Back to Multiple platform build/check report for BioC 3.19:   simplified   long
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This page was generated on 2024-05-21 11:38:32 -0400 (Tue, 21 May 2024).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 22.04.3 LTS)x86_644.4.0 (2024-04-24) -- "Puppy Cup" 4751
palomino3Windows Server 2022 Datacenterx644.4.0 (2024-04-24 ucrt) -- "Puppy Cup" 4485
lconwaymacOS 12.7.1 Montereyx86_644.4.0 (2024-04-24) -- "Puppy Cup" 4515
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 1992/2300HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.14.0  (landing page)
Joshua David Campbell
Snapshot Date: 2024-05-20 14:00:15 -0400 (Mon, 20 May 2024)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_19
git_last_commit: cd29b84
git_last_commit_date: 2024-04-30 11:06:02 -0400 (Tue, 30 Apr 2024)
nebbiolo1Linux (Ubuntu 22.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino3Windows 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
kjohnson3macOS 13.6.5 Ventura / arm64see weekly results here

CHECK results for singleCellTK on lconway


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: 2.14.0
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.14.0.tar.gz
StartedAt: 2024-05-20 23:56:39 -0400 (Mon, 20 May 2024)
EndedAt: 2024-05-21 00:13:46 -0400 (Tue, 21 May 2024)
EllapsedTime: 1027.0 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings singleCellTK_2.14.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/singleCellTK.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.14.0’
* 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  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 37.621  0.434  38.355
runDoubletFinder         33.604  0.322  34.160
plotScDblFinderResults   27.959  1.006  29.398
importExampleData        18.282  2.312  21.340
runScDblFinder           17.481  0.454  18.047
plotBatchCorrCompare     11.781  0.214  12.105
plotScdsHybridResults     9.911  0.215  10.217
plotBcdsResults           8.811  0.261   9.160
plotDecontXResults        8.436  0.126   8.629
runDecontX                7.525  0.083   7.654
runUMAP                   7.320  0.111   7.492
plotCxdsResults           7.256  0.114   7.423
detectCellOutlier         7.118  0.195   7.382
plotUMAP                  6.929  0.125   7.120
plotTSCANClusterDEG       6.390  0.134   6.569
runSeuratSCTransform      6.199  0.139   6.389
plotEmptyDropsScatter     6.224  0.066   6.336
plotEmptyDropsResults     6.191  0.065   6.303
runEmptyDrops             6.157  0.063   6.272
plotFindMarkerHeatmap     5.431  0.071   5.553
plotDEGViolin             5.177  0.124   5.339
convertSCEToSeurat        4.999  0.275   5.328
getEnrichRResult          0.374  0.052   5.412
* 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
  ‘/Users/biocbuild/bbs-3.19-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.


Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/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 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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 
  0.248   0.104   0.324 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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
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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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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 21 | SKIP 0 | PASS 224 ]

