Back to Multiple platform build/check report for BioC 3.17:   simplified   long
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This page was generated on 2023-03-16 11:07:29 -0400 (Thu, 16 Mar 2023).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 22.04.1 LTS)x86_64R Under development (unstable) (2023-01-10 r83596) -- "Unsuffered Consequences" 4540
palomino3Windows Server 2022 Datacenterx64R Under development (unstable) (2023-01-10 r83596 ucrt) -- "Unsuffered Consequences" 4302
merida1macOS 10.14.6 Mojavex86_64R Under development (unstable) (2023-01-10 r83596) -- "Unsuffered Consequences" 4330
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 merida1


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 1900/2189HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.9.0  (landing page)
Yichen Wang
Snapshot Date: 2023-03-15 14:00:15 -0400 (Wed, 15 Mar 2023)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: master
git_last_commit: 4468720
git_last_commit_date: 2022-11-01 11:17:41 -0400 (Tue, 01 Nov 2022)
nebbiolo1Linux (Ubuntu 22.04.1 LTS) / x86_64  OK    OK    ERROR  
palomino3Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
merida1macOS 10.14.6 Mojave / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published

Summary

Package: singleCellTK
Version: 2.9.0
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_2.9.0.tar.gz
StartedAt: 2023-03-16 07:00:58 -0400 (Thu, 16 Mar 2023)
EndedAt: 2023-03-16 07:32:21 -0400 (Thu, 16 Mar 2023)
EllapsedTime: 1883.6 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_2.9.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.17-bioc/meat/singleCellTK.Rcheck’
* using R Under development (unstable) (2023-01-10 r83596)
* using platform: x86_64-apple-darwin17.0 (64-bit)
* R was compiled by
    Apple clang version 12.0.0 (clang-1200.0.32.29)
    GNU Fortran (GCC) 8.2.0
* running under: macOS Mojave 10.14.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.9.0’
* 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  6.5Mb
  sub-directories of 1Mb or more:
    extdata   1.5Mb
    shiny     2.8Mb
* 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     47.356  0.932  64.972
plotDoubletFinderResults   34.246  0.171  45.040
runScDblFinder             33.606  0.560  43.223
importExampleData          24.613  1.818  40.113
runDoubletFinder           24.864  0.115  32.919
plotBatchCorrCompare       13.629  0.124  17.734
plotScdsHybridResults      12.724  0.159  17.463
plotBcdsResults            11.510  0.238  14.732
plotDecontXResults         11.543  0.076  15.335
plotTSCANClusterDEG        11.417  0.092  15.261
plotFindMarkerHeatmap      10.351  0.042  14.080
plotEmptyDropsResults      10.347  0.032  13.800
plotEmptyDropsScatter      10.319  0.040  13.641
plotDEGViolin               9.750  0.126  12.487
runEmptyDrops               9.640  0.034  12.495
runDecontX                  8.662  0.050  11.862
plotCxdsResults             8.638  0.056  10.912
plotDEGRegression           8.452  0.063  10.894
detectCellOutlier           7.903  0.150  10.271
plotUMAP                    7.746  0.050  10.473
runUMAP                     7.659  0.042   9.693
runFindMarker               7.085  0.055   9.041
getFindMarkerTopTable       6.785  0.056   8.986
plotDEGHeatmap              6.470  0.095   8.105
convertSCEToSeurat          6.163  0.204   8.313
runSeuratSCTransform        5.033  0.045   6.489
importGeneSetsFromMSigDB    4.702  0.159   6.325
plotTSCANDimReduceFeatures  4.806  0.026   6.657
plotTSCANPseudotimeHeatmap  4.794  0.027   6.569
plotTSCANClusterPseudo      4.786  0.029   6.535
plotTSCANPseudotimeGenes    4.664  0.027   6.334
plotTSCANResults            4.547  0.027   6.136
runCxdsBcdsHybrid           3.842  0.044   5.141
getTSCANResults             3.710  0.037   5.025
runBcds                     3.662  0.047   5.010
* 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 ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.17-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/4.3/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 Under development (unstable) (2023-01-10 r83596) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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 
  0.357   0.085   0.452

singleCellTK.Rcheck/tests/testthat.Rout


R Under development (unstable) (2023-01-10 r83596) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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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Error in fitdistr(mahalanobis.sq.null[nonzero.values], "gamma", lower = 0.01) : 
  optimization failed
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...
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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 22 | SKIP 0 | PASS 221 ]

