Back to Multiple platform build/check report for BioC 3.20:   simplified   long
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This page was generated on 2024-11-19 12:40 -0500 (Tue, 19 Nov 2024).

HostnameOSArch (*)R versionInstalled pkgs
teran2Linux (Ubuntu 24.04.1 LTS)x86_644.4.1 (2024-06-14) -- "Race for Your Life" 4505
nebbiolo2Linux (Ubuntu 24.04.1 LTS)x86_644.4.1 (2024-06-14) -- "Race for Your Life" 4765
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" 4539
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: 2024-11-18 13:40 -0500 (Mon, 18 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
nebbiolo2Linux (Ubuntu 24.04.1 LTS) / x86_64  OK    OK    OK  
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
kunpeng2Linux (openEuler 22.03 LTS-SP1) / aarch64  OK    OK    OK  


CHECK results for singleCellTK on teran2

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: /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings singleCellTK_2.16.0.tar.gz
StartedAt: 2024-11-19 07:50:36 -0500 (Tue, 19 Nov 2024)
EndedAt: 2024-11-19 08:04:34 -0500 (Tue, 19 Nov 2024)
EllapsedTime: 837.6 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings singleCellTK_2.16.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/singleCellTK.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0
    GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0
* running under: Ubuntu 24.04.1 LTS
* using session charset: UTF-8
* 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 ... 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 ... 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 loading without being on the library search path ... 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 33.768  0.049  39.033
runDoubletFinder         31.479  0.074  33.036
runSeuratSCTransform     25.591  0.538  27.995
plotScDblFinderResults   23.647  0.243  26.439
runScDblFinder           13.777  0.077  14.837
plotBatchCorrCompare     10.891  0.007  14.037
importExampleData         8.543  0.359  11.255
plotScdsHybridResults     8.446  0.015   9.840
plotBcdsResults           7.690  0.077   9.054
plotDecontXResults        6.730  0.004   7.362
runUMAP                   6.662  0.019   7.106
runDecontX                6.659  0.005   7.289
plotUMAP                  6.392  0.007   7.139
plotCxdsResults           5.999  0.010   7.323
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.


Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/media/volume/teran2_disk/biocbuild/bbs-3.20-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 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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 
  0.097   0.047   0.135 

