Back to Multiple platform build/check report for BioC 3.20:   simplified   long
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This page was generated on 2024-11-20 12:07 -0500 (Wed, 20 Nov 2024).

HostnameOSArch (*)R versionInstalled pkgs
teran2Linux (Ubuntu 24.04.1 LTS)x86_644.4.2 (2024-10-31) -- "Pile of Leaves" 4481
nebbiolo2Linux (Ubuntu 24.04.1 LTS)x86_644.4.2 (2024-10-31) -- "Pile of Leaves" 4479
palomino8Windows Server 2022 Datacenterx644.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" 4359
lconwaymacOS 12.7.1 Montereyx86_644.4.1 (2024-06-14) -- "Race for Your Life" 4539
kunpeng2Linux (openEuler 22.03 LTS-SP1)aarch644.4.1 (2024-06-14) -- "Race for Your Life" 4493
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 1977/2289HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.16.0  (landing page)
Joshua David Campbell
Snapshot Date: 2024-11-19 13:40 -0500 (Tue, 19 Nov 2024)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_20
git_last_commit: 6bbe76f
git_last_commit_date: 2024-10-29 11:30:33 -0500 (Tue, 29 Oct 2024)
teran2Linux (Ubuntu 24.04.1 LTS) / x86_64  ERROR    ERROR  skipped
nebbiolo2Linux (Ubuntu 24.04.1 LTS) / x86_64  ERROR    ERROR  skipped
palomino8Windows Server 2022 Datacenter / x64  ERROR    ERROR  skippedskipped
lconwaymacOS 12.7.1 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kunpeng2Linux (openEuler 22.03 LTS-SP1) / aarch64  OK    OK    OK  

CHECK results for singleCellTK on lconway

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

raw results


Summary

Package: singleCellTK
Version: 2.16.0
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.16.0.tar.gz
StartedAt: 2024-11-20 02:46:48 -0500 (Wed, 20 Nov 2024)
EndedAt: 2024-11-20 03:02:06 -0500 (Wed, 20 Nov 2024)
EllapsedTime: 918.0 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.16.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/singleCellTK.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.16.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ...Warning: unable to access index for repository https://CRAN.R-project.org/src/contrib:
  cannot open URL 'https://CRAN.R-project.org/src/contrib/PACKAGES'
 OK
* 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 ... NOTE
  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 ... NOTE
License stub is invalid DCF.
* 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 ... OK
* 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 26.138  0.126  26.307
plotScDblFinderResults   25.148  0.547  25.790
runDoubletFinder         23.790  0.088  23.915
runScDblFinder           15.141  0.352  15.538
importExampleData         9.845  1.185  11.546
plotBatchCorrCompare      8.741  0.068   8.824
plotScdsHybridResults     6.446  0.133   6.585
plotBcdsResults           5.895  0.103   6.005
plotDecontXResults        5.575  0.049   5.638
runUMAP                   5.144  0.068   5.221
runDecontX                4.986  0.045   5.040
plotUMAP                  4.936  0.062   5.006
getEnrichRResult          0.260  0.030   5.148
runEnrichR                0.212  0.022   7.761
* 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: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.20-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.

Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library’
* installing *source* package ‘singleCellTK’ ...
** using staged installation
** R
** data
** exec
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (singleCellTK)

Tests output

singleCellTK.Rcheck/tests/spelling.Rout


R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

> if (requireNamespace('spelling', quietly = TRUE))
+   spelling::spell_check_test(vignettes = TRUE, error = FALSE, skip_on_cran = TRUE)
NULL
> 
> proc.time()
   user  system elapsed 
  0.156   0.064   0.222

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

Attaching package: 'MatrixGenerics'

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

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

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

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, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, saveRDS, setdiff, table,
    tapply, union, 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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

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

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

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

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

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Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 20 | SKIP 0 | PASS 224 ]

[ FAIL 0 | WARN 20 | SKIP 0 | PASS 224 ]
> 
> proc.time()
   user  system elapsed 
194.044   5.554 204.967

