Back to Multiple platform build/check report for BioC 3.20:   simplified   long
ABCDEFGHIJKLMNOPQR[S]TUVWXYZ

This page was generated on 2024-11-09 21:31 -0500 (Sat, 09 Nov 2024).

HostnameOSArch (*)R versionInstalled pkgs
teran2Linux (Ubuntu 24.04.1 LTS)x86_644.4.1 (2024-06-14) -- "Race for Your Life" 4505
palomino8Windows Server 2022 Datacenterx644.4.1 (2024-06-14 ucrt) -- "Race for Your Life" 4506
lconwaymacOS 12.7.1 Montereyx86_644.4.1 (2024-06-14) -- "Race for Your Life" 4538
kjohnson3macOS 13.6.5 Venturaarm644.4.1 (2024-06-14) -- "Race for Your Life" 4486
kunpeng2Linux (openEuler 22.03 LTS-SP1)aarch644.4.1 (2024-06-14) -- "Race for Your Life" 4493
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

Package 1977/2289HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.16.0  (landing page)
Joshua David Campbell
Snapshot Date: 2024-11-08 13:40 -0500 (Fri, 08 Nov 2024)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_20
git_last_commit: 6bbe76f
git_last_commit_date: 2024-10-29 11:30:33 -0500 (Tue, 29 Oct 2024)
teran2Linux (Ubuntu 24.04.1 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino8Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
lconwaymacOS 12.7.1 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kjohnson3macOS 13.6.5 Ventura / arm64  OK    OK    OK    OK  NO, package depends on 'enrichR' which is not available
kunpeng2Linux (openEuler 22.03 LTS-SP1) / aarch64  OK    OK    OK  


CHECK results for singleCellTK on kjohnson3

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.
- If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information.

raw results


Summary

Package: singleCellTK
Version: 2.16.0
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_2.16.0.tar.gz
StartedAt: 2024-11-09 13:36:20 -0500 (Sat, 09 Nov 2024)
EndedAt: 2024-11-09 13:45:30 -0500 (Sat, 09 Nov 2024)
EllapsedTime: 549.4 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_2.16.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/singleCellTK.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.7
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.16.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ...Warning: unable to access index for repository https://CRAN.R-project.org/src/contrib:
  cannot open URL 'https://CRAN.R-project.org/src/contrib/PACKAGES'
 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  6.8Mb
  sub-directories of 1Mb or more:
    R         1.0Mb
    extdata   1.5Mb
    shiny     2.9Mb
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code 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 whether 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
plotDoubletFinderResults 13.184  0.062  13.246
plotScDblFinderResults   12.327  0.202  12.533
runDoubletFinder         12.281  0.053  12.336
runScDblFinder            9.240  0.111   9.351
importExampleData         4.581  0.377   5.397
getEnrichRResult          0.127  0.016   6.887
* 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 ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.20-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/4.4-arm64/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 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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 
  0.069   0.016   0.084 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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, saveRDS, setdiff, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:utils':

    findMatches

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

Loading required package: S4Arrays
Loading required package: abind

Attaching package: 'S4Arrays'

The following object is masked from 'package:abind':

    abind

The following object is masked from 'package:base':

    rowsum

Loading required package: SparseArray

Attaching package: 'DelayedArray'

The following objects are masked from 'package:base':

    apply, 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 390
Number of edges: 9849

Running Louvain algorithm...
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Maximum modularity in 10 random starts: 0.8351
Number of communities: 7
Elapsed time: 0 seconds
Using method 'umap'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 20 | SKIP 0 | PASS 224 ]