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: x86_64-pc-linux-gnu

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

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

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  |======================================================================| 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'
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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  |======================================================================| 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 
226.130   4.569 249.763 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0010.0010.002
SEG0.0020.0010.002
calcEffectSizes0.1180.0030.122
combineSCE0.5340.0490.828
computeZScore0.1710.0090.185
convertSCEToSeurat3.0030.0523.165
convertSeuratToSCE0.2110.0020.214
dedupRowNames0.0440.0030.048
detectCellOutlier4.7270.0314.967
diffAbundanceFET0.0400.0010.041
discreteColorPalette0.0040.0000.004
distinctColors0.0010.0000.001
downSampleCells0.3520.0540.406
downSampleDepth0.2930.0020.306
expData-ANY-character-method0.0850.0010.086
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.1070.0010.108
expData-set0.10.00.1
expData0.0830.0000.083
expDataNames-ANY-method0.0760.0020.078
expDataNames0.0710.0160.087
expDeleteDataTag0.0260.0010.027
expSetDataTag0.0180.0020.020
expTaggedData0.0180.0010.019
exportSCE0.0180.0000.018
exportSCEtoAnnData0.0640.0100.073
exportSCEtoFlatFile0.0820.0070.099
featureIndex0.0270.0000.026
generateSimulatedData0.0360.0010.037
getBiomarker0.0400.0010.041
getDEGTopTable0.4480.0060.454
getDiffAbundanceResults0.0350.0000.035
getEnrichRResult0.3310.0182.274
getFindMarkerTopTable0.9780.0051.139
getMSigDBTable0.0000.0030.003
getPathwayResultNames0.0170.0010.018
getSampleSummaryStatsTable0.1250.0000.136
getSoupX000
getTSCANResults0.7660.0100.917
getTopHVG0.5610.0010.580
importAnnData0.0010.0000.001
importBUStools0.1430.0010.180
importCellRanger0.5040.0060.518
importCellRangerV2Sample0.0950.0010.097
importCellRangerV3Sample0.1900.0020.194
importDropEst0.1720.0010.223
importExampleData 8.543 0.35911.255
importGeneSetsFromCollection0.5070.0210.529
importGeneSetsFromGMT0.1460.0020.151
importGeneSetsFromList0.0890.0000.089
importGeneSetsFromMSigDB2.9510.1503.629
importMitoGeneSet0.0370.0020.038
importOptimus0.0020.0000.001
importSEQC0.1050.0000.107
importSTARsolo0.1110.0060.120
iterateSimulations0.1450.0280.204
listSampleSummaryStatsTables0.2000.0310.235
mergeSCEColData0.2960.0100.357
mouseBrainSubsetSCE0.0270.0020.029
msigdb_table0.0020.0000.002
plotBarcodeRankDropsResults0.4490.0010.453
plotBarcodeRankScatter0.4410.0000.449
plotBatchCorrCompare10.891 0.00714.037
plotBatchVariance0.2240.0020.227
plotBcdsResults7.6900.0779.054
plotBubble0.4810.0590.569
plotClusterAbundance0.6270.0160.707
plotCxdsResults5.9990.0107.323
plotDEGHeatmap1.4770.0041.533
plotDEGRegression2.3760.0102.698
plotDEGViolin3.1240.0113.196
plotDEGVolcano0.5930.0030.630
plotDecontXResults6.7300.0047.362
plotDimRed0.1400.0010.141
plotDoubletFinderResults33.768 0.04939.033
plotEmptyDropsResults3.5740.0013.636
plotEmptyDropsScatter3.6260.0034.348
plotFindMarkerHeatmap2.7100.0012.767
plotMASTThresholdGenes0.9480.0070.963
plotPCA0.2240.0010.225
plotPathway0.3770.0010.381
plotRunPerCellQCResults1.5110.0031.650
plotSCEBarAssayData0.1400.0020.144
plotSCEBarColData0.1450.0020.148
plotSCEBatchFeatureMean0.1570.0000.157
plotSCEDensity0.1530.0030.170
plotSCEDensityAssayData0.1240.0010.124
plotSCEDensityColData0.1510.0020.154
plotSCEDimReduceColData0.3570.0010.359
plotSCEDimReduceFeatures0.1900.0010.251
plotSCEHeatmap0.3370.0030.340
plotSCEScatter0.1760.0010.177
plotSCEViolin0.1720.0020.178
plotSCEViolinAssayData0.1830.0020.185
plotSCEViolinColData0.1710.0030.174
plotScDblFinderResults23.647 0.24326.439
plotScanpyDotPlot0.0190.0000.025
plotScanpyEmbedding0.0170.0000.017
plotScanpyHVG0.0170.0000.017
plotScanpyHeatmap0.0160.0010.017
plotScanpyMarkerGenes0.0160.0010.017
plotScanpyMarkerGenesDotPlot0.0160.0010.017
plotScanpyMarkerGenesHeatmap0.0170.0000.017
plotScanpyMarkerGenesMatrixPlot0.0170.0000.017
plotScanpyMarkerGenesViolin0.0170.0000.017
plotScanpyMatrixPlot0.0170.0000.017
plotScanpyPCA0.0160.0010.017
plotScanpyPCAGeneRanking0.0170.0000.017
plotScanpyPCAVariance0.0170.0000.017
plotScanpyViolin0.0160.0010.017
plotScdsHybridResults8.4460.0159.840
plotScrubletResults0.0180.0000.019
plotSeuratElbow0.0160.0010.017
plotSeuratHVG0.0170.0000.018
plotSeuratJackStraw0.0170.0000.017
plotSeuratReduction0.0170.0000.017
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plotTSCANClusterPseudo0.8710.0040.989
plotTSCANDimReduceFeatures0.8610.0060.951
plotTSCANPseudotimeGenes0.9930.0041.149
plotTSCANPseudotimeHeatmap0.9310.0011.070
plotTSCANResults0.7920.0030.837
plotTSNE0.2280.0010.258
plotTopHVG0.4020.0010.405
plotUMAP6.3920.0077.139
readSingleCellMatrix0.0040.0000.004
reportCellQC0.0580.0010.059
reportDropletQC0.0160.0010.018
reportQCTool0.0550.0010.056
retrieveSCEIndex0.0210.0000.022
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runBarcodeRankDrops0.1890.0000.189
runBcds2.8960.0022.409
runCellQC0.0590.0000.059
runClusterSummaryMetrics0.2550.0030.259
runComBatSeq0.3520.0040.357
runCxds0.2190.0000.218
runCxdsBcdsHybrid1.7050.0031.102
runDEAnalysis0.2590.0020.272
runDecontX6.6590.0057.289
runDimReduce0.1950.0020.197
runDoubletFinder31.479 0.07433.036
runDropletQC0.0160.0010.017
runEmptyDrops3.4270.0013.790
runEnrichR0.3500.0072.023
runFastMNN1.2170.0051.901
runFeatureSelection0.1470.0020.151
runFindMarker1.0400.0051.166
runGSVA0.7310.0040.775
runHarmony0.0270.0010.028
runKMeans0.1290.0010.130
runLimmaBC0.0530.0000.053
runMNNCorrect0.2890.0000.293
runModelGeneVar0.2290.0010.309
runNormalization2.3140.0012.561
runPerCellQC0.2420.0000.275
runSCANORAMA000
runSCMerge0.0030.0000.003
runScDblFinder13.777 0.07714.837
runScanpyFindClusters0.0170.0010.018
runScanpyFindHVG0.0170.0000.017
runScanpyFindMarkers0.0170.0000.017
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runScanpyPCA0.0180.0000.018
runScanpyScaleData0.0150.0020.018
runScanpyTSNE0.0170.0000.017
runScanpyUMAP0.0160.0010.017
runScranSNN0.2090.0020.212
runScrublet0.0170.0000.018
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runSeuratFindHVG0.3290.0030.331
runSeuratHeatmap0.0170.0010.018
runSeuratICA0.0160.0010.018
runSeuratJackStraw0.0170.0000.018
runSeuratNormalizeData0.0170.0000.018
runSeuratPCA0.0180.0000.017
runSeuratSCTransform25.591 0.53827.995
runSeuratScaleData0.0180.0000.018
runSeuratUMAP0.0170.0010.017
runSingleR0.0250.0000.025
runSoupX000
runTSCAN0.4460.0040.452
runTSCANClusterDEAnalysis0.5170.0020.569
runTSCANDEG0.4780.0000.497
runTSNE0.6370.8431.485
runUMAP6.6620.0197.106
runVAM0.2050.0010.206
runZINBWaVE0.0020.0000.003
sampleSummaryStats0.1110.0000.112
scaterCPM0.0980.0050.103
scaterPCA0.3090.0010.310
scaterlogNormCounts0.1590.0080.167
sce0.0180.0000.021
sctkListGeneSetCollections0.0550.0010.056
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.0590.0000.060
setSCTKDisplayRow0.7810.0000.961
singleCellTK000
subDiffEx0.2280.0030.232
subsetSCECols0.0570.0010.058
subsetSCERows0.1460.0040.150
summarizeSCE0.0490.0000.049
trimCounts0.1370.0290.166