Multiple platform build/check report for BioC 3.20 - CHECK results for singleCellTK on palomino6

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo2	Linux (Ubuntu 22.04.3 LTS)	x86_64	4.4.1 (2024-06-14) -- "Race for Your Life"	4677
palomino6	Windows Server 2022 Datacenter	x64	4.4.1 (2024-06-14 ucrt) -- "Race for Your Life"	4416
lconway	macOS 12.7.1 Monterey	x86_64	4.4.1 (2024-06-14) -- "Race for Your Life"	4444
kjohnson3	macOS 13.6.5 Ventura	arm64	4.4.1 (2024-06-14) -- "Race for Your Life"	4393
palomino8	Windows Server 2022 Datacenter	x64	4.4.1 (2024-06-14 ucrt) -- "Race for Your Life"	4373
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 palomino6

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: 2.15.0

Command: set _R_CHECK_FORCE_SUGGESTS_=0&& C:\Users\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:singleCellTK.install-out.txt --library=C:\Users\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings singleCellTK_2.15.0.tar.gz

StartedAt: 2024-07-16 04:21:35 -0400 (Tue, 16 Jul 2024)

EndedAt: 2024-07-16 04:43:28 -0400 (Tue, 16 Jul 2024)

EllapsedTime: 1313.3 seconds

RetCode: 0

Status: OK

CheckDir: singleCellTK.Rcheck

Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   set _R_CHECK_FORCE_SUGGESTS_=0&& C:\Users\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:singleCellTK.install-out.txt --library=C:\Users\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings singleCellTK_2.15.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'C:/Users/biocbuild/bbs-3.20-bioc/meat/singleCellTK.Rcheck'
* using R version 4.4.1 (2024-06-14 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 13.2.0
    GNU Fortran (GCC) 13.2.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'singleCellTK/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'singleCellTK' version '2.15.0'
* 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  6.8Mb
  sub-directories of 1Mb or more:
    extdata   1.5Mb
    shiny     2.9Mb
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) dedupRowNames.Rd:10: Lost braces
    10 | \item{x}{A matrix like or /linkS4class{SingleCellExperiment} object, on which
       |                                       ^
checkRd: (-1) dedupRowNames.Rd:14: Lost braces
    14 | /linkS4class{SingleCellExperiment} object. When set to \code{TRUE}, will
       |             ^
checkRd: (-1) dedupRowNames.Rd:22: Lost braces
    22 | By default, a matrix or /linkS4class{SingleCellExperiment} object
       |                                     ^
checkRd: (-1) dedupRowNames.Rd:24: Lost braces
    24 | When \code{x} is a /linkS4class{SingleCellExperiment} and \code{as.rowData}
       |                                ^
checkRd: (-1) plotBubble.Rd:42: Lost braces
    42 | \item{scale}{Option to scale the data. Default: /code{FALSE}. Selected assay will not be scaled.}
       |                                                      ^
checkRd: (-1) runClusterSummaryMetrics.Rd:27: Lost braces
    27 | \item{scale}{Option to scale the data. Default: /code{FALSE}. Selected assay will not be scaled.}
       |                                                      ^
checkRd: (-1) runEmptyDrops.Rd:66: Lost braces
    66 | provided \\linkS4class{SingleCellExperiment} object.
       |                       ^
checkRd: (-1) runSCMerge.Rd:44: Lost braces
    44 | construct pseudo-replicates. The length of code{kmeansK} needs to be the same
       |                                                ^
* 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 62.02   0.17   63.69
runDoubletFinder         60.03   0.06   69.15
plotScDblFinderResults   35.97   5.66   41.70
importExampleData        24.71   4.62   31.49
plotBatchCorrCompare     19.12   0.12   19.84
runScDblFinder           17.31   0.80   18.11
detectCellOutlier        17.41   0.11   18.31
plotEmptyDropsResults    17.36   0.02   17.37
plotScdsHybridResults    16.84   0.44   17.41
plotDecontXResults       16.58   0.04   16.59
plotEmptyDropsScatter    16.46   0.01   17.10
runEmptyDrops            16.11   0.03   16.16
plotUMAP                 15.36   0.12   16.22
convertSCEToSeurat        6.34   7.45   11.27
plotBcdsResults          11.72   0.35   13.60
runDecontX               11.55   0.00   12.34
plotTSCANResults          9.47   0.06    9.53
runUMAP                   9.34   0.13    9.94
plotCxdsResults           9.18   0.14   10.25
dedupRowNames             8.53   0.03    9.75
plotFindMarkerHeatmap     7.21   0.08    7.48
runSeuratSCTransform      7.01   0.16    7.17
plotDEGRegression         5.92   0.06    5.99
plotTSCANClusterDEG       5.80   0.11    6.02
plotDEGHeatmap            5.18   0.41    5.90
plotDEGViolin             5.15   0.22    7.31
getFindMarkerTopTable     3.02   0.07    5.08
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
  Running 'spelling.R'
  Running 'testthat.R'
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  'C:/Users/biocbuild/bbs-3.20-bioc/meat/singleCellTK.Rcheck/00check.log'
for details.

Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   C:\Users\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library 'C:/Users/biocbuild/bbs-3.20-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 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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 
   0.14    0.09    0.17

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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, 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

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

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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  |======================================================================| 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
No annotation package name available in the input data object.
Attempting to directly match identifiers in data to gene sets.
Estimating GSVA scores for 34 gene sets.
Estimating ECDFs with Gaussian kernels

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No annotation package name available in the input data object.
Attempting to directly match identifiers in data to gene sets.
Estimating GSVA scores for 2 gene sets.
Estimating ECDFs with Gaussian kernels

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

  |                                                                            
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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'
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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Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 21 | SKIP 0 | PASS 224 ]

[ FAIL 0 | WARN 21 | SKIP 0 | PASS 224 ]
> 
> proc.time()
   user  system elapsed 
 295.10   16.39  316.26

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

name	user	system	elapsed
MitoGenes	0	0	0
SEG	0.02	0.00	0.01
calcEffectSizes	0.18	0.03	0.22
combineSCE	1.11	0.06	1.17
computeZScore	0.19	0.00	0.19
convertSCEToSeurat	6.34	7.45	11.27
convertSeuratToSCE	0.36	0.02	0.37
dedupRowNames	8.53	0.03	9.75
detectCellOutlier	17.41	0.11	18.31
diffAbundanceFET	0.06	0.01	0.08
discreteColorPalette	0	0	0
distinctColors	0.02	0.00	0.01
downSampleCells	0.59	0.18	0.77
downSampleDepth	1.33	0.03	1.91
expData-ANY-character-method	0.24	0.00	0.23
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method	0.25	0.01	0.27
expData-set	0.26	0.00	0.27
expData	0.20	0.11	0.31
expDataNames-ANY-method	0.25	0.06	0.31
expDataNames	0.22	0.02	0.23
expDeleteDataTag	0.03	0.00	0.03
expSetDataTag	0.03	0.00	0.04
expTaggedData	0.05	0.00	0.04
exportSCE	0.03	0.00	0.03
exportSCEtoAnnData	0.06	0.01	0.08
exportSCEtoFlatFile	0.03	0.05	0.08
featureIndex	0.07	0.00	0.06
generateSimulatedData	0.06	0.00	0.06
getBiomarker	0.03	0.05	0.08