[ FAIL 0 | WARN 20 | SKIP 0 | PASS 224 ]
> 
> proc.time()
   user  system elapsed 
 92.625   2.077  97.650 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0000.0010.002
SEG0.0010.0010.002
calcEffectSizes0.0530.0050.057
combineSCE0.3640.0070.370
computeZScore0.0860.0020.088
convertSCEToSeurat1.3470.0411.388
convertSeuratToSCE0.1280.0010.129
dedupRowNames0.0190.0010.019
detectCellOutlier1.9810.0332.020
diffAbundanceFET0.0220.0010.022
discreteColorPalette0.0020.0000.002
distinctColors0.0010.0000.001
downSampleCells0.2190.0130.231
downSampleDepth0.1570.0100.167
expData-ANY-character-method0.0890.0010.090
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.0900.0020.093
expData-set0.0870.0020.089
expData0.0800.0030.083
expDataNames-ANY-method0.0880.0070.095
expDataNames0.0800.0020.082
expDeleteDataTag0.0140.0020.016
expSetDataTag0.0100.0010.012
expTaggedData0.0110.0010.012
exportSCE0.0100.0020.012
exportSCEtoAnnData0.0420.0010.043
exportSCEtoFlatFile0.0410.0010.042
featureIndex0.0140.0020.015
generateSimulatedData0.0200.0020.022
getBiomarker0.0210.0010.023
getDEGTopTable0.2390.0090.248
getDiffAbundanceResults0.0190.0010.019
getEnrichRResult0.1270.0166.887
getFindMarkerTopTable0.8470.0120.859
getMSigDBTable0.0010.0010.002
getPathwayResultNames0.0110.0020.013
getSampleSummaryStatsTable0.1200.0020.123
getSoupX000
getTSCANResults0.4760.0110.488
getTopHVG0.3210.0070.327
importAnnData0.0010.0000.001
importBUStools0.0650.0010.066
importCellRanger0.2720.0090.282
importCellRangerV2Sample0.0620.0000.063
importCellRangerV3Sample0.1070.0040.111
importDropEst0.0830.0010.084
importExampleData4.5810.3775.397
importGeneSetsFromCollection0.2680.0260.294
importGeneSetsFromGMT0.0240.0010.026
importGeneSetsFromList0.0380.0020.040
importGeneSetsFromMSigDB1.3510.0321.383
importMitoGeneSet0.0210.0030.024
importOptimus0.0010.0000.001
importSEQC0.0760.0070.083
importSTARsolo0.0770.0100.088
iterateSimulations0.130.010.14
listSampleSummaryStatsTables0.1210.0030.124
mergeSCEColData0.1400.0060.146
mouseBrainSubsetSCE0.0180.0030.020
msigdb_table0.0010.0010.002
plotBarcodeRankDropsResults0.2710.0060.277
plotBarcodeRankScatter0.2410.0030.244
plotBatchCorrCompare4.5280.0304.560
plotBatchVariance0.0960.0070.103
plotBcdsResults2.9570.0623.019
plotBubble0.2780.0100.290
plotClusterAbundance0.2390.0030.241
plotCxdsResults2.3130.0272.339
plotDEGHeatmap0.6400.0150.655
plotDEGRegression0.9540.0190.975
plotDEGViolin1.1340.0351.174
plotDEGVolcano0.2890.0040.292
plotDecontXResults2.7990.0272.826
plotDimRed0.0830.0030.086
plotDoubletFinderResults13.184 0.06213.246
plotEmptyDropsResults2.1140.0032.117
plotEmptyDropsScatter2.1240.0032.128
plotFindMarkerHeatmap1.2770.0091.287
plotMASTThresholdGenes0.3930.0080.403
plotPCA0.1370.0030.140
plotPathway0.1960.0030.201
plotRunPerCellQCResults0.5560.0050.561
plotSCEBarAssayData0.0600.0020.062
plotSCEBarColData0.0410.0020.043
plotSCEBatchFeatureMean0.0550.0010.055
plotSCEDensity0.0610.0020.063
plotSCEDensityAssayData0.0610.0020.063
plotSCEDensityColData0.0580.0030.060
plotSCEDimReduceColData0.1770.0030.181
plotSCEDimReduceFeatures0.1080.0030.111
plotSCEHeatmap0.1570.0020.159
plotSCEScatter0.0920.0030.094
plotSCEViolin0.0660.0020.068
plotSCEViolinAssayData0.0820.0020.084
plotSCEViolinColData0.0660.0020.067
plotScDblFinderResults12.327 0.20212.533
plotScanpyDotPlot0.0120.0010.012
