Joshua David Campbell
| Snapshot Date: 2026-03-20 13:40 -0400 (Fri, 20 Mar 2026) |
| git_url: https://git.bioconductor.org/packages/singleCellTK |
| git_branch: devel |
| git_last_commit: 15d4a13 |
| git_last_commit_date: 2026-01-11 08:42:53 -0400 (Sun, 11 Jan 2026) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-03-21 11:35 -0400 (Sat, 21 Mar 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences" | 4866 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2026-03-20 r89666) -- "Unsuffered Consequences" | 4545 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 2038/2368 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| singleCellTK 2.21.1 (landing page) Joshua David Campbell
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
| See other builds for singleCellTK in R Universe. | ||||||||||||||
|
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. |
| Package: singleCellTK |
| Version: 2.21.1 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.21.1.tar.gz |
| StartedAt: 2026-03-21 01:27:25 -0400 (Sat, 21 Mar 2026) |
| EndedAt: 2026-03-21 01:34:15 -0400 (Sat, 21 Mar 2026) |
| EllapsedTime: 409.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: singleCellTK.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.21.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck’
* using R Under development (unstable) (2026-03-20 r89666)
* using platform: aarch64-apple-darwin23
* R was compiled by
Apple clang version 17.0.0 (clang-1700.3.19.1)
GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-03-21 05:27:26 UTC
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.21.1’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 80 non-default packages.
Importing from so many packages makes the package vulnerable to any of
them becoming unavailable. Move as many as possible to Suggests and
use conditionally.
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘singleCellTK’ can be installed ... OK
* checking installed package size ... INFO
installed size is 6.8Mb
sub-directories of 1Mb or more:
R 1.0Mb
extdata 1.5Mb
shiny 2.9Mb
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
dedupRowNames.Rd: SingleCellExperiment-class
detectCellOutlier.Rd: colData
diffAbundanceFET.Rd: colData
downSampleCells.Rd: SingleCellExperiment-class
downSampleDepth.Rd: SingleCellExperiment-class
featureIndex.Rd: SummarizedExperiment-class,
SingleCellExperiment-class
getBiomarker.Rd: SingleCellExperiment-class
getDEGTopTable.Rd: SingleCellExperiment-class
getEnrichRResult.Rd: SingleCellExperiment-class
getFindMarkerTopTable.Rd: SingleCellExperiment-class
getGenesetNamesFromCollection.Rd: SingleCellExperiment-class
getPathwayResultNames.Rd: SingleCellExperiment-class
getSampleSummaryStatsTable.Rd: SingleCellExperiment-class, assay,
colData
getSoupX.Rd: SingleCellExperiment-class
getTSCANResults.Rd: SingleCellExperiment-class
getTopHVG.Rd: SingleCellExperiment-class
importAlevin.Rd: DelayedArray, readMM
importAnnData.Rd: DelayedArray, readMM
importBUStools.Rd: readMM
importCellRanger.Rd: readMM, DelayedArray
importCellRangerV2Sample.Rd: readMM, DelayedArray
importCellRangerV3Sample.Rd: readMM, DelayedArray
importDropEst.Rd: DelayedArray, readMM
importExampleData.Rd: scRNAseq, Matrix, DelayedArray,
ReprocessedFluidigmData, ReprocessedAllenData, NestorowaHSCData
importFromFiles.Rd: readMM, DelayedArray, SingleCellExperiment-class
importGeneSetsFromCollection.Rd: GeneSetCollection-class,
SingleCellExperiment-class, GeneSetCollection, GSEABase, metadata
importGeneSetsFromGMT.Rd: GeneSetCollection-class,
