Back to Multiple platform build/check report for BioC 3.16:   simplified   long
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This page was generated on 2023-04-12 11:06:27 -0400 (Wed, 12 Apr 2023).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 20.04.5 LTS)x86_644.2.3 (2023-03-15) -- "Shortstop Beagle" 4502
palomino4Windows Server 2022 Datacenterx644.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle" 4282
lconwaymacOS 12.5.1 Montereyx86_644.2.3 (2023-03-15) -- "Shortstop Beagle" 4310
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 lconway


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: 2023-04-10 14:00:05 -0400 (Mon, 10 Apr 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 -0400 (Tue, 01 Nov 2022)
nebbiolo2Linux (Ubuntu 20.04.5 LTS) / x86_64  OK    OK    TIMEOUT  
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: /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_2.8.0.tar.gz
StartedAt: 2023-04-10 22:44:13 -0400 (Mon, 10 Apr 2023)
EndedAt: 2023-04-10 22:56:28 -0400 (Mon, 10 Apr 2023)
EllapsedTime: 735.3 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_2.8.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.16-bioc/meat/singleCellTK.Rcheck’
* using R version 4.2.3 (2023-03-15)
* using platform: x86_64-apple-darwin17.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.8.0’
* 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  6.6Mb
  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   22.847  0.721  23.614
plotDoubletFinderResults 21.231  0.180  21.447
importExampleData        16.778  1.690  19.078
runDoubletFinder         16.502  0.107  16.630
runScDblFinder           15.302  0.377  15.724
plotBatchCorrCompare      9.561  0.107   9.677
plotScdsHybridResults     7.928  0.163   8.103
plotDecontXResults        6.874  0.065   6.953
plotBcdsResults           6.654  0.128   6.790
runDecontX                6.113  0.088   6.211
plotEmptyDropsScatter     5.781  0.023   5.827
runUMAP                   5.651  0.077   5.727
plotUMAP                  5.606  0.079   5.691
plotCxdsResults           5.475  0.102   5.586
plotEmptyDropsResults     5.546  0.019   5.575
runEmptyDrops             5.370  0.017   5.400
detectCellOutlier         5.036  0.135   5.188
* 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-3.16-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/4.2/Resources/library’
* installing *source* package ‘singleCellTK’ ...
** using staged installation
** R
** data
** exec
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (singleCellTK)

