Back to Multiple platform build/check report for BioC 3.17
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This page was generated on 2023-04-12 10:55:31 -0400 (Wed, 12 Apr 2023).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 22.04.1 LTS)x86_644.3.0 alpha (2023-04-03 r84154) 4547
nebbiolo2Linux (Ubuntu 20.04.5 LTS)x86_64R Under development (unstable) (2023-02-14 r83833) -- "Unsuffered Consequences" 4333
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 nebbiolo1


To the developers/maintainers of the singleCellTK package:
- 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 Troubleshooting Build Report for more information.

- Use the following Renviron settings to reproduce errors and warnings.

Note: If "R CMD check" recently failed on the Linux builder over a missing dependency, add the missing dependency to "Suggests" in your DESCRIPTION file. See the Renviron.bioc for details.

raw results

Package 1914/2207HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.9.0  (landing page)
Yichen Wang
Snapshot Date: 2023-04-11 14:00:16 -0400 (Tue, 11 Apr 2023)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: devel
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    OK  
nebbiolo2Linux (Ubuntu 20.04.5 LTS) / x86_64  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/site-library --timings singleCellTK_2.9.0.tar.gz
StartedAt: 2023-04-11 23:37:39 -0400 (Tue, 11 Apr 2023)
EndedAt: 2023-04-11 23:52:04 -0400 (Tue, 11 Apr 2023)
EllapsedTime: 865.1 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/site-library --timings singleCellTK_2.9.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/singleCellTK.Rcheck’
* using R version 4.3.0 alpha (2023-04-03 r84154)
* using platform: x86_64-pc-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 22.04.2 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  5.4Mb
  sub-directories of 1Mb or more:
    shiny   2.3Mb
* 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 loading without being on the library search path ... OK
* checking startup messages can be suppressed ... 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   31.407  0.512  31.916
plotDoubletFinderResults 27.355  0.416  27.768
runDoubletFinder         20.129  0.144  20.273
importExampleData        17.547  2.195  20.331
runScDblFinder           14.304  1.035  15.339
plotBatchCorrCompare     13.956  0.595  14.543
plotScdsHybridResults    13.149  0.200  11.845
plotBcdsResults          10.772  0.309   9.506
plotDecontXResults        8.254  0.236   8.490
plotCxdsResults           8.126  0.212   8.335
plotUMAP                  7.638  0.032   7.666
runUMAP                   7.018  0.340   7.356
plotEmptyDropsResults     6.764  0.008   6.773
plotEmptyDropsScatter     6.717  0.032   6.749
runDecontX                6.457  0.116   6.574
runEmptyDrops             6.405  0.015   6.421
detectCellOutlier         5.804  0.171   5.976
plotTSCANClusterDEG       5.903  0.040   5.943
* 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/site-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 4.3.0 alpha (2023-04-03 r84154)
Copyright (C) 2023 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 
  0.147   0.037   0.175 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.3.0 alpha (2023-04-03 r84154)
Copyright (C) 2023 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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Error in fitdistr(mahalanobis.sq.null[nonzero.values], "gamma", lower = 0.01) : 
  optimization failed
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
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 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'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 23 | SKIP 0 | PASS 221 ]

