Back to Multiple platform build/check report for BioC 3.14
ABCDEFGHIJKLMNOPQR[S]TUVWXYZ

This page was generated on 2022-01-24 13:05:41 -0500 (Mon, 24 Jan 2022).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 20.04.4 LTS)x86_644.1.2 (2021-11-01) -- "Bird Hippie" 4329
tokay2Windows Server 2012 R2 Standardx644.1.2 (2021-11-01) -- "Bird Hippie" 4080
machv2macOS 10.14.6 Mojavex86_644.1.2 (2021-11-01) -- "Bird Hippie" 4141
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 nebbiolo2


To the developers/maintainers of the singleCellTK package:
- Please 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 How and When does the builder pull? When will my changes propagate? here for more information.
- Make sure to use the following settings in order to reproduce any error or warning you see on this page.

raw results

Package 1807/2083HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.4.0  (landing page)
Yichen Wang
Snapshot Date: 2022-01-23 01:55:04 -0500 (Sun, 23 Jan 2022)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_14
git_last_commit: 91f98fc
git_last_commit_date: 2021-10-27 11:24:49 -0500 (Wed, 27 Oct 2021)
nebbiolo2Linux (Ubuntu 20.04.4 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
tokay2Windows Server 2012 R2 Standard / x64  OK    OK    ERROR    OK  
machv2macOS 10.14.6 Mojave / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published

Summary

Package: singleCellTK
Version: 2.4.0
Command: /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.14-bioc/R/library --no-vignettes --timings singleCellTK_2.4.0.tar.gz
StartedAt: 2022-01-23 09:43:19 -0500 (Sun, 23 Jan 2022)
EndedAt: 2022-01-23 09:55:08 -0500 (Sun, 23 Jan 2022)
EllapsedTime: 708.8 seconds
RetCode: 0
Status:   OK  
CheckDir: singleCellTK.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.14-bioc/R/library --no-vignettes --timings singleCellTK_2.4.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.14-bioc/meat/singleCellTK.Rcheck’
* using R version 4.1.2 (2021-11-01)
* using platform: x86_64-pc-linux-gnu (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.4.0’
* 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  6.5Mb
  sub-directories of 1Mb or more:
    extdata   1.6Mb
    shiny     2.8Mb
* 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 dependencies in R code ... NOTE
Namespaces in Imports field not imported from:
  'AnnotationDbi' 'RColorBrewer'
  All declared Imports should be used.
* 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 LazyData ... 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 23.693  0.263  23.945
plotScDblFinderResults   21.114  0.280  21.314
importExampleData        19.489  1.659  22.091
runDoubletFinder         16.845  0.128  16.973
plotBatchCorrCompare     12.270  0.053  12.302
runScDblFinder           11.646  0.376  11.987
plotBcdsResults           9.268  0.141   8.418
plotScdsHybridResults     9.215  0.117   8.453
plotDecontXResults        7.930  0.080   8.010
plotCxdsResults           7.068  0.200   7.260
plotEmptyDropsResults     6.743  0.015   6.759
findMarkerDiffExp         6.266  0.488   6.754
plotEmptyDropsScatter     6.690  0.016   6.705
runEmptyDrops             6.407  0.016   6.423
plotUMAP                  6.166  0.096   6.253
findMarkerTopTable        5.848  0.248   6.096
runDecontX                5.893  0.008   5.901
plotMarkerDiffExp         5.587  0.052   5.639
detectCellOutlier         5.170  0.155   5.327
getUMAP                   4.692  0.372   5.055
plotDEGHeatmap            4.887  0.116   5.002
* 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 ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.14-bioc/meat/singleCellTK.Rcheck/00check.log’
for details.



Installation output

singleCellTK.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD INSTALL singleCellTK
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.14-bioc/R/library’
* installing *source* package ‘singleCellTK’ ...
** using staged installation
** R
** data
*** moving datasets to lazyload DB
** 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 4.1.2 (2021-11-01) -- "Bird Hippie"
Copyright (C) 2021 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 
  0.194   0.033   0.213 

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.1.2 (2021-11-01) -- "Bird Hippie"
Copyright (C) 2021 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, 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 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


Attaching package: 'DelayedArray'

The following objects are masked from 'package:base':

    aperm, apply, rowsum, 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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Estimating GSVA scores for 34 gene sets.
Estimating ECDFs with Gaussian kernels

