Back to Mac ARM64 build report for BioC 3.17
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This page was generated on 2023-10-20 09:38:12 -0400 (Fri, 20 Oct 2023).

HostnameOSArch (*)R versionInstalled pkgs
kjohnson2macOS 12.6.1 Montereyarm644.3.1 (2023-06-16) -- "Beagle Scouts" 4347
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 1934/2230HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
singleCellTK 2.10.0  (landing page)
Yichen Wang
Snapshot Date: 2023-10-15 14:00:07 -0400 (Sun, 15 Oct 2023)
git_url: https://git.bioconductor.org/packages/singleCellTK
git_branch: RELEASE_3_17
git_last_commit: 277e675
git_last_commit_date: 2023-04-25 11:01:21 -0400 (Tue, 25 Apr 2023)
kjohnson2macOS 12.6.1 Monterey / arm64  OK    OK    OK    OK  UNNEEDED, same version is already published

CHECK results for singleCellTK on kjohnson2


To the developers/maintainers of the singleCellTK package:
- 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: 2.10.0
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_2.10.0.tar.gz
StartedAt: 2023-10-19 01:45:21 -0400 (Thu, 19 Oct 2023)
EndedAt: 2023-10-19 02:13:36 -0400 (Thu, 19 Oct 2023)
EllapsedTime: 1695.9 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_2.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/singleCellTK.Rcheck’
* using R version 4.3.1 (2023-06-16)
* using platform: aarch64-apple-darwin20 (64-bit)
* 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 12.6.7
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘singleCellTK/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘singleCellTK’ version ‘2.10.0’
* 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  6.7Mb
  sub-directories of 1Mb or more:
    extdata   1.5Mb
    shiny     2.9Mb
* 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 startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                             user system elapsed
plotScDblFinderResults     33.723  0.716  62.224
importExampleData          22.052  2.566  45.813
runScDblFinder             24.172  0.354  43.776
plotDoubletFinderResults   23.572  0.287  40.632
runDoubletFinder           17.794  0.147  31.846
plotBatchCorrCompare       10.330  0.195  19.593
plotScdsHybridResults       8.881  0.197  16.654
plotBcdsResults             7.848  0.175  14.551
plotDecontXResults          7.894  0.080  13.986
plotTSCANClusterDEG         6.843  0.116  12.416
plotEmptyDropsResults       6.636  0.050  11.263
plotEmptyDropsScatter       6.620  0.049  11.966
runDecontX                  6.398  0.071  11.454
runEmptyDrops               6.221  0.044  11.128
plotCxdsResults             6.163  0.092  11.572
plotUMAP                    5.991  0.093  10.643
runUMAP                     5.880  0.080  11.175
plotFindMarkerHeatmap       5.885  0.062  10.572
detectCellOutlier           5.520  0.160  10.124
plotDEGViolin               5.369  0.123   9.840
plotDEGRegression           4.580  0.083   8.305
runSeuratSCTransform        4.400  0.086   8.026
importGeneSetsFromMSigDB    4.028  0.230   7.669
runFindMarker               4.151  0.081   7.398
getFindMarkerTopTable       4.048  0.077   7.433
plotDEGHeatmap              3.529  0.129   6.602
convertSCEToSeurat          3.440  0.192   6.501
plotTSCANPseudotimeHeatmap  2.955  0.049   5.052
plotTSCANClusterPseudo      2.871  0.054   5.195
plotTSCANDimReduceFeatures  2.840  0.046   5.194
plotRunPerCellQCResults     2.775  0.041   5.029
plotTSCANPseudotimeGenes    2.766  0.043   5.031
getEnrichRResult            0.391  0.045   9.759
runEnrichR                  0.355  0.035   9.483
* 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: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.17-bioc-mac-arm64/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/4.3-arm64/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 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20 (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 
  0.212   0.063   0.514

singleCellTK.Rcheck/tests/testthat.Rout


R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(testthat)
> library(singleCellTK)
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats

Attaching package: 'MatrixGenerics'

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

    colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
    colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
    colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
    colWeightedMeans, colWeightedMedians, colWeightedSds,
    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
    rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
    rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
    rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
    rowWeightedSds, rowWeightedVars

Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics

Attaching package: 'BiocGenerics'

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

    IQR, mad, sd, var, xtabs

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

    Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:utils':

    findMatches

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

    I, expand.grid, unname

Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'Biobase'

The following object is masked from 'package:MatrixGenerics':

    rowMedians

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

    anyMissing, rowMedians

Loading required package: SingleCellExperiment
Loading required package: DelayedArray
Loading required package: Matrix