[ FAIL 0 | WARN 23 | SKIP 0 | PASS 221 ]
> 
> proc.time()
   user  system elapsed 
244.480   8.686 253.705 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0030.0000.003
SEG0.0030.0000.002
calcEffectSizes0.1580.0000.158
combineSCE1.5260.0521.578
computeZScore0.2800.0160.296
convertSCEToSeurat3.1920.2043.396
convertSeuratToSCE0.4400.0000.441
dedupRowNames0.0580.0000.058
detectCellOutlier5.8040.1715.976
diffAbundanceFET0.0520.0010.053
discreteColorPalette0.0080.0000.007
distinctColors0.0030.0000.003
downSampleCells0.6780.0510.730
downSampleDepth0.5770.0130.589
expData-ANY-character-method0.3450.0000.345
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.4390.0000.439
expData-set0.3810.0000.381
expData0.3440.0160.359
expDataNames-ANY-method0.4010.0030.406
expDataNames0.340.000.34
expDeleteDataTag0.0380.0000.039
expSetDataTag0.0280.0000.028
expTaggedData0.0250.0040.029
exportSCE0.0250.0000.025
exportSCEtoAnnData0.0820.0150.097
exportSCEtoFlatFile0.0910.0070.100
featureIndex0.0380.0030.042
generateSimulatedData0.0470.0050.050
getBiomarker0.0550.0030.060
getDEGTopTable0.9750.0281.003
getDiffAbundanceResults0.0420.0010.042
getEnrichRResult0.5080.0912.257
getFindMarkerTopTable3.5400.2123.753
getMSigDBTable0.0020.0030.004
getPathwayResultNames0.0250.0000.025
getSampleSummaryStatsTable0.3740.0190.394
getSoupX0.3680.0040.372
getTSCANResults1.9950.1282.124
getTopHVG0.8600.0110.870
importAnnData0.0020.0000.002
importBUStools0.2620.0120.274
importCellRanger1.1330.0681.202
importCellRangerV2Sample0.2510.0040.255
importCellRangerV3Sample0.3890.0000.390
importDropEst0.3040.0120.317
importExampleData17.547 2.19520.331
importGeneSetsFromCollection0.8160.0640.879
importGeneSetsFromGMT0.0720.0040.076
importGeneSetsFromList0.1350.0120.146
importGeneSetsFromMSigDB4.3300.3484.678
importMitoGeneSet0.0570.0000.057
importOptimus0.0020.0000.002
importSEQC0.2610.0200.281
importSTARsolo0.2810.0360.318
iterateSimulations0.3590.0270.386
listSampleSummaryStatsTables0.5320.0440.577
mergeSCEColData0.5040.0270.530
mouseBrainSubsetSCE0.0230.0040.028
msigdb_table0.0020.0000.002
plotBarcodeRankDropsResults0.9360.0911.027
plotBarcodeRankScatter0.8400.0330.873
plotBatchCorrCompare13.956 0.59514.543
plotBatchVariance0.3590.0090.367
plotBcdsResults10.772 0.309 9.506
plotClusterAbundance1.2190.0561.275
plotCxdsResults8.1260.2128.335
plotDEGHeatmap2.8530.1082.961
plotDEGRegression3.6610.0923.746
plotDEGViolin4.3570.0764.427
plotDEGVolcano1.0310.0151.046
plotDecontXResults8.2540.2368.490
plotDimRed0.2740.0080.282
plotDoubletFinderResults27.355 0.41627.768
plotEmptyDropsResults6.7640.0086.773
plotEmptyDropsScatter6.7170.0326.749
plotFindMarkerHeatmap4.5890.0324.621
plotMASTThresholdGenes1.8180.0041.822
plotPCA0.5390.0080.546
plotPathway0.9550.0320.987
plotRunPerCellQCResults1.3550.0121.367
plotSCEBarAssayData0.1780.0000.177
plotSCEBarColData0.1410.0080.149
plotSCEBatchFeatureMean0.2440.0000.245
plotSCEDensity0.2320.0000.231
plotSCEDensityAssayData0.180.000.18
plotSCEDensityColData0.2680.0000.268
plotSCEDimReduceColData0.7950.0040.800
plotSCEDimReduceFeatures0.3870.0040.391
plotSCEHeatmap0.8150.0510.866
plotSCEScatter0.3950.0120.408
plotSCEViolin0.2520.0160.267
plotSCEViolinAssayData0.2740.0040.279
plotSCEViolinColData0.3310.0000.331
plotScDblFinderResults31.407 0.51231.916
plotScdsHybridResults13.149 0.20011.845
plotScrubletResults0.0260.0000.027
plotSeuratElbow0.0260.0000.026
plotSeuratHVG0.0320.0040.035
plotSeuratJackStraw0.0270.0000.027
plotSeuratReduction0.0270.0000.026
plotSoupXResults0.2090.0040.214
plotTSCANClusterDEG5.9030.0405.943
plotTSCANClusterPseudo2.2590.0522.310
plotTSCANDimReduceFeatures2.3080.0042.311
plotTSCANPseudotimeGenes2.1960.0202.217
plotTSCANPseudotimeHeatmap2.5260.0242.551
plotTSCANResults2.2540.0042.257
plotTSNE0.5020.0030.506
plotTopHVG0.4130.0000.413
plotUMAP7.6380.0327.666
readSingleCellMatrix0.0050.0000.005
reportCellQC0.1750.0040.179
reportDropletQC0.0250.0000.024
reportQCTool0.1890.0000.189
retrieveSCEIndex0.0330.0000.033
runBBKNN000
runBarcodeRankDrops0.4720.0000.472
runBcds2.4480.0401.553
runCellQC0.1750.0000.175
runComBatSeq0.4510.0040.455
runCxds0.6100.0040.614
runCxdsBcdsHybrid2.3450.0201.506
runDEAnalysis0.6320.0000.632
runDecontX6.4570.1166.574
runDimReduce0.4430.0040.447
runDoubletFinder20.129 0.14420.273
runDropletQC0.0250.0000.024
runEmptyDrops6.4050.0156.421
runEnrichR0.4820.0321.727
runFastMNN1.7890.0531.841
runFeatureSelection0.2100.0000.209
runFindMarker3.1750.0553.232
runGSVA0.7110.0560.767
runHarmony0.0390.0030.043
runKMeans0.4750.0590.535
runLimmaBC0.0780.0030.082
runMNNCorrect0.5540.0560.611
runModelGeneVar0.4490.0370.485
runNormalization0.5670.0790.646
runPerCellQC0.4970.0350.533
runSCANORAMA000
runSCMerge0.0040.0000.005
runScDblFinder14.304 1.03515.339
runScranSNN0.7360.0560.793
runScrublet0.0240.0040.028
runSeuratFindClusters0.0260.0000.025
runSeuratFindHVG0.6160.0560.673
runSeuratHeatmap0.0240.0000.024
runSeuratICA0.0240.0000.023
runSeuratJackStraw0.0230.0000.024
runSeuratNormalizeData0.0230.0000.023
runSeuratPCA0.0240.0000.023
runSeuratSCTransform3.2610.3283.589
runSeuratScaleData0.0220.0040.026
runSeuratUMAP0.0240.0000.024
runSingleR0.0380.0000.038
runSoupX0.1850.0000.185
runTSCAN1.4500.1001.551
runTSCANClusterDEAnalysis1.6140.0921.706
runTSCANDEG1.6690.0361.705
runTSNE0.8520.0240.876
runUMAP7.0180.3407.356
runVAM0.5630.0040.568
runZINBWaVE0.0050.0000.005
sampleSummaryStats0.3170.0040.322
scaterCPM0.1360.0040.140
scaterPCA0.4430.0280.471
scaterlogNormCounts0.2590.0040.263
sce0.0240.0000.025
sctkListGeneSetCollections0.0680.0120.080
sctkPythonInstallConda0.0010.0000.000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.0820.0080.090
setSCTKDisplayRow0.3970.0440.441
singleCellTK0.0010.0000.000
subDiffEx0.5080.0200.528
subsetSCECols0.1680.0070.176
subsetSCERows0.4120.0000.413
summarizeSCE0.0540.0040.058
trimCounts0.2570.0160.273