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |==                                                                    |   3%
  |                                                                            
  |====                                                                  |   6%
  |                                                                            
  |======                                                                |   9%
  |                                                                            
  |========                                                              |  12%
  |                                                                            
  |==========                                                            |  15%
  |                                                                            
  |============                                                          |  18%
  |                                                                            
  |==============                                                        |  21%
  |                                                                            
  |================                                                      |  24%
  |                                                                            
  |===================                                                   |  26%
  |                                                                            
  |=====================                                                 |  29%
  |                                                                            
  |=======================                                               |  32%
  |                                                                            
  |=========================                                             |  35%
  |                                                                            
  |===========================                                           |  38%
  |                                                                            
  |=============================                                         |  41%
  |                                                                            
  |===============================                                       |  44%
  |                                                                            
  |=================================                                     |  47%
  |                                                                            
  |===================================                                   |  50%
  |                                                                            
  |=====================================                                 |  53%
  |                                                                            
  |=======================================                               |  56%
  |                                                                            
  |=========================================                             |  59%
  |                                                                            
  |===========================================                           |  62%
  |                                                                            
  |=============================================                         |  65%
  |                                                                            
  |===============================================                       |  68%
  |                                                                            
  |=================================================                     |  71%
  |                                                                            
  |===================================================                   |  74%
  |                                                                            
  |======================================================                |  76%
  |                                                                            
  |========================================================              |  79%
  |                                                                            
  |==========================================================            |  82%
  |                                                                            
  |============================================================          |  85%
  |                                                                            
  |==============================================================        |  88%
  |                                                                            
  |================================================================      |  91%
  |                                                                            
  |==================================================================    |  94%
  |                                                                            
  |====================================================================  |  97%
  |                                                                            
  |======================================================================| 100%

Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
[09:53:33] WARNING: amalgamation/../src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.
[09:53:34] WARNING: amalgamation/../src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.
[09:53:55] WARNING: amalgamation/../src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 15 | SKIP 0 | PASS 126 ]

[ FAIL 0 | WARN 15 | SKIP 0 | PASS 126 ]
> 
> proc.time()
   user  system elapsed 
203.380   3.945 206.075 

