Back to Multiple platform build/check report for BioC 3.16
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This page was generated on 2023-01-27 11:06:50 -0500 (Fri, 27 Jan 2023).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 20.04.5 LTS)x86_644.2.2 (2022-10-31) -- "Innocent and Trusting" 4510
palomino4Windows Server 2022 Datacenterx644.2.2 (2022-10-31 ucrt) -- "Innocent and Trusting" 4288
lconwaymacOS 12.5.1 Montereyx86_644.2.2 (2022-10-31) -- "Innocent and Trusting" 4317
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 nebbiolo2


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 1889/2183HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.8.0  (landing page)
Yichen Wang
Snapshot Date: 2023-01-26 14:00:04 -0500 (Thu, 26 Jan 2023)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_16
git_last_commit: 711d2ed
git_last_commit_date: 2022-11-01 11:17:41 -0500 (Tue, 01 Nov 2022)
nebbiolo2Linux (Ubuntu 20.04.5 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino4Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
lconwaymacOS 12.5.1 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published

Summary

Package: singleCellTK
Version: 2.8.0
Command: /home/biocbuild/bbs-3.16-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.16-bioc/R/library --timings singleCellTK_2.8.0.tar.gz
StartedAt: 2023-01-26 23:48:43 -0500 (Thu, 26 Jan 2023)
EndedAt: 2023-01-27 00:02:45 -0500 (Fri, 27 Jan 2023)
EllapsedTime: 842.3 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.16-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.16-bioc/R/library --timings singleCellTK_2.8.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.16-bioc/meat/singleCellTK.Rcheck’
* using R version 4.2.2 (2022-10-31)
* using platform: x86_64-pc-linux-gnu (64-bit)
* using session charset: UTF-8
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.8.0’
* 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   26.385  0.479  26.857
plotDoubletFinderResults 26.238  0.144  26.376
importExampleData        22.689  2.312  25.607
runDoubletFinder         23.355  0.132  23.487
runScDblFinder           16.874  0.596  17.470
plotScdsHybridResults    12.403  0.209  11.306
plotBatchCorrCompare     11.291  0.273  11.548
plotBcdsResults           8.976  0.212   8.156
plotDecontXResults        8.405  0.116   8.521
plotEmptyDropsScatter     8.401  0.064   8.466
plotUMAP                  8.074  0.108   8.174
runDecontX                7.927  0.088   8.015
plotCxdsResults           6.961  0.068   7.022
plotEmptyDropsResults     6.955  0.000   6.955
runEmptyDrops             6.633  0.004   6.638
plotTSCANClusterDEG       6.539  0.064   6.603
runUMAP                   6.414  0.088   6.492
detectCellOutlier         5.660  0.184   5.845
* 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-3.16-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.



Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.16-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.16-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 version 4.2.2 (2022-10-31) -- "Innocent and Trusting"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-pc-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 
  0.210   0.027   0.220 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.2.2 (2022-10-31) -- "Innocent and Trusting"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-pc-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
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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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
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 20 | SKIP 0 | PASS 221 ]

