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This page was generated on 2025-02-06 12:09 -0500 (Thu, 06 Feb 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.1 LTS)x86_644.4.2 (2024-10-31) -- "Pile of Leaves" 4753
palomino8Windows Server 2022 Datacenterx644.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" 4501
merida1macOS 12.7.5 Montereyx86_644.4.2 (2024-10-31) -- "Pile of Leaves" 4524
kjohnson1macOS 13.6.6 Venturaarm644.4.2 (2024-10-31) -- "Pile of Leaves" 4476
taishanLinux (openEuler 24.03 LTS)aarch644.4.2 (2024-10-31) -- "Pile of Leaves" 4407
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: 2025-02-03 13:00 -0500 (Mon, 03 Feb 2025)
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)
nebbiolo2Linux (Ubuntu 24.04.1 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino8Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
merida1macOS 12.7.5 Monterey / x86_64  OK    OK    OK    NA  
kjohnson1macOS 13.6.6 Ventura / arm64  OK    OK    OK    OK  YES
taishanLinux (openEuler 24.03 LTS) / aarch64  OK    OK    OK  

CHECK results for singleCellTK on merida1

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: 2025-02-04 10:17:27 -0500 (Tue, 04 Feb 2025)
EndedAt: 2025-02-04 10:43:54 -0500 (Tue, 04 Feb 2025)
EllapsedTime: 1586.5 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 4.4.2 (2024-10-31)
* 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 ... 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
plotScDblFinderResults   48.822  1.041  50.769
plotDoubletFinderResults 42.926  0.384  44.158
runDoubletFinder         39.640  0.180  40.316
runScDblFinder           32.665  0.513  33.639
importExampleData        22.462  2.683  27.406
plotBatchCorrCompare     14.036  0.170  14.485
plotScdsHybridResults    12.771  0.266  13.750
plotBcdsResults          11.128  0.269  11.995
plotFindMarkerHeatmap    10.173  0.080  10.681
plotDecontXResults       10.082  0.122  10.323
plotEmptyDropsResults     9.968  0.049  10.293
plotEmptyDropsScatter     9.879  0.045  10.333
plotDEGViolin             9.623  0.186  10.012
runEmptyDrops             9.425  0.030   9.552
plotTSCANClusterDEG       8.925  0.231  10.278
convertSCEToSeurat        8.675  0.468   9.632
runSeuratSCTransform      8.270  0.182   8.795
plotCxdsResults           8.282  0.097   8.578
plotDEGRegression         7.973  0.090   8.099
runDecontX                7.976  0.059   8.308
plotUMAP                  7.536  0.077   7.971
runUMAP                   7.430  0.066   7.553
detectCellOutlier         6.995  0.224   7.438
importGeneSetsFromMSigDB  6.007  0.219   6.400
plotDEGHeatmap            5.344  0.073   5.664
getEnrichRResult          0.752  0.108   6.818
* 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 4.4.2 (2024-10-31) -- "Pile of Leaves"
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 
  0.361   0.120   0.448

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
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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  |======================================================================| 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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  |======================================================================| 100%
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 
416.200  10.308 440.498