Attaching package: 'Matrix'

The following object is masked from 'package:S4Vectors':

    expand

Loading required package: S4Arrays
Loading required package: abind

Attaching package: 'S4Arrays'

The following object is masked from 'package:abind':

    abind

The following object is masked from 'package:base':

    rowsum


Attaching package: 'DelayedArray'

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

    apply, scale, sweep


Attaching package: 'singleCellTK'

The following object is masked from 'package:BiocGenerics':

    plotPCA

> 
> test_check("singleCellTK")
Found 2 batches
Using null model in ComBat-seq.
Adjusting for 0 covariate(s) or covariate level(s)
Estimating dispersions
Fitting the GLM model
Shrinkage off - using GLM estimates for parameters
Adjusting the data
Found 2 batches
Using null model in ComBat-seq.
Adjusting for 1 covariate(s) or covariate level(s)
Estimating dispersions
Fitting the GLM model
Shrinkage off - using GLM estimates for parameters
Adjusting the data
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

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

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Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Uploading data to Enrichr... Done.
  Querying HDSigDB_Human_2021... Done.
Parsing results... Done.
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene means
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating gene variance to mean ratios
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Estimating GSVA scores for 34 gene sets.
Estimating ECDFs with Gaussian kernels

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Estimating GSVA scores for 2 gene sets.
Estimating ECDFs with Gaussian kernels

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

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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: 9590

Running Louvain algorithm...
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Maximum modularity in 10 random starts: 0.8042
Number of communities: 6
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
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 19 | SKIP 0 | PASS 220 ]

[ FAIL 0 | WARN 19 | SKIP 0 | PASS 220 ]
> 
> proc.time()
   user  system elapsed 
268.941   7.027 503.790