SingleCellExperiment-class, getGmt, GSEABase, metadata
importGeneSetsFromList.Rd: GeneSetCollection-class,
SingleCellExperiment-class, GSEABase, metadata
importGeneSetsFromMSigDB.Rd: SingleCellExperiment-class, msigdbr,
GeneSetCollection-class, GSEABase, metadata
importMitoGeneSet.Rd: SingleCellExperiment-class,
GeneSetCollection-class, GSEABase, metadata
importMultipleSources.Rd: DelayedArray
importOptimus.Rd: readMM, DelayedArray
importSEQC.Rd: readMM, DelayedArray
importSTARsolo.Rd: readMM, DelayedArray
iterateSimulations.Rd: SingleCellExperiment-class
listSampleSummaryStatsTables.Rd: SingleCellExperiment-class, metadata
plotBarcodeRankDropsResults.Rd: SingleCellExperiment-class
plotBarcodeRankScatter.Rd: SingleCellExperiment-class
plotBatchCorrCompare.Rd: SingleCellExperiment-class
plotBatchVariance.Rd: SingleCellExperiment-class
plotBcdsResults.Rd: SingleCellExperiment-class
plotClusterAbundance.Rd: colData
plotCxdsResults.Rd: SingleCellExperiment-class
plotDEGHeatmap.Rd: SingleCellExperiment-class
plotDEGRegression.Rd: SingleCellExperiment-class
plotDEGViolin.Rd: SingleCellExperiment-class
plotDEGVolcano.Rd: SingleCellExperiment-class
plotDecontXResults.Rd: SingleCellExperiment-class
plotDoubletFinderResults.Rd: SingleCellExperiment-class
plotEmptyDropsResults.Rd: SingleCellExperiment-class
plotEmptyDropsScatter.Rd: SingleCellExperiment-class
plotEnrichR.Rd: SingleCellExperiment-class
plotFindMarkerHeatmap.Rd: SingleCellExperiment-class
plotPCA.Rd: SingleCellExperiment-class
plotPathway.Rd: SingleCellExperiment-class
plotRunPerCellQCResults.Rd: SingleCellExperiment-class
plotSCEBarAssayData.Rd: SingleCellExperiment-class
plotSCEBarColData.Rd: SingleCellExperiment-class
plotSCEBatchFeatureMean.Rd: SingleCellExperiment-class
plotSCEDensity.Rd: SingleCellExperiment-class
plotSCEDensityAssayData.Rd: SingleCellExperiment-class
plotSCEDensityColData.Rd: SingleCellExperiment-class
plotSCEDimReduceColData.Rd: SingleCellExperiment-class
plotSCEDimReduceFeatures.Rd: SingleCellExperiment-class
plotSCEHeatmap.Rd: SingleCellExperiment-class
plotSCEScatter.Rd: SingleCellExperiment-class
plotSCEViolin.Rd: SingleCellExperiment-class
plotSCEViolinAssayData.Rd: SingleCellExperiment-class
plotSCEViolinColData.Rd: SingleCellExperiment-class
plotScDblFinderResults.Rd: SingleCellExperiment-class
plotScdsHybridResults.Rd: SingleCellExperiment-class
plotScrubletResults.Rd: SingleCellExperiment-class
plotSoupXResults.Rd: SingleCellExperiment-class
plotTSCANClusterDEG.Rd: SingleCellExperiment-class
plotTSCANClusterPseudo.Rd: SingleCellExperiment-class
plotTSCANDimReduceFeatures.Rd: SingleCellExperiment-class
plotTSCANPseudotimeGenes.Rd: SingleCellExperiment-class
plotTSCANPseudotimeHeatmap.Rd: SingleCellExperiment-class
plotTSCANResults.Rd: SingleCellExperiment-class
plotTSNE.Rd: SingleCellExperiment-class
plotUMAP.Rd: SingleCellExperiment-class
readSingleCellMatrix.Rd: DelayedArray
reportCellQC.Rd: SingleCellExperiment-class
reportClusterAbundance.Rd: colData
reportDiffAbundanceFET.Rd: colData
retrieveSCEIndex.Rd: SingleCellExperiment-class
runBBKNN.Rd: SingleCellExperiment-class
runBarcodeRankDrops.Rd: SingleCellExperiment-class, colData
runBcds.Rd: SingleCellExperiment-class, colData
runCellQC.Rd: colData
runComBatSeq.Rd: SingleCellExperiment-class
runCxds.Rd: SingleCellExperiment-class, colData
runCxdsBcdsHybrid.Rd: colData
runDEAnalysis.Rd: SingleCellExperiment-class
runDecontX.Rd: colData
runDimReduce.Rd: SingleCellExperiment-class
runDoubletFinder.Rd: SingleCellExperiment-class