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0040.0050.011
SEG0.0050.0040.008
calcEffectSizes0.4250.0130.441
combineSCE2.6110.0352.678
computeZScore0.4370.0170.458
convertSCEToSeurat8.6750.4689.632
convertSeuratToSCE0.6790.0140.704
dedupRowNames0.1220.0100.151
detectCellOutlier6.9950.2247.438
diffAbundanceFET0.1040.0090.115
discreteColorPalette0.0110.0010.014
distinctColors0.0040.0010.006
downSampleCells1.1180.1321.270
downSampleDepth0.9040.0490.970
expData-ANY-character-method0.2720.0060.279
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.3670.0100.380
expData-set0.3390.0100.357
expData0.2690.0060.277
expDataNames-ANY-method0.2790.0120.295
expDataNames0.2850.0350.323
expDeleteDataTag0.0690.0050.075
expSetDataTag0.0450.0100.063
expTaggedData0.0460.0050.053
exportSCE0.0420.0090.051
exportSCEtoAnnData0.1390.0060.147
exportSCEtoFlatFile0.1680.0100.183
featureIndex0.0710.0060.077
generateSimulatedData0.0970.0090.111
getBiomarker0.1110.0100.122
getDEGTopTable1.5470.0501.621
getDiffAbundanceResults0.0910.0060.099
getEnrichRResult0.7520.1086.818
getFindMarkerTopTable3.4450.1743.685
getMSigDBTable0.0070.0070.017
getPathwayResultNames0.0410.0070.054
getSampleSummaryStatsTable0.4240.0080.453
getSoupX0.0010.0000.001
getTSCANResults2.3320.0772.435
getTopHVG1.8150.0291.858
importAnnData0.0020.0010.003
importBUStools0.3370.0060.346
importCellRanger1.8110.0581.879
importCellRangerV2Sample0.3520.0040.361
importCellRangerV3Sample0.6120.0210.635
importDropEst0.4510.0060.458
importExampleData22.462 2.68327.406
importGeneSetsFromCollection2.8320.1773.042
importGeneSetsFromGMT0.1350.0080.144
importGeneSetsFromList0.2750.0070.282
importGeneSetsFromMSigDB6.0070.2196.400
importMitoGeneSet0.1150.0150.133
importOptimus0.0030.0010.005
importSEQC0.3430.0180.380
importSTARsolo0.3730.0340.413
iterateSimulations0.3870.0340.474
listSampleSummaryStatsTables0.5940.0680.715
mergeSCEColData0.8420.0570.909
mouseBrainSubsetSCE0.0630.0060.070
msigdb_table0.0020.0050.007
plotBarcodeRankDropsResults1.3450.0181.369
plotBarcodeRankScatter1.6150.0191.650
plotBatchCorrCompare14.036 0.17014.485
plotBatchVariance0.7460.0280.789
plotBcdsResults11.128 0.26911.995
plotBubble1.5610.0491.688
plotClusterAbundance1.9840.0162.191
plotCxdsResults8.2820.0978.578
plotDEGHeatmap5.3440.0735.664
plotDEGRegression7.9730.0908.099
plotDEGViolin 9.623 0.18610.012
plotDEGVolcano1.7720.0331.829
plotDecontXResults10.082 0.12210.323
plotDimRed0.3940.0110.407
plotDoubletFinderResults42.926 0.38444.158
plotEmptyDropsResults 9.968 0.04910.293
plotEmptyDropsScatter 9.879 0.04510.333
plotFindMarkerHeatmap10.173 0.08010.681
plotMASTThresholdGenes3.2870.0523.543
plotPCA0.7040.0150.877
plotPathway1.2860.0171.374
plotRunPerCellQCResults4.6010.0384.862
plotSCEBarAssayData0.4080.0090.437
plotSCEBarColData0.3160.0090.339
plotSCEBatchFeatureMean0.5760.0070.609
plotSCEDensity0.4760.0100.489
plotSCEDensityAssayData0.3760.0120.415
plotSCEDensityColData0.4890.0110.528
plotSCEDimReduceColData1.1950.0201.360
plotSCEDimReduceFeatures0.6750.0140.744
plotSCEHeatmap0.9610.0121.017
plotSCEScatter0.5520.0130.638
plotSCEViolin0.5510.0120.635
plotSCEViolinAssayData0.5710.0140.626
plotSCEViolinColData0.5840.0160.606
plotScDblFinderResults48.822 1.04150.769
plotScanpyDotPlot0.0410.0040.049
plotScanpyEmbedding0.0390.0040.047
plotScanpyHVG0.0410.0040.046
