Back to Multiple platform build/check report for BioC 3.18:   simplified   long
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This page was generated on 2024-03-18 11:36:21 -0400 (Mon, 18 Mar 2024).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 22.04.3 LTS)x86_644.3.3 (2024-02-29) -- "Angel Food Cake" 4665
palomino4Windows Server 2022 Datacenterx644.3.3 (2024-02-29 ucrt) -- "Angel Food Cake" 4401
merida1macOS 12.7.1 Montereyx86_644.3.3 (2024-02-29) -- "Angel Food Cake" 4425
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 1971/2266HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.12.2  (landing page)
Joshua David Campbell
Snapshot Date: 2024-03-15 14:05:07 -0400 (Fri, 15 Mar 2024)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_18
git_last_commit: 14c92130
git_last_commit_date: 2024-02-05 14:45:10 -0400 (Mon, 05 Feb 2024)
nebbiolo2Linux (Ubuntu 22.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino4Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
merida1macOS 12.7.1 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kjohnson1macOS 13.6.1 Ventura / arm64see weekly results here

CHECK results for singleCellTK on nebbiolo2


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: 2.12.2
Command: /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.18-bioc/R/site-library --timings singleCellTK_2.12.2.tar.gz
StartedAt: 2024-03-16 02:36:06 -0400 (Sat, 16 Mar 2024)
EndedAt: 2024-03-16 02:51:19 -0400 (Sat, 16 Mar 2024)
EllapsedTime: 913.0 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.18-bioc/R/site-library --timings singleCellTK_2.12.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.18-bioc/meat/singleCellTK.Rcheck’
* using R version 4.3.3 (2024-02-29)
* using platform: x86_64-pc-linux-gnu (64-bit)
* R was compiled by
    gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
    GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.12.2’
* 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  7.0Mb
  sub-directories of 1Mb or more:
    R         1.0Mb
    extdata   1.6Mb
    shiny     3.0Mb
* 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
plotDoubletFinderResults 32.978  0.207  33.182
runDoubletFinder         31.122  0.208  31.331
runSeuratSCTransform     30.632  0.216  30.850
plotScDblFinderResults   27.333  0.456  27.786
runScDblFinder           19.493  0.132  19.625
importExampleData        17.731  1.112  19.357
plotBatchCorrCompare     10.442  0.200  10.635
plotScdsHybridResults     9.635  0.148   8.918
plotDecontXResults        7.945  0.196   8.142
plotBcdsResults           7.871  0.184   7.179
plotEmptyDropsScatter     6.597  0.024   6.621
plotEmptyDropsResults     6.590  0.008   6.598
runDecontX                6.544  0.016   6.560
runUMAP                   6.329  0.088   6.415
runEmptyDrops             6.374  0.008   6.382
detectCellOutlier         6.108  0.184   6.293
plotUMAP                  6.010  0.028   6.036
plotCxdsResults           6.003  0.032   6.033
plotTSCANClusterDEG       5.109  0.064   5.173
* 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-3.18-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.



Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.18-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 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 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 
  0.172   0.020   0.181 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 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 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
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  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Uploading data to Enrichr... Done.
  Querying HDSigDB_Human_2021... Done.
Parsing results... Done.
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Estimating GSVA scores for 34 gene sets.
Estimating ECDFs with Gaussian kernels

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

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Performing log-normalization
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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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
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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: 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'
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 22 | SKIP 0 | PASS 223 ]

