Back to Multiple platform build/check report for BioC 3.18:   simplified   long
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This page was generated on 2024-03-29 11:36:23 -0400 (Fri, 29 Mar 2024).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 22.04.3 LTS)x86_644.3.3 (2024-02-29) -- "Angel Food Cake" 4669
palomino4Windows Server 2022 Datacenterx644.3.3 (2024-02-29 ucrt) -- "Angel Food Cake" 4404
merida1macOS 12.7.1 Montereyx86_644.3.3 (2024-02-29) -- "Angel Food Cake" 4427
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: 2024-03-27 14:05:05 -0400 (Wed, 27 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: 2024-03-28 02:49:19 -0400 (Thu, 28 Mar 2024)
EndedAt: 2024-03-28 03:04:32 -0400 (Thu, 28 Mar 2024)
EllapsedTime: 913.3 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  6.9Mb
  sub-directories of 1Mb or more:
    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 31.197  0.212  31.407
runSeuratSCTransform     29.915  0.684  30.601
runDoubletFinder         29.961  0.176  30.137
plotScDblFinderResults   28.427  0.528  28.952
runScDblFinder           20.272  0.560  20.833
importExampleData        15.528  0.924  17.018
plotBatchCorrCompare     10.427  0.200  10.619
plotScdsHybridResults     9.467  0.160   8.732
plotBcdsResults           8.104  0.177   7.398
plotDecontXResults        7.935  0.244   8.179
plotEmptyDropsResults     6.700  0.016   6.716
runUMAP                   6.507  0.184   6.687
plotEmptyDropsScatter     6.561  0.056   6.618
runEmptyDrops             6.341  0.020   6.361
runDecontX                6.278  0.028   6.306
detectCellOutlier         5.983  0.259   6.243
plotCxdsResults           6.006  0.023   6.027
plotUMAP                  5.915  0.064   5.977
plotTSCANClusterDEG       5.206  0.044   5.250
* 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 
  0.179   0.008   0.174 

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 
263.820   8.008 272.325 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0030.0000.003
SEG0.0000.0020.003
calcEffectSizes0.2650.0050.269
combineSCE2.1140.0522.165
computeZScore0.2600.0160.276
convertSCEToSeurat4.2870.1554.444
convertSeuratToSCE0.5150.0040.520
dedupRowNames0.0580.0000.059
detectCellOutlier5.9830.2596.243
diffAbundanceFET0.0600.0010.060
discreteColorPalette0.0070.0000.007
distinctColors0.0020.0000.002
downSampleCells0.6640.0910.757
downSampleDepth0.5560.0010.556
expData-ANY-character-method0.2990.0000.298
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.3460.0120.357
expData-set0.3270.0080.335
expData0.3350.0120.347
expDataNames-ANY-method0.3090.0000.309
expDataNames0.3030.0040.307
expDeleteDataTag0.0370.0000.037
expSetDataTag0.0220.0040.026
expTaggedData0.0270.0000.027
exportSCE0.0230.0000.023
exportSCEtoAnnData0.0970.0000.097
exportSCEtoFlatFile0.0890.0080.097
featureIndex0.0370.0000.037
generateSimulatedData0.0530.0000.053
getBiomarker0.0620.0000.061
getDEGTopTable0.9260.0400.966
getDiffAbundanceResults0.0570.0000.057
getEnrichRResult0.4490.0313.569
getFindMarkerTopTable3.7360.0923.828
getMSigDBTable0.0040.0000.004
getPathwayResultNames0.0270.0000.027
getSampleSummaryStatsTable0.3750.0000.374
getSoupX000
getTSCANResults2.1110.0202.131
getTopHVG1.2370.0081.245
importAnnData0.0020.0000.001
importBUStools0.2940.0080.301
importCellRanger1.2800.0401.321
importCellRangerV2Sample0.2720.0120.284
importCellRangerV3Sample0.4240.0040.428
importDropEst0.3490.0000.350
importExampleData15.528 0.92417.018
importGeneSetsFromCollection0.6820.0080.690
importGeneSetsFromGMT0.0640.0000.064
importGeneSetsFromList0.1140.0040.118
importGeneSetsFromMSigDB3.3670.1603.528
importMitoGeneSet0.0520.0000.052
importOptimus0.0020.0000.001
importSEQC0.2390.0120.251
importSTARsolo0.250.020.27
iterateSimulations0.3600.0120.373
listSampleSummaryStatsTables0.3610.0000.361
mergeSCEColData0.4190.0080.426
mouseBrainSubsetSCE0.0320.0040.036
msigdb_table0.0010.0000.002
plotBarcodeRankDropsResults0.8050.0120.817
plotBarcodeRankScatter0.7580.0040.762
plotBatchCorrCompare10.427 0.20010.619
plotBatchVariance0.3110.0040.315
plotBcdsResults8.1040.1777.398
plotBubble1.0330.0041.037
plotClusterAbundance0.8430.0160.859
plotCxdsResults6.0060.0236.027
plotDEGHeatmap2.8280.0202.849
plotDEGRegression3.6070.0203.621
plotDEGViolin4.4750.0524.522