runDropletQC.Rd: colData
runEmptyDrops.Rd: SingleCellExperiment-class, colData
runEnrichR.Rd: SingleCellExperiment-class
runFastMNN.Rd: SingleCellExperiment-class, BiocParallelParam-class
runFeatureSelection.Rd: SingleCellExperiment-class
runFindMarker.Rd: SingleCellExperiment-class
runGSVA.Rd: SingleCellExperiment-class
runHarmony.Rd: SingleCellExperiment-class
runKMeans.Rd: SingleCellExperiment-class, colData
runLimmaBC.Rd: SingleCellExperiment-class, assay
runMNNCorrect.Rd: SingleCellExperiment-class, assay,
BiocParallelParam-class
runModelGeneVar.Rd: SingleCellExperiment-class
runPerCellQC.Rd: SingleCellExperiment-class, BiocParallelParam,
colData
runSCANORAMA.Rd: SingleCellExperiment-class, assay
runSCMerge.Rd: SingleCellExperiment-class, colData, assay,
BiocParallelParam-class
runScDblFinder.Rd: SingleCellExperiment-class, colData
runScranSNN.Rd: SingleCellExperiment-class, reducedDim, assay,
altExp, colData, igraph
runScrublet.Rd: SingleCellExperiment-class, colData
runSingleR.Rd: SingleCellExperiment-class
runSoupX.Rd: SingleCellExperiment-class
runTSCAN.Rd: SingleCellExperiment-class
runTSCANClusterDEAnalysis.Rd: SingleCellExperiment-class
runTSCANDEG.Rd: SingleCellExperiment-class
runTSNE.Rd: SingleCellExperiment-class
runUMAP.Rd: SingleCellExperiment-class, BiocParallelParam-class
runVAM.Rd: SingleCellExperiment-class
runZINBWaVE.Rd: SingleCellExperiment-class, colData,
BiocParallelParam-class
sampleSummaryStats.Rd: SingleCellExperiment-class, assay, colData
scaterPCA.Rd: SingleCellExperiment-class, BiocParallelParam-class
scaterlogNormCounts.Rd: logNormCounts
sctkListGeneSetCollections.Rd: GeneSetCollection-class
sctkPythonInstallConda.Rd: conda_install, reticulate, conda_create
sctkPythonInstallVirtualEnv.Rd: virtualenv_install, reticulate,
virtualenv_create
selectSCTKConda.Rd: reticulate
selectSCTKVirtualEnvironment.Rd: reticulate
setRowNames.Rd: SingleCellExperiment-class
setSCTKDisplayRow.Rd: SingleCellExperiment-class
singleCellTK.Rd: SingleCellExperiment-class
subsetSCECols.Rd: SingleCellExperiment-class
subsetSCERows.Rd: SingleCellExperiment-class, altExp
summarizeSCE.Rd: SingleCellExperiment-class
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
plotDoubletFinderResults 15.915 0.196 16.604
runDoubletFinder 14.754 0.193 15.507
plotScDblFinderResults 12.995 0.306 13.769
runScDblFinder 7.827 0.118 8.202
importExampleData 5.465 0.953 7.473
plotBatchCorrCompare 5.586 0.102 5.969
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘spelling.R’
Running ‘testthat.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 NOTE
See
‘/Users/biocbuild/bbs-3.23-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.
singleCellTK.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL singleCellTK ### ############################################################################## ############################################################################## * installing to library ‘/Library/Frameworks/R.framework/Versions/4.6/Resources/library’ * installing *source* package ‘singleCellTK’ ... ** this is package ‘singleCellTK’ version ‘2.21.1’ ** using staged installation ** R ** data ** exec ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (singleCellTK)
singleCellTK.Rcheck/tests/spelling.Rout
R Under development (unstable) (2026-03-20 r89666) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> if (requireNamespace('spelling', quietly = TRUE))
+ spelling::spell_check_test(vignettes = TRUE, error = FALSE, skip_on_cran = TRUE)
All Done!
