Back to Build/check report for BioC 3.17
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This page was generated on 2023-02-23 01:34:28 -0000 (Thu, 23 Feb 2023).

HostnameOSArch (*)R versionInstalled pkgs
kunpeng1Linux (Ubuntu 22.04.1 LTS)aarch64R Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences" 4245
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

CHECK results for singleCellTK on kunpeng1


To the developers/maintainers of the singleCellTK package:
- Please 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 How and When does the builder pull? When will my changes propagate? for more information.
- Make sure to use the following settings in order to reproduce any error or warning you see on this page.

raw results

Package 1876/2164HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.9.0  (landing page)
Yichen Wang
Snapshot Date: 2023-02-21 12:29:53 -0000 (Tue, 21 Feb 2023)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: master
git_last_commit: 4468720
git_last_commit_date: 2022-11-01 15:17:41 -0000 (Tue, 01 Nov 2022)
kunpeng1Linux (Ubuntu 22.04.1 LTS) / aarch64  OK    OK    OK  

Summary

Package: singleCellTK
Version: 2.9.0
Command: /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/library --timings singleCellTK_2.9.0.tar.gz
StartedAt: 2023-02-22 12:57:58 -0000 (Wed, 22 Feb 2023)
EndedAt: 2023-02-22 13:17:58 -0000 (Wed, 22 Feb 2023)
EllapsedTime: 1199.7 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/library --timings singleCellTK_2.9.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/singleCellTK.Rcheck’
* using R Under development (unstable) (2023-01-14 r83615)
* using platform: aarch64-unknown-linux-gnu (64-bit)
* R was compiled by
    gcc (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
    GNU Fortran (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
* running under: Ubuntu 22.04.1 LTS
* using session charset: UTF-8
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.9.0’
* 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  6.7Mb
  sub-directories of 1Mb or more:
    extdata   1.6Mb
    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 R 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 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   37.772  0.568  38.337
plotDoubletFinderResults 28.494  0.312  28.802
runScDblFinder           26.394  0.595  26.991
importExampleData        24.280  1.916  33.520
runDoubletFinder         21.807  0.148  21.955
plotBatchCorrCompare     12.564  0.287  12.842
plotScdsHybridResults    11.194  0.144  10.295
plotBcdsResults          10.107  0.230   9.313
plotDecontXResults        9.345  0.176   9.521
runDecontX                7.699  0.020   7.719
plotCxdsResults           7.469  0.088   7.553
plotTSCANClusterDEG       7.361  0.060   7.421
plotUMAP                  7.195  0.095   7.287
runUMAP                   6.908  0.219   7.124
plotFindMarkerHeatmap     6.387  0.020   6.408
detectCellOutlier         6.128  0.179   6.309
plotDEGViolin             6.157  0.116   6.273
plotEmptyDropsScatter     5.816  0.060   5.875
plotEmptyDropsResults     5.748  0.028   5.776
runEmptyDrops             5.324  0.016   5.340
plotDEGRegression         5.077  0.140   5.216
getEnrichRResult          0.380  0.089  32.158
runEnrichR                0.407  0.052  77.292
* 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 in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
  ‘singleCellTK.Rmd’ using ‘UTF-8’... OK
 NONE
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/home/biocbuild/bbs-3.17-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.



Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.17-bioc/R/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 Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu (64-bit)

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 
  0.205   0.026   0.216 

singleCellTK.Rcheck/tests/testthat.Rout


R Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu (64-bit)

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, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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


Attaching package: 'DelayedArray'

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

    apply, rowsum, 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Estimating GSVA scores for 34 gene sets.
Estimating ECDFs with Gaussian kernels

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Estimating GSVA scores for 2 gene sets.
Estimating ECDFs with Gaussian kernels

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

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  |======================================================================| 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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Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 390
Number of edges: 9590

Running Louvain algorithm...
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Maximum modularity in 10 random starts: 0.8042
Number of communities: 6
Elapsed time: 0 seconds
Using method 'umap'
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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**************************************************|
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[----|----|----|----|----|----|----|----|----|----|
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Performing log-normalization
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 21 | SKIP 0 | PASS 221 ]