[ FAIL 0 | WARN 22 | SKIP 0 | PASS 221 ]
> 
> proc.time()
   user  system elapsed 
421.902   6.586 553.756

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0040.0030.010
SEG0.0050.0030.008
calcEffectSizes0.4310.0100.585
combineSCE3.2270.0554.422
computeZScore0.4870.0140.664
convertSCEToSeurat6.1630.2048.313
convertSeuratToSCE0.8520.0091.133
dedupRowNames0.1100.0040.147
detectCellOutlier 7.903 0.15010.271
diffAbundanceFET0.0840.0050.114
discreteColorPalette0.0110.0010.015
distinctColors0.0040.0010.010
downSampleCells1.3470.1491.959
downSampleDepth1.0400.0321.429
expData-ANY-character-method0.6420.0060.839
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.7200.0080.959
expData-set0.7540.0111.022
expData0.6410.0080.844
expDataNames-ANY-method0.6280.0060.824
expDataNames0.6430.0070.847
expDeleteDataTag0.0800.0040.108
expSetDataTag0.0440.0030.064
expTaggedData0.0450.0030.062
exportSCE0.0440.0050.061
exportSCEtoAnnData0.1710.0020.219
exportSCEtoFlatFile0.1670.0050.238
featureIndex0.0700.0060.094
generateSimulatedData0.0860.0070.121
getBiomarker0.1000.0050.133
getDEGTopTable1.8330.0952.407
getDiffAbundanceResults0.0750.0010.099
getEnrichRResult0.5940.0402.010
getFindMarkerTopTable6.7850.0568.986
getMSigDBTable0.0070.0030.014
getPathwayResultNames0.0430.0050.068
getSampleSummaryStatsTable0.7900.0061.057
getSoupX0.7610.0111.041
getTSCANResults3.7100.0375.025
getTopHVG1.5780.0132.163
importAnnData0.0020.0000.002
importBUStools0.5740.0030.745
importCellRanger2.3320.0543.238
importCellRangerV2Sample0.5490.0030.759
importCellRangerV3Sample0.8430.0151.087
importDropEst0.6690.0070.857
importExampleData24.613 1.81840.113
importGeneSetsFromCollection1.5290.1052.083
importGeneSetsFromGMT0.1230.0070.167
importGeneSetsFromList0.2600.0110.338
importGeneSetsFromMSigDB4.7020.1596.325
importMitoGeneSet0.1130.0080.146
importOptimus0.0020.0000.002
importSEQC0.5920.0050.754
importSTARsolo0.5940.0060.762
iterateSimulations0.6690.0080.884
listSampleSummaryStatsTables0.8520.0061.117
mergeSCEColData0.9540.0181.264
mouseBrainSubsetSCE0.0500.0030.071
msigdb_table0.0020.0030.005
plotBarcodeRankDropsResults1.7610.0192.270
plotBarcodeRankScatter2.7440.0233.602
plotBatchCorrCompare13.629 0.12417.734
plotBatchVariance0.7070.0471.001
plotBcdsResults11.510 0.23814.732
plotClusterAbundance2.3840.0373.039
plotCxdsResults 8.638 0.05610.912
plotDEGHeatmap6.4700.0958.105
plotDEGRegression 8.452 0.06310.894
plotDEGViolin 9.750 0.12612.487
plotDEGVolcano2.2290.0152.939
plotDecontXResults11.543 0.07615.335
plotDimRed0.5650.0040.742
plotDoubletFinderResults34.246 0.17145.040
plotEmptyDropsResults10.347 0.03213.800
plotEmptyDropsScatter10.319 0.04013.641
plotFindMarkerHeatmap10.351 0.04214.080
plotMASTThresholdGenes3.3520.0254.463
plotPCA1.1560.0101.555
plotPathway1.7820.0142.329
plotRunPerCellQCResults2.7960.0293.746
plotSCEBarAssayData0.5160.0060.688
plotSCEBarColData0.2840.0050.376
plotSCEBatchFeatureMean0.4870.0040.667
plotSCEDensity0.4680.0050.627