>
> proc.time()
user system elapsed
0.097 0.036 0.131
singleCellTK.Rcheck/tests/testthat.Rout
R Under development (unstable) (2026-03-20 r89666) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(testthat)
> library(singleCellTK)
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats
Attaching package: 'MatrixGenerics'
The following objects are masked from 'package:matrixStats':
colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
colWeightedMeans, colWeightedMedians, colWeightedSds,
colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
rowWeightedSds, rowWeightedVars
Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: generics
Attaching package: 'generics'
The following objects are masked from 'package:base':
as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
setequal, union
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
as.data.frame, basename, cbind, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
unsplit, which.max, which.min
Loading required package: S4Vectors
Attaching package: 'S4Vectors'
The following object is masked from 'package:utils':
findMatches
The following objects are masked from 'package:base':
I, expand.grid, unname
Loading required package: IRanges
Loading required package: Seqinfo
Loading required package: Biobase
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Attaching package: 'Biobase'
The following object is masked from 'package:MatrixGenerics':
rowMedians
The following objects are masked from 'package:matrixStats':
anyMissing, rowMedians
Loading required package: SingleCellExperiment
Loading required package: DelayedArray
Loading required package: Matrix
Attaching package: 'Matrix'
The following object is masked from 'package:S4Vectors':
expand
Loading required package: S4Arrays
Loading required package: abind
Attaching package: 'S4Arrays'
The following object is masked from 'package:abind':
abind
The following object is masked from 'package:base':
rowsum
Loading required package: SparseArray
Attaching package: 'DelayedArray'
The following objects are masked from 'package:base':
apply, scale, sweep
Attaching package: 'singleCellTK'
The following object is masked from 'package:BiocGenerics':
plotPCA
>
> test_check("singleCellTK")
Found 2 batches
Using null model in ComBat-seq.
Adjusting for 0 covariate(s) or covariate level(s)
Estimating dispersions
Fitting the GLM model
Shrinkage off - using GLM estimates for parameters
Adjusting the data
Found 2 batches
Using null model in ComBat-seq.
Adjusting for 1 covariate(s) or covariate level(s)
Estimating dispersions
Fitting the GLM model
Shrinkage off - using GLM estimates for parameters
Adjusting the data
Performing log-normalization
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
|
| | 0%
|
|======================================================================| 100%
Calculating gene variances
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
|
| | 0%
|
|======================================================================| 100%
|
| | 0%
|
|======================================================================| 100%
Calculating gene variances
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Uploading data to Enrichr... Done.
Querying HDSigDB_Human_2021... Done.
Parsing results... Done.
Performing log-normalization
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Performing log-normalization
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
|
| | 0%
|
|======================================================================| 100%
[01:33:19] WARNING: src/learner.cc:782:
Parameters: { "nthreads" } are not used.
[01:33:20] WARNING: src/learner.cc:782:
Parameters: { "nthreads" } are not used.
Performing log-normalization
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
|
| | 0%
|
|======================================================================| 100%
Calculating gene variances
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
|
| | 0%
|
|======================================================================| 100%
|
| | 0%
|
|======================================================================| 100%
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 390
Number of edges: 9849
Running Louvain algorithm...