[ FAIL 0 | WARN 21 | SKIP 0 | PASS 224 ]
> 
> proc.time()
   user  system elapsed 
292.447   8.314 306.268 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0030.0020.005
SEG0.0030.0020.005
calcEffectSizes0.2180.0230.243
combineSCE1.6860.0641.764
computeZScore0.2690.0110.281
convertSCEToSeurat4.9990.2755.328
convertSeuratToSCE0.6050.0140.628
dedupRowNames0.0700.0050.075
detectCellOutlier7.1180.1957.382
diffAbundanceFET0.0700.0050.077
discreteColorPalette0.0070.0010.007
distinctColors0.0030.0010.003
downSampleCells0.7780.1020.895
downSampleDepth0.6530.0560.719
expData-ANY-character-method0.3530.0100.366
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.4030.0100.417
expData-set0.3980.0100.409
expData0.3820.0330.421
expDataNames-ANY-method0.3760.0280.405
expDataNames0.3580.0100.370
expDeleteDataTag0.0480.0040.053
expSetDataTag0.0320.0030.038
expTaggedData0.0330.0050.039
exportSCE0.0300.0040.035
exportSCEtoAnnData0.0960.0040.102
exportSCEtoFlatFile0.0980.0040.103
featureIndex0.0430.0040.048
generateSimulatedData0.0610.0060.067
getBiomarker0.0750.0080.085
getDEGTopTable1.0970.0491.156
getDiffAbundanceResults0.0670.0050.074
getEnrichRResult0.3740.0525.412
getFindMarkerTopTable4.2030.0944.333
getMSigDBTable0.0050.0030.008
getPathwayResultNames0.0300.0040.034
getSampleSummaryStatsTable0.3890.0100.402
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getTSCANResults2.2540.0632.332
getTopHVG1.3970.0281.438
importAnnData0.0010.0010.002
importBUStools0.3350.0080.346
importCellRanger1.4370.0491.505
importCellRangerV2Sample0.3450.0070.356
importCellRangerV3Sample0.5070.0200.535
importDropEst0.3620.0080.374
importExampleData18.282 2.31221.340
importGeneSetsFromCollection0.8600.1431.015
importGeneSetsFromGMT0.0870.0070.095
importGeneSetsFromList0.1520.0070.160
importGeneSetsFromMSigDB2.8230.1222.972
importMitoGeneSet0.0690.0090.081
importOptimus0.0020.0010.003
importSEQC0.3520.0280.385
importSTARsolo0.3380.0090.351
iterateSimulations0.4310.0140.450
listSampleSummaryStatsTables0.5180.0130.537
mergeSCEColData0.5750.0290.615
mouseBrainSubsetSCE0.0430.0050.049
msigdb_table0.0020.0020.003
plotBarcodeRankDropsResults1.0150.0281.051
plotBarcodeRankScatter1.0610.0181.089
plotBatchCorrCompare11.781 0.21412.105
plotBatchVariance0.3930.0280.428
plotBcdsResults8.8110.2619.160
plotBubble1.2690.0591.345
plotClusterAbundance1.0060.0171.036
plotCxdsResults7.2560.1147.423
plotDEGHeatmap3.4260.1353.593
plotDEGRegression4.3500.0854.470
plotDEGViolin5.1770.1245.339
plotDEGVolcano1.1360.0181.163
plotDecontXResults8.4360.1268.629
plotDimRed0.3400.0080.352
plotDoubletFinderResults37.621 0.43438.355
plotEmptyDropsResults6.1910.0656.303
plotEmptyDropsScatter6.2240.0666.336
plotFindMarkerHeatmap5.4310.0715.553
plotMASTThresholdGenes1.7940.0441.849
plotPCA0.5710.0140.592
plotPathway1.0120.0191.040
plotRunPerCellQCResults2.6600.0402.729
plotSCEBarAssayData0.2240.0080.235
plotSCEBarColData0.1910.0090.206
plotSCEBatchFeatureMean0.2610.0050.269
plotSCEDensity0.2970.0100.312
plotSCEDensityAssayData0.1970.0080.210
plotSCEDensityColData0.2350.0090.247
plotSCEDimReduceColData0.7950.0170.817
plotSCEDimReduceFeatures0.4920.0180.519
plotSCEHeatmap0.7630.0130.781
plotSCEScatter0.4510.0130.470
plotSCEViolin0.3030.0080.316
plotSCEViolinAssayData0.3740.0100.388
plotSCEViolinColData0.2970.0100.312
plotScDblFinderResults27.959 1.00629.398