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0010.0020.003
SEG0.0020.0020.004
calcEffectSizes0.1360.0180.155
combineSCE0.6100.0250.637
computeZScore0.1780.0070.185
convertSCEToSeurat3.1700.1533.333
convertSeuratToSCE0.2190.0050.223
dedupRowNames0.0410.0020.042
detectCellOutlier4.0130.0974.127
diffAbundanceFET0.0420.0030.044
discreteColorPalette0.0050.0000.005
distinctColors0.0020.0000.001
downSampleCells0.4000.0570.467
downSampleDepth0.3080.0240.334
expData-ANY-character-method0.0930.0060.098
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1350.0070.142
expData-set0.1120.0040.117
expData0.0940.0040.098
expDataNames-ANY-method0.0900.0040.094
expDataNames0.0850.0030.089
expDeleteDataTag0.0270.0010.029
expSetDataTag0.0210.0020.023
expTaggedData0.0210.0010.022
exportSCE0.0180.0020.020
exportSCEtoAnnData0.0700.0030.073
exportSCEtoFlatFile0.0680.0020.071
featureIndex0.0280.0020.030
generateSimulatedData0.0410.0030.043
getBiomarker0.0450.0030.048
getDEGTopTable0.5280.0590.588
getDiffAbundanceResults0.0390.0030.041
getEnrichRResult0.2600.0305.148
getFindMarkerTopTable1.0920.0281.122
getMSigDBTable0.0040.0020.006
getPathwayResultNames0.0190.0030.022
getSampleSummaryStatsTable0.1400.0030.143
getSoupX000
getTSCANResults0.8180.0370.858
getTopHVG0.6110.0100.625
importAnnData0.0010.0000.001
importBUStools0.1130.0040.118
importCellRanger0.6250.0290.661
importCellRangerV2Sample0.1020.0020.104
importCellRangerV3Sample0.2190.0110.232
importDropEst0.1500.0030.153
importExampleData 9.845 1.18511.546
importGeneSetsFromCollection1.4100.1071.523
importGeneSetsFromGMT0.0500.0040.053
importGeneSetsFromList0.0910.0030.094
importGeneSetsFromMSigDB2.6610.0882.752
importMitoGeneSet0.0390.0040.042
importOptimus0.0010.0000.002
importSEQC0.1060.0050.112
importSTARsolo0.1060.0040.111
iterateSimulations0.1340.0050.139
listSampleSummaryStatsTables0.2020.0130.215
mergeSCEColData0.3040.0200.329
mouseBrainSubsetSCE0.0300.0050.036
msigdb_table0.0010.0020.003
plotBarcodeRankDropsResults0.4580.0060.467
plotBarcodeRankScatter0.5280.0100.540
plotBatchCorrCompare8.7410.0688.824
plotBatchVariance0.2450.0060.252
plotBcdsResults5.8950.1036.005
plotBubble0.5560.0310.589
plotClusterAbundance0.6400.0040.646
plotCxdsResults4.7610.0444.811
plotDEGHeatmap1.6360.0251.664
plotDEGRegression2.5010.0332.542
plotDEGViolin3.0870.0743.196
plotDEGVolcano0.6650.0090.675
plotDecontXResults5.5750.0495.638
plotDimRed0.1480.0040.152
plotDoubletFinderResults26.138 0.12626.307
plotEmptyDropsResults4.7000.0114.718
plotEmptyDropsScatter4.8140.0124.833
plotFindMarkerHeatmap3.0200.0193.044
plotMASTThresholdGenes1.0240.0231.052
plotPCA0.2900.0070.298
plotPathway0.4130.0090.423
plotRunPerCellQCResults1.5280.0181.549
plotSCEBarAssayData0.1560.0050.161
plotSCEBarColData0.1140.0050.119
plotSCEBatchFeatureMean0.1620.0020.165
plotSCEDensity0.1710.0050.183
plotSCEDensityAssayData0.1370.0050.142
plotSCEDensityColData0.1700.0040.177
plotSCEDimReduceColData0.4270.0090.439
plotSCEDimReduceFeatures0.2090.0060.220
plotSCEHeatmap0.3350.0050.341
plotSCEScatter0.1960.0060.203
plotSCEViolin0.2240.0060.233
plotSCEViolinAssayData0.2010.0070.213
plotSCEViolinColData0.1860.0040.193
plotScDblFinderResults25.148 0.54725.790
plotScanpyDotPlot0.0200.0030.023
plotScanpyEmbedding0.0180.0020.021
plotScanpyHVG0.0200.0030.023