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Maximum modularity in 10 random starts: 0.8351
Number of communities: 7
Elapsed time: 0 seconds
Using method 'umap'
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
|
| | 0%
|
|======================================================================| 100%
|
| | 0%
|
|======================================================================| 100%
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
|
| | 0%
|
|======================================================================| 100%
|
| | 0%
|
|======================================================================| 100%
Performing log-normalization
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 19 | SKIP 0 | PASS 225 ]
[ FAIL 0 | WARN 19 | SKIP 0 | PASS 225 ]
>
> proc.time()
user system elapsed
110.010 3.078 123.545
singleCellTK.Rcheck/singleCellTK-Ex.timings
| name | user | system | elapsed | |
| MitoGenes | 0.001 | 0.000 | 0.002 | |
| SEG | 0.001 | 0.001 | 0.003 | |
| calcEffectSizes | 0.059 | 0.002 | 0.066 | |
| combineSCE | 0.266 | 0.009 | 0.282 | |
| computeZScore | 0.112 | 0.004 | 0.120 | |
| convertSCEToSeurat | 1.942 | 0.106 | 2.124 | |
| convertSeuratToSCE | 0.148 | 0.005 | 0.160 | |
| dedupRowNames | 0.036 | 0.003 | 0.043 | |
| detectCellOutlier | 2.582 | 0.075 | 2.752 | |
| diffAbundanceFET | 0.032 | 0.002 | 0.037 | |
| discreteColorPalette | 0.002 | 0.001 | 0.002 | |
| distinctColors | 0.001 | 0.000 | 0.001 | |
| downSampleCells | 0.301 | 0.025 | 0.354 | |
| downSampleDepth | 0.176 | 0.012 | 0.244 | |
| expData-ANY-character-method | 0.055 | 0.002 | 0.063 | |
| expData-set-ANY-character-CharacterOrNullOrMissing-logical-method | 0.066 | 0.002 | 0.072 | |
| expData-set | 0.071 | 0.003 | 0.079 | |
| expData | 0.057 | 0.003 | 0.063 | |
| expDataNames-ANY-method | 0.042 | 0.002 | 0.051 | |
| expDataNames | 0.043 | 0.003 | 0.046 | |
| expDeleteDataTag | 0.018 | 0.001 | 0.019 | |
| expSetDataTag | 0.013 | 0.001 | 0.014 | |
| expTaggedData | 0.014 | 0.000 | 0.014 | |
| exportSCE | 0.015 | 0.001 | 0.017 | |
| exportSCEtoAnnData | 0.046 | 0.002 | 0.049 | |
| exportSCEtoFlatFile | 0.044 | 0.002 | 0.047 | |
| featureIndex | 0.029 | 0.004 | 0.037 | |
| generateSimulatedData | 0.024 | 0.002 | 0.025 | |
| getBiomarker | 0.032 | 0.002 | 0.036 | |
| getDEGTopTable | 0.284 | 0.028 | 0.322 | |
| getDiffAbundanceResults | 0.036 | 0.002 | 0.041 | |
| getEnrichRResult | 0.201 | 0.040 | 3.201 | |
| getFindMarkerTopTable | 0.579 | 0.021 | 0.613 | |
| getMSigDBTable | 0.002 | 0.001 | 0.003 | |
| getPathwayResultNames | 0.015 | 0.002 | 0.018 | |
| getSampleSummaryStatsTable | 0.066 | 0.001 | 0.067 | |