[ FAIL 0 | WARN 21 | SKIP 0 | PASS 221 ]
> 
> proc.time()
   user  system elapsed 
304.772   6.926 395.281 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0030.0010.003
SEG0.0030.0000.002
calcEffectSizes0.2370.0000.237
combineSCE1.9540.0512.005
computeZScore0.3200.0120.333
convertSCEToSeurat4.0080.1954.204
convertSeuratToSCE0.5310.0000.531
dedupRowNames0.070.000.07
detectCellOutlier6.1280.1796.309
diffAbundanceFET0.0500.0040.054
discreteColorPalette0.0080.0000.008
distinctColors0.0000.0030.003
downSampleCells0.9010.0480.949
downSampleDepth0.7370.0110.749
expData-ANY-character-method0.3980.0000.398
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.4590.0190.479
expData-set0.4530.0400.493
expData0.3920.0160.408
expDataNames-ANY-method0.4070.0040.410
expDataNames0.3820.0080.390
expDeleteDataTag0.0470.0000.047
expSetDataTag0.0290.0000.029
expTaggedData0.0320.0000.032
exportSCE0.0290.0000.029
exportSCEtoAnnData0.0920.0040.097
exportSCEtoFlatFile0.0960.0000.095
featureIndex0.0450.0000.046
generateSimulatedData0.0500.0040.055
getBiomarker0.0550.0040.059
getDEGTopTable1.0900.0361.125
getDiffAbundanceResults0.1190.0000.119
getEnrichRResult 0.380 0.08932.158
getFindMarkerTopTable4.4760.2284.705
getMSigDBTable0.0000.0040.004
getPathwayResultNames0.0280.0000.028
getSampleSummaryStatsTable0.4310.0200.452
getSoupX0.5340.0160.549
getTSCANResults2.4260.0842.511
getTopHVG1.0110.0201.031
importAnnData0.0010.0000.001
importBUStools0.4060.0080.416
importCellRanger1.4810.0281.513
importCellRangerV2Sample0.3700.0120.382
importCellRangerV3Sample0.5820.0120.594
importDropEst0.4310.0080.441
importExampleData24.280 1.91633.520
importGeneSetsFromCollection0.9540.0641.017
importGeneSetsFromGMT0.0780.0000.079
importGeneSetsFromList0.1570.0030.161
importGeneSetsFromMSigDB4.0470.2724.319
importMitoGeneSet0.0650.0010.065
importOptimus0.0010.0000.001
importSEQC0.3080.0270.338
importSTARsolo0.3610.0190.382
iterateSimulations0.4030.0320.434
listSampleSummaryStatsTables0.5990.0320.631
mergeSCEColData0.6160.0200.636
mouseBrainSubsetSCE0.0270.0040.031
msigdb_table0.0020.0000.002
plotBarcodeRankDropsResults1.1190.0681.188
plotBarcodeRankScatter0.9980.0201.018
plotBatchCorrCompare12.564 0.28712.842
plotBatchVariance0.4310.0230.454
plotBcdsResults10.107 0.230 9.313
plotClusterAbundance1.5260.0281.554
plotCxdsResults7.4690.0887.553
plotDEGHeatmap3.9310.0563.988
plotDEGRegression5.0770.1405.216
plotDEGViolin6.1570.1166.273
plotDEGVolcano1.3780.0041.382
plotDecontXResults9.3450.1769.521
plotDimRed0.3330.0080.340
plotDoubletFinderResults28.494 0.31228.802
plotEmptyDropsResults5.7480.0285.776
plotEmptyDropsScatter5.8160.0605.875
plotFindMarkerHeatmap6.3870.0206.408
plotMASTThresholdGenes2.0470.0242.070
plotPCA0.7480.0000.748
plotPathway1.1220.0001.124
plotRunPerCellQCResults1.7780.0081.786
plotSCEBarAssayData0.2150.0000.215
plotSCEBarColData0.1780.0040.182
plotSCEBatchFeatureMean0.3020.0080.310