plotScanpyEmbedding0.0110.0020.012
plotScanpyHVG0.0110.0010.012
plotScanpyHeatmap0.0110.0010.012
plotScanpyMarkerGenes0.0110.0020.012
plotScanpyMarkerGenesDotPlot0.0110.0010.012
plotScanpyMarkerGenesHeatmap0.0110.0010.012
plotScanpyMarkerGenesMatrixPlot0.0110.0020.012
plotScanpyMarkerGenesViolin0.0110.0010.012
plotScanpyMatrixPlot0.0110.0010.012
plotScanpyPCA0.0100.0010.012
plotScanpyPCAGeneRanking0.0110.0010.012
plotScanpyPCAVariance0.0110.0010.012
plotScanpyViolin0.0110.0010.012
plotScdsHybridResults3.4110.0663.478
plotScrubletResults0.0120.0000.014
plotSeuratElbow0.0110.0000.012
plotSeuratHVG0.0110.0010.011
plotSeuratJackStraw0.0110.0010.012
plotSeuratReduction0.0110.0000.011
plotSoupXResults000
plotTSCANClusterDEG1.4810.0221.503
plotTSCANClusterPseudo0.6340.0080.641
plotTSCANDimReduceFeatures0.6210.0090.629
plotTSCANPseudotimeGenes0.5950.0070.601
plotTSCANPseudotimeHeatmap0.6290.0070.636
plotTSCANResults0.5940.0080.603
plotTSNE0.1410.0030.146
plotTopHVG0.1650.0040.169
plotUMAP2.5160.0312.547
readSingleCellMatrix0.0010.0010.002
reportCellQC0.0500.0010.052
reportDropletQC0.0110.0010.012
reportQCTool0.0520.0020.053
retrieveSCEIndex0.0130.0010.015
runBBKNN0.0000.0010.000
runBarcodeRankDrops0.1230.0010.126
runBcds0.6030.0260.629
runCellQC0.0550.0030.059
runClusterSummaryMetrics0.2110.0110.223
runComBatSeq0.1600.0040.164
runCxds0.1450.0030.148
runCxdsBcdsHybrid0.6340.0120.646
runDEAnalysis0.2040.0020.206
runDecontX2.8760.0192.895
runDimReduce0.1350.0040.139
runDoubletFinder12.281 0.05312.336
runDropletQC0.0120.0010.012
runEmptyDrops2.0510.0022.053
runEnrichR0.1120.0121.185
runFastMNN0.5500.0220.572
runFeatureSelection0.0780.0020.080
runFindMarker0.9450.0130.958
runGSVA0.3110.0120.323
runHarmony0.0110.0010.010
runKMeans0.1250.0030.128
runLimmaBC0.0210.0000.022
runMNNCorrect0.1520.0020.155
runModelGeneVar0.1580.0040.162
runNormalization0.9090.0260.934
runPerCellQC0.1510.0050.157
runSCANORAMA000
runSCMerge0.0020.0010.002
runScDblFinder9.2400.1119.351
runScanpyFindClusters0.0100.0010.010
runScanpyFindHVG0.0090.0000.010
runScanpyFindMarkers0.0090.0000.010
runScanpyNormalizeData0.0480.0010.048
runScanpyPCA0.0090.0010.010
runScanpyScaleData0.0100.0000.009
runScanpyTSNE0.0090.0000.009
runScanpyUMAP0.0090.0010.010
runScranSNN0.1750.0040.179
runScrublet0.010.000.01
runSeuratFindClusters0.0090.0000.010
runSeuratFindHVG0.1990.0140.213
runSeuratHeatmap0.0090.0000.010
runSeuratICA0.010.000.01
runSeuratJackStraw0.0090.0000.010
runSeuratNormalizeData0.0090.0000.009
runSeuratPCA0.0090.0000.010
runSeuratSCTransform1.9450.0202.009
runSeuratScaleData0.0120.0010.013
runSeuratUMAP0.0110.0000.012
runSingleR0.0110.0010.012
runSoupX000
runTSCAN0.3990.0160.416
runTSCANClusterDEAnalysis0.4390.0080.447
runTSCANDEG0.4220.0040.426
runTSNE0.3260.0110.337
runUMAP2.6760.0242.700
runVAM0.1500.0020.151
runZINBWaVE0.0020.0010.002
sampleSummaryStats0.0800.0020.082
scaterCPM0.0580.0020.060
scaterPCA0.1890.0190.209
scaterlogNormCounts0.0950.0080.102
sce0.0120.0020.014
sctkListGeneSetCollections0.0270.0030.029
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment0.0000.0000.001
setRowNames0.0280.0030.030
setSCTKDisplayRow0.1350.0050.140
singleCellTK000
subDiffEx0.1580.0090.167
subsetSCECols0.0530.0030.056
subsetSCERows0.1200.0030.124
summarizeSCE0.0260.0020.028
trimCounts0.0850.0060.090