plotSCEDensityAssayData0.3500.0040.485
plotSCEDensityColData0.4600.0050.632
plotSCEDimReduceColData1.7470.0132.346
plotSCEDimReduceFeatures0.7730.0081.037
plotSCEHeatmap1.6310.0122.152
plotSCEScatter0.7390.0060.974
plotSCEViolin0.5100.0050.669
plotSCEViolinAssayData0.5510.0070.730
plotSCEViolinColData0.5120.0060.711
plotScDblFinderResults47.356 0.93264.972
plotScdsHybridResults12.724 0.15917.463
plotScrubletResults0.0450.0040.069
plotSeuratElbow0.0430.0030.063
plotSeuratHVG0.0450.0050.065
plotSeuratJackStraw0.0420.0030.065
plotSeuratReduction0.0440.0040.068
plotSoupXResults0.3850.0110.552
plotTSCANClusterDEG11.417 0.09215.261
plotTSCANClusterPseudo4.7860.0296.535
plotTSCANDimReduceFeatures4.8060.0266.657
plotTSCANPseudotimeGenes4.6640.0276.334
plotTSCANPseudotimeHeatmap4.7940.0276.569
plotTSCANResults4.5470.0276.136
plotTSNE1.0550.0081.429
plotTopHVG0.8070.0071.111
plotUMAP 7.746 0.05010.473
readSingleCellMatrix0.0080.0010.009
reportCellQC0.3670.0040.504
reportDropletQC0.0390.0030.057
reportQCTool0.3610.0050.501
retrieveSCEIndex0.0540.0030.072
runBBKNN0.0010.0000.000
runBarcodeRankDrops0.8890.0081.204
runBcds3.6620.0475.010
runCellQC0.3840.0080.526
runComBatSeq0.9960.0251.351
runCxds1.1520.0261.606
runCxdsBcdsHybrid3.8420.0445.141
runDEAnalysis1.4180.0101.919
runDecontX 8.662 0.05011.862
runDimReduce0.9800.0091.376
runDoubletFinder24.864 0.11532.919
runDropletQC0.0450.0040.062
runEmptyDrops 9.640 0.03412.495
runEnrichR0.5410.0301.829
runFastMNN3.6020.0464.483
runFeatureSelection0.4230.0030.527
runFindMarker7.0850.0559.041
runGSVA1.4020.0111.782
runHarmony0.0770.0010.101
runKMeans0.8610.0091.087
runLimmaBC0.1640.0020.204
runMNNCorrect1.1290.0161.441
runModelGeneVar1.0620.0111.369
runNormalization1.1380.0081.467
runPerCellQC0.9460.0091.217
runSCANORAMA0.0000.0000.001
runSCMerge0.0060.0000.010
runScDblFinder33.606 0.56043.223
runScranSNN1.6090.1072.182
runScrublet0.0410.0040.056
runSeuratFindClusters0.0440.0050.069
runSeuratFindHVG1.2770.0101.650
runSeuratHeatmap0.0410.0050.060
runSeuratICA0.0420.0080.063
runSeuratJackStraw0.0490.0020.070
runSeuratNormalizeData0.0460.0060.067
runSeuratPCA0.0420.0020.056
runSeuratSCTransform5.0330.0456.489
runSeuratScaleData0.0420.0040.060
runSeuratUMAP0.0430.0030.061
runSingleR0.0760.0030.097
runSoupX0.3810.0060.487
runTSCAN3.0240.0173.818
runTSCANClusterDEAnalysis3.3570.0224.310
runTSCANDEG3.2190.0174.120
runTSNE1.8020.0092.274
runUMAP7.6590.0429.693
runVAM1.1730.0081.484
runZINBWaVE0.0070.0000.009
sampleSummaryStats0.6400.0070.828
scaterCPM0.2570.0020.345
scaterPCA0.9050.0071.173
scaterlogNormCounts0.4980.0050.633
sce0.0400.0060.061
sctkListGeneSetCollections0.1620.0090.213
sctkPythonInstallConda0.0000.0010.000
sctkPythonInstallVirtualEnv0.0010.0000.000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.1830.0060.241
setSCTKDisplayRow0.8490.0131.083
singleCellTK0.0000.0010.000
subDiffEx1.0190.0251.321
subsetSCECols0.3760.0080.480
subsetSCERows0.9010.0121.150
summarizeSCE0.1230.0040.161
trimCounts0.4610.0060.584