plotDEGVolcano1.0200.0081.028
plotDecontXResults7.9350.2448.179
plotDimRed0.2640.0000.265
plotDoubletFinderResults31.197 0.21231.407
plotEmptyDropsResults6.7000.0166.716
plotEmptyDropsScatter6.5610.0566.618
plotFindMarkerHeatmap4.0490.0364.085
plotMASTThresholdGenes1.4600.0241.485
plotPCA0.4610.0040.466
plotPathway0.8240.0000.824
plotRunPerCellQCResults2.1280.0042.132
plotSCEBarAssayData0.1780.0000.178
plotSCEBarColData0.1360.0000.136
plotSCEBatchFeatureMean0.2050.0000.205
plotSCEDensity0.2460.0000.246
plotSCEDensityAssayData0.170.000.17
plotSCEDensityColData0.2040.0000.204
plotSCEDimReduceColData0.6580.0040.662
plotSCEDimReduceFeatures0.3870.0040.391
plotSCEHeatmap0.6170.0000.617
plotSCEScatter0.3970.0000.397
plotSCEViolin0.2360.0000.236
plotSCEViolinAssayData0.2460.0000.246
plotSCEViolinColData0.2280.0000.228
plotScDblFinderResults28.427 0.52828.952
plotScanpyDotPlot0.0240.0000.024
plotScanpyEmbedding0.0200.0040.024
plotScanpyHVG0.0220.0000.023
plotScanpyHeatmap0.0220.0000.022
plotScanpyMarkerGenes0.0230.0000.023
plotScanpyMarkerGenesDotPlot0.0190.0030.023
plotScanpyMarkerGenesHeatmap0.0240.0000.024
plotScanpyMarkerGenesMatrixPlot0.0230.0000.023
plotScanpyMarkerGenesViolin0.0190.0040.023
plotScanpyMatrixPlot0.0240.0000.024
plotScanpyPCA0.0230.0000.024
plotScanpyPCAGeneRanking0.0240.0000.024
plotScanpyPCAVariance0.0230.0000.023
plotScanpyViolin0.0240.0000.024
plotScdsHybridResults9.4670.1608.732
plotScrubletResults0.0240.0000.024
plotSeuratElbow0.0240.0000.024
plotSeuratHVG0.0240.0000.024
plotSeuratJackStraw0.0230.0000.023
plotSeuratReduction0.0230.0000.023
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plotTSCANClusterDEG5.2060.0445.250
plotTSCANClusterPseudo2.4490.0042.453
plotTSCANDimReduceFeatures2.2800.0362.316
plotTSCANPseudotimeGenes2.0910.0322.123
plotTSCANPseudotimeHeatmap2.3360.0002.336
plotTSCANResults2.1240.0002.124
plotTSNE0.4550.0000.456
plotTopHVG0.3880.0000.388
plotUMAP5.9150.0645.977
readSingleCellMatrix0.0040.0000.004
reportCellQC0.1590.0000.159
reportDropletQC0.0240.0000.024
reportQCTool0.1610.0000.161
retrieveSCEIndex0.0290.0000.029
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runBcds2.2540.0481.409
runCellQC0.1580.0040.163
runClusterSummaryMetrics0.6620.0040.666
runComBatSeq0.4250.0080.433
runCxds0.4410.0120.452
runCxdsBcdsHybrid2.2140.0121.397
runDEAnalysis0.6380.0280.666
runDecontX6.2780.0286.306
runDimReduce0.4250.0000.426
runDoubletFinder29.961 0.17630.137
runDropletQC0.0240.0000.025
runEmptyDrops6.3410.0206.361
runEnrichR0.4330.0601.810
runFastMNN1.6710.0761.748
runFeatureSelection0.2040.0280.232
runFindMarker3.5240.2923.817
runGSVA0.7530.1200.873
runHarmony0.0350.0040.040
runKMeans0.4300.0280.458
runLimmaBC0.0800.0040.083
runMNNCorrect0.4940.0640.557
runModelGeneVar0.4660.0240.489
runNormalization2.5030.3442.846
runPerCellQC0.4740.0240.499
runSCANORAMA0.0000.0000.001
runSCMerge0.0040.0000.004
runScDblFinder20.272 0.56020.833
runScanpyFindClusters0.0260.0000.026
runScanpyFindHVG0.0230.0000.024
runScanpyFindMarkers0.0240.0000.023
runScanpyNormalizeData0.1980.0160.213
runScanpyPCA0.0250.0000.024
runScanpyScaleData0.0240.0000.024
runScanpyTSNE0.0230.0000.024
runScanpyUMAP0.0230.0000.023
runScranSNN0.7630.0560.819
runScrublet0.0270.0000.028
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runSeuratFindHVG2.4760.2322.709
runSeuratHeatmap0.0250.0000.024
runSeuratICA0.0230.0000.024
runSeuratJackStraw0.0150.0080.024
runSeuratNormalizeData0.0230.0000.023
runSeuratPCA0.0260.0000.025
runSeuratSCTransform29.915 0.68430.601
runSeuratScaleData0.0240.0000.024
runSeuratUMAP0.0230.0000.023
runSingleR0.0360.0000.036
runSoupX000
runTSCAN1.4190.0081.427
runTSCANClusterDEAnalysis1.5130.0161.530
runTSCANDEG1.4440.0081.452
runTSNE0.8690.0120.881
runUMAP6.5070.1846.687
runVAM0.5280.0000.528
runZINBWaVE0.0050.0000.004
sampleSummaryStats0.2920.0000.291
scaterCPM0.1330.0080.140
scaterPCA0.4230.0080.431
scaterlogNormCounts0.2540.0000.254
sce0.0230.0000.023
sctkListGeneSetCollections0.0750.0080.083
sctkPythonInstallConda0.0010.0000.000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.0790.0040.084
setSCTKDisplayRow0.4000.0160.415
singleCellTK0.0010.0000.000
subDiffEx0.5100.0120.522
subsetSCECols0.1730.0000.173
subsetSCERows0.3690.0080.377
summarizeSCE0.0640.0000.064
trimCounts0.2040.0080.212