[ FAIL 0 | WARN 22 | SKIP 0 | PASS 223 ]
> 
> proc.time()
   user  system elapsed 
264.237   4.288 269.272 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0020.0000.003
SEG0.0020.0000.002
calcEffectSizes0.3070.0040.311
combineSCE2.2170.1362.353
computeZScore0.2620.0160.277
convertSCEToSeurat4.5320.1444.676
convertSeuratToSCE0.5110.0280.540
dedupRowNames0.0580.0000.058
detectCellOutlier6.1080.1846.293
diffAbundanceFET0.0610.0000.061
discreteColorPalette0.0060.0000.006
distinctColors0.0020.0000.002
downSampleCells0.6680.0720.741
downSampleDepth0.5700.0030.574
expData-ANY-character-method0.2980.0030.302
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.3490.0090.357
expData-set0.3460.0040.349
expData0.3320.0270.360
expDataNames-ANY-method0.3030.0050.307
expDataNames0.3090.0160.325
expDeleteDataTag0.0370.0030.041
expSetDataTag0.0260.0010.026
expTaggedData0.0280.0000.027
exportSCE0.0160.0070.025
exportSCEtoAnnData0.0910.0090.099
exportSCEtoFlatFile0.0930.0030.097
featureIndex0.0380.0010.037
generateSimulatedData0.0540.0000.054
getBiomarker0.0600.0000.061
getDEGTopTable0.9050.0270.933
getDiffAbundanceResults0.0540.0010.054
getEnrichRResult0.7380.0444.167
getFindMarkerTopTable3.7100.0603.769
getMSigDBTable0.0040.0000.003
getPathwayResultNames0.0210.0040.025
getSampleSummaryStatsTable0.3130.0040.317
getSoupX000
getTSCANResults1.8670.0281.896
getTopHVG1.1020.0281.131
importAnnData0.0000.0010.001
importBUStools0.2770.0060.283
importCellRanger1.1890.0761.266
importCellRangerV2Sample0.2670.0040.271
importCellRangerV3Sample0.4180.0040.423
importDropEst0.3090.0000.309
importExampleData17.731 1.11219.357
importGeneSetsFromCollection0.7250.0240.749
importGeneSetsFromGMT0.0660.0040.070
importGeneSetsFromList0.1230.0000.123
importGeneSetsFromMSigDB3.8440.1483.991
importMitoGeneSet0.0550.0000.055
importOptimus0.0020.0000.001
importSEQC0.260.000.26
importSTARsolo0.2670.0230.290
iterateSimulations0.3900.0040.394
listSampleSummaryStatsTables0.3800.0000.381
mergeSCEColData0.4590.0000.459
mouseBrainSubsetSCE0.0380.0000.038
msigdb_table0.0010.0000.001
plotBarcodeRankDropsResults0.8640.0080.871
plotBarcodeRankScatter0.7940.0000.794
plotBatchCorrCompare10.442 0.20010.635
plotBatchVariance0.3040.0000.304
plotBcdsResults7.8710.1847.179
plotBubble1.0510.0041.055
plotClusterAbundance0.8550.0000.855
plotCxdsResults6.0030.0326.033
plotDEGHeatmap2.7740.0362.811
plotDEGRegression3.4420.0283.465
plotDEGViolin4.2010.0724.268
plotDEGVolcano0.9670.0000.967
plotDecontXResults7.9450.1968.142
plotDimRed0.2760.0000.276
plotDoubletFinderResults32.978 0.20733.182
plotEmptyDropsResults6.5900.0086.598
plotEmptyDropsScatter6.5970.0246.621
plotFindMarkerHeatmap4.0160.0484.064
plotMASTThresholdGenes1.5310.0161.547
plotPCA0.5120.0040.516
plotPathway0.7730.0040.777
plotRunPerCellQCResults2.1860.0042.189
plotSCEBarAssayData0.1820.0040.186
plotSCEBarColData0.1420.0000.141
plotSCEBatchFeatureMean0.2500.0000.249
plotSCEDensity0.2110.0000.211
plotSCEDensityAssayData0.170.000.17
plotSCEDensityColData0.2150.0000.216
plotSCEDimReduceColData0.7250.0000.725
plotSCEDimReduceFeatures0.3560.0000.357
plotSCEHeatmap0.6300.0040.635
plotSCEScatter0.4010.0040.405
plotSCEViolin0.2430.0000.243
plotSCEViolinAssayData0.2440.0000.244
plotSCEViolinColData0.2300.0000.229
plotScDblFinderResults27.333 0.45627.786
plotScanpyDotPlot0.0250.0000.025
plotScanpyEmbedding0.0210.0040.025
