Back to Multiple platform build/check report for BioC 3.21:   simplified   long
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This page was generated on 2025-10-13 11:42 -0400 (Mon, 13 Oct 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.3 LTS)x86_644.5.1 (2025-06-13) -- "Great Square Root" 4833
merida1macOS 12.7.5 Montereyx86_644.5.1 RC (2025-06-05 r88288) -- "Great Square Root" 4614
kjohnson1macOS 13.6.6 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: 2025-10-09 13:40 -0400 (Thu, 09 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 12.7.5 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kjohnson1macOS 13.6.6 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: 2025-10-10 14:01:56 -0000 (Fri, 10 Oct 2025)
EndedAt: 2025-10-10 14:22:35 -0000 (Fri, 10 Oct 2025)
EllapsedTime: 1239.2 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     45.459  0.264  45.814
plotScDblFinderResults   44.959  0.418  45.586
plotDoubletFinderResults 44.479  0.239  44.922
runDoubletFinder         37.798  0.257  38.125
runScDblFinder           27.584  0.575  28.207
importExampleData        14.790  1.014  21.898
plotBatchCorrCompare     14.730  0.146  15.239
plotScdsHybridResults    12.359  0.096  11.528
plotBcdsResults          11.550  0.142  10.737
plotDecontXResults       10.009  0.069  10.094
plotCxdsResults           8.808  0.112   9.062
plotDEGViolin             8.660  0.160   8.838
plotUMAP                  7.938  0.090   8.183
runDecontX                7.879  0.052   7.945
runUMAP                   7.864  0.042   8.045
plotTSCANClusterDEG       7.416  0.119   7.598
plotDEGRegression         6.921  0.045   6.979
detectCellOutlier         6.733  0.208   6.953
convertSCEToSeurat        6.293  0.251   6.556
plotFindMarkerHeatmap     6.034  0.044   6.090
plotEmptyDropsScatter     5.748  0.036   5.793
plotEmptyDropsResults     5.738  0.001   5.748
runEmptyDrops             5.192  0.016   5.216
plotRunPerCellQCResults   5.024  0.013   5.045
getEnrichRResult          0.418  0.028   8.359
runEnrichR                0.364  0.059   8.817
* 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 
  0.196   0.037   0.220 

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
MitoGenes0.0000.0030.003
SEG0.0030.0000.003
calcEffectSizes0.2750.0240.301
combineSCE1.1560.0241.182
computeZScore0.3030.0120.315
convertSCEToSeurat6.2930.2516.556
convertSeuratToSCE0.4640.0160.481
dedupRowNames0.0800.0080.088
detectCellOutlier6.7330.2086.953
diffAbundanceFET0.0710.0000.071
discreteColorPalette0.0090.0000.008
distinctColors0.0030.0000.003
downSampleCells0.7370.0640.802
downSampleDepth0.6280.0000.629
expData-ANY-character-method0.1690.0040.173
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.2310.0160.247
expData-set0.2270.0040.232
expData0.1820.0030.187
expDataNames-ANY-method0.1600.0030.164
expDataNames0.1590.0000.159
expDeleteDataTag0.0400.0030.045
expSetDataTag0.0330.0000.032