| getSoupX | 0 | 0 | 0 | |
| getTSCANResults | 0.372 | 0.018 | 0.396 | |
| getTopHVG | 0.361 | 0.011 | 0.384 | |
| importAnnData | 0.001 | 0.000 | 0.003 | |
| importBUStools | 0.049 | 0.003 | 0.060 | |
| importCellRanger | 0.345 | 0.020 | 0.375 | |
| importCellRangerV2Sample | 0.040 | 0.001 | 0.040 | |
| importCellRangerV3Sample | 0.105 | 0.007 | 0.118 | |
| importDropEst | 0.077 | 0.002 | 0.082 | |
| importExampleData | 5.465 | 0.953 | 7.473 | |
| importGeneSetsFromCollection | 0.280 | 0.047 | 0.332 | |
| importGeneSetsFromGMT | 0.027 | 0.002 | 0.030 | |
| importGeneSetsFromList | 0.043 | 0.001 | 0.044 | |
| importGeneSetsFromMSigDB | 0.378 | 0.025 | 0.413 | |
| importMitoGeneSet | 0.024 | 0.003 | 0.032 | |
| importOptimus | 0.000 | 0.000 | 0.001 | |
| importSEQC | 0.046 | 0.002 | 0.047 | |
| importSTARsolo | 0.041 | 0.001 | 0.043 | |
| iterateSimulations | 0.069 | 0.003 | 0.075 | |
| listSampleSummaryStatsTables | 0.105 | 0.003 | 0.111 | |
| mergeSCEColData | 0.109 | 0.006 | 0.116 | |
| mouseBrainSubsetSCE | 0.018 | 0.001 | 0.019 | |
| msigdb_table | 0.000 | 0.000 | 0.002 | |
| plotBarcodeRankDropsResults | 0.393 | 0.021 | 0.429 | |
| plotBarcodeRankScatter | 0.293 | 0.007 | 0.310 | |
| plotBatchCorrCompare | 5.586 | 0.102 | 5.969 | |
| plotBatchVariance | 0.176 | 0.004 | 0.185 | |
| plotBcdsResults | 3.684 | 0.076 | 3.977 | |
| plotBubble | 0.263 | 0.005 | 0.283 | |
| plotClusterAbundance | 0.490 | 0.010 | 0.525 | |
| plotCxdsResults | 3.141 | 0.049 | 3.360 | |
| plotDEGHeatmap | 0.790 | 0.021 | 0.836 | |
| plotDEGRegression | 1.405 | 0.025 | 1.467 | |
| plotDEGViolin | 1.838 | 0.040 | 1.920 | |
| plotDEGVolcano | 0.379 | 0.008 | 0.394 | |
| plotDecontXResults | 3.698 | 0.052 | 3.881 | |
| plotDimRed | 0.128 | 0.006 | 0.142 | |
| plotDoubletFinderResults | 15.915 | 0.196 | 16.604 | |
| plotEmptyDropsResults | 2.239 | 0.028 | 2.328 | |
| plotEmptyDropsScatter | 2.318 | 0.035 | 2.423 | |
| plotFindMarkerHeatmap | 1.443 | 0.025 | 1.535 | |
| plotMASTThresholdGenes | 0.434 | 0.014 | 0.466 | |
| plotPCA | 0.220 | 0.011 | 0.247 | |
| plotPathway | 0.267 | 0.008 | 0.285 | |
| plotRunPerCellQCResults | 0.951 | 0.007 | 0.963 | |
| plotSCEBarAssayData | 0.116 | 0.004 | 0.125 | |
| plotSCEBarColData | 0.077 | 0.002 | 0.079 | |
| plotSCEBatchFeatureMean | 0.120 | 0.001 | 0.122 | |
| plotSCEDensity | 0.101 | 0.002 | 0.103 | |
| plotSCEDensityAssayData | 0.116 | 0.004 | 0.124 | |
| plotSCEDensityColData | 0.102 | 0.002 | 0.106 | |
| plotSCEDimReduceColData | 0.256 | 0.006 | 0.266 | |
| plotSCEDimReduceFeatures | 0.169 | 0.005 | 0.181 | |
| plotSCEHeatmap | 0.168 | 0.006 | 0.184 | |
| plotSCEScatter | 0.143 | 0.004 | 0.150 | |