[ FAIL 0 | WARN 20 | SKIP 0 | PASS 221 ]
> 
> proc.time()
   user  system elapsed 
229.910   9.051 239.455 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0030.0000.003
SEG0.0020.0000.002
calcEffectSizes0.1490.0000.150
combineSCE1.3560.0361.392
computeZScore0.2670.0120.278
convertSCEToSeurat3.0190.1123.131
convertSeuratToSCE0.4200.0040.424
dedupRowNames0.0500.0000.049
detectCellOutlier5.6600.1845.845
diffAbundanceFET0.0460.0040.049
discreteColorPalette0.0030.0040.007
distinctColors0.0020.0000.003
downSampleCells0.6750.0280.703
downSampleDepth0.5020.0200.523
expData-ANY-character-method0.2960.0080.304
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.3410.0000.340
expData-set0.3380.0040.342
expData0.3120.0000.312
expDataNames-ANY-method0.3380.0040.342
expDataNames0.2890.0160.306
expDeleteDataTag0.0380.0000.038
expSetDataTag0.0270.0000.027
expTaggedData0.0240.0040.027
exportSCE0.0230.0000.024
exportSCEtoAnnData0.0910.0040.095
exportSCEtoFlatFile0.0800.0120.093
featureIndex0.0350.0000.036
generateSimulatedData0.0420.0000.042
getBiomarker0.0450.0040.048
getDEGTopTable0.7930.0040.797
getDiffAbundanceResults0.0370.0000.038
getEnrichRResult0.4730.1202.224
getFindMarkerTopTable3.9370.2554.193
getMSigDBTable0.0000.0050.006
getPathwayResultNames0.0320.0020.033
getSampleSummaryStatsTable0.3290.0070.337
getSoupX0.5530.0010.552
getTSCANResults1.9830.0322.016
getTopHVG0.9290.0390.969
importAnnData0.0020.0010.002
importBUStools0.4170.0190.438
importCellRanger1.1110.0231.135
importCellRangerV2Sample0.2770.0010.276
importCellRangerV3Sample0.3560.0000.356
importDropEst0.5810.0030.585
importExampleData22.689 2.31225.607
importGeneSetsFromCollection0.7450.0640.809
importGeneSetsFromGMT0.0650.0040.069
importGeneSetsFromList0.1120.0000.113
importGeneSetsFromMSigDB3.5240.2323.756
importMitoGeneSet0.0460.0040.051
importOptimus0.0010.0000.001
importSEQC0.2370.0120.249
importSTARsolo0.2840.0120.297
iterateSimulations0.4000.0240.425
listSampleSummaryStatsTables0.3670.0040.371
mergeSCEColData0.4320.0160.447
mouseBrainSubsetSCE0.0280.0000.027
msigdb_table0.0000.0010.001
plotBarcodeRankDropsResults0.8290.0300.859
plotBarcodeRankScatter0.7100.0320.742
plotBatchCorrCompare11.291 0.27311.548
plotBatchVariance0.3160.0120.328
plotBcdsResults8.9760.2128.156
plotClusterAbundance1.0800.0321.112
plotCxdsResults6.9610.0687.022
plotDEGHeatmap3.0600.0123.073
plotDEGRegression3.6890.0443.726
plotDEGViolin4.4110.1284.533
plotDEGVolcano1.0670.0121.079
plotDecontXResults8.4050.1168.521
plotDimRed0.2720.0000.272
plotDoubletFinderResults26.238 0.14426.376
plotEmptyDropsResults6.9550.0006.955
plotEmptyDropsScatter8.4010.0648.466
plotFindMarkerHeatmap4.4900.0044.495
plotMASTThresholdGenes1.4960.0121.507
plotPCA0.4770.0040.481
plotPathway1.0070.0121.020
plotRunPerCellQCResults1.2990.0001.299
plotSCEBarAssayData0.1590.0040.163
plotSCEBarColData0.1280.0000.129
plotSCEBatchFeatureMean0.2190.0000.220
plotSCEDensity0.2520.0000.252
plotSCEDensityAssayData0.1620.0040.166
plotSCEDensityColData0.2080.0000.208
plotSCEDimReduceColData0.7640.0080.772
plotSCEDimReduceFeatures0.3890.0080.397
plotSCEHeatmap0.7350.0000.735
plotSCEScatter0.3590.0000.359
plotSCEViolin0.2510.0000.251
plotSCEViolinAssayData0.3360.0000.336
plotSCEViolinColData0.2310.0000.233
plotScDblFinderResults26.385 0.47926.857
plotScdsHybridResults12.403 0.20911.306
plotScrubletResults0.0260.0000.025
plotSeuratElbow0.0220.0040.026
plotSeuratHVG0.0260.0000.026
plotSeuratJackStraw0.0270.0000.027
plotSeuratReduction0.0260.0000.026
plotSoupXResults0.2080.0040.211
plotTSCANClusterDEG6.5390.0646.603
plotTSCANClusterPseudo3.5270.0083.535
plotTSCANDimReduceFeatures2.5390.0082.547
plotTSCANPseudotimeGenes2.2870.0162.304
plotTSCANPseudotimeHeatmap2.3880.0242.412
plotTSCANResults2.4330.0042.438
plotTSNE0.5580.0000.558
plotTopHVG0.4890.0040.496
plotUMAP8.0740.1088.174
readSingleCellMatrix0.0010.0040.005
reportCellQC0.1990.0000.199
reportDropletQC0.0260.0000.026
reportQCTool0.2040.0000.204
retrieveSCEIndex0.0330.0000.033
runBBKNN000
runBarcodeRankDrops0.4480.0000.448
runBcds2.3740.0161.508
runCellQC0.2130.0000.213
runComBatSeq0.4610.0080.469
runCxds0.7190.0280.747
runCxdsBcdsHybrid2.6820.0321.737
runDEAnalysis0.7560.0200.777
runDecontX7.9270.0888.015
runDimReduce0.5330.0000.534
runDoubletFinder23.355 0.13223.487
runDropletQC0.0270.0000.027
runEmptyDrops6.6330.0046.638
runEnrichR0.3690.0241.886
runFastMNN1.9410.2042.146
runFeatureSelection0.2190.0200.239
runFindMarker3.5970.2283.826
runGSVA0.8400.0880.928
runHarmony0.0440.0000.044
runKMeans0.4520.0360.488
runLimmaBC0.0880.0040.092
runMNNCorrect0.6030.0160.619
runModelGeneVar0.4940.0480.542
runNormalization0.6430.0560.699
runPerCellQC0.6200.0160.636
runSCANORAMA000
runSCMerge0.0040.0000.004
runScDblFinder16.874 0.59617.470
runScranSNN0.6390.0680.708
runScrublet0.0240.0000.024
runSeuratFindClusters0.0230.0000.023
runSeuratFindHVG0.5690.0680.637
runSeuratHeatmap0.0230.0000.023
runSeuratICA0.0230.0000.022
runSeuratJackStraw0.0230.0000.022
runSeuratNormalizeData0.0180.0030.022
runSeuratPCA0.0220.0010.022
runSeuratSCTransform3.0040.1913.198
runSeuratScaleData0.0240.0000.023
runSeuratUMAP0.0230.0000.022
runSingleR0.0340.0000.034
runSoupX0.1730.0000.172
runTSCAN1.3520.0121.363
runTSCANClusterDEAnalysis1.5410.0241.565
runTSCANDEG1.5940.0321.626
runTSNE0.8210.0080.829
runUMAP6.4140.0886.492
runVAM0.5180.0000.519
runZINBWaVE0.0030.0000.004
sampleSummaryStats0.2890.0000.289
scaterCPM0.1410.0000.141
scaterPCA0.4790.0000.480
scaterlogNormCounts0.2510.0040.255
sce0.0240.0000.025
sctkListGeneSetCollections0.0790.0000.079
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv000
selectSCTKConda0.0000.0000.001
selectSCTKVirtualEnvironment000
setRowNames0.0880.0000.088
setSCTKDisplayRow0.3890.0000.390
singleCellTK000
subDiffEx0.4610.0040.464
subsetSCECols0.1610.0040.165
subsetSCERows0.430.000.43
summarizeSCE0.0770.0000.077
trimCounts0.2530.0040.256