expTaggedData0.0320.0000.032
exportSCE0.0280.0000.028
exportSCEtoAnnData0.0800.0000.081
exportSCEtoFlatFile0.0580.0200.078
featureIndex0.0440.0000.044
generateSimulatedData0.0590.0080.068
getBiomarker0.0700.0040.074
getDEGTopTable0.9720.0601.034
getDiffAbundanceResults0.0570.0000.057
getEnrichRResult0.4180.0288.359
getFindMarkerTopTable2.0300.1522.187
getMSigDBTable0.0050.0000.004
getPathwayResultNames0.0300.0000.031
getSampleSummaryStatsTable0.2640.0560.320
getSoupX000
getTSCANResults1.4400.1121.556
getTopHVG1.0600.0561.118
importAnnData0.0010.0000.002
importBUStools0.1890.0200.211
importCellRanger1.0170.0681.091
importCellRangerV2Sample0.1930.0040.196
importCellRangerV3Sample0.4050.0400.446
importDropEst0.2550.0120.269
importExampleData14.790 1.01421.898
importGeneSetsFromCollection1.0420.0681.113
importGeneSetsFromGMT0.0850.0000.087
importGeneSetsFromList0.1670.0040.172
importGeneSetsFromMSigDB1.4130.0881.504
importMitoGeneSet0.070.000.07
importOptimus0.0010.0000.002
importSEQC0.1870.0280.217
importSTARsolo0.2110.0200.233
iterateSimulations0.2420.0230.266
listSampleSummaryStatsTables0.4470.0320.481
mergeSCEColData0.5030.0200.525
mouseBrainSubsetSCE0.0450.0000.045
msigdb_table0.0020.0000.002
plotBarcodeRankDropsResults2.7160.1522.874
plotBarcodeRankScatter1.0610.0081.073
plotBatchCorrCompare14.730 0.14615.239
plotBatchVariance0.6940.0200.716
plotBcdsResults11.550 0.14210.737
plotBubble1.1140.0041.120
plotClusterAbundance2.1020.0122.119
plotCxdsResults8.8080.1129.062
plotDEGHeatmap3.0940.0043.108
plotDEGRegression6.9210.0456.979
plotDEGViolin8.6600.1608.838
plotDEGVolcano1.4000.0161.418
plotDecontXResults10.009 0.06910.094
plotDimRed0.4050.0000.407
plotDoubletFinderResults44.479 0.23944.922
plotEmptyDropsResults5.7380.0015.748
plotEmptyDropsScatter5.7480.0365.793
plotFindMarkerHeatmap6.0340.0446.090
plotMASTThresholdGenes2.0100.0122.025
plotPCA0.5740.0000.574
plotPathway1.1560.0041.163
plotRunPerCellQCResults5.0240.0135.045
plotSCEBarAssayData0.4180.0080.427
plotSCEBarColData0.4110.0000.412
plotSCEBatchFeatureMean0.7020.0000.704
plotSCEDensity0.4900.0040.495
plotSCEDensityAssayData0.4050.0000.406
plotSCEDensityColData0.4740.0000.476
plotSCEDimReduceColData1.2720.0041.279
plotSCEDimReduceFeatures0.580.000.58
plotSCEHeatmap0.6470.0040.653
plotSCEScatter0.5960.0000.597
plotSCEViolin0.5790.0000.581
plotSCEViolinAssayData0.6840.0120.701
plotSCEViolinColData0.5860.0000.588
plotScDblFinderResults44.959 0.41845.586
plotScanpyDotPlot0.0260.0000.027
plotScanpyEmbedding0.0270.0000.026
plotScanpyHVG0.0260.0000.027
plotScanpyHeatmap0.0260.0000.026
plotScanpyMarkerGenes0.0260.0000.026
plotScanpyMarkerGenesDotPlot0.0180.0080.026
plotScanpyMarkerGenesHeatmap0.0270.0000.027
plotScanpyMarkerGenesMatrixPlot0.0260.0000.026
plotScanpyMarkerGenesViolin0.0270.0000.027
plotScanpyMatrixPlot0.0270.0000.027
plotScanpyPCA0.0270.0000.026
plotScanpyPCAGeneRanking0.0260.0000.027