plotScanpyHeatmap0.0440.0070.055
plotScanpyMarkerGenes0.0410.0040.050
plotScanpyMarkerGenesDotPlot0.0420.0050.047
plotScanpyMarkerGenesHeatmap0.0450.0050.051
plotScanpyMarkerGenesMatrixPlot0.0430.0050.049
plotScanpyMarkerGenesViolin0.0420.0040.046
plotScanpyMatrixPlot0.0400.0040.046
plotScanpyPCA0.0390.0050.047
plotScanpyPCAGeneRanking0.0390.0040.045
plotScanpyPCAVariance0.0410.0030.045
plotScanpyViolin0.0420.0060.050
plotScdsHybridResults12.771 0.26613.750
plotScrubletResults0.0410.0040.053
plotSeuratElbow0.0410.0040.047
plotSeuratHVG0.0400.0030.052
plotSeuratJackStraw0.0390.0040.049
plotSeuratReduction0.0380.0060.045
plotSoupXResults000
plotTSCANClusterDEG 8.925 0.23110.278
plotTSCANClusterPseudo2.8560.0343.115
plotTSCANDimReduceFeatures2.9240.0413.218
plotTSCANPseudotimeGenes3.3920.0433.818
plotTSCANPseudotimeHeatmap3.1320.0393.442
plotTSCANResults2.5340.0402.592
plotTSNE0.7120.0130.744
plotTopHVG1.1830.0301.273
plotUMAP7.5360.0777.971
readSingleCellMatrix0.0100.0020.012
reportCellQC0.1780.0060.185
reportDropletQC0.0420.0040.045
reportQCTool0.1760.0090.186
retrieveSCEIndex0.0540.0080.071
runBBKNN0.0000.0010.001
runBarcodeRankDrops0.4710.0080.484
runBcds3.3760.0523.604
runCellQC0.1830.0090.208
runClusterSummaryMetrics0.8870.0160.911
runComBatSeq1.0070.0311.106
runCxds0.6800.0250.709
runCxdsBcdsHybrid3.4350.1243.592
runDEAnalysis0.8900.0700.969
runDecontX7.9760.0598.308
runDimReduce0.6470.0090.698
runDoubletFinder39.640 0.18040.316
runDropletQC0.0390.0060.045
runEmptyDrops9.4250.0309.552
runEnrichR0.6690.0483.388
runFastMNN4.0150.0784.144
runFeatureSelection0.4600.0070.470
runFindMarker3.2910.0463.371
runGSVA1.6770.0651.766
runHarmony0.0930.0020.095
runKMeans0.3840.0160.408
runLimmaBC0.1790.0020.181
runMNNCorrect0.9000.0060.920
runModelGeneVar0.6980.0090.713
runNormalization3.0830.0383.149
runPerCellQC0.7290.0130.749
runSCANORAMA0.0000.0010.001
runSCMerge0.0070.0020.009
runScDblFinder32.665 0.51333.639
runScanpyFindClusters0.0380.0070.044
runScanpyFindHVG0.0390.0050.046
runScanpyFindMarkers0.0390.0050.043
runScanpyNormalizeData0.2070.0050.214
runScanpyPCA0.0390.0040.044
runScanpyScaleData0.0390.0060.046
runScanpyTSNE0.0390.0040.043
runScanpyUMAP0.0400.0070.048
runScranSNN0.6460.0160.671
runScrublet0.0390.0030.043
runSeuratFindClusters0.0400.0060.047
runSeuratFindHVG1.0570.0131.101
runSeuratHeatmap0.0390.0050.044
runSeuratICA0.0380.0070.046
runSeuratJackStraw0.0380.0020.040
runSeuratNormalizeData0.0380.0040.043
runSeuratPCA0.0400.0030.043
runSeuratSCTransform8.2700.1828.795
runSeuratScaleData0.0400.0050.044
runSeuratUMAP0.0450.0040.049
runSingleR0.0850.0050.089
runSoupX0.0000.0010.001
runTSCAN1.5080.0221.573
runTSCANClusterDEAnalysis1.6600.0251.688
runTSCANDEG1.6570.0371.700
runTSNE1.2970.0191.333
runUMAP7.4300.0667.553
runVAM0.6930.0100.710
runZINBWaVE0.0060.0020.008
sampleSummaryStats0.3610.0070.370
scaterCPM0.2320.0050.237
scaterPCA1.0460.0121.083
scaterlogNormCounts0.4520.0040.463
sce0.0380.0080.049
sctkListGeneSetCollections0.1830.0100.198
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv0.0000.0010.001
selectSCTKConda0.0010.0010.000
selectSCTKVirtualEnvironment0.0000.0000.001
setRowNames0.1860.0050.191
setSCTKDisplayRow0.6780.0120.695
singleCellTK0.0000.0010.001
subDiffEx0.6740.0490.740
subsetSCECols0.1760.0100.187
subsetSCERows0.5590.0400.601
summarizeSCE0.1300.0100.141
trimCounts0.3600.0120.373