Back to Multiple platform build/check report for BioC 3.16:   simplified   long
ABCDEFGHIJKLMNOPQR[S]TUVWXYZ

This page was generated on 2023-04-12 11:05:52 -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 palomino4


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: set _R_CHECK_FORCE_SUGGESTS_=0&& F:\biocbuild\bbs-3.16-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:singleCellTK.install-out.txt --library=F:\biocbuild\bbs-3.16-bioc\R\library --no-vignettes --timings singleCellTK_2.8.0.tar.gz
StartedAt: 2023-04-11 06:07:39 -0400 (Tue, 11 Apr 2023)
EndedAt: 2023-04-11 06:22:15 -0400 (Tue, 11 Apr 2023)
EllapsedTime: 875.2 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   set _R_CHECK_FORCE_SUGGESTS_=0&& F:\biocbuild\bbs-3.16-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:singleCellTK.install-out.txt --library=F:\biocbuild\bbs-3.16-bioc\R\library --no-vignettes --timings singleCellTK_2.8.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'F:/biocbuild/bbs-3.16-bioc/meat/singleCellTK.Rcheck'
* using R version 4.2.3 (2023-03-15 ucrt)
* using platform: x86_64-w64-mingw32 (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 whether package 'singleCellTK' can be installed ... OK
* checking installed package size ... NOTE
  installed size is  6.5Mb
  sub-directories of 1Mb or more:
    extdata   1.5Mb
    shiny     2.8Mb
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                          user system elapsed
plotScDblFinderResults   27.17   0.83   28.03
plotDoubletFinderResults 25.04   0.13   25.48
importExampleData        17.68   2.21   20.29
runDoubletFinder         18.93   0.04   19.04
runScDblFinder           17.33   0.31   17.65
plotEmptyDropsScatter    11.42   0.05   11.47
plotBatchCorrCompare     11.33   0.12   11.50
plotEmptyDropsResults    11.32   0.06   11.37
runEmptyDrops            10.86   0.03   10.89
plotScdsHybridResults    10.03   0.19    9.72
plotBcdsResults           8.09   0.18    8.18
plotDecontXResults        8.14   0.05    8.20
runDecontX                6.70   0.05    6.75
plotTSCANClusterDEG       6.59   0.09    6.69
plotCxdsResults           6.58   0.09    6.68
plotUMAP                  6.62   0.02    6.69
runUMAP                   6.53   0.04    6.59
detectCellOutlier         5.76   0.11    6.36
* 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
  'F:/biocbuild/bbs-3.16-bioc/meat/singleCellTK.Rcheck/00check.log'
for details.



Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.16-bioc\R\bin\R.exe CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library 'F:/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 4.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (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 
   0.15    0.04    0.23 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (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

Attaching package: 'IRanges'

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

    windows

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

  |                                                                            
  |                                                                      |   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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Estimating GSVA scores for 34 gene sets.
Estimating ECDFs with Gaussian kernels

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |==                                                                    |   3%
  |                                                                            
  |====                                                                  |   6%
  |                                                                            
  |======                                                                |   9%
  |                                                                            
  |========                                                              |  12%
  |                                                                            
  |==========                                                            |  15%
  |                                                                            
  |============                                                          |  18%
  |                                                                            
  |==============                                                        |  21%
  |                                                                            
  |================                                                      |  24%
  |                                                                            
  |===================                                                   |  26%
  |                                                                            
  |=====================                                                 |  29%
  |                                                                            
  |=======================                                               |  32%
  |                                                                            
  |=========================                                             |  35%
  |                                                                            
  |===========================                                           |  38%
  |                                                                            
  |=============================                                         |  41%
  |                                                                            
  |===============================                                       |  44%
  |                                                                            
  |=================================                                     |  47%
  |                                                                            
  |===================================                                   |  50%
  |                                                                            
  |=====================================                                 |  53%
  |                                                                            
  |=======================================                               |  56%
  |                                                                            
  |=========================================                             |  59%
  |                                                                            
  |===========================================                           |  62%
  |                                                                            
  |=============================================                         |  65%
  |                                                                            
  |===============================================                       |  68%
  |                                                                            
  |=================================================                     |  71%
  |                                                                            
  |===================================================                   |  74%
  |                                                                            
  |======================================================                |  76%
  |                                                                            
  |========================================================              |  79%
  |                                                                            
  |==========================================================            |  82%
  |                                                                            
  |============================================================          |  85%
  |                                                                            
  |==============================================================        |  88%
  |                                                                            
  |================================================================      |  91%
  |                                                                            
  |==================================================================    |  94%
  |                                                                            
  |====================================================================  |  97%
  |                                                                            
  |======================================================================| 100%