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0020.0000.002
SEG0.0020.0000.002
calcEffectSizes0.1510.0040.155
combineSCE2.0210.0122.032
computeZScore0.3090.0310.342
convertSCEToSeurat2.8380.0612.898
convertSeuratToSCE0.5140.0830.597
dedupRowNames0.0540.0130.065
detectCellOutlier5.1700.1555.327
diffAbundanceFET0.0450.0000.045
discreteColorPalette0.0060.0000.005
distinctColors0.0020.0000.002
downSampleCells0.7940.0200.813
downSampleDepth0.5670.0040.571
enrichRSCE0.3940.0231.984
exportSCE0.0020.0000.002
exportSCEtoAnnData0.1250.0080.133
exportSCEtoFlatFile0.1110.0200.130
featureIndex0.0250.0000.025
findMarkerDiffExp6.2660.4886.754
findMarkerTopTable5.8480.2486.096
generateSimulatedData0.0500.0030.054
getBiomarker0.0360.0000.037
getDEGTopTable0.8350.0220.858
getMSigDBTable0.0030.0000.003
getTSNE0.3930.0170.408
getTopHVG0.3240.0240.348
getUMAP4.6920.3725.055
importAnnData0.0010.0000.001
importBUStools0.3670.0000.368
importCellRanger1.5040.0121.516
importCellRangerV2Sample0.3470.0030.350
importCellRangerV3Sample0.5060.0040.509
importDropEst0.4370.0000.437
importExampleData19.489 1.65922.091
importGeneSetsFromCollection0.7550.0480.803
importGeneSetsFromGMT0.0660.0040.070
importGeneSetsFromList0.1700.0040.174
importGeneSetsFromMSigDB4.0760.2244.301
importMitoGeneSet0.0490.0000.049
importOptimus0.0010.0000.001
importSEQC0.3190.0000.320
importSTARsolo0.3350.0050.339
iterateSimulations0.5180.0040.522
mergeSCEColData0.5120.0000.513
mouseBrainSubsetSCE0.0010.0000.002
msigdb_table0.0010.0000.001
plotBarcodeRankDropsResults1.0260.0041.030
plotBarcodeRankScatter0.8290.0000.828
plotBatchCorrCompare12.270 0.05312.302
plotBatchVariance0.2720.0240.296
plotBcdsResults9.2680.1418.418
plotClusterAbundance0.6500.0280.677
plotCxdsResults7.0680.2007.260
plotDEGHeatmap4.8870.1165.002
plotDEGRegression3.2940.0083.290
plotDEGViolin3.8640.0523.901
plotDecontXResults7.930.088.01
plotDimRed0.3040.0000.304
plotDoubletFinderResults23.693 0.26323.945
plotEmptyDropsResults6.7430.0156.759
plotEmptyDropsScatter6.6900.0166.705
plotMASTThresholdGenes2.8620.1643.025
plotMarkerDiffExp5.5870.0525.639
plotPCA0.6750.0000.675
plotRunPerCellQCResults0.0020.0000.002
plotSCEBarAssayData0.1070.0000.107
plotSCEBarColData0.0850.0000.085
plotSCEBatchFeatureMean0.1720.0000.172
plotSCEDensity0.1570.0040.161
plotSCEDensityAssayData0.1250.0000.125
plotSCEDensityColData0.1520.0080.160
plotSCEDimReduceColData0.8520.0000.851
plotSCEDimReduceFeatures0.3980.0040.402
plotSCEHeatmap0.9510.0080.959
plotSCEScatter0.3720.0040.377
plotSCEViolin0.1660.0000.166
plotSCEViolinAssayData0.1910.0000.191
plotSCEViolinColData0.1720.0000.172
plotScDblFinderResults21.114 0.28021.314
plotScdsHybridResults9.2150.1178.453
plotScrubletResults0.0010.0000.002
plotTSNE0.6590.0040.663
plotTopHVG0.5000.0080.508
plotUMAP6.1660.0966.253
readSingleCellMatrix0.0040.0000.004
reportCellQC0.2150.0000.215
reportDropletQC0.0010.0000.001
reportQCTool0.2150.0000.216
retrieveSCEIndex0.0140.0000.014
runANOVA1.240.061.30
runBBKNN000
runBarcodeRankDrops0.6470.0040.651
runBcds2.4750.0281.630
runCellQC0.2170.0000.218
runComBatSeq0.4460.0040.450
runCxds0.7230.0000.723
runCxdsBcdsHybrid2.5060.0041.660
runDEAnalysis1.0640.0041.068
runDESeq24.7830.0084.790
runDecontX5.8930.0085.901
runDimReduce1.1140.0041.119
runDoubletFinder16.845 0.12816.973
runDropletQC0.0020.0000.002
runEmptyDrops6.4070.0166.423
runFastMNN1.6520.0161.668
runFeatureSelection0.2040.0000.203
runGSVA0.9710.0280.998
runKMeans0.6130.0160.629
runLimmaBC0.1050.0000.104
runLimmaDE0.9270.0080.936
runMAST3.6540.0163.628
runMNNCorrect0.6710.0000.671
runNormalization1.5180.0321.551
runPerCellQC0.4830.0240.508
runSCANORAMA000
runSCMerge0.0010.0000.001
runScDblFinder11.646 0.37611.987
runScranSNN0.5990.0040.603
runScrublet0.0010.0000.001
runSingleR0.0500.0000.049
runVAM0.7940.0040.798
runWilcox1.0530.0041.055
runZINBWaVE0.0020.0000.001
sampleSummaryStats0.4460.0000.445
scaterCPM0.1860.0000.185
scaterPCA0.7880.0040.793
scaterlogNormCounts0.8900.0120.903
sce0.0000.0010.001
scranModelGeneVar0.2590.0030.262
sctkListGeneSetCollections0.2270.0040.232
sctkPythonInstallConda000
sctkPythonInstallVirtualEnv0.0010.0000.000
selectSCTKConda000
selectSCTKVirtualEnvironment0.0010.0000.000
setSCTKDisplayRow0.4790.0000.478
seuratComputeHeatmap0.0000.0010.001
seuratComputeJackStraw0.0000.0010.001
seuratElbowPlot0.0020.0010.001
seuratFindClusters0.0010.0000.001
seuratFindHVG0.0010.0000.001
seuratICA0.0010.0000.001
seuratJackStrawPlot0.0010.0000.001
seuratNormalizeData0.0010.0000.001
seuratPCA0.0010.0000.001
seuratPlotHVG0.0010.0000.001
seuratReductionPlot0.0010.0000.001
seuratRunUMAP0.0010.0000.001
seuratSCTransform3.1150.0003.116
seuratScaleData0.0020.0000.001
singleCellTK000
subDiffEx0.6120.0040.616
subsetSCECols0.240.000.24
subsetSCERows0.6110.0040.614
summarizeSCE0.0610.0000.060
trimCounts0.3390.0280.367