Back to Multiple platform build/check report for BioC 3.19:   simplified   long
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This page was generated on 2024-06-18 17:58 -0400 (Tue, 18 Jun 2024).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 22.04.3 LTS)x86_644.4.0 (2024-04-24) -- "Puppy Cup" 4758
palomino3Windows Server 2022 Datacenterx644.4.0 (2024-04-24 ucrt) -- "Puppy Cup" 4492
merida1macOS 12.7.4 Montereyx86_644.4.0 (2024-04-24) -- "Puppy Cup" 4464
kjohnson1macOS 13.6.6 Venturaarm644.4.0 (2024-04-24) -- "Puppy Cup" 4464
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: 2024-06-16 14:00 -0400 (Sun, 16 Jun 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
merida1macOS 12.7.4 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kjohnson1macOS 13.6.6 Ventura / arm64  OK    OK    OK    OK  UNNEEDED, same version is already published


CHECK results for singleCellTK on nebbiolo1

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: /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings singleCellTK_2.14.0.tar.gz
StartedAt: 2024-06-17 03:56:45 -0400 (Mon, 17 Jun 2024)
EndedAt: 2024-06-17 04:11:31 -0400 (Mon, 17 Jun 2024)
EllapsedTime: 886.7 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings singleCellTK_2.14.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/singleCellTK.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: x86_64-pc-linux-gnu
* 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 ‘2.14.0’
* 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  5.6Mb
  sub-directories of 1Mb or more:
    shiny   2.3Mb
* 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 ... 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 30.254  0.563  30.816
runSeuratSCTransform     28.910  0.764  29.675
plotScDblFinderResults   28.417  0.688  29.102
runDoubletFinder         27.613  0.132  27.745
runScDblFinder           19.898  0.600  20.498
importExampleData        13.845  2.086  16.480
plotBatchCorrCompare     11.025  0.476  11.495
plotScdsHybridResults     9.206  0.172   8.482
plotBcdsResults           7.529  0.288   6.935
plotDecontXResults        7.000  0.328   7.328
plotUMAP                  6.986  0.079   7.063
plotEmptyDropsScatter     6.637  0.040   6.676
plotEmptyDropsResults     6.582  0.028   6.609
runDecontX                6.359  0.124   6.483
runEmptyDrops             6.304  0.012   6.317
runUMAP                   6.136  0.160   6.294
plotCxdsResults           5.918  0.212   6.126
detectCellOutlier         5.118  0.196   5.315
* 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: 3 NOTEs
See
  ‘/home/biocbuild/bbs-3.19-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.


Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.19-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 4.4.0 (2024-04-24) -- "Puppy Cup"
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 
  0.153   0.034   0.175 