Estimating GSVA scores for 2 gene sets.
Estimating ECDFs with Gaussian kernels

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |===================================                                   |  50%
  |                                                                            
  |======================================================================| 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: 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 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 221 ]

[ FAIL 0 | WARN 20 | SKIP 0 | PASS 221 ]
> 
> proc.time()
   user  system elapsed 
 256.62    7.70  266.42 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.000.010.02
SEG000
calcEffectSizes0.280.000.28
combineSCE2.220.212.43
computeZScore0.340.000.35
convertSCEToSeurat2.720.254.24
convertSeuratToSCE0.390.030.43
dedupRowNames0.970.020.98
detectCellOutlier5.760.116.36
diffAbundanceFET0.040.000.03
discreteColorPalette0.030.000.03
distinctColors000
downSampleCells0.870.080.96
downSampleDepth0.670.010.68
expData-ANY-character-method0.320.000.32
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.320.020.34
expData-set0.350.010.36
expData0.280.030.31
expDataNames-ANY-method0.300.020.31
expDataNames0.360.020.38
expDeleteDataTag0.060.000.07
expSetDataTag0.030.020.04
expTaggedData0.030.010.05
exportSCE0.000.050.05
exportSCEtoAnnData0.060.020.08
exportSCEtoFlatFile0.060.000.06
featureIndex0.050.010.07
generateSimulatedData0.040.000.04
getBiomarker0.070.000.07
getDEGTopTable0.950.061.01
getDiffAbundanceResults0.030.000.03
getEnrichRResult0.270.051.10
getFindMarkerTopTable3.360.133.48
getMSigDBTable000
getPathwayResultNames0.040.000.05
getSampleSummaryStatsTable0.350.030.37
getSoupX0.330.060.39
getTSCANResults1.840.162.09
getTopHVG1.040.031.07
importAnnData000
importBUStools0.300.000.33
importCellRanger1.300.061.47
importCellRangerV2Sample0.340.000.34
importCellRangerV3Sample0.450.030.53
importDropEst0.350.020.38
importExampleData17.68 2.2120.29
importGeneSetsFromCollection0.700.130.83
importGeneSetsFromGMT0.060.030.10
importGeneSetsFromList0.160.000.15
importGeneSetsFromMSigDB3.280.063.43
importMitoGeneSet0.070.030.10
importOptimus000
importSEQC0.280.000.31
importSTARsolo0.330.000.34
iterateSimulations0.420.040.45
listSampleSummaryStatsTables0.420.030.46
mergeSCEColData0.480.090.59
mouseBrainSubsetSCE0.030.000.03
msigdb_table000
plotBarcodeRankDropsResults0.860.030.89
plotBarcodeRankScatter0.750.030.78
plotBatchCorrCompare11.33 0.1211.50
plotBatchVariance0.460.000.45
plotBcdsResults8.090.188.18
plotClusterAbundance1.140.001.14
plotCxdsResults6.580.096.68
plotDEGHeatmap2.950.093.05
plotDEGRegression3.860.084.03
plotDEGViolin4.630.104.72
plotDEGVolcano1.060.011.08
plotDecontXResults8.140.058.20
plotDimRed0.330.010.35
plotDoubletFinderResults25.04 0.1325.48
plotEmptyDropsResults11.32 0.0611.37