getDEGTopTable	0.67	0.06	0.74
getDiffAbundanceResults	0.05	0.03	0.08
getEnrichRResult	0.29	0.05	4.21
getFindMarkerTopTable	3.02	0.07	5.08
getMSigDBTable	0	0	0
getPathwayResultNames	0.02	0.04	0.05
getSampleSummaryStatsTable	0.25	0.01	0.26
getSoupX	0	0	0
getTSCANResults	3.23	0.11	3.74
getTopHVG	0.92	0.03	0.95
importAnnData	0	0	0
importBUStools	0.22	0.00	0.22
importCellRanger	0.97	0.06	1.09
importCellRangerV2Sample	0.20	0.00	0.21
importCellRangerV3Sample	1.67	1.65	2.04
importDropEst	0.25	0.00	0.25
importExampleData	24.71	4.62	31.49
importGeneSetsFromCollection	1.75	0.17	2.11
importGeneSetsFromGMT	0.04	0.03	0.08
importGeneSetsFromList	0.11	0.02	0.12
importGeneSetsFromMSigDB	3.55	0.19	3.81
importMitoGeneSet	0.06	0.00	0.06
importOptimus	0	0	0
importSEQC	1.95	0.01	2.31
importSTARsolo	0.24	0.00	0.24
iterateSimulations	0.29	0.03	0.33
listSampleSummaryStatsTables	0.30	0.05	0.34
mergeSCEColData	0.42	0.05	0.50
mouseBrainSubsetSCE	0.05	0.01	0.06
msigdb_table	0	0	0
plotBarcodeRankDropsResults	0.69	0.02	0.71
plotBarcodeRankScatter	0.67	0.03	0.72
plotBatchCorrCompare	19.12	0.12	19.84
plotBatchVariance	0.30	0.05	0.34
plotBcdsResults	11.72	0.35	13.60
plotBubble	0.81	0.04	0.86
plotClusterAbundance	1.13	0.03	3.81
plotCxdsResults	9.18	0.14	10.25
plotDEGHeatmap	5.18	0.41	5.90
plotDEGRegression	5.92	0.06	5.99
plotDEGViolin	5.15	0.22	7.31
plotDEGVolcano	0.85	0.02	0.86
plotDecontXResults	16.58	0.04	16.59
plotDimRed	1.62	0.02	1.66
plotDoubletFinderResults	62.02	0.17	63.69
plotEmptyDropsResults	17.36	0.02	17.37
plotEmptyDropsScatter	16.46	0.01	17.10
plotFindMarkerHeatmap	7.21	0.08	7.48
plotMASTThresholdGenes	1.28	0.11	1.39
plotPCA	0.36	0.05	0.41
plotPathway	0.65	0.04	0.72
plotRunPerCellQCResults	3.00	0.08	3.22
plotSCEBarAssayData	0.15	0.05	0.18
plotSCEBarColData	0.12	0.03	0.16
plotSCEBatchFeatureMean	0.16	0.03	0.19
plotSCEDensity	0.25	0.02	0.26
plotSCEDensityAssayData	0.16	0.03	0.19
plotSCEDensityColData	0.17	0.03	0.20
plotSCEDimReduceColData	0.55	0.06	0.61
plotSCEDimReduceFeatures	0.33	0.06	0.39
plotSCEHeatmap	2.2	0.0	2.2
plotSCEScatter	0.33	0.04	0.36
plotSCEViolin	0.23	0.00	0.24
plotSCEViolinAssayData	0.24	0.04	0.28
plotSCEViolinColData	0.20	0.03	0.23
plotScDblFinderResults	35.97	5.66	41.70
plotScanpyDotPlot	0.00	0.02	0.02
plotScanpyEmbedding	0.01	0.01	0.03
plotScanpyHVG	0.02	0.02	0.03
plotScanpyHeatmap	0.03	0.00	0.03
plotScanpyMarkerGenes	0.02	0.01	0.04
plotScanpyMarkerGenesDotPlot	0.01	0.02	0.03
plotScanpyMarkerGenesHeatmap	0.02	0.01	0.03
plotScanpyMarkerGenesMatrixPlot	0.00	0.04	0.03
plotScanpyMarkerGenesViolin	0.01	0.01	0.03
plotScanpyMatrixPlot	0.02	0.02	0.03
plotScanpyPCA	0.00	0.01	0.01
plotScanpyPCAGeneRanking	0.00	0.02	0.01
plotScanpyPCAVariance	0.00	0.01	0.02
plotScanpyViolin	0.02	0.00	0.02
plotScdsHybridResults	16.84	0.44	17.41
plotScrubletResults	0.03	0.00	0.03
