Back to Build/check report for BioC 3.17:   simplified   long
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This page was generated on 2023-03-01 07:38:51 -0000 (Wed, 01 Mar 2023).

HostnameOSArch (*)R versionInstalled pkgs
kunpeng1Linux (Ubuntu 22.04.1 LTS)aarch64R Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences" 4266
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 1882/2171HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.9.0  (landing page)
Yichen Wang
Snapshot Date: 2023-02-27 07:53:22 -0000 (Mon, 27 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: 2023-02-28 15:41:43 -0000 (Tue, 28 Feb 2023)
EndedAt: 2023-02-28 16:02:53 -0000 (Tue, 28 Feb 2023)
EllapsedTime: 1269.6 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   39.219  0.539  39.755
plotDoubletFinderResults 27.683  0.191  27.871
runScDblFinder           27.109  0.628  27.738
importExampleData        24.803  1.559  34.483
runDoubletFinder         21.710  0.064  21.775
plotBatchCorrCompare     12.781  0.249  13.021
plotScdsHybridResults    11.354  0.140  10.431
plotBcdsResults           9.946  0.231   9.138
plotDecontXResults        9.156  0.160   9.316
runDecontX                7.589  0.052   7.642
plotCxdsResults           7.345  0.084   7.425
plotUMAP                  7.124  0.103   7.223
runUMAP                   6.904  0.212   7.113
plotTSCANClusterDEG       6.995  0.056   7.051
detectCellOutlier         6.235  0.216   6.451
plotFindMarkerHeatmap     6.146  0.044   6.190
plotDEGViolin             5.908  0.144   6.051
plotEmptyDropsScatter     5.777  0.056   5.833
plotEmptyDropsResults     5.711  0.028   5.739
runEmptyDrops             5.296  0.000   5.296
getEnrichRResult          0.383  0.108  92.493
runEnrichR                0.385  0.080 107.046
* 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 
  0.191   0.034   0.211 

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 
297.377   8.583 376.149 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0030.0000.003
SEG0.0030.0000.003
calcEffectSizes0.2330.0080.242
combineSCE2.0800.0522.132
computeZScore0.3330.0160.349
convertSCEToSeurat4.1240.1204.244
convertSeuratToSCE0.5570.0000.557
dedupRowNames0.0690.0040.073
detectCellOutlier6.2350.2166.451
diffAbundanceFET0.0560.0000.056
discreteColorPalette0.0040.0040.008
distinctColors0.0000.0030.003
downSampleCells0.9540.0320.986
downSampleDepth0.7660.0040.770
expData-ANY-character-method0.4260.0040.430
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.4750.0200.496
expData-set0.4870.0080.495
expData0.4320.0000.432
expDataNames-ANY-method0.4610.0080.469
expDataNames0.4210.0160.436
expDeleteDataTag0.0510.0000.052
expSetDataTag0.0330.0000.033
expTaggedData0.0300.0040.034
exportSCE0.0310.0000.031
exportSCEtoAnnData0.0920.0040.097
exportSCEtoFlatFile0.0790.0160.094
featureIndex0.0490.0000.049
generateSimulatedData0.0560.0000.056
getBiomarker0.0570.0040.061
getDEGTopTable1.1770.0201.198
getDiffAbundanceResults0.1230.0000.124
getEnrichRResult 0.383 0.10892.493
getFindMarkerTopTable4.2770.3444.621
getMSigDBTable0.0040.0000.005
getPathwayResultNames0.0250.0040.029
getSampleSummaryStatsTable0.4250.0160.441
getSoupX0.5030.0440.547
getTSCANResults2.4120.0642.475
getTopHVG1.0310.0521.082
importAnnData0.0020.0000.001
importBUStools0.4060.0040.412
importCellRanger1.4720.0201.495
importCellRangerV2Sample0.3460.0000.346
importCellRangerV3Sample0.590.020.61
importDropEst0.4290.0200.451
importExampleData24.803 1.55934.483
importGeneSetsFromCollection0.9830.0561.039
importGeneSetsFromGMT0.0820.0000.085
importGeneSetsFromList0.1620.0070.169
importGeneSetsFromMSigDB4.0730.1974.270
importMitoGeneSet0.0640.0040.067
importOptimus0.0000.0020.001
importSEQC0.3250.0120.340
importSTARsolo0.3610.0080.370
iterateSimulations0.4260.0280.454
listSampleSummaryStatsTables0.6190.0200.639