plotScanpyHVG0.0230.0000.023
plotScanpyHeatmap0.0240.0000.023
plotScanpyMarkerGenes0.0230.0000.023
plotScanpyMarkerGenesDotPlot0.0200.0030.023
plotScanpyMarkerGenesHeatmap0.0240.0000.024
plotScanpyMarkerGenesMatrixPlot0.0230.0000.023
plotScanpyMarkerGenesViolin0.0190.0040.023
plotScanpyMatrixPlot0.0230.0000.023
plotScanpyPCA0.0240.0000.024
plotScanpyPCAGeneRanking0.0250.0000.025
plotScanpyPCAVariance0.0250.0000.025
plotScanpyViolin0.0250.0000.025
plotScdsHybridResults9.6350.1488.918
plotScrubletResults0.0240.0000.024
plotSeuratElbow0.0240.0000.023
plotSeuratHVG0.0240.0000.023
plotSeuratJackStraw0.0230.0000.024
plotSeuratReduction0.0240.0000.023
plotSoupXResults000
plotTSCANClusterDEG5.1090.0645.173
plotTSCANClusterPseudo2.3110.0042.316
plotTSCANDimReduceFeatures2.1470.0082.155
plotTSCANPseudotimeGenes2.0870.0162.103
plotTSCANPseudotimeHeatmap2.0670.0042.072
plotTSCANResults2.0260.0082.035
plotTSNE0.4570.0040.461
plotTopHVG0.3950.0000.395
plotUMAP6.0100.0286.036
readSingleCellMatrix0.0050.0000.005
reportCellQC0.1640.0000.164
reportDropletQC0.0240.0000.023
reportQCTool0.1650.0000.165
retrieveSCEIndex0.0290.0000.029
runBBKNN0.0010.0000.000
runBarcodeRankDrops0.3840.0000.384
runBcds2.2480.0121.393
runCellQC0.1740.0000.174
runClusterSummaryMetrics0.6920.0040.696
runComBatSeq0.430.000.43
runCxds0.4540.0000.454
runCxdsBcdsHybrid2.2490.0121.427
runDEAnalysis0.6480.0200.668
runDecontX6.5440.0166.560
runDimReduce0.430.000.43
runDoubletFinder31.122 0.20831.331
runDropletQC0.0250.0000.024
runEmptyDrops6.3740.0086.382
runEnrichR0.6720.0482.151
runFastMNN1.6880.0441.732
runFeatureSelection0.2260.0000.226
runFindMarker3.3510.0123.364
runGSVA2.1590.0282.187
runHarmony0.0340.0000.034
runKMeans0.40.00.4
runLimmaBC0.0730.0000.073
runMNNCorrect0.4750.0040.479
runModelGeneVar0.4280.0000.428
runNormalization2.0260.0042.030
runPerCellQC0.4960.0000.496
runSCANORAMA000
runSCMerge0.0040.0000.004
runScDblFinder19.493 0.13219.625
runScanpyFindClusters0.0250.0000.025
runScanpyFindHVG0.0240.0000.024
runScanpyFindMarkers0.0240.0000.023
runScanpyNormalizeData0.1920.0080.200
runScanpyPCA0.0250.0000.025
runScanpyScaleData0.0240.0000.024
runScanpyTSNE0.0240.0000.024
runScanpyUMAP0.0240.0000.024
runScranSNN0.7320.0440.776
runScrublet0.0230.0000.023
runSeuratFindClusters0.0240.0000.024
runSeuratFindHVG0.8460.0280.874
runSeuratHeatmap0.0240.0000.024
runSeuratICA0.0240.0000.024
runSeuratJackStraw0.0240.0000.024
runSeuratNormalizeData0.0240.0000.024
runSeuratPCA0.0230.0000.023
runSeuratSCTransform30.632 0.21630.850
runSeuratScaleData0.0210.0040.024
runSeuratUMAP0.0240.0000.024
runSingleR0.0360.0000.036
runSoupX0.0010.0000.000
runTSCAN1.4400.0041.444
runTSCANClusterDEAnalysis1.5580.0001.558
runTSCANDEG1.5170.0001.517
runTSNE0.8670.0160.883
runUMAP6.3290.0886.415
runVAM0.5220.0080.530
runZINBWaVE0.0050.0000.005
sampleSummaryStats0.2880.0040.292
scaterCPM0.1360.0000.136
scaterPCA0.4230.0000.423
scaterlogNormCounts0.2510.0000.251
sce0.0240.0000.024
sctkListGeneSetCollections0.0770.0000.077
sctkPythonInstallConda0.0010.0000.000
sctkPythonInstallVirtualEnv000
selectSCTKConda0.0010.0000.000
selectSCTKVirtualEnvironment000
setRowNames0.0900.0000.089
setSCTKDisplayRow0.4070.0000.406
singleCellTK000
subDiffEx0.5320.0000.531
subsetSCECols0.1710.0000.171
subsetSCERows0.3880.0000.389
summarizeSCE0.0660.0000.066
trimCounts0.2020.0000.201