plotSCEDensity0.3720.0000.372
plotSCEDensityAssayData0.2160.0040.220
plotSCEDensityColData0.2870.0040.290
plotSCEDimReduceColData1.0660.0081.074
plotSCEDimReduceFeatures0.5750.0000.574
plotSCEHeatmap0.9700.0040.974
plotSCEScatter0.4680.0000.468
plotSCEViolin0.4150.0040.420
plotSCEViolinAssayData0.3330.0080.342
plotSCEViolinColData0.3230.0040.328
plotScDblFinderResults37.772 0.56838.337
plotScdsHybridResults11.194 0.14410.295
plotScrubletResults0.0290.0000.029
plotSeuratElbow0.0280.0000.028
plotSeuratHVG0.0310.0000.031
plotSeuratJackStraw0.0310.0000.031
plotSeuratReduction0.0320.0000.032
plotSoupXResults0.2330.0000.233
plotTSCANClusterDEG7.3610.0607.421
plotTSCANClusterPseudo3.0910.0003.091
plotTSCANDimReduceFeatures2.9520.0322.985
plotTSCANPseudotimeGenes2.8630.0402.904
plotTSCANPseudotimeHeatmap2.9620.0202.983
plotTSCANResults2.7910.0322.823
plotTSNE0.6370.0230.661
plotTopHVG0.5130.0000.514
plotUMAP7.1950.0957.287
readSingleCellMatrix0.0050.0000.005
reportCellQC0.2420.0080.250
reportDropletQC0.0350.0000.035
reportQCTool0.2420.0040.246
retrieveSCEIndex0.0350.0000.035
runBBKNN0.0000.0000.001
runBarcodeRankDrops0.5720.0000.572
runBcds3.2180.0292.198
runCellQC0.2350.0040.239
runComBatSeq0.6760.0040.680
runCxds0.8560.0080.864
runCxdsBcdsHybrid3.3210.0352.307
runDEAnalysis0.9070.0120.919
runDecontX7.6990.0207.719
runDimReduce0.6300.0000.629
runDoubletFinder21.807 0.14821.955
runDropletQC0.0260.0040.030
runEmptyDrops5.3240.0165.340
runEnrichR 0.407 0.05277.292
runFastMNN2.3240.2412.564
runFeatureSelection0.2890.0120.301
runFindMarker4.2870.3404.627
runGSVA0.9140.0720.985
runHarmony0.0470.0030.051
runKMeans0.5770.0840.662
runLimmaBC0.0930.0120.105
runMNNCorrect0.7120.0480.760
runModelGeneVar0.5860.0320.618
runNormalization0.7000.0440.744
runPerCellQC0.5920.0280.620
runSCANORAMA000
runSCMerge0.0050.0000.005
runScDblFinder26.394 0.59526.991
runScranSNN0.9960.0921.088
runScrublet0.0270.0000.027
runSeuratFindClusters0.0270.0000.027
runSeuratFindHVG0.7340.0200.754
runSeuratHeatmap0.0240.0040.027
runSeuratICA0.0260.0000.026
runSeuratJackStraw0.0270.0000.027
runSeuratNormalizeData0.0260.0000.026
runSeuratPCA0.0270.0000.027
runSeuratSCTransform3.6380.2153.861
runSeuratScaleData0.0240.0030.027
runSeuratUMAP0.0220.0030.026
runSingleR0.0410.0040.045
runSoupX0.2280.0000.228
runTSCAN1.8080.0721.880
runTSCANClusterDEAnalysis2.0070.0762.083
runTSCANDEG1.9170.0481.965
runTSNE1.2890.0161.306
runUMAP6.9080.2197.124
runVAM0.7400.0080.747
runZINBWaVE0.0040.0000.005
sampleSummaryStats0.3950.0000.394
scaterCPM0.1510.0040.156
scaterPCA0.5680.0040.572
scaterlogNormCounts0.3090.0000.309
sce0.0270.0000.027
sctkListGeneSetCollections0.0930.0000.096
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.0980.0040.101
setSCTKDisplayRow0.5000.0240.524
singleCellTK000
subDiffEx0.6330.0200.653
subsetSCECols0.2240.0150.241
subsetSCERows0.5290.0240.553
summarizeSCE0.0740.0030.077
trimCounts0.2830.0160.300