plotSeuratElbow	0.02	0.01	0.03
plotSeuratHVG	0.01	0.02	0.03
plotSeuratJackStraw	0.03	0.00	0.03
plotSeuratReduction	0.03	0.00	0.03
plotSoupXResults	0	0	0
plotTSCANClusterDEG	5.80	0.11	6.02
plotTSCANClusterPseudo	3.69	0.09	4.38
plotTSCANDimReduceFeatures	1.89	0.05	1.93
plotTSCANPseudotimeGenes	2.78	0.06	2.97
plotTSCANPseudotimeHeatmap	2.00	0.03	2.05
plotTSCANResults	9.47	0.06	9.53
plotTSNE	2.12	0.05	2.47
plotTopHVG	0.49	0.05	0.53
plotUMAP	15.36	0.12	16.22
readSingleCellMatrix	0	0	0
reportCellQC	0.15	0.00	0.15
reportDropletQC	0.02	0.02	0.04
reportQCTool	0.14	0.01	0.15
retrieveSCEIndex	0.03	0.02	0.05
runBBKNN	0	0	0
runBarcodeRankDrops	2.35	0.02	2.81
runBcds	1.36	0.22	1.53
runCellQC	0.15	0.03	0.19
runClusterSummaryMetrics	2.10	0.05	2.12
runComBatSeq	0.65	0.00	0.66
runCxds	0.38	0.03	0.40
runCxdsBcdsHybrid	1.36	0.26	1.69
runDEAnalysis	0.59	0.07	0.66
runDecontX	11.55	0.00	12.34
runDimReduce	0.34	0.03	0.38
runDoubletFinder	60.03	0.06	69.15
runDropletQC	0.00	0.03	0.03
runEmptyDrops	16.11	0.03	16.16
runEnrichR	0.22	0.02	2.48
runFastMNN	1.44	0.05	1.50
runFeatureSelection	0.23	0.01	0.25
runFindMarker	2.69	0.28	2.97
runGSVA	0.72	0.03	0.75
runHarmony	0.03	0.00	0.03
runKMeans	0.36	0.04	0.39
runLimmaBC	0.06	0.00	0.07
runMNNCorrect	0.49	0.03	0.51
runModelGeneVar	0.34	0.03	0.38
runNormalization	2.41	0.01	2.43
runPerCellQC	0.44	0.02	0.45
runSCANORAMA	0	0	0
runSCMerge	0	0	0
runScDblFinder	17.31	0.80	18.11
runScanpyFindClusters	0.01	0.01	0.03
runScanpyFindHVG	0.00	0.02	0.02
runScanpyFindMarkers	0.00	0.03	0.03
runScanpyNormalizeData	0.14	0.01	0.15
runScanpyPCA	0.03	0.00	0.04
runScanpyScaleData	0.03	0.00	0.03
runScanpyTSNE	0.03	0.00	0.03
runScanpyUMAP	0.05	0.00	0.05
runScranSNN	0.64	0.05	0.68
runScrublet	0.03	0.00	0.03
runSeuratFindClusters	0.03	0.02	0.05
runSeuratFindHVG	0.68	0.06	0.74
runSeuratHeatmap	0.01	0.01	0.03
runSeuratICA	0.03	0.00	0.03
runSeuratJackStraw	0.02	0.02	0.03
runSeuratNormalizeData	0.01	0.02	0.03
runSeuratPCA	0.02	0.01	0.03
runSeuratSCTransform	7.01	0.16	7.17
runSeuratScaleData	0.02	0.01	0.03
runSeuratUMAP	0.03	0.00	0.04
runSingleR	0.03	0.02	0.04
runSoupX	0	0	0
runTSCAN	1.27	0.03	1.30
runTSCANClusterDEAnalysis	1.25	0.09	1.34
runTSCANDEG	1.61	0.05	1.68
runTSNE	0.64	0.03	0.68
runUMAP	9.34	0.13	9.94
runVAM	0.44	0.03	0.47
runZINBWaVE	0	0	0
sampleSummaryStats	0.22	0.01	0.23
scaterCPM	0.10	0.02	0.11
scaterPCA	0.53	0.03	0.56
scaterlogNormCounts	0.20	0.02	0.22
sce	0.02	0.01	0.03
sctkListGeneSetCollections	0.04	0.03	0.08
sctkPythonInstallConda	0	0	0
sctkPythonInstallVirtualEnv	0	0	0
selectSCTKConda	0	0	0
selectSCTKVirtualEnvironment	0	0	0
setRowNames	0.10	0.01	0.11
setSCTKDisplayRow	0.33	0.02	0.35
singleCellTK	0	0	0
subDiffEx	1.50	0.16	1.61
subsetSCECols	0.17	0.00	0.17
subsetSCERows	0.33	0.03	0.36
summarizeSCE	0.04	0.03	0.08
trimCounts	0.16	0.03	0.18