
importGeneSetsFromCollection1.0540.0721.129
importGeneSetsFromGMT0.0940.0040.165
importGeneSetsFromList0.1970.0000.357
importGeneSetsFromMSigDB1.3710.0921.625
importMitoGeneSet0.070.000.07
importOptimus0.0020.0000.002
importSEQC0.2050.0280.326
importSTARsolo0.2160.0160.239
iterateSimulations0.2340.0200.254
listSampleSummaryStatsTables0.4300.0360.467
mergeSCEColData0.5290.0080.595
mouseBrainSubsetSCE0.0550.0000.056
msigdb_table0.0020.0000.001
plotBarcodeRankDropsResults2.7380.1073.128
plotBarcodeRankScatter1.0580.0081.072
plotBatchCorrCompare14.422 0.20817.062
plotBatchVariance0.6680.0080.677
plotBcdsResults11.493 0.13014.356
plotBubble1.1470.0001.417
plotClusterAbundance2.1100.0112.160
plotCxdsResults 8.728 0.05710.511
plotDEGHeatmap2.9080.0122.946
plotDEGRegression6.5790.0647.789
plotDEGViolin8.2670.0639.029
plotDEGVolcano1.3820.0071.413
plotDecontXResults10.181 0.09811.910
plotDimRed0.3930.0050.397
plotDoubletFinderResults43.723 0.20449.972
plotEmptyDropsResults5.7600.0116.318
plotEmptyDropsScatter5.7040.0206.299
plotFindMarkerHeatmap5.7600.0716.118
plotMASTThresholdGenes1.8920.0122.045
plotPCA0.5310.0000.538
plotPathway0.9850.0041.138
plotRunPerCellQCResults4.6910.0435.217
plotSCEBarAssayData0.3910.0030.397
plotSCEBarColData0.3320.0000.400
plotSCEBatchFeatureMean0.6260.0000.701
plotSCEDensity0.4430.0000.444
plotSCEDensityAssayData0.3840.0040.391
plotSCEDensityColData0.4510.0000.593
plotSCEDimReduceColData1.0950.0001.097
plotSCEDimReduceFeatures0.5290.0000.535
plotSCEHeatmap0.5820.0000.588
plotSCEScatter0.5460.0030.550
plotSCEViolin0.5410.0000.723
plotSCEViolinAssayData0.5920.0000.593
plotSCEViolinColData0.5720.0040.585
plotScDblFinderResults43.913 0.31751.188
plotScanpyDotPlot0.0330.0000.070
plotScanpyEmbedding0.0300.0000.029
plotScanpyHVG0.030.000.03
plotScanpyHeatmap0.0260.0040.030
plotScanpyMarkerGenes0.030.000.03
plotScanpyMarkerGenesDotPlot0.030.000.03
plotScanpyMarkerGenesHeatmap0.0260.0040.029
plotScanpyMarkerGenesMatrixPlot0.0300.0000.029
plotScanpyMarkerGenesViolin0.0290.0000.029
plotScanpyMatrixPlot0.0260.0040.030
plotScanpyPCA0.0310.0000.031
plotScanpyPCAGeneRanking0.0300.0000.029
plotScanpyPCAVariance0.030.000.03
plotScanpyViolin0.0290.0000.029
plotScdsHybridResults13.346 0.13514.893
plotScrubletResults0.0290.0000.029
plotSeuratElbow0.0290.0000.029
plotSeuratHVG0.0290.0000.029
plotSeuratJackStraw0.0280.0000.029
plotSeuratReduction0.0290.0000.029
plotSoupXResults000
plotTSCANClusterDEG7.3050.0957.960
plotTSCANClusterPseudo2.0520.0002.065
plotTSCANDimReduceFeatures1.9250.0122.148
plotTSCANPseudotimeGenes2.4760.0282.814
plotTSCANPseudotimeHeatmap2.0380.0002.340
plotTSCANResults1.7860.0041.795
plotTSNE0.5470.0000.554
plotTopHVG0.9000.0000.903
plotUMAP7.7860.0798.573
readSingleCellMatrix0.0060.0000.006
reportCellQC0.1070.0000.107
reportDropletQC0.0260.0000.026
reportQCTool0.1050.0000.105
retrieveSCEIndex0.0330.0000.032
runBBKNN000
runBarcodeRankDrops0.2840.0000.284
runBcds3.8650.0323.941
runCellQC0.1040.0000.105
runClusterSummaryMetrics0.4900.0080.499
runComBatSeq0.6500.0120.687
runCxds0.4310.0000.431
runCxdsBcdsHybrid3.9110.0564.092
runDEAnalysis0.5610.0000.562
runDecontX7.8300.0198.804
runDimReduce0.3750.0000.376
runDoubletFinder38.265 0.12241.174
runDropletQC0.0230.0040.027
runEmptyDrops5.2060.0086.157
runEnrichR 0.412 0.08816.731
runFastMNN2.3130.2472.765
runFeatureSelection0.2980.0160.328
runFindMarker1.9210.1322.096
runGSVA1.0100.0721.152
runHarmony0.0580.0000.058
runKMeans0.3060.0400.347
runLimmaBC0.1160.0120.128
runMNNCorrect0.5730.0360.611
runModelGeneVar0.4330.0160.559
runNormalization2.8140.2043.196
runPerCellQC0.4140.0040.419
runSCANORAMA000
runSCMerge0.0040.0000.005
runScDblFinder27.433 0.47830.353
runScanpyFindClusters0.0240.0040.028
runScanpyFindHVG0.0270.0000.027
runScanpyFindMarkers0.0270.0000.027
runScanpyNormalizeData0.1310.0000.131
runScanpyPCA0.0280.0000.027
runScanpyScaleData0.0270.0000.028
runScanpyTSNE0.0240.0040.028
runScanpyUMAP0.0280.0000.027
runScranSNN0.3870.0040.571
runScrublet0.0330.0000.066
runSeuratFindClusters0.0290.0000.056
runSeuratFindHVG0.6520.0000.807
runSeuratHeatmap0.0300.0000.029
runSeuratICA0.0260.0040.031
runSeuratJackStraw0.0250.0040.030
runSeuratNormalizeData0.0310.0000.030
runSeuratPCA0.030.000.03
runSeuratSCTransform44.176 0.32249.432
runSeuratScaleData0.0310.0000.030
runSeuratUMAP0.0310.0000.031
runSingleR0.0510.0000.052
runSoupX000
runTSCAN0.9380.0041.435
runTSCANClusterDEAnalysis1.0430.0001.185
runTSCANDEG0.9700.0041.051
runTSNE1.0470.0041.137
runUMAP 7.976 0.26711.461
runVAM0.4090.0360.455
runZINBWaVE0.0040.0000.005
sampleSummaryStats0.2320.0080.240
scaterCPM0.1360.0080.144
scaterPCA0.6470.0320.773
scaterlogNormCounts0.2750.0120.288
sce0.0250.0000.024
sctkListGeneSetCollections0.1040.0080.186
sctkPythonInstallConda0.0010.0000.000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.0950.0120.107
setSCTKDisplayRow0.5870.0400.707
singleCellTK000
subDiffEx0.4250.0120.467
subsetSCECols0.1080.0000.108
subsetSCERows0.3560.0160.556
summarizeSCE0.0910.0000.107
trimCounts0.2410.0160.258