Example timings

singleCellTK.Rcheck/singleCellTK-Ex.timings

nameusersystemelapsed
MitoGenes0.0030.0020.008
SEG0.0030.0010.008
calcEffectSizes0.2200.0230.429
combineSCE1.8640.0553.446
computeZScore0.4070.0150.764
convertSCEToSeurat3.4400.1926.501
convertSeuratToSCE0.5650.0111.035
dedupRowNames0.0780.0020.141
detectCellOutlier 5.520 0.16010.124
diffAbundanceFET0.0530.0070.109
discreteColorPalette0.0090.0010.014
distinctColors0.0030.0000.008
downSampleCells0.8030.0851.604
downSampleDepth0.6010.0241.122
expData-ANY-character-method0.3850.0090.706
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method0.4290.0110.783
expData-set0.4210.0210.801
expData0.4290.0380.835
expDataNames-ANY-method0.3840.0090.712
expDataNames0.3830.0090.699
expDeleteDataTag0.0440.0030.079
expSetDataTag0.0300.0030.058
expTaggedData0.0310.0020.059
exportSCE0.0300.0030.057
exportSCEtoAnnData0.1000.0070.188
exportSCEtoFlatFile0.1010.0070.191
featureIndex0.0410.0030.077
generateSimulatedData0.0480.0050.089
getBiomarker0.0590.0060.107
getDEGTopTable1.0750.0451.944
getDiffAbundanceResults0.0450.0040.090
getEnrichRResult0.3910.0459.759
getFindMarkerTopTable4.0480.0777.433
getMSigDBTable0.0050.0030.012
getPathwayResultNames0.0260.0030.052
getSampleSummaryStatsTable0.4120.0070.762
getSoupX000
getTSCANResults2.3730.0614.406
getTopHVG1.0090.0191.956
importAnnData0.0020.0010.007
importBUStools0.5040.0100.963
importCellRanger1.3460.0502.482
importCellRangerV2Sample0.3300.0050.594
importCellRangerV3Sample0.4950.0210.927
importDropEst0.4130.0070.752
importExampleData22.052 2.56645.813
importGeneSetsFromCollection0.9380.1061.940
importGeneSetsFromGMT0.0910.0050.168
importGeneSetsFromList0.1740.0060.329
importGeneSetsFromMSigDB4.0280.2307.669
importMitoGeneSet0.0670.0070.107
importOptimus0.0020.0010.003
importSEQC0.360.020.59
importSTARsolo0.3600.0350.640
iterateSimulations0.4920.0330.904
listSampleSummaryStatsTables0.5040.0100.787
mergeSCEColData0.5880.0290.972
mouseBrainSubsetSCE0.0310.0050.055
msigdb_table0.0010.0020.004
plotBarcodeRankDropsResults1.1140.0571.918
plotBarcodeRankScatter0.8440.0181.576
plotBatchCorrCompare10.330 0.19519.593
plotBatchVariance0.3920.0120.654
plotBcdsResults 7.848 0.17514.551
plotClusterAbundance1.3880.0282.349
plotCxdsResults 6.163 0.09211.572
plotDEGHeatmap3.5290.1296.602
plotDEGRegression4.5800.0838.305
plotDEGViolin5.3690.1239.840
plotDEGVolcano1.3350.0242.442
plotDecontXResults 7.894 0.08013.986
plotDimRed0.3280.0080.538
plotDoubletFinderResults23.572 0.28740.632
plotEmptyDropsResults 6.636 0.05011.263
plotEmptyDropsScatter 6.620 0.04911.966
plotFindMarkerHeatmap 5.885 0.06210.572
plotMASTThresholdGenes1.8950.0383.452
plotPCA0.6080.0141.124
plotPathway1.1110.0212.014
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plotSCEBarAssayData0.2200.0080.406
plotSCEBarColData0.1650.0060.289
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plotSCEDensity0.3400.0090.610
plotSCEDensityAssayData0.2010.0070.355
plotSCEDensityColData0.2510.0080.436
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plotSCEViolinAssayData0.3040.0080.564
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plotScanpyHVG0.0530.0030.095
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plotSeuratElbow0.0270.0030.044
plotSeuratHVG0.0270.0030.053
plotSeuratJackStraw0.0280.0010.061
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plotTSCANClusterPseudo2.8710.0545.195
plotTSCANDimReduceFeatures2.8400.0465.194
plotTSCANPseudotimeGenes2.7660.0435.031
plotTSCANPseudotimeHeatmap2.9550.0495.052
plotTSCANResults2.6840.0434.732
plotTSNE0.6870.0131.244
plotTopHVG0.4510.0120.824
plotUMAP 5.991 0.09310.643
readSingleCellMatrix0.0050.0010.011
reportCellQC0.2250.0070.354
reportDropletQC0.0270.0040.041
reportQCTool0.2220.0070.340
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runCxdsBcdsHybrid2.1500.0603.843
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runDimReduce0.5770.0101.040
runDoubletFinder17.794 0.14731.846
runDropletQC0.0310.0020.064
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runEnrichR0.3550.0359.483
runFastMNN2.1100.0503.744
runFeatureSelection0.2540.0060.462
runFindMarker4.1510.0817.398
runGSVA0.9020.0221.664
runHarmony0.0420.0020.081
runKMeans0.5020.0130.922
runLimmaBC0.0970.0020.176
runMNNCorrect0.6310.0111.151
runModelGeneVar0.5790.0131.066
runNormalization0.7750.0201.440
runPerCellQC0.6950.0161.276
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runScanpyFindHVG0.0280.0020.056
runScanpyFindMarkers0.0270.0030.054
runScanpyNormalizeData0.3120.0350.616
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runSeuratFindHVG0.8100.0151.478
runSeuratHeatmap0.0290.0020.056
runSeuratICA0.0270.0020.056
runSeuratJackStraw0.0310.0020.059
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runSeuratPCA0.0280.0020.053
runSeuratSCTransform4.4000.0868.026
runSeuratScaleData0.0290.0020.056
runSeuratUMAP0.0310.0020.057
runSingleR0.0460.0020.085
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runTSCANClusterDEAnalysis1.9860.0353.640
runTSCANDEG1.8730.0313.384
runTSNE0.9810.0251.806
runUMAP 5.880 0.08011.175
runVAM0.6960.0151.252
runZINBWaVE0.0050.0020.011
sampleSummaryStats0.3840.0070.685
scaterCPM0.1550.0070.294
scaterPCA0.5520.0101.010
scaterlogNormCounts0.2960.0100.551
sce0.0280.0080.063
sctkListGeneSetCollections0.0970.0050.185
sctkPythonInstallConda0.0010.0000.001
sctkPythonInstallVirtualEnv0.0010.0000.001
selectSCTKConda0.0010.0000.000
selectSCTKVirtualEnvironment000
setRowNames0.1130.0070.213
setSCTKDisplayRow0.5870.0211.077
singleCellTK0.0000.0010.001
subDiffEx0.6070.0231.138
subsetSCECols0.2210.0060.404
subsetSCERows0.5210.0130.957
summarizeSCE0.0690.0050.130
trimCounts0.3140.0150.583