plotScanpyDotPlot0.0290.0050.035
plotScanpyEmbedding0.0260.0040.032
plotScanpyHVG0.0350.0040.039
plotScanpyHeatmap0.0360.0050.042
plotScanpyMarkerGenes0.0270.0040.031
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plotScanpyMarkerGenesMatrixPlot0.0270.0050.033
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plotScanpyPCA0.0270.0040.031
plotScanpyPCAGeneRanking0.0280.0030.032
plotScanpyPCAVariance0.0260.0040.030
plotScanpyViolin0.0410.0050.048
plotScdsHybridResults 9.911 0.21510.217
plotScrubletResults0.0270.0060.034
plotSeuratElbow0.0240.0020.027
plotSeuratHVG0.0250.0020.028
plotSeuratJackStraw0.0310.0030.033
plotSeuratReduction0.0310.0040.035
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plotTSCANClusterPseudo2.7870.0502.861
plotTSCANDimReduceFeatures2.7060.0452.773
plotTSCANPseudotimeGenes2.6600.0462.732
plotTSCANPseudotimeHeatmap2.9790.0553.072
plotTSCANResults2.6130.0462.682
plotTSNE0.6080.0150.629
plotTopHVG0.6040.0170.628
plotUMAP6.9290.1257.120
readSingleCellMatrix0.0060.0010.007
reportCellQC0.2230.0090.233
reportDropletQC0.0250.0010.027
reportQCTool0.2070.0090.218
retrieveSCEIndex0.0380.0050.042
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runBcds1.9910.0772.090
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runClusterSummaryMetrics0.8290.0420.875
runComBatSeq0.5170.0210.540
runCxds0.5190.0110.533
runCxdsBcdsHybrid2.2400.0702.332
runDEAnalysis0.9280.0500.989
runDecontX7.5250.0837.654
runDimReduce0.6140.0150.639
runDoubletFinder33.604 0.32234.160
runDropletQC0.0310.0050.036
runEmptyDrops6.1570.0636.272
runEnrichR0.3340.0382.159
runFastMNN2.0830.0592.156
runFeatureSelection0.2650.0050.272
runFindMarker4.3700.0674.458
runGSVA1.0030.0451.057
runHarmony0.0460.0010.047
runKMeans0.5230.0130.538
runLimmaBC0.1000.0020.102
runMNNCorrect0.6640.0180.686
runModelGeneVar0.5120.0090.525
runNormalization2.3770.0502.440
runPerCellQC0.5990.0150.617
runSCANORAMA0.0010.0010.000
runSCMerge0.0050.0020.007
runScDblFinder17.481 0.45418.047
runScanpyFindClusters0.0290.0020.033
runScanpyFindHVG0.0230.0030.026
runScanpyFindMarkers0.0270.0050.035
runScanpyNormalizeData0.2410.0090.253
runScanpyPCA0.0280.0030.032
runScanpyScaleData0.0300.0040.035
runScanpyTSNE0.0280.0040.032
runScanpyUMAP0.0280.0040.032
runScranSNN0.8650.0190.889
runScrublet0.0260.0030.029
runSeuratFindClusters0.0310.0020.033
runSeuratFindHVG0.9770.0881.072
runSeuratHeatmap0.0300.0040.035
runSeuratICA0.0260.0060.032
runSeuratJackStraw0.0250.0030.028
runSeuratNormalizeData0.0310.0040.036
runSeuratPCA0.0270.0040.031
runSeuratSCTransform6.1990.1396.389
runSeuratScaleData0.0310.0050.036
runSeuratUMAP0.0290.0040.033
runSingleR0.0480.0020.051
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runTSCAN1.8660.0391.918
runTSCANClusterDEAnalysis1.8110.0321.856
runTSCANDEG1.8350.0331.881
runTSNE0.9190.0170.945
runUMAP7.3200.1117.492
runVAM0.6290.0130.646
runZINBWaVE0.0050.0020.006
sampleSummaryStats0.3550.0110.369
scaterCPM0.1530.0030.159
scaterPCA0.8350.0180.860
scaterlogNormCounts0.2700.0080.282
sce0.0290.0060.035
sctkListGeneSetCollections0.0870.0080.096
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv000
selectSCTKConda000
selectSCTKVirtualEnvironment000
setRowNames0.1790.0140.195
setSCTKDisplayRow0.4840.0110.501
singleCellTK000
subDiffEx0.5740.0250.603
subsetSCECols0.1960.0090.207
subsetSCERows0.4810.0150.501
summarizeSCE0.0870.0090.097
trimCounts0.2270.0100.239