plotScanpyHeatmap0.0190.0020.023
plotScanpyMarkerGenes0.0190.0030.022
plotScanpyMarkerGenesDotPlot0.0180.0030.021
plotScanpyMarkerGenesHeatmap0.0170.0020.019
plotScanpyMarkerGenesMatrixPlot0.0180.0020.020
plotScanpyMarkerGenesViolin0.0180.0020.021
plotScanpyMatrixPlot0.0180.0020.020
plotScanpyPCA0.0180.0020.020
plotScanpyPCAGeneRanking0.0190.0020.020
plotScanpyPCAVariance0.0190.0030.022
plotScanpyViolin0.0190.0020.021
plotScdsHybridResults6.4460.1336.585
plotScrubletResults0.0210.0020.024
plotSeuratElbow0.0200.0020.022
plotSeuratHVG0.0210.0020.023
plotSeuratJackStraw0.0200.0020.022
plotSeuratReduction0.0200.0060.028
plotSoupXResults0.0000.0010.001
plotTSCANClusterDEG2.9180.0753.002
plotTSCANClusterPseudo0.9400.0200.962
plotTSCANDimReduceFeatures0.9370.0200.959
plotTSCANPseudotimeGenes1.0890.0181.112
plotTSCANPseudotimeHeatmap1.0360.0171.057
plotTSCANResults0.8730.0140.888
plotTSNE0.2420.0060.247
plotTopHVG0.4050.0120.417
plotUMAP4.9360.0625.006
readSingleCellMatrix0.0050.0010.006
reportCellQC0.0650.0020.068
reportDropletQC0.0180.0030.021
reportQCTool0.0580.0040.062
retrieveSCEIndex0.0220.0030.025
runBBKNN000
runBarcodeRankDrops0.1710.0050.177
runBcds1.2080.0331.245
runCellQC0.0620.0060.068
runClusterSummaryMetrics0.2640.0060.271
runComBatSeq0.3420.0100.353
runCxds0.2490.0110.262
runCxdsBcdsHybrid1.2300.0561.289
runDEAnalysis0.3170.0510.368
runDecontX4.9860.0455.040
runDimReduce0.2050.0050.210
runDoubletFinder23.790 0.08823.915
runDropletQC0.0210.0050.026
runEmptyDrops4.6610.0134.685
runEnrichR0.2120.0227.761
runFastMNN1.2640.0441.313
runFeatureSelection0.1760.0050.181
runFindMarker1.1150.0281.146
runGSVA0.6000.0430.647
runHarmony0.0280.0010.030
runKMeans0.1360.0060.143
runLimmaBC0.0580.0010.060
runMNNCorrect0.3080.0040.313
runModelGeneVar0.2430.0090.253
runNormalization1.7120.0181.743
runPerCellQC0.2470.0080.255
runSCANORAMA0.0000.0010.001
runSCMerge0.0030.0010.005
runScDblFinder15.141 0.35215.538
runScanpyFindClusters0.0180.0040.022
runScanpyFindHVG0.0190.0030.022
runScanpyFindMarkers0.0190.0020.020
runScanpyNormalizeData0.0760.0030.080
runScanpyPCA0.0190.0030.023
runScanpyScaleData0.0200.0030.023
runScanpyTSNE0.0190.0020.022
runScanpyUMAP0.0210.0040.024
runScranSNN0.2250.0090.235
runScrublet0.0190.0030.022
runSeuratFindClusters0.0190.0030.021
runSeuratFindHVG0.3550.0080.364
runSeuratHeatmap0.0200.0030.024
runSeuratICA0.0190.0040.023
runSeuratJackStraw0.0190.0020.021
runSeuratNormalizeData0.0190.0020.022
runSeuratPCA0.0220.0020.024
runSeuratSCTransform4.0180.1234.236
runSeuratScaleData0.0200.0030.022
runSeuratUMAP0.0200.0010.021
runSingleR0.0280.0010.029
runSoupX0.0000.0010.000
runTSCAN0.5190.0140.535
runTSCANClusterDEAnalysis0.5920.0150.608
runTSCANDEG0.5790.0200.601
runTSNE0.5050.0140.521
runUMAP5.1440.0685.221
runVAM0.2310.0070.238
runZINBWaVE0.0030.0010.003
sampleSummaryStats0.1270.0070.134
scaterCPM0.1060.0020.110
scaterPCA0.3490.0060.354
scaterlogNormCounts0.1790.0020.181
sce0.0190.0070.026
sctkListGeneSetCollections0.0670.0060.075
sctkPythonInstallConda0.0000.0010.000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment0.0000.0000.001
setRowNames0.0710.0040.074
setSCTKDisplayRow0.2550.0090.265
singleCellTK000
subDiffEx0.2720.0140.287
subsetSCECols0.0700.0050.074
subsetSCERows0.1750.0070.183
summarizeSCE0.0930.0210.114
trimCounts0.1600.0070.167