| plotSCEViolin | 0.194 | 0.011 | 0.224 | |
| plotSCEViolinAssayData | 0.141 | 0.003 | 0.149 | |
| plotSCEViolinColData | 0.144 | 0.004 | 0.154 | |
| plotScDblFinderResults | 12.995 | 0.306 | 13.769 | |
| plotScanpyDotPlot | 0.012 | 0.000 | 0.012 | |
| plotScanpyEmbedding | 0.013 | 0.001 | 0.013 | |
| plotScanpyHVG | 0.012 | 0.001 | 0.012 | |
| plotScanpyHeatmap | 0.012 | 0.000 | 0.011 | |
| plotScanpyMarkerGenes | 0.018 | 0.001 | 0.023 | |
| plotScanpyMarkerGenesDotPlot | 0.011 | 0.001 | 0.012 | |
| plotScanpyMarkerGenesHeatmap | 0.011 | 0.000 | 0.011 | |
| plotScanpyMarkerGenesMatrixPlot | 0.011 | 0.000 | 0.012 | |
| plotScanpyMarkerGenesViolin | 0.011 | 0.001 | 0.011 | |
| plotScanpyMatrixPlot | 0.011 | 0.000 | 0.011 | |
| plotScanpyPCA | 0.011 | 0.000 | 0.011 | |
| plotScanpyPCAGeneRanking | 0.014 | 0.000 | 0.016 | |
| plotScanpyPCAVariance | 0.012 | 0.000 | 0.012 | |
| plotScanpyViolin | 0.011 | 0.001 | 0.012 | |
| plotScdsHybridResults | 4.104 | 0.090 | 4.339 | |
| plotScrubletResults | 0.016 | 0.001 | 0.019 | |
| plotSeuratElbow | 0.011 | 0.000 | 0.012 | |
| plotSeuratHVG | 0.011 | 0.000 | 0.012 | |
| plotSeuratJackStraw | 0.011 | 0.001 | 0.012 | |
| plotSeuratReduction | 0.011 | 0.001 | 0.012 | |
| plotSoupXResults | 0.000 | 0.000 | 0.001 | |
| plotTSCANClusterDEG | 1.797 | 0.031 | 1.881 | |
| plotTSCANClusterPseudo | 0.467 | 0.011 | 0.485 | |
| plotTSCANDimReduceFeatures | 0.455 | 0.011 | 0.479 | |
| plotTSCANPseudotimeGenes | 0.591 | 0.020 | 0.643 | |
| plotTSCANPseudotimeHeatmap | 0.476 | 0.012 | 0.502 | |
| plotTSCANResults | 0.419 | 0.010 | 0.434 | |
| plotTSNE | 0.160 | 0.007 | 0.176 | |
| plotTopHVG | 0.221 | 0.005 | 0.228 | |
| plotUMAP | 3.267 | 0.071 | 3.483 | |
| readSingleCellMatrix | 0.002 | 0.000 | 0.002 | |
| reportCellQC | 0.039 | 0.003 | 0.044 | |
| reportDropletQC | 0.011 | 0.000 | 0.012 | |
| reportQCTool | 0.029 | 0.000 | 0.030 | |
| retrieveSCEIndex | 0.015 | 0.000 | 0.016 | |
| runBBKNN | 0.000 | 0.001 | 0.000 | |
| runBarcodeRankDrops | 0.116 | 0.005 | 0.127 | |
| runBcds | 0.598 | 0.035 | 0.648 | |
| runCellQC | 0.045 | 0.002 | 0.050 | |
| runClusterSummaryMetrics | 0.136 | 0.005 | 0.147 | |
| runComBatSeq | 0.200 | 0.012 | 0.221 | |
| runCxds | 0.137 | 0.005 | 0.149 | |
| runCxdsBcdsHybrid | 0.743 | 0.052 | 0.835 | |
| runDEAnalysis | 0.156 | 0.005 | 0.168 | |
| runDecontX | 2.996 | 0.034 | 3.145 | |
| runDimReduce | 0.106 | 0.004 | 0.122 | |
| runDoubletFinder | 14.754 | 0.193 | 15.507 | |
| runDropletQC | 0.012 | 0.000 | 0.014 | |
| runEmptyDrops | 2.147 | 0.027 | 2.239 | |
| runEnrichR | 0.122 | 0.015 | 2.255 | |
| runFastMNN | 0.542 | 0.014 | 0.557 | |