plotScanpyPCAVariance0.0220.0040.027
plotScanpyViolin0.0270.0000.028
plotScdsHybridResults12.359 0.09611.528
plotScrubletResults0.0320.0000.032
plotSeuratElbow0.0340.0000.035
plotSeuratHVG0.0310.0000.032
plotSeuratJackStraw0.0280.0040.032
plotSeuratReduction0.0330.0000.033
plotSoupXResults000
plotTSCANClusterDEG7.4160.1197.598
plotTSCANClusterPseudo2.1030.0082.119
plotTSCANDimReduceFeatures2.0530.0082.070
plotTSCANPseudotimeGenes2.5630.0242.601
plotTSCANPseudotimeHeatmap2.0210.0122.042
plotTSCANResults1.8270.0161.851
plotTSNE0.5660.0000.567
plotTopHVG0.9770.0040.984
plotUMAP7.9380.0908.183
readSingleCellMatrix0.0070.0000.006
reportCellQC0.1120.0040.117
reportDropletQC0.0290.0000.029
reportQCTool0.1140.0040.119
retrieveSCEIndex0.0360.0000.036
runBBKNN000
runBarcodeRankDrops0.3080.0000.309
runBcds3.1020.0242.033
runCellQC0.1040.0200.125
runClusterSummaryMetrics0.5480.0200.571
runComBatSeq0.6840.0000.686
runCxds0.4420.0000.444
runCxdsBcdsHybrid3.1170.0362.063
runDEAnalysis0.5410.0160.558
runDecontX7.8790.0527.945
runDimReduce0.3940.0000.395
runDoubletFinder37.798 0.25738.125
runDropletQC0.0250.0000.026
runEmptyDrops5.1920.0165.216
runEnrichR0.3640.0598.817
runFastMNN2.4280.1552.593
runFeatureSelection0.3070.0160.323
runFindMarker2.0910.0992.196
runGSVA1.0320.0601.096
runHarmony0.0560.0000.056
runKMeans0.3130.0320.345
runLimmaBC0.1070.0120.118
runMNNCorrect0.5440.0480.593
runModelGeneVar0.4450.0200.465
runNormalization2.8530.2553.113
runPerCellQC0.4460.0000.448
runSCANORAMA000
runSCMerge0.0050.0000.004
runScDblFinder27.584 0.57528.207
runScanpyFindClusters0.030.000.03
runScanpyFindHVG0.0310.0000.030
runScanpyFindMarkers0.0320.0000.032
runScanpyNormalizeData0.1310.0040.135
runScanpyPCA0.0310.0000.030
runScanpyScaleData0.0320.0000.033
runScanpyTSNE0.0320.0000.033
runScanpyUMAP0.0360.0000.035
runScranSNN0.3890.0000.389
runScrublet0.0270.0000.028
runSeuratFindClusters0.0290.0000.028
runSeuratFindHVG0.6340.0000.634
runSeuratHeatmap0.0270.0000.028
runSeuratICA0.0280.0000.028
runSeuratJackStraw0.0280.0000.028
runSeuratNormalizeData0.030.000.03
runSeuratPCA0.0250.0040.029
runSeuratSCTransform45.459 0.26445.814
runSeuratScaleData0.0270.0000.027
runSeuratUMAP0.0270.0000.026
runSingleR0.0520.0000.051
runSoupX000
runTSCAN0.9200.0000.921
runTSCANClusterDEAnalysis1.0040.0041.010
runTSCANDEG0.9740.0200.996
runTSNE1.0580.0081.068
runUMAP7.8640.0428.045
runVAM0.4210.0000.422
runZINBWaVE0.0040.0000.004
sampleSummaryStats0.2230.0000.224
scaterCPM0.140.000.14
scaterPCA0.6660.0010.668
scaterlogNormCounts0.30.00.3
sce0.0280.0000.029
sctkListGeneSetCollections0.1050.0000.105
sctkPythonInstallConda0.0010.0000.000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment0.0010.0000.000
setRowNames0.1140.0000.114
setSCTKDisplayRow0.5780.0190.599
singleCellTK000
subDiffEx0.4320.0040.437
subsetSCECols0.1160.0000.117
subsetSCERows0.3280.0040.333
summarizeSCE0.0860.0000.086
trimCounts0.2430.0000.244