plotEmptyDropsScatter11.42 0.0511.47
plotFindMarkerHeatmap4.940.044.99
plotMASTThresholdGenes1.820.041.86
plotPCA0.680.000.67
plotPathway1.150.011.41
plotRunPerCellQCResults1.350.061.40
plotSCEBarAssayData0.150.020.17
plotSCEBarColData0.130.020.14
plotSCEBatchFeatureMean0.250.000.25
plotSCEDensity0.220.010.24
plotSCEDensityAssayData0.20.00.2
plotSCEDensityColData0.250.000.25
plotSCEDimReduceColData0.950.020.97
plotSCEDimReduceFeatures0.440.030.47
plotSCEHeatmap0.780.010.80
plotSCEScatter0.360.000.36
plotSCEViolin0.300.000.57
plotSCEViolinAssayData0.370.000.38
plotSCEViolinColData0.30.00.3
plotScDblFinderResults27.17 0.8328.03
plotScdsHybridResults10.03 0.19 9.72
plotScrubletResults0.030.010.04
plotSeuratElbow0.030.020.05
plotSeuratHVG0.020.020.03
plotSeuratJackStraw0.030.010.05
plotSeuratReduction0.030.020.04
plotSoupXResults0.210.030.24
plotTSCANClusterDEG6.590.096.69
plotTSCANClusterPseudo2.430.062.49
plotTSCANDimReduceFeatures2.220.042.25
plotTSCANPseudotimeGenes2.340.012.36
plotTSCANPseudotimeHeatmap2.420.002.42
plotTSCANResults2.080.082.15
plotTSNE0.500.030.53
plotTopHVG0.420.000.43
plotUMAP6.620.026.69
readSingleCellMatrix0.020.000.02
reportCellQC0.170.010.18
reportDropletQC0.050.000.05
reportQCTool0.180.030.22
retrieveSCEIndex0.030.020.05
runBBKNN000
runBarcodeRankDrops0.470.030.50
runBcds2.140.051.68
runCellQC0.190.010.21
runComBatSeq0.640.020.70
runCxds0.610.010.62
runCxdsBcdsHybrid2.330.112.00
runDEAnalysis0.750.030.79
runDecontX6.700.056.75
runDimReduce0.460.020.46
runDoubletFinder18.93 0.0419.04
runDropletQC0.050.020.06
runEmptyDrops10.86 0.0310.89
runEnrichR0.230.020.76
runFastMNN1.660.031.80
runFeatureSelection0.20.00.2
runFindMarker3.240.083.32
runGSVA0.700.030.73
runHarmony0.030.010.05
runKMeans0.470.020.48
runLimmaBC0.080.000.08
runMNNCorrect0.580.000.58
runModelGeneVar0.510.010.53
runNormalization0.550.000.55
runPerCellQC0.560.020.58
runSCANORAMA000
runSCMerge000
runScDblFinder17.33 0.3117.65
runScranSNN0.750.000.75
runScrublet0.030.010.05
runSeuratFindClusters0.040.020.06
runSeuratFindHVG0.800.030.83
runSeuratHeatmap0.020.020.03
runSeuratICA0.010.030.05
runSeuratJackStraw0.030.010.04
runSeuratNormalizeData0.030.000.04
runSeuratPCA0.040.020.04
runSeuratSCTransform3.460.033.52
runSeuratScaleData0.040.000.03
runSeuratUMAP0.010.030.05
runSingleR0.050.000.04
runSoupX0.190.000.19
runTSCAN1.540.021.56
runTSCANClusterDEAnalysis1.780.061.85
runTSCANDEG1.500.031.53
runTSNE0.800.020.81
runUMAP6.530.046.59
runVAM0.600.020.61
runZINBWaVE000
sampleSummaryStats0.290.010.32
scaterCPM0.110.000.11
scaterPCA0.500.020.52
scaterlogNormCounts0.290.000.29
sce0.050.000.05
sctkListGeneSetCollections0.110.000.11
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.090.000.09
setSCTKDisplayRow0.430.010.44
singleCellTK000
subDiffEx0.480.030.51
subsetSCECols0.190.020.21
subsetSCERows0.500.040.54
summarizeSCE0.060.000.07
trimCounts0.220.020.23