Tests output

singleCellTK.Rcheck/tests/spelling.Rout


R version 4.2.3 (2023-03-15) -- "Shortstop Beagle"
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 
  0.174   0.063   0.228 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.2.3 (2023-03-15) -- "Shortstop Beagle"
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Error in fitdistr(mahalanobis.sq.null[nonzero.values], "gamma", lower = 0.01) : 
  optimization failed
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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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 
206.647   5.047 215.683 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0020.0020.004
SEG0.0020.0020.004
calcEffectSizes0.1290.0050.133
combineSCE1.2660.0201.292
computeZScore0.2600.0100.271
convertSCEToSeurat3.1810.2013.393
convertSeuratToSCE0.3860.0060.391
dedupRowNames0.0540.0030.057
detectCellOutlier5.0360.1355.188
diffAbundanceFET0.0370.0010.039
discreteColorPalette0.0050.0000.006
distinctColors0.0020.0000.002
downSampleCells0.6000.0570.659
downSampleDepth0.5400.0500.593
expData-ANY-character-method0.3610.0090.370
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.3450.0070.352
expData-set0.3560.0080.365
expData0.3190.0050.324
expDataNames-ANY-method0.2990.0040.305
expDataNames0.2640.0060.271
expDeleteDataTag0.0410.0050.047
expSetDataTag0.0260.0020.028
expTaggedData0.0300.0020.033
exportSCE0.0280.0050.034
exportSCEtoAnnData0.0840.0020.085
exportSCEtoFlatFile0.0910.0030.094
featureIndex0.0350.0040.039
generateSimulatedData0.0430.0030.045
getBiomarker0.0430.0030.046
getDEGTopTable0.8070.0340.843
getDiffAbundanceResults0.0390.0010.041
getEnrichRResult0.3130.0401.930
getFindMarkerTopTable3.0160.0383.062
getMSigDBTable0.0030.0020.005
getPathwayResultNames0.0230.0040.027
getSampleSummaryStatsTable0.3460.0050.352
getSoupX0.3950.0130.409
getTSCANResults1.6100.0321.646
getTopHVG0.6620.0090.673
importAnnData0.0010.0010.001
importBUStools0.2500.0030.254
importCellRanger0.8760.0260.910
importCellRangerV2Sample0.2460.0020.250
importCellRangerV3Sample0.3350.0120.349
importDropEst0.2960.0040.301
importExampleData16.778 1.69019.078
importGeneSetsFromCollection0.7480.1210.878
importGeneSetsFromGMT0.0690.0050.075
importGeneSetsFromList0.1120.0050.117
importGeneSetsFromMSigDB3.0340.1223.167
importMitoGeneSet0.0450.0070.052
importOptimus0.0010.0000.002
importSEQC0.2570.0070.267
importSTARsolo0.2760.0090.287
iterateSimulations0.3300.0170.348
listSampleSummaryStatsTables0.4060.0210.428
mergeSCEColData0.4500.0190.477
mouseBrainSubsetSCE0.0260.0020.028
msigdb_table0.0010.0020.004
plotBarcodeRankDropsResults0.7250.0110.738
plotBarcodeRankScatter0.7130.0150.731
plotBatchCorrCompare9.5610.1079.677
plotBatchVariance0.2890.0060.297
plotBcdsResults6.6540.1286.790
plotClusterAbundance0.8860.0380.926
plotCxdsResults5.4750.1025.586
plotDEGHeatmap2.5140.0772.602
plotDEGRegression3.1360.0463.192
plotDEGViolin3.4990.0723.575
plotDEGVolcano0.9560.0120.969
plotDecontXResults6.8740.0656.953
plotDimRed0.2240.0030.228
plotDoubletFinderResults21.231 0.18021.447
plotEmptyDropsResults5.5460.0195.575
plotEmptyDropsScatter5.7810.0235.827
plotFindMarkerHeatmap4.2580.0294.311
plotMASTThresholdGenes1.3770.0201.409
plotPCA0.5760.0090.612
plotPathway0.7950.0130.814
plotRunPerCellQCResults1.2160.0151.236
plotSCEBarAssayData0.1770.0050.183
plotSCEBarColData0.1320.0030.136
plotSCEBatchFeatureMean0.2480.0030.251
plotSCEDensity0.2080.0040.213
plotSCEDensityAssayData0.1610.0040.172
plotSCEDensityColData0.2120.0050.218
plotSCEDimReduceColData0.8370.0090.852
plotSCEDimReduceFeatures0.3010.0040.305
plotSCEHeatmap0.6570.0080.667
plotSCEScatter0.4190.0090.430
plotSCEViolin0.1880.0040.193
plotSCEViolinAssayData0.2520.0040.257
plotSCEViolinColData0.2000.0040.206
plotScDblFinderResults22.847 0.72123.614
plotScdsHybridResults7.9280.1638.103
plotScrubletResults0.0200.0020.023
plotSeuratElbow0.0200.0020.022
plotSeuratHVG0.0220.0020.025
plotSeuratJackStraw0.0210.0020.023
plotSeuratReduction0.0190.0020.022
plotSoupXResults0.1600.0040.166
plotTSCANClusterDEG4.7890.0754.871
plotTSCANClusterPseudo2.0420.0232.070
plotTSCANDimReduceFeatures1.8970.0151.914
plotTSCANPseudotimeGenes1.8740.0181.896
plotTSCANPseudotimeHeatmap1.9220.0161.941
plotTSCANResults1.8860.0191.910
plotTSNE0.4080.0050.414
plotTopHVG0.3450.0060.353
plotUMAP5.6060.0795.691
readSingleCellMatrix0.0030.0000.003
reportCellQC0.1760.0050.181
reportDropletQC0.0230.0040.028
reportQCTool0.1640.0060.171
retrieveSCEIndex0.0280.0030.031
runBBKNN000
runBarcodeRankDrops0.3910.0050.396
runBcds1.5410.0381.581
runCellQC0.1520.0050.155
runComBatSeq0.4230.0170.442
runCxds0.6060.0390.650
runCxdsBcdsHybrid1.6730.0331.711
runDEAnalysis0.5900.0070.598
runDecontX6.1130.0886.211
runDimReduce0.4310.0060.439
runDoubletFinder16.502 0.10716.630
runDropletQC0.0210.0040.024
runEmptyDrops5.3700.0175.400
runEnrichR0.2260.0201.787
runFastMNN1.5010.0361.548
runFeatureSelection0.2100.0020.213
runFindMarker2.8320.0322.873
runGSVA0.6720.0160.690
runHarmony0.0280.0010.028
runKMeans0.4120.0070.421
runLimmaBC0.0700.0010.071
runMNNCorrect0.4810.0040.487
runModelGeneVar0.3990.0060.407
runNormalization0.5340.0080.546
runPerCellQC0.5060.0230.530
runSCANORAMA000
runSCMerge0.0030.0010.004
runScDblFinder15.302 0.37715.724
runScranSNN0.6540.0090.665
runScrublet0.0200.0020.022
runSeuratFindClusters0.0200.0020.021
runSeuratFindHVG0.5390.1130.655
runSeuratHeatmap0.0230.0080.032
runSeuratICA0.0220.0020.024
runSeuratJackStraw0.0210.0020.024
runSeuratNormalizeData0.0280.0040.033
runSeuratPCA0.0270.0040.031
runSeuratSCTransform3.4040.0983.513
runSeuratScaleData0.0300.0030.033
runSeuratUMAP0.0300.0070.037
runSingleR0.0350.0020.037
runSoupX0.1740.0040.178
runTSCAN1.4270.0191.449
runTSCANClusterDEAnalysis1.4230.0141.439
runTSCANDEG1.4730.0171.493
runTSNE0.8060.0120.819
runUMAP5.6510.0775.727
runVAM0.4810.0040.486
runZINBWaVE0.0030.0000.004
sampleSummaryStats0.2820.0060.289
scaterCPM0.1120.0070.118
scaterPCA0.4050.0080.413
scaterlogNormCounts0.2420.0030.246
sce0.0230.0060.028
sctkListGeneSetCollections0.0610.0030.064
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv000
selectSCTKConda0.0000.0010.000
selectSCTKVirtualEnvironment000
setRowNames0.0660.0020.068
setSCTKDisplayRow0.3440.0060.350
singleCellTK000
subDiffEx0.4790.0250.505
subsetSCECols0.1480.0060.155
subsetSCERows0.3660.0050.372
summarizeSCE0.0550.0010.057
trimCounts0.2440.0060.251