mergeSCEColData0.6340.0040.639
mouseBrainSubsetSCE0.0310.0000.031
msigdb_table0.0010.0000.001
plotBarcodeRankDropsResults1.1010.0241.125
plotBarcodeRankScatter1.0050.0081.013
plotBatchCorrCompare12.781 0.24913.021
plotBatchVariance0.4470.0120.459
plotBcdsResults9.9460.2319.138
plotClusterAbundance1.4860.0081.494
plotCxdsResults7.3450.0847.425
plotDEGHeatmap3.7200.0953.816
plotDEGRegression4.9160.0604.975
plotDEGViolin5.9080.1446.051
plotDEGVolcano1.320.021.34
plotDecontXResults9.1560.1609.316
plotDimRed0.340.000.34
plotDoubletFinderResults27.683 0.19127.871
plotEmptyDropsResults5.7110.0285.739
plotEmptyDropsScatter5.7770.0565.833
plotFindMarkerHeatmap6.1460.0446.190
plotMASTThresholdGenes1.9890.0041.992
plotPCA0.7020.0080.710
plotPathway1.0820.0041.087
plotRunPerCellQCResults1.7150.0001.716
plotSCEBarAssayData0.1980.0120.210
plotSCEBarColData0.1670.0040.172
plotSCEBatchFeatureMean0.2930.0040.297
plotSCEDensity0.3480.0040.352
plotSCEDensityAssayData0.2080.0040.212
plotSCEDensityColData0.2690.0030.272
plotSCEDimReduceColData0.9990.0001.000
plotSCEDimReduceFeatures0.5450.0000.544
plotSCEHeatmap0.9110.0040.915
plotSCEScatter0.4540.0000.454
plotSCEViolin0.4070.0000.407
plotSCEViolinAssayData0.3250.0040.329
plotSCEViolinColData0.2980.0110.310
plotScDblFinderResults39.219 0.53939.755
plotScdsHybridResults11.354 0.14010.431
plotScrubletResults0.0280.0000.028
plotSeuratElbow0.0260.0000.026
plotSeuratHVG0.0230.0040.027
plotSeuratJackStraw0.0260.0000.026
plotSeuratReduction0.0270.0000.027
plotSoupXResults0.2230.0040.227
plotTSCANClusterDEG6.9950.0567.051
plotTSCANClusterPseudo2.8920.0122.905
plotTSCANDimReduceFeatures2.9020.0042.905
plotTSCANPseudotimeGenes2.8060.0042.810
plotTSCANPseudotimeHeatmap3.0430.0043.048
plotTSCANResults2.8880.0162.904
plotTSNE0.6540.0000.654
plotTopHVG0.5170.0000.518
plotUMAP7.1240.1037.223
readSingleCellMatrix0.0050.0000.005
reportCellQC0.2280.0000.229
reportDropletQC0.0270.0000.028
reportQCTool0.2280.0000.227
retrieveSCEIndex0.0340.0000.034
runBBKNN000
runBarcodeRankDrops0.5510.0000.551
runBcds3.150.042.14
runCellQC0.2200.0000.221
runComBatSeq0.6510.0040.655
runCxds0.8090.0000.809
runCxdsBcdsHybrid3.2460.0362.251
runDEAnalysis0.8620.0240.886
runDecontX7.5890.0527.642
runDimReduce0.6040.0000.603
runDoubletFinder21.710 0.06421.775
runDropletQC0.030.000.03
runEmptyDrops5.2960.0005.296
runEnrichR 0.385 0.080107.046
runFastMNN2.3870.2442.631
runFeatureSelection0.2980.0080.306
runFindMarker4.5590.3044.863
runGSVA0.9710.0561.027
runHarmony0.0510.0000.051
runKMeans0.6230.0520.675
runLimmaBC0.0960.0160.112
runMNNCorrect0.7290.0520.781
runModelGeneVar0.6430.0240.667
runNormalization0.7330.0600.793
runPerCellQC0.6130.0320.644
runSCANORAMA000
runSCMerge0.0050.0000.005
runScDblFinder27.109 0.62827.738
runScranSNN1.0060.0641.070
runScrublet0.0280.0000.027
runSeuratFindClusters0.0270.0000.027
runSeuratFindHVG0.7700.0080.779
runSeuratHeatmap0.0270.0000.028
runSeuratICA0.0270.0040.030
runSeuratJackStraw0.0270.0000.027
runSeuratNormalizeData0.0270.0000.027
runSeuratPCA0.0260.0000.027
runSeuratSCTransform3.6710.2363.915
runSeuratScaleData0.0280.0000.028
runSeuratUMAP0.0270.0000.027
runSingleR0.0430.0040.047
runSoupX0.2240.0080.232
runTSCAN1.8420.0241.866
runTSCANClusterDEAnalysis2.0310.0082.039
runTSCANDEG1.9100.0081.919
runTSNE1.3170.0041.321
runUMAP6.9040.2127.113
runVAM0.7210.0120.733
runZINBWaVE0.0050.0000.005
sampleSummaryStats0.3770.0030.380
scaterCPM0.1520.0000.152
scaterPCA0.5580.0040.563
scaterlogNormCounts0.3070.0120.318
sce0.0270.0000.027
sctkListGeneSetCollections0.0970.0000.097
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment0.0010.0000.000
setRowNames0.1080.0000.107
setSCTKDisplayRow0.5150.0240.539
singleCellTK000
subDiffEx0.6260.0280.655
subsetSCECols0.2300.0040.233
subsetSCERows0.5560.0000.556
summarizeSCE0.0750.0000.076
trimCounts0.2950.0040.299