| runFeatureSelection | 0.090 | 0.003 | 0.098 | |
| runFindMarker | 0.467 | 0.014 | 0.485 | |
| runGSVA | 0.369 | 0.033 | 0.419 | |
| runHarmony | 0.022 | 0.001 | 0.026 | |
| runKMeans | 0.079 | 0.003 | 0.087 | |
| runLimmaBC | 0.041 | 0.002 | 0.049 | |
| runMNNCorrect | 0.150 | 0.003 | 0.159 | |
| runModelGeneVar | 0.121 | 0.004 | 0.131 | |
| runNormalization | 1.010 | 0.015 | 1.068 | |
| runPerCellQC | 0.111 | 0.004 | 0.128 | |
| runSCANORAMA | 0 | 0 | 0 | |
| runSCMerge | 0.003 | 0.001 | 0.005 | |
| runScDblFinder | 7.827 | 0.118 | 8.202 | |
| runScanpyFindClusters | 0.013 | 0.000 | 0.013 | |
| runScanpyFindHVG | 0.011 | 0.001 | 0.011 | |
| runScanpyFindMarkers | 0.011 | 0.001 | 0.011 | |
| runScanpyNormalizeData | 0.034 | 0.001 | 0.035 | |
| runScanpyPCA | 0.012 | 0.001 | 0.013 | |
| runScanpyScaleData | 0.012 | 0.000 | 0.012 | |
| runScanpyTSNE | 0.016 | 0.001 | 0.019 | |
| runScanpyUMAP | 0.015 | 0.000 | 0.016 | |
| runScranSNN | 0.120 | 0.006 | 0.134 | |
| runScrublet | 0.013 | 0.001 | 0.015 | |
| runSeuratFindClusters | 0.011 | 0.001 | 0.011 | |
| runSeuratFindHVG | 0.168 | 0.004 | 0.178 | |
| runSeuratHeatmap | 0.012 | 0.001 | 0.013 | |
| runSeuratICA | 0.011 | 0.001 | 0.012 | |
| runSeuratJackStraw | 0.011 | 0.000 | 0.012 | |
| runSeuratNormalizeData | 0.015 | 0.001 | 0.018 | |
| runSeuratPCA | 0.015 | 0.001 | 0.019 | |
| runSeuratSCTransform | 1.871 | 0.049 | 2.066 | |
| runSeuratScaleData | 0.013 | 0.000 | 0.015 | |
| runSeuratUMAP | 0.012 | 0.001 | 0.015 | |
| runSingleR | 0.013 | 0.001 | 0.016 | |
| runSoupX | 0 | 0 | 0 | |
| runTSCAN | 0.233 | 0.014 | 0.269 | |
| runTSCANClusterDEAnalysis | 0.348 | 0.018 | 0.389 | |
| runTSCANDEG | 0.278 | 0.010 | 0.299 | |
| runTSNE | 0.294 | 0.004 | 0.307 | |
| runUMAP | 3.137 | 0.042 | 3.289 | |
| runVAM | 0.110 | 0.003 | 0.116 | |
| runZINBWaVE | 0.001 | 0.000 | 0.002 | |
| sampleSummaryStats | 0.051 | 0.001 | 0.052 | |
| scaterCPM | 0.058 | 0.002 | 0.064 | |
| scaterPCA | 0.143 | 0.002 | 0.147 | |
| scaterlogNormCounts | 0.086 | 0.001 | 0.087 | |
| sce | 0.011 | 0.001 | 0.012 | |
| sctkListGeneSetCollections | 0.036 | 0.001 | 0.038 | |
| sctkPythonInstallConda | 0 | 0 | 0 | |
| sctkPythonInstallVirtualEnv | 0 | 0 | 0 | |
| selectSCTKConda | 0 | 0 | 0 | |
| selectSCTKVirtualEnvironment | 0.000 | 0.001 | 0.000 | |
| setRowNames | 0.029 | 0.000 | 0.030 | |
| setSCTKDisplayRow | 0.183 | 0.004 | 0.194 | |
| singleCellTK | 0 | 0 | 0 | |
| subDiffEx | 0.156 | 0.008 | 0.168 | |
| subsetSCECols | 0.031 | 0.001 | 0.032 | |
| subsetSCERows | 0.072 | 0.003 | 0.075 | |
| summarizeSCE | 0.027 | 0.001 | 0.029 | |
| trimCounts | 0.092 | 0.002 | 0.097 | |