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-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, 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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  |======================================================================| 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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**************************************************|
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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 
259.874   9.645 269.692 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0000.0020.003
SEG0.0000.0020.002
calcEffectSizes0.1540.0080.162
combineSCE1.4860.0441.530
computeZScore0.9220.0720.994
convertSCEToSeurat4.0110.1244.136
convertSeuratToSCE0.4420.0120.455
dedupRowNames0.0550.0040.059
detectCellOutlier5.1180.1965.315
diffAbundanceFET0.0580.0000.058
discreteColorPalette0.0070.0000.006
distinctColors0.0030.0000.002
downSampleCells0.6540.0440.698
downSampleDepth0.4730.0150.489
expData-ANY-character-method0.2690.0000.269
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.3120.0040.317
expData-set0.2940.0080.302
expData0.2920.0280.321
expDataNames-ANY-method0.2620.0000.262
expDataNames0.2620.0000.262
expDeleteDataTag0.0300.0040.034
expSetDataTag0.0250.0000.025
expTaggedData0.0270.0000.026
exportSCE0.0190.0040.024
exportSCEtoAnnData0.0980.0000.098
exportSCEtoFlatFile0.0890.0080.098
featureIndex0.0370.0000.037
generateSimulatedData0.0510.0080.059
getBiomarker0.060.000.06
getDEGTopTable0.7990.0240.823
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getEnrichRResult0.4920.0482.077
getFindMarkerTopTable3.1910.2723.463
getMSigDBTable0.0000.0040.004
getPathwayResultNames0.0200.0040.024
getSampleSummaryStatsTable0.2850.0200.305
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getTopHVG1.0530.0921.146
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importBUStools0.2290.0080.237
importCellRanger1.0570.0361.094
importCellRangerV2Sample0.2350.0000.235
importCellRangerV3Sample0.3810.0120.393
importDropEst0.3430.0240.368
importExampleData13.845 2.08616.480
importGeneSetsFromCollection0.6890.1000.789
importGeneSetsFromGMT0.0610.0040.064
importGeneSetsFromList0.1120.0000.112
importGeneSetsFromMSigDB2.3380.2122.550
importMitoGeneSet0.0540.0000.053
importOptimus0.0020.0000.002
importSEQC0.2260.0240.251
importSTARsolo0.2340.0360.270
iterateSimulations0.3670.0040.371
listSampleSummaryStatsTables0.3540.0040.358
mergeSCEColData0.4270.0160.442
mouseBrainSubsetSCE0.0380.0000.038
msigdb_table0.0020.0000.001
plotBarcodeRankDropsResults0.8380.0240.861
plotBarcodeRankScatter0.7790.0480.827
plotBatchCorrCompare11.025 0.47611.495
plotBatchVariance0.2950.0280.323
plotBcdsResults7.5290.2886.935
plotBubble0.8630.0360.900
plotClusterAbundance0.7600.0320.793
plotCxdsResults5.9180.2126.126
plotDEGHeatmap2.7640.0802.845
plotDEGRegression3.4280.0443.466
plotDEGViolin4.0780.0884.160
plotDEGVolcano0.9590.0230.981
plotDecontXResults7.0000.3287.328
plotDimRed0.2500.0000.249
plotDoubletFinderResults30.254 0.56330.816
plotEmptyDropsResults6.5820.0286.609
plotEmptyDropsScatter6.6370.0406.676
plotFindMarkerHeatmap4.0560.0364.092
plotMASTThresholdGenes1.4410.0321.473
plotPCA0.4360.0160.452
plotPathway0.7800.0000.781
plotRunPerCellQCResults1.9100.0121.922
plotSCEBarAssayData0.1660.0040.171
plotSCEBarColData0.1310.0000.132
plotSCEBatchFeatureMean0.1950.0000.195
plotSCEDensity0.2090.0080.217
plotSCEDensityAssayData0.1870.0200.208
plotSCEDensityColData0.2060.0000.206
plotSCEDimReduceColData0.6430.0080.650
plotSCEDimReduceFeatures0.3980.0000.398
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plotSCEScatter0.3520.0040.356
plotSCEViolin0.2220.0000.221
plotSCEViolinAssayData0.2360.0000.236
plotSCEViolinColData0.2200.0040.224
plotScDblFinderResults28.417 0.68829.102
plotScanpyDotPlot0.0220.0040.025
plotScanpyEmbedding0.0250.0000.026
plotScanpyHVG0.0240.0000.024
plotScanpyHeatmap0.0240.0000.024
plotScanpyMarkerGenes0.0240.0000.025
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plotScdsHybridResults9.2060.1728.482
plotScrubletResults0.0240.0000.024
plotSeuratElbow0.0230.0000.023
plotSeuratHVG0.0230.0000.022
plotSeuratJackStraw0.0220.0000.023
plotSeuratReduction0.0230.0000.022
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plotTSCANClusterDEG4.7940.0434.837
plotTSCANClusterPseudo2.0410.0082.049
plotTSCANDimReduceFeatures2.0770.0712.148
plotTSCANPseudotimeGenes1.9360.0081.944
plotTSCANPseudotimeHeatmap2.2100.0042.215
plotTSCANResults2.0400.0282.068
plotTSNE0.4920.0080.500
plotTopHVG0.5190.0000.519
plotUMAP6.9860.0797.063
readSingleCellMatrix0.0050.0000.005
reportCellQC0.1630.0000.163
reportDropletQC0.0240.0000.024
reportQCTool0.1690.0000.169
retrieveSCEIndex0.0330.0000.032
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runClusterSummaryMetrics0.6930.0080.700
runComBatSeq0.4210.0000.420
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runCxdsBcdsHybrid2.2180.0121.394
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runDoubletFinder27.613 0.13227.745
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runEmptyDrops6.3040.0126.317
runEnrichR0.5160.0242.035
runFastMNN1.6280.1521.780
runFeatureSelection0.2070.0160.222
runFindMarker3.1470.2963.443
runGSVA0.8600.1280.989
runHarmony0.0330.0040.036
runKMeans0.4040.0280.431
runLimmaBC0.0760.0000.076
runMNNCorrect0.4850.0360.522
runModelGeneVar0.4250.0160.441
runNormalization2.1790.3922.571
runPerCellQC0.4430.0230.467
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runSCMerge0.0040.0000.004
runScDblFinder19.898 0.60020.498
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runScanpyFindHVG0.0240.0000.023
runScanpyFindMarkers0.0230.0000.023
runScanpyNormalizeData0.1860.0080.194
runScanpyPCA0.0240.0000.024
runScanpyScaleData0.0230.0000.024
runScanpyTSNE0.0240.0000.024
runScanpyUMAP0.0200.0040.024
runScranSNN0.6900.0680.758
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runSeuratFindHVG0.7580.0760.834
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runSeuratICA0.0240.0000.024
runSeuratJackStraw0.0230.0000.023
runSeuratNormalizeData0.0240.0000.024
runSeuratPCA0.0240.0000.024
runSeuratSCTransform28.910 0.76429.675
runSeuratScaleData0.0250.0000.025
runSeuratUMAP0.0240.0000.023
runSingleR0.0300.0040.034
runSoupX0.0010.0000.000
runTSCAN1.2670.0161.284
runTSCANClusterDEAnalysis1.4450.0241.469
runTSCANDEG1.370.021.39
runTSNE0.8400.0280.868
runUMAP6.1360.1606.294
runVAM0.4680.0040.471
runZINBWaVE0.0040.0000.004
sampleSummaryStats0.2610.0000.260
scaterCPM0.1330.0040.136
scaterPCA0.5980.0120.610
scaterlogNormCounts0.2230.0200.243
sce0.0240.0000.023
sctkListGeneSetCollections0.0740.0000.074
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv0.0000.0000.001
selectSCTKConda000
selectSCTKVirtualEnvironment0.0010.0000.000
setRowNames0.080.000.08
setSCTKDisplayRow0.4080.0080.416
singleCellTK000
subDiffEx0.4590.0120.471
subsetSCECols0.1590.0000.159
subsetSCERows0.3720.0120.384
summarizeSCE0.0650.0000.064
trimCounts0.1880.0120.200